GUS 0262: Fundamentals of GIS Spring 2007
Due April 24
Lab 7: Raster Data Model
Purpose of the lab: To introduce raster data handling.
1. Get and Browse Your Data
Using ArCatalog, copy the following grids from the shared drive over to your workspace:
S:/GUS_0262/NED/elevation
S:/GUS_0262/NLCD/NLCD_1992/lc_1992
Using MyComputer, copy the following files from the shared drive over to your workspace:
S:/GUS_0262/NED/elevation_metadata.htm
S: /GUS_0262/NLCD/NLCD_1992/lc_1992_metadata.HTM
The elevation grid is, naturally, an elevation data set in which each grid cell encodes the elevation in meters above mean sea level.
The lc_1992 grid is a land cover data set derived from 1992 satellite imagery. Each grid cell encodes a land cover classification.
Preview the two grids in ArcCatalog
Review the associated metadata files by opening them from MyComputer. Note that the encoding for the land cover classifications is described under the ‘Entity_and_Attribute_Information:’ heading about ¾ of the way through the document.
2. Masking a grid
Masking a grid is analogous to clipping a grid to the boundaries of another data layer, as though you were using a cooking cutter to ‘clip’ the grid. Here, you will mask the grids to the boundary of Chester County.
Create a new shapefile that includes only the boundary of Chester County.
Go to ArcToolbox->Spatial Analyst Tools->Extraction->Extract by Mask.
For the ‘Input raster’, enter the grid you wish to clip.
For the ‘Input raster or feature mask data’, enter the shapefile you wish to use as the ‘cookie cutter’.
For the ‘Output raster’, enter the name of the grid you are about to create (make sure it is no more than 13 characters with no spaces in the name of the grid).
For the remainder of the exercise part of the lab, use these new grids that are clipped to Chester County.
3. Transform both grids to UTM
Both grids are in geographic projection (latitude/longitude) and use a NAD83 datum. Transform the grids to UTM by going to ArcToolbox->Data Management Tools->Projections and Transformations->Raster->Project Raster.
For the ‘Resampling Technique’ choose ‘Nearest’.
For the ‘Output Cell Size’ choose ‘30’. This will create an output grid with a 30 meter resolution.
4. Create a Hillshade
A hillshade is a grid that encodes the reflectance value off an elevation surface given a light source at a certain theoretical position in the ‘sky’. It allows for the visualization of the elevation surface that photorealistic, as though you were viewing the terrain from an airplane.
Start ArcMap and add your UTM elevation data.
Explore your elevation data by zooming in closely to certain areas and using the Identify tool to retrieve elevation values.
Go to ArcToolbox->Spatial Analyst Tools->Surface->Hillshade to create the hillshade grid.
Review the new data set. Add another data layer, like rivers or streets, to help you get oriented viewing the hillshade.
You can also exaggerate the vertical height to improve the visualization of the terrain.
Perform another hillshade but this time change the Z factor to 2 or 3.
Experiment with other parameter changes in the hillshade, including the ‘location’ of the light source, and see how this changes the resulting hillshade layer.
4. Visualizing Terrain
Impressive visualizations of terrain can be easily generated by using the elevation and hillshade grids together. Turn off everything except the elevation and your ‘best’ hillshade grids.
For the elevation grid, go to Properties->Symbology and choose a multi-color color ramp like the one shown here:
Then for the hillshade grid, go to Properties->Display and change the transparency to 30%. Move the hillshade grid above the elevation grid in the Table of Contents.
You can also add land use in the mix. Add the UTM land use layer and move it between the hillshade and elevation grids in the Table of Contents. Make the transparency for land use 40%. Make the transparency for the hillshade grid 50%.
Experiment with different transparency settings.
Try displaying only the developed area in the land use grid to show where the cities are in relation to the elevation information.
5. Generating Slope Data
You can also generate a grid in which each grid cell encodes the slope at that grid cell. It generates slope data for each grid cell location by looking at the immediate cell neighbors for each slope calculation.
Go to ArcToolbox->Spatial Analyst->Surface ->Slope
Make sure your input data is your elevation grid.
Visualize the slope theme. You can see where the steepest slopes occur.
6. Performing a Zonal Function to Summarize Slope by Land Use
Using a zonal function, we can summarize the slope by the land use. In other words, we can derive a single value that summarizes the slope for each individual land use to see if slope varies among different land uses.
Go to ArcToolbox->Spatial Analyst Tools->Zonal->Zonal Statistics as Table
For Zone dataset enter the land use grid
For Zone field enter value
For Value raster enter the slope grid
The zonal function generates a table in which each record is a land use and the fields contain information on the minimum, maximum, range, mean, standard deviation, and sum (which is not applicable here) of the slope values for each land use.
To see the table you must click on the source tab at the bottom of the Table of Contents.
ASSIGNMENT
Objective
The objective of this assignment is to investigate the mean elevation and slope of different types of forest cover in Bucks County: deciduous forest, evergreen forest, and mixed forest, as captured in the 1992 land cover data set.
Deliverables
Turn in a report addressing this objective. This report should include a table showing the area of each of the three types of forest cover, as well as the minimum, maximum, mean, and standard deviation of the elevation and slope for each forest and agricultural cover. Include in your report a land cover and a terrain map.
Getting Started
You can use the zonal statistics function to summarize the area, elevation, and slope by the different land cover classes.
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