Geography 338: Remote Sensing: Lab 5

Background and Goals

The objective of this lab was to be exposed to the processing and data structure of LiDar data. This included processing various surface and terrain models and the creation of intensity images and similar models using derivative products from point cloud data. Data was presented in LAS file format.

Methods

The first section lab was to create a LAS database in ArcMap using the LAS files in the class folder. Once I created the data base, I calculated the statistics of the data. The next process that I needed to complete to bring the data into ArcMap was to assign the data coordinate system for both XY and Z. To find the correct coordinate system for the data I looked in the metadata for the LAS files where I found the correct coordinate systems. For the XY (horizontal) coordinates the coordinate systems was D_North_American_1983 and the Z (vertical) was North American Vertical Datum of 1988.

I then imported the newly created LAS dataset into ArcMap (figure 1). To make sure the data was spatially located correctly, I overlaid the LAS data set with a shapefile that contained the outline of Eau Claire. After verifying that the data was indeed correct I proceeded to the next section lab.

The next section of the lab involved using the LAS to Raster and Raster Surface tools in ArcMap to create both Digital Surface (DSM) and Digital Terrain Models (DTM). To create the DSM, I first used the LAS Raster Tool to convert my LAS Dataset into a raster image where the the Raster Surface Tool could process it. In the LAS TO Raster Tool, I used the elevation field, set the cell assignment to Maximum, and Void Fill Method to natural neighbor. Changed the cell size to 6.56 (~2 meters). Once the raster tool had processed the image, I brought this new image into a blank new ArcMap browser, where I ran the Hillshade Raster Surface tool to create the DSM image (Figure 2).

To create the DTM model I filtered the original LAS data set to only show the Ground category and used the LAS TO Raster Tool again used similar parameters as used to create the DSM image. I set the Interpolation method to Binning, Cell Assignment Type to Minimum, Void Fill Method to Natural Neighbor, and Sampling Cell value to 6.56 feet. I then used the Raster Surface Tool and processed the image using the Hillshade option. Where I created the image in (Figure 3).

The DTM model shows the information only at the ground level and excludes surface features such as buildings and vegetation. DSM models are useful for identifying surface features and determining spatial relationships between them. DTM models are better for studying the shape and topology of the actual bare surface.

I then created an Intensity Image from the LAS data. Intensity Images measure the highest voltage captured by the sensor. This can be used to aid in identifying classified Lidar data. To create this model, I filtered the LAS Dataset to First Return. I then used the LAS To Rater Tool set the Value Field to Intensity, Binning Assignment to Average, Void Fill to Natural Neighbor, and Cell Size to 6.56 feet. Once the Image was finished processing I converted the image to a TIFF file where I could then open it in Erdas Imagine (Figure 4).

Results