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Remote sensing uses images taken from aircraft or satellites to analyze surfaces at different wavelengths. Infrared is commonly used to monitor vegetation and flooding, while radar can track clouds and ground movement. Spectrometers aid in hyperspectral imaging, and computers identify objects for analysis.
Remote sensing analysis is the interpretation of images taken from remote locations, such as aboard an aircraft or a satellite in Earth orbit. Various imaging systems can image surfaces at different wavelengths of the light spectrum. Subsequent analysis is typically used to view an image differently than the human eye can see it. In the case of remote sensing, hyperspectral imaging is sometimes part of analyzing multiple bandwidths of light in an image. Images can be viewed as a type of photograph, but digital image processing is often part of remote sensing analysis because computers can interpret the data quickly.
A common wavelength used with remote sensing is infrared. Water and vegetation are often distinguishable with the naked eye, but in cases of flooding and forest modification, visible light is sometimes not enough. An infrared image of a forest or other area of vegetation can help measure its health. Researchers can monitor deforestation over time by performing remote sensing analyzes of images taken at different times. They can also monitor the state of floodplains and even determine the potential for landslides in hilly terrain.
Radar images are often used to track clouds at night. Using radar, scientists can also perform remote sensing analyzes of ground movement to provide valuable information about earthquakes and areas of sinking. Computer programs are often capable of analyzing data from images taken at different spectral wavelengths. The same multispectral analysis can also be applied to medicine, through the imaging of biological cells and tissues to diagnose infections and diseases. Such laboratory tests can be used in combination with magnetic resonance imaging (MRI) scans and radiographs.
Instruments called spectrometers often aid in remote sensing analysis. These instruments are usually capable of hyperspectral imaging, which means bands of images are scanned at different wavelengths. Such images are characterized by their physical width and how far they extend. It is also possible to measure the reflected energy, which determines the spectral response of an object. Interpreting such data usually requires knowing how certain features radiate each wavelength of light.
Computers typically need to be able to identify objects, such as vehicles, bridges, or water, to provide adequate remote sensing analysis. Measurement techniques generally need to distinguish one object from another. With digital image processing, each pixel of the image is represented numerically as part of the automatic remote sensing analysis. Images can also be viewed on a computer screen in great detail, in both black and white and color.
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