Lab 3    

    Goal: The goal for lab three was to introduce us to geoprocessing tools for vector analysis. The tools that we would use would help us to determine suitable habitat for bears in the study area of Marquette County, Michigan. We used a variety of spatial analysis tools along with a few non-spatial tools. The tools used in this lab will lay the ground work for the final two upcoming labs as we will continue to use these tools throughout the remainder of this course.
    Background: The objective of this lab was to workout a scenario for the Michigan DNR. They asked us to find and determine the forest types where black bears are found in central Marquette County based off of the GPS locations from the bears. They want us to determine if they bears are mostly found near the streams, to find bear habitat based on land cover and distance from streams, to find the areas that are managed by the DNR in these bear habitats, while eliminating areas near urban or built up lands, and to be able to generate a data flow model showcasing our workflow and cartographic output.
    Methods: The first tool I used was in objective two. I completed a simple inside spatial join between the bear locations and land cover to give me a table. Upon opening the output attribute table I summarized the minor type field which in turn gave me how many bears live in each land cover. The top three land covers were: mixed forest land with 31, forest wetlands with 17, and evergreen forests with 14 bears respectively.
    The next two tools I used came in objective three, which asked me to find the number of bears that were located within 500 meters of a stream. The first tool I used was a buffer. I buffered the streams to 500 meters and did a dissolve all option which gave me all the streams buffered rather then each individual stream. The next tool I used was the clip tool. I clipped the bear locations and the streams buffer, this gave me the number of bears inside the 500 meter buffer. There were 49 bears inside the buffer out of 68. This equaled 72%, anything over 30% is considered an important characteristic. So, the distance for a stream is relative to bear habitat and is an important characteristic.
    The next two tools again came in objective four. This task asked me to find suitable bear habitat based on two criteria: suitable land cover types, and within 500 meters of a stream. The first tool I used in this task was the intersect tool. I intersected land cover and the streams buffer, this gave me an out of land_streams_intersect. It shows suitable landcover types within 500 meters from a stream. The next tool I used was the dissolve tool. Since polygons from the land cover and streams buffer overlapped, I wanted to get rid of all internal boundaries. I dissolved land_streans_intersect, which gave me landstreams_intersect_dissolve. This rid the internal boundaries in the buffer zone.
    Objective five asked for recommendations to the DNR for a bear management plan. The DNR were looking for suitable bear habitat that were located on their management lands. I had to perform overlay analysis from the political boundaries to find all areas in the suitable habitat that were within the DNR management lands. I clipped DNR_mgmt and the study area. This gave me all the DNR management lands inside the study area of Marquette County. Next I just wanted to find the DNR management lands that were inside my 500 meter buffer. I again clipped the previous clip of DNR_mgmt_clip and the landstreams_intersect_disolve, this gave me the DNR management lands just inside the 500 meter buffer.
    Objective six ask for me to make another map. The DNR liked the work done on objective four that they decided they wanted to change the bear management areas to outside 5 kilometers of urban or built up lands. I began with selecting the urban lands by the select by attributes. I created a feature class out of this selection. The next tool I used was the buffer tool. I buffered 5 kilometers around the urban lands. I then had to clip the buffer to the study area which gave me the area that isn't suitable and the area that is. A majority of the suitable area lies in the northern half of the county while the urban non suitable lands fell in the southern half.
 Results:

 Pictured above is the final maps that I created for this lab. The top right map is a small locator map of Marquette County. The bottom left map if from objective four of the lab asking to show suitable bear habitat based off of two criteria, 500 meters from a stream and land cover. The top left map is from objective six asking to show habitat that is outside of the 5 kilometers from urban lands. The stripped area is not suitable for bears.
Pictured above is my data flow model throughout the lab. It reads from right to left then down. So, it goes streams buffer, then clip, and then down to intersect.

    Python: Above is a small introduction to python script from this lab. The lab wanted to teach us just a few things of how python works and how to understand the script that we were writing. To me, after using python, I think that it is much easier to use then using the tools in Arcmap. It is easier to understand, and easier to come to the conclusion you are looking for. I am excited to use more of python in future labs.
    Sources: There were four different sources that we used to create this map of bear habitat in Marquette County, Michigan. The first source is : Michigan Geographic Data Library.
Source two, land cover is from the USGS NLCD,
http://www.mcgi.state.mi.us/mgdl/nlcd/metadata/nlcdshp.html

Source three, DNR management units,

http://www.dnr.state.mi.us/spatialdatalibrary/metadata/wildlife_mgmt_units.htm

Source four, Streams,

http://www.mcgi.state.mi.us/mgdl/framework/metadata/Marquette.html