Advances in Earth Observations Analytics: Leveraging Radar and Optical Together

Dear Colleagues,

Recent advances in Earth Observation (EO) technologies have provided a unique opportunity for increasing detailed understanding of various features of the Earth system. In particular, radar and optical remote sensing systems are collecting multitemporal, multispectral, and multifrequency imagery and data with increasing spatial resolution. These exceptional data bring both opportunities and challenges for detection, identification, classification, and mapping of the Earth. Consequently, now is the time to leverage these advanced technologies to advance our capacity to monitor our dynamic planet and environment.

EO analytics, based on today’s open source technology, artificial intelligence and machine learning, and high-performance computing, can benefit from these opportunities and address the challenges. This technology can provide accurate, up to date, diversified geospatial information for various natural resource, and environmental and societal applications. These applications range from land use/land cover mapping (e.g., monitoring urbanization, croplands, desertification, deforestation and forest health, glaciers and sea ice) to detecting and monitoring of air pollution and oil spills, to geology mapping.

This Special Issue of Remote Sensing, entitled “Advances in Earth Observations Analytics: Leveraging Radar and Optical Together”, aims at presenting the state-of-the-art and original analytical methods for converging diverse advanced remote sensing data into information relevant to various earth sciences applications. Research papers that examine the latest developments in concepts, methods, techniques, and case study applications are welcomed. These analytical methods could be developed for individual or integrated remotely sensed data, e.g., optical (multispectral and hyperspectral), radar (polarimetry and interferometry), LiDAR (terrestrial and airborne), and thermal imagery acquired by satellite, airborne, and UAV sensors.

Dr. Saeid Homayouni
Dr. H. Peter White
Dr. Alireza Tabatabaeenejad
Dr. Pedram Ghamisi
Guest Editors

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