Modeling data for burn severity of the East Troublesome and Grizzly Creek for integration with post-fire debris flow in the upper Colorado River basin, USA
These data were compiled for/to provide an example and assess methods and results of pre-fire estimation of predicted differenced normalized burn ration (dNBR) for predicting post-fire debris flow hazard classification. Objective(s) of our study were to develop predictive models for burn severity, using variables of pre-fire conditions, for two large wildfires from 2020 in Colorado, USA. These data represent pre-fire predictions of post-fire differenced normalized burn ratio (dNBR) as a proxy of burn severity and further understand pre-fire modeling of burn severity. These data were collected/created in the fire perimeters the East Troublesome Fire (10/14/2020 – 11/30/2020) and the Grizzly Creek Fire (8/10/2020 – 12/18/2020), Colorado, USA. These data were collected/created by use of random forest modeling of variables representing pre-fire conditions (satellite spectral data, landscape biophysical data, GIS topographic data, and meteorological/climate data) against observed estimates of post-fire difference in normalized burn ratio (dNBR). These data can be used to provide estimates of burn severity for post-fire hazard analysis.
Citation Information
Publication Year | 2024 |
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Title | Modeling data for burn severity of the East Troublesome and Grizzly Creek for integration with post-fire debris flow in the upper Colorado River basin, USA |
DOI | 10.5066/P9T077XK |
Authors | Adam G Wells, Todd J Hawbaker, Paul F Steblein, John (Kevin) K. Hiers, Rachel A Loehman, Jason W Kean |
Product Type | Data Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Southwest Biological Science Center - Flagstaff, AZ, Headquarters |
Rights | This work is marked with CC0 1.0 Universal |