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SeligSIM Assignment 1
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X-Plane Assignment 1
Lab 07 - X-Plane Simulator
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Week 4

The goal of Lab 6 was to practice working with common digital datasets and learn how to bring in both downloaded and provided data into ArcGIS Pro. This lab also focused on building skills that show up constantly in GIS projects, like selecting features, exporting subsets, changing projections, adjusting symbology, and editing attribute tables. By the end of the lab, I produced five separate maps that each used a different type of data and workflow.
For Map 1, I worked with the National Map cities dataset. I added the provided cities shapefile into ArcGIS Pro and zoomed to Kodiak Island. Because the layer was originally in geographic coordinates, I changed the map projection to Alaska State Plane NAD83 2011 Zone 5 in US feet so the map displayed properly and did not look stretched near the poles. I then used the lasso selection tool to manually select only the cities on Kodiak Island and exported the selected points into a new feature class. After removing the original nationwide layer, I labeled the selected cities and adjusted label placement and text styling so the names were clear. I finished by creating a clean layout with the basemap and exporting the map as a PDF.
For Map 2, I created a population density map using the cen_StX_U83 block group dataset. I opened the attribute table and explored the pden_psqkm field to understand the range and distribution. Viewing statistics showed a long tailed pattern, which explained why default symbology looked uneven. I symbolized the data with graduated colors using geometric interval classification and increased the number of classes so the density patterns were easier to see. To improve readability, I removed polygon outlines so small block groups were not hidden by borders. I then added the US_cities layer and used Select by Location to select only cities that fell within the census study area. I exported those selected cities into a new shapefile and created a layout showing both the density polygons and the city points.
For Map 3, I used county level census data and practiced data cleanup. I added the county shapefile, manually selected only the lower 48 states using a rectangle selection, and exported the selection into a new layer. The table contained many unnecessary DP fields, so I used the Delete Field geoprocessing tool to remove most columns while keeping the ObjectID, Shape, NAMELSAD10, and DP0010001 fields. After switching the coordinate system to NAD83 Contiguous USA Albers, I created a graduated symbol map based on county population. I adjusted the symbol size range and then manually increased the largest symbol size to better represent the extreme difference between low and high population counties.
For Map 4, I created a shaded relief and hydrography map. I added watershed boundaries, fixed labels by using the SUBBASIN field, and exported just the Lower St. Croix watershed for context. I then added the DEM and displayed it with a stretched color ramp using standard deviations. After running the Hillshade tool, I adjusted hillshade transparency so both elevation color and terrain shading were visible. Finally, I added NHD waterbodies and flowlines, symbolized them using unique values, and cleaned up the legend by removing unused categories.
For Map 5, I worked with wetlands data and focused on table manipulation. I added a new text field called Size and used manual selections with Calculate Field to assign classes based on polygon area. I created categories for Small, Medium, and Large wetlands, then labeled upland polygons as Upland and assigned the OUT polygons as Wisconsin. After verifying that values were not overwritten, I symbolized the wetlands layer using unique values based on the Size field and created the final layout.
Overall, this lab helped me get more comfortable using real datasets and showed how much time GIS work involves organizing data and making it usable. The selection tools, exporting subsets, and field calculations were especially useful since they are workflows that apply to almost every GIS project. Making five different maps also helped me practice consistent layout design while still adjusting symbology and projections to match each dataset.
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