Using Lidar Data

Lab 5: Using Lidar Data

Introduction

To create accurate and high resolution maps we need to use data that is not from Digital Elevation Models which are becoming obsolete. The data that we need to use to create highly accurate high resolution maps is known as LIDAR or Light Detection and Ranging. This data is very interesting since it using UV Visible and NIR wavelengths to map physical features by emitting a laser to the ground and measuring the return rate. Using this data we can begin to create high resolution maps that are useful for Agriculture, Geologic process, surveying and even mapping of the ocean floor. Our application of LIDAR was to create basic hill shaded Digital Terrain Models (DTM) and Digital Surface Models (DSM)

Goals

The main goal of this lab exercise was to gain basic knowledge of lidar data structure and processing. The tasks that we were required to do were the processing and retrieval of the various surface and terrain models and to use this data to process and create a variety of images and products from the point cloud developed by the lidar data.

Methods

To create these high resolution maps we first downloaded the raw Lidar data from the assigned lab folder provided. Using this data we created a new LAS data set named Eau_Claire_City. After adding the LAS files to the data set window we were able to calculate and project a coordinate system for the xyz axis. When this data was projected onto ArcMap we were able to see the point cloud returns from the data. Using this raw Lidar data we are able to warp the map based on elevation, contour lines, aspect and slope. We were also using the lidar dat to create interactive views by using the profile view tool in the LAS Toolbar

The power of Lidar, Returns of Phoenix park bridge 

We were then able to create a DSM and DTM by manipulating the LIDAR data. We used the Arc Tool box to create a raster from the LIDAR data by following the route:

Conversion tools to raster> to las dataset> to raster

This allowed us to create a DSM based on the criteria that we selected. For our models we used parameters of Binning, Cell Assignment set to maximum and natural neighbor as the void fill method with a cell size of 2 meters per pixel for the raster. After the DSM was completed we then created a Hillshade effect to the DSM.

DSM Raster before Hillshade

DSM after Hillshade

Next we created a DTM which would only show the terrain of the area we were studying. We followed the same route as the DSM but switched it to minimum cell assignment type. We also only looked at the ground return of the LIDAR data. This will ignore all other returns except for those marked by the ground effectively giving us a look at only the terrain model.

DTM Raster with Hillshade

We also created an Intensity image that is only in black and white. This is very helpful for identifying features where a lot of detail is needed.

Intensity Image

Results

The results involved us creating new and exciting LIDAR maps based on DSM, DTM and Intensity. All of these will allow us to use lidar data to our advantage. This will be helpful in geologic practices, land use surveying and slope effects in the Eau Claire area.