Wildfire Suppression Difficulty Index 97th Percentile (2026)

SDI (Rodriguez y Silva et al. 2020) factors in topography, fuels, expected fire behavior under prevailing conditions, fireline production rates in various fuel types with and without heavy equipment, and access via roads, trails, or cross-country travel. SDI is currently classified into six categories representing low through extreme difficulty. Extreme SDI zones represented in red are “watch out” situations where engagement is likely to be very challenging given the combination of potential high intensity fire behavior and difficult suppression environment (high resistance fuel types, steep terrain, and low accessibility). Low difficulty zones represented in blue indicate areas where some combination of reduced potential for dangerous fire behavior and ideal suppression environment (low resistance fuel types, mellow terrain, and high accessibility) make suppression activities easier. SDI does not account for standing snags or other overhead hazards to firefighters, so it is not a firefighter hazard map. It is only showing in relative terms where it is harder or easier to perform suppression work. SDI incorporates flame length and heat per unit area from basic FlamMap runs (Finney et al. 2019). SDI is based on fire behavior modeled using regionally appropriate percentile fuel moisture conditions and uphill winds. This product uses the wind blowing uphill option to represent a consistent worst-case scenario. Input fuels data are updated to the most recent fire year using a crosswalk for surface and canopy fuel modifications for fires and fuel treatments that occurred after the most recent LANDFIRE version. For example, LANDFIRE 2016 model inputs are modified to incorporate fires (Monitoring Trends in Burn Severity (MTBS), Geospatial Multi- Agency Coordination (GeoMac), and Wildland Fire Interagency Geospatial Services (WFIGS) and fuel treatments (USFS Forest Activity Tracking System (FACTS) and DOI National Fire Plan Operations and Reporting System (NFPORS) hazardous fuels reduction treatments) from 2017-present. Road and trail inputs are developed from a combination of HERE 2020 Roads, USFS, and DOI road and trails databases. Hand crew and dozer fireline production rates are from FPA 2012 (Dillon et al. 2015). Classification of topography and accessibility thresholds are detailed in Rodriguez et al. (2020). Dillon, G.K.; Menakis, J.; Fay, F. (2015) Wildland Fire Potential: a tool for assessing wildfire risk and fuels management needs. In: Keane, R.E.; Jolly, M.; Parsons, R.; Riley, K., eds. Proceedings of the large wildland fires conference; May 19-23, 2014; Missoula, MT. Proc. RMRS-P-73. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 345 p. Finney, M.A.; Brittain, S.; Seli, R.C.; McHugh, C.W.; Gangi, L. (2019) FlamMap:Fire Mapping and Analysis System (Version 6.0) [Software]. Available from https://www.firelab.org/document/flammap-software Rodriguez y Silva, F.; O'Connor, C.D.; Thompson, M.P.; Molina, J.R.; Calkin, D.E. (2020). Modeling Suppression Difficulty: Current and Future Applications. International Journal of Wildland Fire. More detail on SDI Methods can be found on the RMA Sharepoint Site (RMA Dashboard Analytics --> Suppression Difficulty Index (SDI) folder.压制难度指数（Suppression Difficulty Index，SDI）（Rodriguez y Silva等人，2020年）综合考量了地形、可燃物、当前工况下的预期火灾行为、不同可燃物类型在配备与未配备重型装备时的火线生成速率，以及通过道路、步道或越野通行的可达性。 SDI目前被划分为六个等级，覆盖低难度至极端难度区间。其中以红色标注的极端SDI区域属于“需警惕”场景：结合潜在的高强度火灾行为与艰难扑救环境（高阻力可燃物类型、陡峭地形及低可达性），此类区域的扑救工作往往极具挑战性。以蓝色标注的低难度区域则表明，该区域兼具危险火灾行为发生概率较低与理想扑救环境（低阻力可燃物类型、平缓地形及高可达性）的特征，从而大幅简化扑救作业流程。 SDI未将立枯木或其他针对消防员的高空隐患纳入评估范畴，因此其并非消防员危险地图，仅能相对展示扑救作业的难易程度差异。 SDI整合了基础FlamMap火灾绘图与分析系统（FlamMap，Finney等人，2019年）运行输出的火焰长度与单位面积热量数据。该指数基于采用区域适配百分位可燃物湿度条件与上坡风模拟的火灾行为模型构建，本产品使用上坡风选项以表征统一的最坏场景。 输入的可燃物数据已更新至最近的火灾年度，通过交叉对照表整合了最新LANDFIRE版本发布后发生的火灾与可燃物处理带来的地表及冠层可燃物变化。例如，LANDFIRE 2016模型输入已整合2017年至今的火灾数据（来源于烧伤严重度监测趋势（Monitoring Trends in Burn Severity，MTBS）、地理空间多机构协调（Geospatial Multi-Agency Coordination，GeoMac）以及野外火灾跨机构地理空间服务（Wildland Fire Interagency Geospatial Services，WFIGS））与可燃物处理数据（来源于美国林务局森林活动跟踪系统（USFS Forest Activity Tracking System，FACTS）以及内政部国家火灾计划运营与报告系统（DOI National Fire Plan Operations and Reporting System，NFPORS）的危险可燃物削减处理项目）。 道路与步道输入数据整合了HERE 2020道路数据集（HERE 2020 Roads）、美国林务局（USFS）与内政部（DOI）的道路及步道数据库。手工作业队与推土机的火线生成速率数据来源于FPA 2012（Dillon等人，2015年）。地形与可达性阈值的分类细节详见Rodriguez等人（2020年）的研究。 Dillon, G.K.; Menakis, J.; Fay, F.（2015）《野外火灾潜力：评估野火风险与可燃物管理需求的工具》，收录于：Keane, R.E.; Jolly, M.; Parsons, R.; Riley, K. 主编. 大型野火会议论文集；2014年5月19日至23日；蒙大拿州米苏拉. 美国农业部林务局落基山研究站RMRS-P-73会议论文集. 科林斯堡, CO: 美国农业部林务局落基山研究站. 共345页。 Finney, M.A.; Brittain, S.; Seli, R.C.; McHugh, C.W.; Gangi, L.（2019）《FlamMap：火灾绘图与分析系统（版本6.0）》[软件]. 可从https://www.firelab.org/document/flammap-software获取。 Rodriguez y Silva, F.; O'Connor, C.D.; Thompson, M.P.; Molina, J.R.; Calkin, D.E.（2020）. 《模拟扑救难度：当前与未来应用》. 《国际野火杂志》。 关于SDI方法的更多细节可在RMA共享点网站查询（RMA仪表板分析 --> 压制难度指数（SDI）文件夹）。