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).

Orbits and pointing

As an example of a typical optical Earth observation orbit, let’s take Landsat 9’s parameters from Wikipedia:

• Regime: Sun-synchronous orbit. This means the orbit is designed to always pass overhead at about the same local solar time. Put another way, any two Landsat 9 images of a given spot at a given time of year will have the same angle of sunlight on the surface, and the same angle between the surface and the sensor. Specifically, it always crosses the equator on its southbound half-orbit at 10:00 (and, therefore, on its northbound half-orbit at 22:00). This mid-morning window is the sweet spot for most optical imaging purposes. In most climates where cumulus clouds are common, they generally form around midday as the mixed layer rises. It’s also claimed that this is the heritage of cold war IMINT workers wanting shadows to estimate structure heights. (If you image around noon, you get places with vertical shadows in the tropics. This gives you depth perception problems, like you get walking though brush with a headlamp instead of a hand-held flashlight. Citation needed, though.) Virtually all commercial satellite imagery that you see on commercial maps has shadows that point west and away from the equator – in fact, as of 2022, this is so consistent that if you see a shadow pointing a different direction, it’s a good hint that the imagery is actually aerial (taken from a plane/UAV/balloon inside the atmosphere), not satellite.

• Altitude: 705 km (438 mi). This is basically chosen to be as close to the surface as reasonably possible without grazing the atmosphere enough to perturb the orbit. It is substantially higher than the International Space Station, for example, but ISS has to constantly boost itself back up and that’s expensive. (ISS does occasionally underfly imaging satellites.) For comparison, if Earth were the size of a 30 cm (12 inch) desktop globe, Landsat 9’s orbit would be at 17 mm (2/3 inch) – grazing your knuckles if you held the globe like a basketball. (Developing some intuition about this relative size can help understand the practicalities of things like off-nadir imaging.)

• Inclination: 98.2°. This is the angle at which the satellite crosses the equator. It makes the orbit slightly retrograde, which is part of the equation for staying sun-synchronous. A consequence is that although orbits like this one are sometimes called polar in a loose sense, they never exactly cross the pole – Landsat 9 always misses the south pole on its left and the north pole on its right. This leaves two relatively small polar gaps that are never imaged.

• Period: 99.0 minutes. This is the time it takes to do one full orbit. This is another variable constrained by the requirements of syn-synchrony and the lowest reasonable altitude.

• Repeat interval: 16 days. Every 16 days, Landsat 9 is in exactly the same spot relative to Earth (± very small deflections due to space weather, micrometeorites, tides, maneuvers to avoid debris, etc.) and takes an image that can be exactly co-registered with the previous cycle’s. Furthermore, pairs (or mini-constellations) like Landsat 8 and 9 or Sentinel-2A and 2B are in identical orbits but half-phased such that, from a data user’s perspective, they act like a single satellite with half the repeat time. (Specifically, 8 days for Landsat 8/9 and 5 days for Sentinel-2A/B.) More or less by definition, constellations are designed to fill in each other’s gaps; for example, the wide-swath, low-resolution MODIS instruments are on a pair of satellites with near-daily coverage, but one mid-morning and the other mid-afternoon.

We used Landsat 9 here because it’s familiar to most people in the industry and is well documented. Other imaging satellites will have different sets of capabilities and constraints. For example, the Landsat series is on-nadir (looking straight down) more than 99% of the time. It only rolls to the side to look away from its ground track for exceptional events, e.g., major volcanic eruptions. But a high-res commercial satellite, e.g., in the Airbus Pléiades or Maxar WorldView constellations, is constantly looking off-nadir. One of these satellites might point its optics in easily half a dozen directions on a given orbit, and would only very rarely happen to look straight down.

Commercial users typically want images that are on-nadir and settle for images less than about 30° off-nadir. Around that angle, atmospheric and terrain correction starts getting hard, tall things are seen from the side as well as from above and block whatever’s behind them (an effect called layover), and the practical utility of imagery falls off for most purposes. But the area within 30° of nadir is quite large: about 400 km or 250 mi wide, according to some light trig.

High-resolution commercial satellites schedule collections in a process called tasking (as in “Tokyo is tasked for tomorrow”). This is in contrast to the survey mode collection used by Landsat, Sentinel, etc., which are essentially always collecting when they’re over land.