Thermal Remote Sensing In Land Surface Processes

Although remote sensing is recognized as a powerful tool, less attention has been given in the past to the use of thermal, and especially thermal infrared (TIR) remote sensing. TIR data is useful for understanding the fluxes and redistribution of materials as a key aspect of land surface processes and land-atmosphere inter-relationships. This book

This book provides a comprehensive overview of the state of the art in the field of thermal infrared remote sensing. Temperature is one of the most important physical environmental variables monitored by earth observing remote sensing systems. Temperature ranges define the boundaries of habitats on our planet. Thermal hazards endanger our resources and well-being. In this book renowned international experts have contributed chapters on currently available thermal sensors as well as innovative plans for future missions. Further chapters discuss the underlying physics and image processing techniques for analyzing thermal data. Ground-breaking chapters on applications present a wide variety of case studies leading to a deepened understanding of land and sea surface temperature dynamics, urban heat island effects, forest fires, volcanic eruption precursors, underground coal fires, geothermal systems, soil moisture variability, and temperature-based mineral discrimination. ‘Thermal Infrared Remote Sensing: Sensors, Methods, Applications’ is unique because of the large field it spans, the potentials it reveals, and the detail it provides. This book is an indispensable volume for scientists, lecturers, and decision makers interested in thermal infrared technology, methods, and applications.

Although remote sensing is recognized as a powerful tool, less attention has been given in the past to the use of thermal, and especially thermal infrared (TIR) remote sensing. TIR data is useful for understanding the fluxes and redistribution of materials as a key aspect of land surface processes and land-atmosphere inter-relationships. This book

This book provides a comprehensive and advanced overview of the basic theory of thermal remote sensing and its application in hydrology, agriculture, and forestry. Specifically, the book highlights the main theory, assumptions, advantages, drawbacks, and perspectives of these methods for the retrieval and validation of surface temperature/emissivity and evapotranspiration from thermal infrared remote sensing. It will be an especially valuable resource for students, researchers, experts, and decision-makers whose interest focuses on the retrieval and validation of surface temperature/emissivity, the estimation and validation of evapotranspiration at satellite pixel scale, and the application of thermal remote sensing. Both Prof. Huajun Tang and Prof. Zhao-Liang Li work at the Chinese Academy of Agricultural Sciences (CAAS), China.

This is a detailed description of the steps leading from raw signals measured in space, to calibrated comparable long term data sets, to its final form: useful information for user communities. Examples of applications and data validations result from different investigations in the Mediteranean area. An appendix summarizes useful formulas of the evaluation of satellite data.

Remote Sensing of Soil and Land Surface Processes: Monitoring, Mapping, and Modeling couples artificial intelligence and remote sensing for mapping and modeling natural resources, thus expanding the applicability of AI and machine learning for soils and landscape studies and providing a hybridized approach that also increases the accuracy of image analysis. The book covers topics including digital soil mapping, satellite land surface imagery, assessment of land degradation, and deep learning networks and their applicability to land surface processes and natural hazards, including case studies and real life examples where appropriate. This book offers postgraduates, researchers and academics the latest techniques in remote sensing and geoinformation technologies to monitor soil and surface processes. ? Introduces object-based concepts and applications, enhancing monitoring capabilities and increasing the accuracy of mapping ? Couples artificial intelligence and remote sensing for mapping and modeling natural resources, expanding the applicability of AI and machine learning for soils and sediment studies ? Includes the use of new sensors and their applications to soils and sediment characterization ???????? Includes case studies from a variety of geographical areas