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Remote Sensing for Natural Resources    2025, Vol. 37 Issue (3) : 152-161     DOI: 10.6046/gyzyyg.2023383
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Multifactor-based assessment of forest fire risk in Chongqing City, China
CHEN Yanying1(), YOU Yangsheng2(), YANG Qian3, WANG Yanbo4
1. CMA Key Open Laboratory of Transforming Climate Resources to Economy, Chongqing Institute of Meteorological Sciences, Chongqing 401147, China
2. School of Civil Engineering,Chongqing University Chongqing 400045, China
3. Chongqing Meteorological Station, Chongqing 401147, China
4. Chaoyang Normal University, Chaoyang 122000, China
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Abstract  

By objectively assessing the response of forest fires to factors like terrain, vegetation, and human activities, this study aims to provide technical guidance for forest fire prevention and risk zoning in Chongqing City, China. In this study, 1 206 historical forest fire data of Chongqing City from 2000 to 2022 were used as dependent variables. The height, slope, terrain ruggedness, vegetation cover, land cover classification, and road network distance data were utilized as forest fire risk factors. With these data, a piecewise function was established to obtain the single-factor risk probabilities of forest fires. Based on the criteria importance through intercriteria correlation (CRITIC), the weights of the single-factor risk probabilities of forest fires were calculated to derive the spatial distribution of weighted forest fire risk probabilities in Chongqing City. Finally, according to the risk probabilities of forest fires, the forest fire risk in Chongqing City was divided into the low, relatively low, relatively high, high, and extremely high levels. The results indicate that among nine forest fire risk factors, the contributions of forest land, dry land, and vegetation cover to forest fire risk ranked top three, whereas the slope, height, and terrain ruggedness contributed little to forest fire risk. The forest fire risk levels of Chongqing City based on the weights of single-factor risk probabilities demonstrated satisfactory verification effects. Forest fires falling in zones at relatively high and above risk levels represented 83 %. In contrast, forest fires falling in zones at low and relatively low risk levels represented 8.33 % and 8.67 %, respectively. The forest fire risk in Chongqing City was intimately associated with the terrain trend, land use, and human activities. The high-risk and extremely high-risk zones were primarily distributed in low to middle mountain forest areas subjected to frequent human activities. Additionally, the areas surrounding forest land, located near farmland, rural roads, residential areas, and cemeteries, were also classified into high-risk zones since the frequent use of fire for production and daily life was prone to induce forest fires. The low-risk zones included primarily low and flat non-forest areas and steep forest areas, along with building land, water bodies, and paddy and dry lands that are far from forest land. Overall, the results of this study can be used to assess the spatial distribution of forest fire risk, providing scientific guidance for forest fire prevention.
Keywords forest fire risk      impact factors      risk probability      risk level     
ZTFLH:  TP79  
Issue Date: 01 July 2025
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Yanying CHEN
Yangsheng YOU
Qian YANG
Yanbo WANG
Cite this article:   
Yanying CHEN,Yangsheng YOU,Qian YANG, et al. Multifactor-based assessment of forest fire risk in Chongqing City, China[J]. Remote Sensing for Natural Resources, 2025, 37(3): 152-161.
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https://www.gtzyyg.com/EN/10.6046/gyzyyg.2023383     OR     https://www.gtzyyg.com/EN/Y2025/V37/I3/152
土地覆盖
类型		 2021年各类土地
占比/%		 林火数/次 林火数百分比/%
水田 14.560 193 16.0
旱地 25.972 358 29.7
林地 56.697 603 50.0
灌木 0.340 9 0.7
草地 0.062 2 0.2
水体 0.990 13 1.1
裸地 0.001 0 0.0
Tab.1  Statistics on the number of forest fire in different surface types
Fig.1  Classification of forest fire risk factors
Fig.2  The relationship between the number of forest fire and the topographic indexs
林火与林地
距离/m		 林地平均
距离/m		 水田平均
距离/m		 旱地平均
距离/m		 林火数/次 林火
占比/%
0 0.0 383.0 204.0 614 50.9
(0,500] 149.1 92.6 31.2 481 39.9
(500,1000] 618.6 33.5 67.5 66 5.5
>1000 1 606.0 26.0 77.0 45 3.7
Tab.2  The number of forest fire in different distance intervals of forest land and the relationship between forest fires and distance of paddy and dry land
Fig.3  The relationship between the number of forest fire and the distance of forest and grassland, dry land and paddy
Fig.4  The relationship between the number of forest fire and the distance to buildings and county roads
Fig.5  The relationship between forest fire number and vegetation coverage
Fig.6-1  Classification of single factor forest fire risk levels
Fig.6-2  Classification of single factor forest fire risk levels
指标 权重/%
高程 9.71
坡度 8.77
起伏度 9.68
植被覆盖度 12.67
道路距离 10.21
建筑距离 11.55
林地距离 13.42
林地约束下的旱地距离 13.00
林地约束下的水田距离 10.79
Tab.3  Table of weight value for various forest fire risk indicators
Fig.7  Results of forest fire risk assessment in Chongqing
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