| Autor: |
D. B. Bausch, Prativa Sharma, Kristy F. Tiampo, Lingcao Huang, Michael J. Willis, Margaret Glasscoe, Bandana Kar, Zhiqiang Chen, C. Simmons, R. Estrada, C. Woods |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
IGARSS |
| DOI: |
10.1109/igarss47720.2021.9553601 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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