dataset : LandCarbon Conterminous United States Burned Area and Severity Mosaics 2001-2050 Metadata

U.S. Geological Survey

usgs-landcarbon-burn-area

LandCarbon Conterminous United States Burned Area and Severity Mosaics 2001-2050 Metadata

The burn area and severity data were stochastically generated using a probabilistic ignition model and mechanistic fire-spread model. The ignition model consisted of a general linear model with a binary response, constructed by relating daily ignition locations in the monitoring trends in burn severity database (MTBS; Eidenshink et al 2007) to predictor variables including daily weather, fuel moisture, fire behavior indices, monthly and seasonal climate variables, and vegetation and land cover. In the simulations, the ignition model was used to stochastically generate ignition locations. After a location was generated, fires were spread using the minimum-travel time algorithm (MTT; Finney 2002) which generates spatially-explicit burn scars in relation to weather and fuel moisture conditions, fuels, and topography. Simulations were first calibrated using historic, observed weather data from 1984-2008 (Maurer et al. 2002) and then future projections were made using downscaled GCM data (Maurer et al. 2007). For this assessment, the climate change projections included data produced by the CCCma CGCM 3.1, CSIRO–Mk3.0, MIROC 3.2-medres GCMs for the A1B, A2, and B1 scenarios. Fuels and vegetation data were provided by the LANDFIRE project (Rollins 2008). Detailed information about the methods used to simulate burned area can be found in Hawbaker and Zhu (2012). Eidenshink, J., B. Schwind, K. Brewer, Z Zhu, B. Quayle and S. Howard, 2007, A project for monitoring trends in burn severity: Fire Ecology, v. 3, no. 1, p. 3–21, doi:10.4996/fireecology.0301003. Finney, M.A., 2002, Fire growth using minimum travel time methods: Canadian Journal of Forest Research, v. 32, no. 8, p. 1420–1424, doi:10.1139/x02-068. Hawbaker, T. and Z. Zhu. 2012. Projected Future Wildland Fires and Emissions for the Western United States. Chapter 8 in Zhu, Zhiliang, and Reed, B.C., eds., 2012, Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Western United States: U.S. Geological Survey Professional Paper 1797, 192 p. (Also available at http://pubs.usgs.gov/pp/1797/.) Maurer, E.P., L. Brekke, T. Pruitt, and P.B. Duffy, 2007, Fine-resolution climate projections enhance regional climate change impact studies: Eos, v. 88, no. 47, p. 504. Maurer, E.P., A.W. Wood, J.C. Adam, D.P. Lettenmaier, and B. Nijssen, 2002, A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States: Journal of Climate, v. 15, no. 22, p. 3237–3251, doi:10.1175/1520-0442(2002)0152.0.CO;2. Rollins, M.G., 2009, LANDFIRE; A nationally consistent vegetation, wildland fire, and fuel assessment: International Journal of Wildland Fire, v. 18, no. 3, p. 235–249, doi:10.1071/WF08088.

The spatial range for this dataset is 22.7541° to 47.975864° latitude, and -127.922278° to -74.013589° longitude. map (center)


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