Hyperspectral Remote Sensing of Vegetation

Hyperspectral narrow-band (or imaging spectroscopy) spectral data are fast emerging as practical solutions in modeling and mapping vegetation. Recent research has demonstrated the advances in and merit of hyperspectral data in a range of applications including quantifying agricultural crops, modelin...

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Bibliographic Details
Main Authors Thenkabail, Prasad Srinivasa, Lyon, John Grimson, Huete, Alfredo
Format eBook Book
LanguageEnglish
Published Boca Raton CRC Press 2012
CRC Press, an imprint of Taylor & Francis
CRC Press LLC
Edition1
Subjects
Crops
Crops > Remote sensing
Multispectral imaging
Multispectral photography
Plants
Plants > Remote sensing
Remote sensing
Vegetation monitoring
Red Edge NDVI
Spectral Bands
Hyperspectral Image Data
HS Imagery
Hyperspectral Sensor
Red Edge
PLSR Model
NPV
Vegetation Water Content
Spectral Indices
Hyperspectral Data
Red Edge Bands
Hyperspectral Remote Sensing
HSI
Pixel Vector
Vegetation Index
Redundant Bands
Hyperspectral Vegetation Indices
SMA
NDWI
Lidar Data
Rt Model
Leaf Chlorophyll Content
Rep
Chlorophyll Content
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Table of Contents:
  • Front Cover -- Contents -- Foreword -- Preface -- Acknowledgments -- Editors -- List of Acronyms and Abbreviations -- Contributors -- Chapter 1: Advances in Hyperspectral Remote Sensing of Vegetation and Agricultural Croplands -- Chapter 2: Hyperspectral Sensor Characteristics: Airborne, Spaceborne, Hand-Held, and Truck-Mounted -- Integration of Hyperspectral Data with LIDAR -- Chapter 3: Hyperspectral Remote Sensing in Global Change Studies -- Chapter 4: Hyperspectral Data Mining -- Chapter 5: Hyperspectral Data Processing Algorithms -- Chapter 6: Nondestructive Estimation of Foliar Pigment (Chlorophylls, Carotenoids, and Anthocyanins) Contents: Evaluating a Semianalytical Three-Band Model -- Chapter 7: Forest Leaf Chlorophyll Study Using Hyperspectral Remote Sensing -- Chapter 8: Estimating Leaf Nitrogen Concentration (LNC) of Cereal Crops with Hyperspectral Data -- Chapter 9: Characterization on Pastures Using Field and Imaging Spectrometers -- Chapter 10: Optical Remote Sensing of Vegetation Water Content -- Chapter 11: Estimation of Nitrogen Content in Crops and Pastures Using Hyperspectral Vegetation Indices -- Chapter 12: Spectral Bioindicators of Photosynthetic Efficiency and Vegetation Stress -- Chapter 13: Spectral and Spatial Methods of Hyperspectral Image Analysis for Estimation of Biophysical and Biochemical Properties of Agricultural Crops -- Chapter 14: Hyperspectral Vegetation Indices -- Chapter 15: Remote Sensing Estimation of Crop Biophysical Characteristics at Various Scales -- Chapter 16: Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems -- Chapter 17: Crop Type Discrimination Using Hyperspectral Data -- Chapter 18: Identification of Canopy Species in Tropical Forests Using Hyperspectral Data
  • Chapter 19: Detecting and Mapping Invasive Plant Species by Using Hyperspectral Data -- Chapter 20: Hyperspectral Remote Sensing for Forest Management -- Chapter 21: Hyperspectral Remote Sensing of Wetland Vegetation -- Chapter 22: Characterization of Soil Properties Using Reflectance Spectroscopy -- Chapter 23: Analysis of the Effects of Heavy Metals on Vegetation Hyperspectral Reflectance Properties -- Chapter 24: Hyperspectral Narrowbands and Their Indices on Assessing Nitrogen Contents of Cotton Crop Applications -- Chapter 25: Using Hyperspectral Data in Precision Farming Applications -- Chapter 26: Hyperspectral Data in Long-Term, Cross-Sensor Continuity Studies -- Chapter 27: Hyperspectral Analysis of Rocky Surfaces on the Earth and Other Planetary Bodies -- Chapter 28: Hyperspectral Remote Sensing of Vegetation and Agricultural Crops: Knowledge Gain and Knowledge Gap After 40 Years of Research -- Back Cover