Emergency response to flooding following extreme weather and other events is limited by the lack of accurate and timely maps of flood extent and depth. Image-based flood mapping approaches are limited by daylight and miss areas obscured by buildings, clouds, cloud shadows, trees, and other vegetation. Alternative approaches based on hydrodynamic models depend on stream gauge data, which is available in only a limited number of locations where measuring equipment is installed.

When deployed as an automated workflow, the FIST model will decrease the delivery latency of critical wide area flood depth maps to emergency responders. Accurate and timely flood maps based on observed data will be invaluable for mobility, logistical, structural, and economic impact analysis.