Sar Shoreline Processor: Methodology and First Results

• Published in: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium pp. 1451 - 1455
• Main Authors: Savastano, Salvatore, Pattle, Mark E., Garcia-Mondejar, Albert, Estella-Perez, Victor, Da Silva, Paula Gomes, Martinez Sanchez, Jara, Payo, Andres, Castillo, Yeray, Monteys, Xavier
• Format: Conference Proceeding
• Language: English
• Published: IEEE 07.07.2024
• Subjects: Clouds; coastal erosion; Coastlines; Earth Observation; incidence angle; Optical filters; Optical sensors; Radar tracking; remote sensing; SAR; Sea measurements; shoreline; Surfaces; topography
• ISSN: 2153-7003
• DOI: 10.1109/IGARSS53475.2024.10642221

Coastlines are continuously transforming, and satellite-based remote sensing represents a cost-effective observation method able to accurately map and monitor these changes. While optical technology is limited by factors like darkness, clouds, and rain, Synthetic Aperture Radar (SAR) remains unaffected, offering the advantage of potentially providing more frequent updates for shoreline mapping. This study presents an innovative automatic processor to extract shorelines (SLs) from SAR data to track coastline variations over time. It is applied across various sites, showing the effects on the SL positions of the incidence angle between the sensor's line of sight and the scene topography. The research findings consistently show that SAR-derived SLs align with positions above the high-water mark across all the studied sites. Depending on the topography, the SLs acquired in ascending (ASC) and descending (DESC) tracks show overlapping or mismatch. This paper presents two examples of such occurrences. This offers coastal scientists and stakeholders a unique tool for complementing the analysis conducted by optical sensors, which is especially relevant in regions of the Earth that are constantly affected by cloud cover.