Mangroves are among the most productive ecosystems in existence, with many ecological benefits. Therefore, generating accurate thematic maps from mangrove ecosystems is crucial for protecting, conserving, and reforestation planning for these valuable natural resources. In this paper, Sentinel-1 and Sentinel-2 satellite images were used in synergy to produce a detailed mangrove ecosystem map of the Hara protected area, Qeshm, Iran, at 10 m spatial resolution within the Google Earth Engine (GEE) cloud computing platform. In this regard, 86 Sentinel-1 and 41 Sentinel-2 data, acquired in 2019, were employed to generate seasonal optical and synthetic aperture radar (SAR) features. Afterward, seasonal features were inserted into a pixel-based random forest (RF) classifier, resulting in an accurate mangrove ecosystem map with average overall accuracy (OA) and Kappa coefficient (KC) of 93.23% and 0.92, respectively, wherein all classes (except aerial roots) achieved high producer and user accuracies of over 90%. Furthermore, comprehensive quantitative and qualitative assessments were performed to investigate the robustness of the proposed approach, and the accurate and stable results achieved through cross-validation and consistency checks confirmed its robustness and applicability. It was revealed that seasonal features and the integration of multi-source remote sensing data contributed towards obtaining a more reliable mangrove ecosystem map. The proposed approach relies on a straightforward yet effective workflow for mangrove ecosystem mapping, with a high rate of automation that can be easily implemented for frequent and precise mapping in other parts of the world. Overall, the proposed workflow can further improve the conservation and sustainable management of these valuable natural resources.

Oceans cover approximately 71% of the Earth's surface and provide numerous services to the environment and humans. Precise, real-time, and large-scale monitoring of the oceanographic parameters is essential for ocean conservation and understanding the interactions between oceans and the atmosphere. In this regard, Synthetic Aperture Radar (SAR) systems, with unique capabilities (e.g., day-night and almost all-weather data acquisition), provide valuable datasets for ocean studies. Many studies have exploited the applications of SAR imagery for oceans and have proposed numerous methods to study oceanographic parameters. In this study, a brief introduction to SAR and the interaction between microwave signals and the ocean surface are initially provided. Then, the important spaceborne and airborne SAR systems for oceanographic applications are summarized. Subsequently, 12 different applications of SAR systems in the ocean are comprehensively discussed, and the advantages and disadvantages of SAR systems for ocean studies are extensively explored. Finally, the research trend on SAR applications in the ocean is provided by analyzing all the relevant papers published between 1973 and the end of December 2022, and the existing challenges are discussed for future studies.