GIS 1 Lab 3: Vector Analysis with ArcGIS
Goal: The primary goal of
the lab was to determine suitable habitat for bears in Marquette County,
Michigan, using various geoprocessing tools.
Methods: Detailed
methods are provided under each heading.
Objective
One: Map a GPS MS Excel file of Black Bear Locations in Central Marquette
County, Michigan.
The lab3.zip file was downloaded and placed in my lab3 folder
and this information was added to the map. The bear locations were located in a
non-spatial database and needed to be added as an event theme. Once this was
completed I exported them to place them in my geodatabase and saved the event
theme as bear_locations.
Objective
Two: Determine Bear Habitat.
All feature classes in the bear_management_area feature class
were added to a data frame. Bear habitat was determined by performing a spatial
join operation by using the bear_locations and land_cover feature classes; this
new feature class was named bear_cover. I then found the number of bears in
each habitat by selecting attributes using the Minor_Type field. The results
were used to create a layer called top_bear_habitat_type; the three types of
cover were evergreen forest land, forested wetlands, and mixed forest land types.
Objective
Three: Determine Bear Locations Within 500 meters of a Stream.
Bear_locations was intersected with the results of a 500
meter stream buffer which was dissolved (named dissolved_500m_stream_buffer),
which resulted in 49 out of 68 (72%) of the bears were located within 500 meters of streams in area of interest. Biologists consider any number above 30% to be significant.
Objective
Four: Determine Suitable Bear Habitat.
For this objective, I performed an intersection of top_bear_habitat_type
and dissolved_500m_stream_buffer and then ran dissolve, which resulted in
suitable_bear_habitat.
Objective
Five: Suitable Bear Habitat in DNR Managed Land.
I determined the DNR managed land area by performing a clip
using the dnr_mgmt and study_area feature classes to eliminate areas that the
DNR does not control. An intersection was then performed to determine the
suitable bear habitat under DNR control. A dissolve was then performed on the
resultant suitable_bear_habitat_dnr_management_area, which I named
dissolved_suitable_bear_habitat_dnr_management_area.
Objective
Six: Final Determination of Ideal Bear Management Areas.
The
land_cover feature class was used and a select by attributes query (by Major_Type field) was
performed to determine urban or built-up areas. The result was used to create a
layer called urban_or_built_up_areas. A buffer was performed on this layer
which resulted in urban_or_built_up_areas_5k_buffer, which was then dissolved.
The resultant dissolved layer (dissolved_urban_or_built_up_areas_5k_buffer) was
then intersected with the dissolved_suitable_bear_habitat_dnr_management_area.
An erase was then performed on this result which enabled me to find the
final_ideal_bear_habitat_area.
Objective Seven: Generate a Map and Data
Flow Model.
The final map was created in ArcGIS with a legend, north arrow, study area insert, source and author information and scale added to conform with cartographic methodologies. A data flow chart was created using MS Visio.
Objective Eight: Introductory Python
Scripting.
The purpose of this objective was exposure to Python
scripting using simple commands in preparation for more advanced GIS courses. A
buffer analysis was performed with the arcpy.Buffer_analysis command. An
additional buffer was then run on the streams feature class with a distance of
one kilometer. The results of this buffer were then intersected with suitable
land use with the command arcpy.Intersect_analysis ([“streams_buf”,
suitable_bear_habitat”}, “land_stream”). An erase of the buffer of urban areas
was then performed with the command arcpy.Erase_analysis(suitable_bear_habitat”,
Urban_area_buff”, suitable_hab_URBAN”). The results can be seen in the last
diagram in the results section.
Results:
The resultant map depicts the areas that the DNR considers ideal bear habitat; it is habitat that contains streams and the proper landcover and is located within DNR management boundaries. The area that fits the ideal bear habitat is quite small; most bears are found on land not controlled by the DNR which could potentially limit the effectiveness of governmental management of bear management.The data flow model outlines the steps that I took in determining ideal bear habitat per DNR guidelines set for the simulated project. The Python script lists the steps and commands used in the simple introductory Python objective.
The resultant map depicts the areas that the DNR considers ideal bear habitat; it is habitat that contains streams and the proper landcover and is located within DNR management boundaries. The area that fits the ideal bear habitat is quite small; most bears are found on land not controlled by the DNR which could potentially limit the effectiveness of governmental management of bear management.The data flow model outlines the steps that I took in determining ideal bear habitat per DNR guidelines set for the simulated project. The Python script lists the steps and commands used in the simple introductory Python objective.
Sources
All data were
downloaded from the State of Michigan Open GIS Data Site at http://gis.michigan.opendata.arcgis.com
Landcover Data USGS NLCD from http://www.mcgi.state.mi.us/mgdl/nlcd/metadata/nlcdshp.html
DNR Management Units from http://www.dnr.state.mi.us/spatialdatalibrary/metadata/wildlife_mgmt_units.htm
Streams Data from http://www.mcgi.state.mi.us/mgdl/framework/metadata/Marquette.html
Michigan
Center for Geographic Information at https://www.mcgi.state.mi.us/mgdl/
