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Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation de Prasad S. Thenkabail

Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation: Hyperspectral Remote Sensing of Vegetation, Second Edition

Editat de Prasad S. Thenkabail, John G. Lyon, Alfredo Huete
en Limba Engleză Hardback – 11 dec 2018
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 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. It emphasizes the importance of hyperspectral remote sensing tools for studying vegetation processes and functions as well as the appropriate use of hyperspectral data for vegetation management practices. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume IV through the editors’ perspective.
Key Features of Volume IV:
  • Guides readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation.
  • Includes specific applications on agriculture, crop management practices, study of crop stress and diseases, crop characteristics based on inputs (e.g., nitrogen, irrigation), study of vegetation impacted by heavy metals, gross and net primary productivity studies, light use efficiency studies, crop water use and actual evapotranspiration studies, phenology monitoring, land use and land cover studies, global change studies, plant species detection, wetland and forest characterization and mapping, crop productivity and crop water productivity mapping, and modeling.
  • Encompasses hyperspectral or imaging spectroscopy data in narrow wavebands used across visible, red-edge, near-infrared, far-infrared, shortwave infrared, and thermal portions of the spectrum.
  • Explains the implementation of hyperspectral remote sensing data processing mechanisms in a standard, fast, and efficient manner for their applications.
  • Discusses cloud computing to overcome hyperspectral remote sensing massive big data challenges.
  • Provides hyperspectral analysis of rocky surfaces on the earth and other planetary systems.
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Din seria Hyperspectral Remote Sensing of Vegetation, Second Edition

  • Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation
    Preț: 35070 lei
  • 11% Biophysical and Biochemical Characterization and Plant Species Studies
    Preț: 30548 lei
  • 11% Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation
    Preț: 30674 lei
  • 13% Hyperspectral Indices and Image Classifications for Agriculture and Vegetation
    Preț: 29611 lei
  • 25% Hyperspectral Remote Sensing of Vegetation, Second Edition, Four Volume Set
    Preț: 268975 lei

Preț: 105839 lei

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Specificații

ISBN-13: 9781138364769
ISBN-10: 1138364762
Pagini: 425
Ilustrații: 142
Dimensiuni: 178 x 254 x 24 mm
Greutate: 1.19 kg
Ediția:2nd edition
Editura: CRC Press
Colecția CRC Press
Seria Hyperspectral Remote Sensing of Vegetation, Second Edition

Locul publicării:Boca Raton, United States

Public țintă

General

Cuprins

Section I: Detecting Crop Management Practices, Plant Stress, and Disease 1. Using Hyperspectral Data in Precision Farming Applications 2. Hyperspectral Narrowbands and Their Indices in Study of Nitrogen Content of Cotton Crops 3. Analysis of the Effects of Heavy Metals on Vegetation Hyperspectral Reflectance Properties Section II: Vegetation Processes and Function (ET, Water Use, GPP, LUE, Phenology) 4. Mapping the Distribution and Abundance of Flowering Plants Using Hyperspectral Sensing 5. Crop Water Productivity Estimation with Hyperspectral Remote Sensing 6. Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems 7. Hyperspectral Applications to Landscape Phenology Section III: Land Cover, Forests, and Wetland and Urban Applications Using Hyperspectral Data 8. The Use of Hyperspectral Earth Observation Data for Land Use/Cover Classification: Present Status, Challenges, and Future Outlook 9. Hyperspectral Remote Sensing for Forest Management 10. Characterization of Pastures Using Field and Imaging Spectrometers 11. Hyperspectral Remote Sensing of Wetland Vegetation Section IV: Thermal, SWIR, and Visible Remote Sensing 12. Hyperspectral Remote Sensing of Fire: A Review Section V: Hyperspectral Data in Global Change Studies 13. Hyperspectral Data in Long-Term, Cross-Sensor Continuity Studies Section VI: Hyperspectral Remote Sensing of Other Planets 14. Hyperspectral Analysis of Rocky Surfaces on Earth and Other Planetary Bodies Section VII: Conclusions 15. Fifty Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume IV: Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation

Recenzii

"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

Notă biografică

Prasad S. Thenkabail, John G. Lyon, Alfredo Huete

Descriere

This volume discusses the use of hyperspectral data in numerous applications such as forest management, precision farming, monitoring invasive species, local to global land cover change detection, crop yield modeling and crop moisture assessment. Also emphasizes the importance of hyperspectral remote sensing tools for studying vegetation.