Thenkabail P.S., Lyon J.G., Huete A. (eds.) Hyperspectral Remote Sensing of Vegetation

CRC Press, 2012. — 765 p.Over the years, I have seen a real need for a book on hyperspectral remote sensing (imaging spectroscopy) of vegetation, especially given the recent rapid advances made in imaging spectroscopy and opportunities for unique applications hitherto thought to be infeasible using broadband remote sensing. The need for a book to catalogue these knowledge advances in the study of terrestrial vegetation using hyperspectral narrowband data is of critical importance to a wide spectrum of scientific community, students, and professional application practitioners. Given this need, the goal of this book was to provide a comprehensive set of chapters documenting knowledge advances made in applying hyperspectral remote sensing technology in the study of terrestrial vegetation. This is a very practical offering about a complex subject that is rapidly advancing its knowledge-base and practical utility in wide array of applications. In a very practical way, the book demonstrates the experience, utility, methods, and models used in studying vegetation using hyperspectral data. Written by leading experts in the global arena, each chapter (a) focuses on specific applications, (b) reviews “state-of-the-art” knowledge, (c) highlights the advances made, and (d) provides guidance for appropriate use of hyperspectral (or imaging spectroscopy) data in the study of vegetation such as crop yield modeling, crop biophysical and biochemical property characterization, crop moisture assessment, species identification, spectrally separating vegetation types, and modeling biophysical and biochemical quantities.
This book focuses specifically on hyperspectral remote sensing as applied to terrestrial vegetation applications. This is a big market area, and the chapters discuss in detail a wide array of applications such as agricultural croplands; study of crop moisture and forests; and numerous other applications such as droughts, crop stress, crop productivity, and water productivity. To the best of our knowledge, there is no comparable book, source, and/or organization that has brought this body of knowledge together in one place, making this a “must buy” for professionals. This is clearly a unique contribution whose time has come.Introduction and Overview
Advances in Hyperspectral Remote Sensing of Vegetation and Agricultural Croplands
Hyperspectral Sensor Systems
Hyperspectral Sensor Characteristics: Airborne, Spaceborne, Hand-Held, and Truck-Mounted; Integration of Hyperspectral Data with LIDAR
Hyperspectral Remote Sensing in Global Change Studies
Data Mining, Algorithms, Indices
Hyperspectral Data Mining
Hyperspectral Data Processing Algorithms
Leaf and Plant Biophysical and Biochemical Properties
Nondestructive Estimation of Foliar Pigment (Chlorophylls, Carotenoids, and Anthocyanins) Contents: Evaluating a Semianalytical Three-Band Model
Forest Leaf Chlorophyll Study Using Hyperspectral Remote Sensing
Estimating Leaf Nitrogen Concentration (LNC) of Cereal Crops with Hyperspectral Data
Characterization on Pastures Using Field and Imaging Spectrometers
Optical Remote Sensing of Vegetation Water Content
Estimation of Nitrogen Content in Crops and Pastures Using Hyperspectral Vegetation Indices
Vegetation Biophysical Properties
Spectral Bioindicators of Photosynthetic Efficiency and Vegetation Stress
Spectral and Spatial Methods of Hyperspectral Image Analysis for Estimation of Biophysical and Biochemical Properties of Agricultural Crops
Hyperspectral Vegetation Indices
Remote Sensing Estimation of Crop Biophysical Characteristics at Various Scales
Vegetation Processes and Function (ET, Water Use, GPP, LUE, Phenology)
Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems
Species Identification
Crop Type Discrimination Using Hyperspectral Data
Identification of Canopy Species in Tropical Forests Using Hyperspectral Data
Detecting and Mapping Invasive Plant Species by Using Hyperspectral Data
Land Cover Applications
Hyperspectral Remote Sensing for Forest Management
Hyperspectral Remote Sensing of Wetland Vegetation
Characterization of Soil Properties Using Reflectance Spectroscopy
Detecting Crop Management, Plant Stress, and Disease
Analysis of the Effects of Heavy Metals on Vegetation Hyperspectral Reflectance Properties
Hyperspectral Narrowbands and Their Indices on Assessing Nitrogen Contents of Cotton Crop Applications
Using Hyperspectral Data in Precision Farming Applications
Hyperspectral Data in Global Change Studies
Hyperspectral Data in Long-Term, Cross-Sensor Continuity Studies
Hyperspectral Remote Sensing of Outer Planets
Hyperspectral Analysis of Rocky Surfaces on the Earth and Other Planetary Bodies
Conclusions and Way Forward
Hyperspectral Remote Sensing of Vegetation and Agricultural Crops: Knowledge Gain and Knowledge Gap after 40 Years of Research