EXERCISE 12 – Cost Surface Analysis

I. Cost Surface Analysis
Today we're going to take a quick look at a modeling technique known as cost surface analysis. It's often used to model the potential movement of some entity (e.g., animal or pollutants) through an area. The cost surface describes how easy or difficult it is for our entity to travel through each cell (yes, it's raster based) in a study area. For example, if we're modeling salamander movement, a four lane highway would have a rather high cost of movement since it's a very difficult feature for a salamander to cross, while a forested wetland would have a low cost of movement.

Let's say we have an area with two populations of salamanders in the northern Barnegat Bay watershed. A local land conservation group is interested in preserving land that will help these two populations of salamanders remain connected to promote healthy populations and genetic diversity. We need to find out the areas that make the most sense for them to preserve.

First we need to generate a cost surface. A cost surface can be derived from any combination of layers, such as wetlands, major highways and land use. To keep things simple we're using a land use/land cover layer that sufficiently delineates high and low travel cost areas from a salamander's point of view.Open ArcMap andadd \\ad-rsc\data\teach\intgeo\ClassWork\costpath\lu06 and open the attribute table. Notice there is a cost field already here. The higher the value the more difficult a salamander will find the area to cross (the value must always be higher than 0). We're going to use this cost data to determine the least cost path (i.e. the easiest path) that connects the two salamander populations.

In order to do this, we need a raster layer that has the cost data in its value field. We can create this by using the Spatial Analyst | Reclass | Lookup tool on the lu06 layer, with the cost field as the lookup field. Save the output to your personal folder, and call it something you’ll remember.

Once we have the cost raster, we need to designate a source population of salamanders that we can calculate a cost distance surface to. The source data does not need to be in raster format, and it has already been created for you (vernsource.shp). The cost distance surface adds up the cost of moving from the source to every other cell in the cost raster.

Create the cost distance surface via the Cost Distance tool (located in Spatial Analyst | Distance). The input source will be …\ClassWork\costpath\vernsource and the cost raster is the cost surface we just created from the land cover data. You'll want to create an output backlink raster (we'll need it later), which identifies the direction of easiest movement from the cell to the source.

The cost distance raster shows the minimum cost of movement from the source to each cell. Now that we've created it, we can use it and the backlink raster to determine the least cost path to our destination population of salamanders. Open the Cost Path tool (Spatial Analyst | Distance). The destination data layer is …\ClassWork\costpath\verndest, which is just a point showing the location of the other salamander population. The cost distance and backlink rasters are those we just created, and we can accept the defaults for the rest.

The output raster shows the path of ‘least cost’ that connects the populations of salamanders. This shows where preservation activities should be concentrated in order to ensure connectivity between the populations.

Assignment: This assignment is optional, for extra credit. If you haven't turned in other assignments previously this semester, you might want to consider completing this lab.

Make a copy of the lu06 layer in your personal folder. Edit the values in the cost field to values of your own choosing (higher is more difficult, and values must be greater than zero) and turn this into a cost surface raster. Then create the least cost path as above and make a nice map using the land use data and final path. You'll have to convert the cost path raster to a line for it to show up well in your map (you can do this via Raster to Features (use type polyline) under Spatial Analyst | Convert).

Hand it in by Monday, May 4th.

A Few Other Tips & Tools for the Last Lab of the Semester

II. Select by location

One potentially useful tool you should take a look at is the Select by Location tool, found under the Selection menu. This tool allows us to select features of one layer using the location of features in another layer. We could, for example, select land cover polygons that intersect roads or a set of sample points. We aren't limited to using intersections, either. There is a relatively comprehensive list of geographic relationships we can use, including within a distance of. We can also buffer the features in the layer we're using to select the other features.

III. Labeling and Legends

By now you should be advanced enough in your map making skills to find the labels and legends defaults in ArcGIS a bit limiting. What can you do about them?

Well, the engine that ArcGIS uses to place labels on maps is powerful, with many options that can be adjusted under the Label properties for any layer. I'm not going to talk about them because I don't think they're very useful for most of the labeling issues you'll encounter in class. Instead I'll tell you the nuclear option for getting the labels to look the way you want them. If you have a labeled layer and you're just not happy with the positioning, you can right-click on the layer in the TOC and Convert the Labels to Annotation. This turns every label into its own free-floating text box that you can then manipulate to your heart's content. Why is this  the nuclear option? Because, you delink the labels from the label properties for the layer, meaning the label properties of the layer will no longer change the appearance of the layer. You can select all the labels and alter their appearance by using the Select All Elements tool under the Edit menu.