Question

hyperspectral remote sensing

Answer 1

Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of minerals, terrestial vegetation, and man-made materials and backgrounds.

Answer 2

Answer:

Hyperspectral remote sensing is the science of acquiring digital imagery of earth materials in many narrow contiguous spectral bands. Hyperspectral sensors or imaging spectrometers measure earth materials and produce complete spectral signatures with no wavelength omissions. Such instruments are flown aboard space and air-based platforms. Handheld versions also exist and are used for accuracy assessment missions and small scale investigations.

Hyperspectral remote sensing instruments are typical with several contiguous bands in all parts of the spectrum in which they operate. Digital Airborne Imaging Spectrometer, for example, is hyperspectral, having 63 bands, 27 in the visible, and near infra-red (0.4-1.0 microns), two in the short wave infrared (1.0-1.6 microns), 28 in the short wave infrared important for mapping clay minerals (2.0-2.5 microns), and 6 in the thermal infrared. The ability to measure reflectance in several contiguous bands across a specific part of the spectrum allows these instruments to produce a spectral curve that can be compared to reference spectra for any number of minerals, thereby allowing the mineral content of a particular piece of ground to be determined.

Explanation:

Hyperspectral remote sensing involves breaking a broadband from the visible and infra-red into hundreds of spectral parts, which allows a very precise match of ground characteristics, such as color, to the reference standards. The technique is so sensitive that it can detect camouflaged objects and has been used in forestry to measure biomass and damage caused by plant disease. Hyperspectral remote sensing combines imaging and spectroscopy in a single system, which often includes large data sets and require new processing methods. Hyperspectral data sets are generally composed of about 100 to 200 spectral bands of relatively narrow bandwidths (5-10 nm), whereas, multispectral data sets are usually composed of about 5 to 10 bands of relatively large bandwidths.