Terrain Mapping and Analysis by gR1AvP38

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									Terrain Mapping and
      Analysis
      Chapter 12
Introduction
 Terrain mapping
 Land surface is 3-D
 Elevation data or z-data is treated as a
  cell value or a point data attribute rather
  than as a coordinate.
Data for Terrain Mapping and Analysis
   Digital Elevation Model (DEM)
       Array of elevation points
       7.5 minute USGS quads into 4 levels
       Level 1 RMS 7-15 meters
       Level 2 RMS of ½ contour interval
       Level 3 RMS of 1/3 contour interval not to
        exceed 7 meters
       What happened to Level 4?
   Relative and absolute errors
Data for Terrain Mapping and Analysis
   Triangulated Irregular Network (TIN)
       Series of non-overlapping triangles
       Elevation values are stored at nodes
       Irregular distribution
       Sources: DEMs, surveyed elevation points,
        contour lines, and breaklines
       Breaklines are line features that represent
        changes of the land surface such as streams,
        shorelines, ridges, and roads
Data for Terrain Mapping and Analysis
   Triangulated Irregular Network (TIN)
       Not every point in DEM is used
       Only points most important
       VIP (Very Important Points) algorithm
       Maximum z-tolerance algorithm
       Delaunay triangulation: all nodes are
        connected to their nearest neighbor to form
        triangles which are as equi-angular as
        possible.
   Borders are a problem
       Go beyond study area and clip to make best
Terrain Mapping
 Contouring is most common method for
  terrain mapping
 Contour lines connect points of equal
  elevation (isolines)
 Contour intervals represent the vertical
  distance between contour lines.
 Arrangement of contour lines reflect
  topography
Terrain Mapping
   Vertical profile shows changes in elevation
    along a line, such as a hiking trainl, road
    or stream.
Terrain Mapping
 Hill shading is also known as a shaded
  relief or simply shading
 Attempts to simulate how the terrain looks
  with the interaction between sunlight and
  surface features.
 Helps viewers recognize the shape of land-
  form features on a map.
 Digital shaded-relief map of US
Terrain Mapping
   Four factors control the visual effect of
    hill-shading
       Sun’s azimuth is direction of incoming light (0
        to 360°)
       The sun’s altitude from horizon (0-90°)
       Surface slope (0-90°)
       Surface aspect (0 to 360°)
Terrain Mapping
   Hypsometric tinting
       Applies different color symbols to represent
        elevation zones.
Terrain Mapping
   Perspective View
       Perspectives are 3-D views of the terrain
        wherein the appearance is as viewed from an
        airplane.
       Viewing azimuth (0 to 360°)
       Viewing angle (0-90°)
       Viewing distance
       Z-scale is ratio between he vertical scale and
        the horizontal scale (exaggeration factor)
   3-D draping of vector information
Terrain Analysis
 Slope measures the rate of change of
  elevation at a surface location
 Aspect is the directional measure of the
  slope (degrees- 4 or 8 directions)
 Important for analyzing an visualizing
  landform characteristics
 Accuracy an issue
 If you want to try, use the worked
  examples in the text with Excel
Terrain Analysis
 Surface curvature: convex or concave
 Viewshed analysis
       Viewshed refers to the areas of the land
        surface that are visible from an observation
        point or points.
   Watershed analysis
       Watershed is an area that drains water and
        other substances to a common outlet
Terrain Analysis
   Watershed analysis
       Requires three data sets in raster format
       Filled elevation grid
       Flow direction grid
       Flow accumulation grid
Grid vs TIN
 Different algorithms and type of output
 Can be converted from TIN to grid or grid
  to TIN
 TIN has flexibility of input sources: DEM,
  breaklines, contour lines, GPS data and
  survey data as well as user added
  elevation points.
 Elevation grid is fixed with a given cell size
Grid vs TIN
 Computational efficiency with grid
 TIN gives sharper image
 How are they built and used?

								
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