385 pages | 95 Color Illus. | 47 B/W Illus.
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:
"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
Section I: Detecting Crop Management Practices, Plant Stress, and Disease
1. Using Hyperspectral Data in Precision Farming Applications
[Haibo Yao, Yanbo Huang, Lie Tang, Lei Tian, Deepak Bhatnagar, and Thomas E. Cleveland]
2. Hyperspectral Narrowbands and Their Indices in Study of Nitrogen Content of Cotton Crops
[Jianlong Li, Jingjing Zhang, Chunliu Tao, Dehua Zhao, and Chengcheng Gang]
3. Analysis of the Effects of Heavy Metals on Vegetation Hyperspectral Reflectance Properties
[E. Terrence Slonecker]
Section II: Vegetation Processes and Function (ET, Water Use, GPP, LUE, Phenology)
4. Mapping the Distribution and Abundance of Flowering Plants Using Hyperspectral Sensing
[Tobias Landmann, Hannes Feilhauer, Miaogen Shen, Jin Chen, and Suresh Raina]
5. Crop Water Productivity Estimation with Hyperspectral Remote Sensing
[Michael Marshall, Itiya Aneece, Daniel Foley, Cai Xueliang, and Trent Biggs]
6. Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems
[Pamela Lynn Nagler, B. B. Maruthi Sridhar, Aaryn Dyami Olsson, Willem J. D. van Leeuwen, and Edward P. Glenn]
7. Hyperspectral Applications to Landscape Phenology
[Alfredo Huete, Werapong Koedsin, and Jin Wu]
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
[Prem Chandra Pandey, Kiril Manevski, Prashant K. Srivastava, and George P. Petropoulos]
9. Hyperspectral Remote Sensing for Forest Management
10. Characterization of Pastures Using Field and Imaging Spectrometers
11. Hyperspectral Remote Sensing of Wetland Vegetation
[Elijah Ramsey III and Amina Rangoonwala]
12. Hyperspectral Remote Sensing of Fire: A Review
[Sander Veraverbeke, Philip Dennison, Ioannis Gitas, Glynn Hulley, Olga Kalashnikova, Thomas Katagis, Le Kuai, Ran Meng, Dar Roberts, and Natasha Stavros]
13. Hyperspectral Data in Long-Term, Cross-Sensor Continuity Studies
[Tomoaki Miura and Hiroki Yoshioka]
14. Hyperspectral Analysis of Rocky Surfaces on Earth and Other Planetary Bodies
[R. Greg Vaughan, Timothy N. Titus, Jeffrey R. Johnson, Justin J. Hagerty, Laurence A. Soderblom, Paul E. Geissler, David P. Mayer, and Will M. Grundy]
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
[Prasad S. Thenkabail, John G. Lyon, and Alfredo Huete]