Instructor: Brian Klinkenberg
Office: Room 209
Office Hours: Tues 12:30-1:30
Lab Help: Jose Aparicio
Office: Room 240D
Instructor: Brian Klinkenberg
Office: Room 209
Office Hours: Tues 12:30-1:30
Lab Help: Jose Aparicio
Office: Room 240D
In this lab you will explore the impact that spatial resolution has on the results of spatial pattern analyses. We will do this by considering how the landscape around Winnipeg, Manitoba changed from 1966 to 1976, using Fragstats to calculate some landscape metrics (Google Map).
You must first download the Canada Land Use Monitoring Program (CLUMP) data for Winnipeg from the Geogratis web site for (i.e., winma66u.zip and winma76u.zip). Unzip the files, and store the data in C:\data\Lab2\. (Reminder: Lab 1 contains the full details on how to find the data.) A description of the land uses documented in CLUMP (e.g., what is included in 'outdoor recreation' lands) is available here. Don't forget: ArcMap Etiquette
Start ArcMap. Within ArcToolbox, import the interchange file (winma##u.e00) (Conversion Tools / To Coverage / Import from E00). In the Import window, save the file in C:\data\G479Lab2\ as Win## [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\.
In order to explore what impact spatial resolution has on the results, when converting the vector files to raster files produce one set of rasters with a resolution of 100m and, for 1976, another raster with a resolution of 500m (i.e., you will have three raster files in the end). (ArcToolbox / Conversion Tools / To Raster / Polygon to Raster) (Don't forget to specify "USE" as the Value field in your conversion.) Currently Fragstats will not read ArcMap raster / grid files. Therefore, you will have to export each raster to a GeoTIFF file (as described in Lab 1) before doing your Fragstats analyses.
In order to assist you in your interpretation of the Fragstat 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, 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).
Note that the 1976 land use map has additional classes not present in 1966 (classes L and G), and that both maps have blank classes (i.e., there is no 'use' associated with some cells). You should provide a label for those blank cells in the fcd file--given them a name of 'unknown'.
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). Then, using the information contained in the raster attribute file (Open the Attribute Table in ArcMap) you can create the class properties file. Here is an example fcd (from Saskatoon) that you can use as a template (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.
To add the fcd file to your Fragstats analysis, you need to point to the file in the Common Tables section.
Start Fragstats, and create a New file:
Accept the program defaults for all of the other values.
For the purposes of this lab you will only be examining a few selected metrics for each of the three grid files: Class metrics (Area or Aggregation: Total Area, Percentage of Landscape, Number of Patches, Total Edge) and Landscape metrics (Area or Aggregation: Number of Patches, Patch Density; Diversity: Shannon's Diversity Index, Shannon's Evenness Index). Select the Class and Landscape metrics from their respective windows.
IMPORTANT NOTE: You need to select two additional Class metrics and two additional Landscape metrics and, in your written report, you must describe those four additional statistics (why you choose them and what the statistical values showed). If you read over the Fragstats help file (PDF) and, in particular, go through the documentation that provides an overview of each group of metric (e.g., Area and Edge, Aggregation), you should be able to identify some relevant metrics to employ. (If you start Fragstats, and then click on Help (Help Contents), and then go to the Contents / Fragstats Metrics / Overview, and read over the group descriptions, this should help.)
Set the Class and Landscape metrics accordingly. Run Fragstats.
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 Winnipeg has changed over time, and how changes in spatial resolution affect the results.
You should ignore any results associated with those classes that have fewer than 25 cells, and the results associated with the one class that has no CLUMP code associated with it.
You also need to create a transition matrix that shows how the land uses in 1966 changed over time. 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 rasters(that is, the attribute table shows you what a cell was classified as in1966 and what it was classified 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). 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.
IMPORTANT NOTE: Do not store the results of the combine operation in a Geodatabase. If you do the attribtue table will not contain the two 'extra' columns that contain the links to the original raster files (the join fields).
Before exporting the table, however, we should add the actual USE codes to the combined table. 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 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 raster. You should now export the attribute table.
Import the 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 USE columns], 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.
Once the pivot table is created, we need to convert the raw numbers into percentages, and provide proper row/column labels (e.g., changing the use codes (e.g., 8) to meaning names (e.g., Unmapped areas)). You should also delete the blank ('unknown') row / column. To make the calculation of the %'ages easier, you could copy the entire pivot table and then paste 'values' to a new worksheet. You should include this final (%) table, and a discussion of what it shows, in your report. (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--both as a result of changing the spatial resolution (only one paragraph on this), and as a result of the change in the land use around the area of Winnipeg between 1966 and 1976 (this discussion should form the bulk of your report). In your report you must not only present the results but also explain what each metric means.
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 Winnipeg (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 differences, a map that illustrates the impact that a change in scale has on the data. Ensure that you use a consistent colour scheme for all of your land use maps (i.e., a land use on all three 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]), while the other map should show the effect that changing scale had on the data (therefore you must use the raster maps).(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--Jan 30th, at the beginning of the lab. You should include tables showing the Fragstat statistics for the three grids (combining the three landscape metric outputs into one table), the transition matrix table, and several graphs highlighting some of the interesting statistics.
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)