{ "culture": "en-US", "name": "s1_flooddetection", "guid": "C41E06A8-907F-4B51-A810-8E1FEFF3E1DF", "catalogPath": "", "snippet": "Flood Detection using Sentinel-1 Synthetic Aperture Radar for the Flooding in Texas July 2025.", "description": "
Date of Images:<\/span><\/p> Post-Event: Jul 11, 2025 at 00:35 UTC (July 10, 2025, 7:35:12 PM CDT)<\/span><\/p> Pre-Event: Jun 05, 2025 <\/span><\/p> Date of Next Image:<\/span><\/p> July 2, 2025<\/span><\/p> Summary:<\/span><\/p> We developed a rapid-response workflow to map flooded areas during this emergency event using multi-temporal Sentinel-1 SAR data. Sentinel-1\u2019s SAR backscatter characteristics are particularly effective for detecting surface water: water surfaces typically exhibit low backscatter, whereas non-water areas show higher backscatter. Leveraging this physical property, we distinguished between water and non-water surfaces from both pre- and post-flood observations.<\/span><\/p> To highlight flood-induced surface changes, we computed the differenced co-polarized VV backscatter (dVV = VV_post \u2013 VV_pre). This change detection technique enhances the visibility of newly inundated areas. We then applied a simple threshold to the dVV image to separate flooded from non-flooded areas.<\/span><\/p> Suggested Use:<\/span><\/p> The final output is a binary raster product, where pixels with a value of 1 represent flooded areas (dark blue color).<\/span><\/p> Satellite/Sensor:<\/span><\/p> Sentinel-1 /Synthetic Aperture Radar (SAR)<\/span><\/p> Resolution:<\/span><\/p> 10 meters<\/span><\/p>