Instructor: Brian Klinkenberg
Office: Room 209
Office Hours: Tues 12:30-1:30
Instructor: Brian Klinkenberg
Office: Room 209
Office Hours: Tues 12:30-1:30
You must first download the Canada Land Use Monitoring Program (CLUMP) data for Edmonton from the Geogratis web site for (i.e., EDMAP66u.zip and EDMAB76u.zip). Unzip the files, and store the data in C:\data\Lab2\.
Step 1: To download the data from the Geogratis web site:
Open the Readme file in order to identify the datum and coordinate system associated with the data, and scroll down until you find the legend information. It would be helpful if you cut / pasted the legend text (Valid CLUMP land Use Codes) into a new Notepad txt file (e.g., save it as legend.txt).
Although we won't be exploring this aspect of the data in this class, note that the land use classification used in the first set of CLUMP maps (from 1966 through to 1976) was changed for the later set of maps (from 1981 to 1986). This change in the attribute resolution would affect any temporal analysis we could make of the data (an example of how changes in the classification scheme changes our view of a landscape is presented below--Figure 5.5 from the text Landscape Ecology).
Some of the important concepts you should become familiar with before using the program--some landscape ecology terms--can be found here.
Step 2: Importing and organizging the data:
Start ArcMap. Within ArcToolbox, import the interchange file (EDMAB##u.e00) (Conversion Tools / To Coverage / Import from E00). In the Import window, save the file in C:\data\Lab2\ as ED## [where ## is the year of your CLUMP file] and leave the File type as Basic types. It may appear that the import process fails, but if you click on the Add file button [+] you should be able to find the coverage file in C:\data\Lab2\. (When displaying the vector [or raster] files, you should import the legend scheme from one map to the other in order to be able to quickly visually compare the two maps.)
Convert the vector files to raster files in order produce two rasters (one for 1966, one for 1976) with a resolution of 100m. (ArcToolbox / Conversion Tools / To Raster / Polygon to Raster) (Specify "USE" as the Value field in your conversion and set the output file format to GRID.) However, as Fragstats cannot read ArcMap 10.x raster / grid files you will also have to create a GeoTIFF file by exporting the data after you perform the conversion. To do this, right-mouse click on each EDXX100 file, select Data -> Export Data. Ensure that the output location is C:\data\lab2, set the output format to TIFF, and name the file EDxx1000
Step 3: Providing metadata for Fragstats:
In order to assist you in your interpretation of the Fragstats results, it is useful to explicitly state what CLUMP land uses are associated with each raster class. In order for Fragstats to know what the classes actually refer to (e.g., that class 1 represents Cropland), you need to create a class descriptors file for each year. This is a text file (with the extension fcd) that lists ID, Name, Enabled, IsBackground, where ID refers to the grid value associated with a particular land use, Name refers to the associated CLUMP land use, Enabled is a binary variable [true or false] that indicates whether that class should be included in the analyses [true] or not [false], and IsBackground is another binary variable [t or f] that tells Fragstats to either include that class in the analyses [false] or to treat that class as a background class [true]. There should not be any blank lines in the fcd file (if so, the program will not run).
The easiest way to create the class properties file is to open the README.TXT file that comes with the CLUMP data and to cut / paste the CLUMP land use codes into a blank text file (note that you will have to remove any commas "," associated with the land use names; call the text file that contains just the list of the legend codes legends.txt). Then, using the information contained in the raster attribute file (Open the Attribute Table in ArcMap; you need to replace the CLUMP codes in the README file with the ID's from the raster attribute table) you can create the class properties file. Here is an example of the steps / files you should use in creating your FCD file (note that the order of the entries doesn't matter, and that unmapped areas should be considered as the background class). Read over the Fragstats help file on creating the class descriptors file for further details (open help and search for fcd). It is important that the syntax rules for the class properties file are followed (that is, each field is followed by a comma, and there are no commas elsewhere in the file), or you will run into problems. Once you have created the fcd file, Save As the file by explicitly setting the extension to .fcd. (Here is a template fcd file you can start with.)
Note: When producing your final maps you can import the land use codes (extracted from the readme.txt file) into ArcMap, and then join that table to your vector or raster layers in order to have the land use names displayed in the legends (I describe this process below).
To add the fcd file to your Fragstats analysis, you need to point to the file in the Common Tables section, as described below (noting that there should be a unique fcd file for each year).
Step 4: Start Fragstats, and create a New file:
Accept the program defaults for all of the other values. Note that you have to run Fragstats two times, once for each raster file, and that the FCD file is specific to each raster file.
For the purposes of this lab you will only be examining
a few selected metrics for each of the three grid files:
Before producing the results, make sure that you can the input file selected in the layers list under File Management..
Using Excel you can take the output files from Fragstats (open the *.class and *.land files as comma-delimited text files) and produce a number of plots. You must label the land uses using the appropriate CLUMP descriptors. You can then compare the results of your analyses and see how the landscape around Edmonton has changed over time.
You should ignore any results associated with those classes that have fewer than 50 cells.
You will now create a transition matrix that shows how the land uses in 1966 changed over time (i.e., what uses did they become in 1976?). In order to do this we can use the 'combine' tool [ArcToolbox / Spatial Analyst Tools / Local / Combine]. The result of this operation will be a raster that contains the matches between the two input GRID rasters (that is, the attribute table shows you what a cell was classified as in1966 and what it was classified as in 1976) (an illustration of what combine does--taken from the ESRI Help file for Combine--where InRas1 and InRas2 would correspond to your two land use rasters). Name the output combine.
IMPORTANT NOTE: Do not store the results of the combine operation in a Geodatabase. If you do the attribute table will not contain the two 'extra' columns that contain the links to the original raster files (the join fields).
Before completing the next step and exporting the combine table, however, we should add (JOIN) the actual USE codes (and then the actual land use names) to the results. Select the combined raster, and select Joins and Relates -- Join. You will be joining a table--select the field associated with the 1966 raster as the join field (the field name should match the name of your 1966 100 m resolution GRID raster). Select the attribute table from the 1966 raster, and select VALUE as the join field. Click on Okay. Look at the attribute table of the combined raster to ensure that the join worked properly. Repeat the join process, but this time select the 1976 column in the combine attribute table and, in the 1976 raster, Value as the join field. Check to ensure that the second join worked properly.
As I demonstrated in the lab, you can perform a second set of joins which will enable you to bring in the actual land use names to the combine attribute table. The simplest way to achieve this is to:
In order to make a transition matrix you need to export the attribute table (open the attribute table of our combined result and Select Export under Table Options) as a DBF, and then open that DBF file in Excel. Check to ensure that the dbf is being exported to C:\Data\Lab2.
Import the dbf file into Excel (you'll need to set the file type to *.* in order to select the DBF file). You should tidy up the file a bit by removing the extraneous columns. To create the transition matrix you need to create a Pivot Table (Microsoft's description). Highlight the three columns you'll need to summarize [Count, showing the number of cells associated with each pair of land use codes, and the two columns that contain the land use names], and then click on Insert -- Pivot Table. For the column labels select the 1976 raster values, for the row labels select the 1966 raster values, and select Count as the Σ (Sum of) field. The default is just to show a series of 1's in the table. You need to change the default to show the sum (which would represent the number of cells that were in land use X in 1966 that become land use X (or Y or Z....) in 1976. In the Pivot table, click on the down-arrow in theΣ (Sum of) field and select Value Field Settings.... and select Sum as the operation.
You table should look like this, if the four sets off joins worked out correctly and you created the pivot table correctly::
Once the pivot table is created, we need to convert the raw numbers into percentages. You should also delete the rows/columns associated with those land uses with fewer than 50 cells.
To make the calculation of the %'ages easier, you should copy the entire pivot table and then paste 'values' to a new worksheet. I will show you in class how to easily calculate percentages for each of the cells. You should include this final (%) table, and a discussion of what it shows, in your report. (A question to ponder: What percentage values to calculate? That is, you could calculate the percentages based on the row totals [showing how a land use in 1966 changed over time], based on the column totals [showing where a land use in 1976 came from], or based on the sum total. We will talk about this in class.)
A 3-4 page report (excluding the tables and figures) on the results of your analyses. Use tables / graphs to demonstrate the changes that you observed in the landscape metrics as a result of the change in the land use around the area of Edmonton between 1966 and 1976. In your report you must not only present the results but also briefly explain what each metric means (the explanations could be included in an Appendix).
The report should be written from the perspective of a consultant hired by the city council to examine the changes in the land use around the area of Edmonton, AB (therefore, include a cover page [report title, your name, the date] and an Executive Summary [a short paragraph] as the second page. Your report should include maps showing the land uses in the two years and, using blow-ups of an area in order to highlight the changes . Ensure that you use a consistent colour scheme for all of your land use maps (i.e., a land use on the two maps should have the same colour). Two of the maps should show the entire study area, one for each time period (can be produced using the vector maps [import the legend to ensure that they correspond]), (Here is an explanation of how to create a map with two zoomed-in raster maps as well as an inset map highlighting where the zoomed-in maps are located relative to the entire area.)
The results of this lab will be due in two weeks--Friday, Jan 27th, at the beginning of the class. You should include tables showing the Fragstats statistics for the two grids (combining the landscape metric outputs into one table), the transition matrix table, and several graphs highlighting some of the interesting statistics that you discuss in your report..
Ritters et al. (PDF) explored the relations among 55 of the landscape metrics provided by FRAGSTAT and found that there are very high correlations among many of them ( in fact, those 55 metrics statistically only represented 6 different factors). [Riitters et al., 1995. A factor analysis of landscape pattern and structure metrics. Landscape Ecology 10:23-39.] [freely available from this web site]
Two other papers of interest:
Hansen, J. A. G. 1984. Canadian small settlements and the uptake of agricultural land, 1966–1976. Social Indicators Research 15(1): 61-84. (Link)