TerrAlert Team · 2026-09-09
Geospatial data is any information that is tied to a specific place on Earth. A weather reading is geospatial data if it says where it was taken. A satellite image is geospatial data because every pixel corresponds to a real location. Once you see it that way, the field stops sounding exotic. It is just data with a location attached, plus the tools to work with that location meaningfully.
Coordinates. The simplest geospatial fact is a single point: a latitude and longitude, like 40.7128° N, 74.0060° W (New York City). Latitude measures north-south position, longitude measures east-west position, and together they pin down one point on the globe.
Polygons. Most real monitoring is not about a single point but an area, a farm, a forest concession, a construction site. A polygon is a shape defined by a list of coordinate points connected in order, closing back to the start. Drawing a boundary around "the property I want to watch" on a map produces exactly this: a polygon.
Pixels. A satellite image is a grid of pixels, and, critically, each pixel is georeferenced, meaning the system knows exactly which real-world coordinates that pixel corresponds to. This is what lets software compare "this pixel in this week's image" against "the same real-world spot in last week's image," even if the satellite approached from a slightly different angle each time.
Layers. Geospatial tools commonly show multiple kinds of data stacked on the same map: imagery as a base layer, a boundary polygon on top, detected changes highlighted on top of that. Each layer is independent data that happens to share the same coordinate system, which is what makes stacking them meaningful instead of arbitrary.
Two datasets can only be compared or overlaid correctly if they use the same coordinate reference system. Get this wrong and a boundary that should sit exactly on a property line can appear shifted by meters or more, a common and consequential mistake in geospatial work. This is a big part of why building reliable geospatial software takes real engineering: getting the visuals to look plausible is easy, and getting the coordinates to actually line up correctly is the part that takes care.
GeoJSON is a widely used, human-readable text format for describing geospatial shapes, points, lines, polygons, using ordinary latitude/longitude coordinates. It looks like this for a simple rectangular area:
{ "type": "Polygon", "coordinates": [[[100.0, 0.0], [101.0, 0.0], [101.0, 1.0], [100.0, 1.0], [100.0, 0.0]]] }
Because it is plain, standardized text, GeoJSON is easy to generate programmatically, easy to inspect by eye, and works across nearly every mapping tool and geospatial API, including TerrAlert's, where an Area of Interest can be submitted as GeoJSON directly through the REST API instead of drawn by hand. For how these building blocks combine into an actual insight, see How Maps and Satellite Data Help Us Understand What Is Happening on the Ground.
Do I need to understand coordinate systems to use a monitoring tool? No. A well-built tool handles that internally. It matters if you are ever comparing data between two different tools or building your own integration.
What's the difference between a "point" and a "polygon"? A point is a single location; a polygon is a closed shape made of multiple connected points, used to describe an area rather than a single spot.
See how this fits together practically in How TerrAlert Works or the API guide.
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