The purpose of this lab is to determine suitable bear habitat within a certain study area of Marquette County, Michigan. Factors which influence bear habitat will be overlaid with each other to determine the best habitat locations. One goal is to show how to properly use a data flow model. The data flow model in this post will show the process which will contain each input needed to create the map. Antoher goal of this lab is to create a map showing bear habitat areas in a study area in Marquette County. The last goal of this lab is to demonstrate a very basic understanding of some simple Python coding. The tools Buffer, Intersect, and Erase will be coded.
Methods
Step 1: Export and map GPS coordinates from an excel file into ArcMap.
To do this, first, the excel document was added to ArcMap. Then, the data was added through the Add XY Data label under the File tab. The X-Field and Y-Field were changed to "POINT_X" and "POINT_Y". Also, the coordinate system was changed to "NAD_1983_HARN_Michigan_GeoRef_Meters". After hitting the "OK" button, ArcMap made a shapefile by default. Instead of using the shapefile, it was exported into a feature class with the name bear_locations.
Step 2: Determine Bear Habitat
First, all of the necessary feature classes were added: BearLocations, Landcover, Streams, study_area, and dnr_mgmt. Then, with BearLocations and Landcover, an Intersect was performed creating a new layer called bear_cover. By doing this, the land cover type can be assigned with the bear locations. A summarize was performed on the MINOR_TYPE field of the bear_cover feature class in order to see which land cover types were the most common with bear locations. The three types include Mixed Forest land, Forested Wetlands, and Evergreen Forest Land. With this information a query was performed on the Landcover feature class to select any entry in the MINOR_TYPE field which had any three of the above land cover types. After the selection, a new layer was created with the selected attributes and was given the name PrimeBearLandcover. The data flow model for this step is shown below in Fig 3.0.
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| Fig 3.0: Data Flow Model for Step 2 |
Step 3: Link Bears to Streams and Land Cover
In this step, it was determined that streams were a very important part of suitable bear habitat. This was determined by creating a buffer of 500 meters from the feature class Streams, and then performing the Dissolve tool on it. The name assigned to it was Stream500mBufferDissolve which was then intersected with PrimeBearLandcover to see how many bears were located within this stream buffer. This outputted the new feature class named PrimeBearHabitatNearStreams. It turns out that the vast majority of the bears were located within this stream buffer zone. For clarity, PrimeBearHabitatNearStreams is dissolved creating a new feature class named PrimeBearHabitatNearStreamsDissolved. This feature class shows the bear habitat which have close proximity to a stream and have the suitable land cover type. The data flow model for this step is shown below in Fig 3.1.
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| Fig 3.1: Data Flow Model for Step 3 |
Step 4: Locate DNR Management Areas Within the Study Area
The feature class dnr_mgmt had polygons located inside of polygons. This is because there are groupings within the management areas. However, for this analysis, all that mattered was the DNR management areas, not the groups. To fix this, the Dissolve tool was used on dnr_mgmt. The new output feature class was given the name Dnr_mgmtDissolved. This feature class was then intersected with the feature class PrimeBearHabitatNearStreamsDissolved. The name given to this feature class was BearhabStreamsDnr_mgmt. This new feature class shows the DNR management areas located within 500 meters of a stream and areas that have the three main land cover types. The data flow model for this step is shown below in Fig 3.2.
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| Fig 3.2: Data Flow Model for Step 4 |
Step 5: Find Bear Habitat 5 km Away from Urban and Built Up Areas
In order to find bear habitat that is 5 km away from urban or built up areas, these areas must be identified. These can be identified by using the MAJOR_TYPE field in the Landcover feature class. First, a query must be performed to select only those entries with urban/built up in them. Then, a new layer and feature class is created using the selected attributes. This new feature class is given the name UrbanBuiltUpLand. This is then buffered out 5 km. The buffer tool is ran on it and the new feature class UrbanBuiltupLand5KmBuffer is created. Because this has many polygons in the layer the Dissolve tool is ran on it as well. This creates a new output feature class titled UrbanLanDissolved5KmBuffer. A clip is performed using the feature class created in step 5: PrimeBearHabitatNearStreamsDissolved and UrbanLanDissolved5KmBuffer. This outputted a feature class given the name BearHabWithin5Km. This has an area which has suitable bear habitat and is within 5 km of urban or built up lands. However, the DNR wants to know suitable bear habitat areas which are farther than 5 km away from urban or built up lands. In order to display this area on the map, the feature class BearHabWithin5Km must be placed above PrimeBearHabitatNearStreamsDissolved in the table of contents. By doing this, PrimeBearHabitatNearStreamsDissolved will display the suitable bear habitat at least 5 km away from urban or built up lands. The DNR management lands must also be displayed on the map to be at least 5 km away from urban or built up lands. To do this, the Erase tool is used between the BearhabStreamsDnr_mgmt and UrbanLandDissolved5KmBuffer feature classes. This feature class is given the name PrimeBearLocations. The data flow model for this step is shown below in Fig 3.3.
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| Fig 3.3: Data Flow Model for Step 5 |
Step 6: Map the Data
Using the features PrimeBearLocations, BearHabWithin5Km, Streams, BearLocations, and PrimeBearHabitatNearStreams, a cartographically pleasing map was created. An inset map, scale bar, legend, title, base map, and north arrow were all added to the map. Some transparency was added to the polygon feature classes so contrast was was pleasing to the eye. The map shows the prime bear habitat areas within with sections being separated by a 5 km buffer from urban or built up lands. The map is displayed in the results section below in Fig 3.6.
Step 7: Write Some Python Code
The Buffer, Intersect, and Erase tools were all successfully used by using the ArcGIS Python window. Basic code was written to run these tools. The purpose of doing this was to see that writing code is a much more powerful way to run tools than to do it through the user interface of ArcMap. Below, in Fig 3.4, are the lines of code which have been put into a word processor to make it look neater. Headers have been added which are not part of the code to make it easier to identify the tool being used. Both the entry and results lines are displayed.
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| Fig 3.4: Python Script for Buffer, Intersect, and Erase |
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| Fig 3.5: Data Flow Model |
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| Fig 3.6: Bear Study Areas Within Marquette County, Michigan |
The map above displays the features described in Step 6. Streams are a very important part of bear habitat. As seen in the map, most of the bear locations occur within the buffer zone of 500 meters of a stream. Also important is the 5 km buffer which can be seen by the change in color of the habitat area. Bear locations are much more common outside the buffer zone than within. This seems appropriate because bears tend to stay away from humans. The DNR management areas which overlay with the suitable bear habitat, are shown in a dark purple. This area is small enough where there is no point where a bear was tracked in this area. This has probably more to do with the area being pretty small than anything else. The ideal bear habitat is found in both the dark and light purple areas.
Sources
Michigan Geographic Framework: Marquette County. (2014, June 1). Retrived December 9, 2016 from http://www.mcgi.state.mi.us/mgdl/framework/metadata/Marquette.html
Wildlife_mgmt_units. (2001, August). Retrieved December 9, 2016, from http://www.dnr.state.mi.us/spatialdatalibrary/metadata/wildlife_mgmt_units.htm
Michigan 1992 NLCD Shapfile by County. (2002, January 11). Retrieved December 9, 2016 from http://www.mcgi.state.mi.us/mgdl/nlcd/metadata/nlcdshp.html
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