Advanced GeoSpatial Analysis
2/16/2016
Extra Credit Objectives
This exercise will provide you the opportunity to practice some more complicated raster
analysis methods.
The exercise is designed with minimal instructions, with the expectation you will
read the documentation on the grid functions you will use.
Setup
Define proj
You will work with the following ArcInfo data sets:
Seadem (a digital elevation model grid stored as an ASCII raster file),
seadem.asc in the zipped file exc8b.zip on the website.
Neighborhood Districts (you will need to get this from
wagda.lib.washington.edu > Download (Quick Links) City of Seattle Data >
Neighborhood Boundaries > Neighborhood districts)
Notes:
1. The ASCII raster file (seadem.asc) needs to be imported as a grid
before you can perform any mapping or analysis.
2. The seadem grid is stored in projection UTM, Zone 10, Units
Meters, Datum NAD83.
3. The Neighborhood Districts shapefile is stored in projection State
Plane, Zone 4601 (Washington North Zone), Units Feet, North
American Datum (where could you find this information?).
4. (Check-you may need to define the projection for the DEM using
ArcToolbox and the specified projection files (seadem.prj) that
was located in the zip file.)
5. You will need to export the Neighborhood Districts shapefile
to match the elevation grid before doing any analysis—they
need to be saved in the same coordinate system before
performing analyses otherwise bad things might happen.
6. The field in this attribute table representing neighborhoods is
Nbhood. This is the field you should use for all analysis and grid
conversions.
7. For the Seattle Area, datum HPGN is also known as NAD83
HARN.
8. Spaces are not allowed anywhere in any pathname in which
grids are stored or used.
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Advanced GeoSpatial Analysis
2/16/2016
Background and Definitions
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Advanced GeoSpatial Analysis
2/16/2016
Grid Statistics:
Directions
It is highly recommended that you set your geoprocessing environments
(analysis extent and snap raster) whenever conducting raster analysis.
1. Create a slope grid from the Seadem grid. Use degrees as the unit.
Q1. What are the overall grid value statistics (mean, minimum, maximum, and
standard deviation) for the slope grid?
Provide these values in a tabular format so they are easier to read (any table will
do, not necessarily a GIS output)
2. “Clip" the slope grid using the non-water polygons in the Neighborhood
Districts shapefile. In order to do this you will need to:
1. Create a polygon shapefile that consists of only non-water polygons.
2. Either use the new non-water shapefile as an "analysis mask" or use
one of the Extract functions (see ArcGIS help) to create a new grid
whose value is the same as the slope grid, but limited by the nonwater polygons.
3. If you go with the analysis mask, apply the mask and then perform a
calculation where the expression is identical to the input grid name.
Q2. What are the overall grid value statistics (mean, minimum, maximum, and
standard deviation) for the new masked slope grid? Add these values to the table
created in question 1.
Zonal Statistics:
3. Perform a zonal statistics function on the masked slope grid, using the Neighborhood
Districts to define zones. (NOTE: check to see if your slope layer is a floating point
raster. If so, you need to convert it to an integer file. Read up on floating point files and
use the Int() function in raster calculator to create an integer raster).
Q3. What neighborhood has the greatest mean slope?
Q4. Does this make sense to you given what you know about Seattle topography?
Q5. What are the grid value statistics (mean, minimum, maximum, and standard
deviation) of slope for each Neighborhood? Provide these values in a tabular
format so they are easier to read (any table will do).
4. Join the statistics output table to the neighborhood districts layer and
symbolize the districts by their mean slope value.
6. Create a map where the district overlay is 50% transparent over non-water
slope grid. Export a jpeg of the map.
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Advanced GeoSpatial Analysis
2/16/2016
Focal Functions:
5. Focal functions can perform a number of different operations that take
into account local variation in the neighborhood around each input cell.
Focal functions are frequently referred to as "Neighborhood Functions."
6. Perform a Focal Statistics analysis on the slope grid (use the Variety
statistic in a 3 x 3 cell rectangular window).
7. What is the range of values in the newly created grid?
7. Color the grid using the classified symbology and a red to blue color ramp. Make the
lower values blue and higher values red.
8. Which neighborhood reflects the lowest contrast in slope, what is the dominant color
of the neighborhood in the grid?
9. What do you know about this area’s geomorphology to explain the phenomena?
Deliverable
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Provide tabular answers for questions 1,2, and 5.
Provide written answers for questions 3,4,7,8, and 9.
Insert the jpeg from question 6 – make sure you have a proper
map with all the fixin’s…!!
This should be in a Word document submitted to the CollectIt folder
by February 13, 2014.
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