Lab 2

Lab 5

Goal:

LiDAR is an extremely using way of remotely sensing features. In this lab LiDAR data was used to process various surface and terrain models and create intensity images. All the LiDAR point clouds are formatted in LAS files.

Methods:

Part One of the lab consisted of copying the LAS files to a personal folder.

Part Two: Generate a LAS dataset and explore lidar point clouds with ArcGIS

In this part, as a GIS manager, I am working on a project for the city of Eau Claire, WI using LAS files acquired from the city. First, the LAS files were brought into ArcGIS, which is the program that is used throughout this lab. They were arranged into an LAS dataset. Once they are brought in, the statistics of each file can be observed. To make sure the data were accurate, the elevation of certain points can be compared to Eau Claire’s actual elevation. To ensure accuracy, the XY coordinate system was set to NAD 1983 HARN Wisconsin CRS Eau Claire (US Feet) and the vertical coordinate system was set to NAVD 1988 US Feet. A shapefile of Eau Claire was added to confirm that the data was spatially located correctly. 

Once the data were brought in, the LiDAR data was observed using different LAS data surfaces. Elevation, slope and contour were closely looked at. Looking at these surfaces with all the different filters using returns (All, ground and first) gave different perspectives also. Another useful tool is the Profile View tool, which allows the user to select an area of the image to view separately in either a 3D or a 2D view.

Part Three: Generating LiDAR derivative products.

Section One:

In this section a digital surface model with first return (DSM), digital terrain model (DTM) and hillshades of both were created. To determine spatial resolution the average nominal pulse spacing was determined. The spatial resolution was determined to be 2 meters. The LAS to Raster tool is used to create the models and natural neighbor was used to filled in any voids. A hillshade tool was used to create a hillshade which enhanced the DSM and DTM models. The images are revealed in the results portion. The difference between the DSM and the DTM models is that DSM uses the first return LiDAR points to display surface features, such as houses and trees, as well as the ground. The DTM model uses ground return points which better display elevation and terrain of the bare Earth.

Section Two:

In this section a LiDAR intensity image was created using almost the exact same method as DTM and DSM. Intensity imagery is created using first return points and the natural neighbor method was used again. Intensity images help interpret and classify LiDAR masspoints.

Results:

This image is slope LiDAR data.

This is contoured LiDAR data.

This is a 2D profile of a bridge using the LiDAR data.

Using the 3D profile tool one can view the bridge from different angles.

The following is the DSM, which shows suface features such as houses and trees.

 The following is the DTM, which shows ground features and reveals more information about the terrain.