The primary goal of this lab was to use a variety of geoprocessing tools we have learned within ArcGIS to find the best bear habitat for a study area found in Marquette county, Michigan.
Background:
Using recorded GPS data and tools in ArcGIS, the DNR of Michigan wanted to know what the best suitable habitat was for black bears following a couple of specific criteria.
Methods:
Included in the data was an excel file that had the bear locations. In order for it to be used I had to import it into ArcGIS. Once the data was imported and exported as a feature class I could add it to my geodatabase. Once adding the bear locations to my study area map I was able to see where the bears were located.
In order to find the top habitats based on the bear locations I had to join them with the land cover type class. After analyzing and summarizing the data I was able to find the top three land covers. They included mixed forest land, forested wetlands, and evergreen forest land. I created a separate feature class just including these three.
The next step was seeing how many bears were found near to streams. I put a 500 meter buffer around the streams in the study area. Along with adding the buffer it was also dissolved for clarity reasons. Once those two processes were finished the result was clipped with the bear locations. Over 70% of bears located were within 500 meters of a stream. This made sense as streams can be used as a major source of nourishment.
The next step was to find the best habitat within the 500m buffer. To do so I intersected the feature class that included the three land covers and the buffered stream. This resulted in a potential habitat feature class. I dissolved this class like the other for clarity and continuity purposes.
One of the last factors I had to account for was DNR owned land that fell into the potential bear habitat. I clipped the DNR feature class with the study area. This got rid of any impertinent data. Once again I dissolved the internal boundaries and intersected this feature with the potential habitat. This resulted in creating a feature class showcasing potential bear habitat on DNR land.
The last factor I had to consider was proximity to Urban or Built-Up lands. I ran the buffer tool on a feature class I created that just had that Major type of land cover. I then erased the result but left it on the map in a different color showing habitat that met all criteria except being outside of 5km on urban area.
The steps I used can be found in the model labeled Figure 1. Figure 2. consists of Python code that was used to make a stream buffer, intersect it with land cover and then erase the urban area near. Figure 3. shows the results of the lab.
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| Figure 1. |
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| Figure 2. |
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| Figure 3. |
The map above highlights habitat areas for black bears in the study area. The DNR land is primarily in the middle of the study area. The suitable habitat near urban areas is found in the southern half specifically south west. There is a lot of suitable habitat found the northern half away especially in the northwest part away from urban areas so if the DNR was looking to expand it's coverage; there would be many suitable options.
Data Sources:
http://www.mcgi.state.mi.us/mgdl/nlcd/metadata/nlcdshp.html
DNR management units http://www.dnr.state.mi.us/spatialdatalibrary/metadata/wildlife_mgmt_units.htm
Streams
http://www.mcgi.state.mi.us/mgdl/framework/metadata/Marquette.html
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