Browsing by Author "Bausch, D."

Now showing 1 - 1 of 1
  • Thumbnail Image
    A Machine Learning Approach to Flood Depth and Extent Detection Using Sentinel 1A/B Synthetic Aperture Radar
    Tiampo, K.; Woods, C.; Huang, L.; Sharma, P.; Chen, Z.; Kar, B.; Bausch, D.; Simmons, C.; Estrada, R.; Willis, Michael J.; Glasscoe, M. (IEEE, 2021-01-01)
    The rising number of flooding events combined with increased urbanization is contributing to significant economic losses due to damages to structures and infrastructures. Here we present a method for producing all weather maps of flood inundation using a combination of synthetic aperture radar (SAR) remote sensing data and machine learning methods that can be used to provide information on the evolution of flood hazards to DisasterAware©, a global alerting system, that is used to disseminate flood risk information to stakeholders across the globe. While these efforts are still in development, a case study is presented for the major flood event associated with Hurricane Harvey and associated floods that impacted Houston, TX in August of 2017.