The Lower San Antonio Watershed study area is approximately 1,485 square miles and covers portions of Bexar, Calhoun, DeWitt, Goliad, Guadalupe, Karnes, Refugio, Victoria, and Wilson Counties. This Risk MAP project is finalizing the Discovery phase, and areas are being selected for Risk Assessment and Identification. This study area extends from Kendall County down into Karnes County where it confluences with the San Antonio River. The Cibolo Creek study area is approximately 854 square miles. This Risk MAP project will leverage previously developed DFIRM hydraulic models, 2009/2010 LiDAR data, and 2013 LiDAR data to produce additional flood risk data products for an estimated 350 stream miles. This study area extends from Bandera County down into Bexar County where it confluences with the San Antonio River. The Medina River study area is approximately 1,348 square miles and is comprised of 2 major sub-watersheds, the Medina River Watershed and the Leon Creek Watershed. This Risk MAP project will seek to leverage previously developed DFIRM hydraulic models and 2009/2010 LiDAR data to produce additional flood depth and flood risk data products for approximately 250 stream miles. Both of these major sub-watersheds are predominately located within Bexar County. The Upper San Antonio study area is approximately 507 square miles and is comprised of 2 major sub-watersheds, the Upper San Antonio River Watershed and the Salado Creek Watershed. Each project includes three phases: “Discovery,” “Risk Identification and Assessment,” and “Regulatory Product Update.” These projects are supported by a combination of FEMA grant funding and SARA local match dollars and in-kind services. These are the Upper San Antonio River, the Medina River, Cibolo Creek, and Lower San Antonio River. This is powerful example of how geospatial analytics and up-to-date imagery of anywhere can affect the speed and accuracy of disaster response and long-term recovery.Projects are underway in each of the four major watersheds in the San Antonio River Basin. Using only two datasets covering Los Angeles, CA and Corpus Christi, TX, the model has reached an F1 score of 92.3% accuracy. Each image dataset was split into two components with 80% of the images reserved for testing and 20% for validation. Each dataset consisted of 200 different RGB, 15cm resolution, 2500x2500px images with an associated ground truth. Slingshot ran tests over two datasets for Los Angeles, CA, and Corpus Christi, TX. Identification of low risk staging areas with easy access to highways and hospitals.Given the appropriate raw imagery, labels, and ground truth images, Slingshot’s building extraction model makes a pixel-by-pixel classification and creates a semantically segmented mask. Slingshot’s Flood Mask layered on BAE’s GXP combined with geocoded imagery (source: Planet) of Memorial Dr. Map of observed flood extent using cloud penetrating SAR (data source: Sentinel-1) Slingshot’s flood depth mask highlighting varying degrees of flooding (data source: Planet) Slingshot’s flood mask of West Houston overlaid on RGB (data source: Planet) Take a look at the mapping they’ve done in the storm’s aftermath: BAE Systems leveraged their cloud-hosted GXP solutions to provide Team Rubicon’s disaster response teams with the ability to visualize and analyze Planet imagery and Slingshot products. Slingshot also used its algorithms to quickly identify flood relief and triage staging areas close to non-flooded roadways and optimal hospital routes. With this knowledge, they were able to highlight dry areas to assess search and rescue efforts to enable first responders and medical crews to safely reach those in need. Working with Team Rubicon and the BAE Systems Geospatial eXploitation Products™ (GXP®), Slingshot was able to use its flood detection algorithms on up-to-date satellite imagery to determine the extent of the flooding and its severity. When Hurricane Harvey made landfall in Houston earlier this month, Slingshot Aerospace, a Planet Application Developer Program partner, leapt into action.
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