Lab 5 Vector Processing and Pyton Scripting.

Objectives: For Lab 5 there were a few objectives. First vector processing, the second part of the lab will be python scripting in part 2.    
Part 1:  Objective 1:  
Q1: Marquette_bear_study is a database. 
Q2: bear_management_area and landcover are data sets and shapefile.  
The objectives were to map a GPS MS Excel file of black bear locations in Michigan, to determine the forest types where black bears are found in central Marquette County, Michigan based on GPS locations of black bears, to determine if bears are found near streams, to find suitable bear habitat based on two criteria, to find all areas of suitable bear habitat within areas managed by the Michigan DNR, to eliminate areas near urban  lands, generate cartographic output, and to generate a digital data flow model of the procedures used to determine suitable bear habitat in Marquette County, Michigan. 

 Methods: The first thing to do was to add the bear locations as an XY event theme.  The best way to do this is to go to the File menu in ArcMap and choose add data and choose add XY data.  When the window pops up choose bear_location_geo$ from file folder and choose point_x for x field and point_y for y field.
Choose edit and choose NAD_1983_Hotline_Oblique_Mercator_Azimuth_Natural_Origin and click ok and ok again.  The bears should appear as points in ArcMap.  Once they are mapped export to bring them into your geodatabase as a feature class which has the ID number of the bear and the land cover type in which is was found in the attribute table. I then named the new feature class bear cover. 

Using the data found the 3 best habitat types. 
Q4a:  Habitat 1:  Evergreen Forest Land
Q4b:  Habitat 2:  Forested Wetlands
Q4c:  Habitat 3:  Mixed Forest

Objective 3:




 Add all the feature classes within the bear_management_area feature dataset to a data frame and arrange them properly. Then change the symbology for landcover layer so that  “minor type” field is able to be seen.  Then new landcover and bear locations should be intersected to create the bear cover feature layer.  Then use summarize to find out which are the top 3 habitats that bears are found in. Take bear locations and use select by locations to select areas that are within 500 meters of a stream when there GPS location was collected.  There were 49 out of 60 or 81.67 % of bears were found within 500 meters of a stream. 
I find this area to be suitable for bears due to the fact that the area selected is near streams and wooded areas away from the urban areas.  If 49 out of 60 bears are located there, then I would say that it a good representation of a good habitat for bears. 

Objective 4:

To find suitable areas of bear habitat by first using the select by attributes tool to select the 3 land types that bears were found in most and name it bear habitat. .  Then intersect the bear habitat and the bears found within 500 meters of a stream.  Then the dissolve tool is used to get rid of the polygon shapes that are found from more than one layer being combined.

Objective 5:

Next, add in the Michigan DNR data called DNR Management from the file.  To find suitable bear habitat that is located on the DNR management lands.  Use the intersect tool to intersect the habitat with the DNR management feature class to find a location within the DNR lands and then dissolve  to make the polygons solid and without features within polygons (Q8).

 

To find an area that is away from the urban environment use select by attribute to determine the urban areas so as to stay away from them.  Then use the buffer tool to buffer out a 5 kilometer area from urban areas.  Then dissolve the buffer so that there is one solid buffer.  Finally use erase so that only the best possible locations are available.

Results:  The first image is of the data flow model used to help follow along with what was done for methods.  The second image is of the map made with the best possible locations available.

Figure 1: Data Flow Model resulting in the best possible locations for a bear habitat. 

Figure 2:  Suitable Bear Habitat, Marquette, Michigan, notice the light green inset of the study area. 

The above map shows the areas that are ideal for bear habitat in pink, they are located near streams and have the attributes for proper living conditions for bears.  The dots are where bears are located and the red is where it is not suitable for bears. 

Discussion:
It is interesting that the areas in red that were not suitable for bear habitat did not have any bears in that area according to the data given, they were only close to the red in one area of the map located on the southwestern part of the map.  Also, the areas that are suitable for bears had a great deal of bears in the areas.  There were areas suitable that did have any bears in that area according to the data. This study area had a lot of areas suitable for bears. 

Part 2:  Introduction to Python Scripting

Introduction:

The objective of this lab is to learn how to use Python Scripting using ArcGIS with the python window and to explore the functionalities to run tools by writing scripts. 

Section 1: 

Objective is to find suitable areas for the development of tourist resorts.  The Wisconsin Department of Tourism wants to find areas within the state that have high potential for the establishment of suitable resorts.  The resorts should be within 10 miles from the city and 5 square miles in area.

First, I opened ArcMap and opened a new map.  I created a new map and I added the following features to my map, WI_Cities, Interstates, Lakes, an d Counties, then I clicked the python window to begin.  I then proceeded with the instructions to make a 10 mile buffer. 

Figure 1:  Buffer distance of 10 miles of a city. 

After typing in the codes, I pressed F2 to check for errors and there were none present, then I executed the command. 

Next, find the lakes that are greater than 5 square miles by writing a code to select the attribute. 

Figure 2: Lakes greater than 5 square miles. 

I had some trouble with this one but got it to work after some trial and error to make sure I had it written exactly right the last time I tried it. Final result is the last command. 






Figure 3:  Best Locations for Lakeside Resort Buffer

Section 2:  Modeling air pollution impact zones

Wisconsin EPA is interested in the assessment of potential impact zones for nitrous oxide and other air pollutants from automobiles near the interstates in Wisconsin and the human and ecosystem health. 

The criteria for air pollution impacts:  The Wisconsin EPA has determined that areas within six miles of an interstate have potential for air pollution problems with the impacts reducing the farther one is from an interstate.  The WI EPA wants you to develop an index model that will show six zone of potential air quality problems within a one mile interval. 

I created a multiple ring buffer.

Figure 4: Multiple Ring Buffer

Figure 5:  Interstate Multiple Ring Buffer Map with Cities. 

 

Figure 6: Zoomed in of Multiple Buffers to show values.