Digital Terrain Analysis

Digital Topography
Datasets differ in scale oresolution of the data.

Raster digital elevation model (DEM) data are the most common.

    • global such as the Etopo1 dataset elevation data point every 1 arc-minute of latitude and longitude

 …plus many other “global” data sets

    • Regional Scale (3 arc second data from digitizing contours on 1:250,000 maps, 1 degree quads) data (USGS; now archived…not used much.)

Western Half of the Salt Lake City 1 x 2 degree sheet

    • SRTM (Shuttle radar topography mission) (formerly 3 arc-second global data, now 1 arc-second globally)
      was the first global topographic dataset of earth (but long after Mars….)

      example from near Mt. Cook New Zealand ( about 1/2 degree E-W)
      — note the white patches (voids) where thick clouds or topographic shadows prevented transmission of the radar signal.
    • 1 arc second (roughly 30 m) data is available for the entire US at the National Map had the former National Elevation Dataset (NED) and now 3D Elevation Program (3DEP)

Here’s  Lexington, VA 7.5 minute quadrangle as a DEM.
This dataset was assembled from a variety of sources, including digitizing contours, analysis of aerial photography, and now airborne lidar and radar projects.

  • Topography as contours (on 1:100,000 scale) in SDTS format (“hypsography”)
  • Topography as contours (on 1:24,000 scale) in SDTS format

DEM data layers start out as

  • air photos (and now satellite images) from which a stereo-model (of contours or points) is made. Control points on the ground are needed to calibrate the model (most USGS 30m DEMs started this way)
    try parallax exercise
  • field survey points, from which a surface is interpolated.
    digitized contours maps (1:250,000 scale or 3-arc second maps were created that way; lots of contour artifacts)
  • satellite measurements (SRTM)

What’s in a name—-DEMs, TINs, DLGs, DTMs  (geez)

  • DTM – digital terrain model (general name for digital topography, involves representation/generalization)
  • DEM – digital elevation model (gridded representation of point topography)
  • DLG – digital line graph (of contours, but same format for rivers rivers, transport)
  • TIN – triangular irregular network (triangular “facets,” each of which has a constant slope and aspect). Also known as “nets,”
  • Point cloud – returns from a terrestrial or airborne LIDAR that give ground and vegetation elevation (we’ll cover these later)
    Some advantages of TINS include:

  • Fewer points are needed to represent the topography—less computer disk space needed.
  • Points can be concentrated in important areas where the topography is variable and a low density of points can be used in areas where slopes are constant.
  • Points of known elevation such as surveyed benchmarks can easily be incorporated
  • Areas of constant elevation such as lakes can easily be incorporated
  • Lines of slope inflection such as ridge lines and steep canyons streams can be incorporated as breaklines in TINS to force the TIN to reflect these breaks in topography.

Open the topo_data project demo\topo\ folder.

    1. The first tab “lat long vs UTM” shows GCS vs projected data. We’ll talk about projection. These are 1 arc second data points (raster) in Lat/Long (geographic coordinate system or “GCS”) and same data projected to a 30 m grid (raster) in UTM.
    2. The second map tab “National Map downloads” shows the difference between grid resolution data for the same 1×1 degree square.
    3. The third map tab “Data Types” shows many different DTM versions.
      1. We will examine grid, TIN, and contour datasets.
      2. Compare these data to what’s available online
        1. select the “add data button” and from the “living atlas” select “Terrain.” (not “Terrain: something else”)
        2. increase the transparency of the layer
        3. “add data” and choose “Terrain: multidirectional hillshade” from the Living Atlas, make sure it is below the DEM
        4. Group these two layers like the existing DEM
    4. Fourth map tab is for later…. visibility analysis.