2nd Edition

Remote Sensing Handbook, Volume I Sensors, Data Normalization, Harmonization, Cloud Computing, and Accuracies

Edited By Prasad S. Thenkabail Copyright 2025
    640 Pages 166 Color & 44 B/W Illustrations
    by CRC Press

    Volume I of the Remote Sensing Handbook, Second Edition, is focused on satellites and sensors including Radar, LiDAR, Microwave, Hyperspectral, UAVs and their applications. It discusses data normalization and harmonization, accuracies and uncertainties of remote sensing products, GNSS theory and practice, crowdsourcing, cloud computing environments, Google Earth Engine, and remote sensing and space law. This thoroughly revised and updated volume draws on the expertise of a diverse array of leading international authorities in remote sensing and provides an essential resource for researchers at all levels interested in using remote sensing. It integrates discussions of remote sensing principles, data, methods, development, applications, and scientific and social context.


    • Provides the most up-to-date comprehensive coverage of remote sensing science.
    • Discusses and analyzes data from old and new generations of satellites and sensors.
    • Provides comprehensive methods and approaches for remote sensing data normalization, standardization, and harmonization.
    • Includes numerous case studies on advances and applications at local, regional, and global scales.
    • Introduces advanced methods in remote sensing such as machine learning, cloud computing, and AI.
    • Highlights scientific achievements over the last decade and provides guidance for future developments.

    This volume is an excellent resource for the entire remote sensing and GIS community. Academics, researchers, undergraduate and graduate students, as well as practitioners, decision-makers, and policymakers, will benefit from the expertise of the professionals featured in this book, and their extensive knowledge of new and emerging trends.

    Part I: Earth Observing Satellites and Sensors from Different Eras and their Characteristics

    1. Remote Sensing Satellites and Sensors: Optical, Radar, LiDAR, Microwave, Hyperspectral, and UAVs

    Sudhanshu S. Panda, Mahesh N. Rao, Prasad S. Thenkabail, et al.

     Part II: Global Navigation Satellite Systems (GNSS) and their Characteristics

    2. Global Navigation Satellite Systems Theory and Practice:  Evolution, State of Art, and Future Pathways

    Mohinder S. Grewal

     3. Global Navigation Satellite System Reflectometry for Ocean and Land Applications

    Kegen Yu, Chris Rizos, and Andrew Dempster

     4. Global Navigation Satellite Systems (GNSS) for a Wide Array of Terrestrial Applications

    D. Myszor, O. Antemijczuk, M. Grygierek, et al.

     Part III: Fundamentals of Remote Sensing: Evolution, State-of-Art, and Future Possibilities

    5. Fundamentals of Remote Sensing for Terrestrial Applications: Evolution, Current State of Art, and Future Possibilities

    Natascha Oppelt and Arnab Muhuri

     Part IV: Data Normalization, Harmonization, and Inter-Sensor Calibration

    6. Overview of Satellite Image Radiometry in the Solar-Reflective Optical Domain

    Philippe M. Teillet

     7. Post-Launch Radiometric Calibration of Satellite-Based Optical Sensors with Emphasis on Terrestrial Reference Standard Sites

    Philippe M. Teillet and Gyanesh Chander

     8. Remote Sensing Data Normalization

    Rudiger Gens and Jordi Cristóbal Rosselló

     9. Satellite Data Degradations and their Impacts on High Level Products

    Aolin Jia and Dongdong Wang

     Part V: Vegetation Index Standardization and Cross Calibration of Data from Multiple Sensors

    10. Inter- and Intra-sensor Spectral Compatibility and Calibration of the Enhanced Vegetation Indices

    Tomoaki Miura, Kenta Obata, Hiroki Yoshioka,et al.

     11. Towards Standardisation of Vegetation Indices

    Michael D. Steven, Timothy J. Malthus and Frédéric Baret

     Part VI: Crowdsourcing of Remote Sensing Data

    12. Crowdsourcing and Remote Sensing: Combining Two Views of the Earth

    Fabio Dell’Acqua and Silvio Dell’Acqua

     Part VII: Cloud Computing and Remote Sensing

    13. Processing Remote Sensing Data in Cloud Computing Environments

    Ramanathan Sugumaran, James W. Hegeman, Vivek B. Sardeshmukh, et al.

     14. Cloud Computing in Remote Sensing: A Comprehensive Assessment of State of Arts

    Lizhe Wang, Jining Yan, Yan Ma, et al.

     Part VIII: Google Earth for Remote Sensing

    15. The Legacy of Google Earth in Remote Sensing

    John E. Bailey and Josh Williams

    Part IX: Accuracies, Errors, and Uncertainties of Remote Sensing Derived Products

    16. Assessing Positional and Thematic Accuracies of Maps Generated from Remotely Sensed Data

    Russell G. Congalton

     Part X: Remote Sensing Law

    17. Remote Sensing Law: An Overview of its Development and its Trajectory in the Global Context

    P.J. Blount

     Part XI: Summary and Synthesis of Volume I

    18. Remote Sensing Handbook, Volume I: Sensors, Data Normalization, Harmonization, Cloud Computing, and Accuracies

    Prasad S. Thenkabail


    Dr. Prasad S. Thenkabail, Senior Scientist (ST), United States Geological Survey (USGS), is a world-recognized expert in remote sensing science with major contributions in the field for nearly 40 years. He has made the list of the world’s top 1% of scientists across 22 scientific fields and 176 sub-fields. Dr. Thenkabail has conducted pioneering research in hyperspectral remote sensing of vegetation, global croplands, and their water use for food security. He obtained his PhD from the Ohio State University in 1992 and has 168 peer-reviewed publications including 15 books, including this six-volume set, and over 15 major data releases such as the Landsat-derived global cropland extent product @ 30m and Landsat-derived rainfed and irrigated cropland area product @ 30 m (LGRIP30). He was recognized as a Fellow of the American Society of Photogrammetry and Remote Sensing (ASPRS) in 2023. His scientific papers have won several awards for demonstrating world-class, highest-quality research. He was a Landsat Science Team Member (2007-2011).