What Is Hyperspectral Remote Sensing?

High-resolution remote sensing is a technique for continuous remote sensing imaging of ground features using very narrow and continuous spectral channels. In the visible light to short-wave infrared bands, the spectral resolution is as high as the order of nanometers (nm). It usually has many bands, and the number of spectral channels is up to tens or even hundreds, and the spectral channels are often continuous, so the hyperspectral Remote sensing is often called imaging spectral remote sensing.

The emergence and application of Hyperspectral Remote Sensing has more than two decades of history. It is in

Compared with traditional remote sensing technology with low spectral resolution, hyperspectral remote sensing provides a wider range of applications in ground observation and environmental surveys, mainly in the following aspects:

1) The ability of distinguishing and recognizing features is greatly improved, and different types of features belonging to the same type can be distinguished, which is not easy to achieve in traditional low-spectral-resolution remote sensing. At the same time, due to the narrowing of the imaging spectrum band and the increase in the number of imaging channels that can be selected, the phenomenon of "foreign matter in the same spectrum" and "same spectrum foreign matter" is reduced. The phenomenon can be greatly controlled, which undoubtedly provides the most reliable guarantee for further analysis.

2) The imaging channels are greatly increased, making the selectivity of the spectrum flexible and diverse in the analysis of different applications. This greatly increases the number of targets that can be analyzed by remote sensing, such as those of different tree species. Identification, identification of different minerals, expands the scope of application of remote sensing technology.

3) Due to the improvement of spectral spatial resolution, applications that were previously impossible are possible, such as the extraction of biophysical and chemical parameters, and the use of hyperspectral data for biochemical analysis of vegetation chlorophyll a, lignin, cellulose, etc. Good results provide a new research direction for the application of remote sensing technology.

4) It is possible to transform from qualitative analysis of remote sensing to quantitative or semi-quantitative. The main application of traditional imaging remote sensing technology is qualitative analysis. The accuracy of some quantitative analysis results is not ideal. This is obviously due to the spectrum of the imaging sensor It is related to the limitations of spatial resolution, interference of the atmosphere and soil background. Hyperspectral resolution imaging remote sensing first broke through the limitation of spectral resolution, and greatly suppressed the influence of other interference factors in the spectral space. The improved accuracy of the results has greatly helped ^[2]

Hyperspectral remote sensing is currently

United States: AIS, AVIRIS, WIS (812 band), PROBE, TEEMS, MODIS, Hyperion, FTHSIAHI (256 thermal bands), SEBASS (242 thermal bands)

· Australia: Hymap, ARIES, TIPS (100 thermal bands)

· Canada: CAS

· Germany: ROSIS

· France: IMS

· Finland: AISA

· ESA: CHRIS (PROBA Small Satellite, October 22, 2000)

· Japan: GLI

· China: MAIS, PHI, OMIS-1 (10 thermal bands), CMODIS (Shenzhou III), Env-DD (small satellite for environmental disasters)