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Remote Sensing for Natural Resources    2025, Vol. 37 Issue (4) : 140-151     DOI: 10.6046/zrzyyg.2024119
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Spatiotemporal variations of geological disaster risk and obstacle factor diagnosis: A case study of the western Sichuan region
YANG Hengjun1(), YANG Xin1,2(), ZHOU Xiong3
1. College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China
2. Key Laboratory of Earth Exploration and Information Techniques, Ministry of Education, Chengdu 610059, China
3. Institute of Multipurpose Utilization of Mineral Resources, Chinese Academy of Geological Science, Chengdu 610041, China
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Abstract  

Geological disasters, influenced by natural and human factors, directly threaten the safety of people’s lives and property. Exploring the spatiotemporal variations and development mechanisms of geological disaster risk can enhance disaster prevention and mitigation. This study examined 31 factors such as topography, rainfall, and social economy from the perspectives of nature and humanity. Based on the four-factor risk theory, this study investigated the variations of geological disaster risk in the western Sichuan region using methods like the analytic hierarchy process, principal component analysis, information value model, entropy weight method, and hot/cold spot analysis. Employing the obstacle degree model, this study explored the degrees of influence of various factors on geological disaster risk in the western Sichuan region. The results indicate that from 2007 to 2022, the geological disaster risk in the western Sichuan region was generally characterized by higher levels in the west and lower levels in the east. Kangding and Maerkang were the concentrated distribution areas of perennial cold spots. The area of extremely low and low risk levels increased by 8 871.1 km2 and 12 478.6 km2 respectively at growth rates of 1.056%/a and 1.485%/a respectively. The area of high and extremely high risk levels decreased by 10 127.8 km2 and 9 880.1 km2 respectively at growth rates of -0.02484 km2/a. The degrees of influence of various factors on risk levels exhibited temporal heterogeneity. The dominant obstacle factors (obstacle degree: above 5 %) were concentrated in risk and disaster prevention and mitigation indicators. Factors including rainfall, topography, and medical resources contributed significantly to geological disaster risk.
Keywords risk assessment      geological disaster      obstacle degree      hot/cold spot analysis      analytic hierarchy process     
ZTFLH:  TP79  
Issue Date: 03 September 2025
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Hengjun YANG
Xin YANG
Xiong ZHOU
Cite this article:   
Hengjun YANG,Xin YANG,Xiong ZHOU. Spatiotemporal variations of geological disaster risk and obstacle factor diagnosis: A case study of the western Sichuan region[J]. Remote Sensing for Natural Resources, 2025, 37(4): 140-151.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2024119     OR     https://www.gtzyyg.com/EN/Y2025/V37/I4/140
Fig.1  Schematic diagram of study area
目标层 准则层 因子层
风险
评价		 危险性 高程
坡度
坡向
起伏度
地震峰值加速度
年均降雨量
地层岩性
土地利用类型
道路
水系
距断层距离
植被覆盖度
风险
评价		 脆弱性 农业人口占比
第一产业占比
耕地面积占比
粮食产量
农林牧渔产值
规模以上工业企业数量
暴露性 人口数量及密度
地区生产总值
农田面积占比
建筑面积占比
林地面积占比
草地面积占比
防灾减灾能力 地方财政支出
居民人均可支配收入
每千人医院数量
每千人床位数量
每千人医生数量
每千人护士数量
每千人卫生技术人员数量
Tab.1  Geological hazard risk assessment factors
因子 分级 2007年 2012年 2017年 2022年
I W I W I W I W
高程/m [0,1 500) 0.344 0.037 0.939 0.049 0.427 0.092 0.376 0.028
[1 500,2 500) 0.346 0.960 0.416 0.366
[2 500,3 500) 0.273 0.877 0.367 0.324
[3 500,4 500) 0.134 0.696 0.264 0.233
[4 500,+∞) 0.236 0.223 0.135 0.118
坡度/(°) [0,15) 0.166 0.108 0.104 0.110 0.132 0.049 0.113 0.101
[15,25) 0.125 0.083 0.097 0.084
[25,35) 0.067 0.045 0.057 0.051
[35,45) 0.071 0.045 0.062 0.049
[45,90) 0.111 0.059 0.062 0.057
坡向/(°) [0,45) 0.073 0.09 0.061 0.091 0.044 0.058 0.029 0.063
[45,135) 0.076 0.099 0.062 0.041
[135,225) 0.059 0.076 0.053 0.035
[225,315) 0.036 0.061 0.030 0.020
[315,360) 0.029 0.026 0.020 0.013
起伏度/m [0,30) 0.118 0.106 0.572 0.110 0.110 0.110 0.103 0.101
[30,70) 0.044 0.519 0.050 0.047
[70,200) 0.063 0.524 0.041 0.038
[200,300) 0.074 0.103 0.071 0.067
[300,+∞) 0.074 0.577 0.071 0.067
地震峰值加速度/(m·s-2) 0.10 g 0.074 0.099 0.142 0.092 0.121 0.082 0.113 0.089
0.15 g 0.077 0.147 0.118 0.105
0.20 g 0.043 0.078 0.036 0.031
0.30 g 0.019 0.042 0.061 0.058
0.40 g 0.064 0.065 0.101 0.092
年均降雨量/mm [0,700) 0.417 0.115 0.910 0.109 0.355 0.055 0.155 0.104
[700,750) 0.289 0.534 0.079 0.187
[750,800) 0.257 0.529 0.064 0.129
[800,850) 0.461 0.439 0.022 0.104
[850,+∞) 0.604 0.496 0.044 0.261
地层岩性 坚硬岩 0.132 0.074 0.715 0.102 0.094 0.091 0.108 0.090
较坚硬岩 0.067 0.684 0.087 0.103
较软岩 0.174 0.814 0.172 0.203
软岩 0.105 0.127 0.109 0.128
极软岩 0.105 0.605 0.065 0.078
道路/m [0,100) 0.697 0.065 0.367 0.055 0.375 0.109 0.300 0.097
[100,200) 0.588 0.313 0.273 0.174
[200,300) 0.548 0.236 0.240 0.138
[300,400) 0.469 0.272 0.208 0.142
[400,+∞) 0.339 0.179 0.173 0.153
水系/m [0,100) 0.683 0.064 0.481 0.091 0.429 0.110 0.123 0.092
[100,200) 0.589 0.430 0.325 0.137
[200,300) 0.501 0.373 0.282 0.119
[300,400) 0.448 0.361 0.284 0.146
[400,+∞) 0.336 0.231 0.196 0.061
距断层距离/m [0,500) 0.138 0.086 0.073 0.051 0.094 0.102 0.077 0.083
[500,1 000) 0.118 0.072 0.091 0.064
[1 000,2 000) 0.097 0.041 0.054 0.049
[2 000,3 000) 0.114 0.057 0.057 0.037
[3 000,+∞) 0.062 0.039 0.053 0.042
植被覆盖度 [0,0.2) 0.130 0.096 0.031 0.058 0.031 0.051 0.021 0.081
[0.2,0.4) 0.111 0.129 0.173 0.050
[0.4,0.6) 0.176 0.193 0.181 0.030
[0.6,0.8) 0.164 0.190 0.182 0.051
[0.8,1] 0.054 0.152 0.200 0.021
土地利用类型 裸地 0.178 0.058 0.273 0.082 0.175 0.091 0.251 0.070
草原 0.331 1.023 0.340 0.441
森林 0.335 1.032 0.361 0.443
水域 0.219 1.338 0.288 0.501
耕地 0.495 1.295 0.528 0.665
城镇 0.457 0.984 0.500 0.713
Tab.2  Information value(I) and weight(W) of risk assessment factors
指标 时间 道孚县 雅江县 丹巴县 九龙县 壤塘县 金川县 康定市 马尔康市
防灾减
灾能力		 2007年 1.536 1.605 1.506 1.371 1.471 1.351 0.999 0.891
2012年 1.733 1.731 1.704 1.673 1.620 1.613 1.246 0.906
2017年 1.691 1.695 1.630 1.661 1.600 1.545 1.110 0.951
2022年 1.726 1.698 1.518 1.654 1.708 1.616 0.983 1.084
脆弱性 2007年 0.996 0.817 0.749 0.962 0.829 0.880 0.681 0.922
2012年 0.898 0.885 0.662 0.947 0.934 0.843 0.684 0.994
2017年 0.828 0.941 0.837 0.812 0.915 0.877 0.652 1.008
2022年 1.325 1.102 1.211 0.960 1.092 0.858 0.781 0.969
暴露性 2007年 1.060 0.767 1.001 0.895 0.674 1.115 1.076 0.828
2012年 0.834 0.780 1.103 0.820 0.679 0.886 1.108 0.699
2017年 0.759 0.656 0.983 0.779 0.669 0.964 1.033 0.739
2022年 0.857 0.747 1.000 0.753 0.747 1.100 1.259 0.804
Tab.3  Weight of indicators for vulnerability, exposure, and disaster prevention and mitigation capability
危险性 防灾减
灾能力		 脆弱性 暴露性 Wi
危险性 1 3 4 5 0.520 0
防灾减灾能力 1/3 1 3 4 0.268 2
脆弱性 1/4 1/3 1 3 0.140 9
暴露性 1/5 1/4 1/3 1 0.070 9
Tab.4  Results of analytic hierarchy process
Fig.2  Distribution of hazard levels
危险
等级		 2007年 2012年 2017年 2022年
灾害点/
个		 灾害点
占比/%		 区域面积
占比/%		 灾害点/
个		 灾害点
占比/%		 区域面积
占比/%		 灾害点/
个		 灾害点
占比/%		 区域面积
占比/%		 灾害点/
个		 灾害点
占比/%		 区域面积
占比/%
极低 0 0.00 4.51 0 0.00 2.86 0 0.00 6.48 2 0.07 8.57
低 2 0.53 13.07 0 0.00 10.90 98 3.62 32.48 114 3.78 29.87
中 37 9.76 41.62 42 3.14 38.64 608 22.45 38.49 543 18.02 36.33
高 175 46.17 37.82 428 31.96 39.33 839 30.98 16.66 1 080 35.84 20.07
极高 165 43.54 2.98 869 64.90 8.27 1 163 42.95 5.90 1 274 42.28 5.16
Tab.5  Proportion of area by risk levels
Fig.3  Accuracy analysis of risk assessment
Fig.4  Distribution of vulnerability levels
Fig.5  Distribution of exposure levels
Fig.6  Distribution of disaster prevention and mitigation capability levels
Fig.7  Distribution of risk levels
Fig.8  Trend of cold and hot spot aggregation distribution
Fig.9  Fitting analysis of risk change trend
Fig.10  Changes in proportion of risk areas
指标 因子 2007年 2012年 2017年 2022年
危险性 地震峰值加速度 7.21 6.24 7.06 7.04
年均降雨量 7.46 6.55 7.88 6.68
土地利用类型 5.60 5.56 5.17 5.85
起伏度 7.25 8.01 7.92 8.02
坡度 6.33 6.18 6.43 6.67
坡向 — 6.05 6.03 —
防灾减
灾能力		 地方财政总支出 5.12 — 5.19 5.77
每千人病床张数 5.48 5.49 — 5.44
每千人卫生技术人员数 — 5.53 5.30 —
每千人护士数 6.80 7.72 7.27 7.27
Tab.6  Main factors for obstacle assessment(%)
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