Lab 5: LiDAR remote sensing

Goal:

The Goal for this lab was to become familiar with LiDAR data and to use it to make various products such as DTM and hillshade models.

Methods:

Part 1:

For the first part of this lab, LAS data was imported into Erdas Imagine so the LiDAR point cloud can be visualized. This is done by selecting the LAS files that are desired and to open them in Erdas Imagine. This will bring in the point cloud into the workspace and allow it to be visualized.

Part 2:

For this part of the lab, a LAS dataset needs to be created and to make sure that the quality of the data is good by looking at the statistics. To do this, arcmap needs to be opened and the folder the LAS data is in needs to be connected to arcmap. Next, in the catalog, a new LAS dataset needs to be created by right clicking on the folder its going into and selecting new and then LAS dataset. Once the LAS dataset is created and named, the individual LAS files can be brought into the newly created dataset. Once the files are in the dataset, the statistics tab can be opened and the calculate button can be pressed. This will calculate statistics based on the LAS files added to the dataset. The next thing that needs to happen is the horizontal and vertical coordinate system need to set. This information can be found in the metadata for the LAS files. Once the vertical and horizontal coordinate systems are found in the metadata, the LAS dataset can be set to the same coordinate systems. Next, a shapefile for the study area is added to ensure that the coordinate system is correct.

Part 3:

For the last part of the lab, a DSM and DTM are created from the point cloud. To do this, keep the LAS data in the workspace and navigate to the conversion tools and then to raster and finally click on LAS dataset to Raster. Use the LAS dataset at the input and select elevation as the value field. Select Binning interpolation with the cell assignment type set to maximum and the void fill method to natural neighbors and set the sampling value to 6.56168, which is about 2 meters. Once this is done, the tool can be run to make the DTM. Next, navigate to the 3d analyst tools and then to raster surface and finally to hillshade. Open the hillshade tool and use the DTM as the input. This will create a hillshade model for the DTM. Next, set the LAS dataset to show only ground point and use that to do the same steps as the DTM except change cell assignment type to minimum. This will create a DTM with a hillshade.

Results:

Part 1:

The results for part one can be seen below in figure 1. Figure 1 shows the point clouds for the LAS data.

Figure 1. LAS point cloud. 

Part 2: The results from this part of the lab is that statistics were calculated (figure 2) and the horizontal (figure 3) and vertical coordinate systems (figure 4) are set.

figure 2. Statistics for the LAS dataset. 

Figure 3. Horizontal coordinate system for LAS dataset. 

figure 4. The vertical coordinate system for LAS dataset. 

Part 3: 

This part of the lab resulted in two hillshade models made from the DTM and DSM. Figure 5 below shows the hillshade made from the DSM. Figure 6 below shows the hillshade made from the DTM.

Figure 5. DSM hillshade model. 

Figure 6. DTM hillshade model. 

Source:

Lidar point cloud and Tile Index are from Eau Claire County, 2013.

Eau Claire County Shapefile is from Mastering ArcGIS 6th Edition data by Margaret Price, 2014