Hazard assessment of forest fire in Miyun District of Beijing based on the subcompartment scale
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摘要:目的
森林火灾危险性评价是实现科学林火管理工作的重要前提和基础,基于小班尺度开展森林火灾危险性评价及其空间特征分析,可为林火精细化管理提供依据。
方法以密云区为研究对象,基于2019年森林资源二类调查小班数据、森林可燃物数据、气象数据、重要火源点等数据,构建密云区森林火灾危险性评价体系,应用层次分析法和熵权法相结合的主客观赋权法确定评价体系中各指标权重,根据评价体系中最终权重采用加权综合评价法计算各小班的危险性指数,依据自然断点分级法划分为高、中高、中低、低4个等级;采用全域和局域莫兰指数判断各小班之间的空间自相关性和聚集分布特征。
结果(1)基于小班尺度综合4类因子构建体系,权重分布比例合理,可较好地开展火灾危险性评价;(2)研究区内高等级、中高等级、中低等级、低等级危险性的小班面积占比分别为12.75%,19.01%,41.70%,26.54%。其中,高等级危险性小班以灌木林、侧柏林、油松林为主,小班面积占比分别为38.40%、25.76%、24.13%;(3)高等级危险性小班分布在研究区范围的东部以及中南部区域,从乡镇尺度分析,呈片状分布于巨各庄镇、高岭镇和新城子镇;(4)小班危险性的全域莫兰指数为0.241 3(大于0),说明密云区各小班存在一定的正相关性,即小班呈现出聚集分布的特征,采用局域莫兰指数分析发现火灾危险性等级为高−高聚集型小班的面积达34 637.77 hm²,占密云区面积的15.56%。
结论(1)构建的森林火灾危险性评价体系中,野外火源所占权重最大,是影响森林火灾危险性的主要因素;(2)高等级危险性小班区域灌木林占比较高,且聚集分布特征明显,根据权重结果,建议增强对野外火源和重点人群的监督和管理;另一方面,制定可燃物清理的标准和要求,定期在农林交错地区和火源点周围进行可燃物清理作业。
Abstract:ObjectiveForest fire hazard assessment is an important prerequisite and foundation for achieving scientific forest fire management. Conducting forest fire hazard assessment and spatial feature analysis on subcompartment scale can provide a basis for refined forest fire management.
MethodTaking the subcompartment of Miyun District as the research object, based on the data of forest resource secondary survey subcompartment, forest fuel data, meteorological data, important fire source points, etc. in 2019, a forest fire hazard assessment system was constructed. We used the subjective and objective weighting methods of combining analytic hierarchy process and entropy weight method to determine the weights of various indicators in the evaluation system. Based on the natural breakpoint classification method, four levels were divided as high, medium-high, medium-low, and low. Global and local Moran indices were used to determine the spatial autocorrelation and clustering distribution characteristics between subcompartments.
Result(1) Research was based on the construction of a comprehensive system of 4 types of factors at the subcompartment, with reasonable weight distribution ratios, which can effectively carry out fire hazard assessment. (2) The proportions of hazard subcompartment areas with high level, medium-high level, medium-low level, and low level were 12.75%, 19.01%, 41.70%, and 26.54%, respectively. Among them, the high-level hazard subcompartment was mainly composed of shrubbery, Platycladus orientalis forest, and Pinus tabuliformis forest, with subcompartment areas accounting for 38.40%, 25.76%, and 24.13%, respectively. (3) High level hazardous small classes were distributed in the eastern and central southern regions of the research area. From a township level analysis, they were distributed in a patchy pattern in Jugezhuang Town, Gaoling Town, and Xinchengzi Town. (4) The global Moran index of the hazard of subcompartments was 0.2413 (> 0), indicating that there was a certain positive correlation among the subcompartments in Miyun District and the subcompartments exhibited clustering distribution characteristics. Using the local Moran index analysis, it was found that the area of the subcompartments with a high to high clustering was 346 37.77 ha, accounting for 15.56% of the area of Miyun District.
Conclusion(1) In the forest fire hazard assessment system constructed in this article, the weight of outdoor fire sources is the largest, which is the main factor affecting the forest fire hazard. (2) The proportion of shrub forests in high-risk small class areas is relatively high, and the clustering distribution characteristics are obvious. Based on the weight results, it is recommended to strengthen the supervision and management of outdoor fire sources and key populations; on the other hand, establishing standards and requirements for combustible material cleaning, and combustible material cleaning operations were regularly carried out in areas where agriculture and forestry intersect and around fire sources.
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表 1 森林火灾危险性评价指标
Table 1 Forest fire hazard assessment index
准则层
Rule layer标准层
Standard layer描述
Description单位 Unit 森林可燃物
Forest fuel地表可燃物载量 Surface fuel load 单位面积灌木、草本、枯落物等可燃物的载量 Amount of surface fuel (shrub, herb, litter) per unit area t/hm2
t/ha细小可燃物载量 Fine fuel load 单位面积枯落物1(直径 < 0.6 cm 的小枝、叶和杂草)、枯落物2(直径0.6 ~ 2.5 cm的小枝、叶和杂草)等可燃物的载量 Total load of combustible materials such as litter 1 (twigs, leaves, and weeds with a diameter of less than 0.6 cm) and litter 2 (twigs, leaves, and weeds with a diameter of 0.6−2.5 cm) per unit area t/hm2
t/ha优势树种(组)可燃性 Dominant tree species (group) flammability 森林被引燃着火的难易程度以及着火后所表现出的燃烧状态和燃烧速度和火强度等的综合 Difficulty of forest ignition, as well as the combustion state (type of fire), combustion speed, and fire intensity exhibited after ignition 气象条件
Meteorological factor月大风日数 Monthly gale day 月平均出现瞬时风力5级或以上的天气日数 Monthly average number of weather days with instantaneous wind force 5 or above is expressed d 月平均风速 Monthly average wind speed 月每日平均风速的平均值 Average value of monthly daily average wind speed m/s 月平均降水量 Monthly mean precipitation 总降水量的月平均值 Monthly average of total rainfall mm 月平均气温 Monthly mean temperature 月每日平均气温的平均值Average daily temperature of the month ℃ 月最高温度 Monthly maximum temperature 月每日最高气温的最高值 The highest value of daily maximum temperature ℃ 月最小相对湿度 Monthly minimum relative humidity 月每日最小相对湿度的最小值 The minimum value of monthly daily minimum relative humidity % 野外火源
Outdoor fire source用火次数 Fire usage frequency 近20年,林区范围内发生的一般、较大森林火灾的总次数 Total number of general and major forest fires that have occurred within the forest area in the past 20 years 次数
times重要火源点个数 Number of important ignition source 林区范围内散坟、露营地、旅游景区、公墓、农村集体安葬点等火源点总数量 Total number of fire sources such as scattered graves, camping sites, tourist attractions, cemeteries, and rural collective burial sites within the forest area 无民事行为能力和限制民事行为能力人口数量 Number of people without or with limited capacity for civil conduct 林区范围内0 ~ 14岁人口、65岁(含)以上人口和残障人口总数量 Total number of people aged 0 − 14, aged 65 or above, and disabled within the forest area 地形因子
Topographical factor坡度 Slope 坡面的垂直高度和水平宽度的比值 Ratio of vertical height to
horizontal width of a slope(°) 坡向 Aspect 坡面的朝向 Orientation of slope 坡位 Slope position 坡面所处的地貌部位 Landform on which a slope is located 表 2 森林火灾危险性评价指标权重
Table 2 Weights of forest fire hazard assessment index
一级指标
Primary index一级指标
综合权重
Comprehensive
weight of first
level index二级指标
Secondary index二级指标
熵权法权重
Entropy weight
of secondary
index二级指标
层次分析法权重
Chromatography
analysis weight of
secondary index二级指标
综合权重
Comprehensive
weight of
secondary
index计算尺度
Computing scale森林可燃物
Forest fuel0.215 地表可燃物载量 Surface fuel load 0.020 0.110 0.065 小班
Subcompartment细小可燃物载量 Fine fuel load 0.040 0.140 0.090 小班
Subcompartment优势树种(组)可燃性
Dominant tree species (group) flammability0.020 0.100 0.060 小班
Subcompartment气象条件
Meteorological
factor0.245 月大风日数 Monthly gale day 0.050 0.050 0.050 小班
Subcompartment月平均风速
Monthly average wind speed0.040 0.040 0.040 小班
Subcompartment月平均降水量
Monthly mean precipitation0.030 0.060 0.045 小班
Subcompartment月平均气温
Monthly mean temperature0.040 0.040 0.040 小班
Subcompartment月最高温度
Monthly maximum temperature0.040 0.040 0.040 小班
Subcompartment月最小相对湿度
Monthly minimum relative humidity0.010 0.050 0.030 小班
Subcompartment野外火源
Outdoor fire source0.385 用火次数 Fire usage frequency 0.260 0.100 0.180 乡镇 Township 重要火源点数量
Number of important ignition sources0.130 0.100 0.115 乡镇 Township 无民事行为能力和限制民事行为能力人口数量 Number of people without or with limited capacity for civil conduct 0.120 0.060 0.090 乡镇 Township 地形因子
Topographical
factor0.155 坡度 Slope 0.140 0.040 0.090 小班
Subcompartment坡向 Aspect 0.030 0.040 0.035 小班
Subcompartment坡位 Slope position 0.030 0.030 0.030 小班
Subcompartment -
[1] 胡源, 赵凤君, 陈锋, 等. 气候变暖及大尺度气候波动对全球林火与森林碳排放的影响[J]. 陆地生态系统与保护学报, 2021, 1(1): 75−81. Hu Y, Zhao F J, Chen F, et al. Impacts of global warming and large-scale climate fluctuation on forest fires and forest carbon emissions[J]. Terrestrial Ecosystem and Conservation, 2021, 1(1): 75−81.
[2] 国务院第一次全国自然灾害综合风险普查领导小组办公室. 森林和草原火灾风险调查与评估[M]. 北京: 应急管理出版社, 2021. Office of the Leading Group for the First National Comprehensive Survey of Natural Disaster Risks under The State Council. Forest and grassland fire risk investigation and assessment[M]. Beijing: Emergency Management Press, 2021.
[3] Shu H, Qi S, Ning N, et al. Risk assessment of debris flow disaster: a case study of Wudu District in the south of Gansu Province, China[J]. Journal of Natural Disasters, 2016, 25(6): 34−41.
[4] Yukili L. Forest fire hazard rating assessment mapping in Sabah, Malaysia[D]. Subang Jaya: Universiti Putra Malaysia, 2015.
[5] 范晨. 基于GIS的森林火灾风险评价的分析与研究[D]. 北京: 北京交通大学, 2010. Fan C. Analysis and research on forest fire risk assessment based on GIS [D]. Beijing: Beijing Jiaotong University, 2010.
[6] Dvornik A A, Dvornik A M, Kurilenko R S, et al. Mapping of forest fire hazard depending on weather conditions using geoinformation technologies[J]. Proceedings of the National Academy of Sciences, 2021, 66(3): 320−332.
[7] Mitsopoulos I, Trapatsas P, Xanthopoulos G. SYPYDA: a software tool for fire management in Mediterranean pine forests of Greece[J]. Computers and Electronics in Agriculture, 2016, 121: 195−199. doi: 10.1016/j.compag.2015.12.011
[8] Walding N G, Williams H T P, McGarvie S, et al. A comparison of the US National Fire Danger Rating System (NFDRS) with recorded fire occurrence and final fire size[J]. International Journal of Wildland Fire, 2018, 27(2): 99−113. doi: 10.1071/WF17030
[9] 林业部森林防火办公室. 全国森林火险区划等级:LY 1063—1992[S]. 北京: 中华人民共和国林业部, 1992. Forest Fire Prevention Office of the Ministry of Forestry. National forest fire risk zoning level: LY 1063−1992[S]. Beijing: Ministry of Forestry of the PRC, 1992.
[10] Krueger E S, Ochsner T E, Quiring S M, et al. Measured soil moisture is a better predictor of large growing-season wildfires than the Keetch–Byram drought index[J]. Soil Science Society of America Journal, 2017, 81(3): 490−502. doi: 10.2136/sssaj2017.01.0003
[11] 胡海清, 罗斯生, 罗碧珍, 等. 森林可燃物含水率及其预测模型研究进展[J]. 世界林业研究, 2017, 30(3): 64−69. Hu H Q, Luo S S, Luo B Z, et al. Forest fuel moisture content and its prediction model[J]. World Forestry Research, 2017, 30(3): 64−69.
[12] You W, Lin L, Wu L, et al. Geographical information system-based forest fire risk assessment integrating national forest inventory data and analysis of its spatiotemporal variability[J]. Ecological Indicators, 2017, 77: 176−184. doi: 10.1016/j.ecolind.2017.01.042
[13] 蒋春颖, 杨雪清, 张国丽, 等. 森林火灾风险评估技术体系探讨[J]. 林业资源管理, 2023(2): 17−26. Jiang C Y, Yang X Q, Zhang G L, et al. Discussion on the technical system of forest fire risk assessment[J]. Forest Resources Management, 2023(2): 17−26.
[14] Xie M X, Wang J Y, Yang A M, et al. DPSIR model-based evaluation index system for geographic national conditions[J]. Wuhan University Journal of Natural Sciences, 2017, 22(5): 402−410. doi: 10.1007/s11859-017-1265-y
[15] 牛若芸, 翟盘茂, 孙明华. 森林火险气象指数及其构建方法回顾[J]. 气象, 2006, 32(12): 3−9. doi: 10.3969/j.issn.1000-0526.2006.12.001 Niu R Y, Zhai P M, Sun M H. Review of forest fire danger weather indexes and their calculation methods[J]. Meteorological Monthly, 2006, 32(12): 3−9. doi: 10.3969/j.issn.1000-0526.2006.12.001
[16] 田晓瑞, 舒立福, 王明玉, 等. 利用Keetch-Byram干旱指数预测森林火险[J]. 火灾科学, 2003, 12(3): 151−155. doi: 10.3969/j.issn.1004-5309.2003.03.005 Tian X R, Shu L F, Wang M Y, et al. Using the Keetch-Byram drought index to predict forest fire risk[J]. Fire Safety Science, 2003, 12(3): 151−155. doi: 10.3969/j.issn.1004-5309.2003.03.005
[17] Cohen J D, Deeming J E. The national fire-danger rating system: basic equations[R]. Berkeley, CA: Pacific Southwest Forest and Range Experiment Station, 1985.
[18] 舒立福, 张小罗, 戴兴安, 等. 林火研究综述(Ⅱ): 林火预测预报[J]. 世界林业研究, 2003, 16(4): 34−37. doi: 10.3969/j.issn.1001-4241.2003.04.007 Shu L F, Zhang X L, Dai X A, et al. Forest fire research(Ⅱ): fire forecast[J]. World Forestry Research, 2003, 16(4): 34−37. doi: 10.3969/j.issn.1001-4241.2003.04.007
[19] 丽娜. 气候变化背景下内蒙古草原火灾风险动态评价与预估研究[D]. 长春: 东北师范大学, 2021. Li N. Dynamic risk assessment and prediction of grassland fire disaster in Inner Mongolia under climate change[D]. Changchun: Northeast Normal University, 2021.
[20] 国家林业局森林防火指挥部办公室. 全国森林火险区划等级: LY/T 1063—2008[S]. 北京:国家林业局, 2008. Office of the Forest Fire Prevention Headquarters of the State Forestry Administration. National forest fire risk zoning level. LY/T 1063−2008[S]. Beijing: State Forestry Administration, 2008.
[21] 陈羚, 陈锋, 牛树奎, 等. 北京鹫峰景观格局空间特征与森林火险的关联分析[J]. 北京林业大学学报, 2021, 43(6): 41−49. doi: 10.12171/j.1000-1522.20180431 Chen L, Chen F, Niu S K, et al. Correlation analysis between the spatial characteristics of landscape pattern and risk of forest fire in Jiufeng Forest Park of Beijing[J]. Journal of Beijing Forestry University, 2021, 43(6): 41−49. doi: 10.12171/j.1000-1522.20180431
[22] 宗学政, 田晓瑞, 刘畅. 林分尺度上的森林火灾风险评估方法及应用[J]. 林业科学研究, 2021, 34(5): 69−78. Zong X Z, Tian X R, Liu C. Forest fire risk assessment methods and applications at the stand scale[J]. Forest Research, 2021, 34(5): 69−78.
[23] 吴明山, 周汝良, 张明莎, 等. 林分尺度上的森林火险动态评估[J]. 林业资源管理, 2020(2): 126−134. Wu M S, Zhou R L, Zhang M S, et al. A dynamic assessment of forest fire risk on stand scale[J]. Forest Resources Management, 2020(2): 126−134.
[24] 罗丹, 王庆飞, 晁碧霄, 等. 广州市森林和城镇交界域林分尺度上的火险等级评价[J]. 林业资源管理, 2023(3): 56−64. Luo D, Wang Q F, Zhao B X, et al. Evaluation on fire risk rating of forest stand in wildland-urban interface: a case study of Guangzhou City[J]. Forest Resources Management, 2023(3): 56−64.
[25] Goldarag Y J, Mohammadzadeh A, Ardakani A S. Fire risk assessment using neural network and logistic regression[J]. Journal of the Indian Society of Remote Sensing, 2016, 44(6): 885−894. doi: 10.1007/s12524-016-0557-6
[26] Choi M Y, Jun S. Fire risk assessment models using statistical machine learning and optimized risk indexing[J/OL]. Applied Sciences, 2020, 10(12): 4199[2023−08−30]. https://www.mdpi.com/2076-3417/10/12/4199.
[27] Vilà-Vilardell L, Keeton W S, Thom D, et al. Climate change effects on wildfire hazards in the wildland-urban-interface–Blue pine forests of Bhutan[J/OL]. Forest Ecology and Management, 2020, 461: 117927[2023−08−30]. https://www.sciencedirect.com/science/article/abs/pii/S0378112719319024.
[28] 宗学政, 田晓瑞, 马帅, 等. 基于火模拟的森林火灾风险定量评估: 以中国林业科学研究院亚热带林业实验中心为例[J]. 北京林业大学学报, 2022, 44(9): 83−90. doi: 10.12171/j.1000-1522.20210328 Zong X Z, Tian X R, Ma S, et al. Quantitative assessment for forest fire risk based on fire simulation: taking the subtropical forest experimental center of Chinese Academy of Forestry as an example[J]. Journal of Beijing Forestry University, 2022, 44(9): 83−90. doi: 10.12171/j.1000-1522.20210328
[29] 张恒, 王轩, 张鑫, 等. 内蒙古赤峰市森林火险等级评价及火灾危险性评估[J]. 西南林业大学学报(自然科学), 2019, 39(2): 143−150. Zhang H, Wang X, Zhang X, et al. Forest fire danger rating and fire hazard assessment in Chifeng City of Inner Mongolia[J]. Journal of Southwest Forestry University (Natural Science), 2019, 39(2): 143−150.
[30] 陈羚. 北京市妙峰山林场景观安全与火灾危险性研究[D]. 北京: 北京林业大学, 2019. Chen L. Study on pattern of landscape security and fire hazard in Miaofengshan Mountain Forest Farm, Beijing [D]. Beijing: Beijing Forestry University, 2019.
[31] 周长明, 齐海超, 魏帅, 等. 基于GIS与AHP的黑龙江大兴安岭森林雷击火危险性划分[J]. 黑龙江气象, 2021, 38(3): 33−35. Zhou C M, Qi H C, Wei S, et al. Classification of forest lightning fire risk in the Greater Xing’an Mountains of Heilongjiang Province based on GIS and AHP[J]. Heilongjiang Meteorology, 2021, 38(3): 33−35.
[32] 王博, 杨雪清, 蒋春颖, 等. 基于GIS的北京市延庆区森林火灾蔓延风险[J]. 林业科学, 2023, 59(8): 90−101. Wang B, Yang X Q, Jiang C Y, et al. Forest fire spread risk in Yanqing District of Beijing based on GIS[J]. Scientia Silvae Sinicae, 2023, 59(8): 90−101.
[33] 鲁绍伟, 余新晓, 刘凤芹, 等. 北京八达岭林场森林燃烧性及防火措施研究[J]. 北京林业大学学报, 2006, 28(3): 109−114. doi: 10.3321/j.issn:1000-1522.2006.03.019 Lu S W, Yu X X, Liu F Q, et al. Forest fuel combustibility and methods for fire prevention at the Badaling Forest Farm, Beijing[J]. Journal of Beijing Forestry University, 2006, 28(3): 109−114. doi: 10.3321/j.issn:1000-1522.2006.03.019
[34] 牛树奎, 崔国发, 雷鸣, 等. 北京喇叭沟门林区森林燃烧性及防火区研究[J]. 北京林业大学学报, 2000, 22(4): 109−112. doi: 10.3321/j.issn:1000-1522.2000.04.020 Niu S K, Cui G F, Lei M, et al. Study on the forest combustibility and the fire districts in Labagoumen Forest region[J]. Journal of Beijing Forestry University, 2000, 22(4): 109−112. doi: 10.3321/j.issn:1000-1522.2000.04.020
[35] 周玉祥, 赵玉, 聂仁东, 等. 下辽河平原土地沙漠化程度及预测研究[J]. 生态环境学报, 2023, 32(6): 1133−1139. Zhou Y X, Zhao Y, Nie R D, et al. Characterization and prediction of land desertification in the lower Liaohe River Plain[J]. Ecology and Environmental Sciences, 2023, 32(6): 1133−1139.
[36] 徐建华. 现代地理学中的数学方法[M]. 北京: 高等教育出版社, 2004. Xu J H. Mathematical methods in modern geography[M]. Beijing: Higher Education Press, 2004.
[37] 孙朝锋, 吴立, 黄川容, 等. 基于GIS的福建省塑料大棚风害风险评估与区划[J]. 气象与环境科学, 2022, 45(4): 67−73. Sun C F, Wu L, Huang C R, et al. Risk assessment and zoning of wind damage in plastic greenhouses in Fujian Province based on GIS[J]. Meteorological and Environmental Science, 2022, 45(4): 67−73.
[38] 王娟, 牛晓宇, 孙亚玲. 甘肃省黑河中游段河流生态系统健康评价[J]. 陕西水利, 2023(9): 80−83. Wang J, Niu X Y, Sun Y L. Health evaluation of river ecosystem in the middle reaches of Heihe River in Gansu Province[J]. Shaanxi Water Resources, 2023(9): 80−83.
[39] 李洁, 郭梦晓, 高雯珂. 基于GIS的河南省洪涝灾害风险评估[J]. 现代农业科技, 2023, 837(7): 149−152, 158. Li J, Guo M X, Gao W K. Assessment of flood disaster risk in Henan Province based on GIS[J]. Modern Agricultural Sciences and Technology, 2023, 837(7): 149−152, 158.
[40] 邬建国. 景观生态学: 格局、过程、尺度与等级[M]. 2版. 北京: 高等教育出版社, 2007. Wu J G. Landscape ecology: patterns, processes, scales, and levels[M]. 2nd ed. Beijing: Higher Education Press, 2007.
[41] Anselin L. Local indicators of spatial association—LISA[J]. Geographical Analysis, 1995, 27(2): 93−115. doi: 10.1111/j.1538-4632.1995.tb00338.x
[42] 侯丽丽, 都瓦拉, 银山, 等. 基于牧户尺度的草原火灾风险评价: 以东乌珠穆沁旗为例[J]. 草业学报, 2021, 30(5): 1−12. doi: 10.11686/cyxb2020200 Hou L L, Duwala, Yin S, et al. Risk assessment of grassland fires at the herder scale: the Dongwuzhumuqin Banner as an example[J]. Acta Prataculturae Sinica, 2021, 30(5): 1−12. doi: 10.11686/cyxb2020200
[43] 安佳怡, 冯仲科, 马天天, 等. 基于GIS格网的重庆合川区森林火险等级区划[J]. 中南林业科技大学学报, 2022, 42(9): 91−101. An J Y, Feng Z K, Ma T T, et al. Zoning of forest fire risk levels in the Hechuan District of Chongqing based on GIS grid[J]. Journal of Central South University of Forestry & Technology, 2022, 42(9): 91−101.
[44] 王露秋. 基于GIS技术的洪雅县森林火险等级区划[D]. 成都: 四川农业大学, 2018. Wang L Q. Classification of forest fire risk in Hongya County based on GIS technology[D]. Chengdu: Sichuan Agricultural University, 2018.
[45] 张志强, 殷继艳. 西南高山林区森林火灾风险评价研究[J]. 中国应急救援, 2021(5): 30−35. Zhang Z Q, Yin J Y. Research on forest fire risk assessment in high mountain forest areas in Southwest China[J]. China Emergency Rescue, 2021(5): 30−35.
[46] 苏立娟, 何友均, 陈绍志. 1950—2010年中国森林火灾时空特征及风险分析[J]. 林业科学, 2015, 51(1): 88−96. Su L J, He Y J, Chen S Z. Temporal and spatial characteristics and risk analysis of forest fires in China from 1950 to 2010[J]. Scientia Silvae Sinicae, 2015, 51(1): 88−96.
[47] Catry F X, Rego F C, Bacao F, et al. Modeling and mapping wildfire ignition risk in Portugal[J]. International Journal of Wildland Fire, 2009, 18(8): 921−931. doi: 10.1071/WF07123
[48] 王武建. 2001—2016年安徽省森林火灾发生的时间趋势及火源特征[J]. 现代农业科技, 2023(17): 131−133, 138. doi: 10.3969/j.issn.1007-5739.2023.17.034 Wang W J. The time trend and fire source characteristics of forest fires in Anhui Province from 2001 to 2016[J]. Modern Agricultural Science and Technology, 2023(17): 131−133, 138. doi: 10.3969/j.issn.1007-5739.2023.17.034
[49] 吕常笑, 秦乃花, 李萍, 等. 山东省森林火灾时空分布及火源特征研究[J]. 森林防火, 2023, 41(2): 1−6. Lü C X, Qin N H, Li P, et al. Study on the spatiotemporal distribution and fire source characteristics of forest fires in Shandong Province[J]. Journal of Wildland Fire Science, 2023, 41(2): 1−6.
[50] 王秋华, 肖慧娟, 徐盛基, 等. 滇中安宁“3·29”重大森林火灾火烧迹地灌木林的燃烧性研究[J]. 安全与环境学报, 2016, 16(1): 138−141. Wang Q H, Xiao H J, Xu S J, et al. A study on the burning characteristics of shrubs in the “3.29” major forest fire in Anning, Central Yunnan[J]. Journal of Safety and Environment, 2016, 16(1): 138−141.
[51] 李顺, 吴志伟, 梁宇, 等. 大兴安岭林火发生的时空聚集性特征[J]. 生态学杂志, 2017, 36(1): 198−204. Li S, Wu Z W, Liang Y, et al. The temporal and spatial clustering characteristics of forest fires in the Great Xing’an Mountains[J]. Chinese Journal of Ecology, 2017, 36(1): 198−204.
[52] 肖良成, 刘同香, 蔡玉轩. 基于CRITIC的野外火源因素的重要度分析[J]. 林业科技通讯, 2022(12): 47−49. Xiao L C, Liu T X, Cai Y X. Importance analysis of field fire source factors based on CRITIC technical research[J]. Forest Science and Technology, 2022(12): 47−49.
[53] Reiner A L, Baker C, Wahlberg M, et al. Region-specific remote-sensing models for predicting burn severity, basal area change, and canopy cover change following fire in the southwestern United States[J/OL]. Fire, 2022, 5(5): 137[2023−09−10]. https://doi.org/10.3390/fire5050137.
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