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Digital Elevation Models (DEM) / DTM. Fogo Island, Cape Verde Republic ASTER DEM / image. Uses: queries and analysis, layers in classification, 3D visualisation. DEM data sources. Almost all DEMs have been created from remote sensing: a. DEMs from digitising contours (e.g. NTDB)

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Digital Elevation Models (DEM) / DTM

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Digital elevation models dem dtm l.jpg

Digital Elevation Models (DEM) / DTM

Fogo Island, Cape Verde RepublicASTER DEM / image

Uses: queries and analysis, layers in classification, 3D visualisation


Dem data sources l.jpg

DEM data sources

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 -> convert to raster

b. Digital Stereo photogrammetry: (e.g. BC TRIM)

Mass points captured from aerial photographs

stereo photos -> mass points -> convert to raster


Bc trim dem l.jpg

BC TRIM DEM

Interpolated to 25m grid

By 1:250,000 map sheets

(100 tiles assembled together)

Vertical accuracy to within 10metres

UTM pixel coordinates to even 25m

Resampled to BC Albers

16 bit codes, -9999 for invalid numbers

e.g. across border into AB


Post 2000 methods l.jpg

Post 2000 methods

  • c. Direct image grid DEM data from imagery

  • RADAR (interferometry) e.g. Shuttle Radar Topographic Mission (SRTM)

  • Stereo aerial photos, and optical satellite imagery from path overlap


Dem availability l.jpg

DEM availability

A DEM is a continuous grid of elevation values –

one height value per pixel ….. in a channel (not a band)

AGENCY  SCALE  RESOLUTION (metres)

Municipal  1: 2,000  1 

Provincial  1: 20,000  25 

Federal  1: 50,000  50 

Federal  1: 250,000  200 

Global  1: 1,000,000  500-1000 

Download Canadian data from geobase.ca (1:50,000 / 1:25,000)

* BC is provincial data (25m) resampled for NTDB (50m)


Dem sources global gtopo30 1993 1km l.jpg

DEM sources: global GTOPO30 ~1993 1km

http://edc.usgs.gov/products/elevation/gtopo30/gtopo30.html


Slide7 l.jpg

SRTM  (Shuttle Radar Topographic Mission) Feb 2000

90 metre pixels, 60ºS-60ºN latitude e.g. Google Earth


Aster dem global dem 30m l.jpg

ASTER DEM<- global DEM 30m


Aster image svalbard norway 15 metre resolution l.jpg

ASTER image: Svalbard, Norway (15 metre resolution)


Dem layers l.jpg

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


Slide11 l.jpg

b. Shaded relief

A cartographic layer, DN= 0 - 255 (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.

Also useful for detecting errors and assessing quality


Slide12 l.jpg

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


1 metre hillshaded dem from contours l.jpg

1 metre hillshaded DEM … from contours


C slope l.jpg

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


4 aspect l.jpg

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


Slide16 l.jpg

5. Incidence

Image data look similar to shaded relief, but with values 0-90

the angle (degree) of light incidence for each pixel, based on the sun position at time of scene capture. Requires knowledge of sun elevation and azimuth for the scene = metadata (file acquired with scene data)


Slide17 l.jpg

6. Second derivatives: slope concavity and convexity, used in generating watersheds and also viewsheds using line of sight


Slide18 l.jpg

7. 3D perspectives / fly-throughs e.g. Google Earth etc..


Castle glacier cariboo mountains l.jpg

Castle Glacier, Cariboo Mountains


Dem from photogrammetry tatras slovakia 2m l.jpg

DEM from Photogrammetry: Tatras, Slovakia 2m


Directed high res sensors ikonos 1999 4 m l.jpg

Directed high res sensors- Ikonos 1999 4 m

http://www.satimagingcorp.com/galleryimages/ikonos-high-resolution-dem-eritrea.jpg


8 anaglyphs malaspina glacier alaska l.jpg

8. Anaglyphs (Malaspina Glacier, Alaska)


Klinakline glacier south coast mountains l.jpg

Klinakline Glacier, south Coast Mountains

N


Slide25 l.jpg

Kamchatka, Russia


Manicouagan crater quebec l.jpg

Manicouagan Crater, Quebec


Dem products l.jpg

DEM products

Elevation 0- ? 16 bit

Hillshading 0-255

Slope 0-90 (if in degrees)

Aspect 0-359 16 bit

Visual: Anaglyphs and 3D perspectives


Can dems enhance digital image classification l.jpg

Can DEMs Enhance Digital Image Classification?

SPOT image data

http://www.gisdevelopment.net/aars/acrs/1997/ts9/ts9007pf.htm


Dem summary l.jpg

DEM summary

  • Use of DEMs / DTMs:

  • queries and analysis

  • layers in classification

  • 3D modelling and visualisation

  • Resolutions and datasets available:

  • NTDB 50m

  • TRIM 25m (BC only)

  • ASTER 30m (global)

  • SRTM 90m (near global)

  • GTOPO30 1km (global)


Lidar dem 2009 unbc area light detection and ranging l.jpg

LiDAR DEM 2009 – UNBC area: (Light Detection And Ranging)

Resolution 50 cm

Flooded PG bowl image

by Shane ~ 10,000 BP


Slide31 l.jpg

The UNBC

Geowall

In lab

this week


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