Objective: The objective of this lab is to use some classic raster manipulations to begin 'thinking in raster'. You'll use some of ArcMap's raster modeling capabilites. These are provided via the spatial analyst extension. In this lab you will:
The data are on \\Odin\Data\ You should already have the drive "mapped".
To Import a DEM: select the Red Toolbox and then do ArcTools -> Conversion Tools -> to Raster -> DEM to raster. In the dialog, set the input to be USGS DEM from the path \\Odin\Data\10mDEMs\Oahu10\honolulu.dem and set the output to be U:\honolulu. The output defaults to "float" and the vertical exageration to "1", and those work ok. Run it. It might take a minute and a half. In ArcMap, you can add that to your map, perhaps after associating the UTM Zone 4N coordinate system with it. 9.2 seems to do this automatically.
Derive Contour, Slope, Aspect, and Hill-Shaded (shaded relief) rasters from the DEM data. These are available in the Spatial Analyst -> Surface Analysis -> Contour, Slope, Aspect, Hill-Shade (skip viewshed and cut/fill for now). Examine the maps.
What does each of these renderings highlight in the data? What contour interval seems reasonable? Why? Which rendering gives you the best overall impression of the terrain configuration? Why? What doesn't it show well?
A lot of raster analysis can be done using a couple of simple operations. One is 'reclass' the other is to do cell by cell arithmatic operations, such as adding, subtracting, multiplying and dividing the values in corresponding cells. Judicious combination of the 'reclass' and such calculations form the back-bone of raster analysis.
The operations are avaialable as:
Spatial Analyst -> Reclassify... (set input, set value reasignments)
Spatial Analyst -> Raster Calculator... (set what to calculate)
Suppose that you want to find a place on the Honolulu Quadrangle to build a new school. The site has to have moderate slope, an east-facing aspect, and an elevation that would avoid tsunamis and sea-level rise but not be really high for students to climb to. (A more realistic site analysis might also include information on the locations of students, existing schools, transportation infrastructure etc., but we needn't worry about those things today.)
You might approach this task by reclassing each of the elevation, slope, and aspect maps into areas that are suitable and those that are unsuitable according to some criteria. Then overlaying these three layers should indicate the areas where all three are suitable.
One strategy is to create three binary rasters of good vs not-good solutions (one reclassifying the aspect map so that East-facing is '1' and not East-facing is '0'; one reclassifying the slope map with Moderate Slope as '1' and Immoderate Slope '0'), and one from reclassifying the elevation map so that the suitable range is '1' and the unsuitable elevations are '0'. Obviously, this requires that you set bounds on what is suitable and unsuitable based on interpretations of the criteria.
You could then combine these rasters by multiplication (in the raster calculator) to get a map where '1' indicates places that are suitable on all three criteria, and '0' indicates unsuitable sites. Or you could combine then by addition and get a map that has '3', '2', '1' or '0' in each cell depending on how many of the criteria were met in each raster cell.
An alternative strategy is to reclass the original data into rankings of suitability of each cell on each factor. These rankings can then be combined by adding, multiplying, averaging, etc. to produce a map of relative suitability. Careful attention to your coding scheme, the operations on it and the interpretation of the results are in order. The operations and results can be contrived to reflect weights or importance of the various layers and the rankings within them.
Try experimenting with these approaches to find suitable school sites.
Do you get very different suitable areas when you try different schemes in your reclassifications and combinations? What two places (by coordinates) would you suggest as suitable alternative school sites?
One of the important uses of DEM data has been to support hydrological studies. ArcGIS has a considerable suite of capabilities for this. In ArcGIS Desktop Help, search for "An overview of Hydrology tools" and read about "Basin", "Fill", "Flow Accumulation", "Flow Direction", "Sink", "Stream Order", "Watershed", etc.
For example, to calculate the set of drainage basins on your DEM data, use the raster calculator in spatial analyst to invoke the basin function. (You can use this function in scripts and other dialogs as well, but for now we'll just invoke it this way.).
Assuming your DEM elevation data is called 'mydem' and you want to produce a basin map called 'mybasins', click spatial analyst : raster calculator and then type this command into the panel:
To better display the basins:
ArcMap's Spatial Analyst has several ways to make raster data from vector data. The simplest, Spatial Analyst -> Convert -> Features to Rasters..., puts a value from a vector feature's data table into each raster cell it touches. The Spatial Analyst -> Distance -> Straight Line... function makes a raster of distances from vector features. (It can also do a couple of fancier things that we'll see soon.) The Spatial Analyst -> Distance -> Allocation... function makes a raster verisons of Theissen polygons around input points. They are pretty easy, so let's dig-in and convert some vector data to rasters.
Start with your allroads3, schools, and census block centroids data. Convert each into thee rasters using the two techniques above. (The third one may not work with the roads. But try.) Describe the differences in each set of outputs.
Let's use ArcGIS to do some cost-surface modelling.
Print your least-cost paths map and write a paragraph describing what it means.
Answer the questions in bold type above.
Help - is on the main menu.
Topics like "flowdirection", "distance", "cost-distance" and "least-cost" in Spatial Analyst will get you where you need to be.
Set the Spatial Analyst -> Options...