ArcMap Raster Intro Lab

Due in two weeks

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:

Import a DEM and experiment with some of ArcMap's terrain visualization and analysis functions (calculate contours, slope, aspect, and hill-shaded rasters).
Use some more general raster GIS functions (reclassify and raster calculator) to do a simple terrain-based site suitability analysis.
Gain further experience with raster mode analysis with Spatial Analyst's hydrological analysis facilities.
Convert several vector datasets into rasters showing feature locations and showing distances to features.
Gain further experience with 'thinking in raster mode' using Spatial Analyst's cost-distance and least cost path facilities to model routes from block centroids to schools.

Data Needed

The data are on \\Odin\Data\ You should already have the drive "mapped".

Spatial Analyst extension - OK, it's not data, but you do need it for this.
honolulu.dem - (in \\Odin\Data\10mDEMs\Oahu10\honolulu.dem) USGS 10m DEM for Honolulu Quad
schools.txt - (or the shapefile you made from it) latitude, longitude, feature class, and name for a set of points representing schools on Oahu
allroad3.shp - as before
oahucbpts.shp - the census block centroids points that you have used previously.

Preliminaries (the set-up):

(After starting ArcMap...) Make the Spatial Analyst extension available by right-clicking "Tools" in the main menu and making sure that "Spatial Analyst" is checked.
Load the Spatial Analyst extension by left-clicking "Tools" in the main menu, then under extensions, click the "Spatial Analyst" check box.
Set several options that impact Spatial Analyst Extensions. Spatial Analyst -> Options... Then on the General tab, set the "working directory" that ArcMap will use when it needs disk-space for its operations to be either the C:\temp directory of the PC you are working on (it will run faster) or your (U:\username) directory (it will save the cruft with your other stuff). On the Extent tab set it to be "union of inputs". On the Cell size tab, choose "minimum of inputs".

Displaying and Messin' wi' DEM Data

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 Site Suitability Example Using classic Raster Manipulations

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?

A foray into hydrological analysis

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:

[mybasins] = basin(flowdirection([mydem]))

and then click 'Evaluate'. This is a shorthand way to say use the elevation data in mydem to calculate flow directions and then calculate drainage basins from those flow directions.

To better display the basins:

make them transparent (properties of the layer)
symbolize them as unique values
pick a 'fruits and minerals' color scheme
display the hillshade of the terrain under them

Cool, huh? Examine the basins and write a sentence or two on whether the result seems plausible given your understanding of the area's terrain and hydrography. How could you use the DEM with the reclass and raster calculator to get rid of the odd artifacts out in the ocean? (The analysis mask in the Spatial Analyst -> Options panel can help automatically do this kind of thing.)

Converting Vector to Raster Data

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.

Calculating Cost-distance surfaces and least-cost paths

Let's use ArcGIS to do some cost-surface modelling.

Try this:

calculate the cost-distance surface from your 'schools' points using the "distance from allroads3" raster as a "cost raster". (Spatial Analyst -> Distance -> Cost-Weighted), with Distance_to='schools', Cost_Raster=, check the boxes for create direction and create allocation.

Now,

Find the shortest paths from your schools to your block centroids. (Spatial Analyst -> Distance -> shortest path), with Path-to='sources', cost distance raster = 'CostDist to Sinks", Cost direction raster= "CostDirection to sinks", Path type = "For Each Cell". OK?
That should have produced a set of least-cost paths from each source point to the nearest sink point.

Print your least-cost paths map and write a paragraph describing what it means.

Deliverables

Answer the questions in bold type above.

Hints

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...