Radar Remote Sensing for Crop Biophysical Parameter Estimation

Radar Remote Sensing for Crop Biophysical Parameter Estimation

Radar Remote Sensing for Crop Biophysical Parameter Estimation

Radar Remote Sensing for Crop Biophysical Parameter Estimation

Paperback(1st ed. 2021)

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Overview

This book presents a timely investigation of radar remote sensing observations for agricultural crop monitoring and advancements of research techniques and their applicability for crop biophysical parameter estimation. It introduces theoretical background of radar scattering from vegetation volume and semi-empirical modelling approaches that are the foundation for biophysical parameter inversion. The contents will help readers explore the state-of-the-art crop monitoring and biophysical parameter estimation using approaches radar remote sensing. It is useful guide for academicians, practitioners and policymakers.


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Product Details

ISBN-13: 9789811644269
Publisher: Springer Nature Singapore
Publication date: 08/17/2021
Series: Springer Remote Sensing/Photogrammetry
Edition description: 1st ed. 2021
Pages: 236
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author

Dr. Dipankar Mandal received his B.Tech. degree in agricultural engineering from Bidhan Chandra Krishi Viswavidyalaya, India, in 2015, and M.Tech + Ph.D. dual degree in Geoinformatics and Natural Resources Engineering from the Indian Institute of Technology (IIT) Bombay, Mumbai, India, in 2020. He was a visiting researcher with the Agriculture and Agri-Food Canada (AAFC), Ottawa, Canada, and Carleton University, Ottawa, from October 2018 to February 2019. As a visiting researcher, he contributed to the Synthetic Aperture Radar (SAR) Intercomparison experiment for crop biophysical parameter estimation within the Joint Experiment for Crop Assessment and Monitoring (JECAM) network of GEO Global Agricultural Monitoring. His research interests include applications of SAR polarimetry for crop classification, vegetation biophysical parameter estimation, deriving radar vegetation indices and yield forecasting. Dr. Mandal was a recipient of the Shastri Research Student Fellowship 2018–2019 Award by the Shastri Indo-Canadian Institute, India.

Dr. Avik Bhattacharya received his integrated M.Sc. degree in Mathematics from the Indian Institute of Technology (IIT) Kharagpur, India, in 2000, and a Ph.D. degree in remote sensing image processing and analysis from Télécom ParisTech, Paris, France, and the Ariana Research Group, Institut National de Recherche en Informatique et en Automatique (INRIA), France, in 2007. He is currently a professor with the Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, India. Before joining IIT Bombay, he was a Canadian Government Research Fellow with the Canadian Centre for Remote Sensing (CCRS) in Canada. His current research interests include SAR polarimetry, statistical analysis of polarimetric SAR images, radar remote sensing applications in agriculture, cryosphere, urban and planetary studies. Dr. Bhattacharya was a recipient of the Natural Sciences and Engineering Research Council of Canada visiting Scientist Fellowship with the Canadian national laboratories from 2008 to 2011. He is the Editor-in-Chief of IEEE Geoscience and Remote Sensing Letters (GRSL).

Dr. Yalamanchili Subrahmanyeswara Rao received his M.Sc. degree in physics from Andhra University, Andhra Pradesh, India, in 1982, and the Ph.D. degree in passive microwave remote sensing of soil moisture from the Indian Institute of Technology (IIT) Bombay, India, in 1992. He joined the Centre of Studies Resources Engineering, IIT Bombay, in 1985, as a senior research assistant and then became a research scientist in 1999. During 2005–2009, he was a senior research scientist and then an associate professor from 2009 to 2014. He is currently continuing as a professor. He worked in passive and active microwave remote sensing for several applications, viz., soil moisture, vegetation dynamics, flood mapping and land use/land cover. He has participated in several space-borne campaigns to collect synchronous ground-truth data and has experience handling various datasets for several applications. His research interests include the application of polarimetry for geophysical parameter retrieval and SAR interferometry for digital elevation models and displacement map generation.

Table of Contents

Introduction.- Basic theory of radar polarimetry.- Vegetation models: Empirical and Theoretical approaches.- Evolution of Semi-empirical approach: Modeling and Inversion.- Biophysical parameter retrieval using full and dual-pol SAR data.- Biophysical parameter retrieval using compact-pol SAR data.- Radar vegetation indices for crop growth monitoring.- Summary and Conclusions.

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