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Remote Sensing is collecting and interpreting information on targets without being in physical contact with the objects. Aircraft, satellites ...etc are the major platforms for remote sensing observations. Unlike electrical, magnetic and gravity surveys that measure force fields, remote sensing technology is commonly referred to methods that employ electromagnetic energy as radio waves, light and heat as the means of detecting and measuring target characteristics. Geoscience is a study of nature world from the core of the earth, to the depths of oceans and to the outer space. This branch of study can help mitigate volcanic eruptions, floods, landslides ... etc terrible human life disaster and help develop ground water, mineral ores, fossil fuels and construction materials. Also, it studies physical, chemical reactions to understand the distribution of the nature resources. Therefore, the geoscience encompass earth, atmospheric, oceanography, pedology, petrology, mineralogy, hydrology and geology. This book covers latest and futuristic developments in remote sensing novel theory and applications by numerous scholars, researchers and experts. It is organized into 26 excellent chapters which include optical and infrared modeling, microwave scattering propagation, forests and vegetation, soils, ocean temperature, geographic information , object classification, data mining, image processing, passive optical sensor, multispectral and hyperspectral sensing, lidar, radiometer instruments, calibration, active microwave and SAR processing. Last but not the least, this book presented chapters that highlight frontier works in remote sensing information processing. I am very pleased to have leaders in the field to prepare and contribute their most current research and development work. Although no attempt is made to cover every topic in remote sensing and geoscience, these entire 26 remote sensing technology chapters shall give readers a good insight. All topics listed are equal important and significant.

Remote sensing. --- Remote-sensing imagery --- Remote sensing systems --- Remote terrain sensing --- Sensing, Remote --- Terrain sensing, Remote --- Aerial photogrammetry --- Aerospace telemetry --- Detectors --- Space optics --- Geological surface processes (geomorphology)

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Pattern recognition systems --- Remote sensing --- Remote-sensing imagery --- Remote sensing systems --- Remote terrain sensing --- Sensing, Remote --- Terrain sensing, Remote --- Aerial photogrammetry --- Aerospace telemetry --- Detectors --- Space optics --- Data processing

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PREFACE. ACKNOWLEDGEMENTS. 1. INTRODUCTION. 2. HISTORICAL PERSPECTIVE AND PHOTO MENSURATION. 3. RADIOMETRY AND RADIATION PROPAGATION. 4. THE GOVERNING EQUATION FOR RADIANCE REACHING THE SENSOR. 5. SENSING SYSTEMS. 6. IMAGING SENSORS AND INSTRUMENTCALIBRATION. 7. ATMOSPHERIC COMPENSATION: SOLUTIONS TO THE GOVERNING EQUATION. 8. DIGITAL IMAGE PROCESSING PRINCIPLES. 9. MULTISPECTRAL REMOTE SENSING ALGORITHMS: LAND COVER CLASSIFICATION. 10. SPECTROSCOPIC IMAGE ANALYSIS. 11. USE OF PHYSICS-BASED MODELS TO SUPPORT SPECTRAL IMAGE ANALYSIS ALGORITHMS. 12. IMAGE/DATA COMBINATION ANDINFORMATION DISSEMIN

Remote sensing. --- Remote-sensing imagery --- Remote sensing systems --- Remote terrain sensing --- Sensing, Remote --- Terrain sensing, Remote --- Aerial photogrammetry --- Aerospace telemetry --- Detectors --- Space optics

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Since the launch of Seasat, TIROS-N, and Nimbus-7 satellites equipped with ocean observation sensors in 1978, a new era of ocean remote sensing has opened. Today, remotely sensed data have been widely used in oceanographic studies. This reprint collects various advanced ocean remote sensing technologies and their applications, including the use of artificial intelligence techniques to explore ocean information and bibliometric analysis to assess researchers and trends in this scientific field. The observations of various sensors enrich the application of ocean environment monitoring and ocean dynamical analysis. If you are interested in understanding the application of ocean remote sensing, this monograph should be very helpful.

Remote sensing. --- Remote-sensing imagery --- Remote sensing systems --- Remote terrain sensing --- Sensing, Remote --- Terrain sensing, Remote --- Aerial photogrammetry --- Aerospace telemetry --- Detectors --- Space optics

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When adopting remote sensing techniques in precision agriculture, there are two main areas to consider: data acquisition and data analysis methodologies. Imagery and remote sensor data collected using different platforms provide a variety of information volumes and formats. For example, recent research in precision agriculture has used multispectral images from different platforms, such as satellites, airborne, and, most recently, drones. These images have been used for various analyses, from the detection of pests and diseases, growth, and water status of crops to yield estimations. However, accurately detecting specific biotic or abiotic stresses requires a narrow range of spectral information to be analyzed for each application. In data analysis, the volume and complexity of data formats obtained using the latest technologies in remote sensing (e.g., a cube of data for hyperspectral imagery) demands complex data processing systems and data analysis using multiple inputs to estimate specific categorical or numerical targets. New and emerging methodologies within artificial intelligence, such as machine learning and deep learning, have enabled us to deal with these increasing data volumes and the analysis complexity.

Remote sensing. --- Remote-sensing imagery --- Remote sensing systems --- Remote terrain sensing --- Sensing, Remote --- Terrain sensing, Remote --- Aerial photogrammetry --- Aerospace telemetry --- Detectors --- Space optics