Remote Sensing Handbook, Volume I: Sensors, Data Normalization, Harmonization, Cloud Computing, and Accuracies, Edition 2
About this ebook
FEATURES
- 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.
About the author
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).
