Filters: Tags: burn probability (X) > Categories: Data (X)
22 results (23ms)
Filters
Date Range
Extensions Types Contacts
Tag Types Tag Schemes |
Burn probability (BP) raster dataset predicted for the 2080-2100 period in the Rio Grande area was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5 Representative Concentration Pathway.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
future climate,
gis,
rio grande,
Burn probability (BP) for Fireline Intensity Class 6 (FIL6) with flame lengths in the range of 3.7-15 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 2 (FIL2) with flame lengths in the range of 0.6-1.2 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 5 (FIL5) with flame lengths in the range of 2.4-3.7 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 4 (FIL4) with flame lengths in the range of 1.8-2.4 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) raster dataset predicted for the 2020-2040 period in the Rio Grande area was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5 Representative Concentration Pathway.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
future climate,
gis,
rio grande,
Burn probability (BP) for Fireline Intensity Class 1 (FIL1) with flame lengths in the range of 0-0.6 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 3 (FIL3) with flame lengths in the range of 1.2-1.8 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 1 (FIL1) with flame lengths in the range of 0-0.6 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 4 (FIL4) with flame lengths in the range of 1.8-2.4 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 6 (FIL6) with flame lengths in the range of 3.7-15 m predicted for the 2020-2040 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 6 (FIL6) with flame lengths in the range of 3.7-15 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) raster dataset predicted for the 2050-2070 period in the Rio Grande area was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5 Representative Concentration Pathway.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
future climate,
gis,
rio grande,
Burn probability (BP) for Fireline Intensity Class 4 (FIL4) with flame lengths in the range of 1.8-2.4 m predicted for the 2020-2040 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 5 (FIL5) with flame lengths in the range of 2.4-3.7 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 2 (FIL2) with flame lengths in the range of 0.6-1.2 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 2 (FIL2) with flame lengths in the range of 0.6-1.2 m predicted for the 2020-2040 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 3 (FIL3) with flame lengths in the range of 1.2-1.8 m predicted for the 2020-2040 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) for Fireline Intensity Class 5 (FIL5) with flame lengths in the range of 2.4-3.7 m predicted for the 2020-2040 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: burn probability,
fire,
fireline intensity,
future climate,
gis,
Burn probability (BP) models the likelihood that a location could burn. However, predicting BP is extremely challenging, because fire behavior varies strongly among landscapes and with changing weather conditions and wildfire spread simulations are computationally intensive and require integration of data with large spatial and temporal variability. In this data release we include the monthly BP estimation for the state of California, USA for the 2015-2019 period produced using a machine learning model and two different sets of input features. For the first case, the baseline, the model used all available input features to predict BP. The second output set corresponds to the BP predictions when the model used only...
Categories: Data;
Tags: California,
Climatology,
Ecology,
Land Use Change,
USGS Science Data Catalog (SDC),
|
|