Goal and Background:
The goal of this exercise was to show my ability to: processes and retrieve various surface and terrain models and process and create an intensity image and other derivative products from a point cloud.
Methods:
Part 1: Point Cloud Visualization in Edras Imagine
I opened the LAS dataset with ArcMap and used the label manager and a shapefile to determine the tile position of the files within the dataset.
Part 2: Generate a LAS dataset and explore Lidar point clouds with ArcGIS
Section 1: Create Folder Connection
I used ArcCatalog to created a LAS dataset containing the Eau Claire data files. I ensured that the correct statistics were with the files and looked at the metadata to assign the proper horizontal and vertical coordinate systems.
Part 3: Generation of Lidar derivative products
Section 1: Deriving DSM and DTM products from point clouds
I used the LAS Dataset to Raster tool in the ArcToolbox to create my digital surface model of the first return by setting the points tool to color for elevation and the filter for first return. I used a Binning interpolation method with a natural neighbor void filling and a 2 meter cell size. I then created a hillshade of the DSM by using the 3D Analyst Tools in the ArcToolbox.
I then used the LAS Dataset to Raster tool in the ArcToolbox again, this time setting the filter to GROUND with the point tool show points colored for elevation to create the DTM. I used a Binning interpolation method with a natural neighbor void filling and a 2 meter cell size. I then created a hillshade of the DTM by using the 3D Analyst Tools in the ArcToolbox.
Section 2: Deriving Lidar Intensity image from point cloud
I set the LAS dataset to Points and the filter to first return. I then used the LAS Dataset to Raster tool in the ArcToolbox, setting the value field to INTENSITY, the Binning cell assignment to AVERAGE, the void fill to natural neighbor and the cell size to 2 meters.
Results:
Figure 1. This image demonstrates the results from part 3, section 1 and shows the hillshade image of the DSM.
Section 1: Create Folder Connection
I used ArcCatalog to created a LAS dataset containing the Eau Claire data files. I ensured that the correct statistics were with the files and looked at the metadata to assign the proper horizontal and vertical coordinate systems.
Part 3: Generation of Lidar derivative products
Section 1: Deriving DSM and DTM products from point clouds
I used the LAS Dataset to Raster tool in the ArcToolbox to create my digital surface model of the first return by setting the points tool to color for elevation and the filter for first return. I used a Binning interpolation method with a natural neighbor void filling and a 2 meter cell size. I then created a hillshade of the DSM by using the 3D Analyst Tools in the ArcToolbox.
I then used the LAS Dataset to Raster tool in the ArcToolbox again, this time setting the filter to GROUND with the point tool show points colored for elevation to create the DTM. I used a Binning interpolation method with a natural neighbor void filling and a 2 meter cell size. I then created a hillshade of the DTM by using the 3D Analyst Tools in the ArcToolbox.
Section 2: Deriving Lidar Intensity image from point cloud
I set the LAS dataset to Points and the filter to first return. I then used the LAS Dataset to Raster tool in the ArcToolbox, setting the value field to INTENSITY, the Binning cell assignment to AVERAGE, the void fill to natural neighbor and the cell size to 2 meters.
Results:
Figure 1. This image demonstrates the results from part 3, section 1 and shows the hillshade image of the DSM.
Sources:
All data was provided by Dr. Wilson with Lab 5.
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