Exercise 6: Assessing Landscape Metrics in Fragstats



Exercise 6: Assessing Landscape Metrics in Fragstats

Learn about landscape metrics

Learn how to conduct basic analysis in Fragstats

1. For this exercise you will need to install Fragstats, a free software available for download from the web, from home or office, go to the website:



2. Click on FRAGSTATS Downloads (on the left navigation bar) and scroll down to FragStats4.2.zip () save this file in c:\temp.

3. Extract the contents of this folder into c:\temp

4. Double click on Fragstats.exe to install the program.

5. You can save the program on the C drive default (C:\Program Files\Fragstats 4)

When done you should be able to find Fragstats 4.2 from the Start>Programs menu

6. The data files for this exercise are stored in exc6.zip on the website

In ArcCatalog you should see the following layers:

• L_Fp99.dbf [Pierce county Fragstats output for 1999 landscape metrics]

• Landcover_classes.layer [A layer file for symbology of the land cover grids]

• New_extent.shp [The extent of analysis we will be doing]

• P_Fp99.dbf [Pierce county Fragstats output for 1999 patch metrics]

• Pie99rcid8 [Pierce county 1999 Fragstats output for non-urban patches]

• Pie_91_lc10 [Pierce county 1991 land cover data, raster format]

• Pie_99_lc10 [Pierce county 1999 land cover data, raster format]

Definitions of landscape, patch and landscape level analysis are included in an attached document “definitions” under exercise 6.

The following are a few metrics which are calculated in this exercise, there are many more. The help menu in Fragstats has a good summary of the major landscape metrics, how they are calculated and what they are helpful for. The following details are pulled directly from the help pages:

Number of Patches

[pic]

Patch Area

[pic]

Aggregation Index

[pic]

Largest Patch Index

[pic]

Shape Index

[pic]

Importing layers to correct the symbology

1. Open ArcMap and add Pie_91_lc10, Pie_99_lc10 and new_extent

2. Save the file as exc6.mxd in your personal space.

3. Two of these data sets are rasters. Each of these rasters has values from 1 to 11, although it is not clear what these numbers represent.

4. Double click on Pie_91_lc10 and select the Symbology tab.

5. Click on Import… [pic] (in the upper right hand corner of the popup window) and navigate to the location where you saved all the data for this exercise. ArcMap is looking for a layer file. These files are useful for storing legend information such as colors and fills, and labels. Select landcover_classes.lyr and press add. Notice how the colors changed and the labels are filled with text such as High urban and Medium urban.

6. Press OK.

7. Repeat the above steps for Pie_99_lc10

8. Create a jpeg of the 1999 Pierce county landcover map with the following specifications:

• Page size with a landscape orientation

• Scale of 1 m = 500 km (of entire map)

• Scale, legend, north arrow, and title (24 pt font) clearly and eloquently included.

• Save the jpeg, at 150dpi, clipped to graphics extent, into your personal space for later insertion.

Reclassifying Landcover Images

You are now ready to reclassify the 1991 landcover as urban and not urban. You will be creating a Boolean value of 0 or 1 depending on whether the land cover classes represent urban or non-urban covers. First you will set the mask and output for the data so that we create a data set for only a small portion of Pierce County, this will save us some room.

1. Make sure that the Spatial Analyst extension is turned on. To turn on the extension, go to Customize > Extensions and check the Spatial Analyst check box. Click close.

2. Go to Geoprocessing > Environments and set the following information:

• Workspace > Current Workspace> browse to your personal space (folder)

• Processing Extent > Extent > Same as layer new_extent

• Raster Analysis > Cell Size> Same as Pie_91_lc10

• Raster Analysis > Mask > new_extent

• Click OK

3. Now search for Reclassify (a spatial analyst tool). This can also be found here: ArcToolbox > Spatial Analyst Tools> Reclass > Reclassify

4. Make sure the input raster is Pie_91_lc10

• Reclass Field is Value

• Set the old and new values according to the chart below:

• Notice how cover such as urban and cleared is classified as 0, while non-urban covers are classified as 1.

• Set the output raster as Pie91_rc in your personal space.

5. Press Ok.

Notice how the new raster only has two colors, one for 0(urban) and one for 1 (non-urban).

We will now use this reclassified image to measure a few patch and landscape metrics for Pierce County in 1991. Later we will compare these values with calculated values for 1999.

6. Now we need to get our raster ready for Fragstats:

One more step is needed before we can run the most recent version of Fragstats. Fragstats 4.2 can’t use ArcGIS 10.2’s raster data… so we need to use another data format!)

Find the Raster to Other Format tool. Make sure the input raster is pie91_rc. Create a new folder called “Raster” in your Exercise 6 personal space and make that your Output Workspace.

Choose “TIFF” for the Raster Format.

Example::[pic]

Now hit OK. This will take a minute.

You now have a layer you can add to Fragstats.

7. Save the ArcMap project, close ArcMap.

Create a Class Properties file

1. Open up notepad (Start, All Programs, Accessories, Notepad).

2. You will now create a Class properties file. This is used by Fragstats to figure out which category to do the analysis on (patches of urban or patches of non-urban, for example). Type in the following information (exactly as it appears below):

ID, Name, Enabled, IsBackground

0, urban, false, true

1, noturban, true, false

You are creating a comma delineated file which has the following information:

• new_class ID [ as you just reclassified the grid],

• class_type [urban or not-urban, word descriptions for what each class represents],

• true for enabled false for disabled [analysis will be conducted on this cell value], and lastly is

• background [useful for looking at the edge of the grid, so that it knows not to count these values]. You can visit the help files to learn more – page 47, here: .

Q1. Based on this information, which class are we going to calculate the patch information for?

3. Save this file as type “All files” and named: pierce91_99.fcd. The new file name is fcd, which is a file type which Fragstats recognizes.

Note: make sure before you exit notepad that everything is correct. If you try to open the file again in notepad to make further edits, Fragstats will stop recognizing the file.

Running Fragstats

1. Launch Fragstats with a single click.

2. Click on New (File): [pic] [pic]

3. In the Input layers tab, set the following:

1. Click Add layer…

a. TIFF as the Data Type selection

b. Then click on the “…” button to the right of the Dataset Name: entry field. Here you will navigate to the location of the new reclassified image you just created (Raster/pie91_rc).

c. Leave the background value as 999.

d. Hit OK.

e. You may see a message “warning: units not specified, meters assumed” in your activity log. Fortunately the units are meters (you can check looking at the properties of the layer in ArcCatalog).

2. Now load the Class descriptors file (the fcd file we just created in notepad). This is located under “Common Tables --> Class descriptors”

4. Next we will set the Analysis parameters (click the tab to the right of the input layers tab).

a. Select the neighbor rule as 8 cell.

b. Click to automatically save results. Specify where by navigating to your working folder. Type in a new (subfolder) name within your folder to save your Fragstats results (e.g. Fragstats).

c. Select No sampling. Check patch metrics, landscape metrics and generate patch ID file.

Now we will set the Patch and Landscape Metrics (in the panel on the right of our dialogue box).

First, click on the red Patch Metrics button [pic]. Here select Shape Index (under Shape tab) and specify Landscape Level Deviations, Standard Deviation.

[pic]

1. Then under the Area-Edge tab, select patch area, again specify only Landscape Level Deviations (Standard Deviation).

[pic]

2. Now select the blue Landscape Metrics button [pic]

• Within the Area-Edge tab, choose Largest Patch Index.

[pic]

• Within the Aggregation tab, select Number of Patches and Aggregation Index.

[pic]

Now you are ready to run fragstats.

1. Save your file as Pierce.fca.

2. Press the green Run arrow.

• Click Proceed.

If all was completed successfully, the lower right activity log should be populated with something along the lines of the image below (13:36:35 and later lines. If you had an error, you could see something like the messages received earlier ~13:24:59-13:25:09).

[pic]

Navigate to your files, you should see the following outputs (there are more, but these are the three we will be using today):

• Pie91_rc_id8 (this will be in your Raster folder)

• Fpie91rc.patch (these will be in your Fragstats folder)

• Fpie91rc.land

3. In Windows Explorer copy the file Fpie_91rc.patch, paste the copy in the same folder and rename to: patch_Fpie_91rc.txt

• you will get a warning message about changing the file type. Click yes, since you want to make sure that the file extension is changed to txt. A txt file can be read by ArcGIS.

[pic]

• Do the same for Fpie_91rc.land except rename as land_Fpie_91rc.txt

Joining the table to the patch output grid

1. Go back to ArcMAP, add the new TIFF pie_91rc_id8 that is located in your Raster folder.

a. Say yes to create display pyramids. (it is ok for now that spatial information is missing)

b. ArcGIS can’t join tables to the TIFF. So, let’s convert it back into a GRID file.

i. Find the “Raster to Other Format” tool again. Make sure the input raster is pie91_rc_id8.tif. Make your output workspace the new folder “Raster” in your Exercise 6 personal space that we created before.

ii. Choose “GRID” for the Raster Format.

iii. Hit OK, this will take a little while.

iv. When finished, add the new GRID to your map (it will be in the Raster folder, called “pie91_rc_id8” with no file extension (.tif has a file extension).

2. Add the table patch_Fpie_91rc.txt; this has the information about the patch metrics.

3. Join this table to Pie91_rcid8. Join the Value to the PID (that’s the Patch Identification).

a. You can let ArcMap create an index if it asks.

4. Open up the attribute table for pie_rcid8 and look at the different columns:

• Rowid is just an automatic identification given to each Patch.

• Value is the specific patch ID given to each patch by fragstats.

• Count is the number of cells in each patch,

• F91_OID, F91.ID are automatic numbers given to each object in the table F91, PID is the patch id,

• type is the written description you entered for each patch type in the class properties field,

• area is the size of the patch in hectares, and

• area_LSD is the standard deviation of the size of the patch

• shape_1 is the shape index

• Shape_LSD is the standard deviation of the shape index.

Each cell is 30 x 30 meters. The area of the patches is given in hectares.

Q2. Can you calculate the relationship between ‘count’ and area? (HINT: you can add a field to the raster table and use the field calculator or you can calculate the values in excel).

Viewing Patch Metrics

When you join a table to a layer, this connection is not permanent. You can work with the layer and joined table, but if you open the layer again, it will not be joined to the data table. We will make this join permanent in order to change the symbology.

1. Optional: To permanently join your table, export (Data > Export Data…) the layer (with the joined table) to create a new layer. Call the new layer patch91. Make sure the format is GRID.

2. We will now change the symbology of pie91_rc_id8 such that you can see which patches are larger and which are smaller. Double click on the grid, and click on the symbology tab. Select ‘Classified’ and change the field value to Area (it should be the first option). Choose a blue gradient with smaller values being a lighter blue and larger values being a darker blue.

[pic]

a. Manually change the color of the smallest group to yellow and the largest to purple by double clicking on the color (or right click, properties for selected colors).

b. Use four classess; with natural breaks (Jenks).

3. Make a new map with this image, add a descriptive title, north arrow, legend and scale bar.

4. Q3. Create a jpeg of this image.

5. Q4. Reopen the attribute table, which patch (use PID value) has the most complex shape?

Viewing the landscape metrics

1. Add the table land_Fpie_91rc.txt

2. In excel, make a table like the one below:

3. Open the attribute table and write down the following values in the 1991 column. You may need to adjust the column width to make sure you see the whole number.

We have processed the data for you through fragstats following the very same steps, such that the 1999 landcover has been similarly reclassified, the same patch and landscape metrics were calculated in fragstats and the output files were exported as dbfs.

4. Add the 1999 file (l_fp99.dbf) and type in the values in your excel chart.

5. Make an excel graph that shows the change in the number of patches between 1991 and 1999. Make sure that the graph is self-explanatory (it should have a title, x- and y- axis labels, and the y-axis scale should begin at zero).

6. Q5 What happened to the Aggregation Index? What does this mean, both spatially and ecologically speaking? Remember, information about the Aggregation Index can be found at the top of this exercise or online.

Congratulations, you’re done with Exercise 6! (Phew)

In a new document, insert the following:

1. the answers to the highlighted questions above

2. the 1999 landcover jpeg

3. the 1991 non-urban patches jpeg

4. the landscape metrics table

5. the number of non-urban patches graph

Remember to type your name on the top and or submit to CollectIt with yourname_exc6.

Due on January 28, 2014 at midnight.

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Objectives

Setup

Background and Definitions

Directions

Deliverable

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