Hyperspectral remote sensing of vegetation Prasad S. Thenkabail; John G. Lyon & Alfredo Huete.

By:

Thenkabail, Prasad

Contributor(s):

Material type: Text

TextLanguage: English Publication details: Boca Raton, FL: CRC Press, 2012.Edition: 17Description: xxxv, 705 pages: illustrations (some color), maps (some color); 27 cmISBN:

9781439845370

Subject(s):

DDC classification:

581.7 THE

Contents:

pt. 1. Introduction and overview pt. 2. Hyperspectral sensor systems pt. 3. Data mining, algorithms, indices pt. 4. Leaf and plant biophysical and biochemical properties pt. 5. Vegetation biophysical properties pt. 6. Vegetation processes and function (ET, water use, GPP, LUE, phenology) pt. 7. Species identification pt. 8. Land cover applications pt. 9. Detecting crop management, plant stress, and disease pt. 10. Hyperspectral data in global change studies pt. 11. Hyperspectral remote sensing of outer planets pt. 12. Conclusions and way forward.

Summary: The book demonstrates the experience, utility, methods and models used in studying vegetation using hyperspectral data. Written by leading experts, including pioneers in the field, each chapter presents specific applications, reviews existing state-of-the-art knowledge, highlights the advances made, and provides guidance for the appropriate use of hyperspectral data in the study of vegetation as well as its numerous applications, such as crop yield modeling, crop and vegetation biophysical and biochemical property characterization, and crop moisture assessment

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Reference Books	CUTN Central Library Reference	Reference	581.7 THE (Browse shelf(Opens below))	Not For Loan		36730

pt. 1. Introduction and overview
pt. 2. Hyperspectral sensor systems
pt. 3. Data mining, algorithms, indices
pt. 4. Leaf and plant biophysical and biochemical properties
pt. 5. Vegetation biophysical properties
pt. 6. Vegetation processes and function (ET, water use, GPP, LUE, phenology)
pt. 7. Species identification
pt. 8. Land cover applications
pt. 9. Detecting crop management, plant stress, and disease
pt. 10. Hyperspectral data in global change studies
pt. 11. Hyperspectral remote sensing of outer planets
pt. 12. Conclusions and way forward.

The book demonstrates the experience, utility, methods and models used in studying vegetation using hyperspectral data. Written by leading experts, including pioneers in the field, each chapter presents specific applications, reviews existing state-of-the-art knowledge, highlights the advances made, and provides guidance for the appropriate use of hyperspectral data in the study of vegetation as well as its numerous applications, such as crop yield modeling, crop and vegetation biophysical and biochemical property characterization, and crop moisture assessment

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