How to Interpret a Satellite Image:
Five Tips and Strategies

By Holli Riebeek Design by Robert Simmon November 18, 2013

Satellite images are like maps: they are full of useful and interesting information, provided you have a key. They can show us how much a city has changed, how well our crops are growing, where a fire is burning, or when a storm is coming. To unlock the rich information in a satellite image, you need to:

  1. Look for a scale
  2. Look for patterns, shapes, and textures
  3. Define the colors (including shadows)
  4. Find north
  5. Consider your prior knowledge

These tips come from the Earth Observatory’s writers and visualizers, who use them to interpret images daily. They will help you get oriented enough to pull valuable information out of satellite images.

Look for a Scale

One of the first things people want to do when they look at a satellite image is identify the places that are familiar to them: their home, school, or place of business; a favorite park or tourist attraction; or a natural feature like a lake, river, or mountain ridge. Some images from military or commercial satellites are detailed enough to show many of these things. Such satellites zoom in on small areas to collect fine details down to the scale of individual houses or cars. In the process, they usually sacrifice the big picture.

High-resolution satellite view of the Boulder water treatment plant.
Full-resolution Landsat image of the Platte River and Boulder, Colorado.

Images from the commercial WorldView-2 satellite (top) can show street by street details of the September 2013 flood in Boulder, Colorado, while the scientific Landsat 8 satellite (lower) can be zoomed in to give a city size scale. (Worldview-2 image based on data ©2013 DigitalGlobe. Landsat image by Jesse Allen and Robert Simmon, using data from the USGS Earth Explorer.)

NASA satellites take the opposite approach. Earth science researchers typically want a wide-angle lens to see whole ecosystems or atmospheric fronts. As a result, NASA images are less detailed but cover a wider area, ranging from the landscape scale (185 kilometers across) to an entire hemisphere. The level of detail depends on the satellite’s spatial resolution. Like digital photographs, satellite images are made up of little dots called pixels. The width of each pixel is the satellite’s spatial resolution.

Commercial satellites have a spatial resolution down to 50 centimeters per pixel. The most detailed NASA images show 10 meters in each pixel. Geostationary weather satellites, which observe a whole hemisphere at a time, are much less detailed, seeing one to four kilometers in a pixel.

Full MODIS scene of Boulder, Colorado and the central United States.

Raw Landsat scenes (top) provide a landscape view, while MODIS (lower) provides a wider view. The images are from September 17 (Landsat) and September 14 (MODIS), 2013. (Landsat image by Jesse Allen and Robert Simmon, using data from the USGS Earth Explorer. MODIS image by Jeff Schmaltz LANCE/EOSDIS MODIS Rapid Response Team, GSFC.)

Depending on the image resolution, a city may fill an entire satellite image with grids of streets or it may be a mere dot on a landscape. Before you begin to interpret an image, it helps to know what the scale is. Does the image cover 1 kilometer or 100? What level of detail is shown? Images published on the Earth Observatory include a scale.

You can learn different things at each scale. For example, when tracking a flood, a detailed, high-resolution view will show which homes and businesses are surrounded by water. The wider landscape view shows which parts of the county or metropolitan area are flooded and perhaps where the water is coming from. A broader view would show the entire region—the flooded river system or the mountain ranges and valleys that control the flow. A hemispheric view would show the movement of weather systems connected to the floods.


GOES satellites offer a nearly full view of the Earth’s disk. This image shows North and South America on September 14, 2013. (Image by the NASA/NOAA GOES Project Science Office.)

Look for patterns, shapes, and textures

If you have ever spent an afternoon identifying animals and other shapes in the clouds, you’ll know that humans are very good at finding patterns. This skill is useful in interpreting satellite imagery because distinctive patterns can be matched to external maps to identify key features.

Bodies of water—rivers, lakes, and oceans—are often the simplest features to identify because they tend to have unique shapes and they show up on maps.

Other obvious patterns come from the way people use the land. Farms usually have geometric shapes—circles or rectangles—that stand out against the more random patterns seen in nature. When people cut down a forest, the clearing is often square or has a series of herring-bone lines that form along roads. A straight line anywhere in an image is almost certainly human-made, and may be a road, a canal, or some kind of boundary made visible by land use.

Satellite image of Reese Michigan and the surrounding fields.

Straight lines and geometric shapes in this image of Reese, Michigan, are a result of human land use. Roads cut diagonally across the squares that define farm fields. (NASA Earth Observatory image by Jesse Allen and Robert Simmon, using ALI data from the NASA EO-1 team.)

Geology shapes the landscape in ways that are often easier to see in a satellite image. Volcanoes and craters are circular, and mountain ranges tend to run in long, sometimes wavy lines. Geologic features create visible textures. Canyons are squiggly lines framed by shadows. Mountains look like wrinkles or bumps.

These features can also affect clouds by influencing the flow of air in the atmosphere. Mountains force air up, where it cools and forms clouds. Islands create turbulence that results in swirling vortices or wakes in the clouds. When you see a line of clouds or vortices, they provide a clue about the topography of the land below.

South American ocean, forest, mountains, and plains.

Central Chile and Argentina offer a wide range of geographic features, including snow-covered mountains, canyons, and volcanoes. (NASA image courtesy Jeff Schmaltz LANCE/EOSDIS MODIS Rapid Response Team, GSFC.)

Occasionally, shadows can make it hard to tell the difference between mountains and canyons. This optical illusion is called relief inversion. It happens because most of us expect an image to be lit from the top left corner. When the sunlight comes from another angle (especially from the lower edge), the shadows fall in ways we don’t expect and our brains turn valleys into mountains to compensate. The problem is usually resolved by rotating the image so the light appears to come from the top of the image.

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