Remote sensing, which involves monitoring Earth’s environment from airborne platforms and satellites, is rapidly advancing. Researchers from diverse backgrounds increasingly use remotely sensed data. The new edition of "Comprehensive Remote Sensing" meets their need for up-to-date, in-depth information on various aspects of the field, from principles and data analysis to applications. Containing over 100 chapters from world experts in the field, this edition includes all recent developments, with a focus on satellite missions, sensors, models, practical inversion algorithms, high-level products and applications. In addition to governments, many private companies are launching satellites. Advances in computing power and data storage have enabled massive data processing and analysis. Consequently, remote sensing has become essential for geographers, oceanographers, meteorologists, physicists, computer scientists, and others. "Comprehensive Remote Sensing" addresses this diversity with structured chapters that begin with fundamental concepts and principles, followed by reviews of the latest developments and a comprehensive list of references. It is a valuable resource for readers at various levels of specialization. Volume 1 focuses on satellite missions and sensors. Volume 2 covers various data processing techniques, including cloud and shadow detection, analysis-ready data (ARD) techniques for high-resolution data, and machine learning methods. Volumes 3-8 discuss advances in new inversion methods and high-level satellite products that characterize the spatio-temporal variations in essential environmental variables under a changing climate. Volume 9 highlights remote sensing applications, which have entered a new era with the availability of vast high-resolution satellite and UAV observations.

Table of Contents:
1. Remote sensing missions and sensors Major satellite programs and associated sensors: EOS; Landsat , SPOT; JPSS program, other national space programs (JAXA, China, India, etc.) 2. Remote sensing data processing and analysis methodology Geometric processing; radiometric processing; data fusion, image classification, data assimilation 3. Quantitative remote sensing of vegetation Vegetation index, Biochemical properties, Vegetation structural information (tree high, etc.), LAI, FAPAR, fractional vegetation, biomass, gross/net primary, productivity, phenology 4. Remote sensing of hydrological cycle Precipitation, evapotranspiration, soil moisture, snow water equivalent, surface and underground water storage 5. Remote sensing of Earth energy budget TOA net radiation (albedo, outgoing radiation), surface net radiation (incident shortwave radiation, albedo, downward and upwelling longwave radiation), land surface temperature and emissivity, SST, surface sensible heat flux 6. Remote Sensing of land surface type change Land cover mapping, plant functional types, land use change detection (afforestation/reforestation/deforestation, urban expansion and urban heat island, crop distribution, irrigation), invasive species, surface water, wetland, fire burned area, hazardous mapping (drought, flooring, landslides, etc.), snow cover, frozen/shaw, surface topography 7. Atmospheric remote sensing Atmospheric profiles (temperature, water vapor), aerosols, clouds, ozone, carbon, wind 8. Oceanic remote sensing Ocean color, acoustic tomography, surface topography, salinity, wind and velocity, sea level, sea ice, Coastal Environment 9. Remote sensing applications Various applications in Earth system science and societal benefit areas, such as agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and weather