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Remote Sensing Lab 5

Purpose: 

The purpose of this lab was to gain basic knowledge of LiDAR data structure and processing. This was done in two distinct phases. The first phase involved the retrieval and processing of surface and terrain models. The second phase dealt with the processing and creation of intensity images and other products using Point Cloud data in LAS file format. The data for this lab was sourced from Eau Claire County and the 6th edition of Mastering ArcGIS by Margaret Price.

Methods:

The first portion of the lab involved retrieving and processing data for analysis. Because of the very large size of the data, a separate folder was created to store it. The next step was to create an LAS dataset in ArcMap. The dataset was created using Lidar Point Cloud data for the City of Eau Claire The data provided by the instructor was copied into a personal folder and an LAS dataset was created within the LAS folder under the ArcMap catalog. The dataset was renamed and the LAS files were added. After the points were added, statistics for the dataset were calculated using the calculate feature under the statistics tab. The data set was assigned the NAD 1983 HARN Wisconsin CRS Eau Claire (US Feet) horizontal and NAVD 1988 US feet vertical coordinate systems.

The second part of the lab dealt using the created LAS data set was used to generate a variety of Lidar products. To do this the LAS dataset was converted to a raster using the LAS dataset to a digital surface model (DSM) raster conversion tool. The parameters included an elevation value field, a maximum cell assignment type, a natural neighbor void fill method and a cell size sampling type with a value of 6.56168. This raster DSM was then enhanced using the Hill shade raster surface tool in the 3d analyst toolset. The results may be seen below in figure 1.

The second product generated in this lab was a Hillshade Digital Terain Model (DTM). Using the LAS dataset toolbar in ArcMap, the raster imaged was filtered to make the ground visible. Then, a new raster was generated using the LAS dataset to raster tool. The parameters used for the first raster were repeated, except the cell assignment type was changed to minimum. The Hillshade tool was then used on the resulting raster. The results can be seen below in figure 2.
The final generated product was a Lidar Intensity image. The created dataset was set to points and filtered to First Return. This is because intensity is captured by first return echos. The intensity image was created with the following parameters; an intensity value field, an Average binning cell assignment type, a natural neighbor void fill, and a cell size of 6.56168. The result was then saved as a tiff file and displayed in Erdas Imagine software to enhance the image. The results can be seen below in figure 3. 

Results: 

Figure 1
Hillshade Digital Surface Model of the city of Eau Claire

Figure 2
Hillshade Digital Terrain Model of the city of Eau Claire

Figure 3
Lidar Intensity image of the city of Eau Claire

Data Sources

Lidar and Point Cloud data: City of Eau Claire 2013

Eau Claire County Shapefile: Mastering ArcGIS 6th Edition by Margaret Price

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