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Biophysical and Biochemical Characterization and Plant Species Studies
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Biophysical and Biochemical Characterization and Plant Species Studies

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Hyperspectral remote sensing has been increasingly used in studding and assessing biophysical and biochemical properties of agricultural crops. This volume demonstrates the experience and the methods used in studying terrestrial vegetation using hyperspectral data. It focuses on specific applications, reviews existing “state-of-art” knowledge, highlights the advances made, and provides guidance for appropriate use of hyperspectral data in applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessment. Includes extensive discussions on data processing and how to implement data processing mechanisms.

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 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.

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優惠價:90 6885
若需訂購本書,請電洽客服 02-25006600[分機130、131]。

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