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Hyperspectral Remote Sensing of Vegetation demonstrates the experience, utility, methods and models used in studying terrestrial vegetation using hyperspectral data. Written by global experts, each chapter focuses on specific applications, reviews existing "state-of-art" knowledge, highlights the advances made, and provides guidance for appropriate use of hyperspectral data in study of vegetation and its numerous applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessment. The second edition includes extensive discussions on data processing and how to implement data processing mechanisms in a standard, fast, and efficient manner for their applications.
- Introduction and Overview
- Hyperspectral Sensor Systems
- Pre-Processing to Normalize and Harmonize Hyperspectral Data
- Data Mining, Algorithms, and Indices
- Image Analysis Methods, Approaches, and Algorithms
- Leaf and Plant Biophysical and Biochemical Properties
- Vegetation Processes and Function (ET, Water Use, GPP, LUE, Phenology)
- Hyperspectral Data in Global Change Studies
- Vegetation Biophysical and Biochemical Properties
- Plant Species Identification and Discrimination
- Detecting Crop Management Practices, Plant Stress, and Disease
- Land Cover, Forests, Wetland, and Urban Applications Using Hyperspectral Data
- Soil Characterization and Mapping Using Hyperspectral Data
- Hyperspectral Remote Sensing of Outer Planets
Dr. Prasad S. Thenkabail is a well known global expert in remote sensing and spatial sciences. Currently, he 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 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 at 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.
Reviews of the first edition:
"The authors solicited the help of numerous high-quality hyperspectral remote sensing scientists to write this book. The characteristics of hyperspectral remote sensing systems are explained clearly. Fundamental hyperspectral data analysis, hyperspectral indices, and data mining methods are introduced. I am particularly impressed with the in-depth treatment on leaf and plant biophysical and biochemical properties, especially related to remote sensing of: chlorophyll content, leaf nitrogen concentration, photosynthetic efficiency, quantifying plant litter, leaf-area-index, and vegetation stress detection. The book documents numerous practical applications of hyperspectral remote sensing for forest management, precision farming, monitoring invasive species, and local to global land cover change detection. No other book contains such detailed information about hyperspectral remote sensing of vegetation."
– Dr. John R. Jensen, PhD, Carolina Distinguished Professor, Department of Geography, University of South Carolina, Columbia, USA
"Hyperspectral Remote Sensing of Vegetation fills an important gap in today's literature. This comprehensive text covers all aspects of hyperspectral sensing of plants and vegetation, from sensor systems, data mining, biophysical properties and plant functioning, to species mapping and land cover applications. This book will greatly increase the research communities' understanding of how to use hyperspectral data to solve otherwise intractable problems in plant applications from crops to forests."
– Susan L. Ustin, Professor of Environmental and Resource Sciences, Department of Land, Air, and Water Resources, University of California at Davis, USA
"Hyperspectral Remote Sensing of Vegetation provides excellent coverage of the research and application of high spectral resolution measurements for vegetation mapping, monitoring and analysis. This book brings together an enormous range of topical areas, leaving the reader with a much improved understanding of the vital role and use of the hyperspectral sensing for plant and ecosystem studies."
– Greg Asner, Professor, Department of Global Ecology, Carnegie Institution for Science, Stanford University, California, USA
"The publication of this book, Hyperspectral Remote Sensing of Vegetation, marks a milestone in the application of imaging spectrometry to studies of the 70% of the Earth's landmass which is vegetated. This book shows not only the breadth of international involvement in the use of hyperspectral data but also in the breadth of innovative application of mathematical techniques to extract information from the image data."
– From the Foreword by Alexander F. H. Goetz, Chairman and Chief Scientist, Analytical Spectral Devices Inc., Boulder, Colorado, USA