DTM/DEM generation involves creating digital models of terrain elevation from various data sources. A DTM provides height values referenced to positions and can include other terrain features, while a DEM only provides regular elevation values. Photogrammetry and remote sensing are common methods to acquire elevation data and generate DTMs/DEMs. The data often needs editing and filtering to remove errors and refine the models. Raster and TIN representations are common formats, with rasters using a grid and TINs using irregular triangles. Accuracy depends on factors like the data source and grid size for rasters. DSMs include above-ground features and require processing to derive bare earth DTMs below the features.

1. DTM/DEM Generation
SUG541

2. Introduction → Map/GIS Layers
Spatial information layers require a
base comprising a DTM/DEM &
imagery
The ortho-image layer: a critical
element, which is draped over a
DTM

3. Introduction → DEM & ortho-imagery
DEM provides height, referenced
to position
Ortho-image provides metrically
correct map for feature extraction

4. Ortho-image draped over a DTM

5. Modern photogrammetric process for
geospatial information collection

6. DTM Generation: Contents
• Terminology
• DTM Acquisition
• DTM Editing
• DTM Representation
• Accuracy Issue
• From DSM to DTM/DEM
• DTM Manipulation

7. Terminology
• DEM (Digital Elevation Model)
– Refers to regular array of elevations
• DTM (Digital Terrain Model)
– More complex concept involving elevations and other GIS
features
– (e.g., rivers, ridges, break lines, etc.);
– Encompasses terrain relief, planimetric, and derived data (slope,
aspect, visibility, etc.)
• DHM (Digital Height Model)
– Similar as DEM, but less commonly used terminology
• DGM (Digital Ground Model)
• More emphasis on digital models of the solid/continuous
surface of the earth (used in the UK)

8. Terminology
• DTED (Digital Terrain Elevation Data)
– Term used by the US Mapping Community; comes
from military specs.
– Usually refers to gridded/regular arrays
– DTEDs come in different ‘levels’
• DSM (Digital Surface Model)
– Refers to digital model including features above
surface of the earth (e.g., trees, buildings)
– Very important for orthophoto generation

9. DTM Acquisition
• Photogrammetric data capture (passive sensor)
• Aerial photography
• Digital satellite imagery
– Image matching used to automatically extract a dense
– point cloud of 3D surface points from stereo image pairs
and potentially multi-image coverage; DTM derived via
‘regularization’ of the point cloud.
• RADAR: RAdio Detection And Ranging (active sensor)
• LIDAR: LIght Detection And Ranging (active sensor)
• Digitized contour maps
• Ground surveying

10. DSM to DTM

11. DTM Editing
Modification and refinement of DTMs, and
derivation of intermediate models.
• Editing: correcting errors and updating DTMs
• Filtering: smoothing, enhancing, compression
and resampling
• Merging and joining DTMs:
– combining DTMs from several sources (possibly from
different dates)
– Converting DTMs from one data structure to another

12. DEM Representation
• Raster DEM
– Elevations are available at equally spaced grid points
• TIN (Triangulated Irregular Network)
– Elevation data at irregular points that are formed into
triangles
– The TIN is generated in such a way that the summation
of the lengths of the triangle legs is a minimum
Delaunay
Triangulation

13. Triangulated Irregular Network (TIN)

15. Raster DEM & TINs
RASTER: Effect of Grid Size on Surface Representation
• Sampling interval will affect
– Amount of detail captured (accuracy)
– Amount of storage (redundancy, efficiency)
• Optimum sampling interval depends on the nature of the terrain
• Raster DEM & TINs
TINS:
• Each vertex must have the following information
– Height
– Connectivity information
– Surface normal
• The triangle legs can be forced to coincide with the break lines

16. Raster vs. TINs

17. Shaded DSM
Source image (1 of stereo pair) Shaded DSM

18. Accuracy of Photogrammetric DSM
from IKONOS

19. DSM to DTM
Morphological operations

20. Morphological operations: removal of
above-ground features
DSM
DTM

21. DSM to DTM
Multiple height bin method for object detection & removal

22. Multiple height in method for object detection
image DSM Detected above-ground objects

23. DTM Manipulation
• Nearest neighbour assignment
• Linear interpolation
• Bilinear interpolation
• Cubic convolution

24. Nearest Neighbour Assignment
• Assigns the values of the
nearest grid point to the
output grid cell
• No actual interpolation
is performed based on
values of neighbouring
points
• Does not create a
continuous surface

25. Bilinear Interpolation
• Determines the height of a point based on a
weighted average of the 4 grid points
• Generated surface is continuous, but not smooth

26. Bilinear Interpolation

27. Cubic Convolution
• Determine the Z value of
a point using 16
neighbouring grid points
• Convolve with a smooth
curve function