Vector Analysis with ArcGIS

Goals

The goal of this lab was to utilize numerous geoprocessing tools for vector analysis, in order to determine suitable bear habitats in Marquette County, Michigan.

Background

Each point on the map represents a bear location, which was collected using a global positioning system (GPS). Based off these points the Michigan DNR would like to know which areas are suitable for them to study bear habitats.

Methods

To begin the lab I had gather all the necessary data. However, all the data had already been uploaded to our class folder, which made this process fairly simple. The landcover information came from the USGS NLCD and the DNR management units can be found here. After familiarizing myself with the data and information it can apparent to me that the bear locations were in an X Y coordinate format that was not from a spatial database. In order to correct this issue I had add the X Y coordinates as an ‘event theme’. An ‘event theme’ is a temporary display of X Y data in ArcMap. Once a created the ‘event theme’ the bear locations appeared as points in ArcMap. Since an ‘event theme’ is only temporary it was necessary to then export the points as a feature class.

After establishing the bear locations as a feature class, I then went ahead and added all the rest of the feature classes that would further assist me in the lab. Next I performed a spatial join between the bear_locations and landcover feature classes. As a result, I was able to determine which land cover type most of the bears were located in when the GPS points were collected. Based off this information I was able to conclude that the top three bear habitat types are within the landcover categories, Mixed Forest Land, Forested Wetlands, and Evergreen Forest Land.

Numerous streams are located within the study area, and based off biologist’s findings, it has been assumed that bears might be found within close proximity to streams. To test their assumption I performed a spatial query, using bear_cover as the target layer and streams as the source layer. When I examined the output table from the spatial query I found that approximately 72 percent of the bears were located within 500 meters of a stream. Since a majority of the bears are located within 500 meters of a stream, it confirms the biologist’s assumption about the relationship between bears and streams. Thus, the distance to streams is an important habitat characteristic.

Next, I wanted to find which areas within Marquette County, Michigan, are the most suitable areas for bear habitats. In order to accomplish this task I had to begin by exploring the various analysis tools within ArcToolbox. I determined that I would be a good idea to start by using the buffer tool from the overlay analysis tool category. I performed a 500 meter buffer on streams feature class, titling the output feature class as streams_buff500m. Then I executed an Intersect between suitable land cover and streams_buff500m. Following the intersect I decided to dissolve my newly created intersect feature class, which removed the internal boundaries.

After prepping my data from the previous steps, I added the dnr_mgmt feature class for Marquette County, MI. At this point I decided to use the Clip tool from ArcToolbox and clip the study_area and dnr_mgmt feature classes together. Next I intersected my newly clipped feature class (Clip_DNR) with my Suit_Buff_Int_Dis feature class, which established Suit_DNR_Area feature class. Following that operation I decided it would be a good idea to dissolve the Suit_DNR_Area, which would eliminate the internal boundaries.

In order to provide the Michigan DNR with a more suitable habitat model for bears in Marquette County, I needed to provide them with bear management areas that are at least five kilometers from an Urban or Built up lands. I began this objective by taking the landcover feature class and performing a query on Urban or Built up lands. From this query I created a new feature class from the selected areas and titled the output feature class as Urban_Built. From this point I buffered the Urban_Built feature class by five kilometers. Following the buffer I then utilized the erase tool from the ArcToolbox, naming my output feature class DNR_Suit. As result of all these steps I finally arrived at my answer which can be further observed in Figure 1.

After arriving at my answer, which provides the Michigan DNR with a suitable habitat for bears within Marquette County, I went ahead and created a visually appealing map. I tried my best to create an acceptable Legend which would allow the intended audience to easily understand the data that is being depicted in my map. Furthermore, I provided a second map within my data frame of the state of Michigan with Marquette County being highlighted in yellow. Highlighting Marquette County within the state of Michigan will provide the intended audience with a perspective into the specific geographical location where the suitable bear habitats are positioned.

To become more familiar with Python, I was requested to write a few simple commands to perform a couple of the geoprocessing operations that I conducted in the lab. I began loading ArcGIS python window and docking it to the bottom of screen. From here I ran a buffer on the streams feature class, but this time I used a one kilometer buffer instead of the 500 meter buffer that I used in the lab. After the buffer, I wrote a code that would perform an intersect operation between the results from my new buffer and the suitable land use. Finally, I wrote a command within the python window which would erase the buffer of the urban areas that were utilized in my lab. The results from my commands in python can be seen below in figure 4.

Results:

Figure 1 depicts the Marquette County Suitable Bear Habitats. Figures 2 and 3 shows my data flow model which I used in objectives two through six. Figure 4 is the command codes that I wrote to perform the steps in the last objective of the lab.