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Title: Hyperspectral Remote Sensing-Sensors and Applications

Author
item JENSEN, RYAN - BRIGHAM YOUNG UNIV, UTAH
item Yang, Chenghai

Submitted to: Manual of Remote Sensing
Publication Type: Book / Chapter
Publication Acceptance Date: 6/8/2009
Publication Date: 12/20/2009
Citation: Jensen, R.R., Yang, C. 2009. Hyperspectral remote sensing-sensors and applications. Manual of Remote Sensing. 1.1:205-224.

Interpretive Summary: This manuscript is a book chapter and doesn’t report on original research. An Interpretive Summary is not required.

Technical Abstract: Multispectral remote sensors have been traditionally used to map and monitor anthropogenic and environmental changes in the biosphere. While these sensors have proven robust for many applications, they often lack the spectral resolution necessary to differentiate characteristics of the Earth’s surface – especially when the spectral changes are very small or only occur in a very narrow region of the electromagnetic spectrum. Therefore, hyperspectral imaging systems have been developed that acquire images in many narrow wavebands throughout the visible, near-infrared, middle-infrared, and thermal infrared portions of the spectrum from both airborne and spaceborne platforms. These narrow spectral bands facilitate better discrimination among vegetation types, crops, and other earthly features. Government agencies and private companies have developed scores of hyperspectral remote sensing systems. These systems are often designed to study specific research questions, and several of the more common hyperspectral remote sensing systems are described in this chapter. A hyperspectral image contains spectral data in tens to hundreds of narrow wavebands for each pixel. How to accurately and efficiently extract the information in the image is an important issue in hyperspectral remote sensing. Although standard image processing and analytical techniques developed for broadband multispectral imagery can be used for hyperspectral imagery, a large number of techniques and methods have been developed to take advantage of the full spectral information present in hyperspectral imagery. Some of the techniques and procedures commonly-used for hyperspectral data processing and analysis are discussed in the chapter. Example hyperspectral remote sensing applications are explored.