In this article, we will go over some basic terminology you are likely to find throughout our documentation and application and review some introductory concepts related to Earth observation and satellite data. If you are already familiar with these concepts, feel free to skip this section.
Remote-sensing is the acquisition of information about an object or phenomenon without making physical contact with the object. Most often remote-sensed data refers to data collected by sensors on-board aircrafts and satellites.
Open and commercial data
Thanks to the efforts of many governments, space agencies, and scientists, troves of satellite data have been made available to the public for free through programs such as Landsat (operated by NASA), the Earth Observation System (operated by NASA), and the Copernicus program (operated by ESA).
Data collected by the satellites from these programs is free-to-use (in accordance to the rules and regulations of the programs) and are often referred to as "open data", or "free data".
By contrast, data collected by commercial satellite operators are called "commercial data", and occasionally "high-resolution data", as the data collected offer a much finer resolution than open data. Currently, the finest available resolution through open data is 10 m, while most commercial operators offer sub-meter resolutions. Due to regulations, the finest resolution available for non-military use is 30 cm.
Most often, when talking about Earth observation data, resolution means spatial resolution.
Spatial resolution is the size of one pixel on the ground. Pixel stands for 'picture element' – the smallest individual 'block' that makes up the image. With a finer spatial resolution, 30 cm for example – where each pixel represents a 30 x 30 cm area, for optical data – you would be able to distinguish details, such as houses or cars. With a coarser resolution, an image of a similar digital size would cover a much larger surface on Earth and smaller features become harder to distinguish.
Note: The above definition only applies to optical data. Synthetic aperture radar data (SAR) is not acquired at nadir like optical data but rather on a slant. Therefore the data is in slant range and the pixels on the ground are not square.
To learn more about resolution, you can read our guide: What resolution do I need when using satellite Earth observation data.
Satellite sensors record electromagnetic energy across narrow bands of the spectrum and send back a radiance value between 0 (no energy recorded) and 255 (maximum amount of energy recorded). On a digital image, all 0 values will appear as black pixels and all 255 values as white pixels.
The electromagnetic spectrum ranges from the shorter wavelengths (including gamma and x-rays) to the longer wavelengths (including microwaves and broadcast radio waves). There are several regions of the electromagnetic spectrum which are useful for remote sensing, including the visible light spectrum, infrared, and near-infrared. Radar bands are also widely used by SAR satellites.
Satellites indicate which bands of the electromagnetic spectrum data was recorded for by the on-board sensors. By combining data from several bands together, scientists can highlight different features in the scene captured based on their spectral signature.
Optical, thermal, radar (SAR)
Depending on which bands are recorded, the information displayed will be different. Data recorded within the visible light spectrum are referred to as optical data. Most satellites carrying optical sensors also carry sensors capable of recording infrared and near-infrared values, since they are frequently used in conjunction with data from the red, green, blue, and panchromatic bands.
Thermal data is data recorded within the 10-12.5 micrometer range. In the thermal bands, dark pixels represent cool temperatures and light pixels represent hot temperatures. Thermal band data provide important information about water irrigation use in arid land, as well as heat units in urban areas.
Synthetic-aperture radar (SAR) satellites are equipped with radio transmitters and sensors to record the bounced back signals. They provide high-resolution, day-and-night and weather-independent images for a multitude of applications ranging from geoscience and climate change research, environmental and Earth system monitoring, 2-D and 3-D mapping, change detection, 4-D mapping (space and time), security-related applications up to planetary exploration. Radar satellites are particularly well-suited for surveillance of vast lands with limited above-ground distinct features, such as glaciers and deserts. It is also used extensively for areas optical satellites have trouble covering, such as cloud-covered areas, or areas shrouded in darkness, as radars can penetrate through clouds and do not need sunlight to illuminate the scenes they are capturing.
Multispectral and hyperspectral
Multispectral sensors can capture data in several spectral bands, with some sensors recording up to 10 different bands. Hyper-spectral sensors however record data in much narrower spectral bands, allowing us to focus our attention in very small specific parts of the electromagnetic spectrum. Some hyperspectral sensors can record data in over a thousand different bands.