The spatial question I chose for this final project is "Where is a good place for me to live in Saint Croix County?". The objectives for this project are to live within 10 miles of a park, 5 miles of urban areas, and 25 miles from a beach. Also, the location needs to be 2 miles away from any previous fire occurrences. For this map in particular, I would be the main intended audience because it was created by my preferences. Although, I am sure there are other people that might have similar preferences that could use the map I created as well to find a suitable place to live. Anyone who prefers living close to urban areas, and enjoys parks and beaches would benefit from this information. Or, anyone who wants to be aware of areas where fires have occurred to hopefully help prevent a house fire as well.
Data Sources:
To create the map based on my spatial question, fire occurrences, urban areas, parks, and recreation data were used. I started by clipping each of these features so only Saint Croix County would show data. I retrieved this data from a few locations. Fire occurrences were from the Wisconsin DNR database and urban area, parks, and recreation data were used from Esri database. The only concerns I have relating to the data is if there has been any changes since that information has been released. Although the Wisconsin DNR is from 2014 and the Esri data is from 2013, there are changes made all the time and new locations being created as well. Also, the fire occurrences data was taken between 1982-2008 which leaves around 8 years that fires could have happened but not been recorded. There is always an issue with coordinate systems and how well they will relate in the data frame as well. However, I did not come across any problems while working.
Methods:
To start off, I clipped all of the data I retrieved so that it would just be shown in Saint Croix County. The four tools I used were buffer, intersect, union and erase. First, I completed a query through recreational areas to find any beach locations, in which Browns Beach was the only one selected. I created a new layer for Browns Beach and set a buffer to 25 miles and then intersected the buffer to Saint Croix County. Next, I set buffers for urban areas (5 miles), parks (10 miles), and fire occurrences (2 miles) while dissolving to combine the internal boundaries for each buffer layer. Then, I intersected each buffer with Saint Croix County once again so the buffers would only be shown within the county. After that, I used the union tool for the parks buffer and the urban buffer and then intersected that with the beach buffer. Lastly, I used the erase tool with input feature being the parks, urban and beach buffer layer and the erase feature being the fire occurrences buffer. This final layer showed the area best suited for me to live based on my criteria.
Figure 1: Data Flow Model
After completing all of the steps in my methods section, it appears that the best area for me to live within Saint Croix County would be on the Western side of the county. This area is closer to urban areas, parks, and Browns Beach. This area is also 2 miles away from any fire occurrences that had happened between the years of 1982-2008. The map below shows in yellow the results of where the best area to live would be. I included parks, urban areas, Browns Beach, fire occurrences, interstand and highways so that the viewer would have a better understanding on why the results are located in the area that they are. I also included a locater map so that one can see where Saint Croix County is located in the state of Wisconsin.
Figure 2: Map of the best area to live within Saint Croix County
Evaluation:
I really enjoyed completing this project overall. It was nice to be able to use the information I learned throughout this course to complete a map on my own spatial question. If I were to repeat this project again, I would have liked to be able to use other data as well like where certain restaurants were located or where hiking trails are. I think I would be able to access this data in the future when I know how to download alternate data correctly. The biggest challenge I faced throughout this process was probably just trying to stay organized. I wrote down each step to make sure I wouldn't forget anything when trying to describe my methods. I also constructed the data flow model in my notes as I went to make it easier to complete in Microsoft Word. I am very pleased with how this project turned out because it was nice to be able to put my own project together and produce a map of the results that reflected my criteria.
Sources:
ArcGIS Data
Wisconsin DNR
Esri-GIS Mapping, Software, Solutions, Services, Maps, and Data.
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