DIGITAL ELEVATION
MODELS
A Guidance Note on how Digital Elevation Models
are created and used – includes key definitions, sample
Terms of Reference and how best to plan a DEM-mission
DIGITAL
ELEVATION MODELS
A Guidance Note on how Digital Elevation Models
are created and used – includes key definitions, sample Terms of
Reference and how best to plan a DEM-mission
DIGITAL ELEVATION MODELS
A Guidance Note on how Digital Elevation Models are created and used – includes key definitions, sample Terms
of Reference and how best to plan a DEM-mission
Louise Croneborg, Keiko Saito, Michel Matera, Don McKeown, Jan van Aardt
The Guidance note was developed as a collaboration between the Africa Water sector, the Latin America and
Caribbean Disaster Risk Management unit and the Global Facility for Disaster Reduction and Recovery (GFDRR)
at the World Bank
©2015 International Bank for Reconstruction and Development
1818 H street, NW, Washington, DC, 20433
Telephone: 202–473–1000; Internet: www.worldbank.org
All rights reserved.
Disclaimer
This volume is a product of the staff of the World Bank with external contributions. The findings, interpretations
and conclusions expressed in this work do not necessarily reflect the views of the World Bank, its Executive
Directors of the World Bank or the governments they represent.
The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors,
denominations, and other information shown on any map in this work do not imply any judgement on the part of
the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.
The information and advice contained in this volume is provided as general guidance only. Every effort has been
made to ensure the accuracy of the information. This publication is not a substitute for specific specialist advice.
The World Bank and the authors accept no liability.
Table of Contents iii
Table of Contents
Acknowledgement................................................................................................................................................................... v
Introduction...........................................................................................................................................................................vii
Executive Summary............................................................................................................................................................... ix
01 The Digital Elevation Model Primer......................................................................................................................... 01
What are Digital Elevation Models?................................................................................................................................01
DEM Applications............................................................................................................................................................. 02
Water Resources Management................................................................................................................................. 03
Disaster Risk Management....................................................................................................................................... 07
Geological Applications............................................................................................................................................. 09
Infrastructure...............................................................................................................................................................10
Agricultural Applications........................................................................................................................................... 12
3D Visualization........................................................................................................................................................... 12
Ecological Modeling.................................................................................................................................................... 13
Commercial Forestry.................................................................................................................................................. 13
Mapping........................................................................................................................................................................ 14
Ancillary DEM Applications and Products..............................................................................................................16
02 Operational Guide to Tender a Digital Elevation Model.......................................................................................19
Digital Elevation Models: Design Issues for Consideration.......................................................................................19
Decision Points to Acquire a DEM for Projects............................................................................................................19
Requirements and Options............................................................................................................................................. 20
Suitability Matrix...............................................................................................................................................................23
Application Requirements Matrix...................................................................................................................................25
03 How DEMs are Generated: Data Acquisition and Mission Planning,
Development of Requirements and Product Attributes of DEMs...................................................................... 27
Key Attributes for DEMs...................................................................................................................................................27
Project Area..................................................................................................................................................................28
Digital Surface Data Type..........................................................................................................................................28
DEM Model Types.......................................................................................................................................................28
Source............................................................................................................................................................................29
Point Spacing and Ground Sample Distance..........................................................................................................29
Accuracy....................................................................................................................................................................... 30
Surface Treatments..................................................................................................................................................... 31
Artifacts.........................................................................................................................................................................32
Horizontal and Vertical Datum.................................................................................................................................32
Geoid Model.................................................................................................................................................................32
iv Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Coordinate Systems....................................................................................................................................................32
Units..............................................................................................................................................................................32
Output Data Format................................................................................................................................................... 33
File Size and IT Requirements.................................................................................................................................. 33
Metadata....................................................................................................................................................................... 33
DEM Acquisition: The Terms of Reference...................................................................................................................34
Overview.......................................................................................................................................................................34
Technical Requirements.............................................................................................................................................34
Quality Assurance.......................................................................................................................................................34
Metadata....................................................................................................................................................................... 35
Deliverables.................................................................................................................................................................. 35
Costing Factors and Approximations......................................................................................................................37
04 Data Sharing and Dissemination............................................................................................................................... 39
Data and Data Compression Formats............................................................................................................................39
File Size................................................................................................................................................................................39
Public Domain vs. Restricted Access..............................................................................................................................39
Licensing Considerations................................................................................................................................................ 40
Data Storage, Sharing Platforms.................................................................................................................................... 40
05 Case Studies....................................................................................................................................................................41
Mozambique Flood Risk Mapping.................................................................................................................................. 41
Haiti Flood Risk Mapping................................................................................................................................................. 41
(Hypothetical Example) DEM for Urban Development.............................................................................................42
(Hypothetical Example) Earthquake and DEM............................................................................................................42
(Hypothetical Example) Commercial Forestry............................................................................................................43
06 Glossary.......................................................................................................................................................................... 45
07 Selected Resources........................................................................................................................................................55
08 Technical Annex........................................................................................................................................................... 57
Annex A................................................................................................................................................................................59
Light Detection and Ranging (Lidar).......................................................................................................................59
Radio Detection and Ranging (Radar) and IfSAR................................................................................................. 60
Photogammetry...........................................................................................................................................................61
Satellite-derived DEM Products................................................................................................................................. 62
Annex B................................................................................................................................................................................67
Annex C.............................................................................................................................................................................. 69
Annex D...............................................................................................................................................................................77
Annex E................................................................................................................................................................................ 81
Annex F................................................................................................................................................................................85
Annex G...............................................................................................................................................................................87
Annex H.............................................................................................................................................................................. 89
Acknowledgement
Mr. Don McKeown (Distinguished Researcher; Chester F. Carlson Center for Imaging Science, Rochester
Institute of Technology, Rochester, NY, USA; mckeown@cis.rit.edu)
Dr. Jan van Aardt (Associate Professor; Chester F. Carlson Center for Imaging Science, Rochester Institute of
Technology, Rochester, NY, USA; vanaardt@cis.rit.edu)
Marian Mabel (editor)
Eric Foster-Moore (team support)
The team would like to thank the following peer reviewers
Alanna Simpson (Sr. Disaster Risk Management Specialist)
Nagaraja Rao Harshadeep (Sr. Water Resources and Environmental Specialist)
Marc Forni (Sr. Disaster Risk Management Specialist)
Abigail Baca (Infrastructure Specialist)
Anna Burzykowska (Project Specialist)
Michael Bonte (Sr. Disaster Risk Management Specialist)
Henrike Brecht (Sr. Infrastructure Specialist)
Maria Madrid (Knowledge Management & Operations Officer)
Simone Balog (Disaster Risk Management Analyst)
Delwyn Moller (Sr. Remote Sensing Expert)
v
Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Introduction
Digital Elevation Models (DEMs) in its most generic Figure 1. This coastal and near off-shore DEM, developed by
term implies elevation of the terrain devoid of the National Oceanic and Atmospheric Administration (NOAA),
vegetation and manmade features. It represents the greatly aids in forecasting efforts for early tsunami warning
elevation of the earth’s surface in the form of a digital systems. Such a DEM provides the necessary morphology to
image where each pixel1 contains an elevation value of forecast the magnitude and extent of coastal flooding during an
the center point of the pixel, as illustrated in Figure 1. extreme storm or tsunami even.
DEMs are a primary input to any modeling or process
quantification involving the earth’s topography,
and are used across several areas of development.
For instance, in water resources management, the
earth’s surface determines water flow; hence, there
is intrinsic dependence on accurate elevation or
topographical information typically represented as
elevation map layers. In disaster risk management,
disaster risks related to floods, coastal erosion,
storm and/or tidal surges are directly linked to
elevation. Access to elevation, and slope maps enable
responders to assess where floods will infill the Source: www.noaa.gov.
landscape, create inaccessible areas, or create health
risks, e.g., cholera. DEMs are also used prominently in
infrastructure planning and mapping; road design and construction for transportation; urban environmental planning to
assess construction, drainage and green landscaping; agriculture planting and irrigation strategies; ecological modeling
to assess ecosystem flora and fauna; and geological applications such as seismic and coastal monitoring.
Accurate elevation information is therefore key for a wide range of development projects related to poverty
reduction, urban development, water management and other concerns. Thus, the ability to design and
commission or acquire DEMs is increasing in relevance across the globe.
The primary target audiences of this DEMs Guidance Note are World Bank Group Task Team Leaders (TTLs),
project managers and their clients, or anyone interested in DEMs. It primarily aims to: (a) provide sufficient
information to understand the overall processes involved in the acquisition of DEMs and their uses, and (b) to
inform and guide the decision-making criteria; different design and implementation strategies; and options and
costs that exist when acquiring DEMs. This information and guidance can then help facilitate the most targeted,
efficient, meaningful, and economic decisions for DEM acquisition that can be made contextually by both
decision makers and implementers.
As this document demonstrates, Digital Elevation Models is a highly technical topic, thus it is recommended that
Task Team Leaders consult or hire a specialist before embarking on projects that require DEM.
1 A pixel is the smallest controllable element of a picture represented on the screen. In the context of a Digital Elevation Model, a pixel’s address
corresponds to its physical coordinates on the earth’s surface. vii
Executive Summary
The cost of creating DEMs can be significant, often running into millions of dollars, due to their diverse and
extensive utility. The use of DEMs is abundant in spatial analyses. As such, a clear understanding of the range
of DEM types and applications, their operational requirements, and pros and cons of each model is important
before deciding whether to acquire existing data or commissioning a new survey. Having robust background
knowledge can help plan the optimal DEM acquisition. This Guidance Note aims to compile such knowledge
in one publication and thereby address all pertinent topics of DEM creation and use, including a workflow to
facilitate the best way to plan a well-informed DEM-mission or proposal, primarily aimed at non-specialists.
Given the technical nature and complexity of the subject, this Note points out specific sections and key tables
to simplify the reader’s ease-of-use and navigation. Readers who are interested in the more technical aspects of
DEMs should refer to publications such as Maune (ed.) (2007).
DEM Applications
This Note includes an extensive list of applications for a DEM, in topics such as water resources management,
disaster risk management, geology, agriculture and several others (See Section I-2: DEMs Applications). When
drafting a proposal for DEM creation, it is often useful to state other potential uses of DEMs in the proposal
rather than only the intended one; in this way the potential return on investment (ROI) is clearer to the funder.
The ROI’s maximum realization potential is achieved if the license of the generated DEM is made open.
The DEM’s usage greatly determines the DEM output’s technical specifications. For example, for the modeling
of coastal erosion, the DEM must meet the optimal specification (spec) requirements for the coastal erosion
modeling methodology. Several options may exist to produce a DEM that fulfills the required spec for the
project. In these cases, it is necessary for the project bidder to describe in the technical proposal the detailed
methodologies envisaged to create the output DEM.
DEMs can be created for terrains (land surface) as well as underwater (e.g. seabeds). Underwater DEMs are
called Bathymetry, and their generation require a different approach and use of instruments compared to
terrestrial DEM. For underwater, acquisition methods are different depending on whether near-shore or off-shore
bathymetry is required, the threshold typically being water depth of 50m where beyond that sonar equipment are
used. The costs of bathymetry data acquisition and generation is generally speaking 4–5 times more than that of
terrestrial DEMs.
Modalities of DEM Generation
DEMs need to be extensive and exhaustive in spatial scope using remote sensing, to be truly useful. Remote
sensing, from an airborne (e.g., aircraft or drone) or a spaceborne platform (e.g., satellites), represents one of the
ix
best approaches for the development of large area, high-spatial resolution DEMs. The diversity of remote sensing
modalities used to generate DEM products presents a breadth of choices, each with their relative strengths and
x Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
weaknesses and different types of output. The objectives, scope, geographical location and budget of each project
will determine which of the remote sensing approaches are most appropriate to the task. Section II-1: Operational
Guide to Tender a Digital Elevation Model, discusses the different DEMs’ modalities, and Section II-2: Workflow to
Acquire a DEM for Projects, describes five key steps to acquire a DEM for projects.
Three remote sensing technologies provide elevation data: Light Detection and Ranging (Lidar) is more automated and
finely scaled; Radio Detection and Ranging (Radar) is more effective in foggy or cloudy conditions. Stereo photography
(three-dimensional imaging), however, only collects ground elevation data for physically observed or imaged areas.
Lidar offers dense 3D point clouds, vegetation-penetrating abilities, and multiple secondary applications. Radar also
offers vegetation penetration, but lower spatial resolution and higher processing needs. This can result in lower
quality and increased cost in some circumstances/situations. Stereo photography offers context through imagery, but
offers lower spatial resolution and only top-most surface heights.
Spaceborne platforms offer accessibility and coverage, but at the cost of spatial resolution and horizontal and
vertical accuracy, making them especially useful for large areas (e.g., regional-to-continental mapping). In contrast,
airborne platforms have much higher accuracy but sacrifice coverage and accessibility in very remote areas.
Multiple variables also define the output quality and characteristics of a DEM. The most commonly
quoted variables are the vertical accuracy and horizontal point spacing (resolution). For vertical accuracy,
photogrammetric or Lidar systems are best for higher vertical resolution applications in the order of less than 1m.
Medium or lower accuracy applications allow the use of Interferometric Synthetic Aperture Radar (IfSAR), in the
order of 1m to 5m, and satellite archive data. Section II-3: Requirements and Options includes Table 9: Key accuracy
requirements for a range of application areas, which shows the required DEM vertical accuracy for various
applications. Section II-3.3.vii: Budget Constraints, includes Table 10: DEM product costs for various remote
sensing modalities and vendors, which shows some examples of DEM product types (some being commercial-off-
the-shelf (COTS) products), their vertical accuracy, and the approximate price range and licensing conditions. It is
worth mentioning that there are global COTS DEM products available at either no charge2 or at cost.3
However, in most instances DEM applications in topics such as water resource management, disaster preparedness,
or agriculture generally require a finer spatial resolution than what best global products can provide.
The objectives, scope, geographical location and budget of each project will determine which of the remote
sensing approaches are most appropriate to the task. Section II-3 and 4: Sustainability Matrix and Applications
Requirements Matrix discusses the various modalities of DEM generation.
Generating DEMs and the Terms of References (ToRs)
A given project could also use certain key attributes to define DEM products and to generate a ToR, (also referred
to as a Statement of Work (SoW)), and a Request for Proposal (RFP) for product vendors. Section III-1: Key
Attributes for DEMs and the Annexes provide a list of the 15 attributes discussed herein.
This Note also provides the key decisions and many considerations needed to plan a Lidar survey, based on the
intended use of the DEM when commissioning such instrument. One such decision is whether the output DEM
2 For example, Shuttle Radar Topography Mission (SRTM) http://www2.jpl.nasa.gov/srtm/
3 WorldDEMTM http://www.astrium-geo.com/worlddem/
Executive Summary xi
will include/exclude the non-Earth surface vertical information (i.e., buildings or vegetation) depending upon the
desired information. There are three different types of digital surface data: DEM, Digital Terrain Models (DTM),
and Digital Surface Models (DSM). Section III-1B: Digital Surface Data Types, describes these further. Another
consideration during the undertaking of a Lidar survey is whether to acquire aerial photographs concurrently,
given that it is a common and cost-effective practice.
Regardless of how the DEM is created, it is recommended that a specialist be involved in the drafting of the ToR,
especially if the preferred modality is Lidar. A Lidar specialist should be fundamental to the team to ensure that
the ToR incorporates and specifies all variables. The specialist would also evaluate the proposals to ascertain
there are no pitfalls or gaps in the technical components of the selected bid, which may not be as transparent
or simple to the untrained eye. When a Lidar aerial survey is to be executed, there are standard documents and
reports that are expected to be submitted by the vendor prior, during, and post-flight, to ensure data quality.
Section III-2E: Deliverables, discusses a project’s expected deliverables from a vendor.
The requirements for the output DEM—such as the resolution, accuracy, deliverables, and cost implications—
are different from project to project, depending on the envisaged usage of the DEM. It is important to clarify
the intended use of the DEM before commissioning the work to identify the optimal DEM specs. The ToR or
SoW communicates these specs. The ToR serves as the common point of reference between the project manager
and the vendor. It requires careful specification by the project manager, as a vendor is only responsible for what
is contained in the ToR and the technical and financial proposal. If the project manager should decide to alter
or add to the vendor’s requirements after a ToR agreement is established, there is significant risk of a price
increase or slip-up in schedule. Section III-4: DEM Acquisition Terms of Reference, discusses the ToR’s technical
specifications requirement(s) to generate a DEM. ToR and licensing agreement examples are provided in the
Annexes. It is also important to consider data storage and sharing plans as part of the implementation plan. The
data will be wasted unless it is stored and technically made useable by end users.
The Cost of Creating DEMs
The cost of DEMs is highly variable, ranging from free to millions of dollars. Of the free datasets,4 SRTM30 is
available for most of the world except for the Polar Regions at 30m horizontal spacing. Of the free datasets,
SRTM30 provides the best geographical coverage as well as overall quality. In general the cost of a DEM is mainly
determined by the resolutions needed, geographical area to be covered, and whether there is archive data or new
data collection is required. Unfortunately looking for archive data is not as easy as it could be, and may require
specialist knowledge to know where to look for. Sources of archive DEM data include commercial vendors.
The resolution of the required DEM is one of the main drivers of the cost and should be determined based
on the intended usage of the DEM in consultation with a specialist. When no existing data is available, a new
data collection must be commissioned. The cost of such data collection is determined by a range of mission
parameters such as operating costs (aircraft operations, equipment maintenance, and labor associated with
instrument operations, travel expenses) and amount of data processing.
As of 2015, the average pricing for terrestrial DEMs across major vendors is:
4 For Open high-resolution DEM, check opentopography.org. Unfortunately most of the available datasets are of north America.
xii Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
• Lidar: DEM product cost/km2 for new acquisition is approximately US$120 to US$200.
• IfSAR: For a project-specific IfSAR (new acquisition—DEM product costs range from US$30/km2 to US$100/km2
depending on location, area size, terrain, foliage, and extracted vector data.
For an archival IfSAR—Data reprocessing depends on the usability of existing processed data. A project
essentially buys a limited-use license to use the archived data from the vendor. DEM cost ranges from US$11/
km2 to US$25/km2 and US$7/km2 for IfSAR images.
• Stereo Photography: DEM product cost/km2 is approximately US$30. This will depend on whether the stereo
photographs already exist or whether they need to be acquired.
In general, bathymetry data costs 4–5 times more than terrestrial DEM. Section III-2.E.iv: Costing Factors
and Approximation, features Table 9: A general pricing structure for archival lfSAR data, which provides an
estimate of the range of costs associated with the accuracy of the DEM required. Section IV: Data Sharing and
Dissemination discusses cost considerations for different scenarios.
The above costs are for terrestrial DEM. Bathymetry data (terrain data for sea bed)
Case Studies
This Guidance Note concludes by presenting case studies from World Bank projects, as well as other hypothetical
cases. (See Section V: Case Studies).
01
Chapter
The Digital
Elevation
Model Primer
What are Digital Elevation Figure 2. Difference between DEM/DTM and DSM. Digital
Elevation Model (DEM) and Digital Terrain Model (DTM) = (bare
Models? earth) surface without any objects. Digital Surface Model (DSM)
= (earth) surface including objects on the surface
The term Digital Elevation Model (DEM) is a
generic description for digital imagery of elevation,
topography, and/or bathymetry. It is “digital” in the
sense that DEMs most often are produced, distributed,
and analyzed in soft-copy or electronic format. It
describes the “elevation” of the ground surface,
exclusive of man-made structures, vegetation, or any
other objects above ground. Finally, it is a “model”
in two senses: (i) a DEM is a pixel-based “modeled
representation” of the earth’s surface, where each Digital Sur ace Model
pixel of a DEM represents an elevation value; and (ii) Digital Terrain Model
computers or algorithms can use a DEM as input to
model or analyze three-dimensional (3D) topography. Source: http://en.wikipedia.org/wiki/Digital_elevation_model.
There are a variety of topographical definitions related to DEMs however. The main definitions that a user may
encounter when working with topographical data are:
• Digital Terrain Model (DTM). The term “Digital Terrain Model” is synonymous with Digital Elevation Model
(DEM), where the “terrain” refers to the ground, or bare-earth surface, and as such aligns with concept of
a DEM. DTMs are a more refined version of a DEM, however, where additional processing is used to more
accurately represent distinctive terrain features. A DEM/DTM is the standard product used for topographical
analysis, e.g., flood mapping, aspect analysis, and city planning.
• Digital Surface Model (DSM). A “Digital Surface Model”, on the other hand, is a term often confused with a DEM.
In a DSM, “surface” typically refers to the top-most (radar reflective) surface for a given area. This includes
all exposed objects or surfaces in the scene, registering the height of bare-earth or the ground surface only
when nothing else is above it. So for a DSM, while a laser or radio wave will interact with the first object it
encounters—whether a treetop, a building, or exposed ground—a DEM retains only ground points in order to
develop a ground height model. Figure 2 visualizes the difference between a DTM and a DSM. See also Figure 3.
• Canopy Height Model (CHM). A “Canopy Height Model” is a height-above-ground model and is the standard format
used for determining vegetation structure or height. CHM can be expressed as the difference between the top
canopy surface (DSM) and the underlying ground topography (DEM or DTM). For instance, a specific pixel (image
point) in a forested area may be 330m (DSM) minus 300m (DEM), equaling a 30m tree-height for that specific pixel. 01
02 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Figure 3. A digital elevation model (DEM) and Digital Surface • Building Height Model (CHM). A “Building
Model (DSM) for a forested area derived from light detection and Height Model” is analogous to a Canopy Height
ranging (Lidar) data Model, but instead of measuring vegetation, it
measures the height of any structure that is the object
of an analysis. For example, building height model or
tree-, vehicle-, pole-, height models (Figure 4).
• Triangulated Irregular Network (TIN). A
“Triangular Irregular Network” of a DEM refers to a
digital elevation surface that is represented, not as
a grid (i.e., by pixels), but as a connected series of
contiguous, non-overlapping triangles. The triangles
are made from a set of points called “mass points”,
and within each triangle the surface is represented
by a plane. The more mass points, and the more
carefully collected, the more accurate the model of
the surface. A TIN represents one of the digital data
structures used in a Geographic Information System
(GIS) for the representation of surfaces.
The remainder of this Guidance Note discusses
various applications of DEMs, the remote sensing
methods used to measure heights for creating a
DEM, the necessary planning for generating a DEM
(“mission planning”), and quality aspects of DEM
Source: www.frec.vt.edu; courtesy Dr. Jan van Aardt (Rochester Institute of creation and usage.
Technology)
The illustrations below show various elevation grids
or surfaces. Each grid contains pixels, which in turn
contain a specific, single elevation value. With this
data, continuous and gridded height values can be
presented as images, similar to displaying per-pixel
Modeled Height Surface
red, green, and blue (RGB) values for a digital photo.
In the context of a modeled height surface, any DEM represents
a height estimate (z-value) on a per-pixel basis for the (x,y)
coordinate.
DEM Applications
So while DEMs can be considered to be continuous height surfaces
(i.e., made up of adjacent pixels across a large uninterrupted space),
The potential of DEMs to derive actual ground-
the pixel height is constant for an entire pixel. In others, however,
height and height-above-ground has far-reaching
a pixel may not have contained an original height measurement to
begin with, so its height is interpolated. In other words, the height applications with broad practical and analytical
measurement of a pixel is estimated from a sparser set of actual utility. This chapter focuses on DEMs as a
height measurements. principal input for geospatial products, modeling,
monitoring and analysis. However, the quality of a
In either, height measurements can be derived by:
DEM—especially in terms of spatial resolution or
cell size, accuracy, and completeness—has critical
1. Physical measurements such as ground surveys; or
2. Remote sensing modalities (Lidar, radar and stereo imagery). implications for the usefulness of the resulting
applications or information.
The Digital Elevation Model Primer 03
Water Resources Management Figure 4. Example of the canopy height model (CHM) as the
difference between the above DSM and DEM (Figure 3) (DSM-
Water flow is determined by the shape of the earth’s DEM=CHM). Instead of creating a “height-above-sea-level”
surface. Water Resources Management (WRM) and product, as with DSM and DEM, CHM creates a grid where each
all of its sub-categories are intrinsically dependent pixel contains the “height-above-ground” value. Brighter tones
on accurate elevation or topographical information, represent taller trees, darker tones represent height values
typically presented as elevation map layers. close to the ground level. End-users can now analyze such a
CHM for forest volume and biomass assessments
WRM is taken here to encompass hydrological
modeling and bathymetric analysis. Hydrological
modeling consists of both the hydraulic and
hydrological process, where hydraulic refers to
the physical/mechanical flow of water (e.g., water
pressure, friction, disturbance, turbulence), and
hydrological represents the flow of both ground and
surface water through the ecosystem. Bathymetric
represents underwater topography. Below, the
typical DEM applications for hydrological modeling
and bathymetric mapping are discussed.
Hydrological Modeling
Hydrological modeling encompasses both hydrology Source: www.frec.vt.edu; courtesy Dr. Jan van Aardt (Rochester Institute of Technology)
and hydraulics in this Guidance Note. While the two
concepts are closely coupled, the focus in this document is primarily on hydrology.
Flow Channel Characterization
A flow channel typically is defined as conduit with a free surface, as opposed to a pipe with no free surface. More
practically, a flow channel represents an open, natural, or man-made structure or “canal” which guides water flow
in a specific direction at a speed that is coupled to the size and slope of that channel. Characterizing flow channels
for the purpose of DEMs depends heavily on the ability to map stream form and riparian (river zone) vegetation.
Riparian vegetation can be classified by structural metrics, such as height in proximity to flow channels, or by type,
such as classes, genera, or even species. The focus here is on the use of DEMs to characterize the specific metrics
that define stream form (Figure 5).
Figure 5. Metrics that define stream form.
• Bank condition Bank top Spill Area
• Arti icial in-stream barriers Top Le Bank Spill
Channel Width Top Right
Le Bank Spill
• Streambed width
Ba
le
Convexity Le B. Channel Depth
nk
g
An
• Bank ull/channel width Le
x-sectional area
k
n
an
gt
Le Bank In lexions h
tB
gh
• River centerlines
Ri
Bottom Le Bank Bed Width
Bottom Rigth Bank
• Water body Transect minimum
Image: courtesy of David Moore, RPS Australia East.
04 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Most of these metrics can be assessed using DEMs, although other higher-order products from Lidar, aerial
photography, or radar sensing also are useful. Figures 6 and 7 show remote sensing workflows, in this case based
on Lidar and aerial imagery used to derive many of stream form metrics.
Flow channel characteristics have a direct influence on the physical mechanics of water movement
(hydraulics), which in turn drives the flow of water through the system (hydrology). As illustrated by Figure
6 and 7, flow channel characteristics are best derived from topographical data for the entire streambed.
Bathymetric Lidar can assess the depth and morphology of underwater topography, though water depth
and turbidity can cloud the assessment of terrain features on the bottom of lake, rivers, or other bodies
of water. In these and other instances, scientists and practitioners tend to interpolate data (estimate
between measured points) or extrapolate data (estimate beyond measured points) to gauge a flow channel’s
structure. Once a best guess is obtained, hydrologists can model flow characteristics, such as water flow
(speed), turbulence, or pressures, and in turn estimate run-off, erosion, flood parameters, or other outcomes.
Water catchment (watershed) mapping.
A water catchment, also called a watershed or drainage basin, refers to the spatial extent of an area of land where
surface water (from rain, melting snow or ice) drains to a single outflow point at a lower elevation. Since the
shape of the Earth governs water flow, a DEM is extremely useful for identifying flow channels, connecting these
channels in the form of stream networks, and as a result, delineating catchment areas. Catchment maps, such as
Figure 6. Stream Form DEM. (a) An example of a Lidar point cloud separating vegetation from
the ground, to derive a DEM (top-right); (b) associated color-infrared imagery, here shown in
true color, used to generate (c) riparian zone foliage cover, (d) with imagery shown as an infrared
representation; red indicates healthy vegetation.
(d)
Source: Courtesy of Nathan Quadros, Department of Sustainability and Environment, Victoria, Australia.
The Digital Elevation Model Primer 05
Figure 7. Streambed and Bank Metrics. (a) From the Lidar point cloud and DEM in figure above (a) to
extraction of stream form metrics, streambed width and channel width; and (b) representations of
the streambed and bank full width metrics, as shown on a DEM and (c) as a top view.
(b) (c)
Source: Courtesy of Nathan Quadros; Department of Sustainability and Environment, Victoria, Australia.
in Figure 8, enable water resource managers to designate management areas, map influence extents for pollution
management, dam construction, and other needs, and to calculate water resource quantities.
Specific examples of the applicability of DEMs at the watershed level include instances where a hydrologist,
ecologist, or general catchment manager may want to:
• Assess drought severity in the order of streams
Characterization of Flow Channels
impacted (i.e., the smaller streams, converging to
form a larger stream, dry up first); The characterization of flow channels relies heavily on the ability to
• Map downstream impacts of pollution; map what is called stream form and also the riparian (river-zone)
• Monitor streamflow and water supply via weirs; vegetation.
• Drive policy decisions based on constituent water
As opposed to random samples of both types of information, most
resource use;
remote sensing approaches enable extensive and exhaustive
• Plan infrastructure development and minimize its collection of information, specifically in the form of DEMs (stream form).
impacts; and
• Direct land use and land cover change to best Riparian vegetation generally can be classified using either structural
utilize water resources. metrics, e.g., height classes by proximity to flow channels, or
via type, e.g., vegetation classes, genera, or even species if the
necessary imaging tools are available. These imaging tools would at
In efforts by to manage and collect water within
the very least include color and near-infrared imagery, even though
a catchment and control its outflow, DEMs are an more spectral information, i.e., color, various near-infrared bands,
essential part of the modeling and decision-making and even shortwave-infrared bands would be more beneficial to
chain that informs water resource managers. With a advanced products like species maps.
DEM, a water drop can essentially be placed at any
The most typical riparian vegetation characteristics include
place within the model and its path can be evaluated
vegetation width, fragmentation, overhang, size, presence of weeds,
as it moves through the catchment. This has a
foliage cover, and structure, all of which can be assessed using a
significant impact on the ability to manage natural combination of remote sensing sensors.
water resources.
06 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Figure 8. Watershed Catchment Area. Floodplain characterization
Example of a water catchment area, made up DEMs are critical for characterizing the
of many river or flow channels, all of which floodplain—the geographical extent of low-lying
converge at the head of the catchment, as land areas that will be subject to flooding above
defined by the DEM. certain thresholds. Having assessed flow channels
and connected them in stream networks to form
a catchment or watershed based on ground
morphology, DEMs can portray the associated
floodplains. This is discussed in more detail in the
section “Disaster Risk Management.”
Stormwater management
Stormwater managers rely heavily on DEMs for
monitoring and modeling watersheds, streams, and
other flow channels. DEMs can track hydrologic
processes (such as modeling the water’s volume flow
during peak rainfall events) and hydraulic processes
(modeling where that water will flow and how storm
water will interact with structures such as culverts
Source: Image courtesy of David Moore, RPS Australia East. and bridges). In concert with channel morphology
modeled from DEMs and associated remote sensing,
data on existing structures can be collected from municipal maps or from the DEMs’ remote sensing sources.
A high spatial resolution color camera, e.g., used with Lidar, can add data, classifying structures by height and
shape, which more completely informs stormwater flow and interactions across the landscape. This use of
DEMs is often focused on urban areas, but channel morphology interacts with man-made structures in rural
environments as well.
Wetland Mapping
Wetlands are characterized by their morphology, their location within the landscape, and the vegetation species
that live there. The concepts of context, shape, and vegetation type are of critical importance when it comes to
delineating wetlands. Photogrammetry has been used extensively to detect boundaries between land and water,
and by extension, wet vs. dry and plants vs. no plants. But stereo imagery is not ideal for characterizing wetland
topography because wetlands often lack distinct features to use for the stereo process. Lidar, on the other hand,
is often better suited for the mapping of wetland topography. Land features cannot be mapped if one cannot
see through the land cover, and Lidar has been unable in many instances to penetrate to the ground, especially
if there are dense wetland vegetation species. This, to some extent, can be remedied by using Lidar system with
denser point spacing (more hits/m2) and multiple returns for every laser pulse; increases in both these system
parameters lead to better penetration of the laser pulses to the ground surface.
The combined use, however, of Lidar (vegetation height) and high spatial resolution aerial imagery enables more
than eighty percent accuracy in classification of most wetland species. So while a DEM is insufficient on its own
for mapping densely vegetated wetlands, the fusion of DEM’s structure and photogrammetry’s color information
can both map wetlands and classify the associated species.
Water Supply and Sanitation
Accurate topographical data is essential for water supply management and maintenance of hydrological and
ecological services that provide water. High-resolution, high-accuracy DEMs can be a prerequisite for effective
The Digital Elevation Model Primer 07
water supply and sanitation management, delineating
watersheds and catchment areas for wells, and enable Example: DEMs & Water Supply and Sanitation
users to map how water flows through a landscape. Most
The U.S. Environmental Protection Agency’s (EPA) Wellhead
commercial GIS software packages now have the ability to
Protection Program involves an area around a well or field
map watersheds based on an underlying DEM. that sources a public water supply and that may be at risk of
contaminants. To protect the wellhead, a management agency may
Bathymetric Analysis (depth maps) establish a local team to:
Bathymetric analysis, or water depth analysis, is important
• Assess which area provides water to public supply wells;
to applications related to domains such as ecology
• Determine where existing and potential sources of
(submerged morphology, e.g., seafloor structure); traffic
contamination exist;
and transport (harbors, landing zones); disaster modeling • Develop management plans relating to these sources of
and response (wave action, tsunami impacts); beach erosion contamination to minimize their impacts on water sources; and
monitoring and mitigation, and others. Many bathymetric • Establish a contingency plan in case of emergencies, to identify
analyses therefore are coupled with water resource where pollution sources originate, or which wells may have to
close, as management of continuous water supply may become
management and coastal monitoring.
challenging.
Source: www.epa.gov.
Disaster Risk Management
Three-dimensional (3D) data are essential for mapping and assessing disaster risks as well as preparing for,
responding to, and preventing disasters. For example, terrain modeling and surveying for both exposed and
below-water topographies are increasingly being used to predict, map, and manage storm and other natural
disaster events. The focus of disaster risk management strategies is to increase awareness of risk reduction
and response strategies, physically reduce the risk of property and landscape damage and loss of life, and to
continuously increase community resilience to disasters. DEMs are also important for DRM, in areas such as:
• Elevation-related disaster risks. For example, disasters risks related to floods, coastal erosion, storm and/or tidal
surges are directly linked to elevation. Access to elevation and slope maps enable responders to assess where
floods will infill the landscape, create inaccessible areas, or create health risks (e.g., cholera).
• Structural building damage. When the type of building damage is not visible in aerial or satellite imagery,
structural damage at a level of detail necessary for appropriate disaster response is best assessed through
3D Lidar data. This is especially critical in the case of earthquakes, where “pancaked” building failures or
completely flattened buildings that seemingly look intact from above, dot the landscape.
• Wildfire risks are tied to elevation data in that the vegetation height (fire fuel load) is calculated by subtracting
the top-most height surface from the DEM. Furthermore, fire models assume that fire propagation speeds
increase upslope, a property that is also derived from DEMs.
DEMs are useful for a variety of so called “derivative products”, or products that include a DEM as precursor
to its derivation—e.g., building heights, tree heights, fire fuel loads, etc. What follows is a closer look at two
examples of disaster response DEM applications where a DEM is integral to the actual application: flood
management and coastal inundation.
Floodplain Management: Flood Extent, Depth, and Impact
Flood risks are an increasing concern given changing global climate and landscapes. Not only are extreme
water-related events more frequent and severe than in the past, but landscapes are losing their natural buffering
functions (root-soil binding, increasing water absorption rates, and so forth) as well, becoming impervious
surfaces that exacerbate water runoff and associated flood risks. Given these growing risks, accurate, high spatial
08 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
resolution and large area coverage DEMs are essential for: (i) developing flood hazard models; (ii) producing flood
risk maps; (iii) evaluating flood response plans; and (iv) developing floodplain management strategies (Figure 9).
Floodplain management approaches can use DEMs for real-time applications as well as “virtual flood” modeling.
Real-time flood monitoring and mapping lead to products such as:
• Estimated flood depth based on rainfall amounts (derived from meteorological data) or flood extent or
delineation (derived from flood mapping via airborne imagery).
• Run-off modeling based on stream flow characteristics (e.g., flow quantity, speed, turbulence) given the rainfall
and terrain properties (DEM).
• Erosion or soil loss modeling where DEMs (and their inherent slope, aspect, topographical information) form
one input to erosion models, along with data on rainfall characteristics (e.g., amount, duration, severity), soil
type, and surface vegetation.
• Relocation strategies where DEMs are essential for relocation planning and reduction of flood impacts on
internally displaced persons (IDPs) camps.
These kinds of products can inform floodplain management strategies. This might include remedial or preventive
actions such as vegetation cover on steep slopes, stream channeling via engineering structures (berms, support
structures), policies that prevent development in high flood risk areas, disaster management (priority response
areas, impact assessments, etc.). Floodplain management strategies also rely heavily on the concept of virtual
Figure 9. An example of a DEM (grey underlying surface; brighter = higher elevations), used to
map a river’s floodplain and a 100-year flood event’s depth across a landscape in California, USA.
Note that the flood depth and extent can be exactly mapped, based on the underlying DEM and
using assumed rainfall amounts, expected run-off as per impervious surface maps, and existing
conditions (water table depth, soil saturation).
Source: www.nps.gov
The Digital Elevation Model Primer 09
flood plain modeling. Remedial actions can be based on projected, or modeled flood events, derived with high
resolution, high accuracy DEM.
Coastal Inundation
Coastal inundation refers to the flooding of coastal areas by severe weather events, including hurricanes,
tsunamis, or other large storms. A continuous topographical and bathymetric DEM can be an extremely valuable
input to models that quantify inundation threats and inform management of coastal inundation risks and events.
Bathymetric Lidar, for assessing water depth and underwater bottom topography, is especially useful in inter-
tidal zones where accessibility hampers traditional assessment methods. Mapping bottom roughness is also
critical for accurate inundation assessment, given the impact on wave propagation.
Geological Applications
DEMs are of significant use in the fields of geology, geomorphology, and geophysics. Examples include land form
and geo-hazard mapping based on shaded relief maps that provide insight to, for example, illumination angles,
contour maps, aspect maps, or slope maps Figure 10). Two related applications are discussed in detail—fault
mapping and coastal monitoring.
Subsidence or Fault Mapping (seismic monitoring)
Scientists and agencies that monitor seismic fault zones require DEMs of high spatial resolution and accuracy to
monitor these areas. Ideally, DEMs should be constructed prior to any seismic event to establish a baseline for
comparison to post-event topographical or survey data. DEMs are essential for monitoring movement along such
fault lines and for assessing damage after earthquakes or volcanoes. For example, significant vertical changes in the
DEM are indicative of subsurface instability. Rapid and frequent monitoring is essential in such destabilized areas,
Figure 10. An example of a 1m gridded DEM hillshade (left) and the associated slope map (right). The slope map was
derived from the DEM, while the colors show steep slopes (red) to flatter slopes (blue).
Note the indications of steeper slopes, even in this relatively flat terrain example.
10 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
mainly because large-scale events have been correlated to recent landscape shifts, and because, in some instances,
the instability of landforms actually leads to changes in datums and positions, resulting in DEM inaccuracies.
Coastal Monitoring
DEMs are used increasingly for coastal applications, due in large part to technological advances in mapping
and monitoring, and for assessing coastal climate change impacts. DEM applications in these environments are
related to: shoreline delineation, monitoring sea level rise, general coastal management, coastal engineering,
mapping coastal inundation, and underwater applications such as seafloor morphology and underwater
archeology. In coastal monitoring, DEMs especially form an integral part of defining:
• Shoreline delineation. Shoreline delineation is usually related to the legal demarcation of national territory
with the boundary typically expressed in terms of average high water levels over a specified period. Shoreline
delineation is also critical for monitoring ecological processes such as beach erosion or sand deposition.
• Sea level rise. Sea level rise is generating growing concern in the context of global climate change and shrinking
polar ice caps. Coarse resolution DEMs are not suitable for assessing sea level rise, however, since small
differences in shallow elevations across short distances could have a distinct impact on affected areas. Instead,
more sophisticated simulations that incorporate tidal response, wind events, and storm surges are often used
to assess the impact of sea level rise on coastal communities.
• Coastal management. Coastal environmental management agencies rely on accurate DEMs for scientific and
regulatory applications. This can include the determination of erosion hazard areas based on beach dune
boundaries, historic shoreline data, and erosion data, and enforcement of setback regulations for coastal
development projects. Figure 11 shows an example of coastal monitoring, using a Lidar-derived DEM for a
beach area in the Gulf of Mexico, pre and post Hurricane Rita.
• Coastal engineering. Coastal dynamics and monitoring of sand and beach movement are also essential to
coastal engineering applications. DEM applications can inform sediment transport, budgets (amount
and error margins), and the design of coastal structures, such as breakwaters or jetties. DEM engineering
applications may also include locating anchorage areas, harbor engineering, laying pipelines or cables, and gas
and oil production.
• Coastal flooding. Coastal flooding or inundation is determined by both coastal morphology and the storm event
itself, and spans the categories of bathymetric analyses, coastal monitoring, and disaster response.
• Underwater applications. Two prominent applications of DEMs for underwater mapping are: (i) seafloor
morphological assessment and (ii) underwater archeology. Seafloor morphology refers to the physical
geography of the seafloor, which DEMs can quantify and present using artificial illumination and shading to
generate an easily interpreted seafloor scene. Color can be used to drape properties such as depth or sediment
type on top of the DEM. This kind of morphological mapping is useful as it relates to geologic process or for
planning underwater infrastructure, such as fiber-optic cable deployment and pipelines. Figure 12 and 13 show
the detail possible when mapping seafloor morphology, most notably near-shore, underwater structure.
Underwater archeology, on the other hand, requires inspection, monitoring, and conservation activities. Each
component is aided by high-resolution DEMs that can inform safe navigation of archeological sites, such as
shipwrecks, and optimize exploration activities based on seafloor morphological data.
Infrastructure
Infrastructure planning, mapping, and assessment are all activities that rely on DEMs, given the correlation
between infrastructure and the properties of the earth’s surface. Civil engineers typically make use of surveying
The Digital Elevation Model Primer 11
Figure 11. This DEM or 3D image sequence shows, from top-to-bottom, the ground and near-ground
structures before Hurricane Rita, after the storm event, and the change, or difference between the
top and middle images, respectively. Data such as these are useful for assessing beach erosion
and changes and developing management strategies.
Source: www.usgs.gov
Figure 12. This coastal and near off-shore DEM, developed by the National Oceanic and
Atmospheric Administration (NOAA), greatly aids in forecasting efforts for early tsunami warning
systems. Such a DEM provides the necessary morphology to forecast the magnitude and extent of
coastal flooding during an extreme storm or tsunami event.
Source: www.noaa.gov
12 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Figure 13. An example of near-shore underwater topographical procedures to derive a very accurate DEM. Many
mapping via a high resolution DEM. Note the seafloor structure remote sensing modalities have now developed
related to erosive forces, which in turn could impact wave action to the extent where derivative data can be used to
and associated coastal disaster impacts. extract good quality DEMs for road management and
urban analysis.
Transportation
Highly accurate surveys are required in the design
and construction of road infrastructure, often to
the 0.2–0.3 meter contour interval level. Lidar and
stereo photo surveys are commonly used for these
kinds of tasks, given their accuracy, precision, and
comprehensive coverage. DEMs created with these
remote-sensing approaches are useful for planning,
mapping, and constructing roads, as well as for
optimizing construction vehicle roads and ensuring
safer working conditions.
Urban Mnalysis
Source: www.noaa.gov
The use of DEMs, Digital Surface Models, and their
criteria (elevation, slope, aspect, curvature) has
become commonplace in urban environmental
planning and infrastructure assessment. Typical applications include: (i) identifying building construction sites;
(ii) assessing drainage structures and patterns in urban landscapes; (iii) planning green landscapes, such as golf
courses or city parks; and (iv) assessing roadway, bridge, and other infrastructure conditions. Private and public
sector organizations use DEMs to assess building volume and extents for insurance or tax purposes, though most
DEMs have to gap-fill the ground structure beneath building footprints (usually by data interpolation). Digital
Surface Model used for urban applications also come in handy to assess roof heights and possible impacts of a
flood event through submersion of structures.
Agricultural Applications
DEMs in agriculture are used primarily at the field or landscape scale. Farmers in developed and developing
countries use DEMs to inform planting and irrigation strategies, e.g., to avoid waterlogged crops in depressions or
water-stressed crops on rugged, shallow-soil outcrops. DEMs are also used to develop contour-farming strategies
to minimize soil erosion and nutrient losses along the slope direction. At very fine scales, high resolution DEMs
can help inform management of high-value intensive crops, e.g., vineyards, to ensure that each plant is ideally
located or managed for optimal production. The use of DEMs in precision agriculture—responding to inter- and
intra-field crop variability—is more limited, relating mostly to hydrological mapping and monitoring.
3D Visualization
Three dimensional visualization (3D) overlaps with many of the common DEM applications (modeling,
topographical analysis, landform development, contours, break lines, slope, curvature, aspect products, among
others). Other, more diverse applications vary from developing 3D city- and landscapes for the gaming or
The Digital Elevation Model Primer 13
entertainment industries, to developing accurate Figure 14. An example of a virtual 3D scene (for an actual
3D environmental models for simulation purposes. cityscape), which is constructed based on 3D visualization and
An example of the latter is the use of Lidar, ifSAR, modeling data. Empirical simulations can be run in a virtual
or photogrammetry to develop a scene for use in scene of what planned or in-development sensors would “see”.
simulation of imagery from satellite and airborne For instance, still-in-design system specifications of upcoming
sensors still under development. The area shown spaceborne sensors can be used and programmed into a
in Figure 14, as an example, is a virtual scene based simulation environment, and generate simulated but realistic
on airborne data of an actual cityscape, used for scenes for evaluation of the planned system’s capabilities.
simulating imagery from such sensors in development. Sections I-4: 3D Visualization discusses these topics further.
Such made-up scenes are used by agencies such as
NASA to simulate the imagery that an upcoming
satellite might collect for that specific scene. This
was done for NASA’s new Landsat-8 platform, where
researchers generated simulated scenes for the
theoretical Landsat-8 sensor payload for the Lake
Tahoe area in the U.S., prior to the satellite’s launch.
These scenes were used to evaluate engineering design
limits and develop image preprocessing approaches,
even before the satellite was in orbit.
Ecological Modeling
DEMs are widely used for ecological applications
assessing ecosystem flora and fauna. Figure 15 shows
a small portion of an ecosystem as scanned by a
Lidar system. The image is comprised of millions of Source: www.noaa.gov
coordinate points (x,y,z), each of which represents
a “height-above-ground” value. Referencing any point relative to the ground requires an accurate DEM, which
scientists, modelers, or managers can then use to analyze the landscape’s vegetation structure (height, biomass,
canopy dimensions, carbon stored), habitat (canopy gaps, forage amount, vegetation coverage), drainage
patterns, growth patterns (carbon loss/gains), and fragmentation (interconnectivity of animal ranges).
Commercial Forestry
In commercial forestry applications, DEMs are necessary for deriving value-added canopy height models. The
CHMs can be used, in turn, to assess tree stock or biomass, classify stand structure, map roads and drainage, and
plan harvest schedules, among other products. Other key uses for DEMs specific to commercial forestry operations
include (Figure 16):
• Road planning and construction. Forest operations are heavily dependent on road networks for the management
and extraction of woody resources. As such, accurate and detailed DEMs are invaluable to ensure road
development that is accessible as well as sustainable, cost-effective, environmentally friendly, and erosion-
resistant.
• Site suitability mapping. Specific tree species require specific environments for optimal growth. DEMs can be
used, in conjunction with other auxiliary data sets, to assess the suitability of a site for specific tree species, in
14 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Figure 15. This Lidar point cloud illustrates the ecological landscape features that can be assessed
using 3D information. Note the clear-cuts (middle-left), the river’s meandering, individual tree
crowns, and even farmland (bottom-right). These landscape features can only be assessed in terms
of height-above-ground after the DEM, derived from the ground-based Lidar returns, is generated.
Source: Image courtesy of Dr. Jan van Aardt and Mr. Donald McKeown (Rochester Institute of Technology).
that species require certain slope, sun (aspect), and temperature (elevation) regimes to flourish. When DEMs
are combined with data sets such as soil maps, soil chemistry, and weather maps, the forester is endowed with
a useful resource with which to match species to sites.
• General forest management. Commercial forestry includes a host of operations that require the preparation of
sites, planting of seedlings, growing of tree stock, harvesting timber, and minimizing negative site impacts.
DEMs are crucial to all of these operations in that mechanized management requires information on where
machines can safely and sustainably operate with reduced environmental impacts for site preparation and
tree harvesting operations. Much attention is paid to minimizing erosion due to incorrect forestry operations
on especially steep slopes, as well as minimizing soil compaction, which is dictated by soil type, moisture,
and slope.
Mapping
Most maps rely on basic Geographic Information Systems (GIS) “layers,” where each layer represents a feature
on the geographic landscape. Examples include towns (a point layer), rivers and roads (line layers), and province
or state boundaries (an area or “polygon” layer). Additional digital layers offer tremendous value, not only in
terms of adding map context, but more importantly, by adding a quantitative 3D component, i.e., via a DEM layer.
It is also important to note that, without 3D relief or DEM data, most features on any map exhibit what is called
“relief displacement;” this can be thought of as a displacement outward from the center of a vertical photograph,
The Digital Elevation Model Primer 15
Figure 16. Examples of DEM-related commercial forestry products. None of these products are
possible without the estimation of a DEM as first step, as most forestry products (e.g., volume,
stock, road planning, drainage mapping, riparian zone management) rely on height-above-ground
information.
DEM-related forestry applications:
• Woody resource inventory (a)
• Overstory canopy loss (i.e., change detection) (b)
• Road and drainage mapping (c)
• Stocked area plantation mapping (d)
• Rapid volume verification
• Harvest planning
• Net available area in native forests
• Stand structure classification
• DEM products (e.g., slope)
• Biomass estimation
• Forest fuel assessment
• Tracking harvest vehicles
• Tree crown mapping
• General forest management
Source: Courtesy of Russell Turner; Forest Science Centre, Department of Primary Industries New South Wales, Sydney, NSW,
Australia.
of the base and top of a feature. For example, when one views a tall tower at an off-nadir (not straight down)
angle, it seems as if the base and top of that tower is not located at the same x;y coordinate. DEMs allow us to
represent map features in a horizontally accurate fashion by accounting for relief displacement—when photographs
project a feature’s top and bottom to different x,y coordinates, the feature is not exactly vertically aligned and this
displacement can be used to determine the object’s height. In this section, different kinds of maps will be discussed
in how they relate to DEMs.
Planimetric Maps
Planimetric, or two-dimensional, maps show the horizontal (x,y) location of landscape features, such as on
a common road map. This type of mapping requires the use of elevation data, as from a DEM, to represent
16 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Figure 17. An orthophoto of a portion of Port-au-Prince, Haiti horizontal features in their accurate horizontal
shortly after the devastating 2010 earthquake. locations. This is especially true for maps generated
from stereo photography (two or more lenses
with separate image sensors allow capture of 3D
images) where tall objects are displaced more. The
generation of accurate planimetric maps requires
adjustment for elevation differences through a
process called stereo photogrammetry. Exceptions to
this rule include maps that are generated by other
methods, such as field surveys.
Topographic Maps
Topographic maps are a special version of
planimetric maps and are based on the same
principles and methodology. The major difference
is that topographic maps include not only the
planimetric features, but also include contour and/
Note: that this image, which was ortho-corrected using a 1m DEM, shows accurate
or spot height information, such as landscape
building locations in a topographically diverse environment with lots of elevation
changes. Without such a DEM correction, the buildings would have appeared beacons. As such, DEM or 3D data are necessary
deformed and even displaced in terms of base vs. rooftop. when generating the information content found on
topographic maps.
Digital Orthophotos
Digital orthophotos are aerial or spaceborne images that have been corrected for any relief displacement by
using elevation or DEM data. Digital orthophotos can only be free from any relief or tilt displacement if the
images were corrected for the x,y displacement due to elevation differences of each object’s topmost surface.
Using DEMs and top-surface base data to correct for rooftop pixels, for instance, results in a building’s
rooftop appearing directly above its base, as opposed to being distorted in the final orthophoto product
(Figure 17).
Ancillary DEM Applications and Products
The applications mentioned in Section II represent only a sample of possible usages of DEM or DEM-related
products. Many more exist: air navigation and safety (elevation changes, gradients), military (line-of-sight,
cover/concealment, near-shore bathymetry, terrain avoidance), communications (cell tower line-of-sight),
recreation (hiking, fishing), and the real estate sector. DEMs and the information they convey will remain
useful to any application where a 3D or topographical characterization of the terrain is required. In some
sense it is safe to say that any earth-bound 3D application is bound to have some relation to a DEM. Selected
examples include:
• Soil mapping. DEMs and DEM-related products can be used to update soil maps, place soil lines, delineate
landform breaks, adjust soil boundaries by landform boundaries, and plan soil surveys to increase efficiency.
• Engineering applications. Engineers can use DEMs derived to alleviate the need for topographic surveys,
thereby reducing 2–3 days of fieldwork to less than a day’s effort. Other related engineering examples are dam
construction, river modeling, and infrastructure reinforcement (Figure 18).
The Digital Elevation Model Primer 17
• Corridor or right-of-way maps. These maps show Figure 18. A DEM that clearly highlights a small landslide, which
linear corridors associated with power utility could affect infrastructure integrity.
rights-of-way, pipelines, or road infrastructure.
They are most efficiently generated using Lidar
data, but a DEM component is always included
to assess topography and sometimes structure
height-above-ground, e.g., power lines. For
instance, a DEM can be used to express height-
above-ground of utility structures towards
assessment of vegetation encroachment on often-
expensive power grid infrastructure.
• Insurance maps. DEMs can be used to assess
floodplain location and extent, thereby affecting
insurance risk assessments. Other examples
include DEM assessment of high-risk building
sites and post-disaster event damage.
Source: www.usgs.gov
02
Chapter
Operational Guide
to Tender a Digital
Elevation Model
Digital Elevation Models: Design Issues for Consideration
In planning DEM design and implementation, project managers need to identify a combination of data sources,
collection methods and modalities that will get them to a cost-effective response that meets the user’s needs.
There is, however, no simple template, as any particular DEM application will have its own character and
circumstances. This section aims to provide broad guidance for meeting project requirements and operational
parameters, all within a specified budget, weighing various constraints against different modalities, collection
methods, and data sources. A specialist can provide advice on the technical specifications to be defined in the
Scope of Work/Terms of Reference. It is therefore recommended that a DEM specialist be hired on projects that
require the acquisition and use of DEMs to avoid wasting large amounts of funds on generating/acquiring DEMs
that do not meet the needs of the project. The specialist can also provide guidance on whether the delivered
product meets the specifications described in the ToR.
Decision Points to Acquire a DEM for Projects
Need for Digital Elevation Model (DEM) identified for a project.
Hire DEM technical specialist
Plan for data storage and data sharing of the generated DEM
Define the ideal technical spec required for the DEM, based on the intended use
Define the geographical Area Of Interest (AOI) where the DEM is needed
For the AOI, search for:
• Existing DEM datasets generated for other projects covering the same area
• Investigate if globally available off-the-shelf DEMs serve the purpose, for example, WorldDEM (http://www.geo-
airbusds.com/worlddem/), ALOS World 3D (http://alos-world3d.jp/en/), NEXTMAP http://www.intermap.com/
data/nextmap-world-30)
19
• Look into the possibility of using existing raw datasets of the area that can be used to derive a DEM, such as
stereo aerial photography.
20 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
• Research any on-going projects that are planning on generating a DEM for the AOI. (World Bank funded
projects or externally funded projects)—if so, does the timing of the data generation suit the project timeline?
If there are existing DEMs that can be used for the project, purchase the DEM as goods.
If there are no existing DEM datasets that can be used for the project, commission a new DEM dataset for the AOI.
In most cases, this will involve doing a Lidar survey. Lidar surveys can generate very high-resolution DEM. In
cases where a large area is to be covered, it may make sense to compromise on the resolution and generate a
DEM with lower resolution by acquiring satellite radar data (Interferometric Synthetic Aperture Radar- IfSAR) or
use other means.
After all the technical requirements are set following discussions with the client and technical consultant, issue
an EOI, Limited International Bidding (LIB) where only vendors with good track records are invited to bid.
Requirements and Options
Project requirements are driven by the information needs of the end user. Several of them—vertical accuracy,
spatial resolution, study area size, and study area location—effectively predetermine the options for data
acquisition. Realizing DEM requirements can be further constrained by other factors influencing data collection,
such as time allowed for delivery, prevailing weather conditions in the study area, vegetation and structures, and
last but not least, available budget.
Many people will associate the process of generating DEMs with Lidar surveys; however, Lidar is not the only
means to generate a DEM. A DEM with the same spec can be generated using various mediums and datasets.
These different mediums vary from satellite sensors, sensors attached to aircrafts as well as traditional surveying
methods on the ground. Technical details of the different mediums can be found in the accompanying document
“Technical Annex: How DEMs are created: a brief introduction to remote sensing modalities.”
In this section, the technical specifications that need to be specified for a DEM to be generated and some
decision making criteria when there are more than one options will be described. Once the specs for the output
DEMs are defined, it is up to the vendor to suggest the most economic and efficient way to generate the required
DEM, taking into account the context of the overall project.
Vertical Accuracy
Accuracy (especially vertical) is the primary quality metric for DEM products. Accuracy expressed as vertical
error can be characterized as Very High (<0.5m), High (0.5m to 1.0 m), Medium (1.0m to 5.0m), Low (5.0m to
10.0m), or Very Low (>10.0m). Data from airborne collections with ground control usually have the best accuracy
but do not generally have the large area coverage available from archived satellite data. Inaccessible terrain may
make ground control difficult and reduce the attainable accuracy. Higher accuracy requires photogrammetry or
Lidar; lower accuracy allows use of IfSAR and satellite archive data.
The Spatial Analysis Group at the University of Southern Queensland (Australia) has summarized key
requirements (vertical accuracy) for a variety of applications as shown in Table 1. The applications have been
grouped in ascending order of accuracy requirements.
Operational Guide to Tender a Digital Elevation Model 21
Table 1. Key accuracy requirements for a range of application areas.
Grouping Application Area Accuracy
Very High Farm layout redesign – cultivation 0.05–0.5m
<0.5m Hydrological modeling (incl. floodplain) <0.5m
Land and water management plans <0.5m
Insurance risk and assessment <0.5m
High Disaster response 0.5–1m
0.5–1.0m Infrastructure planning and risk assessment 0.5–1m
Water management plans 0.5–1m
Cross slope/batter analysis <1m
Planning scheme/development assessment +/– 1m
Transport corridor planning +/– 1m
Soil erosion control and modeling +/– 1m
Bio-security—disease spread, spray drift +/– 1m
Disaster planning and management (except flood) +/– 1m
Medium Riparian management +/–1–2m
1.0–5.0m Risk management +/–1–2m
Noise studies/assessment—corridor planning +/– 1–2m
Telecommunications planning, visibility analysis 1–5m
Salinity prediction and control +/– 5m
Low Visibility analysis — tourism 5–10m
5.0–10.0m Environmental impact assessment and management +/– 5–10m
Natural resource management 5–10m
Very Low >10m Tourism 20m
Source: Courtesy of the Spatial Analysis Group at the University of Southern Queensland, Australia.
Spatial Resolution (ground sample distance or point spacing)
Spatial (horizontal) resolution is driven by the level of detail and point spacing in the model desired by the
user. The value should be less than the size of the smallest terrain features the user desires to be represented.
For instance if buildings are to be captured, the point spacing should be smaller than the dimensions of the
smallest buildings in the area of interest. Spatial resolution can be characterized as high (<1m), medium (1m to
5m), or low (>5m). Higher resolution is generally needed for areas with rapid changes in elevation, such as steep
terrain or urban areas, while smooth terrain can be suitably covered at lower resolution. Photogrammetric or
Lidar systems are best for higher resolution applications on the order of <1.0m. Medium or lower accuracy
applications allow use of IfSAR, on the order of 1m to 5m, and satellite archive data.
Coverage Location/Area
Coverage extent, accuracy and resolution are typically the largest drivers of project cost and schedule. Study
location drives deployment costs for aircraft and field support, and can be a major cost factor for custom
collections. Inaccessible terrain can make ground control difficult and reduce the attainable accuracy. The
extent of the area is an obvious cost factor, especially for aircraft collections, with costs quoted on an area basis
(e.g. $/km2). Due to the vagaries of large-scale projects, providers of aerial data tend to require longer schedules
to reduce risk. In contrast, archived satellite data, provided it has the needed resolution and accuracy, has the
22 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
lowest schedule risk for large area projects. From a cost perspective, custom airborne photogrammetric or
Lidar are good for smaller areas. IfSAR and satellite archive data are best for large areas if accuracy and
resolution permit.
Weather Constraints
Some areas of the world have significant seasonal weather activity that may render some modalities
ineffective—especially photogrammetry and Lidar—and limit the time window for data collection. IfSAR is
essentially immune to weather, making that modality attractive for areas that are chronically cloud covered. Smoke
is a special case that may be encountered in disaster response applications. Smoke obscuration is problematic for
photographic systems and to a certain extent Lidar, but the operating wavelengths of IfSAR systems are immune
to smoke effects. Heavy haze encountered in some developing urban areas may also present a challenge to
photographic approaches, but can be overcome by Lidar and IfSAR. IfSAR is best for chronically cloudy or foggy
areas, and good for haze conditions and smoke environments. Lidar is also good for heavy haze conditions.
Timeline Constraints
Product delivery timelines, if specified, can impact the options available to the program manager. Products with
the shortest timeline will be those available from archives, though that data may not satisfy requirements of
accuracy, coverage, or temporally relevant scene content. Tight timelines may result in higher procurement costs.
Use of archive data has the shortest timeline if product quality is acceptable.
Foliage Constraints
Foliage can obscure the ground from above, preventing accurate determination of a bare-earth DEM, especially
for photogrammetric methods. Lidar sensors are capable of foliage penetration provided the point density
(spatial resolution) is sufficiently high (small spacing) to get enough pulses between the leaves to the ground.
This will typically require closer flight line spacings, with a consequently higher operational cost. Most
common IfSAR products are based on higher frequency systems such as X-band and thus have poor vegetation
penetration. However, longer wavelength IfSAR, especially P-band, has excellent foliage penetration capability.
Photogrammetry is poor for determination of a bare-earth DEM under heavy foliage. Lidar can be acceptable
with sufficiently high point density. Longer wavelength IfSAR (P-band) has good foliage penetration.
Urban Buildings and Steep Terrain Constraints
Steep terrain, buildings, and other tall structures can create gaps in coverage due to shadowing of Lidar or
IfSAR sensors. This can be overcome for Lidar (and photogrammetry) by closer spacing of flight lines, with
consequently higher operational costs. IfSAR can be more difficult as the system is less flexible. IfSAR is less
suitable for tall urban structures or very steep terrain. Photogrammetry and Lidar can be used with more closely
spaced flight lines.
Budget Constraints
Budget limitations can pose a major constraint on what acceptable options are available for a given project.
Costs for archive data are generally lower on an area basis (cost/km2). The lower cost is usually accompanied by
strict limitations on data use, as the archive owner typically retains ownership of the data and provides a limited
use license to the project. Costs for specific applications may vary significantly, in particular for those requiring
custom data collections. For example, the mobilization costs associated with deployment of a vendor’s aircraft
and equipment to the study area may add €10,000–50,000 (approximately US$13,000–67,000) to the contract
cost depending on distance travelled. The most predictable costs come from archived satellite data sources such
as Digital Globe and Astrium, which have well-established catalog prices. Table 2 presents generalized data on
DEM costs for various vendors and remote sensing modalities.
Operational Guide to Tender a Digital Elevation Model 23
Table 2. DEM product costs for various remote sensing modalities and vendors
Vertical Price $/km2
Vendor DEM Product Accuracy (approx.) Licensing
Various Photogrammetry (Air) 0.25–0.3m $440 User owned
Various Lidar (Air) 0.15–0.3m $180 User owned
Fugro IfSAR Dual X/P Band (Air) 2–5m $80 User owned
DigitalGlobe Photogrammetry (Space) 4m $32 Limited license
Astrium IfSAR “Elevation10 Package” (Space) 5–10m $50 Limited license
IfSAR and space photogrammetry are generally much less expensive but with less vertical accuracy. Archive data
is lowest cost but usually has limited rights for dissemination. Custom airborne photogrammetry and Lidar are
the most expensive but provide the best accuracy and least dissemination restrictions.
Suitability Matrix
To assist decision makers in defining an appropriate remote sensing response for various applications, Table 3 shows
a “Suitability Matrix” which compares the various data acquisition options for a manager to a range of requirements.
Table 3. A suitability matrix that can be used to map a remote sensing modality to different project environments,
time scales, resolution requirements, and cost
Modality Method Source
Photo Lidar IfSAR Air Space Custom Archive Comments
Accuracy
Very/High X X X X High accuracy is best achieved by low flying
Accuracy aircraft with Lidar or photographic sensors.
< 1.0 m Archives tend to have lower accuracy data
compared to custom collects.
Medium X X X X Available from aircraft and some high
Accuracy performance satellite systems. Archives
1.0 to 5.0 m may have contain this quality.
Very/Low X X X Suitable satellite archive info is available for
Accuracy most areas of the world.
> 5.0 m
Spatial Resolution
High X X X X High resolution is best achieved by low
Resolution flying aircraft with lidar or photo sensors.
< 1.0 m
Medium X X X X Airborne IfSAR data can compete effectively
Resolution with photo and Lidar in this domain.
1.0 to 5.0 m
Low X X X Space IfSAR is excellent for low resolution
Resolution DEMs, satellite sensors are a great source
> 5.0 m of low resolution data at reasonable cost.
(continued on next page)
24 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Table 3. A suitability matrix that can be used to map a remote sensing modality to different project environments,
time scales, resolution requirements, and cost (continued)
Modality Method Source
Photo Lidar IfSAR Air Space Custom Archive Comments
Coverage Area
Local X X X X Aircraft are best suited for local scale
collection. Archive data may be available
but pricing is most atractive for larger areas.
Regional X X X X Aircraft are good, satellites are best.
Archive data may be best value if accuracy
and resolution permit.
Operational Issues/ Constraints
Fog/Clouds X X Sometimes aircraft can fly beneath
cloud cover but lighting will be poor for
photography. Lidar and IfSAR can work
in poor lighting conditions. IfSAR can
penetrate clouds if required.
Heavy X X X X Airborne lidar is suitable at higher point
Foliage density and foliage density permits. Low
frequency (P-Band) airborne IfSAR is
generally good for bare earth DEMs in
heavily forested areas.
Urban X X X X Photogrammetry is best, Lidar is adequate
with close flight line spacing. IfSAR can
be problematic due to “shadowing” by
structures.
Timeline
Hrs – Days X X X X Usually for disaster response, must
consider timeline deployment and data
processing. Archives likely will not have
current data. Costs may be higher for faster
production.
Days – X X X X X Photogrammetry and Lidar have well
Weeks developed processing workflows. Relaxed
accuracy requirements can reduce schedule.
Weeks – X X X X X X X Allows for more options including custom
Months collects and archive data. Allows maximum
flexibility for providers which will reduce cost.
Budget Availability
Low Cost X X X X Use of archive-based space products (IfSAR
or photo) are least expensive but usually
have licensing restrictions which limit
dissemination.
Medium X X X X X Lidar is more competitive at this level.
Cost Some custom collects may be cost
effective. Custom collects have least
dissemination restrictions.
High Cost X X X X X Custom airborne collects are most
expensive, dissemination least restrictive.
Operational Guide to Tender a Digital Elevation Model 25
Application Requirements Matrix
The selection of appropriate options for a given application is a process of weighing the various requirements
and constraints against the capabilities offered by different modalities, methods, and sources. Six application
areas have been selected as examples: 1) Disaster Response; 2) Hydrological and Floodplain Mapping; 3) Land
Use Mapping; 4) Urban Modeling; 5) Transportation Infrastructure Analysis; and 6) Bathymetry. Table 4
shows a “Requirements Matrix” that compares the example application areas with requirements for technical
performance and common operational constraints associated with those applications.
Table 4. A requirements matrix that maps specific applications to required DEM characteristics in terms of seven
common operational constraints.
Penetration
Application
Resolution
Timeliness
Comments
Coverage
Accuracy
Visibility
Location
Weather
Terrain/
Vertical
and Size
Foliage
Spatial
Urban
Steep
Disaster
Flood High High Local Hours – Clouds No Buildings Quickly unfolding event usually
Days if urban associated with clouds and rain,
area may continue for several days. Lidar
and IfSAR not normally able to
Earthquake Low High Local Hours – No Buildings Sudden event with response over
Days days and weeks. Impact on built-
up urban areas most
Fire Low High Local Hours – Smoke Yes Steep Rapidly developing, short lived
Days terrain events, smokey conditions and
often undeveloped steep terrain
Hydrological High Medium Regional Weeks – Yes Steep High accuracy bare earth data
and Floodplain Months terrain is essential especially for flood
Mapping in some plain and flood risk analysis.
areas This is particularly important in
flat terrain. Usually a long term
analysis (months),
Land Use Low Low Regional Weeks – No Includes classification of vegetation
Mapping Months and built environments. Interest in
vegetation means leaf-on conditions
which makes DEM extraction more
difficult. However DEM is not as
important in this application.
Urban High High Local Weeks – Haze No Buildings
Modeling Months
Transportation Medium Medium Local Weeks – No
Months
Bathymetry High Medium Regional Weeks – No Requires water penetration using
Months photo or specially selected lidar
wavelengths, IfSAR is not suitable.
26 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
03
Chapter
How DEMs are
Generated:
Data Acquisition and
Mission Planning,
Development of
Requirements and
Product Attributes
of DEMs
Planning for acquisition of digital elevation data begins with good definition of application needs and
requirements. These can in turn be distilled into the specific technical, cost, and schedule requirements forming
the basis for Terms of Reference (ToR). Some example ToRs are included in Appendix A. These ToRs can be used
as the basis for any procurement process; however, a DEM specialist must be consulted in finalizing the ToRs.
In this section, key requirements for DEM products and how to specify them is elaborated. Requirements for a
DEM project are derived from the end use application and are stated in the terms of verifiable product attributes
and quality parameters that can be presented in a vendor specification.
Key Attributes for DEMs
Certain key attributes can be used to define DEM products for a project and to generate a Request for Proposal
(RFP) and Statement of Work (SoW) for product vendors. These attributes, subsequently discussed in greater
detail include:5
• Project Area – size and shape of project area
• Digital Surface Type – bare-earth or top surface including structures and vegetation, etc.
• Model Type – point cloud, grid, contour lines, surface
27
5 These attributes have been captured in a metadata “menu” form in Annex B. Menu originally presented in Digital Elevation Model Technologies and
Applications: The DEM Users Manual, 2nd Edition published in 2007 by the American Society for Photogrammetry and Remote Sensing (ASPRS, 2007).
28 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
• Source – Lidar, IfSAR, photogrammetry
• Point spacing – defines the 2D spacing interval at which ground elevation data are collected
• Accuracy – vertical and horizontal
• Surface Treatment – classification of areas such as bare earth, buildings, vegetation.
• Artifacts - small artificial anomalies or imperfections in the data
• Datum – reference Earth surface for vertical and horizontal measurement, e.g., WGS 84
• Geoid model – the base spherical reference surface used by GPS
• Coordinate Systems – UTM, geographic (Latitude/Longitude), or local defined coordinate
• Units – metric or English units, also specify number of decimal places
• Output Data Format – data file type needed by user, such as shapefile (*.shp) or ASCII text (*.txt)
• File Size – desired size in terms of memory (MBs) or spatial extent (e.g. square kilometer–km2)
• Metadata – Any required ancillary data, e.g., U.S. Federal Geographic Data Committee (FGDC) standard
Project Area
Location. Establishing location(s) and jurisdiction(s) of the project area is a major consideration, especially if a
custom data collection is needed. This is very important for aerial operations where costs are impacted by vendor
travel distance to the area (mobilization costs), access to ground facilities in-country, airspace operations and
restrictions, and local weather.
Extent. The size and shape of the project area is a major cost driver. Care should be taken to ensure the extent
covers any “buffer” needed to provide adequate coverage of watershed boundaries or overlaps needed with pre-
existing datasets. The shape of the area can be a factor in airborne acquisition costs, as collection flight time is more
efficient for rectangular areas (long flight lines with fewer turns) than for highly irregular shapes (short flight lines
with many turns). Airborne system vendors can assist in determining the most efficient area layout. The extent of
the study area is usually documented by means of an Environmental Systems Research Institute (ESRI) shapefile.
Digital Surface Data Type
DEM. DEM products are digital representations of earth’s surface normally using a uniform grid or pixel spacing.
Digital Terrain Models (DTM) are a more refined version of a DEM where additional processing is used to more
accurately represent the bare earth without the artifacts on the surface). Sometimes, DTM is used synonymously
with DEM but if a specific choice between DEM and DTM is available, selecting a DTM will provide better results
if the requirement is to capture the bare-earth topography.
DSM. In addition to Earth surface information, custom Lidar surveys inherently collect non-Earth surface
vertical information such as the tops of man-made structures and vegetation. This can be used to generate a
Digital Surface Model (DSM), which has value for a variety of applications. If a project assumes the expense of
a custom data collection for a bare-earth DEM (DTM), it is a small incremental cost to also include a DSM as a
project deliverable that can be used for applications such as extracting the buildings, vegetation, or any other
artifacts above the earth’s surface.
DEM Model Types
Grid. A gridded DEM or DSM is usually a digital contiguous surface on a regular grid interpolated from elevation
measurements made at discrete points. Gridded DEMs and DSMs are represented as image type data sets where
Data Acquisition and Mission Planning, Development of Requirements and Product Attributes of DEMs 29
the pixel values correspond to elevation. They are efficient for visualization and can be integrated into a large
number of applications. However, they may have errors due to the gridding and interpolation process. Gridded
DEMs are generally accurate enough for bare-earth models but are not sufficiently accurate for representing
precise features such as streamlines, buildings, or roadcuts.
TIN. A Triangular Irregular Network (TIN) is a surface made up of non-overlapping triangles connecting
irregularly spaced measurement points, and are represented as vector data structures. TINs are often used as
the basis for producing gridded DEMs, hence they have a higher level of vertical accuracy. TINs are preferable to
a DEM when it is critical to preserve the location of narrow or small surface features such as ditches or stream
centerlines, levees, or isolated peaks and pits.
Breaklines are linear features incorporated into a TIN that represent changes in continuity of a surface such
as streams, shorelines, ridges, and structures that may not be apparent in an interpolated grid DEM. They are
enforced as edges in the triangulation.
Point Cloud/Mass Point. Data can also be acquired as Point Clouds or Mass Points which are simply points,
often irregularly spaced, that represent raw 3D measurement samples. These are commonly available, for
example, from Lidar data sets. As such, additional processing is required to render a DSM or DEM. These are not
recommended as outputs to be delivered from the vendor except for more sophisticated users.
Source
DEM data can be generated from four primary sources: existing maps, Lidar, radar, and photogrammetry (see
Technical Annex). As long as a DEM product meets the user’s information requirements, the actual source is
somewhat irrelevant to the project manager and need not be specified. However, if procuring a custom DEM, the
specification of a source may determine what other additional information products may be derived. All sources,
however, can collect point data only at a specified spacing interval.
Point Spacing and Ground Sample Distance
Point Spacing
The horizontal spacing of data points for a model, the average spacing for a TIN, and fixed spacing for grids
is derived from the level of detail desired by the user and constrained by the horizontal resolution of the data
collection. The average point spacing of irregularly spaced mass points (from Lidar for example) or of uniformly
spaced grid points is referred to as the “horizontal resolution” of the elevation model. Grid spacing is also
tied to the vertical accuracy of the data. Vertical accuracy requirements will drive the minimum horizontal
resolution requirement that in turn drives grid spacing (see subsequent sections on horizontal resolution and
vertical accuracy).
The data density at which an elevation product is captured and modeled (usually expressed as “points
per sq. meter”) will determine how well terrain features are represented and how accurately the dataset
represents the terrain. Point density is related to horizontal resolution. For example 5 points per square meter
will enable a horizontal resolution of about 30 cm. The specified horizontal resolution should be chosen
carefully, however, because it can have a significant effect on production cost and on data handling efficiency.
Point spacing should also be considered in light of the “horizontal resolution requirement” for the data
collection system.
30 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Horizontal Resolution for Feature Detection and Representation
The ”ground-sample distance” (GSD) is the density at which Lidar or IfSAR systems sample elevations
during collection. The GSD specified for a collection system should be less than the minimum size of and
distance between terrain features to be detected. Likewise, the horizontal spacing for the final product(s)
should be chosen to most efficiently represent the size and frequency of terrain features to be modeled. For
example, characterizing rough or dissected terrain may require collection at a 1m ground-sample distance and
generation of 1m DEMs, while gentle relief may be adequately collected with a 6m GSD and modeled with a 10m
grid spacing.
When deriving a DEM from mass points or TINs, the mass points are normally collected at a higher GSD than
the final resolution specified for the DEM. This approach provides multiple surrounding points for interpolation
of DEM elevation posts. For example, to derive a DEM with uniform post spacing of 5m, it is common for Lidar
dataset mass points to have average post spacings of approximately 3m. This results in an initial denser dataset
from which some points will be removed as a result of post-processing, which eliminates points on manmade
structures or dense vegetation.
Accuracy
Vertical Accuracy
Vertical accuracy is the principal metric of quality for DEM products. Accuracy requirements are a strong
function of the end application. Applications with demanding vertical accuracy requirements include those areas
where small variations in elevation can result in large variations in results. Examples include:
• Marine navigation and safety
• Storm water and floodplain management in relatively flat terrain
• Management of ecologically sensitive areas, e.g., wetlands in flat terrain
• Infrastructure management in dense urban areas
Table 5. U.S. National Map Accuracy Standards The project manager must ascertain the accuracy
(NMAS) contour interval map standards requirements for the finished DEM and be careful
and U.S. National Standard for Spatial not to settle for meeting that requirement at a
Data Accuracy (NSSDA) vertical accuracy lower level of processing. For example, the points
requirement. in a Lidar point cloud may meet a given vertical
accuracy requirement but the DEM surface derived
NSSDA Accuracy
from that point cloud may have greater errors due to
NMAS Contour Requirement, 95%
Interval (m) confidence (m) interpolation and smoothing.
0.3 0.182
As a guideline, the U.S. National Standard for
0.6 0.363
Spatial Data Accuracy (NSSDA) vertical accuracy
1.2 0.726
requirement can be correlated to contour interval
1.5 0.908
map standards from the map-based U.S. National
3.0 1.816
Map Accuracy Standards (NMAS)6 as presented in
6.0 3.632 Table 5.
Source: NMAS and NSSDA.
6 DEM Users guide page 458.
Data Acquisition and Mission Planning, Development of Requirements and Product Attributes of DEMs 31
Vertical Accuracy and Table 6. Map scale and contour intervals.
Horizontal Resolution7 Map Contour Equivalent Post
The vertical accuracy of mass points, TINs, or DEMs scale Interval (m) Spacing (m)
is a function of the horizontal resolution of the 1:1,200 0.3 1
digital topographic data. There are no established
1:2,400 0.6 2
rules that directly correlate the horizontal resolution
1:6,000 1.5 5
of digital elevation data with vertical accuracy,
1:12,000 3.0 10
but there is general agreement that TINs/DEMs
1:24,000 6.0 20
equivalent to 0.3m contours should have narrower
post spacing than TINs/DEMs equivalent to 0.6m Source: NSSDA.
contours, for example. Cartographers typically
associate map scale with contour intervals and DEM Table 7. Horizontal accuracy guidelines.
postings as shown in Table 6.
NSSDA Accuracy Requirement,
Map scale 95% confidence (m)
From these correlations, it can be seen that it
1:1,200 1.159
normally makes little sense to generate a DEM with
1:2,400 2.318
a vertical accuracy equivalent to 1m contours if
the DEM post spacing is 10m. However, there may 1:4,800 4.635
be exceptions if the DEM is supplemented with 1:6,000 5.794
breaklines. Normally, when breaklines are generated 1:12,000 11.588
by alternative means to supplement the DEM data, 1:24,000 13.906
then the average DEM post-spacing may be relaxed. Source: NSSDA.
For example, for the equivalent of 0.6m contours,
FEMA considers a 2m DEM post spacing to be
appropriate if there are no supplemental breaklines. However, 5m post-spacing is adequate if limited breaklines
exist, e.g., along shorelines and at the tops and bottoms of a stream bank; such a DEM can be used in the
hydraulic modeling of floodplains with associated breaklines.
Horizontal Accuracy
Horizontal accuracy is largely controlled by the vertical accuracy requirement (high vertical accuracy requires
high horizontal accuracy). The U.S. NSSDA also has generated guidelines related to map scale, where larger
scales, e.g., 1:1,200, require a higher accuracy than smaller scales, e.g., 1:24,000, due to the relative impact of the
accuracy specification at the given scale (table 7).
Surface Treatments
Here the project must specify what features should be identified in the deliverable product in addition to the
DEM or DSM. Special items include:
• Vegetation – classification of areas where dense vegetation prevents direct measurement of ground surface
• Hydrologic enforcement – additional processing to ensure accurate representation of hydrological features such
as shorelines and streams
• Buildings – interpolation of ground surface that is “occupied” by a building or other man-made structure
7 NDEP page 17.
32 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
• No-data areas – also known as “voids;” areas where there is no elevation data due to lack of Lidar returns such
as over water, dark asphalt, or navigation errors must be clearly identified
• Suspect areas – areas of low confidence in elevation accuracy such as in heavily vegetated areas or sparse
collection of points
Artifacts
Artifacts are small artificial anomalies in the data resulting from processing techniques or the data collection
system. These are difficult to specify and are usually best defined through discussion with the vendor.
Horizontal and Vertical Datum
Horizontal and vertical data are stated in reference to established “datums”—the starting point for calculation
of other measurements. The datum of choice is usually specified by the using agency. Like coordinate systems,
datums may be specified by different users, based on the study area. For example, the standard vertical datum for
U.S. mapping is the North American Vertical Datum of 1988 (NAVD88). Other countries may use a local datum
such as Maputo, which is a vertical datum first defined in Mozambique where the origin is mean sea level at
Maputo. Other reference frames include the International Terrestrial Reference Frame (ITRF).
Geoid Model
Geoid is a model of global mean sea level that is used to measure precise surface elevations.7 Geoid models
are used to correct “ellipsoid heights” (measured by GPS systems relative to a standard reference ellipsoid) to
local “orthometric heights” relative to local mean sea level. The geoid model is simply the difference between
the two heights. It is important that the latest geoid model for the study area is used for all surveys that involve
GPS, including airborne GPS surveys from Lidar and IfSAR. It is also important that the metadata for any digital
elevation dataset include the geoid model that was used.
Coordinate Systems
The coordinate system of choice is usually determined by user preference. Typical choices are Universal
Transverse Mercator (UTM), geographic (latitude, longitude), or a local/regional coordinate system. Many
mapping software programs readily convert from one coordinate system to another, but there may be some
errors introduced by interpolation when doing so.
Units
Both horizontal and vertical units need to be specified realistically. The project should not specify a higher
number of decimal places than is achievable by the technology or that is of value to the user. The number of
decimal places (regarding the unit level of analysis) also drives cost, time for calibration, and processing, as well
as the size of the product files. However, too few decimal places (too large a unit) will result in the appearance
8 NOAA: http://oceanservice.noaa.gov/facts/geoid.html
Data Acquisition and Mission Planning, Development of Requirements and Product Attributes of DEMs 33
of “plateaus” in the DEM. One decimal place (0.1m; Table 8. DEM formats (raster or grid).
10 of a meter) typically is adequate for most
th
Vector Mass Points, Point Gridded DEMs,
applications. However, in floodplain mapping the
data Clouds, TINs DSMs
user could specify centimeter level (0.01m; 100th of
.DGN ACSII x/y/z ASCII x/y/z
a meter), since a 0.1m difference in elevation could
.DLG ASCII w/attribute data .BIL
have a distinct impact on local drainage patterns.
.DWG BIN .BIP
.DXF .LAS .DEM (USGS standard)
Output Data Format .E00 TIN (ArcInfo Export File) DTED
.MIF / .MID ESRI Float Grid
Output DEM data can be provided in a variety of .SHP ESRI Integer Grid
formats. The project should specify the format that STDS GeoTiff
is compatible with the analysis tool set used by the VPF .IMG (ERDAS)
client state. It is also relatively straightforward to
ENVI
convert DEM data between two data formats or
.RLE
software suites. A myriad of DEM (raster or grid)
formats exist as presented in Table 8.
File Size and IT Requirements
The project should specify product file sizes that are manageable by the user agency in terms of the ability to
transfer and store the data, as well as the ability of the user’s analysis software to manipulate the data. Examples
of limiting factors include desktop computing power and capacity, storage/media capacity, file transfer rates,
file display and manipulation, and maintenance efficiency. For large projects, the data may be broken up into
“tiles” that are defined by bounding x,y coordinates. File sizes are generally limited to 1 gigabyte (GB). In some
cases, users may define tile sizes in terms of geographic extent, e.g. 5×5km, while 1×1km tiles are often used for
smaller projects.
Organizations planning to host DEM project data should be prepared to securely support multiple terabytes
(TB) of archive data, preferably using a fault tolerant array of independent disk devices (RAID), that provides
data redundancy and performance improvement. Files can be transferred from the archive to users via a digital
network (internet) or portable media such as CDs, DVDs, or portable hard drives.
For external distribution, portable hard drives offer the best combination of read/write speed and data
capacity. 1TB capacity portable drives are routinely available for less than US$100. One such drive can usually
accommodate an entire DEM project. CDs and DVDs have limited capacity and have limited capabilities for
multiple read/write cycles. Portable hard drives are highly re-useable, offering essentially unlimited read/write.
High speed internal local area networks (LAN) are important for moving files between computers and storage
devices internal to an organization, as well as having the capacity to move data from the archive out onto the
external (internet) network. Network equipment supporting 100 Mbit/sec to 1 Gbit/sec is routinely available.
Metadata
Metadata, or “data about data,” forms an essential component of a useful DEM data set. The user must be able
to quickly assess a DEM’s origins and characteristics (e.g., vendor, data collection date, location, sensor detail,
34 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
date of DEM creation, processing steps, accuracy parameters) to make sure the DEM fits with the data needs
and specifications, and meets archival and dissemination purposes. Metadata forms, which vary by vendor and
user needs, provide this essential information. A sample form, originally presented in “Digital Elevation Model
Technologies and Applications: The DEM User’s Manual” (2nd Edition; American Society for Photogrammetry
and Remote Sensing; 2007), is presented in Annex B. World Bank has a spatial data metadata standard which is
presented in Annex C.
DEM Acquisition: The Terms of Reference
The Terms of Reference (ToR)8 serves as the common point of reference between the project manager and the
vendor. The ToR provides guidelines and the framework for a DEM project; the vendor will submit a technical and
financial proposal based upon the specifications detailed in the ToR. The ToR is an extremely important document
requiring careful specificity by the project manager, as a vendor is only responsible for what is contained in the
ToR and technical and financial proposal. If the project manager should decide to alter or add to the vendor’s
requirements after a ToR agreement is established, there is significant risk of a price increase or slip in schedule.
Overview
The Overview section of the ToR includes a general description of the project background, scope, and project
area. It includes a statement of applicable standards and specifications, as determined by the contracting
agency(ies), and identifies any significant restrictions or special considerations for project implementation.
Technical Requirements
This section of the ToR includes details on the technical specifications of the DEM, such as:
• Describe DEM postings and vertical accuracy
• Data type and format
• Special post processing (e.g., breaklines, hydro enforcement, and others)
• Data quality (voids, overlap offsets, or other areas)
• Acquisition date range
Quality Assurance
The quality of delivered products should be assessed and documented by the vendor and, if desired, by an
independent party. For all custom surveys, the contractor should conduct an independent accuracy test to
verify (i) that fundamental accuracy specifications have been met and, (ii) to provide information on the
supplementary accuracy—and therefore reliability—of the elevation data in various land cover categories. This
effort should be documented in the “Quality Assurance Report,” which is an important component of project
deliverables as described below.
9 In some cases, the term Statement of Work (SoW) is used. For ease of reference, ToR is used throughout the Guidance Note.
Data Acquisition and Mission Planning, Development of Requirements and Product Attributes of DEMs 35
Maintaining internal staff resources capable of Quality Assurance (QA) for a DEM project may not be cost
effective unless there is a steady stream of projects requiring their services. Use of a reputable DEM vendor can
alleviate the need to hire an independent third party and should be a factor in competitive cost analysis. Any
savings from hiring a low-cost vendor without a well-established reputation for quality may be offset by the
need to subsequently commission a third party QA assessment. Another viable approach is to hire a third party
to evaluate the vendor’s QA assessment, which should be a lower cost than having that third party conduct the
assessment itself.
Metadata
A metadata record is a file of information, usually presented as an XML document, which captures the basic
characteristics of a data or information resource. ISO 19115–1:2014 is an international standard that defines
the schema required for describing geographic information and services by means of metadata. It provides
information about the identification, the extent, the quality, the spatial and temporal aspects, the content, the
spatial reference, the portrayal, distribution, and other properties of digital geographic data and services.
Specifically for a DEM collection, the metadata should include a full description of the collection flight
parameters including flight lines and flight dates/times. Product descriptors should include datums, projections,
processing steps, field notes, and positional accuracy.
Deliverables
Deliverables should be well-defined, verifiable, and clearly stated within the Terms of Reference as well
as the technical proposal. As with the ToR, the technical proposal document is extremely important as a
communication tool between the project manager and the data provider. Ultimately, the deliverables depend on
the technical proposal, including custom collection or derivation from archived data. Deliverables for a custom
data collection are presented here as it represents the most complex option. Deliverables for an archive-based
DEM would be a subset of those included here. In general, deliverables for a DEM project can be grouped into
three categories: i) pre-project deliverables; ii) post-project deliverables; and iii) maps products and other
derived products.
Pre-Project Deliverables
Pre-project deliverables should be provided by the vendor as part of their proposal or shortly after contract
award. The main objective is to avoid unpleasant surprises later during the project by ensuring that the
vendor understands the project requirements and how to meet them. Pre-project deliverables also offer
project managers early indications of inconsistencies or other issues with the requirements provided by the
contracting party to the vendor. Finally, experience recommends that vendors present a pre-project summary
by teleconference or in-person to review plans and specifications as documented, to further ensure complete
understanding by both parties. Pre-project deliverables should include:
• Map of the collection area showing study area boundaries, coverage area, planned flight lines and coverage
swath. The maps should be provided in the coordinate system of the end user.
• Shaded relief composite mosaic of all mapping swaths to show any possible gaps in coverage due to:
• Layover (SAR)
• Shadowing (SAR or Lidar)
36 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
• Indeterminate phase unwrapping (SAR)
• Terrain elevation relative to flying height
• Table of estimated amount and type of data voids
• Airborne collection specifications including altitude, airspeed, heading, start and end location, flight time, flight
equipment information (SAR, Lidar, photo), and tolerance specifications for line or mission abort.
• Quality Assurance Plan that conforms to an identified management system and generally complies with
ISO 9001. The plan must address the organization and management of the project, work procedures,
environmental considerations, safety and risk control, and test procedures. The Quality Assurance Plan must
detail the procedures to be used in verifying that the deliverables meet the required specification including
specification of ground control.
• Schedule including flight dates and times, processing schedule, and data delivery dates.
Post-Project Deliverables
The technical details of a post-project report may seem daunting to a project manager, but it serves to signal the
vendor that you are paying close attention to the quality of the collection, aids in third-party quality assessment
or troubleshooting, and provides a comparative point of reference for results from different missions. Post-
project deliverables should include:
• Post-Flight Report details executed data collection performance as compared to the plan, and pertinent
information on factors (e.g., weather conditions, target area surface conditions) that may impact the quality
or information content of the collected data. Other report items include: mission date and times, altitudes,
airspeed, heading, start and end points of each line, look angles, instrument operating modes, GPS/INS data,
and comparison of actual parameters to tolerances.
• Ground Control Report includes all pertinent base station information and mission notes, including
information on GPS station monument names and stability.
• Data Processing Report summarizing data processing parameters and identifies any anomalies.
• Quality Assurance Report includes detailed information on systems to be used in the survey, including all
equipment details and relevant calibration certifications provided by the manufacturer prior to the survey.
QA documentation should also include operational information to be captured during the survey (e.g.,
mission date, time, flight altitude, sensor sampling configurations), maps of survey coverage and boundary
overlaps, flight plans, and any other pertinent survey information. It should also include the methodology for
determining accuracy and an independent accuracy test.
• Quality Checking Documentation. For all custom surveys the contractor is required to carry out an
independent accuracy test to verify that fundamental accuracy specifications have been met and to provide
information on the supplemental accuracy, and therefore reliability, of the elevation data in various land
cover categories.
Map Products
Map products and their derived data are the primary deliverable for the user and should be clearly specified so
they meet the user’s needs in a form compatible with the user’s tools and constraints. The ultimate user should
be closely consulted with regard to:
• Data types and formats (points, TIN, vectors, etc., coordinate system and datums, data precision)
• Tile sizes, metadata format, user specific software formats (e.g. Shapefile)
• Delivery method (FTP, hard drive, USB drive, etc.)
• Licensing
Data Acquisition and Mission Planning, Development of Requirements and Product Attributes of DEMs 37
Costing Factors and Approximations
Contractor pricing for DEM products is driven by direct operating costs and capital costs. Procurement of high
quality topographic sensors such as Lidar may cost a contractor US$800,000 to over US$2 million, typically
amortized over a five-year life.9
Operating costs are a strong function of project parameters and include travel expenses, aircraft operations,
equipment maintenance, and labor associated with instrument operations and data processing. Key elements of
operational cost are:
• Deployment (aircraft hourly rate10 x round trip flight hours from base to project site)
• Flight operations (aircraft hourly rate x estimated number of flight hours11)
• Instrument operations (instrument hourly rate12 x number of flight hours)
• Data processing (processing hourly rate13 x number of processing hours14)
• Contactors may add a separate line item for overhead costs as a fraction of total direct costs or may have their
overhead factored into each individual line item.
Project Pricing
• Lidar. DEM product cost/km2 is approximately US$120-$200.
• IfSAR (Table 9):
• Project-specific IfSAR
• DEM product costs range from US$30/km2 to US$100/km2 depending on location, area size, terrain,
foliage, and extracted vector data
• Archival (warehouse) IfSAR
• Depends on whether existing processed data can be used or reprocessing is required. A project
essentially buys a limited-use license to use the archived data from the vendor. DEM cost ranges from
US$11/km2 to US$25/km2 and US$7/km2 for IfSAR images.
• Photogrammetry (stereo aerial photography):
• Approximate DEM product cost/km2 is US$30.
Table 9. A general pricing structure for archival IfSAR data.
Post Spacing (m) Vertical RMSE (m) DEM US$/km2 DEM & Image US$/km2
5 1.0 $20–$100 $23–$110
10 1.5–2.0 $12–$55 $14–$60
10 2.0–3.0 $10–$45 $12–$50
10 DEM Users Guide page 238.
11 Includes aircraft operational cost (fuel, maintenance, etc.) + flight crew; often quoted as a composite hourly rate.
12 Strong function of project area size and shape, accuracy, resolution, terrain, air traffic control, etc.
13 Amortized depreciation and maintenance.
14 Strong function of level of processing desired.
15 Typically quoted as a factor X instrument operational time, e.g. two hours processing per operational hour.
38 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
04
Chapter
Data Sharing
and Dissemination
Once DEM products are generated, they must be delivered in formats that are useful and accessible to the
end-users and licensed such that they may be shared with other parties as deemed necessary by the end-user
organization. Factors that impact data dissemination include data format, data compression formats, the size of
data files, and data licensing.
Data and Data Compression Formats
Formats for DEM data products are fairly well-established and can be accommodated by most commonly
available DEM analysis software tools. However, it is prudent to check with the end-user organization to
determine what tools are in use at their site to ensure that the vendor delivers the DEM products consistent with
those capabilities. A summary of common data formats used for DEM products can be found in Table 8.
Once the data products are produced in the desired format, they are often “compressed” to reduce the amount
of storage required and to speed up the transmission of the data over the internet. Using “open source” tools
for data compression will ensure maximum accessibility for the end-user and further dissemination. Most DEM
analysis tools have the ability to open files compressed in open source, public domain formats such as JPEG or
ECW, but some compression tools such as MrSid are proprietary and require the user to pay for an additional
license. Even if the end-user has a license for proprietary compression tools, further dissemination from the end-
user to other constituents, through an internet portal for example, may be hindered.
File Size
DEM product file sizes can be large. Care must be taken to ensure that file sizes are compatible with the network,
storage, and computing resources of the end-user.
Public Domain vs. Restricted Access
Openly available, high quality elevation data is of high value to communities in developed and developing
nations. However, some nations have a stricter view than others about what can be shared, especially if the
data reveals information related to national security (or is perceived as such). There may be a desire to limit
the use of data to non-commercial applications so that a user may realize some revenue for issuing licenses to
commercial entities.
39
40 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Licensing Considerations
Licensing is a strong function of the user’s sharing strategy and the project budget. Generally, more open sharing
of data products means higher acquisition cost. DEM products derived from archive data may be significantly
lower cost but come with sharing restrictions, while a custom data collection will cost significantly more but have
much less if any restriction on dissemination. If the desire is to enable dissemination of products in the public
domain, then expect to pay a higher cost.
The dissemination of imagery and DEM products acquired from archive sources, such as those produced by
satellite data vendors, is often highly restricted by an End User License Agreement (EULA) or similar document.
Typical EULAs restrict the use of the data to the internal needs of the user and prevent further dissemination of
the data to others. Derivative products may be less restricted but care must be taken to ensure the EULA does
not also restrict them as well. An example EULA for imagery is provided as Annex D.
For procurement of an archived DEM product, the license will typically limit distribution as shown in the example in
Annex E. In this instance, the DEM product is considered the property of the vendor and the license strictly limits use
to internal purposes only. The example is from Astrium Services and states in its Standard License that the user may:
“(a) Install the PRODUCT on as many individual computers as needed in its premises, including internal
computer network (with the express exclusion of the internet);
(b) Make a maximum of ten (10) copies for: (i) installation of the PRODUCT as per (a) above and (ii) for
archiving and back-up purposes;
(c) Print or use part or all of the PRODUCT for its own internal needs.
The End-User shall be authorized to alter or change the PRODUCT and to create added value to the
PRODUCT provided this is made by—or under the responsibility of—the END-USER and used by and for
END-USER own internal needs only.”
d) sublicense, sell, rent or lease or otherwise transfer or assign the PRODUCT or VAP to a third party,
except as provided in Article 2.1 (f);
e) alter or remove any copyright notice or proprietary legend contained in or on the PRODUCT and any VAP;
f ) publish, distribute or transfer in any way the digital format of the PRODUCT;
All of this is rational for the vendor to recoup their investment, as the data they collected (which for satellite data
is quite a large amount) only has value to the extent that customers are willing to pay for it. However, the cost of
such products for each user will be much lower than for a custom data collection.
If the DEM products are acquired as a custom data acquisition, the cost of collection and processing will be borne by
the user. As a result, the user “owns” the data and any derivative products with full rights to disseminate as desired.
Data Storage, Sharing Platforms
Often, data storage and data sharing plans are lacking from the overall project planning. Without storage and
data sharing plans, the data that was generated using the hundreds of thousands of dollars will not be used. It is
paramount that the data storage and sharing plan be incorporated into every project that has a DEM component
in it. Once data is stored, a mechanism to have the data used by the end user must be implemented. Without this
mechanism, the data will be wasted or be used only once, without achieving its potential usefulness.
05
Chapter
Case Studies
The following provides illustrative examples of the process of how DEM acquisitions were planned from past
World Bank projects as well as others outside the World Bank.
Mozambique Flood Risk Mapping (P104447)
Following the floods that affected the Limpopo river basin in 2013, and in the context of the project
Mainstreaming Disaster Reduction for Sustainable Poverty Reduction: Mozambique, the national disaster
management agency of Mozambique (INGC) required a high-resolution DEM for flood risk mapping. The flood
risk maps were required for a decision support system being developed by INGC. The government engaged an
expert from the University of Eduardo Mondlane to supervise the Lidar survey, with extensive experience on risk
mapping in the Limpopo (he had previously led the preparation of the risk atlas for the basin).
After a review of the data availability, a decision was made by the client to generate a new DEM dataset using
Lidar. The specs for the DEM were defined by the specialist, and limited international bidding was adopted.
Under LIB, and of the three bids received, one vendor was selected, due to the price and the fact that the vendor
already had a plane stationed in the country that would reduce the cost. The Data license was specified to be
open. However, the decision support system was reserved to specialists with the government. The cost of the
DEM was approximately US$500k. Only Lidar data was acquired (e.g. no aerial photography or near infrared).
Approximately one year was needed to complete the data acquisition and DEM generation by the vendor.
The consultant hired by the government assumed the role of being the focal point and took ownership of the
project and data. The consultant was also able to integrate the resulting DEM with the decision making tool
developed by the client. A challenge arose when a follow-up Lidar survey was appropriated by another agency,
which created problems of continuity. It is recommended that a national organization be mandated as custodian
of Lidar data to allow the resulting DEM to be sharable with other prospective users or, in case new surveys are
needed, they be made compatible with existing data.
Rigorous time planning of Lidar is essential. Procurement activities (including also government internal
procedures) should be planned to make sure that the service provider is ready to go to the field when
weather and terrain conditions are at best for the survey. Sometimes this may be overlooked and may lead to
cost increases.
Haiti Flood Risk Mapping (P126346)
In Haiti, a DEM had been generated following the 2010 earthquake. However, this DEM was generated for
damage assessment and did not meet the specs necessary for the flood risk assessment that the project Disaster
Risk Management and Reconstruction (P126346) required. Additionally, the DEM collected in 2010 had a large 41
42 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
gap in the project area for the new project. The flood risk assessment was to be incorporated into a decision
making system for DRM which would have restricted access. DEM was designed to eventually serve projects with
a wide range of objectives in Haiti. The data was to be hosted on Haitidata.org.
The DEM was generated from stereo photography and Lidar, with a budget of a total US$2 million. The densities
of the Lidar points collected were different depending on the survey area. For cities, the points were denser.
Fourteen cities were surveyed first. The second phase saw some delay with the contracting, as well as delays
due to the weather conditions. The procurement process took 6 months. The licensing conditions of the data
were not made explicit in the contract with the vendor. Responsibility for quality assurance sat with the client.
The World Bank team did not hire a specialist to confirm that the delivered product adheres to the spec in the
ToR. It would have been good to have such a specialist on the World Bank team, also a standard ToR for such
specialist would be useful (see Annex F for such template). The DEM was subsequently used for flood modeling,
to the satisfaction of the flood modelers. The necessary specs for a DEM are going to be different from project
to project hence it is not recommended to reuse a ToR from another project. Find the right balance of capacity,
technology, resolution, and price.
(Hypothetical Example) DEM for Urban Development
The client needs DEM models for commercial development planning covering 200 km2. Vertical accuracy
requirement is 5m. However, the area is frequently cloud- and fog-covered. While Lidar or photogrammetric
approaches can easily satisfy the accuracy requirements, clouds and fog make such methods problematic.
However, IfSAR-based products can satisfy the accuracy requirement and are not affected by clouds or fog.
Satellite archive IfSAR DEM data is available from the U.S. Geological Survey (USGS) and from Astrium. The
USGS data is derived from SRTM SAR data and has a vertical accuracy of 5m with a 30m horizontal spatial
resolution. It is also free of charge. Astrium provides TerraSAR derived DEM data which has a relative vertical
accuracy of <5m and a horizontal resolution of 12m for a cost of €30/km2.
The choice is between DEM data at 90m resolution for no-cost versus 12m resolution data for €30/km2 ($39).
For 200km2 coverage, the higher spatial resolution is available for a total of €6,000 (approximately US$8,000).
In this case, given the much higher spatial resolution for a relatively modest cost, the Astrium product would
be advisable.
(Hypothetical Example) Earthquake and DEM
An earthquake has devastated a large area of an island including a densely populated urban center. Information
on damage for response and recovery planning is needed as well as a detailed floodplain hydrological analysis as
the monsoon season is rapidly approaching.
Currently available DEMs for the area are based on 30m resolution SRTM data from the USGS. This resolution is
not sufficient for damage assessment, and the vertical accuracy is not sufficient for hydrological analysis.
Case Studies 43
A custom airborne data collection with Lidar is best suited to satisfy the requirement of high resolution and
accuracy for detailed flood plain analysis and damage assessment. Plus it satisfies the need to obtain data that
shows current status on the ground.
Lidar fight services can be obtained for approximately €136/US$180/km2. Expect that there may be an extra charge
for rapid mobilization which may add 10% to 20% to the per km2 cost (€14–28/US$19–38/km2). There may also
be additional acquisition costs (5% or €7/US$9/km2) due to the need to base flight operations at a neighboring
country because of damage to the local airport infrastructure.
(HYPOTHETICAL EXAMPLE) COMMERCIAL FORESTRY
A forestry company (or national/regional forest service) is in need of an accurate and precise map of forest
volume (yield) and biomass (carbon sequestration) for either a local area or a more regional application. In the
first case, the local need likely dictates accurate mapping for commercial purposes (timber sales) and as such,
Lidar would be the ideal modality. In the latter case, the need probably is for either a synoptic view of forest stock
or to gauge carbon sequestration progress and potential. In this case, IfSAR is a more likely candidate modality,
given the area requirements and synoptic approach.
As with the Earthquake Case Study, a custom airborne data collection with Lidar is an ideal candidate: An
accurate, precise, and high spatial resolution DEM (1–5m) would be coupled with a moderately dense Lidar point
spacing (5 hits/m2), which can be used to estimate tree heights and use these extracted heights to gauge tree,
stand, and area volume. This can be done on the basis of established relationships between tree volume and
height (and also crown width and other tree-level metrics).
For the regional assessment, Lidar could be cost-prohibitive, although many/most commercial forestry
companies do acquire Lidar data for their landholdings. The IfSAR approach, would be similar to that of Lidar,
where a coarser DEM would be coupled to a relatively coarse canopy height surface (“image”) to extract spatially-
explicit forest height. This height image, which will vary spatially, can be used to model the underlying forest’s
biomass, by using a similar approach to that of Lidar. In scientific terminology we say that “forest biomass is a
function of height”, i.e., we can use established models to estimate biomass by using the IfSAR height as an input
variable.
Please see case studies above for an approximate cost estimate for both Lidar and IfSAR.
44 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
06
Chapter
Glossary 16
Accuracy
The closeness of an estimated value (e.g., measured or computed) to a standard or accepted (true) value of a
particular quantity. Note: Because the true value is not known, but only estimated, the accuracy of the measured
quantity is also unknown. Therefore, accuracy of coordinate information can only be estimated.
Absolute Vertical Accuracy
A measure that relates the stated elevation to the true elevation with respect to an established vertical datum.
The computed value for the absolute vertical accuracy (tested, or compiled to) should be included in the
metadata file.
Artifacts
Any feature, whether man-made or system-made, that unintentionally exists in a digital elevation model. Real
features such as buildings, trees, towers, telephone poles, or other elevated features that should be removed
when depicting a DEM of the bare-earth terrain. They also include unintentional by-products of the production
process, such as stripes in manually profiled DEMs.
Aspect
The compass direction, facing downward, with the steepest slope. Identifies the orientation of a surface with
respect to compass direction, as well as calculates the angle of the face.
Breaklines
Linear features that describe a change in the smoothness or continuity of the surface. Typical breaklines are river
streams. The two most common forms of breaklines are as follows:
Soft Breaklines
Ensure that known z-values along a linear feature are maintained, and they ensure that linear features and
polygon edges are maintained in a TIN surface model, as described below, by enforcing the breakline as TIN
edges, but they do not define interruptions in surface smoothness. Soft breaklines are generally synonymous
with 3-D breaklines because they are depicted with series of x/y/z coordinates.
Hard Breaklines
Define interruptions in surface smoothness. They are used to define streams, shorelines, dams, ridges,
building footprints, and other locations with abrupt surface changes. Although some hard breaklines are
3-D breaklines, they are often depicted as 2-D breaklines because features such as shorelines and building
footprints are normally depicted with series of x/y coordinates only.
16 Guidelines for Digital Elevation Data, National Digital Elevation Program (NDEP), May 10, 2004, pages 81–89.
45
46 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Calibration
Procedures used to identify systematic errors in hardware, software, and procedures so that these errors can be
corrected in preparing the data derived therefrom.
Cartesian Coordinates System
A coordinate system consisting of N straight lines (1- dimensional spaces) intersecting at one common point
(the origin) and determining N distinct hyperplaces ((N-1)-dimensional spaces); the n-th (1 ≤ n ≤ N) coordinate
of a point is the distance, along the n-axis, from the origin to the point where that axis is intersected by the
hyperplace containing that point, through the N-1 other axes. Or:
2-D Cartesian Coordinates
A pair of numbers that locate a point by its distances from two intersecting, normally perpendicular lines
in the same plane. Each distance is measured along a parallel to the other line. UTM and State Plane
coordinates are examples of 2-D Cartesian coordinates.
3-D Cartesian Coordinates
A triad of numbers that locate a point by its distance from three fixed planes that intersect one another at
right angles. Except for unique applications, 3-D Cartesian coordinates with z-coordinates are rarely used.
Instead, z-values are more popularly understood as heights or elevations above a curved surface defined by
the vertical datum, ellipsoid, or geoid.
Checkpoint
One of the points in the sample used to estimate the positional accuracy of the dataset against an independent
source of higher accuracy.
Confidence Level
The probability that errors are within a range of given values.
Consolidated Vertical Accuracy
The result of a test of the accuracy of 40 or more check points (z-values) consolidated for two or more of the
major land cover categories, representing both the open terrain and other land cover categories. Computed using
a nonparametric testing method (95th Percentile), a consolidated vertical accuracy is always accompanied by a
fundamental vertical accuracy. See fundamental and supplemental vertical accuracies.
Contour
A line connecting points of equal elevation.
Coordinates
A group of 3-D numbers that define a point in 3-D space. Traditionally, a vertical coordinate would be defined as a
3-D coordinate, that is, a x,y coordinate with an associated z-value
Glossary 47
Datum
Any quantity or set of such quantities that may serve as a basis for calculation of other quantities. Herein, the
term datum is synonymous with geodetic datum defined below.
Datum, Geodetic
A set of constants specifying the coordinate system used for geodetic control, i.e., for calculating coordinates
of points on the Earth. At least eight constants are needed to form a complete datum: three to specify the
location of the origin of the coordinate system, three to specify the orientation of the coordinate system,
and two to specify the dimensions of the reference ellipsoid.
Datum, Horizontal
A geodetic datum specifying the coordinate system in which horizontal control points are located.
Datum, Tidal
A surface with a designated elevation from which heights or depths are reckoned, defined by a certain
phase of the tide. A tidal datum is local, usually valid only for a restricted area near the tide gauge(s) used in
defining the datum.
Datum, Vertical
A set of fundamental elevations that refer to elevation measurements.
Digital Elevation Models (DEMs)
i. “DEM” is a generic term for digital topographic and/or bathymetric data in all its various forms. The
generic DEM normally implies elevations of the terrain (bare-earth z-values) devoid of vegetation and
manmade features.
ii. As used by the U.S. Geological Survey (USGS), a DEM is the digital cartographic representation of the
elevation of the land (digital topography) at regularly spaced intervals in x and y directions, using z-values
referenced to a common vertical datum. There are many types of standard USGS DEMs.
iii. As used by other users in the U.S. and elsewhere, a DEM has bare-earth z-values at regularly spaced intervals
in x and y, but normally following alternative specifications, with for example, narrower grid spacing and
State Plane coordinates.
Digital Line Graphs (DLGs)
Geospatial data, digitized as node, line, and area features, using hundreds of different attribute codes to define
basic cartographic data categories such as hypsography (contours), hydrography, transportation, manmade
features, vegetation, boundaries, survey control, etc. USGS digitizes 11 categories of cartographic features on
its topographic quadrangles at various scales and archives DLGs in the NDCDB. FEMA digitizes 4 categories of
cartographic features on flood hazard maps for the National Flood Insurance Program. Current data collection
in all major mapping programs is directed toward producing topologically structured Level-3 DLG data, referred
to as DLG-3. Other government and private sector organizations collect and produce geospatial datasets in
DLG-3 format to facilitate the interchange and use of DLG data in a standard format compatible with diverse GIS
software programs.
48 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Digital Terrain Elevation Data (DTED)
Standard elevation datasets of the National Geospatial-Intelligence Agency (NGA), similar to standard USGS
DEMs described above.
Digital Orthophotos
Digital orthophotos are aerial or spaceborne images that have been corrected for any relief displacement by using
elevation or DEM data.
Digital Terrain Models (DTMs)
In some countries, DTMs are synonymous with DEMs, representing the bare-earth terrain with uniformly spaced
z-values.
i. As used here, DTMs use DEMs as a starting point, but may also incorporate the elevation of significant
topographic features on the land and change points and breaklines that are irregularly spaced so as to better
characterize the true shape of the bare-earth terrain. The net result is that the distinctive terrain features
are more clearly defined, and contours generated from DTMs more closely approximate the real shape of
the terrain. Such DTMs are normally more expensive and time consuming to produce than uniformly spaced
DEMs because breaklines are ill suited for automation. DTM results are technically superior to standard
DEMs for many applications.
Digital Surface Models (DSMs)
DSMs are similar to DEMs or DTMs, except that they depict the elevations of the top surfaces of buildings, trees,
towers, and other features elevated above the bare earth. DSMs are especially relevant for telecommunications
management, forest management, air safety, 3-D modeling, and simulation.
Elevation
The “official” geodesy definition of elevation is the distance measured upward along a plumb line between a
point and the geoid. The elevation of a point is normally the same as its orthometric height, defined as “H” in the
equation: H=h–N. More generally, the term elevation is used to indicate height above a specific vertical reference,
not always the geoid.
Elevation Post
The vertical component of a DEM grid point, having height above the vertical datum equal to the z-value of its
grid point.
Ellipsoid
A closed surface whose planar sections are either ellipses or circles. The Earth’s ellipsoid is a biaxial ellipsoid of
revolution (defined by its major axis “a” and its minor axis “b”) obtained by rotating an ellipse about its minor
(shorter) axis.
Ellipsoid Height
The height above or below the ellipsoid, i.e., the distance between a point on the Earth’s surface and the
ellipsoidal surface, as measured along the normal (perpendicular) to the ellipsoid at the point and taken positive
Glossary 49
upward from the ellipsoid. Ellipsoidal height Figure 19. Illustration of Ellipsoid, Geoid, and Orthometric height.
elevation measured with GPS. Defined as “h” in the
equation: h = H + N. Figure 19 shows the relationship Earth’s
Ellipsoid “h = H + N” sur ace
between “heights”. P
h
Fundamental Q
Vertical Accuracy N
The fundamental vertical accuracy is the value by “Geoid”
P0
which vertical accuracy can be equitably assessed
and compared among datasets. The fundamental OCEAN
vertical accuracy of a dataset must be determined
h (Ellipsoid height) = Distance along ellipsoid noemal (Q to P)
with check points located only in open terrain where N (Geoid height) = Distance along ellipsoid noemal (Q to P0)
there is a very high probability that the sensor will H (Orthometric height) = Distance along Plump line (P0 to P)
have detected the ground surface. It is obtained
utilizing standard tests for RMSE (root-mean-square Source: www.noaa.gov.
deviation). See supplemental and consolidated
vertical accuracies.
Geoid
The level (equipotential) surface of the earth’s gravity field that, on average, coincides with mean sea level in the
open undisturbed ocean. In practical terms, the geoid is the imaginary surface where the oceans would seek mean
sea level if allowed to continue into all land areas so as to encircle the earth. The geoid undulates up and down
with local variations in the mass and density of the earth. The local direction of gravity is always perpendicular
to the geoid. It is used to measure precise surface elevations, with the vertical coordinate. Z (elevation) is
referenced to the geoid.
Geodetic Datum
Geodetic reference from which measurements are made. See Datum, geodetic
Geoid Height
The difference between an ellipsoid height and an orthometric height. Defined as “N” in the equation: N = h – H.
Geodetic Height
Same as ellipsoidal height
Geospatial Data
Information that identifies the geographic location and characteristics of natural or constructed features and
boundaries of earth. This information may be derived from, among other things, remote sensing, mapping, and
surveying technologies.
Grid
A geographic data model that represents information as an array of equally sized square cells. Each grid cell is
referenced by its geographic or x,y orthogonal coordinates.
50 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Horizontal Accuracy
Positional accuracy of a dataset with respect to a horizontal datum.
Horizontal Error
Magnitude of the displacement of a feature’s recorded horizontal position in a dataset from its true accurate
position, as measured radially and not resolved into x and y.
Horizontal Post Spacing
The smallest distance between two discrete points that can be explicitly represented in a gridded elevation
dataset. It is important to note that features of a size equal to, or even greater than the post spacing, may not be
detected or explicitly represented in a gridded model. For gridded elevation data the horizontal post spacing may
be referenced as the cell size, the grid spacing, the posting interval, or the ground sample distance. Horizontal
post spacing should be documented in the metadata file.
Hydro-enforcement
The removal of elevations from the tops of selected drainage structures (bridges and culverts) in a DEM, TIN or
topographic dataset to depict the terrain under those structures. Also referred to as drainage enforced.
Hypsography
The configuration of land or underwater surfaces with respect to a horizontal and vertical datum. Hypsography
includes topographic and bathymetric contours, spot heights, mass points, breaklines, and all forms of generic
DEM data except DSMs that depict surfaces above the ground.
IfSAR
Interferometric Synthetic Aperture Radar—An airborne or spaceborne interferometer radar system, flown
aboard airplanes, helicopters or space-based platforms, that is used to acquire 3-D coordinates of terrain and
terrain features that are both man-made and naturally occurring. IfSAR systems form synthetic aperture images
of terrain surfaces from two spatially separated antennae over an imaged swath that may be located to the left,
right, or both sides of the imaging platform.
Image Correlation
A computerized technique to match the similarities of pixels in one digital image with comparable pixels in its digital
stereo image to automate or semi-automate photogrammetric compilation. Image correlation provides a faster
method for generating DEMs photogrammetrically, but automatic correlation normally results in DSMs instead of
DEMs, generating elevations of rooftops, treetops and other surface features as imaged on the stereo photographs.
Independent Source of Higher Accuracy
Data acquired independently of procedures to generate the dataset, and that is used to test the positional
accuracy of that dataset. The independent source of higher accuracy shall be of the highest accuracy feasible and
practicable to evaluate the accuracy of the dataset.
Interpolation
The estimation of elevation (z-values) at a point with x/y coordinates, based on the known z-values of
surrounding points.
Glossary 51
Lattice
A method of 3-D surface representation created by a rectangular array of points spaced at a constant sampling
interval in x and y directions, relative to a common origin. A lattice differs from a grid in that it represents the value
of the surface only at the “mesh points” or “elevation posts” of the lattice, rather than the value of the cell area
surrounding each mesh point.
Lidar
Light detection and ranging—An instrument that measures distance to a reflecting object by emitting timed
pulses of light and measuring the time between emission and reception of reflected pulses. The measured time
interval is converted to distance based on the speed of light.
Mass Points
Irregularly spaced points, each with an x/y location and a z-value, used to form a TIN. When generated manually,
mass points are ideally chosen to depict the most significant variations in the slope or aspect of TIN triangles.
However, when generated by automated methods, for example, by Lidar or IfSAR scanners, mass point spacing
and pattern depend on characteristics of the technologies used to acquire the data. Mass points are most often
used to make a TIN, but not always. They can be used as XYZ point data for interpolation of a grid without an
intermediate TIN stage.
Order
The accuracy ranking of one measurement or survey with respect to other measurements or surveys.
Orthometric Height
The height above the geoid as measured along the plumb line between the geoid and a point on the Earth’s
surface, taken positive upward from the geoid. It is the difference between ellipsoidal height from a GPS and
geoid height.
Positional Accuracy
The accuracy of the position of features, including horizontal and/or vertical positions.
Post Spacing
The z-values at regularly spaced intervals of a grid (the ground distance in x and y (“post spacing” = ∆x = ∆y)).
For a DEM, the post-spacing is the distance between points on the elevation grid, usually specified in units of
whole feet or meters. The smaller the post spacings, the greater the imagery detail. Actual grid spacing, datum,
coordinate system, data format, and other characteristics may vary widely from grid to grid.
Profile
A vertical view of a surface derived by sampling surface values along a specified line. In USGS DEMs, profiles are
the basic building blocks of an elevation grid and are defined as one-dimensional arrays, i.e., arrays of n columns
by 1 row, where n is the length of the profile.
Puddle
One or more grid cells totally surrounded by cells of higher elevation (see also pit).
52 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Relative Accuracy
A measure that accounts for random errors in a dataset. Relative accuracy may also be referred to as point-to-
point accuracy. The general measure of relative accuracy is an evaluation of the random errors (systematic errors
and blunders removed) in determining the positional orientation (For example, distance, azimuth, elevation) of
one point or feature with respect to another.
Relative Vertical Accuracy
A measure of the point-to-point vertical accuracy within a specific dataset. To determine relative vertical
accuracy, the vertical difference between two points is measured. That difference is then compared to the
difference in elevation for the same two points on the reference. The difference between the two measures
represents the relative accuracy. The reference must have at least three times the accuracy of the intended
product accuracy, insuring that all systematic errors and blunders have been removed. Relative vertical accuracy,
an important characteristic of elevation data used for calculating slope, should be documented in the DEM
metadata file.
Resolution
In the context of gridded elevation data, resolution is related to the horizontal post spacing and the vertical
precision. Other definitions include:
i. The size of the smallest feature that can be represented in a surface or image.
ii. Sometimes used to state the number of points in x and y directions in a lattice, For example, 1201 x 1201
mesh points in a USGS one-degree DEM.
Root Mean Square Error
The square root of the mean of squared errors for a sample.
Slope
The measure of change in elevation (z-value) over distance, expressed either in degrees or as a percentage. For
example, a rise of 4 meters over a distance of 100 meters describes a 2.3° or 4% slope.
Spatial Data
See geospatial data.
Stereo Photography
See Digital Orthophotos
Surface
A 3-D geographic feature represented by computer
models built from uniformly- or non-uniformly-
spaced points with x/y coordinates and z-values. The
figure here shows an example of 3-D building surface
models created from non-uniform data points in
Source: Image courtesy of Dr. Jan van Aardt and Mr. Donald
imagery and Lidar. McKeown (Rochester Institute of Technology).
Glossary 53
Supplemental Vertical Accuracy
The result of a test of the accuracy of z-values over areas with one or more ground cover categories other
than open terrain. Because elevation errors often vary with the height and density of ground cover, analysts
cannot assume a normal distribution of error and, therefore, they cannot use the standard deviation (RMSE)
to calculate the 95% accuracy value. Instead, the 95th percentile testing method is used for supplemental
vertical accuracy, always accompanied by a fundamental vertical accuracy. See fundamental and consolidated
vertical accuracies.
Triangulated Irregular Networks (TINs)
A TIN is comprised of a set of adjacent, non-overlapping triangles computed from irregularly spaced points with
x,y coordinates and z-values. The TIN data structure is based on irregularly spaced point, line, and polygon data
interpreted as mass points and breaklines. The TIN model stores the topological relationship between triangles and
their adjacent neighbors. The data structure enables efficient generation of surface models for the analysis and
display of terrain and other types of surfaces. A TIN surface can be created from a multiplicity of sources: point,
line and polygon data; contour maps; stereo plotter data; Lidar, IfSAR, or Sonar data; randomly distributed points
in ASCII files; breakline data; and DEM lattices. TINs usually require fewer data points than DEMs or DTMs,
while capturing critical points that define terrain discontinuities and are topologically encoded so that adjacency
and proximity analyses can be performed. TINs have several other advantages over DEMs and DTMs, but they are
probably best known for their superiority in surface modeling, including: calculation of slope, aspect, surface area
and length; volumetric and cut-fill analysis; generation of contours; interpolation of surface z-values; generation
of profiles over multiple surfaces; intervisibility (line-of-sight) analysis; and 3-D visualization, simulation, and
fly-throughs.
Undulation of the Geoid
The rise and fall of the geoid. Sometimes used synonymously with geoid height.
Vertical Accuracy
Measure of the positional accuracy of a dataset with respect to a specified vertical datum.
Vertical Datum (See Datum)
Vertical Error
The displacement of a feature’s recorded elevation in a dataset from its true or more accurate elevation.
Well-defined Point
A point that represents a feature for which the horizontal position is known to a high degree of accuracy and
position with respect to the geodetic datum.
World Geodetic System 1984 (WGS 84)
WGS 84 represents the best available global geodetic reference system of the Earth for practical military
applications of mapping, charting, geo-positioning and navigation. The system includes a defined coordinate
system, fundamental and derived constants, the geoid model (Earth Gravitational Model 1996), the ellipsoid
(normal) gravity model and a list of local datum transformations.
54 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
X-Coordinate
The distance along the x-axis from the origin of a 2-D or 3-D Cartesian coordinate system. An x-coordinate is the
first half of UTM coordinates or the easting of State Plane coordinates.
Y-Coordinate
The distance along the y-axis from the origin of a 2-D or 3-D Cartesian coordinate system. A y-coordinate is the
second half of UTM coordinates or the northing of State Plane coordinates.
Z-Coordinate
1. The distance along the z-axis from the origin of a 3-D Cartesian coordinate system. 2) The elevation or
height above the vertical datum.
Z-units are the units of measure used for the z-values in a geographic dataset.
Z-values are the elevations of the 3-D surface above the vertical datum at designated x/y locations.
07
Chapter
Selected
Resources
Amann, M.-C., T. Bosch, M. Lescure, R. Myllylä, and M Rioux. Year. Laser ranging: a critical review of usual
techniques for distance measurement. Optical Engineering 40 (1): 10–19.
ASPRS LAS specification version 1.3 - R11.2010 (October).
Baltsavias, E. P. Year. Airborne laser scanning: basic relations and formulas. ISPRS Journal of Photogrammetry and
Remote Sensing, 54 (2–3): 199–214.
Baltsavias, E. P. Year. Airborne laser scanning: existing systems and firms and other resources. ISPRS Journal of
Photogrammetry and Remote Sensing, 54 (2–3): 164–198.
Guidelines for Digital Elevation Data, Version 1.0, National Digital Elevation Program (NDEP), May 10, 2004.
Available at http://www.ndep.gov
Jenkins, J. 2006. Key drivers in determining Lidar sensor selection. In Promoting Land Administration and Good
Governance 5th FIG Regional Conference (March 2006), no. TS19.5.
Lefsky, M.A., W.B. Cohen, G.G. Parker, and D.J. Harding. 2002. Lidar remote sensing for ecosystem studies.
Bioscience, 52 (1): 19–30.
Lemmens, M, 2007. Airborne Lidar sensors. GIM International, 21, 2.
Maune D.F. (editor), 2007. Digital Elevation Model Technologies and Applications: The DEM Users Manual, 2nd
Edition. American Society for Photogrammetry and Remote Sensing ASPRS), Bethesda, Maryland, USA; 655p.
Popescu, S.C., R.H. Wynne, and R.F. Nelson. 2002. Estimating plot-level tree heights with Lidar: Local filtering
with a canopy-height based variable window size. Computers and Electronics in Agriculture, 37: 71–95.
van Aardt J.A.N., R.H. Wynne, and J.A. Scrivani. 2008. Lidar-based mapping of forest volume and biomass by
taxonomic group using structurally homogenous segments. Photogrammetric Engineering and Remote Sensing,
74 (8): 1033–1044.
van Aardt J.A.N., D. McKeown, J. Faulring, N. Raqueño, M. Casterline, C. Renschler, R. Eguchi, D. Messinger, R.
Krzaczek, S. Cavillia, J. Antalovich Jr., N. Philips, B. Bartlett, C. Salvaggio, E. Ontiveros, and S. Gill. 2011.
Geospatial disaster response during the Haiti earthquake: A case study spanning airborne deployment, data
collection, transfer, processing, and dissemination. Photogrammetric Engineering and Remote Sensing, 77 (9):
943–952.
Wehr, A., and Lohr, U. Year. Airborne laser scanning — an introduction and overview. ISPRS Journal of
Photogrammetry and Remote Sensing, 54 (2–3): 68–82. http://www.azdot.gov/media
Walker S., 2006. Photogrammetry 101: Facing 21st Century Challenges. Earth Imaging Journal, July/August 2006
(http://eijournal.com/).
55
08
Chapter
Technical Annex
57
Annex A
How DEMs Are
Created: A Brief
Introduction
to Remote
Sensing Modalities
Three main remote sensing modalities are used to collect the elevation data necessary for DEM creation:
(i) light detection and ranging (Lidar); (ii) radio detection and ranging (radar); and (iii) stereo photogrammetry
approaches. In this document, the system, operation, data, processing needs, and advantages versus
disadvantages of each modality will be described. Annex A offers a more detailed description and discussion of
each modality. Finally, DEM products that are generated based on spaceborne platforms will be discussed with an
example for each of the three modalities.
Light Detection and Ranging (Lidar)
Light detection and ranging (Lidar) in general can be regarded as a ranging system, or a system that measures
the range from an instrument to an object. In this case, the Lidar system generates a very brief laser pulse, on
the order of nanoseconds, after which the range to objects in the laser path is calculated based on the time it
takes scattered/reflected light from a surface to return to the Lidar system’s detector. This is possible because
the constant speed of light can be exploited to give us the relation: where R is the range (in meters) at which
scattering/reflectance occurred, t is the duration (in nanoseconds; ns) for the scattered light to return to the
Lidar detector, and c is the speed of light. Note that the factor of ½ is necessary due to the fact that the laser
energy needs to travel to the object and back again. Figure TA1 provides a graphical example of a typical Lidar
system and its operation.
This is a very simple description of the basic operation of a laser-based rangefinder; there are more complex
Lidar equations that govern the transmittance of laser light through the atmosphere, but these fall outside the
scope of this document and are rarely, if ever, of any consideration to the Lidar end user. Although discrete return
Lidar systems, or systems that measures distinct 3D x,y,z (location and elevation) data, are most commonly used
for ranging and associated 3D, topographical, or even DEM-related analysis, it is worthwhile to briefly review
other sensors currently in operation (see Annex A for more detail).
59
60 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Figure TA1. An example of the airplane/Lidar system’s position in 3D space (top-left), the detection of multiple returns
per pulse (top-middle), a resultant 3D x,y,z point cloud (top-right), and a final DEM, constructed by interpolating Lidar
ground returns.
Source: www.neoninc.org.
The main advantages of Lidar are: (i) accuracy (0.15m vertical; 0.5m horizontal), (ii) flexible and dense point
coverage, resulting in high spatial resolution DEMs (i.e., small pixels), (iii) operation in adverse conditions
such as rain (Lidar is an active remote sensing modality, i.e., it generates is own energy), and (iv) multiple uses/
applications, such as DEMs, vegetation analysis, infrastructure assessment, and others. The main disadvantages
are: (i) an irregular spacing, although this is addressed via interpolation to generate a DEM, (ii) relative expense,
(iii) large data volumes, and (iv) high processing/computing requirements.
Radio Detection and Ranging (Radar) and IfSAR
Synthetic Aperture Radar (SAR) is another active imaging system, similar to Lidar in that the sensor system emits
an electromagnetic (microwave) pulse toward a target and measures the reflectance at microwave-wavelengths.
This time delay is used to compute distance between the sensor and target. Thus a conventional SAR sensor can
produce a two dimensional image of returns oriented with one axis along the line of flight and the other along
an axis parallel to the line of sight of the sensor. As such, a conventional SAR image is analogous to a photograph
in that it has features in two dimensions. Figure TA2 shows a typical SAR image in which each “pixel” represents
a reflected return of a radar pulse. However, SAR data are not inherently a DEM any more than a photograph is.
For DEMs, the phase data from two SAR images, taken from slightly offset perspectives, are required in order
to produce an “interferogram” (aka IfSAR), from which a DEM ultimately is derived. Further technical detail is
provided in Annex A.
SAR sensors are characterized in terms of the microwave frequency range in which they operate. The most
common will be generated from C-band, X-band, or L-band sensor systems. (See Annex A.2.1)
How DEMs Are Created: A Brief Introduction to Remote Sensing Modalities 61
Figure TA2. An example of a radar pod (top-left), mounted on a AMPS P-3 aircraft Source: www.sandia.gov (top-right),
and a typical radar image, clearly showing texture (structure) and elevation differences based as varying levels of
image intensity. Source: www.nasa.gov. This specific image, acquired on December 28, 1992 by the European Remote
Sensing 1 satellite, shows stormwater runoff plumes from the Los Angeles and San Gabriel Rivers into the Los
Angeles and Long Beach Harbors. The more recent image at the bottom right is from the Japanese Space Agency’s
(JAXA) PALSAR-2 platform, and was acquired June, 2014; again the structure and texture of the underlying landscape
are evident (www.global.jaxa.jp)
Source: www.usgs.gov .
Photogrammetry
Photogrammetry is loosely defined as the science of making accurate and precise measurements of surface
elevation using aerial stereo photographs. In its simplest form, it is based on the principle of observing the
same object from two different vantage points, the same bio-vision principle as for human 3D sight, an effect
called parallax. Photogrammetrists (3D image analysts) can use analog, hard-copy aerial imagery or modern,
digital, or soft-copy aerial images for extracting elevation data. Analysts can create a 3D stereomodel from
adjacent, overlapping photographs and render it into an orthomap that presents the elevation of the Earth
surface covered by that map. Such maps can indicate where specific features, such as roads, wells, power lines,
manholes, fences, etc. are located, while also proving information on the elevation of such features or enabling
volumetric calculation.
62 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Although stereoscopic imagery is useful for generating a 3D topographical model like a DEM, the associated concept
of “relief displacement” can be exploited to determine individual object height, even though it is not as applicable to
ground elevations (DEMs). Relief displacement means that a feature’s top and bottom will be displaced in terms of
x,y coordinates, if that figure is not exactly at the focal point of a photograph. The concept of relief displacement of
features on single photographs, and measuring the change in relative position between multiple photographs, enable
photogrammetrists to derive object height and elevations, respectively. Such 3D or stereoscopic analyses do have a
number of specific requirements, related to system and collection parameters.
High quality aerial photography requires precision instruments, overlapping photos, good viewing conditions,
and adequate coverage of all landscape features to enable accurate measurements and assessment points. Once
completed, the photogrammetric process can generate a wide range of products, from DEMs and DSMs to elevation-
corrected feature maps. This is because stereo photography—unlike Lidar or radar—offers a rich photographic
context of a landscape, enabling interpretation and classification of its features. Photogrammetry is limited, however,
because as a passive remote sensing technology, it is weather-dependent. More importantly, because (3D) elevation
data can only be extracted for points visible to the camera, photogrammetry cannot capture measurements through
dense forest canopy or vegetation. More detail is provided in Annex A.3, while a slightly more technical, but still
digestible write-up of the photogrammetric process by Walker (2006).
Satellite-derived DEM Products
DEM products can be generated from satellite-based “spaceborne” platforms, including Lidar, radar, and
photogrammetry. The advantages of spaceborne platforms are many, including: (i) coverage of large swaths of the
Earth (synoptic coverage); (ii) the ability to “task”
sensors, directing data acquisition to areas of interest,
ICESat missions: ICESAT-I (Ice, Cloud, and land Elevation Satellite)
was launched in 2003, designed to measure ice sheet mass balance, e.g., following a natural disaster; (iii) standardized and
cloud and aerosol heights, land topography (DEM) and vegetation relatively quick data processing, resulting in consistent
structural characteristics. It was decommissioned in 2010, and will and established workflows; and (iv) coverage in
be followed by ICESAT-II, slated for launch in 2017. ICESat-I, a laser remote locations that are otherwise hard to access.
range finder, operated in the infrared (1,064 nm) and visible green
The comparative disadvantages of spaceborne remote
light (532 nm) ranges, and was able to accurately measure clouds,
sensing are relatively few. Only Lidar and radar
vegetation heights, and ground surface elevation. However, this was
what is called a “large-footprint” system, collecting range data at 40 provide the capability to survey the ground in adverse
hits/s for 70m diameter footprints and spaced at 170-meter intervals. weather conditions, as discussed above. More critical
Therefore, although accurate, this system can be regarded as a limitations are the typically lower spatial resolution
coarse resolution sampler for elevation data. and, with the exception of Lidar, lower precision
and accuracy of spaceborne modalities. As such, the
ICESat-II will have a different Lidar sensor type to ICESat-I (that was
ability of airborne sensor platforms—from an airplane
a waveform Lidar; ICESat-II will be a photon-counting Lidar, which
emits photons and measures their return travel time and thus range. or helicopter—for rapid deployment, high spatial
In short, the resultant data will be noisier and therefore require resolution data acquisition, and highly accurate DEM
additional processing, while the sampling will also lend itself to and derivative data, often trump the corresponding
accurate, but sparse data sets. It thus follows that these data will spaceborne products. It is worth mentioning, however,
be sparse, perhaps too sparse for a global high resolution DEM,
that DEM products that cover the entire globe are still
even though the accuracy is high enough for reliable mapping
extremely useful, even if at lower spatial resolution
of ice sheet elevation changes. Spaceborne radar sensors, on the
other hand, have been in use for a while to generate global ground and accuracy.
and vegetation height profiles.
How DEMs Are Created: A Brief Introduction to Remote Sensing Modalities 63
Figure TA3. A global vegetation canopy height model, derived from ICESat-I data. Although the
coverage is valuable, the spatial resolution of 1 km makes it useful for more regional type analyses.
Source: NASA/JPL-Caltech; www.nasa.gov
Spaceborne Lidar
Spaceborne Lidar sensors are scarce, mainly due to the technical challenges of launching and operating a
precision laser ranging instrument in space. Not only is the laser operation itself challenging, due to the
mechanical-optical components, but the power requirements are also restrictive. The U.S. National Aeronautics
and Space Administration (NASA) is the only agency thus far that has launched and operated spaceborne Lidar
ranging systems, with the main goal of measuring arctic elevation changes as they relate to global climate change.
The two relevant missions are ICESat-I and ICESat-II. (Figure TA3)
Spaceborne SAR (and IfSAR)
Canada and Germany are the main players in the global radar-based DEM product market. Canada has launched and
maintained their RADARSAT suite of two remote sensing satellites, RADARSAT-1 and RADARSAT-2. RADARSAT-2,
currently in operation, provides Earth observation
data supporting applications such as ice monitoring, Example: temporal coverage & accuracies of RADARSAT-2
marine surveillance, disaster management, hydrology, (typical radar instrument)
general mapping, geology, and agriculture. The
RADARSAT-2 satellite orbits the Earth 14 times a However, coverage via the complete 500 km swath (ground coverage
width) is daily north of 70°, 1–2 days between 48°–70°, and 2–3 days
day, taking 24 days to complete one entire orbit cycle
at the equator. Spatial resolution is a claimed 1–3m in the spotlight,
(‘repeat visit cycle’), covering a 500 km-wide swath tasked mode, but varies across the scanning modes. Finer resolutions
of the planet. The ‘temporal resolution’ (the time can be achieved in “spotlight” mode, although this is not ideal for
between repeat images) is also 24 days, the same an large area mapping. Horizontal accuracies are also relatively coarse,
entire orbit cycle. at 100m horizontal requirements (better accuracies, e.g., meter-level,
can be achieved via post-processing), although vertical accuracies at
the millimeter-level have been claimed when using interferometry.
64 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
The German TerraSAR-X radar Figure TA4. An example of the SRTM DEM data set, in this case
satellite and follow-up TanDEM-X at 30m spatial resolution, with a road network overlaid.
twin-satellite missions also
deserve special mention. These
two spaceborne platforms fly
in close formation to form a
spaceborne high-precision ‘radar
interferometer,’ combining
imagery collected over time by
radar, with the primary mission of
generating a global WorldDEM™
dataset (trademark of Astrium;
Airbus Group), notable for its high
quality and accuracy, exceeding the
specifications of other satellite-
based DEMs. Specific strengths,
listed by the provider, are:
Source: www.opentopography.org.
• Vertical accuracy of 2m
(relative)/10m (absolute) at 12x12m spatial resolution
• Global homogeneity and consistency due to data being collected within a 2.5 year cycle; also seamless coverage
with no breaklines
• Geometric precision of the sensors negate the need for ground control information
• Reliable data acquisition due to the ability of these kinds of sensors’ to operate independent of cloud coverage
and lighting conditions
As mentioned, remote sensing at the spaceborne level lends itself more to global, continental, and even regional
mapping rather than fine-scale applications requiring a higher spatial resolution. WorldDEM™ remains a
benchmark technology, however, and its ability to generate expansive and accurate DEM datasets has led to its
widespread use in global topography mapping applications and generation of ortho-imagery.
However, the most complete and highest resolution global digital elevation models of the Earth have been
produced by the Shuttle Radar Topography Mission (SRTM). An international collaborative effort, a modified
SAR system was first installed on board a NASA space shuttle mission in the year 2000. The system acquired SAR
data and covered roughly eighty percent of the Earth’s surface, between 56°S–60°N, at 90m spatial resolution
(30m for the U.S.). Figure TA4 shows an example of a SRTM DEM image. STRM Version 2 (with well-defined
water bodies and coastlines, and noise removal) and Version 3 (additional reduction in void areas) are widely
used for regional topographic assessments and the generation of orthophotography. Its relatively coarse spatial
resolution negates usage in most undulating or high variable topographies.
Spaceborne Photogrammetry
The photogrammetric process is time-consuming and requires significant processing. Two notable efforts,
creating DEMs from spaceborne imaging (“digital photo”) platforms, are Astrium’s Satellite for the Observation
of Earth (SPOT) and the ASTER sensor’s Global Digital Elevation Model (GDEM). Both collect stereo imagery
and generate an elevation for each pixel based on stereoscopic principles (relief displacement and parallax).
How DEMs Are Created: A Brief Introduction to Remote Sensing Modalities 65
Each elevation is on a per-pixel Figure TA5. A SPOT DEM product exaggerated in 3D to show the
basis but only for the top-most or detail available from this approach.
visible surface, even though DEMs
can be generated based on ground
surface extractions and associated
interpolation techniques.
The SPOT series of satellites are
now in their 6th active generation.
Most stereo-processing is based
on the SPOT-5 satellite, however,
because it has a panchromatic “High
Resolution Stereoscopy” (HRS)
instrument on board. The HRS Source: http://www.cnes.fr & SPOT 5 HRS.
stereo imagery advantages include:
consistent imagery brightness, resultant image products at high spatial resolution, and in full spectrum color, as
opposed to only panchromatic (black-and-white) imagery. The HRS can point both forwards and backwards relative
to the satellite’s ground track, enabling the rapid and efficient collection of stereopairs of imagery and associated
stereo-photogrammetric applications. The DEM post-spacing (spatial resolution) is approximately 30m at the
equator, based on a resampled 20m product. The accuracies are claimed at 15–30m horizontal (x,y) and 10–20m
vertical (elevation). Among additional benefits of these kinds of spaceborne DEMs and modalities are that they can
be tasked for specific areas. But, as stated above, for coverage of large areas, data is for the top-most surface only,
with no vegetation canopy penetration. Figure TA5 shows an example of a SPOT DEM.
The GDEM product, derived from the Japanese ASTER satellite, also deserves mention. The ASTER GDEM
was released in 2009 with coverage spanning 83°N-83°S, at 30 m spatial resolution, encompassing ninety-nine
percent of the Earth’s surface. It was generated from more than 1.3 million visible-near-infrared (VNIR) images
collected by the ASTER satellite. However, significant artifacts and height errors have been reported that
decrease the quality and elevation accuracy. NASA has noted that the current GDEM product should be regarded
as “research grade.”
In conclusion, the diversity of remote sensing modalities used to generate DEM products presents a breadth of
choices, each with their relative strengths and weaknesses. Spaceborne platforms offer accessibility and coverage,
but at the cost of spatial resolution and horizontal and vertical accuracy, making them especially useful for large
areas (regional-to-continental mapping, hydrology, and other large area needs) and for use with turnkey DEM
applications. Airborne platforms, in contrast, have much higher accuracy, but sacrifice coverage and accessibility
in very remote areas. Lidar offers dense point clouds, vegetation-penetrating abilities, and multiple secondary
applications. Radar also offers vegetation penetration, but lower spatial resolution and higher processing needs.
Stereo photography offers context through imagery, but lower spatial resolution and only topmost surface heights.
Globally Available (“off-the-shelf”) DEMs
One of the benefits of spaceborne sensor platforms is that they enable the collection of global data products.
Examples of this include the MODIS (Moderate Resolution Imaging Spectrometer) global vegetation cover
products, the Landsat and SPOT satellite series land cover and DEM products, respectively, and the ICESat-1
global canopy height model. Readily available global DEMs exist as well, though often the spatial resolution
66 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
is not amenable to fine-scale applications and, where high spatial resolution products do exist, they are
typically very expensive. Some of these global DEM products have been discussed in previous sections, and are
highlighted below.
• NASA Satellite Radar Topography Mission (SRTM) DEM. A free global DEM, the STRM is available at a nominal
spatial resolution of 90m (30m within the U.S.). The SRTM effort was an international collaborative effort
where a modified SAR system installed on board a NASA space shuttle mission (2000) acquired SAR data and a
resultant DEM for areas between 56°S-60°N: www2.jpl.nasa.gov/srtm/
• Airbus Defence and Space WorldDEM. This is a continuous, exhaustive coverage DEM product, developed by
Airbus Defence and Space, at 12m spatial resolution (4m absolute vertical accuracy reported). The base data
were collected by the radar satellites TanDEM-X and TerraSAR-X to generate a global homogeneous DEM. The
price varies, with quotations tailored based on required editing, coverage, use, and so forth: www.astrium-geo.
com/en/168-tandem-x-global-dem
• United States Geological Survey (USGS) GMTED2010 DEM. This “Global Multi-resolution Terrain Elevation
Data, 2010” DEM was produced by the USGS in 2011 using the “current best available” global elevation data
from public domain sources. It varies in spatial resolution, with different areas at 30-, 15-, and 7.5-arc-second
resolution: http://topotools.cr.usgs.gov/gmted_viewer/
• ASTER Global Digital Elevation Map (GDEM). This is a 30m spatial resolution DEM created via stereoscopy
from 1.3 million ASTER scenes between 83°N–83°S latitudes. It is delivered in 1°x1° tiles as GeoTIFF files.
The quality of this DEM varies, e.g., though nominal elevation postings approximate 30m, only topographical
features between 100–120m in size can be resolved (visually detected), along with other artifacts: http://
asterweb.jpl.nasa. gov/gdem.asp
• National Oceanic and Atmospheric Administration (NOAA) GLOBE DEM. An updated version of the USGS
GTOPO30 DEM data set, this DEM is available in 30 arc second (approximately 1km) tiles. Although the user
can readily specify an area of interest, the data is in a rather rudimentary raw binary format (with a separate
header file): http://www.ngdc.noaa.gov/mgg/topo/globe.html
• INTERMAP’s NEXTMap World30 DEM. A 30m ground sampling DEM, for which INTERMAP has aggregated
ASTER, SRTM, and GTOPO DEM products to generate a gap-filled (no voids) DEM. Advertised prices are as low
as US$0.01/km2: http://intermap.com/en-us/databases/world30.aspx
• LAND INFO Worldwide Mapping, LLC DEM. This company offers international maps and GIS map products, at
costs as high as US$600/1° quad: www.land info.com
• Airbus Defence and Space SPOT satellite DEMs. The SPOT satellite affords overlap between images and enables
extraction of DEM products from the overlap area. A SPOT DEM consists of gridded file at 1 arc second steps,
which equates to approximately 30m at the equator, and varies by latitude. Most SPOT DEM products are
resampled to 20m spatial resolution: http:/astrium-geo.com/en/2790-elevation30-dem-spot-dem
This list represents just a sample of available global DEMs or DEM products, either free or at cost. It is worth
noting, however, that in most instances the spatial resolution specified by agencies or vendors is best suited
to landscape analyses, possibly regional analyses. The WorldDEM product at 12m spatial resolution may be
useful for many applications, even at fine scales. In practice, however, most of the DEM applications discussed
in Chapter 2 of the main document (e.g., water resource management, disaster preparedness, agriculture, etc.)
require a finer spatial resolution than even the best global products can provide. Exceptions include selected
applications in forestry, ecology, and even urban analysis, where a 12m DEM may prove useful for height-above-
ground calculations. Fine-scale applications such as hydrology, on the other hand, will benefit from high spatial
resolution, local DEM products.
Annex B
Sample
NDEP Metadata
Guidelines forfor DEM
Digital Elevation DataDigital Elevation Model Technologies and Applications: The DEM
– taken from
Users Manual
Part 1 Content , 2nd
Edition published in 2007 by the American Society for Photogrammetry and Remote
Sensing (ASPRS, 2007).
T able 1 User R equir ements M enu
G ener al Sur face Descr iption (choose one or more)
E levation Sur face (1.2.1) E levation T ype (choose one) (1.2.2)
Digital surface model (first reflective surface) Orthometric height
Digital terrain model (bare earth) Ellipsoid height
Bathymetric surface Point cloud Other ________________
Mixed surface
M odel T ypes (1.3) (choose one or more) * Designate either feet or meters
Mass points Grid (post spacing = ___ feet/meters) * Contour interval = _____ft /m *
Breaklines Grid (post spacing = ____ arc-seconds) Cross Sections
TIN (average point spacing = ___ feet/meters) * Other (For example, concurrent
image capture)
Sour ce (1.4) (choose one)
Cartographic Photographic IFSAR LIDAR Sonar
If Multi-return system:
First return Last return All returns
V er tical A ccur acy (1.5.1.1) (choose one)
Fundamental Vertical Accuracyz = __ (ft or meters) at 95 percent confidence level in open terrain = RMSEz x
1.9600
Supplemental Vertical Accuracyz = __ (ft or meters) = 95th percentile in other specified land cover categories
Consolidated Vertical Accuracyz = __ (ft or meters) = 95th percentile in all land cover categories combined
H or izontal A ccur acy (1.5.1.2) (choose one)
Accuracyr = ___ ft or meters
Horizontal accuracy at the 95 percent confidence level (Accuracyr) = RMSEr x 1.7308
Sur face T r eatment F actor s (1.5.4) (optional refer to the text)
Hydrography Artifacts
Man-made structures Special Surfaces
Special earthen surfaces
H or izontal Datum (1.6.1) (choose one) V er tical Datum (1.6.2) (choose one)
NAD 83 (default) NAVD 88 (default) MSL
WGS 84 MLLW Other _____
G eoid M odel (1.6.3) (choose one) GEOID03 Other _____
C oor dinate System (1.7) UTM zone ______ State Plane zone ______
(choose one) Geographic Other _____
Units (1.7) Note: For feet and meters, vertical (V) units may differ from horizontal (H) units
Feet to ___ decimal places V H Decimal degrees to ___ decimal places
Meters to ___ decimal places V H DDDMMSS to ___ decimal places
Feet are assumed to be U.S. Survey Feet unless specified to the contrary
Data F or mat (1.8) (Specify desired format(s) for each Product Type. See text for examples.)
Product 1 ______________________ Formats __________________________________________________
Product 2 ______________________ Formats __________________________________________________
Product 3 ______________________ Formats __________________________________________________
F ile size (1.9) (specify acceptable range) ___________ Mb / Gb / Other _________
F ile E xtent
Boundary: ____________Rectangular________________ _________NonRectangular__________
x-dimension _____ m / ft. / degrees / other ___ Bndry name ______________________
y-dimension _____ m / ft. / degrees / other ___ Coordinate source _________________
Over-edge buffer width: _____________________________
M etadata compliant to the C ontent Standar ds for Digital G eospatial M etadata is highly
r ecommended.
67
8
Annex C
World Bank
Spatial Data
Metadata
Standard
World Bank Geographic Metadata Standards Quick Guide
Last Updated: May 18, 2009
The World Bank Geographic Metadata Standards are based on ISO 19115:2003 Geographic Metadata Standards.
This quick guide is designed to help World Bank users uploading data to the World Bank Spatial Data Repository,
found by typing “Spatial” into a World Bank web browser.
Please note that the organization of the metadata form is expected to change slightly in the future to better
facilitate data entry. This document will be updated and redistributed at that time.
Summary of Mandatory and Optional Metadata Fields
Section 1: Identification
Title Mandatory
Date Mandatory
Date Type Mandatory
Edition Optional
Presentation Form skip
Abstract Mandatory
Purpose Optional
Status skip
69
70 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Section 2: Point of Contact
Individual Name Mandatory – record either Individual or
Organization Name organization name
Position Name Optional
Voice Optional
Facsimile Optional
Delivery Point Optional
City Optional
Administrative Area Optional
Postal Code Optional
Country Optional
Electronic Mail Address Optional
Role Mandatory
Maintenance & Update Frequency Optional
Section 3: Descriptive Keywords
Keyword Optional
Keyword Type skip
Country & Regions Mandatory
Access Constraints skip
Use constraints Mandatory
Other constraints Optional
Spatial Representation Type Optional
Section 4: Equivalent Scale
Denominator skip
Language Mandatory
Character set skip
Topic Category Code Mandatory
Denominator skip
Language Mandatory
Character set skip
Topic Category Code Mandatory
Section 5: Temporal Extent
Identifier skip
Begin Date Optional
End Date Optional
Geographic Bounding Box Mandatory
Supplemental Information Mandatory
World Bank Spatial Data Metadata Standard 71
Section 6: Distribution Info
Online Resource Optional
URL Optional
Protocol skip
Description Optional
Section 7: Reference System Info
Code skip
Section8: Data quality info
Hierarchy Level skip
Statement Optional
Section 9: Metadata Author
Individual Name Mandatory – record either individual or
Organization Name organization name
Position Name Optional
Voice Optional
Facsimile Optional
Delivery Point Optional
City Optional
Administrative Area Optional
Postal Code Optional
Country Optional
Electronic Mail Address Optional
Role Optional
[M] = Mandatory [O] = Optional
Section 1: Identification
Title [M]: Name by which the dataset is known and should be cited. At a minimum, the name should indicate
where, what, and when.
Date [M]: Reference date for the cited dataset
Date Type [M]: Event used for reference date. Drop down options are:
• creation (identifies when the dataset was brought into existence)
• publication (identifies when the dataset was issued)
• revision (indentifies when the dataset was examined and improved or amended)
72 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
Edition [O]: Version of the cited dataset
Abstract [M]: Brief narrative summary of the content of the resource(s)
Purpose [O]: Short description of the project for which this dataset was created or used
Section 2: Point of Contact
Individual Name [M]: Name of the responsible person – surname and given name
Organization Name [M]: Name of the responsible organization
Position Name [O]: Role or position of the responsible person
Voice [O]: Phone number
Facsimile [O]: Fax number
Delivery Point [O]: Street or PO address City [O]
Administrative Area [O]: i.e. state, province, district Postal Code [O] Country [O]
Electronic Mail Address [O]: email
Role [M]: Function performed by the responsible party. Drop down options are:
• datasetProvidor (party that supplies the dataset)
• custodian (party that accepts accountability and responsibility for the data and ensures appropriate care and
maintenance of the dataset)
• owner (party that owns the dataset)
• user (party who uses the dataset)
• distributor (party who distributes the dataset)
• originator (party who created the dataset)
• pointOfContact (party who can be contacted for acquiring knowledge about or acquisition of the dataset)
• principalInvestigator (key party responsible for gathering information and conducting research)
• processor (party who has processed the data such that the dataset is modified)
• publisher (party who published the resource)
• author (party who authored the resource)
Maintenance and Update Frequency [O]: Specify the frequency with which the dataset is updated. Drop down
options are:
• annually (data is updated each year)
• asNeeded (data is updated as deemed necessary)
• biannually (data is updated twice each year)
• continual (data is repeatedly and frequently updated)
• daily (data is updated each day)
• fortnightly (data is updated every two weeks)
• irregular (data is upated in intervals that are uneven in duration)
• monthly (data is updated each month)
• notPlanned (there are no plans to update this data)
• quarterly (data is updated every three months)
• unknown (frequency of maintenance for the data is unknown)
• weekly (data is updated on a weekly basis)
World Bank Spatial Data Metadata Standard 73
Section 3: Descriptive Keywords
Keyword [O]: Commonly used word(s) or phrase(s) used to describe the subject
Country or Region [M]: Choose the country or region from the drop down menu associated with the dataset
Use constraints [M]: Constraints applied to assure the protection of privacy or intellectual property, and any
special restrictions or limitation or warning on using the resource or metadata. Drop down options are:
• copyright (exclusive right to the publication, production, or sale of the rights to a literary, dramatic, musical,
or artistic work, or to the use of a commercial print or label, granted by law for a specified period of time to an
author, composer, artist, distributor)
• intellectualPropertyRights (rights to financially benefit from and control distribution of non – tangible property
that is a result of creativity)
• license (formal permission to do something)
• otherRestrictions (limitation not listed)
• patent (government has granted exclusive right to make, sell, use or license an invention or discovery)
• patentPending (produced or sold information awaiting a patent)
• restricted (withheld from general circulation or disclosure)
• trademark (a name, symbol, or other device identifying a produce, officially registered and legally restricted to
the use of the owner or manufacturer)
Other constraints [O]: If “otherRestrictions” is selected from the above drop down menu, describe other
restriction and legal prerequisites for accessing and using the resource or metadata
Spatial Representation Type [O]: Methods used to spatially represent geographic information. Drop down
options are:
• grid (raster)
• stereoModel (stereophotogrammetry imagery)
• textTable (tabular, non spatial data)
• tin (Triangulated Irregular Network data used in 3D surface model)
• vector (points, lines, polygons)
Section 4: Equivalent Scale
Language [M]: From the drop down menu, choose the language used within the dataset
Topic Category Code [M]: Specify the main ISO category(ies) through which your map or data could be
classified. Drop down options are:
• biota (flora and/or fauna in natural environments)
• boundaries (legal land descriptions)
• climatologyMeteorologicalAtmosphere (processes and phenomena of the atmosphere)
• economy (economic activities, conditions, and employment)
• elevation (height above or below the earth’s surface)
74 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
• environment (environmental resources, protection, and conservation)
• farming (rearing of animals and/or cultivation of plants)
• geoscientificInformation (information pertaining to the earth sciences)
• health (health, health services, human ecology, and safety)
• imageryBaseMapsEarthCover (base imagery)
• inlandWaters (inland water features, drainage systems and characteristics)
• intelligenceMilitary (military bases, structures, activities)
• location (positional information and services)
• oceans (features and characteristics of salt water bodies)
• planningCadastre (information used for appropriate future use of the land)
• society (characteristics of society and culture, including demographics)
• structure (man – made construction)
• transportation (means and aids for conveying persons and/or goods)
• utilitiesCommunication (energy, water and waste systems, and communications infrastructure)
Section 5: Temporal Extent
Begin Date [O]: Starting date of dataset date range End Date [O]: Ending date of dataset date range
Geographic Bounding Box [M]: Choose a region or country to automatically populate the geographic extent of
the dataset
Supplemental Information [M]: In the future, “Classification” will be added to this form as a MANDATORY
field. Until then, restrictions on the handling of the dataset will be recorded in this field. Please type one of the
following:
• unclassified (available for general disclosure)
• restricted (not for general disclosure)
• confidential (available to someone who can be entrusted with information)
• secret (kept or meant to be dept private, unknown, or hidden from all but a select group of people)
• topSecret (of the highest secrecy)
• Further supplemental information is OPTIONAL. You might also include:
• place information that is not elsewhere covered
• ‘front’ important information such as related studies, data set limitations, and notifications
Section 6: Distribution Info
Online Resource [O]: Link to a website where the dataset can be downloaded, or users can learn more about the
dataset.
URL [O]: Uniform Resource Locator (URL) address such as http://www.worldbank.org Description [O]:
Description of what the online resource is/does
Section 7: Reference System Info
Not applicable. Skip.
World Bank Spatial Data Metadata Standard 75
Section 8: Data quality info
Statement [O]: A general explanation about the lineage of the dataset
Section 9: Metadata Author
Individual Name [M]: Name of the responsible person – surname and given name
Organization Name [M]: Name of the responsible organization
Position Name [O]: Role or position of the responsible person
Voice [O]: Phone number
Facsimile [O]: Fax number
Delivery Point [O]: Street or PO address City [O]
Administrative Area [O]: i.e. state, province, district Postal Code [O] Country [O]
Electronic Mail Address [O]: email, preferably World Bank email
Role [O]: Function performed by the responsible party. Drop down options are:
• datasetProvidor (party that supplies the dataset)
• custodian (party that accepts accountability and responsibility for the data and ensures appropriate care and
maintenance of the dataset)
• owner (party that owns the dataset)
• user (party who uses the dataset)
• distributor (party who distributes the dataset)
• originator (party who created the dataset)
• pointOfContact (party who can be contacted for acquiring knowledge about or acquisition of the dataset)
• principalInvestigator (key party responsible for gathering information and conducting research)
• processor (party who has processed the data in a manner such that the dataset has been modified)
• publisher (party who published the resource)
• author (party who authored the resource)
Annex D 77
Annex D
Example End User
License Agreement
(EULA)
Source: DigitalGlobe A NNEX D
Example End User License Agreement
https://www.digitalglobe.com//sites/default/files/end_user_license_agreement.pdf (EULA)
Source: DigitalGlobe
https://www.digitalglobe.com//sites/default/files/end_user_license_agreement.pdf
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Elevation
Digital(US) meanings. Models – A Guidance Note on How Digital Elevation Models Are Created and Used
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b. Customer Group.
i. one individual;
ii. one company, corporation, or similar legal entity (excluding affiliates or subsidiaries which will be treated as a
separate Customer Group);
iii. one subsidiary or affiliate of an entity;
iv. one department of a federal agency at the U.S. Cabinet level (e.g., office of the U.S. Dept. of Agriculture of U.S.
Dept. of Interior, but excluding sub-agencies);
v. one civilian federal agency below the U.S. Cabinet level;
vi. one department of the four branches of the military, a defense agency, one of the unified commands, one of the non -
Dept. of Defense entities identified in 50 U.S.C. Section 401a or the State Department;
vii. one department of a foreign military or an international defense or intelligence agency;
viii. one state or provincial agency;
ix. one county or local government;
x. one non-governmental organization or non-profit organization;
xi. one department within a single educational organization within a single country;
xii. one international agency such as NATO, but excluding the United Nations and the European Union;
xiii. one office or department within the United Nations or the European Union; or
xiv. any one entity equivalent to any of the entities listed above, located outside the United States.
c. Demonstration Purpose. Any non-Commercial Purpose for demonstration, promotional or training purposes for a period
of no more than 90 days from Product shipment.
d. Derivative. Any addition, improvement, update, modification, translation, transformation, adaptation or derivative work of
or to the Product, authored, created or developed by or on behalf of You, including, without limitation, any reformatting of
the Product into a different format or media from which it is delivered to You, any addition of data, information or other
content to the Product, or any copy or reproduction of the Product.
e. Educational Purpose. Any non-Commercial Purpose undertaken for study or research solely in furtherance of education.
f. Federal Civil Government Agency. Any government agency at the federal level, EXCLUDING all U.S. Department of
Defense agencies and those agencies defined under U.S. Code Title 50. The U.S. Army Corp of Engineers is included in
the definition of Federal Civil Government Agency under th is Agreement.
g. Fees. The fees set forth in Your Confirmation.
h. Joint Project. An undertaking between You and one or more other Customer Groups based on a contractual relationship
existing as of the Effective Date.
i. Purpose. As may be indicated i n Your Confirmation, Demonstration Purposes or Educational Purposes.
j. State and Local Government Agency. Any government agency at the state and local level. With regard to the United
States, the term “state” includes the 50 United States and the United States’ territories and possessions.
k. User. Employees or contractors of You or, as applicable, a Customer Group.
2. Grant of License. Subject to Your compliance with the terms and conditions of this Agreement, including, without limitation,
payment of all applicable Fees, DigitalGlobe grants to You a non -exclusive, non-transferable, limited license to allow the
number of Users identified on Your Confirmation to access, reproduce, store, display and create Derivatives of the Product ,
solely for the Purpose indicated in Your Confirmation or, if no Purpose is indicated in Your Confirmation, solely for Your own
internal business purposes.
a. If You are not a Federal Civil Government Agency or a State and Local Government Agency, You ma y post the Product
and Derivative on Your website at a resolution no better than 10 meters in a static, non -downloadable, non-distributable,
non-interactive fashion and in a manner that does not allow a third party to extract or access the Product as a sta ndalone
file;
b. If You are a Federal Civil Government Agency, You may post the Product and Derivative to publicly accessible Internet
web sites provided that: (a) the quality of the image data available for download is presented in a color composite jpeg or
a 50:1 compressed file format without associated geospatial information; and (b) the Product or Derivative posted to
publicly accessible websites is in a secure format that allows printing and viewing at no better than ten meter resolution.
The Product and any Derivatives may be posted to secure Intranet websites and may be used only for the purposes of a
Joint Project and subject to Section 3;
c. If You are a State and Local Government Agency, You may post the Product and any Derivatives on Your website at f ull
resolution for non-Commercial Purposes, in a non-downloadable, non-distributable fashion, and in a manner that does not
allow a third party to extract or access the Product as a standalone file;
3. Sublicense . Subject to Your compliance with the terms and conditions of this Agreement, including, without limitation,
payment of all applicable Fees, You may grant sublicenses of the rights granted to You under Section 2 to access, reproduce,
store, and display the Product to Customer Groups engaged in a Joint Project with You solely for the internal business
purposes of the Customer Group in completing the Joint Project with You. All Customer Groups will be identified by You and
confirmed by DigitalGlobe (on Your Confirmation or otherwise) in advance of any sublicense by You. The number of permitted
Users within each Customer Group sublicensed hereunder will be limited to the type of license You have purchased as follows:
Type of License Purchased Number of Permitted Users Within
Sublicensed Customer Group
Base Up to 5
Group From 6 to 10
Enterprise From 11 to 25
Enterprise Premium More than 25
Educational 1
Demonstration 1
If the number of individuals of a sublicensed Customer Group using or accessing the Product exceeds the number of Users
permitted under this Section 3, the Customer Group will be counted as multiple sublicensees based on the number of
individuals using the Product, for purposes of determining compliance with the table above. If a sublicensed Customer Group
is involved in multiple Joint Projects with You, the Customer Group will be counted as multiple sublicensees based on the
number of Joint Projects involved for purposes of determining compliance with the table above. Each sublicense must require
the sublicensee to agree to be bound by this Agreement. You will remain responsible for any noncompliance by any
sublicensee and sublicensee’s breach of this A greement shall be deemed to be Your breach of this Agreement.
4. Restrictions . You recognize and agree that the Product is the property of DigitalGlobe and contains valuable assets and
proprietary information of DigitalGlobe. Accordingly, except as expressly permitted in Sections 2 or 3, You will not, and will not
permit any User or third party to: (a) publish, transmit, reproduce, create Derivatives of or otherwise utilize the Product in any
form, format or media; (b) merge the Product with any other data , information or content; (c) reverse engineer or otherwise
Group From 6 to 10
Enterprise From 11 to 25
Enterprise Premium More than 25
Educational 1
79
Demonstration 1
If the number of individuals of a sublicensed Customer Group using or accessing the Product exceeds the number of Users
permitted under this Section 3, the Customer Group will be counted as multiple sublicensees based on the number Annexof D
individuals using the Product, for purposes of determining compliance with the table above. If a sublicensed Customer Group
is involved in multiple Joint Projects with You, the Customer Group will be counted as multiple sublicensees based on the
number of Joint Projects involved for purposes of determining compliance with the table above. Each sublicense must require
the sublicensee to agree to be bound by this Agreement. You will remain responsible for any noncompliance by any
sublicensee and sublicensee’s breach of this A greement shall be deemed to be Your breach of this Agreement.
4. Restrictions . You recognize and agree that the Product is the property of DigitalGlobe and contains valuable assets and
proprietary information of DigitalGlobe. Accordingly, except as expressly permitted in Sections 2 or 3, You will not, and will not
permit any User or third party to: (a) publish, transmit, reproduce, create Derivatives of or otherwise utilize the Product in any
form, format or media; (b) merge the Product with any other data , information or content; (c) reverse engineer or otherwise
attempt to derive the algorithms, databases or data structures upon which the Product is based; (d) distribute, sublicense, r ent,
lease or loan the Product; (e) use the Product for the business ne eds of any third person or entity, including without limitation,
providing any services to any third parties; (f) remove, bypass or circumvent any electronic or other forms of protection
measure included on or with the Product; (g) alter, obscure or remove any copyright notice, copyright management information
or proprietary legend contained in or on the Product; or (h) otherwise use or access the Product or any Derivatives for any
purpose not expressly permitted under this Agreement, including, without lim itation, for Commercial Purposes. All Products or
Derivatives must contain the following copyright notice conspicuously displayed in connection with the Product or Derivative
Work: “© DigitalGlobe, Inc. All Rights Reserved” for the Product, and “Includes copyrighted material of DigitalGlobe, Inc., All
Rights Reserved” for Derivatives. You acknowledge that You need to obtain a separate distribution license from DigitalGlobe
in order to distribute or publish the Product or any Derivative Work in any form n ot expressly permitted under Section 2 or 3.
5. Ow nership. The Product, and all worldwide intellectual property and proprietary rights therein and related thereto, including,
without limitation, all patents, copyrights, trademarks, trade secrets, moral rig hts, sui generis rights and other right in
databases, and all rights arising from or pertaining to the 2foregoing rights, are and will remain the exclusive property of
DigitalGlobe and its suppliers. All rights in and to the Product not expressly granted t o You are reserved by DigitalGlobe and
its suppliers. This Agreement does not grant You title to the Product or any copies of the Product. Any rights of Customer in
any Derivative do not provide Customer with any rights in or to any Product used or incorporated in that Derivative except as
granted under this Agreement.
6. Confidentiality. The Product includes metadata and other confidential and proprietary information of DigitalGlobe
(“Confidential Information”). You will not use any Confidential Information for any purpose not expressly permitted hereunder
and will disclose Confidential Information only to Your employees and permitted sublicensees who have a need to know for
purposes of this Agreement and who are under a duty of confidentiality no less restrictive than Your duty hereunder. You will
protect the Confidential Information from unauthorized use, access, or disclosure in the same manner as You protect Your own
confidential or proprietary information of similar nature and with no less than reasonable care.
7. Audit. At DigitalGlobe’s request, You will provide assurances acceptable to DigitalGlobe that You are using the Product
consistent with the terms of this Agreement. Upon notice, DigitalGlobe ma y inspect Your records, accounts and books relating
to the use of the Product to ensure that the Product is being used in accordance with this Agreement.
8. Term and Termination. This Agreement remains in full force until terminated as provided below. Dig italGlobe has the right to
terminate this Agreement, effective immediately upon notice to You, if You breach any provision of this Agreement. Upon
termination of this Agreement, all rights granted to You hereunder shall immediately cease and You and Your sublicensees
will: (a) discontinue all use of the Product; (b) if the Product was delivered on a tangible medium, return to DigitalGlobe t he
Product and all copies thereof; (c) purge all copies of the Product or any portion thereof from all computer storag e devices or
medium on which You have placed or permitted others to place the Product; and (d) give DigitalGlobe a written certification
that You have complied with all of Your obligations hereunder.
9. Limited Warranty; Disclaimer . DigitalGlobe warrants that, for a period of 30 days after Your receipt of the Product, the
Product will p erform substantially i n a ccordance with its applicable specifications. DigitalGlobe’s sole obligation and Your
entire remedy for breach of the above warranty is for DigitalGlobe, at its sole option and expense, to: (a) repair or replace the
non-conforming Product returned during the warranty period; or (b) refund all fees paid by You for the non -conforming Product
returned during the warranty period. This limited warranty is void if any non-conformity has resulted from any accident, abuse,
misuse, misapplication, or modification of or to the Product or any breach of this Agreement. E XCEPT AS EXPRESSLY PROVIDED
IN THIS S ECTION 9, ALL P RODUCT IS PROVIDED “AS IS” WITHOUT ANY REPRESENTATIONS OR WARRANTIES OF ANY KIND AND ALL
WARRANTIES, WHETHER EXPRESS OR IMPLIED , ORAL OR WRITTEN , ARISING BY LAW OR OTHERWISE, ARE EXPRESSLY DISCLAIMED AND
EXCLUDED BY DIGITALGLOBE, INCLUDING, WITHOUT LIMITATION ALL IMPLIED WARRANTIES OF MERCHANTABILITY, TITLE, NON -
INFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE. DIGITALGLOBE DOES NOT WARRANT THAT THE P RODUCT WILL BE
ACCURATE, CURRENT OR COMPLETE, THAT THE P RODUCT WILL MEET Y OUR NEEDS OR EXPECTATIONS, OR THAT THE OPERATION OF
THE P RODUCT WILL BE ERROR FREE OR UNINTERRUPTED . DIGITALGLOBE PROVIDES ALL CONTENT AS A SERVICE TO Y OU. S PATIAL,
SPECTRAL, AND TEMPORAL ACCURACY CANNOT BE GUARANTEED. DIGITALGLOBE RESERVES THE RIGHT, AT ITS SOLE DISCRETION, TO
MODIFY CERTAIN IMAGE CHARACTERISTICS OF THE CONTENT INCLUDING, BUT NOT LIMITED TO, WATERMARKING AND DIMENSIONS.
10. Limitation of Liability. IN NO EVENT WILL DIGITALGLOBE OR ITS SUPPLIERS BE LIABLE FOR ANY INCIDENTAL, CONSEQUENTIAL,
SPECIAL, EXEMPLARY, OR INDIRECT DAMAGES (INCLUDING LOST PROFITS OR LOST DATA) ARISING FROM , OR RELATING TO, THIS
AGREEMENT OR THE P RODUCT, EVEN IF DIGITALG LOBE OR ITS SUPPLIERS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
DIGITALGLOBE AND ITS SUPPLIERS’ TOTAL CUMULATIVE LIABILITY IN CONNECTION WITH THIS A GREEMENT AND THE P RODUCT,
WHETHER IN CONTRACT OR TORT OR OTHERWISE, WILL NOT EXCEED THE AMOUNT OF FEES PAID TO DIGITALG LOBE FOR THE P RODUCT.
T HIS S ECTION 10 SHALL BE GIVEN FULL EFFECT EVEN IF THE WARRANTY PROVIDED IN SECTION 9 IS DEEMED TO HAVE FAILED OF ITS
ESSENTIAL PURPOSE.
11. Indemnification. You will indemnify, defend, and hold harmless DigitalGlobe and its subsidiaries, affiliates and
subcontractors, and their respective owners, officers, directors, employees and agents, from and against any and all direct o r
in direct claims, damages, losses, damages, liabilities, expenses, and costs (including reasonable attorneys’ fees) arising from
or out of: (1) Your use of the Product for any purpose; (2) Your actual or alleged breach of any provision of this Agreement; or
(3) damage to property or injury to or death of any person directly or indirectly caused by You. DigitalGlobe will provide You
with notice of any such claim or allegation, and DigitalGlobe has the right to participate in the defense of any such claim a t its
expense.
12. Export Control . You will comply with all applicable export control laws, rules and regulations.
13. Additional Terms .
a. You acknowledge that any actual or threatened breach of Section 2, 3, 4, or 6 will constitute immediate and irreparable
harm to DigitalGlobe for which monetary damages would be an inadequate remedy. Therefore, without limiting any other
remedy available at law or in equity, upon any such breach or any threat thereof, DigitalGlobe will be entitled to seek
injunctive relief against You as remedy for such breach. To the fullest extent not prohibited by applicable law, any action
brought for such relief may be brought by DigitalGlobe upon ex parte application and without notice or posting of any
bond, and You expressly waive any requirement for notice or the posting of any bond. If any action is brought to enforce
this Agreement, the prevailing party will be entitled to receive its reasonable attorney’s fees, court costs, and other
collection expenses, in addition to any other relief it may receive.
b. Failure to require performance of any provision of this Agreement does not waive DigitalGlobe's right to subsequently
require full and proper performance of such provision. If any provision of this Agreement is determined to be invalid or
unenforceable, such provision will to the extent possible be deemed amended by limiting and reducing it to the minimum
extent necessary to make such provision valid and enforceable and the remaining provisions of this Agreement shall
continue to be valid and enforceable and will be liberally construed to carry out the provisions and intent hereof. The
3
80 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
invalidity or unenforceability of any provision of this Agreement in any jurisdiction will not affect the validity or
enforceability of such provision in any other jurisdiction, nor will the invalidity or unenforceability of any provision of this
Agreement with respect to any person affect the validity or enforceability of such provision with respect to any other
person.
c. Neither this Agreement nor any of the rights or obligations hereunder may be assigned or transferred by You (by
operation of law or otherwise) without the prior written consent of DigitalGlobe. This restriction on assignment or transfer
shall apply to assignments or transfers by operation of law, as well as by contract, merger or consolidation. Any
attempted assignment or transfer in violation of the foregoing will be null and void.
d. This Agreement shall be governed by the laws of the State of Colorado, U.S.A., without regard to conflicts of law
principles that would require the application of the laws of any other state or jurisdiction. The United Nations Convention
on Contracts for the International Sale of Goods does not apply to this Agreement. Any action or proceeding arising from
or relating to this Agreement must be brought in the federal courts or state courts for Denver County, Colorado, and each
party irrevocably submits to the jurisdiction and venue of any such court in any such action or proceeding.
e. Any notices to DigitalGlobe rel ating to this Agreement shall be in writing and delivered by personal delivery or U.S.
certified mail (return receipt requested) to the address provided below and will be effective upon receipt by DigitalGlobe:
DIGITALGLOBE, INC.
ATTN: LEGAL DEPT.
1601 Dry Creek Dr., Suite 260
Longmont, CO 80503, USA
All notices to You relating to this Agreement shall be delivered by personal delivery, electronic mail, facsimile transmissio n or by
U.S. certified mail (return receipt requested) to the address DigitalGlob e has on file for You, and will be deemed given upon
personal delivery, 5 days after deposit in the mail, or upon acknowledgment of receipt of electronic transmission.
4
Annex E
Example of an
End User License
Agreement (EULA)
for archived
DEM products
Source: Airbus Defense and Space
http://www2.geo-airbusds.com/files/pmedia/public/r33344_9_worlddem_eula_single_use_final_14052014.pdf
81
Example of an End User License Agreement A NNEX(EULA) E for archived DEM products
Source: Airbus Defense and Space
82 Example of an
Digital Elevation End
Models User
– License
A Guidance Agreement
Note on (EULA)
How Digital Elevation for Are
Models archived DEM
Created and
http://www2.geo-airbusds.com/files/pmedia/public/r33344_9_worlddem_eula_single_use_final_14052014.pdf
Used products
Source: Airbus Defense and Space
http://www2.geo-airbusds.com/files/pmedia/public/r33344_9_worlddem_eula_single_use_final_14052014.pdf
INFOTERRA GMBH EULA WorldDEM - Single User May 2014
INFOTERRA GMBH EULA WorldDEM - Single User May 2014
END USER LICENSE AGREEMENT
Non-Exclusive License to use WorldDEM-Product
END USER LICENSE
Single AGREEMENT
User License
Non-Exclusive License to use WorldDEM-Product
Single User License
Infoterra GmbH
Claude-Dornier-Strasse
between 88090 Immenstaad and END-USER
GermanyGmbH
Infoterra
Claude-Dornier-Strasse
hereinafter called "Airbus DS"
between 88090 Immenstaad and END-USER
Germany
The END-USER accepts and agrees to be bound by the terms of this End-User License Agreement
any of thecalled
hereinafter
("EULA") by doing "Airbus
following: DS" in whole or in part, a quotation for the supply of
(a) accepting,
the PRODUCT; (b) breaking the seal on the package containing the PRODUCT; (c) downloading or
The END-USER
installing accepts and
or manipulating the agrees
PRODUCTto beon any by
bound the terms
computer; this End-User
ofpaying
(d) in whole License Agreement
or in part for the
("EULA")
PRODUCT; by (e)
doing any of
making the following:
available (a) accepting,
any Derivative Works; whole
in(f) or in part,
damaging a quotation
or destroying thefor the supply(g)
PRODUCT; of
the PRODUCT;
retaining (b) breaking
the PRODUCT than on
the seal
for more the package
fourteen containing
(14) calendar days the PRODUCT;
following receipt (c) downloading or
thereof.
installing or manipulating the PRODUCT on any computer; (d) paying in whole or in part for the
This EULA is
PRODUCT; (e)entered
making into by and
available anybetween the
Derivative END-USER
Works; and Infoterra
(f) damaging GmbHthe
or destroying (“Airbus DS”), (g)
PRODUCT; an
entity of Airbus Defence and Space, a division of Airbus Group.
retaining the PRODUCT for more than fourteen (14) calendar days following receipt thereof.
This EULA is entered into by and between the END-USER and Infoterra GmbH (“Airbus DS”), an
entity
ARTICLEof Airbus Defence and Space, a division of Airbus Group.
1 - DEFINITIONS
"DERIVATIVE WORKS": means any product or information, developed by the END-USER, from the
PRODUCT
ARTICLE 1 which does not contain any height information from the PRODUCT and is irreversible and
- DEFINITIONS
uncoupled from the source PRODUCT and in which the PRODUCT origin is not recognizable.
"DERIVATIVE
Notwithstanding WORKS": means
the foregoing, any any product
Digital or information,
Elevation developed
Model (DEM) by theTerrain
or Digital END-USER, Modelfrom the
derived
PRODUCT which does (in
from the PRODUCT contain
not any form any height information
whatsoever, from the PRODUCT
i.e. databases) shall never andbe is irreversible
considered andas
uncoupled
DERIVATIVE from
WORKS.the source PRODUCT and in which the PRODUCT origin is not recognizable.
Notwithstanding the foregoing, any Digital Elevation Model (DEM) or Digital Terrain Model derived
"END-USER":
from the PRODUCT means either
(in any person,
theform acting in his
whatsoever, i.e. own name, orshall
databases) the legal
nevercommercial business
be considered as
entity, including
DERIVATIVE WORKS. its possible offices and branches in its country of residence, which is supplied with the
product and accepts this EULA. When the product is supplied to a public entity (civil agency, public
"END-USER":
department) themeansEND-USEReither shall
the person,
be deemed acting in only
to be his ownsuch name,
part ofor
thethe legalentity
commercial
public business
as located at the
entity,
address including
to which its possible
the PRODUCToffices is and branches
supplied, in its
except uponcountry of residence,
prior written which
agreement is supplied
from with the
Airbus DS.
product and accepts this EULA. When the product is supplied to a public entity (civil agency, public
"PRODUCT"
department) the: means
END-USERWorldDEM be, deemed
shall core and any toother
be only data/geo-information
such part of the publicproduct
entityderived from
as located the
at the
TanDEM-X
address Mission
to which thedata produced
PRODUCT is by Airbus except
supplied, DS (e.g WorldDEM,
upon WorldDEM
prior written DTM).
agreement from Airbus DS.
“VALUE ADDED
"PRODUCT" PRODUCT ("VAP") ”: means any product developed by the END-USER, which
: means WorldDEM core, and any other data/geo-information product derived from the
contains
TanDEM-X height
Missioninformation from the
data produced PRODUCT,
by Airbus DS (e.gand resulting in
WorldDEM, a modification
WorldDEM DTM). of the PRODUCT,
through technical manipulations and/or addition of other data. Notwithstanding the foregoing, by
“VALUE exception,
express ADDED PRODUCT any Digital ("VAP")
Elevation ”: means
Model or any product
Digital developed
Terrain by the END-USER,
Model derived from a PRODUCT which
contains height
shall always informationas
be considered from
a VAP.the PRODUCT, and resulting in a modification of the PRODUCT,
through technical manipulations and/or addition of other data. Notwithstanding the foregoing, by
"WorldDEM core": means
express exception, the unedited
any Digital Elevationdigital surface
Model model derived
or Digital Terrain from
Model the TanDEM-X
derived from Mission data
a PRODUCT
always be by
and distributed
shall Airbus DS.
considered as a VAP.
"WorldDEMcore": means the unedited digital surface model derived from the TanDEM-X Mission data
and distributed by Airbus DS.
Infoterra GmbH 1/4
Registered Office: Claude-Dornier-Str., 88090 Immenstaad, Germany
Register Court: Amtsgericht Ulm (HRB 630970), VAT Identification Number: DE 197540174
Infoterra GmbH 1/4
Registered Office: Claude-Dornier-Str., 88090 Immenstaad, Germany
Register Court: Amtsgericht Ulm (HRB 630970), VAT Identification Number: DE 197540174
Annex E 83
INFOTERRA GMBH EULA WorldDEM - Single User May 2014
ARTICLE 2: LICENSE
2.1 Permitted Uses:
Under the terms and conditions of this EULA, Airbus DS grants to the END-USER a limited, non-
exclusive, non-transferable license:
a) to use the PRODUCT for its own internal needs;
b) to make an unlimited number of copies of the PRODUCT for the Permitted Uses specified in this
Article 2.1;
c) to install the PRODUCT on as many individual computers as needed in its premises, including
internal computer network for the Permitted Uses specified in this Article 2.1;
d) to alter or modify the PRODUCT to produce VAP and/or DERIVATIVE WORKS;
e) to use any VAP for its own internal needs;
f) to make the PRODUCT and/or any VAP available to contractors and consultants, only for use on
behalf of the END-USER for the Permitted Uses specified in this Article 2.1, and only after prior
written agreement of Airbus DS and subject to such contractors and consultants agreeing in writing,
in advance, (I) to be bound by the same limitations on use as applicable to the END-USER, and (II)
to return the PRODUCT and/or any derived products to the END-USER, and to keep no copy
thereof, upon completion of the contracting or consulting engagement;
g) to publish the PRODUCT and any VAP as hardcopy prints and in presentations, provided that the
END-USER conspicuously marks the copyright with the credit as indicated in Article 3.3 below.
Such publishing shall be used for END-USER business promotion purposes only;
h) to post the PRODUCT and/or VAP as browsable image or equivalent (without containing any
height information) to Internet web sites after notifying Airbus DS of the URL that will be used,
provided that the END-USER conspicuously marks the copyright as indicated in Article 3.3 below.
Such posting shall be used for END-USER business promotion purposes only. In no event does
this Agreement allow the downloading of the posting by third parties, nor using to distribute, sell,
assign, dispose of, lease, sublicense or transfer such posting; and
i) to freely use and distribute DERIVATIVE WORKS.
All permitted rights not expressly granted above are hereby retained by Airbus DS.
2.2 Prohibited Uses:
a) The END-USER recognizes and agrees that the PRODUCT is and shall remain the property of
Airbus DS and/or its licensor, and contains proprietary information of Airbus DS and thus is
provided to the END-USER on a confidential basis and under the terms and conditions of this
EULA.
b) Furthermore, the END-USER recognizes and agrees that the PRODUCT is subject to the
“Satellitendatensicherheitsgesetz (SatDSiG)" (German Satellite Data Security Act). The END-
USER shall comply with such regulations.
c) The END-USER shall not, and shall guarantee that any contractor or consultant engaged as per
the provisions of Article 2.1(f) does not:
d) sublicense, sell, rent or lease or otherwise transfer or assign the PRODUCT or VAP to a third party,
except as provided in Article 2.1 (f);
e) alter or remove any copyright notice or proprietary legend contained in or on the PRODUCT and
any VAP;
f) publish, distribute or transfer in any way the digital format of the PRODUCT;
g) use a PRODUCT in the framework of competitive analysis (such as benchmarking); or
h) do anything not expressly permitted under Article 2.1.
Infoterra GmbH 2/4
Registered Office: Claude-Dornier-Str., 88090 Immenstaad, Germany
Register Court: Amtsgericht Ulm (HRB 630970), VAT Identification Number: DE 197540174
84 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
INFOTERRA GMBH EULA WorldDEM - Single User May 2014
ARTICLE 3: INTELLECTUAL PROPERTY RIGHTS
3.1 The satellite data contained in the PRODUCT is the property of the Deutsche Zentrum für Luft-
und Raumfahrt e. V. (DLR) and is protected in accordance with the copyright laws of Germany and
applicable international laws.
The PRODUCTS except the WorldDEMcore are produced by Airbus DS. They are the property of
Airbus DS and are protected in accordance with the copyright laws of Germany and applicable
international laws.
3.2 This License does not give the right to the use of Airbus DS trademarks or logos unless explicitly
authorized by Airbus DS. Unless otherwise communicated by Airbus DS the copyright statement
applies to all PRODUCTs distributed by Airbus DS and any VAP.
3.3 The PRODUCT, when displayed in accordance with the Permitted Uses specified in Article 2.1
shall include the following credit conspicuously displayed and written in full:
For WorldDEMcore:
"© DLR e.V. ____ (year of acquisition), Distribution: Airbus DS/Infoterra GmbH."
For PRODUCTS other than WorldDEMcore:
"© DLR e.V. ____ (year of acquisition) and © Airbus DS/Infoterra GmbH ____ (year of
production)."
ARTICLE 4: WARRANTY
4.1 Airbus DS warrants that it is authorized to grant the license for the right to use the PRODUCT to
the END-USER under the terms of this EULA.
4.2 Airbus DS does not warrant that the PRODUCT is free of bugs, errors, defects or omissions, and
that the operation of the PRODUCT will be error-free or uninterrupted nor that all non-conformities can
be corrected. Airbus DS does not warrant that the PRODUCT will meet the END-USER’s requirements
or expectations, or will fit for the END-USER’s intended purposes. There are no expressed or implied
warranties of fitness or merchantability given in connection with the sale or use of the PRODUCT.
Airbus DS disclaims all other warranties not expressly provided in Articles 4.1 and 4.2.
In case the medium on which the PRODUCT is supplied by Airbus DS to the END-USER is defective,
as demonstrated by the END-USER, Airbus DS shall replace the concerned medium with the
PRODUCT. Any such claim shall be notified to Airbus DS within fourteen (14) calendar days after
delivery of the PRODUCT by Airbus DS.
ARTICLE 5: LIABILITY
5.1 In cases of gross negligence and willful intent Airbus DS will be liable according applicable law.
5.2 In cases of slight negligence – with the exception of cases of injury to life, body or health – Airbus
DS shall be liable only insofar as essential contractual obligations, basic and fundamental duties and
obligations resulting from the contractual relationship which are of particular importance for the proper
fulfilment of the contract, are infringed and such liability shall be limited to typical and foreseeable
damages.
5.3 In cases of Article 5.2 any liability for indirect, consequential or unforeseeable damages, such as
but not limited to loss of profit, stand-by cost, recovery cost, lost savings and economic loss due to a
third party claim, are hereby excluded.
5.4 In cases of Article 5.2 the overall cumulative liability of Airbus DS shall not exceed the price paid
by the END-USER to Airbus DS for the PRODUCT from which such loss or damage directly arose.
5.5 Any further reaching liability than provided in these terms and conditions shall – regardless of the
legal basis of such claim – be excluded.
Infoterra GmbH 3/4
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Annex F
Example Terms
of Reference –
World Bank DEM
Consultant
Support to review technical specifications for LiDAR
survey and the deliverable Digital Elevation Model (DEM)
Objective of the Assignment
The consultant will assist the World Bank team to review the technical specification for LiDAR and aerial imagery
being procured by the [Project-Client] in order to develop [insert objective of use for the DEM].
Background [Add as appropriate]
Scope of Services
The Services to be provided by the consultant include:
• Reviewing the revised technical specification for LiDAR survey received from the [client] in terms of the
generation of digital elevation models (DEM) and point cloud data processing;
• Reviewing the summary of the deliverables against the negotiated technical specifications
• Reviewing the point cloud as well as the Digital Elevation Model delivered by the LiDAR survey firm to the [client]
Qualifications
The successful consultant would be expected to have the following qualifications:
• At least 10 years of experience and in-depth knowledge in surveying, remote sensing, point cloud data
processing and generation of Digital Elevation Models as well as its applications;
85
86 Digital Elevation Models – A Guidance Note on How Digital Elevation Models Are Created and Used
• Postgraduate degree in relevant geomatic, civil or other engineering disciplines, physical geography and other
environmental sciences, mathematics
• Very good command of oral and written English; and
• Working experience in Sri Lanka would be an advantage.
Duration
The consultant should provide the Services for a total of [#] days over the period of [date] to [date]. The
payment will be based on the level of experience and background of the consultant. The appointment will be
International hire.
Inputs
The Bank shall reasonably provide or arrange to be provided to the consultant information and documentation,
related to the Bank and Client, necessary for the consultant to deliver the Services. The consultant shall be
responsible for obtaining information and documentation required to support the Services.
Outputs
• Read and communicate to the World Bank project team potential issues on the specs of the LiDAR survey in
the final draft of the Terms of Reference (to be provided by the World Bank project team) submitted by the
[Client].
Some particular issues to consider:
• Is the specified output DEM adequate for its intended use?
• Is the method of generating the DEM most economic/optimal, considering the context, budget and
other underlying conditions?
• Be on standby to respond to technical queries from the potential bidders on the DEM specs required
• After the project commences, keep track of the on-going activities on a regular basis through communication
with the project team and flag those that could potentially affect the data acquisition and output DEM
• At the end of the project, check the final DEM delivered by the vendor for quality assurance
• Review comments of the deliverables (LiDAR point cloud and derived digital elevation model) submitted
by the [Client] and any recommendation to ensure they meet the technical specifications in the Terms
of Reference
Annex G
ICSM LiDAR
Acquisition
Specifications and
Tender Template
Document available from: http://www.icsm.gov.au/elevation/LiDAR_Specifications_and_Tender_Template.pdf
(last accessed: 1 June, 2015)
87
Annex H
National
Geospatial
Program – Lidar
Base Specification
Chapter 4 of Section B, U.S. Geological Survey Standards
Book 11, Collection and Delineation of Spatial Data
Techniques and Methods 11–B4, Version 1.2,
November 2014 U.S. Department of the Interior, U.S.
Geological Survey
The document is available from http://pubs.usgs.gov/tm/11b4/pdf/tm11-B4.pdf
(last accessed: 1 June, 2015)
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