Load and color DEMs

1

• Load and color DEMs
• Hillshade DEMs
• Slopeshade DEMs
• Combine shade and color
• Differencing, canopy and serial data
• Generating Contours
• Point and Profile queries
• Ground Point Density

DOGAMI lidar data sample from Carpenterville on
Southern Oregon Coast. Bare earth and highest hit
(or first return, or reflective surface) 3 ft
DEMs, from 8 pulse/m2 leaf on data.
2
Load and color DEM

• Add datagt Bare_Earth_DEM and Highest_hit_DEM
• Native scheme is grayscale with low values dark
• Right click layergt propertiesgt symbology
• Select your preferred color scheme
• Note differences between the two DEMs
• DEM image alone is not a particularly useful
  visualization

3
Hillshade visualization

• Arc Toolboxgt 3D Analystgt Raster Surfacegt
  Hillshade
• Input, Bare_Earth_DEM, set output to
  be_hs_315.img, accept defaults and run
• Input Bare_Earth_DEM, set output to
  be_hs_225.img, set azimuth to 225 and run
• Note difference in hillshades, some illumination
  angles simply dont work.
• Experiment with highest_hit_DEM, Azimuth,
  Altitude, Z factor, shadows

4
Slopeshade Visualization

• Arc Toolboxgt 3D analystgt Raster surfacegt slope
• Input Bare_earth_DEM, set output to be_slope.img,
  run
• Default color scheme is poison-dart frog
• Right click layergt propertiesgt symbologygt choose
  stretched, invert, standard deviations and set n
  to 5
• Slopeshade map is universal hillshade.
• Shading curve can be adjusted to illuminate
  features in the very steep or very gentle ends of
  the slope range, under Symbology, click
  histograms and play with nodes on curve to
  reshape
• Experiment with Highest_hit_DEM

5
Combine layers

• Turn off all layers
• Load orthoimage
• Right click layergt propertiesgt displaygt set
  transparency to 50
• Turn on highest hit hillshade or slopeshade
• Turn off all layers except beslope and
  Bare_Earth_DEM. Drag beslope below
  Bare_Earth_DEM, set Bare_Earth_DEM display to 50
  transparency. This combination is very useful
  for mapping geologic and geomorphic features
• Play with combinations of layers!
• 70 orthoimage over 70 highest hit hillshade
  over bare earth slopeshade makes a nice basemap.

6
DifferencingCanopy Height

• Turn off all layers
• Load Highest_Hit_DEM and Bare_Earth_DEM
• Arc Toolboxgt 3D Analystgt Raster Mathgt Minus
• Use Highest_Hit_DEM for input 1, Bare_Earth_DEM
  for input 2, canopy.img for output, run
• Right click canopy layergt propertiesgt displaygt
  set transparency to 50 then symbology and choose
  your favorite color scheme
• Turn on highest hit hillshade or slopeshade and
  position under canopy.
• Combined image shows the height of vegetation,
  structures, can you find the transmission lines?
• Note negative values in canopy. Highest hit and
  bare earth surfaces are made from different
  collections of points.

7
DifferencingSerial Data

• Turn off all layers
• Load be_leaf_off and be_leaf_on, select one and
  click zoom to layer
• Arc Toolboxgt 3D Analystgt Raster Mathgt Minus
• Use be_leaf_off for input 1, be_leaf_on for input
  2, serial.img for output, run
• Right click serial layergt propertiesgt displaygt
  set transparency to 50 then symbologygt
  classified, say yes to create histogram, click on
  classify, and set values to -3, -1, 1 and 3.
  Click ok to return to main symbology tab, double
  click patches to select color, set lowest purple,
  next blue, next (-1 to 1) to no color next to
  orange, highest to red.
• Load leaf_off_beslope and place it under serial
• Image now shows areas of erosion as orange and
  red, deposition as blue and purple. You should be
  able to find two landslides and three debris flow
  scars.
• Widespread noise is due to differences in ground
  models under heavy vegetation
• Serial comparisons require high quality data.

8
Contours

• Arc Toolboxgt 3D Analystgt Raster Surfacegt
  Contour
• Input be_leaf_off.img, accept default output, set
  contour interval to 1, run.
• Resultant 1m contours provide additional detail
  on shape of landscape, particularly in areas of
  low slope.
• Contours can greatly slow down redraw, minimize
  this by using contour with barriers and selecting
  a 1km grid file as the barrier.
• Contours from lidar can be very rough, reflecting
  the high resolution of the DEM and the natural
  roughness of the surface. For nicer looking
  contours without significant loss of accuracy,
  use Arc Toolboxgt Spatial Analystgt Neighborhoodgt
  Focal Statistics to smooth DEM before contouring.

9
Query Lidar, Point and profile

• Turn off all layers
• Turn on slope_be and canopy, select one and click
  zoom to layer
• Click on info tool, select all visible layers,
  click on point of interest to see point location
  and elevation values
• From main menu select Viewgt Toolbarsgt and check
  3D Analyst
• In 3D Analyst toolbar, click layer list control
  and select canopy
• From 3D Analyst toolbar select interpolate line,
  draw line across area of interest.
• Initial interpolate line will be slow while grid
  is indexed.
• When line appears, select create profile graph
  from 3D Analyst toolbar
• Profile will appear in window, which can be
  stretched in X or Y.
• Right click profile to see print and export
  options.

10
Ground Point Density

• It is important to understand how good the data
  behind your DEM is, and ground point density is
  critical
• Add the file 42124B3317.GPD, right click the
  layer and select zoom to layer
• This is a vendor-supplied ground point density
  grid, white areas have gt 1 ground point per 4m2,
  black areas less.
• Zoom to a large area of black, and then turn off
  the GPD grid, leave on only the be_slope grid,
  note the obvious TIN triangle outlines in the
  grid. This is a simple graphic indicator of
  ground point density. Use the measurement tool
  to measure some of the TIN side lengths, some are
  quite long.
• To make your own groundpoint density grid Arc
  Toolboxgt Conversiongt From Filegt LAS to
  Multipoint, choose 44124B3317_ground as input,
  ground_points as output, point spacing of 2 and
  run.
• Select Arc Toolboxgt Conversion Toolsgt To Raster
  gt Point to Raster, use ground_points as input,
  pointcount as value field, accept default output,
  set cell assignment type to COUNT, cellsize to 15
  and run.
• Assign a color scheme to the resulting raster,
  make it 50 transparent and drape over the
  be_slope layer. Examine how the DEM looks in
  areas of low point density.

11
Additional Resources

• http//blogs.esri.com/Dev/blogs/geoprocessing/arch
  ive/2008/11/06/Lidar-Solutions-in-ArcGIS_5F00_part
  -1_3A00_-Assessing-Lidar-Coverage-and-Sample-Densi
  ty.aspx
• http//cws.unavco.org8080/cws/learn/uscs/2008/200
  8Lidar/handouts/GeoEarthScopeDataTutorialApril08.p
  df
• lthttp//cws.unavco.org8080/cws/learn/uscs/2008/20
  08Lidar/handouts/GeoEarthScopeDataTutorialApril08.
  pdfgt
• http//cws.unavco.org8080/cws/learn/uscs/2008/20
  08Lidar/handouts/GLW_and_ArcMap.pdf
  lthttp//cws.unavco.org8080/cws/learn/uscs/2008/20
  08Lidar/handouts/GLW_and_ArcMap.pdfgt
• http//arrowsmith410-598.asu.edu/Lectures/Lecture1
  4/ lthttp//arrowsmith410-598.asu.edu/Lectures/Lect
  ure14/gt
• http//arrowsmith410-598.asu.edu/Lectures/Lecture1
  5/ lthttp//arrowsmith410-598.asu.edu/Lectures/Lect
  ure15/gt