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Satellite imagery

An overview of how satellite imagery is created.

An imaging satellite works in a similar way to a digital camera. Light from the sun is reflected by the Earth and so travels back into space to pass into the satellite’s instruments. The sensors detect the level of red, green and blue light, this is recorded individually for each pixel and this data is transmitted back to Earth along with extra metadata about the image, such as the time and the position of the satellite.

How satellite imagery is created A simplified representation of how satellites produce natural-looking imagery. Courtesy of William Deadman.

Spatial resolution

The spatial resolution of satellite imagery varies considerably, depending on the number of sensors in a satellite’s instruments. Satellite imagery with different resolutions is designed for different applications – imagery is not necessarily better if it has a higher resolution!

A high-resolution true colour image contains more pixels for the same area compared to a low-resolution image – this means that it will usually need more space to store on a computer or server and will take more time to analyse. It is advisable to use the lowest resolution imagery necessary to carry out your specific task. Although it sounds great, a scientist studying the Amazon rainforest would not want imagery of the whole area with 1 metre by 1 metre pixels – this would amount to over 5 trillion pixels!

A rough guide to the pixel size in high-, medium- and low-resolution satellite imagery is provided in the table below, as well as a reasonable indication of the sort of coverage they would usefully provide and an example application.

Resolution Pixel Size Reasonable Coverage Example Application
Low 60m or more Small country to whole Earth Tracking weather systems
Medium 10m to 30m Large city to small country Mapping coastal erosion
High sub-metre to 3m Individual building to large city Personal navigation
In Step 2.1 we explored how digital images work, and how pixels make up an image. Spatial resolution of satellite imagery refers to the pixel size, or the area of terrain represented by one pixel. So, in an image with a pixel size of 60 metres, a pixel summarises an area of 60 by 60 metres.
Many satellites can also collect panchromatic (black-and-white) images at a higher resolution than for RGB data. This can be used to sharpen the colour imagery later and reduces the total amount of data that needs to be collected.
Can you think of any other applications of low, medium and high-resolution satellite imagery that we haven’t mentioned?

Temporal resolution

So far, we have only discussed spatial resolution, but temporal resolution is also very important. Temporal resolution refers to the time between available satellite images for the same location. This simply relates to how frequently the satellite concerned passes over a particular point on the Earth’s surface, and so is related to the orbit of that particular device. Publicly available, medium-resolution satellite imagery collected by NASA and ESA (the European Space Agency) is available every two to ten days for the same location.

Getting this level of temporal resolution for high-resolution imagery would almost certainly cost a considerable amount of money, as high-resolution data generally needs to be obtained from a supplier of commercial satellite imagery.

When working with satellite imagery it is also important to consider the date range for which imagery is available or accessible. It may sound obvious, but imagery will only be available from after the date at which the relevant satellite was placed into orbit! Moreover, all satellites have a finite lifespan, and so they will also have an end date if data collection is not ongoing.

There are some free sources of high resolution imagery, but generally only data from older satellites is included and so very recent imagery (from the last few years) is not made available. It is sometimes possible to obtain high-resolution, recent imagery, but this is usually only released for small, specific areas, often to cover crisis events – for example Maxar’s Open Data Program.

In this course, we are going to be working with several different sources of free imagery. A guide to their spatial and temporal resolutions is provided in the table below.

Satellite(s) Operator Resolution Date Revisit
Landsat 1-4 NASA 30-60m 1972-1993 9-18 days
Landsat 5 NASA 30m 1984-2013 16 days
Landsat 7 NASA 15m 1999- 16 days
Landsat 8-9 NASA 15m 2013- 8 days
Sentinel-2 ESA 10m 2015- 2-10 days
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