Digital Elevation Models (DEM) / DTM

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1 Digital Elevation Models (DEM) / DTM Uses in remote sensing: queries and analysis, 3D visualisation, layers in classification Fogo Island, Cape Verde Republic ASTER DEM / image Banks Peninsula, Christchurch, New Zealand DEM sources where do they come from? Almost all DEMs have been created from remote sensing: a. DEMs from digitising contours (e.g. NTDB) The earliest were created by digitising contours on maps into layers stereo photos -> contour lines -> digitised lines -> interpolate to raster grid Arcmap: topo 2 raster PCI geomatica: vdemint 1

2 b. Digital Stereo photogrammetry: (e.g. BC TRIM) Mass points (70 metre spacing) captured from aerial photographs stereo photos -> mass points -> interpolate to raster grid BC TRIM DEM Interpolated to 25m grid By 1:250,000 map sheets (100 tiles assembled together) Elevation in metres = 16 bit DNs (not 8-bit!) 0-65,535 OR +/- 32, for invalid numbers e.g. across border into AB 2

3 BC: federal and provincial data TRIM DEM (25m) Download Canadian data from geobase.ca (1:50,000 / 1:250,000) = BC provincial data (25m) resampled for NTDB After 2000 methods c. Direct image grid DEM data from imagery RADAR e.g. Shuttle Radar Topographic Mission (SRTM) Stereo digital satellite imagery (adjacent satellite tracks) Issues: cloud cover and missing data (from space) ASTER SPOT 3

4 SRTM (Shuttle Radar Topographic Mission) Feb metre pixels, 56ºS - 60ºN latitude e.g. Google Earth ASTER DEM <- global DEM 30m pixels Global DEM (ASTER) 4

5 ASTER image: Svalbard, Norway (15 metre resolution) DEM availability A DEM is a continuous grid of elevation values one height value per pixel.. in a channel (not a band) Resolutions and datasets available: NTDB 25m (Canada) TRIM 25m (BC only) ASTER 30m (global) with holes SRTM 90m (near global) Download Canadian data from geobase.ca (1:50,000 / 1:25,000) * BC is provincial data (25m) resampled for NTDB 5

6 DEM - layers a. Elevation DN = (metres, 16 bit): represented onscreen as grayscale or pseudocolour tints; DEMs are stored as integer elevations (metres) or 32 bit (after interpolation) some (NTS) DEM tiles in Canada may still be in feet. conversion =.3048 b. Shaded relief (hillshade) A cartographic layer, DN= (relative amount of light reflected), as grayscale; light source can be selected, usually from the NW. High values on NW facing slopes, low values on SE facing slopes. Select light source azimuth and angle Default = 315, 45 useful to detect errors and assessing quality 6

7 DEM grid displayed as grayscale Hillshading (NW light source 315, 45) BC provincial DEM 1985 ( ) Homathko Icefield - mapplace.ca or lrdw.ca Errors from lack of contrast in snowfields = few data mass points 7

8 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 (not 16 or 32 bit) Aspect Displayed as grayscale pseudocolour Darker for lower DN (0- ), brighter for higher DN ( - 359) 8

9 4. Aspect: the compass direction a slope is facing A circular scale: N = 0 and 360 This raises three questions for analysis: north facing slope has both extreme values, 0 and 360 ****** flat slopes have no value (they are given an arbitrary value, e.g. 510) requires 16 bit data; PCI converts to 8 bit by dividing by 2 (flat = 255) 5. Incidence the angle (degree) of light incidence, based on the sun s position DN is related to the reflection based on sun angle 9

10 Incidence Image data look similar to shaded relief, but with values 0-90 the angle (degree) of light incidence, based on the sun position Requires metadata for sun elevation and azimuth for the scene 6. 3D perspectives / fly-throughs e.g. Google Earth etc.. 10

11 7. Anaglyphs (and 3D onscreen) St-Pierre Miquelon SRTM DEM Klinakline Glacier, south Coast Mountains (ASTER DEM) N 11

12 Klinakline Glacier, south Coast Mountains (ASTER DEM) S Manicouagan Crater, Quebec 12

13 DEM from Photogrammetry: Tatras, Slovakia 2m Directed high res sensors- Ikonos m 13

14 DEMs in Digital Image Classification Possible Input channels: Raw bands e.g. Thematic Mapper 3,4,5 Ratios / Indices / Components (e.g. NDVI, Tassel) Elevation Slope gradient Incidence (not aspect) DEMs in Digital Image Classification Land Cover Classification Using IRS LISS III Image and DEM in a Rugged Terrain: A Case Study in Himalayas 1 Green 2 Red 3 NIR 4 MIR 5 NDVI 6 DEM 14

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