conservation applications of lidar€¦ · conservation applications of lidar forestry applications...

Conservation Applications of LiDAR

Forestry Applications Workshop Exercises

2012

These exercises are part of the “Conservation Applications of LiDAR” project – a series of hands‐on workshops designed to help Minnesota GIS specialists effectively use LiDAR‐derived data to address natural resource issues. The project is funded by a grant from the Environment and Natural Resources Trust Fund, and is presented by the University of Minnesota Water Resources Center with expertise provided from the University of Minnesota, MN

Department of Natural Resources, MN Board of Water and Soil Resources, and USDA Natural Resources Conservation Service. More information is at http://tsp.umn.edu/lidar.

Forestry Applications of LiDAR, Exercise 1 Ex1‐1

Exercise 1: Introduction to LiDAR‐Forestry

What You’ll Learn:

- Connect to the DNR LiDAR FTP site

- Understand the data file organization

- Set up data for Lab exercises

- Uncompress LiDAR raw data

Data for this exercise are located in the LiDAR_Exercise1 subdirectory.

Videos for this exercise are located in the \Instructional Videos\LiDAR subdirectory. (soon)

What You’ll Produce:

- a directory structure to store and analyze LiDAR data - loading sample LiDAR data files.

The MN DNR provides LiDAR data for Minnesota. Most of the state is now available, see the Following link for a status map: http://www.mngeo.state.mn.us/committee/elevation/resources/lidar_status_map_mn.pdf Additional information about this data and related programs can be found at: http://www.mngeo.state.mn.us/chouse/elevation/lidar.html All available data is currently accessible via anonymous ftp at: ftp://lidar.dnr.state.mn.us Or MNGeo at ftp://ftp.lmic.state.mn.us /pub/data/elevation/lidar/ As the data files are VERY large it is important to access them via to a FTP client; examples are WS FTP, GNU Wget, or FileZilla. Windows Explorer or other browsers will NOT handle this size data. Some additional information on the LiDAR data is also available at the MNGEO website: http://www.gda.state.mn.us/resource.html?Id=16253#download Use your FTP program to connect to the DNR site (an example is shown to the right of one such program).If you use your own FTP client, use lidar.dnr.state.mn.us for Host Name or Port, enter anonymous as the User name and enter your email address for the Password.

Example


For this exercise we will use a free, open source FTP client, FileZilla FTP Client. The LiDAR training modules and associated training modules are located on the 8GB, Patriot USB drive provided by the instructor. Please return the USB drive to the instructor at the conclusion of your training exercises. Uncap the Patriot USB drive and insert in any USB port on the training room computer. The USB drive will receive one of several possible drive letters: E:\ or F:\ or G:\ depending upon the computer used. All references in these training modules will refer to the USB drive will use the letter E:\. If necessary you should adjust drive letters accordingly. RIGHT click upon the Start Menu in on your computer:

SELECT Explorer (XP)

OR Windows Explorer (Windows 7)


Select the Patriot drive E:\ (It may have a different drive letter) Notice the subdirectories on the Patriot drive. These subdirectories follow the structure used by the MN DNR on the LiDAR data FTP site. For this training and your work back at your site, it is recommended you use this structure to house and manage your data. LiDAR files are very large and a data organization that stays consistent with the source (the MN DNR) will make it easier to find, retrieve and transfer data. Select the Patriot E:\tools directory and then Select then FileZilla FTP Client directory Within the FileZilla FTP Client directory, run (double left click) upon

Enter lidar.dnr.state.mn.us in the Host box, Anonymous in the Username box and your email in the Password box leave the Port box empty, Press Quickconnect.


You are now connected to the MN DNR LiDAR data site. At the bottom of your screen, on the left are your local computer files, on your right are the remote site files. Notice the DNR file structure on the Remote site. It is the same as our training data on the Patriot E:\ USB drive. It is very time consuming to transfer the large LiDAR files from the DNR site via FTP. For these Training exercises we have “preloaded” the data to the Patriot E:\ USB drive. For these training exercises you DO NOT NEED TO TRANSFER any data from the DNR FTP site. At your work site you can use this process to connect and transfer data from the DNR FTP site. The free FileZilla Client is available at http://filezilla‐project.org/download.php Once you connect to the DNR site see a directory similar to the one below (left); note material is

updated frequently on DNR shared sites and your directory may be slightly different than the material in this exercise.

Examine the data on the DNR site. Notice that within the data directory there are subdirectories: see below.


Within the \data\county directory you will find LiDAR data for each MN County (see below)

Both raw data and processed data are available. Raw data are “point clouds,” or sets of x,y,z points, in a .las or .laz formats, two standards used by LiDAR data collectors. These data have been processed to produce elevation data, delivered as digital elevation models (DEMs). Navigate back up to the \data directory and select the \data\raw folder. (See below)

Then select county. Next select a county, Kandiyohi for example.


An example of the data for \data\raw\county\kandiyohi directory is shown below:

Each directory includes a map of data tiles, tile_index_map.pdf that shows the coverage for each raw data LiDAR file. You should use this index map to locate data for you work area.

The tile structure follows the USGS 1:24k topographical map grids. Data are organized by

County, USGS 1:24K grids, 1/16th grid subsections. This structure is shown on the

Tile_index_map.pdf. See example below:

Use the Tile Index to find your area. Note: the sub tiles are numbered 3526‐30‐36 for example


Within the

\data\raw\country\kandiyohi

directory you will also find ESRI

geodatabases (GDB) in the

geodatabase directory, and .laz

files in the laz directory for each

of the tiles.

LiDAR files with the .laz extension are compressed forms of standard LiDAR data files. Because LiDAR data files tend to be quite large, we recommend storing and transferring the compressed forms in most cases. We will explain the .laz extraction process later. Exit FileZilla FTP Client. Do not transfer anything for this exercise, the data is provided for you. Steps for setting up your data space

1. Create a working directory on the PATRIOT USB Drive (named something that makes sense

to you), and copy and unzip (uncompress) the DNR_structure.zip file from the \training

\LiDAR_Lab1 data folder to your working directory.

This will create the empty structure for the lab exercises. The exploded empty directory structure will appear as shown below, on in your subdirectory on the PATRIOT USB drive.


Working With Example Data….? From the \training\LiDAR_Exercise1 directory copy the files: 3526‐30‐36.laz to the (your name)\data\raw\county\kandiyohi\laz subdirectory. Next copy the \training\LiDA_Exercise1 3526‐30‐36.gdb to (your name)\data\raw\county\kandiyohi\geodatabase. Example of structure with files inside is shown to the right.

LiDAR Raw Data in stored within .laz/las

files.

If not already there, create a folder called \las within the

\DNR_structure\data\raw\county\kandiyohi folder.

Navigate to the\DNR_structure\data\raw\county\kandiyohi\laz folder and check to see if the

there is a file present called laszip.exe. This is the free utility created by Martin Isenburg which

compresses and uncompress .las/laz files.

Double left click on laszip.exe, this will

display a command line window similar to

the right figure:

In the command box 1st type *.laz, then

hit return

Then enter 3526‐30‐36.las, and then

press Enter.

The program should run for a minute to 10 minutes, uncompressing the .laz files into .las files.

It will then return with a cursor.


When laszip is complete, close the command box by selecting the RED X in the upper right

corner, or by typing the word exit at

the command line.

Now, use Windows Explorer to move

the file 3526‐30‐36.las to the \las

folder you created a few steps earlier.

You data and folders should appear as

shown in the panel to the right

Start ArcMap

Open the ArcToolbox

Select the 3D Analyst Tools From File

Point File Information

(Shown right)


As show to the right, add the

3526‐30‐36.las as the input.

Direct the output to the

\lasinfo folder. Name the

output shapefile 3526‐30‐

36.shp

And select Summarize by class

code.

Click on the OK button.

After the Point File Information

process has completed, open the

attribute table of the 3526‐30‐36

data layer in ArcMap. (Shown

Right)

This information file describes the contents of the .las file 3526‐30‐36. Review the fields in this summary file. LiDAR measurements have several important features. Each laser pulse is either absorbed or reflected. The reflection timing and intensity are collected for each sent signal. The LiDAR vendor then processes the return file into Classes. Each class is established by the return timing and intensity and given the following values:


CLASS as used by MN DNR ASPRS Standard

0 Unused Created, never classified

1 Processed but not unclassified Unclassified2 Bare Earth Ground Ground3 Unused Low Vegetation4 Vegetation (low, medium, high) Medium Vegetation 5 Unused High Vegetation 6 Buildings Building7 Noise (Low or High) Low Points (noise) 8 Model KeyPoints Model Key‐Points (mass

9 Water Water10 Ignored Ground Reserved for ASPRS 11 Unused Reserved for ASPRS 12 Unused Overlap Points13 Unused Reserved for ASPRS 14 Bridge Decks Reserved for ASPRS

15‐31 Unused Reserved for ASPRS * American Society for Photogrammetry and Remote Sensing

Within the summary file notice that there are total counts of the points included in each class.

Also included is the average spacing between these classified points and the highest and lowest

measured values (ground, building or tree height).

Repeat the 3D Analyst Tools From File Point File Information, use the \las\3526‐30‐36.las

as input and direct the output to the \lasinfo\3526‐30‐36_Total.shp and DO NOT check the

Summarize by Class code box. When the operation is complete examine this new summary

result table.

Open the 3526‐30‐36_Total table; you should get results similar to those shown below:


Note the Pt_Spacing of 0.902386, this measurement is in meters. So OVERALL (all classes), the

average point spacing of the LiDAR pulses/returns is 0.9022386 meters.

The point spacing from the sample data will be used in later labs.

With you own data you should check this value each time as there may be some variation

between LiDAR collection data sets.

Close ArcMap. There is no need to save your project (.mxd)

This is the end of Exercise 1.


Exercise 2: Loading LiDAR data into ArcMap


- Create a geodatabase(GDB)

- Load LAS file into multipoint

- Selectively Load LAS data into multipoint

- Change multipoint into singlepart/point

Data for this exercise are located in the LiDAR_Module2 subdirectory.

Videos for this exercise are located in the \Instructional_Videos\LiDAR subdirectory. (soon)

What You’ll Produce:

- Create a geodatabase(GDB) - multipoint file from a LAS file - sub‐setting a multipoint file for analysis - Multipoint to singlepoint file - Create field to display LiDAR measurement values - Populate the LiDAR measurement field

Open ArcMap and establish a path to the

\training\LiDAR_Module2 subdirectory.

Create a geodatabase (GDB) to store your data. Open Arc

Catalog and navigate to the \LiDAR_Module2 directory

\data\raw\kandiyohi\geodatabase and right click and select

NEW File

Geodatabas

e

When the file is created right click on the

New File Geodatabase and rename it to

3526‐30‐36raw.


Next right click on 3526‐30‐36raw, select NEW, then Select New Feature Dataset.

Name New Feature Dataset, Points and select Next. Import the coordinate system from the

LiDAR_Module2\3526‐30‐36.gdb

Select from DEM01. Select the

Vertical Coordinates, North

American, NAV 1988.

Select Next twice and then Finish.

These steps allow the use of the

default settings for the dataset.

Now we can start loading data.

Select ArcToolbox3D Analyst

ToolsFrom FileLAS to

Mulitpoint.

As shown below use 3536‐30‐36.las as the input

and direct the output to the Points dataset of the

3536‐30‐36raw geodatabase (GDB) you created

previously. Name the feature class

All_Class_Codes. Enter the average point spacing

you determined in Lab 1. In our example it is

0.902386. Do not change other parameter at this

time. The defaults select all returns for all class codes. Select OK

Import coordinates from DEM01


Examine the All_Class_Codes multipoint data

set which is now in your Table of Contents.

Right click on the All_Class_Codes layer

and select Open Attribute Table. Notice

the point file has a Shape* of “Multipoint

Z”, this means that 3500 individual points

are compressed into one record.

To work with the data we need to

uncompress this data but due to the size

of the data file we will first subset the

Multipoint Z file and then uncompress

the much smaller file.

For this Lab we will be focusing

upon a small peninsula within

Kasota Lake.

Select from ArcToolboxAnalysis

ToolsExtractClip.

Select All_Class_Codes as the

input and

StudyAreaBoundary_for_Clip as

the clip features.

Direct the output to the Points dataset naming the Output Feature Class

Study_Area_All_Class_Codes.

See example to above and to the right.

Select OK


Your output should appear as

shown to the right. The image

appears very dark because there

are many thousands of points being

displayed.

This smaller area will allow us to

avoid waiting for long processing

cycles.

Now we can uncompress the

MultiPart Z file. This process is

called Multipart to Single Part. Select this tool in the ArcToolBoxData Management

ToolsFeaturesMultipart to Singlepart; name the output

Study_Area_All_Codes_Single_Part. See below.

Examine the single part layer by

selecting the layer, right click and

Open Attribute Table. Notice

that at this point the single part

layer still looks similar but it is


not; note the increased record count. 315882,576 points

Now repeat the ArcToolbox3D AnalystConversionFrom FileLAS to Multipoint process

and this time extract only the Class 4 codes. This will be extracting only those LiDAR points

classified by the

DNR and LiDAR

vendor as

“Vegetation”.

See below.

Enter the Input

Class Code of 4

and press the +

button to

record your

selection

Accept all other

defaults

Select OK


Next repeat the previous Clip process to subset the Class_4_Codes layer to just the bounds of

the Study Area. Use Study_Area_Class_4_Codes for the output file name and

StudyAreaBoundary_for_Clip as the clip features. See page 3 for instructions.

After producing the Study_Area_Class_4_Codes layer repeat the MultiPart to Single part

process. Use Study_Area_Class_4_Codes_Single_Part as the output name. See page 4 for

instructions.

If not already on your ArcMap, add the following layers:

Study_Areas_All_Class_Codes_Single_Part, Study_Areas_Code_4_Single_Part and

StudyAreaBoundary_for_Clip. Remove of the All_Class_Codes and Study_Area_All_Class_Codes

data layers.

You ArcMap data view should look similar to the figure below.

Open the attribute table for Study_Areas_Code_4_Single_Part and use the drop down box

below the word Table to Add a Field.


Add a new field with the name Measure_Z with a type

of Float, as shown to the right.

Next calculate values into the new

Measure_Z field. Right click on the column

heading of Measure_Z and select Calculate

Geometry.

Answer Yes to the

warning dialog box.

Select Z Coordinate of Point in the

dropdown box for Property and OK.

This will allow the Measure_Z values for

each point to be shown. The units are

meters above the vertical reference

surface; most commonly mean sea

level. In the next Lab we will learn how

to subtract the bare ground elevation

from these values to calculate

vegetation heights.



Exercise 3: Determining Tree Heights


- Calculating LiDAR vegetation coverage

- Extracting elevation values from a DEM

- Calculating/Estimating Tree Heights

- Calculating/Estimating Canopy Density

Data for this exercise are located in the \Training\Module 3 subdirectory of the Patriot USB drive.

Videos for this exercise are located in the \Training\Instructional_Videos\subdirectory. (soon)

What you’ll produce:

- Calculated Tree Heights - Calculated Canopy Density - Explore production of metrics for other Forest measurement models - Layers to visualize vegetation

Start an ArcMap document and select the Blank Map template. Save/Name the ArcMap document (Project) as an .mdx to the Patriot USB drive, name it LiDAR_Module3. Place the document within your subdirectory on the Patriot USB drive.

Add the data Study_Areas_Class_4_Single_Part layer you created from Module 2; (please use the version provided within the Module3 subdirectory) Notice the Measure_Z values which were calculated in the previous exercise.


Select the Table Options, Add Field Create a new Floating Point field, called Elevation. Next add another Floating Point field, called Est_Height. Now add the DEM layer to your Table of Contents. The DEM in found in

Select the DEM01 Next we will extract the ground elevation at each of the 325,672 Class 4 vegetation points. Note: this approach preserves the detailed measurement at each LiDAR point. Later we will (as necessary) use this detail to derive raster layers.

To extract elevation use ArcToolbox Spatial Analyst ToolsExtractionExtract Values to Points Put the output in the Points Dataset with in 3536‐30‐36raw.gdb in \training\LiDAR_Module3\data\raw\county\kandiyohi\geodatabase


Next calculate the Vegetation Height by subtracting Measure_Z from RasterVal (which is the elevation at the LiDAR point. Use Spatial Analyst Tools Map Algebra Raster Calculator

As you can see above, the tree heights range from 3 meters to the low 20’s.

Class 4 Height displayed below, classified into 5 groups (units meters)


Derive a vegetation height raster using the cell MAXIMUM when creating a 4 x 4 grid ArcToolbox ‐ ConversionsTo RasterPoint to Raster

Examples of various options for cell size; this depends on land cover for the area, it is old

growth deciduous or emerging coniferous.

4m

cell

5m

cell

10m

cell

6m

cell


Example: Reclassified Tree Height raster 14 x 14 cell size

With this calculated Height we can now derive raster surfaces and introduce a small amount generalization. Our 1st raster will be to use count LiDAR Class 4 vegetation points within a 4 by 4 meter grid. For this we will use Point to Raster Tool Add the Study_Area_Class4 point layer to your ArcMap Table of Contents. ArcToolbox ‐ Conversion ToolsTo RasterPoint to Raster


Add the Bare Earth Points to ArcMap and clip them to the Study Area ArcToolbox ‐ Analysis ToolsExtract Clip Derive a raster by counting the Study Area Bare Earth Points in a 4 x 4 grid ArcToolbox ‐ ConversionsTo RasterPoint to Raster


Remove the Nulls from the

Vegetation Count layer (4 x 4)

ArcToolbox ‐ Spatial Analyst ToolsMap AlgebraRaster Calculator Select OK Remove the Nulls from the Bare Earth Count layer (4 x 4) ArcToolbox ‐ Spatial Analyst ToolsMap AlgebraRaster Calculator Select OK

Add the Bare Earth raster and the Vegetation Count Raster (4 x 4) ArcToolbox ‐ Spatial Analyst ToolsMap AlgebraRaster Calculator Select OK


Float conversion of one layer to have a Float final raster. ArcToolbox ‐ Spatial Analyst ToolsMathFloat Divide the Vegetation by the Total points to determine Canopy Density ArcToolbox ‐ Spatial Analyst ToolsMap AlgebraRaster Calculator


Study Area Vegetation Density (vegetation over total of everything )


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