Remote Sensing-Based Intelligent Interpretation and Applications of Coastal Areas

Coastal ecosystems are critical intersections of global economic and ecological systems, characterized by diverse landscapes and vital infrastructures. These include mangroves, salt marshes, aquaculture sites, maritime vessels, oil and gas platforms, wind farms, and coral reefs, all of which are essential for ecological conservation, environmental monitoring, resource management, spatial planning, socio-economic development, disaster early warning, and national security. With advances in remote sensing technology, cutting-edge approaches such as remote sensing big data, multimodal remote sensing fusion, cloud computing, and artificial intelligence are increasingly applied to the intelligent interpretation of these typical landscapes, land cover, and targets. These technologies facilitate the integration of data from various sensors—optical, radar, and hyperspectral—enabling efficient recognition and monitoring with unprecedented spatial and temporal resolutions, providing novel support for coastal area development and management.

Despite the growing application of these new remote sensing technologies, challenges persist in the effective integration of multimodal data from different sensors and achieving precise identification of complex landscapes, land cover, and targets through collaborative processing. As cloud computing in remote sensing matures, large-scale, efficient interpretation and spatiotemporal pattern analysis are becoming increasingly feasible. However, the diversity and complexity of the data, alongside the rapid increase in processing scale, require further innovation in intelligent interpretation algorithms, cloud computing platforms, and multimodal data collaboration. Advances in these areas will substantially enhance remote sensing interpretation techniques for coastal areas, enabling more efficient resource monitoring and environmental management.

This research topic seeks to highlight the latest advances in remote sensing-based intelligent interpretation for the classification and recognition of typical landscapes, land cover, and targets in coastal areas. We are emphasizing frontier technologies such as remote sensing big data, multimodal remote sensing fusion, and cloud computing.

Key focus areas include but not limited to the following subtopics:

• Feature construction and parametric representation of landscapes, land cover, and targets in coastal areas.

• Spatiotemporal pattern changes and pattern mining.

• Multimodal remote sensing fusion and collaboration for intelligent interpretation of coastal areas.

• Cloud computing and big data-driven analysis of remote sensing for coastal areas.

• Machine learning, deep learning, and their application in high-precision remote sensing interpretation of coastal areas.

• Insights into human activities, spatial planning, socio-economic development, and disaster early warning through remote sensing-based intelligent interpretation.