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There have been numerous advances in thermal infrared (TIRS) sensors, analytical techniques and applications in recent years. A number of new satellite platforms have launched with TIR capabilities, and others will be ready for launch in the near future. This book builds upon the book Thermal Remote Sensing in Land Surface Processing and provides new and updated information on thermal remote sensing satellite and aircraft-borne sensors. It includes examples of new analysis and modeling techniques, applications on land and water bodies, provides insight into what TIR sensors will be launched in the near future, and includes an open source/digital format with additional interactive materials in each chapter.FeaturesHighlights the latest and updated information on TIR remote sensing, current TIR sensors and future sensors.Explains new and updated TIRS sensor analytical techniques.Focuses on new modeling techniques to derive information on land and water surface processes from TIR sensor data.Includes relevant and updated examples of applications of TIR sensor data to land surface and water body processes.Provides examples of linkage of TIR sensor data with hyperspectral and other remote sensing datasets.This book is for professionals, academics, and students who are part of remote sensing and geospatial community, environmental science community, geologists, geographers, ecologists, spatial statisticians and all those involved in quantitative analysis. It is also an excellent resource for upper-level undergraduate and graduate students taking courses in photogrammetry and image processing in information science and engineering.The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC BY-NC-ND) 4.0 license.

Produktinformation

  • Utgivningsdatum2026-03-05
  • Mått156 x 234 x 22 mm
  • Vikt850 g
  • FormatInbunden
  • SpråkEngelska
  • Antal sidor350
  • FörlagTaylor & Francis Ltd
  • ISBN9781032603032
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