Meng, Lingsheng, Yan, Chi, Lv, Suna, Sun, Haiyang, Xue, Sihan, Li, Quankun, Zhou, Lingfeng, Edwing, Deanna, Edwing, Kelsea, Geng, Xupu, Wang, Yiren, and Yan, Xiao‐Hai
Synthetic Aperture Radar (SAR) has emerged as a pivotal technology in geosciences, offering unparalleled insights into Earth's surface. Indeed, its ability to provide high‐resolution, all‐weather, and day‐night imaging has revolutionized our understanding of various geophysical processes. Recent advancements in SAR technology, that is, developing new satellite missions, enhancing signal processing techniques, and integrating machine learning algorithms, have significantly broadened the scope and depth of geosciences. Therefore, it is essential to summarize SAR's comprehensive applications for geosciences, especially emphasizing recent advancements in SAR technologies and applications. Moreover, current SAR‐related review papers have primarily focused on SAR technology or SAR imaging and data processing techniques. Hence, a review that integrates SAR technology with geophysical features is needed to highlight the significance of SAR in addressing challenges in geosciences, as well as to explore SAR's potential in solving complex geoscience problems. Spurred by these requirements, this review comprehensively and in‐depth reviews SAR applications for geosciences, broadly including various aspects in air‐sea dynamics, oceanography, geography, disaster and hazard monitoring, climate change, and geosciences data fusion. For each applied field, the scientific advancements produced because of SAR are demonstrated by combining the SAR techniques with characteristics of geophysical phenomena and processes. Further outlooks are also explored, such as integrating SAR data with other geophysical data and conducting interdisciplinary research to offer comprehensive insights into geosciences. With the support of deep learning, this synergy will enhance the capability to model, simulate, and forecast geophysical phenomena with greater accuracy and reliability. Synthetic aperture radar (SAR) uses microwaves to remotely see the Earth's surface under all weather conditions, day and night. SAR has been providing high‐resolution images for many decades and they have been applied to many fields in geosciences. Several SAR sensors have been launched in recent years, significantly increasing the SAR data volume and leading to great developments in SAR technology, thereby improving our understanding of geophysical phenomena and processes. This work comprehensively overviews the application of SAR in geosciences, including oceanography, geography, geodesy, climatology, seismology, meteorology, and environmental science. Moreover, this review paper highlights the significance of SAR in various aspects of geosciences, summarizes recent advancements in SAR technology, and demonstrates unique insights and important contributions of SAR in understanding and solving geophysical questions. Future directions and outlooks include integrating SAR with other geophysical data and interdisciplinary applications for complex questions. This review serves as an up‐to‐date guide to the cutting‐edge uses of SAR technology in comprehensive geophysical studies. It is aimed at researchers and practitioners in geosciences, as well as policymakers and stakeholders interested in leveraging SAR for geosciences. Synthetic Aperture Radar (SAR) for geosciences is comprehensively reviewed broadly including oceanography, geography, hazards, and climate changeScientific advances contributed by SAR techniques for each topic are overviewed in‐depth with recent developments and frontiers highlightedData, techniques, and scientific insights of SAR are summarized and prospected, highlighting the role of machine learning Synthetic Aperture Radar (SAR) for geosciences is comprehensively reviewed broadly including oceanography, geography, hazards, and climate change Scientific advances contributed by SAR techniques for each topic are overviewed in‐depth with recent developments and frontiers highlighted Data, techniques, and scientific insights of SAR are summarized and prospected, highlighting the role of machine learning