Table 3 Description of datasets used in this study
From: Simulating flood risk in Tampa Bay using a machine learning driven approach
Dataset | Data sources | Temporal resolution | Spatial resolution/ Data types | Data output |
|---|---|---|---|---|
Hurricane Irma-induced flood damage data | FEMA | 2017 | Points | Flood damage points |
The National Flood Hazard Layer (NFHL) | FEMA | 2024 | Polygon | FEMA 100-year flood plain map (SFHA) |
JRC Global Surface Water | Pekel et al.72 | 2020 | 30 m | Distance from waterbodies |
3DEP DEM | USGS | – | 10 m | Elevation, slope, aspect, curvature, TWI, drainage density |
UCSB-CHG/CHIRPS/DAILY | CHIRPS | 2017 | 5566 m | Precipitation |
Sentinel 2 | ESA | 2017 | 10 m | NDVI, NDBI |
US Building Footprints | Microsoft | 2020 | Polygon | Building density |
Primary and Secondary Road | US Census Bureau | 2023 | Polyline | Road density |
Census data | US Census Bureau | 2020 | Polygon (Block groups) | Vulnerability factors |
