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During the last decade a series of SAR satellites has been launched, including Chinese Gaofen 3, providing great amount of SAR data with varied modes to meet the varieties of applications It becomes a challenge to retrieve information from these big data The main objective of this workshop is to share models, methods and applications of SAR data exploration in the big data era The workshop includes different subjects, such as big SAR data modeling, large scale intelligent SAR processing, SAR applications in big data frameworks It will feature keynote presentations by distinguished researchers on this topics.
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Annotation An increasing number of spaceborne Synthetic Aperture Radar (SAR) systems have been equipped with polarimetric capabilities: ALOS and ALOS-2, Radarsat-2, TerraSAR-X, Envisat-ASAR, Sentinel-1a/b, etc. Future mission will still present this type of diversity: RCM, SAOCOM, Cosmo-Skymed 2nd generation or PAZ. Polarimetry allows sensitivity to the structural and geometric properties of the scene, making it possible a more accurate identification and classification than non-polarimetric systems. Then, polarimetry makes possible new applications, especially in quantitative extraction of bio and geophysical variables. Also, the combination of polarimetry and interferometry allows also to explore the vertical structure of semi-transparent media, like crops and forests. SAR polarimetry is an active field of research in Earth observation. Besides the development of applications, researchers have also focused in theory or physical modelling to make SAR polarimetry an operational technique. This book presents the state of the art in SAR polarimetry, from theory and physical modelling to final applications, but also the current and futures challenges. This book puts also the emphasis on studies for the exploitation of data provided by the new polarimetric space borne SAR sensors, which include additional frequency bands, interferometric capability, enlarged spatial coverage, high spatial resolution and/or shorter revisit times.
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