Digital Elevation Model
1
(i) Introduction
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Objectives
2
 Introduction to Digital Elevation Models (DEMs)
 Types of DEM
 Sources of DEM data
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Introduction
3
DEM of the Malaprabha Catchment in India
A digital representation of the land surface elevation with respect to any
reference datum
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Definitions of DEM
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 Burrough (1986) defined DEM as
“Any digital representation of the continuous
variation of relief over space”
where relief refers to the height of earth’s surface with respect to the datum
considered
 It can also be considered as regularly spaced grids of the elevation
information, used for the continuous spatial representation of any terrain
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Difference between DTM, DSM and DEM
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 Digital Elevation Model (DEM):
 Elevation of the surface with reference to a datum such
as Mean Sea Level (MSL)
 Free of vegetation, buildings and other non ground
objects
 Digital Surface Model (DSM):
Digital Elevation Model (DEM)
 Includes the tops of buildings, power lines, trees and all
objects as seen in a synoptic view.
 Digital Terrain Model (DTM):
 Elevation and other additional information viz., slope,
aspect, curvature and skeleton.
 Gives a continuous representation of the smoothed
surface.
Remote Sensing: M7L1
Digital Terrain Model (DTM)
(Source: www.zackenberg.dk)
D. Nagesh Kumar, IISc
How a DEM is Generated?
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 Using elevation information from several points on the ground

Points may be regularly or irregularly placed

Elevation information may be obtained from field surveys

Contours marked in the topographic sheets may also be used for the elevation information

Point elevation information are interpolated to generate the DEM
 Using photogrammetric techniques

Photogrammetric techniques are used to derive DEM from the stereo pairs of the areal
photographs or satellite imageries

Stereo pairs of the radar imageries are also used for generating DEM
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Types of DEMs
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 Three main types of DEMs based on the data structure used to acquire
and store the elevation information
a)
Regular square grids (Gridded DEM)
b)
Triangulated irregular network (TIN)-DEM
c)
Contour based DEM
(a)
Remote Sensing: M7L1
(b)
(c)
D. Nagesh Kumar, IISc
Gridded DEM (GDEM)
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 Regularly placed uniform grids with elevation
information for each grid

Elevation of the surface as a function of geographic
location at regularly spaced grids.

Values can be accessed without any interpolation
 Accuracy and the data size depend on the grid
size

Small grids fine resolution, but large data size 
computational difficulties

Large grids coarse resolution but smaller data size
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Triangulated Irregular Network (TIN)-DEM
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 TIN structure

Irregular sampling points connected through nonoverlapping triangles

The triangles (facets) represent the plane connecting the
points.

Dense network of triangles for a rough terrain

Sparse network of triangles for a smooth terrain
 TIN data size is generally much less than the
gridded DEM
 The Delaunay triangulation is the most preferred
method for generating TIN
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Contour Based DEM
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 Contour

Line joining points of equal elevations
 Contour based DEM

Contour lines are traced from the topographic maps and are
stored with their location (x, y) and elevation information

Polygons are generated using the contours

Each polygon is tagged with the elevation information from the
bounding contour

Using the contour based DEM, water flow paths can be easily
identified (which are the orthogonals to the contours)
 Drawback:

Infinite number of points along the contour lines, whereas not
many smapling points between the contours.
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Sources of Digital Elevation Data
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 GTOPO30

Global elevation data set published by the United State Geological Survey (USGS)

Spatial resolution of the data is 30 arc second (approximately 1 Kilometer).

The data for the selected areas can be downloaded from the following website.
http://www1.gsi.go.jp/geowww/globalmap-gsi/gtopo30/gtopo30.html
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Sources of Digital Elevation Data…
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 NOAA GLOBE DEM





GLOBE : Global Land One-km Base Elevation
GLOBE project was undertaken by the National Oceanic and Atmospheric Administration (NOAA)
Global DEM is generated by combining data from several sources
GLOBE DEM spatial resolution: 3 arc second (approximately 1 kilometer)
The GLOBE DEM can be obtained from the NOAA National Geophysical Data Centre.
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Sources of Digital Elevation Data…
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 Shuttle Radar Topographic Mission (SRTM) Digital Elevation Data

Near global scale (56° S to 60° N) elevation data using the radar images taken from the space

Jointly run by the National Geospatial-Intelligence Agency (NGA) and the NASA

SRTM DEM for the world at 3 arc seconds (approximately 90 m) spatial resolution is available from
http://srtm.csi.cgiar.org/ .

For the United States and Australia, 30m resolution data is also available
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Sources of Digital Elevation Data…
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 ASTER Global DEM

Near global ( between 83oN and 83oS) elevation data at 30m spatial resolution

Generated from the stereo pair images collected by the Advanced Space Borne Thermal Emission and
Reflection Radiometer (ASTER) instrument onboard the sun-synchronous Terra satellite

The ASTER GDEM in the GeoTIFF format is distributed by METI (Japan) and NASA (USA) and can be
obtained from the following website.
https://lpdaac.usgs.gov/lpdaac/products/aster_products_table
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Sources of Digital Elevation Data…
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 LIDAR DEM

Light Detection and Ranging (LIDAR) sensors operate
on the same principle as that of radar equipment

Generated using the stereo pairs of LIDAR images.

LIDAR uses a sharp beam with high energy and hence
high resolution can be achieved.

It also enables DEM generation of a large area within a
short period of time with minimum human dependence

The disadvantage of LIDAR data is the expense
involved in data collection.
5m resolution Lidar DEM for the
downtown area of Austin
Source: http://www.crwr.utexas.edu
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Applications of DEM
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 DEMs are used to extract

Terrain attributes such as elevation, slope, aspect

To identify terrain features like drainage basins, channel networks
 Applications of DEMs

Hydrologic and geologic analyses

Hazard monitoring

Natural resources exploration

Agricultural management etc.
 Hydrologic applications of the DEM

Groundwater modeling

Estimation of the volume of proposed reservoirs

Flood prone area mapping …etc.
Remote Sensing: M7L1
D. Nagesh Kumar, IISc
Thank You
Remote Sensing: M7L1
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D. Nagesh Kumar, IISc