Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation

Prasad S Thenkabail editor John G Lyon editor Alfredo Huete editor

Format:Hardback

Publisher:Taylor & Francis Ltd

Published:11th Dec '18

Currently unavailable, and unfortunately no date known when it will be back

This hardback is available in another edition too:

Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation cover

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. This book also presents and discusses hyperspectral narrowband data acquired in numerous unique spectral bands in the entire length of the spectrum from various ground-based, airborne, and spaceborne platforms. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume I through the editors’ perspective.

Key Features of Volume I:

  • Provides the fundamentals of hyperspectral remote sensing used in agricultural crops and vegetation studies.

  • Discusses the latest advances in hyperspectral remote sensing of ecosystems and croplands.

  • Develops online hyperspectral libraries, proximal sensing and phenotyping for understanding, modeling, mapping, and monitoring crop and vegetation traits.

  • Implements reflectance spectroscopy of soils and vegetation.

  • Enumerates hyperspectral data mining and data processing methods, approaches, and machine learning algorithms.

  • Explores methods and approaches for data mining and overcoming data redundancy;

  • Highlights the advanced methods for hyperspectral data processing steps by developing or implementing appropriate algorithms and coding the same for processing on a cloud computing platform like the Google Earth Engine.

  • Integrates hyperspectral with other data, such as the LiDAR data, in the study of vegetation.
  • Includes best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, crop productivity and water productivity mapping, and modeling.
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"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


"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

ISBN: 9781138058545

Dimensions: unknown

Weight: 1769g

449 pages

2nd edition