Emergent capabilities for remote coastline and flood mapping with ultra-high-resolution SAR: a case study in American Samoa

A new generation of ultra-high-resolution synthetic aperture radar (SAR) satellites demonstrates the ability to monitor coastlines and high-tide flooding at a resolution needed to track changing shorelines and improve flood forecasting tools as well as fill existing gaps in coverage from other SAR satellites. We showcase results from Umbra imagery in American Samoa, a set of Pacific Islands that confronts extensive challenges in flooding and coastline change due to subsidence and sea level rise. American Samoa has dense cloud cover year-round that significantly reduces usable remote sensing data from many sources such as optical imagery and altimetry measurements, underscoring the importance of usable SAR imagery. Here, we show how targeted, taskable data from Umbra can delineate coastlines at various points in the tidal cycle, establishing a baseline for shoreline management that complements imagery from other satellites. Furthermore, Umbra data captured two examples of high-tide flooding patterns, which were directly compared with forecasts from the American Samoa Sea Level Rise Viewer to show consistent predicted and observed flooding in one case and a divergence between the two in the other, potentially related to differences in land cover. These results will be used to improve forecasting tools. Drawbacks of the data include several issues in geocoding accuracy that limited the utility of some data and difficulty in timing data acquisitions for rapid-response given the limited availability of observations. These issues may improve with future iterations of data and increased capacity over time, and also point to potential fundamental limitations of the data. Despite these drawbacks, our actionable results in a traditionally challenging environment for remote sensing modalities indicate that the advent of ultra-high-resolution SAR data is a crucial addition to the current global catalog of SAR imagery, capable of filling a gap in observation needs.