A 2-minute, no-numbers, plain-English flyover of the whole semester. Read this first.
Remote sensing is just measuring stuff from a distance. Cameras and sensors on satellites, planes, and drones look at the Earth, and we figure things out from what they see.
You learned about sensors that capture a few colors at once (most satellites β Landsat, SPOT, IKONOS), sensors that capture hundreds of very narrow colors (hyperspectral β useful for picking out specific minerals or plants), and sensors that see heat (thermal β works day or night).
Three platforms, each with their trade-offs: satellites cover huge areas but can only revisit every couple weeks, airplanes get finer detail when you need it, and drones (UAS) get centimeter-level detail but only over a small area at a time and with FAA rules to follow.
Here's the magic move at the heart of vegetation science: healthy plants absorb red light and bounce back invisible near-infrared. Compare those two and you get a "how green is this?" score (the famous NDVI). That's how scientists track deforestation, drought, crop health, and the seasons of a continent β all without ever leaving the office.
Once you have an image, you often want to label every pixel as forest, water, urban, or whatever. Two ways to do it:
π¨βπ« Supervised β you teach the computer by saying "this is forest, this is water," and it generalizes.
π€ Unsupervised β the computer finds natural groupings on its own, and you label them after.
Flying a drone for any kind of work means following FAA Part 107: stay under 400 ft, in line-of-sight, away from controlled airspace unless you've got authorization. Sectional charts are the maps that tell you which airspace class you're in, marked by line color (blue solid = busy big-airport zones, magenta = mid-size, dashed blue = small towers). Weather matters too β clouds, visibility, temperature/dewpoint spread.
The whole subject is one big toolkit: pick the right sensor, pick the right platform, do the math (or let the computer do it), and turn that into something a person can act on β a deforestation map, a crop forecast, a flood-extent estimate, a drone survey of a construction site. The exam is mostly testing whether you understand the tools and when to use which one.