甘肃省林火发生的驱动因子与火险区划

doi:10.11707/j.1001-7488.LYKX20230528

Abstract

Abstract:

Objective: The objective of this study is to explore the main influencing factors of forest fires in Gansu Province and the geographical division of forest fire risk in the Province. Method: Based on the historical fire data of Gansu Province from 2000 to 2021, ArcGIS 10.8 was used to extract the spatial information of topography, meteorology, vegetation, human activities, and socio-economic factors, and the Logistic regression model was used to determine the main driving factors of forest fires in Gansu Province. The standardized regression coefficient was used to test the relative importance of each driving factor to the occurrence of forest fires, and the ROC curve was used to test the fitting effect of the model. According to the prediction results of the model, the probability of forest fire occurrence was classified into hierarchical regions. Result: 1) The spatial logistic forest fire risk model established was well fitted. The AUC value of the five training samples was all greater than 0.970, and the prediction accuracy was between 89.6%?90.6%, and the AUC value of the whole sample was 0.972, and the prediction accuracy was 89.1%, indicating that the model was suitable for the predicting of forest fire occurrence in Gansu Province. 2) Elevation, slope, mean monthly temperature, vegetation coverage, and distance to the railway were positively correlated with the probability of forest fires, while mean monthly precipitation, distance to the highway, and distance to the settlement were negatively correlated with the probability of forest fires. 3) According to the standardized regression coefficients, the importance of each driving factor to the occurrence of forest fires in Gansu Province was ranked as follows: vegetation coverage (15.31) > mean monthly temperature (1.647) > slope (1.055) > distance to the railway (1.015) > elevation (1.007) > distance to the highway (0.985) > distance to the settlement (0.852) > mean monthly precipitation (0.808). 4) According to the probability of forest fires, the forest fire risk in Gansu Province was divided into five levels at equal intervals: very low fire danger area (0?0.2), low fire danger area (0.2?0.4), medium fire danger area (0.4?0.6), high fire danger area (0.6?0.8), and very high fire danger area (0.8?1), and the corresponding forest areas were 462 640, 850 160, 1 611 551, 1 715 681 and 705 050 hm², respectively. Conclusion: Vegetation coverage, mean monthly temperature, slope, distance to the railway, elevation, distance to the highway, distance to the settlement, and mean monthly precipitation are the main driving factors of forest fire occurrence in Gansu Province. The probability of forest fire occurrence is generally high in the southeast and low in the northwest, among which the extremely high fire danger areas are mainly distributed in Gannan Tibetan Autonomous Prefecture, Linxia Hui Autonomous Prefecture, Lanzhou and some areas of Longnan, and the high fire danger areas are mainly distributed in the southeast of Longnan and Tianshui, the western part of Pingliang, Lanzhou and some areas of Linxia Hui Autonomous Prefecture.

Key words: Gansu Province, logistic regression model, natural factors, human factors, fire hazard zoning

CLC Number:

S762.2

Zhenjia Lu,Yongzhong Luo,Xuhu Wang,Kangfeng Wang,Lipeng Ma,Cuntao Zhang,Peng Guo,Jing Ma,Liangsheng Zhao. Driving Factors of Forest Fire Occurrence and Fire Risk Zoning in Gansu Province[J]. Scientia Silvae Sinicae, 2025, 61(3): 63-71.

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模型变量 Model variables	极小值 Minimum value	极大值 Maximum value	均值 Mean value	标准差 Standard deviation
火点和随机点数量 Number of fire and random points	0	1	0.33	0.47
海拔 Elevation/m	721	5 110	2 090.74	799.64
坡度 Slope/（°）	0	48.74	11.51	10.5
月均降水量 Mean monthly precipitation/mm	1.88	91.75	40.33	23.45
月均气温 Mean monthly temperature/℃	–9.98	14.98	–5.53	3.67
单位面积GDP Per unit area GDP/ （10⁴yuan·km^-2）	0	29 506	431.66	2 440.61
人口密度 Population density/ （person·km^-2）	0	3 793	113.11	344.5
植被覆盖度 Vegetation coverage（%）	0	1	0.54	0.36
到公路距离 Distance to the highway/m	25	267 054	61 638.92	57 003.87
到铁路距离 Distance to the railway/m	6	296 618	49 783.31	46 619.01
到居民点距离 Distance to the settlement/m	49	666 745	8 362.7	7 970.1

模型变量 Model variables	VIF
海拔 Elevation	1.448
坡度 Slope	1.896
月均降水量 Mean monthly precipitation	3.873
月均气温 Mean monthly temperature	1.007
单位面积GDP Per unit area GDP	10.077
人口密度 Population density	10.436
植被覆盖度 Vegetation coverage	4.084
到公路距离 Distance to the highway	2.468
到铁路距离 Distance to the railway	2.218
到居民点距离 Distance to the settlement	1.392

模型变量 Model variables	样本1 Sample 1	样本2 Sample 2	样本3 Sample 3	样本4 Sample 4	样本5 Sample 5
海拔 Elevation	Y	Y	Y	Y	Y
坡度 Slope	Y	N	N	Y	Y
月均气温 Mean monthly temperature	Y	Y	Y	Y	Y
月均降水量 Mean monthly precipitation	Y	Y	Y	Y	Y
植被覆盖度 Vegetation coverage	Y	Y	Y	Y	Y
到公路距离 Distance to highway	Y	Y	Y	Y	Y
到铁路距离 Distance to the railway	Y	Y	Y	Y	Y
到居民点距离 Distance to the settlement	Y	Y	Y	Y	Y

模型变量 Model variables	估计系数 Estimated coefficient	标准误差 Standard error	卡方值 Chi-square value	Ｐ	标准化回归系数 Normalize regression coefficients
海拔 Elevation	0.007	0.001	65.527	0.000	1.007
坡度 Slope	0.054	0.018	8.776	0.003	1.055
月均降水量 Mean monthly precipitation	–0.213	0.018	134.158	0.000	0.808
月均气温 Mean monthly temperature	1.536	0.192	64.183	0.000	4.647
植被覆盖度 Vegetation coverage	11.939	1.025	135.586	0.000	15.31
到公路距离 Distance to the highway	–0.015	0.004	14.492	0.000	0.985
到铁路距离 Distance to the railway	0.015	0.004	11.669	0.001	1.015
到居民点距离 Distance to the settlement	–0.160	0.004	13.413	0.000	0.852
常数 Constant	–22.476	2.801	64.420	0.000	0.000

项目 Items	样本1 Sample 1	样本2 Sample 2	样本3 Sample 3	样本4 Sample 4	样本5 Sample 5	全样本 Full sample
曲线下面积 Area under the curve	0.973	0.973	0.973	0.971	0.975	0.972
显著水平 Significant level	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
预测准确率 Prediction accuracy(%)	90.1	89.6	90.2	90.6	90.4	89.1

Driving Factors of Forest Fire Occurrence and Fire Risk Zoning in Gansu Province

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项目Items	预测准确率 Prediction accuracy
项目Items	火点 Fire points	随机点 Random points	总预测准确率 Total prediction accuracy
建模样本 Modeling samples	93.5	81.6	89.4
独立检验样本 Independent test samples	63.8	89.5	82.0

序号 Serial number	火险概率 Probability of fire hazard	火险等级 Fire risk rating	森林面积 Area/ hm²	面积百分比 Percentage of area(%)
1	0≤P<0.2	极低火险 Very low fire risk	462 640	8.7
2	0.2≤P<0.4	低火险 Low fire risk	850 160	15.9
3	0.4≤P<0.6	中火险 Medium fire insurance	1 611 550	30.2
4	0.6≤P<0.8	高火险 High fire risk	1 715 680	32.1
5	0.8≤P<1	极高火险 Extremely high fire risk	705 050	13.1

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