In the first half of this weeks lab, we were introduced to spatial analysis. We were led through a module where we were shown the proper order of operations for spatial analysis problem solving and then instructed to perform several analyses on the relationship of certain spatial data in Escambia county Florida. These analyses are deemed queries, which, in essence, are logical statements that define the comparative relationships between datasets. One of these was a location query, where we found how many specific parcels of land where within a certain distance from several variables i.e. schools. We also exercised a spatial join, which is a different type of query. Here we were able to combine two data sets and combine certain areas of the features to solve a problem. For instance, part of the lab was us identifying how many pollutant risk features (points) were inside drainage basins (polygons). We joined the data and were able to represent, in a new layer, all of the pollutant risk features that reside within a drainage basin. In addition, we also learned how to create a geodatabase and change our default geodatabase.
The second part of our lab was more involved. Here, we created the map featured in this post. Our goal was to find a suitable campsite within De Soto National Forest that was a certain distance from roads, water features, and excluded land that was an off-limits conservation area. In this lab we learned to use the Union tool. With a union, you are able to, like in the first half of the lab, join two feature classes (vector data). You can ascribe the numerical value of one to a unique field in their attributes and then Union the feature layers. This combines the data and areas where they overlap (areas both representing a numerical value of one). You can then manipulate the data to isolate areas that may exclude the unioned regions. The areas that are not sharing the numerical value of one from each data set are represented with a zero. You can then select attributes with this zero value and export them as their own layer. We also learned to create buffers, here you can create and equidistant area around certain features, it can be solid or stratified, indicating a unique value for each of the nested buffers.
In my map, I showed the areas that you are not going to want to camp in, which are too close to roads and too close to waterways. I decided to include the conservation areas in my map, even though they are removed from areas where we had road and water feature buffer overlap. I figured if I was finding a suitable place to camp, I would want a map that prevented me from stumbling into these areas. I created a simple scale, a map I retrieved from the state of Mississippi website showing the county boundaries for the state where I overlaid the boundary for De Soto National Forest (found through Google from the USDA Forest Service).
In the map itself, areas within road and water buffers were communicated with polygons and I chose to code them by size (measured in hectares). This way we know the area of these regions. I chose a warm yet dull color symbology for them. The colors stood out but weren't blinding like many of the other options. My biggest issue, outside of the logical arithmetic of choosing how to exclude certain data from an attribute table, was I lost the names of the roads.
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