Goals and Background
The goal of this lab is use and analyze LiDAR point data in the LAS file format. Below is a list of the tasks to complete in this lab.
1. View the LiDAR points in Erdas
2. Import the LiDAR points into ArcMap as a LAS Dataset
3. Calculate statistics for the LAS Dataset in ArcMap
4. Assign a coordinate system to the LAS file in ArcMap
5. Examine the LAS Dataset toolbar and Properties
6. Generate a DSM and Hillshade from 1st returns from the LiDAR points
7. Produce a DTM and Hillshade from the last returns of the LiDAR points
8. Derive a LiDAR inensity image from the LiDAR points
Methods
1. View the LiDAR Points in Erdas
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| Fig 2.1: Prompted Dialog Box |
This was done by first opening Erdas and brining in all the files at once. This can be seen below in figure 2.0. Then a dialog box was promted which the user clicked No and unchecks Always Ask. This can be seen on the right in figure 2.1.
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| Fig 2.0: Bringing in LiDAR points to Erdas |
2. Import the LiDAR points into ArcMap as a LAS Dataset
First, the quarter quarter sections were brought into ArcMap to use as a reference layer for the LAS Dataset. To create the LAS Dataset, first an output folder (LAS) was specified. Then, the LAS Dataset was created by right clicking on the LAS folder and then navigating to New → LAS Dataset. Then, the LAS Dataset was given the name Eau_Claire_City.lasd. To import the LiDAR points into the data set, first, the LAS Files tab in the properties of the LAS Dataset were active. Then, the Add Files... button was used load all of the .las files using a similar process as what is shown in figure 2.0 above.
3. Calculate Statistics for the LAS Dataset in ArcMap
To calculate the statistics for the LAS dataset, the Statistics tab in the LAS Dataset's properties was activated and the Calculate button was clicked. This is shown below with the green ovals in figure 2.2. Then, some of the statistics were looked at such as the minimun and maximum z values.
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| Fig 2.2: Calculating the Statistics for the LAS |
4. Assign a Coordinate Systemto the LAS Dataset in ArcMap
To assign the LAS Dataset a coordinate information, both the coordinate system had to be set in the horizontal in vertical directions. Before the coordinate system could be assigned in ArcMap, the coordinate system information had to found by looking in the metadata of the LAS Dataset in NotePad ++. The section containing the spatial reference information for both the horizontal and vertical references can be seen in figure 2.3. This block of code was found by looking at all of the the tags in the meta data file in blue text and then finding where the spatial reference tags were found. Also, it was found by browsing the file for the spatial reference data. For the horizontal spatial reference, the map projection is Lambert Conformal Conic, the datum used in the North American Datum of 1983, and the units are in survey feet. For the vertical spatial reference the datum used is the North American Vertical Datum of 1988, and the unit used is feet.
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| Fig 2.3: Finding the Horizontal and Vertical Spatial Reference in the Meta Data |
To assign the horizontal coordinate system, the
XY Coordinate System tab was clicked on and the
NAD_1983_HARN_WISCRS_EauClaire_County_Feet coordinate system was searched for and then assigned as shown below in figure 2.4. To assign the vertical coordinate system, the Z Coordinate System tab was clicked on and the NAVD88 (depth) (ftUS) coordinate system was searched for and then assigned as shown below in figure 2.5.
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| Fig 2.5: Assigning the Z Coordinate System |
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| Fig 2.4: Assigning the XY Coordinate System |
5. Examine the LAS Dataset Toolbar And Properties
The LAS Dataset Toolbar was then used to examine the Lidar points without generating any new data. The main features of the toolbar looked at include the
Filters, Points, Interpolation, and
Profile View features. The LAS Dataset Toolbar can be seen below in figure 2.5 along with the labeled features. Before using these, the number of classes used to display the Lidar points in the LAS Dataset was changed from 9 to 8.
The
Point dropdown allows for one to display the LiDAR points as raw points, classified according to class, or classified according to elevation. The
Interpolations/Contour Lines dropdown allows one to display an interpolation of the LiDAR points with the value of the points displaying elevation, slope, or aspect. This dropdown also allows one to display contour lines generated from the LiDAR points. The
Filters dropdown allows one to filter the LiDAR points by the classes
Ground, Non Ground, and
First Return. Lastly, the
Profile View feature was looked at. This allows one to create a 2D or 3D profile of the LiDAR points including measuring and visualizing height differences between different points.
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| Fig 2.6: LAS Dataset Toolbar |
Also, the properties of the LAS Dataset were looked at. In the properties, the
Symbology and
Filter tabs were looked at.
The
Filter tab is another place where the LiDAR points can be reclassified similar to the
Filters on the LAS Dataset toolbar. Here, the predefined settings
All(Default), Ground, Non Ground, and
First Return were analyzed and modified to show different returns in the LiDAR points. Figure 2.7 shows the
Filter tab being used to classify the non ground LiDAR points. The
Symbology tab has similar characteristics of the
Interpolations / Contour Lines feature on the LAS Dataset toolbar except that it does not interpolate the points. In the
Symbology tab, one can choose to display the LiDAR points with their elevation values, their aspect values, their slope values, or can display generated contour lines. Figure 2.8 shows how the
Symbology tab is used to display and classify the slope values of the LiDAR points
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| Fig 2.8: Symbology Tab in the LAS Dataset Properties |
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| Fig 2.7: Filter Tab in the LAS Dataset Properties |
6. Generate a DSM and Hillshade from the 1st Returns of the LiDAR Points
To do this, first the workspace of the ArcMap document was set to this lab's output folder. Then, the
LAS Dataset to Raster tool was used to make the DSM surface. Before opening the tool, the LAS Dataset toolbar was used to display the LiDAR points by first return points coded by elevation. Then, the
LAS Dataset to Raster tool was opened and the parameters were set. The tool input can be seen below in figure 2.8. To produce the hillshade of the DSM, the
Hillshade tool was used with the input being the newly created DSM.
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| Fig 2.8: Generating a DSM from LiDAR |
7. Produce a DTM & Hillshade from the last returns of the LiDAR points
For this, the
LAS Dataset to Raster tool was used to generate the DTM surface. The last returns in the LAS Dataset layer were displayed in the ArcMap view using the LAS Dataset toolbar. To filter these returns, the properties were changed under the
filter tab so that
Ground class and the
Last Return return were checked. Then, the
LAS Dataset to Raster tool was used and set with the parameters shown in figure 2.9 to produce the DTM. To produce the hillshade for the DTM, the
Hillshade tool was used with the newly generated DTM as the input.
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| Fig 2.9: Generating a DTM from LiDAR |
8. Derive a LiDAR Intensity Image from the LiDAR Points
This also consisted of using the
LAS Dataset to Raster tool. Because LiDAR intensity is measured by first returns, the LAS Dataset toolbar was used to display the first returns in the ArcMap view. Then, the
LAS Dataset to Raster tool was used with the the proper input parameters as shown below in figure 2.10.
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| Fig 2.10: Generating the Intensity Image from LiDAR |
Results
Figure 2.11 depicts a map of the DSM generated from task 6. This DSM represents the first returns surface collected by the LiDAR sensor. The DSM values over the water on Halfmoon Lake and parts of the Chippewa River can be ignored because in these areas the LiDAR values were inaccurate due to a low number of points being collected on water surfaces.
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| Fig 2.11: DSM Map |
Shown below in figure 2.12 is a map of the hillshade generated from the DSM above. This hillshade was created as a part of task 6. Because this hillshade is based off of first returns, it is messy. The hillshade is mostly generated to help explain the DSM above through shading and relief. It shows relief values from low to high. The legend for the hillshade values aren't shown because they don't carry any units or analytical meaning. The hillshade is produced just to help visualize the DSM above. Usually, the hillshade can be overlaid with a DSM, but in this case, the result looked unorganized and messy, so they were split apart.
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| Fig 2.12: Hillshade Map Generated from the DSM |
Figure 2.13 shows the DTM of Eau Claire overlaid with the hillshade generated by it. These rasters were created in task 7.To help the hillshade visualize the DTM, the hillshade layer is displayed at 50% transparency. This DTM shows the last returns and the ground returns of the LiDAR points. This DTM could have many potential uses including modeling the volume of hills or sand piles, or flood modeling.
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| Fig 2.13: DTM Overaid with a Hillshade Map |
Lastly, figure 2.14 displays the LiDAR intensity map created from the LiDAR intensity image generated in task 8. The LiDAR intensity image as the look of a black and white aerial photo because like the DSM, the intensity values are based of of the first returns. This map can be used to identify features based on intensity values. For example, water features have very low intensity values and be identified by their black color.
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| Figure 2.14: LiDAR Intensity Map |
Sources
Eau Claire County, 2013. LiDAR Point Cloud and Tile Index
Price, Margaret, 2014, Eau Claire County Shapefile, Mastering ArcGIS 6th Edition Data
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