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									GEO 266: GIS ANALYSIS
MIDTERM EXAM – Due May 3, 2011 (before class)

Instructions
This exam consists of multiple parts that will be completed both in-class and outside of class. The
entire exam is ‘open book’ meaning you can use your textbook, on-line resources (i.e. ESRI help), or
any resources EXCEPT your peers. This is an individual assignment and all answers must be
adequately cited or put into your own words.

To submit your midterm, email all responses and outputs in one document (.pdf) to the instructor.

PART I
Identify the transformation tool used for each illustration. The gray shaded areas indicate polygons in
the dataset. Possible choices are (not all are present): Intersect, Union, Clip, Erase, Symmetrical
Difference, Identity, Dissolve, Buffer, Near, Simplify, Centroid, Spatial Join, Select.




         National Forests            Ecoregions                         Ecoregions


1. ____________________




    Cities                         Highways             Cities have Attribute of Distance to Closest Highway


2. ____________________




3. ____________________
4. ____________________




       Counties                   Cities                     Counties with “summarized” City Attributes

5. ____________________


PART II
LiDAR Data: Based on Josh McLaughlin’s presentation in class answer the following question.

    1. Explain one thing about the LiDAR data acquisition / processing that you find most interesting.

PART III
You will create a map of Heritage Trees in Portland, by Neighborhood.

Instructions
1. Download the ‘Heritage Trees’ dataset from the CivicApps website (www.civicapps.org). Unzip
    the shapefile and add it to an empty map.

2. Go to the T: drive on the classroom computers, and in the GISdata folder you will find the RLIS
   data from Metro. Copy the Neighborhood (nbo_hood) shapefile on your flash drive or import
   into a geodatabase, and add to your map document.

3. Create a multivariate (multiple variables) map that shows the frequency (count) and average height
   of trees within each neighborhood on the same map. You can do this by copying the layer you
   are interested in mapping and pasting it into the same data frame. This gives you two layers to
   symbolize at the same time. Include all relevant map elements.

4. Explain what tools/process you use to get the frequency & average height, by Neighborhood.
PART IV
Problem Statement: You are interested in understanding the spatial distribution of salmon in the Hoh
River watershed on the western Olympic Peninsula of Washington state. To do this, you will create
maps that show high salmon diversity, salmon rivers at risk based on development & logging, and
level of protection for salmon rivers.

Datasets:
Download the Sp11Midterm_Data from the course website containing the following datasets:

   -   Salmon distribution datasets: chinook_distr, chum_distr, coho_distr, sockeye_distr (Note:
       although they look like lines, each of these datasets is actually a five-foot buffer polygon
       around a section of the watercourse)
   -   Road datasets: clallam_roads, jeffereson_roads
   -   Land ownership: land_ownership
   -   Study Area Boundary: study_area
   -   Land Use / Land Cover data: WesternWA_LULC

Deliverables: You need to turn in a written description of what tool(s) you use and the steps you
take to answer each question (steps 1,2,4-8). Include any maps or graphics that you think will
enhance your descriptions.

Getting started: Start by downloading the files and importing into a geodatabase (you will need to
create a blank geodatabase – call it salmon). Start ArcMap, open a new empty map, set your ‘Salmon’
geodatabase as the default geodatabase for the map. Add all the datasets to your new blank map.

Use the following analysis techniques/tools (not necessarily in this order): Clip, Buffer, Export, Select by
attribute, Merge, Feature to Line, Intersect, Union

   1. First you will need to prepare your datasets for analysis. Create one unified feature class from
      the two separate road layers.

   2. Next extract all your datasets to the study area boundary into your geodatabase.

   3. Since you are working within a geodatabase, your feature classes should already have an area
      and length field included. Check your attribute tables to make sure this is the case.

   4. Next, you want to create a new dataset that shows areas of high salmon diversity. This will
      include the watercourses that contain all four salmon species (where the four datasets overlap).
      Call this new feature class, ‘high_salmon_diversity.’ This will be difficult to see on your map –
      convert to a line feature class.

   5. You also need to have a layer that shows the combined range of all salmon species. Create a
      single dataset that shows all the watercourses where any of the salmon species can be found.
   Call this new feature class, ‘salmon_range.’ This will be difficult to see on your map – convert
   to a line feature class.

6. Now you want to find which sections of the salmon ranges are most at risk because they are
   adjacent to logged areas, developed areas (consider agriculture to be a developed area), or
   roads. In the WesternWA_LULC layer, the field “PRIM” provides land use/land cover codes:
   > Everything in the 200’s are developed areas
   > Everything in the 300’s are agriculture
   > Everything in the 610’s are logged areas


   Export these areas into a new feature class and call it ‘developed_logged’

7. To find out which areas are ‘at-risk’, use the ‘salmon_range’ dataset to find
        salmon rivers within 300’ of a logged, developed, or agricultural area
        salmon rivers within 300’ of a road

8. Finally, find out what level of protection exists for salmon in the study area. Use the Land
   Ownership layer with the following assumptions:
   > Olympic National Park = highest level of protection
   > Olympic National Forest/Native American Reservations/Spokane District = moderate
       protection
   > private land = low protection


   In the ownership layer, if the field “AGENCY_NM” is blank, the land is privately owned.

9. Create a map of both the “high salmon diversity” and “salmon range” you created in steps 4
   and 5. Be sure to include all of the standard map elements (title, legend, scale bar, etc.). Export
   the map as a .jpg and paste it in midterm document.

10. Create a map of the “at-risk” salmon ranges you created in step 7. Be sure to include all of the
    standard map elements (title, legend, scale bar, etc.). Export the map as a .jpg and paste it in
    midterm document.

11. Create a map that shows the level of protection from step 8. Be sure to include all of the
    standard map elements (title, legend, scale bar, etc.). Export the map as a .jpg and paste it in
    midterm document.

								
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