{
 "culture": "en-US",
 "name": "SDI_30m",
 "guid": "",
 "catalogPath": "",
 "snippet": "This dataset is a 30-m cell size raster representing Suppression Difficulty Index (SDI) across the project area. Wildfire Suppression Difficulty Index is a quantitative rating of relative difficulty in performing fire control work. SDI factors in topography, fuels, expected fire behavior under severe fire weather conditions, firefighter line production rates in various fuel types, and accessibility (distance from roads/trails) to assess relative suppression effort.Severe fire behavior was modeled in FlamMap at 30m resolution with 15 mph up-slope winds and fully cured fuels. Non-burnable fuel models 91, 92, 93, 98 as well as custom urban fuel models 251 and 252 were set to a SDI value of 0. Custom burnable agriculture fuel models 241 and 242 were set to the production rates of GR1 and GR2 respectively.The SDI can be used to help inform strategic and tactical fire management decisions. Additional information on the SDI can be found in the following references:Rodriguez y Silva, F.; O\u2019Connor, C.D.; Thompson, M.P.; Molina, J.R.; Calkin, D.E. (accepted). Modeling Suppression Difficulty: Current and Future Applications. International Journal of Wildland Fire.O\u2019Connor, C.D., Thompson, M.P., Rodriguez y Silva, F. 2016. Getting ahead of the wildfire problem: quantifying and mapping management challenges and opportunities.Geosciences, 6(3), 35; doi: 10.3390/geosciences6030035Rodríguez y Silva, F, Martínez, JRM, González-Cabán, A (2014) A methodology for determining operational priorities for prevention and suppression of wildland fires.International Journal of Wildland Fire 23, 544-554.",
 "description": "",
 "summary": "This dataset is a 30-m cell size raster representing Suppression Difficulty Index (SDI) across the project area. Wildfire Suppression Difficulty Index is a quantitative rating of relative difficulty in performing fire control work. SDI factors in topography, fuels, expected fire behavior under severe fire weather conditions, firefighter line production rates in various fuel types, and accessibility (distance from roads/trails) to assess relative suppression effort.Severe fire behavior was modeled in FlamMap at 30m resolution with 15 mph up-slope winds and fully cured fuels. Non-burnable fuel models 91, 92, 93, 98 as well as custom urban fuel models 251 and 252 were set to a SDI value of 0. Custom burnable agriculture fuel models 241 and 242 were set to the production rates of GR1 and GR2 respectively.The SDI can be used to help inform strategic and tactical fire management decisions. Additional information on the SDI can be found in the following references:Rodriguez y Silva, F.; O’Connor, C.D.; Thompson, M.P.; Molina, J.R.; Calkin, D.E. (accepted). Modeling Suppression Difficulty: Current and Future Applications. International Journal of Wildland Fire.O’Connor, C.D., Thompson, M.P., Rodriguez y Silva, F. 2016. Getting ahead of the wildfire problem: quantifying and mapping management challenges and opportunities.Geosciences, 6(3), 35; doi: 10.3390/geosciences6030035Rodríguez y Silva, F, Martínez, JRM, González-Cabán, A (2014) A methodology for determining operational priorities for prevention and suppression of wildland fires.International Journal of Wildland Fire 23, 544-554.",
 "title": "SDI_30m",
 "tags": [
  "DNRC",
  "MWRA",
  "Test"
 ],
 "type": "Image Service",
 "typeKeywords": [
  "ArcGIS Server",
  "Data",
  "Image Service",
  "Service"
 ],
 "thumbnail": "",
 "url": "https://testgis.dnrc.mt.gov/arcgis",
 "minScale": 8365956.08266527,
 "maxScale": 261436.12758329,
 "spatialReference": "NAD_1983_StatePlane_Montana_FIPS_2500",
 "accessInformation": "",
 "licenseInfo": "",
 "portalUrl": ""
}