Explore

Geospatial Data Sources

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1. Getting set up and finding the data

We started by setting up a new ArcGIS Pro project and copying the lab data folder to either the temp drive or an external drive. This lab follows Chapter 7 of the GIS Fundamentals textbook and focuses on learning how to download, organize, and work with real-world GIS data. Throughout the lab, we used data from sources like the USGS and the U.S. Census Bureau. We also made sure that every map included proper metadata (data source + my name) and clean, readable scale bars with rounded values.

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2. Kodiak Island map (downloading and trimming data)

First, we worked with cities data from the National Map. Since the dataset included cities from all over the U.S., we zoomed in on Kodiak Island, Alaska, and manually selected only the cities on the island. We then exported that selection as a new layer to make the dataset smaller and easier to work with. After that, we labeled the cities and created a clean map focused only on Kodiak Island, removing unnecessary background clutter.

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3. Population density map (working with census data)

Next, we looked at census block group data and explored population density values. We opened the attribute table to see how the data was distributed and noticed that most areas had low values while a few had very high values. To show this clearly, we used graduated color symbology with geometric intervals and removed polygon outlines so the colors were easier to see. We then added city locations that fell within the census area and created a layout that showed both population density and cities together.

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4. County population map (symbols and table cleanup)

In this section, we worked with county-level population data for the entire U.S. We manually selected only the lower 48 states and exported them as a new layer. Since the table had way too many columns, we deleted everything except the fields we actually needed (county name and total population). We then created a proportional symbol map using graduated circles to show population differences between counties and adjusted symbol sizes so large populations didn’t look misleading.

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5. Shaded relief and hydrography map

Here we worked with elevation (DEM) and water data. We created a shaded relief map by combining elevation colors with a hillshade layer to make terrain features stand out. Then we added rivers, streams, lakes, and canals from the National Hydrologic Dataset and symbolized them by type. Making the hillshade partially transparent helped everything blend together and look more realistic. This map was mainly about visualization and making terrain easier to understand.

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6. Wetlands map (table edits and classification)

For the final section, we worked with wetlands data and focused heavily on the attribute table. We added a new field called “Size” and manually classified wetlands as Small, Medium, or Large based on their area. We also labeled upland areas and areas outside the study region (Wisconsin). After assigning all categories, we symbolized the wetlands using unique values so each size and type was clearly visible on the map.

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