About the Book
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation.
Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics
Volume II, Hyperspectral Indices and Image Classifications for Agriculture and Vegetation evaluates the performance of hyperspectral narrowband or imaging spectroscopy data with specific emphasis on the uses and applications of hyperspectral narrowband vegetation indices in characterizing, modeling, mapping, and monitoring agricultural crops and vegetation
Volume III, Biophysical and Biochemical Characterization and Plant Species Studies demonstrates the methods that are developed and used to study terrestrial vegetation using hyperspectral data. This volume includes extensive discussions on hyperspectral data processing and how to implement data processing mechanisms for specific biophysical and biochemical applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessments
Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection.
Table of Contents:
Contents of Volume I: Section I: Introduction to Hyperspectral Remote Sensing of Agricultural Crops and Vegetation Section II: Hyperspectral Sensor Systems Section III: Hyperspectral Libraries of Agricultural Crops and Vegetation Section IV: Hyperspectral Data Mining, Data Fusion, and Algorithms Contents of Volume II: Section I: Hyperspectral Vegetation Indices Section II: Hyperspectral Image Classification Methods and Approaches Section III: Hyperspectral Vegetation Indices Applications to Agriculture and Vegetation Contents of Volume III: Section I: Vegetation Biophysical and Biochemical Properties Section II: Plant Species Identification and Discrimination Section III: Conclusions Contents of Volume IV: Section I: Detecting Crop Management Practices, Plant Stress, and Disease Section II: Vegetation Processes and Function (ET, Water Use, GPP, LUE, Phenology) Section III: Land Cover, Forests, and Wetland and Urban Applications Using Hyperspectral Data Section IV: Thermal, SWIR, and Visible Remote Sensing Section V: Hyperspectral Data in Global Change Studies Section VI: Hyperspectral Remote Sensing of Other Planets Section VII: Conclusions
About the Author :
Dr. Prasad S. Thenkabail is a well known global expert in remote sensing and spatial sciences. Currently, works as a Research Geographer-15 with the U.S. Geological Survey (USGS). Dr. Thenkabail has conducted pioneering scientific research work in two major areas: Hyperspectral remote sensing of vegetation; Global Irrigated and Rainfed Cropland Mapping. His research papers have won three American Society of Photogrammetric Engineering and Remote Sensing (ASPRS) awards: (a) 2015 ERDAS award for best scientific paper (second author), (a) 2008 ASPRS President’s award (first author), (b) 1994 Autometric Award (first author). He is the Editor-in- Chief of seminal books (Publisher: Taylor and Francis Inc.): (a) three volume (including this), 82 Chapter, Remote Sensing Handbook (November 2015), (b) Hyperspectral Remote Sensing of Vegetation (2012), and (c) Remote Sensing of Global Croplands for Food Security (2009). He is the Editor-in-Chief of Remote Sensing Open Access Journal and is on the editorial board of Remote Sensing of Environment, and ISPRS Journal of Photogrammetry and Remote Sensing. Prasad has work experience in 25+ Countries including working in key remote sensing research\leadership positions @ the International Water Management Institute (IWMI), International Institute of Tropical Agriculture (IITA), Yale Center for Earth Observation (YCEO), and the Indian National Remote Sensing Agency. He was selected by NASA and USGS as a member of Landsat Science Team Member (2007-20011), and was a scientific advisory board member of Rapideye (2001).
John G. Lyon has conducted scientific and engineering research and administrative functions throughout his career. He is formerly the senior physical scientist in the U.S. Environmental Protection Agency’s Office of Research and Development (ORD) and Office of the Science Advisor in Washington, DC, where he co-led work on the Group on Earth Observations and the USGEO subcommittee of the Committee on Environment and Natural Resources, and research on geospatial issues. Lyon was director of ORD’s Environmental Sciences Division for approximately eight years. He was educated at Reed College in Portland, Oregon, and the University of Michigan in Ann Arbor.
Professor Alfredo Huete leads the Ecosystem Dynamics Health and Resilience research program within the Climate Change Cluster (C3) at the University of Technology Sydney, Australia. His main research interest is in using remote sensing to study and analyze broad scale vegetation health and functioning. Recently, he used remote sensing and field measurements to understand the phenology patterns of tropical rainforests and savannas in the Amazon and Southeast Asia and his Amazon work was featured in a National Geographic television special entitled "The Big Picture". Currently his research involves coupling eddy covariance tower flux measurements with ground spectral sensors and satellite observations to study carbon and water cycling across Australian landscapes. He is actively involved with several international space programs, including the NASA-EOS MODIS Science Team, the Japanese JAXA GCOM-SGLI Science Team, the European PROBA-V User Expert Group, and NPOESS-VIIRS advisory group.
Review :
"Very comprehensive and an excellent reference, both for practitioners in the field as well as students hoping to learn more about the uses of Hyperspectral Data for characterizing a diverse set of vegetation...There are books by other authors on Hyperspectral approaches and vegetation characterization(non-hyperspectral), but I believe this book stands alone as the final word on Hyperspectral characterization of vegetation. In fact, all the premier works in literature on Hyperspectral characterization of vegetation have been authored by Thenkabail et al.!"
--Dr. Thomas George, CEO, SaraniaSat Inc.
"The publication of the four-volume set, Hyperspectral Remote Sensing of Vegetation, Second Edition, is a landmark effort in providing an important, valuable, and timely contribution that summarizes the state of spectroscopy-based understanding of the Earth’s terrestrial and near shore environments."
--Susan L. Ustin, John Muir Institute
"The second edition of the book is major revision effort and covers all the aspects most descriptively and explicitly for the students, academia and professionals across the discipline. The book provides breadth of innovative applications of mathematical techniques to extract information from the hyperspectral image data. The chapters are contributed by internationally renowned authors in their respective fields...The hand book Hyperspectral Remote Sensing of Vegetation by Prasad S. Thenkabail, John G. Lyon and Alfredo Huete is most comprehensive, designed for learning and the best book in the discipline today."
--Dr. P.S. Roy, ICRISAT-CGIAR
"This book is an absolute gem. The history, the contemporary and the future of hyperspectral remote sensing of vegetation is contained within these pages. New topics on data mining and machine learning are hugely helpful to understand how scientists can go about processing these massive data sets. With great societal challenges such as food security, sustainability, deforestation and land use change, the research presented in this book provides clear evidence that hyperspectral remote sensing has an important and valuable role to play.
The book is a great resource for undergraduate, postgraduate students, research and academics. There is something in this book for everyone. I want it on my shelf."
--Prof. Kevin Tansey, Leicester Institute for Space & Earth Observation
