Скачать или смотреть FOSS4G 2021 - Integrating Remote Sensed and Modeling data for Local Flood Prediction and Risk Asses

Integrating Remote Sensed and Modeling data for Local Flood Prediction and Risk Assessment

There haven’t been global efforts to identify and determine global flood risk areas and consistently support first responders in the event of a flood, although flooding impacts over half a billion people every year. The lack of objective knowledge of the impact of flooding after the fact, first relief agency assistance is often constrained and therefore less effective. However, these humanitarian catastrophes could be reduced with better transformation of existing observational and modeling technologies into information useful to local populations and decision makers.
Here I present a state-of-the-art mobile, globally-scoped, flood prediction, monitoring capabilities and risk evaluations platform that includes high resolution flood information to better serve local needs. The platform builds upon already available NASA-supported global flood systems, including the DFO - Flood Observatory satellite-based hydrological gauging stations, UMD Global Flood Monitoring System (GFMS) and have these integrated with the European Commission’s GloFAS, and SAR-based high-resolution flood mapping.

Please see the abstract above

Authors and Affiliations –
DFO Flood Observatory, University of Colorado

Track –
Transition to FOSS4G

Topic –
FOSS4G implementations in strategic application domains: land management, crisis/disaster response, smart cities, population mapping, climate change, ocean and marine monitoring, etc.

Level –
1 - Principiants. No required specific knowledge is needed.

Language of the Presentation –
English