Ellicott City Machine Learning-Based Flood Alert System
Description
This project developed a model capable of learning the implicit rainfall-runoff relationships of the Tiber-Hudson Watershed, with a particular focus on understanding how these relationships contribute to flooding in Ellicott City.
Disaster Risk Response Stage
Preparedness
Category
Flood Modeling
Temporal Use
None
Input Network
CEOS
GEO
GEO
Input Network Member
NASA
Provider Organization
NASA GSFC
Point of Contact
John Bolten
E-mail
Geographic Domain
Local
Geographic Product Locations
Unknown
Geographic Product Locations - Detailed
Producing Daily Global Coverage?
No
Globally Extensible
Yes
Product Delivery Latency
N/A
Data Type
Machine learning-based appraoch leveraging NASA EO and in-situ observations
Associated Capacity Development Resources
None
Product Format
N/A
Archived
No
Tailored Service Available
Unknown
License Type
Unknown
Spatial Extent
N/A
Spatial Scale
N/A
Caveats
N/A
Frequency
N/A
Overpass Latency
N/A
Downlink Latency
N/A
Processing Latency
N/A
Impacted By Cloud Shadows
Unknown
Impacted By Terrain Shadows
Unknown
Status
In Development
Input By
John Murray, NASA Applied Sciences
Notes
None
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