Third exercise. Last step of this workflow: Classification and filtering. Here we learned some interesting things about OPALS and SCOP++ software's. First time, when I used SCOP++, but I think, it is an useful software to create DTM's....
Classification and filtering of full-waveform ALS data from Gottfried Mandlburger.
"Program:
Perform the following tasks with one of the prepared datasets:
1) Digital Surface Model (DSM) using OPALS
a) Import first echoes of FWF dataset (project_first_echo.xyz ) into the OPALS Data Manager (opalsImport)
b) Calculate a Digital Surface Model (opalsGrid) and quality models (sigma, excentricity)
c) Visualize the resulting DSM as hill shading (opalsShade) and color coded raster map (opalsZColor)
d) Visualize the sigma and excentricity model (opalsZColor) and compare and interpret the results visually with respect to the hill shading
2) Analysis of Full Waveform (FWF) Attributes:
a) Import last echoes of FWF dataset (project_last_echo.xyz ) into the OPALS Data Manager (opalsImport)
b) Perform raster analysis of FWF attributes (opalsCell):
• Amplitude
• Echo width
c) Derive color coded visualizations of the attribute/echo width raster (opalsZColor)
d) Compare and interpret the results visually with respect to the hill shading
3) Perform a standard DTM filtering / classification of the point cloud
a) Derive a Digital Terrain Model based on the last echoes (project_last_echo.xyz) using SCOP++ (Robust Interpolation, strategy :Lidar DTM Default)
b) Visualize the DTM (hill shading, Z-Coding, Isolines …)
4) Filtering of the point cloud with pre-classification on echo width basis
a) Repeat the steps 3a and 3b for the last echoes with small echo widths (ew<1.9ns (project_last_echo_small_ew.xyz)
b) Compare and interpret the results visually with respect to the results of Step 3 by means of the hill shading
5) Extra task: Difference model
a) Derive a normalized Surface Model: nDSM = DSM-DTM (opalsDiff)
b) Visualize the nDSM (opalsZColor)"
No comments:
Post a Comment