Satellite image data concepts

This page provides an organized list of ideas useful for understanding image data from satellites. It is intended for people with some background or practical knowledge who want to fill in the gaps. Since many concepts are intrinsically cross-cutting, they can’t be forced into a single perfectly hierarchical taxonomy; the goal is merely to keep related ideas reasonably near each other.

We might divide up the kinds of knowledge it’s useful to have when working with satellite data like this:

Layers of abstraction in remote sensing knowledge

Practice	This page	Theory
Learning how to answer questions by actually using data in Photoshop, QGIS, numpy, etc.	Learning technical vocabulary and concepts that apply across sources	Learning rigorously defined principles based in physics, geostatistics, etc.

All of these kinds of knowledge are important to an OSINT practitioner. This page only covers the middle range – ideas that are more abstract than what you can learn from the pixels themselves, but less abstract than what you would get in a higher-level college course.

Within those bounds, the organizational arc here is broadly from the more abstract (orbits) through the relatively concrete (how sensors work) to the practical (what a geotiff is).