【目的】森林火险空间模拟和等级评价对森林防火具有重要意义。为确定不同区域林草资源防火的重点因素,对云南省的林草火险进行空间模拟和等级评价。【方法】采用2001—2014年的MODIS数据,选取反映植被状态、温度、地形和人类活动可达性等4个方面的火环境因素,通过设计抽样方案、训练集和检验集生成程序,得到35个数据集,开发70个地理加权Logistic回归模型,以交叉验证法评估模型性能,最终选择残差空间随机、可靠性和区分能力最优的模型做统计推断。将模拟的每期过火概率图重分为5类,相应火险类别分别记为“低”、“中”、“高”、“很高”、“极高”等级。【结果】火险类别中,“极高”等级占12.7%,“很高”等级占18.1%,二者可解释2001—2014年云南省80%的林草火灾,文山、红河、玉溪、楚雄、丽江、大理等6市的“极高”和“很高”等级面积占全省面积的71.5%,是全省的“重灾区”。【结论】“重灾区”应列为云南林草防火的重点区域,在防火的人、财、物上给予优先考虑。高温是云南省首要火险因素,其次为海拔、坡度、枯死植被、植被量,人类活动可达性影响相对较弱。影响火险的火环境因素在云南省内仅部分区域显著,按显著区及相对权重,云南省可分为西北、西南、西中Ⅰ、西中Ⅱ、东南和中部共6个区域,不同区域应因地制宜确定防火重点并布置防火资源。

【Objective】Spatial modeling and grade evaluation of forest and grass fire dangers are great significance in fire prevention. In this study, a framework of spatial non-stationarity was introduced to carry out fire danger modeling in Yunnan Province. 【Method】 Data from the Moderate Resolution Imaging Spectroradiometer(MODIS), four fire-influencing factors (vegetation status, temperature, topography, and accessibility), and geographically weighted Logistic regression (GWLR) were employed to model and evaluate the forest and grass fire danger. After checking the spatio-temporal distribution of fires during 2001 and 2014, an equal number of unburned and burned points from December to April were sampled according to the designed procedure. The sampled data were divided into seven groups (one group for two years); of these, four were selected to develop the GWLR model (i.e., training and inner validation subset) and three were used to validate the developed model (i.e., independent testing subset), which created thirty five datasets. After excluding potential multicollinearity among the independent variables, the 35 adaptive Gaussian GWLR models and 35 adaptive bi-square GWLR models were developed. Cross validation was utilized to evaluate the performance of the developed GWLR models. Statistical inference was carried out based on the optimal model. 【Result】 We concluded that attention should be paid to overfitting and spatial autocorrelation of residuals in the application of GWLR to fire danger studies as they may hamper fire prevention operations. The “extreme high” danger zone accounted for 12.7%, “very high” for 18.1%, and “high” for 19.0% of the forest and grass fires in Yunnan Province from 2001 to 2014. Together, the “extreme high” and “very high” zones accounted for 80% of these fires and could be labeled as the “key area” in the danger zone. We suggest that the locations of Wenshan, Honghe, Yuxi, Chuxiong, Lijiang, and Dali, which together account for 71.5% of the “key area,” should be recognized as the most fire-prone areas and must be given priority in receiving labor, funds, and goods for forest and grass fire prevention. High temperature was an all-important forest and grass fire-influencing factor in Yunnan Province, followed by altitude, slope, dead vegetation, and fraction of green vegetation. The accessibility of roads and villages also plays a role in controlling the spread of fire. The influence of environmental factors on the presence of fire presented significant spatial variability in this study; however, these factors are unique to the Yunnan Province. 【Conclusion】 According to the significant areas of fire-influencing factors and their relative weights, Yunnan Province can be divided into six fire prevention regions and requires the formulation of different fire prevention policies for each region.