2. DEM products Elevation 0- ~10,000 (earth) 16 bit (signed)
Shaded relief
Slope (if in degrees)
Aspect bit (flat = ?)
Incidence requires orbital metadata
Visual: Anaglyphs and 3D perspectives

3. DEM layers
a. Elevation
DN = (metres, 16 bit):  represented as grayscale or pseudocolour tints;
Raster DEMs are stored as elevations (metres) or 32 bit (after interpolation)
some DEM tiles in Canada may be in feet (how would the values compare ?)
conversion = .3048

4. c. Slope Calculated in degrees (0-90) or % (0 -> infinity)
slope is rise/run = vertical change over the horizontal distance
8 bit results should be adequate for most purposes

5. 4. Aspect
The direction in which a slope is facing, measured by azimuth (0-360)
This raises three question for analysis:
a north facing slope has both extreme values, 0 and 360
flat slopes have no value (they are given an arbitrary numerical value, e.g. 555)
0-360 requires 16 bit data; some software (PCI) converts to 8 bit by dividing by 2

6. ASTER image: Svalbard, Norway (15 metre resolution)

7. Evolution of DEM creation
1950s Generation of contours from stereo photos
1980s Mass points from stereo photos
1990s Automated generation of masspoints
2000s Direct generation of grids from stereo-imagery
(and expansion of LiDAR)

8. SPOT 5 DEM (DSM) : m High Resolution Stereoscopy (HRS) instrument (the high-res multispectral sensor is HRG)

9. Directed high res sensors- Ikonos 1999 2-5m

10. Photogrammetry: Tatras, Slovakia 2m

11. (Airborne) LiDAR 10cm – 10m (Mt.St. Helens)

12. LiDAR Forests for the World, 2009 – DTM and/or DSM

13. City 1 metre DEM (from 1m contours)

14. TRIM DEM

15. DEM quality and errors Scale – Match with needs and imagery
Type of terrain - pixel homogeneity
Horizontal and vertical accuracy
DSM or DTM ? (most satellite imagery create DSMs)
Interpolation / resampling method – from points or lines?
Null values and spikes
Errors are more easily spotted from a hillshaded model

16. DEM creation by interpolation
Inverse distance weighted - simple
Nearest neighbour – honours raw values
Spline – minimizes curvature -> smooth surface
Kriging – uses spatial correlation of points

17. DEM creation by interpolation
Inverse Distance weighted - simple Nearest neighbour – honours raw values
Spline – minimizes curvature -> smooth surface Kriging – uses spatial correlation of points
(employing semi-variogram of distance v difference)

18. DEM Interpolation methods

19. DEM differencing
Differences in DEMs (heights at same x,y) result from:
Interpolation method
Generation mode e.g. DTM v DSM
Resolution (scale)
Resampling and other processing
Real change e.g. landslides, glacier melt, lakes ..

20. 1888 First Canadian Topographic series NTDB 1:50,000 data (1982) 1:40,000 (Eldon sheet), Interval 200’ Interval 40 metres
a. Glacier retreat
b. New melt lakes north of Vermillion Lake
c. Lack of gulleys on north side of Bourgeau Lake

21. Eldon, 1888

22. ETM+ 1999

23. TRIM DEM: PG (vertical accuracy 10 metres)

24. TRIM DEM – masspoints ~70m spacing captured onscreen from stereo-photography ‘soft copy’ (prior to fully automated image matching)

25. BC provincial DEM 1985 (1981-1989) – Homathko Icefield - mapplace
BC provincial DEM 1985 ( ) – Homathko Icefield - mapplace.ca or lrdw.ca

26. Assiniboine Spillway, MB

27. SRTM comparison with topographic DEM

28. SRTM – ASTER comparison Sample area in Indonesia

29. DEMs : Lab next week:
Correction operations require metadata, in this case:
Sun azimuth ~
Sun angle ~ 45.95