What Is GIS and What Can You Do With It?

GIS (geographic information system) is software and a way of organizing data that links information to locations on the earth, so you can make maps and answer spatial questions—for example, which areas are within a certain distance of a feature, or how one layer of data overlaps another. You can start with free, public data and a free or low-cost desktop tool; the main requirements are a clear question, data that covers your area, and a way to check that your map is accurate.

The core idea: layers plus location

GIS combines two kinds of information:

• Spatial data — where something is (points, lines, polygons, or pixels on a grid).
• Attribute data — what it is (names, measurements, dates, categories).

Each theme is stored as a layer. A simple project might stack a boundary layer, a roads layer, and a points layer for sample sites. Turning layers on and off, and comparing them, is the basic operation behind most GIS analysis.

Vector vs. raster

Coordinate systems

Every layer needs a coordinate reference system so locations line up. If two layers appear offset or stretched when combined, a mismatched coordinate system is a common cause. Check the CRS of each layer before you analyze or measure distances.

What you can do with GIS

Common tasks include:

• Map making — produce a printable or shareable map of a study area.
• Overlay and proximity analysis — find features inside a boundary, or within a set distance of something.
• Resource and land-use planning — combine geology, water, and land layers to see where themes coincide.
• Change over time — compare layers from different dates.
• Data QA — spot gaps, duplicates, or misplaced records by plotting them.

For a first project, pick one question you can answer with two or three layers. A concrete example: "Which sample sites fall inside the mapped boundary, and how far is each from the nearest road?" That requires a boundary polygon, a points layer, and a roads layer—enough to practice loading data, setting the CRS, and running a spatial query.

How to start your first GIS project

1. State the question and the output. Decide whether you need a map, a table of results, or both. This determines which layers you need.
2. Collect data. Look for public geospatial data from government agencies and open data portals. State geological surveys, for instance, publish maps and spatial data alongside their publications; the Wyoming State Geological Survey lists an Interactive Maps section and a Mapping Program among its resources, and its site notes that it has moved to main.wsgs.wyo.gov. Confirm the current address and data-download terms on the agency's site before relying on a dataset.
3. Choose a tool. Desktop GIS packages (including free and open-source options) handle layers, coordinate systems, and analysis; web-based mapping tools are quicker for simple display. Match the tool to your question rather than the other way around.
4. Load and check each layer. Verify the CRS, the extent (does it cover your area?), and the attributes (are values in the units you expect?).
5. Run the analysis. Use overlay or proximity tools, then inspect the result rather than trusting it blindly.
6. Make the map. Add a legend, scale bar, north arrow, source credits, and date. Label only what the question needs.
7. Verify. Spot-check a few results against the source data, and note any gaps or assumptions.

Common sticking points

• Layers don't line up — usually a coordinate system mismatch; reproject to a common CRS.
• Missing or incomplete data — check the layer's extent and date; public datasets often cover only part of an area.
• Units differ — confirm whether distances are in meters, feet, or degrees before measuring.
• Overplotting — too many layers obscure the message; keep only what answers the question.

Choosing data and tools by need

Public agency data is a practical starting point because it often comes with documentation, but availability, formats, and any access conditions vary by agency—verify them at the source rather than assuming a dataset is complete or unrestricted.