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Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability...
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Polygon locations of fire perimeters in the Sky Island mountain ranges in the Madrean Archipelago Ecoregion of the southwestern United States and northern Mexico. These fires occurred from 1985 to 2011 and were mapped using Landsat satellite imagery.
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In Alaska, recent research has identified particular areas of the state where both a lack of soil moisture and warming temperatures increase the likelihood of wildfire. While this is an important finding, this previous research did not take into account the important role that melting snow, ice, and frozen ground (permafrost) play in replenshing soil moisture in the spring and summer months. This project will address this gap in the characterization of fire risk using the newly developed monthly water balance model (MWBM). The MWBM takes into account rain, snow, snowmelt, glacier ice melt, and the permafrost layer to better calculate soil moisture replenishment and the amount of moisture that is lost to the atmosphere...
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Wildfire and fuel treatment locations for the USFWS Pacific Southwest Region (California, Nevada, Klamath Basin OR) extracted from the Fire Management Information System (FMIS) on October 23, 2015, for fiscal years 1980-2015.
Solar radiation grids were produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This solar radiation grid was produced using the Area Solar Radiation tool in ArcGIS 10.1, using inputs of the associated 30m DEM.
Solar radiation grids were produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This solar radiation grid was produced using the Area Solar Radiation tool in ArcGIS 10.1, using inputs of the associated 30m DEM.
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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...
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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...
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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...
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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...
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This dataset represents 25 parallel longitudinal profiles that were extracted from terrestrial lidar point clouds taken during six survey periods. The six lidar surveys were conducted between 7 October 2010 and 8 October 2013. Over that time a colluvial hollow eroded into a fluvial channel. The longitudinal profiles show the topography of the colluvial hollow for each survey period. The width of the original colluvial hollow was approximately 1.25 m, and a longitudinal profile was extracted every 5 cm for the entire length of the hollow, resulting in 25 parallel longitudinal profiles. These data can be used to observe the transition of the colluvial hollow to a fluvial channel and furthermore they show the development...
Wildfire refugia are forest patches that are minimally-impacted by fire and provide critical habitats for fire-sensitive species and seed sources for post-fire forest regeneration. Wildfire refugia are relatively understudied, particularly concerning the impacts of subsequent fires on existing refugia. We opportunistically re-visited 122 sites classified in 1994 for a prior fire refugia study, which were burned by two wildfires in 2012 in the Cascade mountains of central Washington, USA. We evaluated the fire effects for historically persistent fire refugia and compared them to the surrounding non-refugial forest matrix. Of 122 total refugial (43 plots) and non-refugial (79 plots) sites sampled following the 2012...
Solar radiation grids were produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This solar radiation grid was produced using the Area Solar Radiation tool in ArcGIS 10.1, using inputs of the associated 30m DEM.
This imagery was collected and produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This imagery and associated metrics was produced using Landsat 5 and 7. This set of imagery and remote sensing metrics have the following file structure: 1. Each sub-folder in the Fires LC Map folder represents an individual fire. 2. Within the folder there are 8 raster tiffs. 1. XXX_post_refl.tif The at-sensor-reflectance of the postfire landsat scene, named with the PolyID unique identifier for the fire, stored in 8-bit i. Band 1 of the Tiff is Band 3 (Red) of Landsat ii. Band 2 of the Tiff is Band 4 (NIR) of Landsat iii. Band 3 of...


map background search result map search result map Burn Probability for Fireline Intensity Class 2, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 4, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 5, predicted for 2080 to 2100 for Rio Grande study area Burn Probability for Fireline Intensity Class 6, predicted for 2080 to 2100 for Rio Grande study area Region 8 FMIS Wildfire and Fuel Treatment Locations 1980-2015 Improving Characterizations of Future Wildfire Risk in Alaska Fourmile Canyon Wildfire Longitudinal Profile Data Future changes in southcentral U.S. wildfire probability due to climate change-Data Mapped fire perimeters from the Sky Island Mountains of US and Mexico: 1985-2011 Fourmile Canyon Wildfire Longitudinal Profile Data Mapped fire perimeters from the Sky Island Mountains of US and Mexico: 1985-2011 Burn Probability for Fireline Intensity Class 2, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 4, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 5, predicted for 2080 to 2100 for Rio Grande study area Burn Probability for Fireline Intensity Class 6, predicted for 2080 to 2100 for Rio Grande study area Future changes in southcentral U.S. wildfire probability due to climate change-Data Region 8 FMIS Wildfire and Fuel Treatment Locations 1980-2015 Improving Characterizations of Future Wildfire Risk in Alaska