赵晓燕, 李永平, 谈树成. GIS支持下CF与信息量耦合模型的攀枝花市矿山地质灾害易发性评价[J]. 云南大学学报(自然科学版), 2022, 44(4): 754-764. doi: 10.7540/j.ynu.20210236
引用本文: 赵晓燕, 李永平, 谈树成. GIS支持下CF与信息量耦合模型的攀枝花市矿山地质灾害易发性评价[J]. 云南大学学报(自然科学版), 2022, 44(4): 754-764. doi: 10.7540/j.ynu.20210236
ZHAO Xiao-yan, LI Yong-ping, TAN Shu-cheng. Evaluation of mine geological hazard susceptibility of coupling CF with information model based on GIS in Panzhihua City[J]. Journal of Yunnan University: Natural Sciences Edition, 2022, 44(4): 754-764. DOI: 10.7540/j.ynu.20210236
Citation: ZHAO Xiao-yan, LI Yong-ping, TAN Shu-cheng. Evaluation of mine geological hazard susceptibility of coupling CF with information model based on GIS in Panzhihua City[J]. Journal of Yunnan University: Natural Sciences Edition, 2022, 44(4): 754-764. DOI: 10.7540/j.ynu.20210236

GIS支持下CF与信息量耦合模型的攀枝花市矿山地质灾害易发性评价

Evaluation of mine geological hazard susceptibility of coupling CF with information model based on GIS in Panzhihua City

  • 摘要: 攀枝花市矿产资源丰富,采矿历史悠久,开采活动强度大,地质结构复杂,生态环境脆弱,矿山地质灾害频发. 基于2019年的三江(怒江,澜沧江,金沙江)北段矿产开发环境遥感监测调查资料,在分析矿山地质灾害发育规律与影响因素关系的基础上,选取坡度、工程地质岩组、距断层的距离、降水量、植被覆盖度、距河流的距离以及距开采活动面的距离7个评价因子,借助ArcGIS软件平台,采用确定性系数(Certainty Factor, CF)模型、信息量模型以及CF与信息量耦合模型开展攀枝花市矿山地质灾害易发性评价研究. 结果表明,工程地质岩组、植被覆盖度、距开采活动面的距离是影响矿山地质灾害分布的控制因子;经过ROC(Receiver Operating Characteristic Curve, ROC)曲线检验,CF与信息量耦合模型的AUC(Area Under the Curve, AUC)值高达0.909,表明耦合模型比单一模型的评价精度高,其精度为耦合模型>信息量模型>确定性系数模型;耦合模型的易发性分区为极高易发区(5.24%)、高易发区(11.67%)、中易发区(41.66%)和低易发区(41.43%),其中极高和高易发区主要分布在开采活动强度较大的煤矿、铁矿和花岗岩矿矿山,即主要分布在仁和区、东区、盐边县和米易县.

     

    Abstract: Panzhihua City is rich in mineral resources, and has a long mining history, high intensity of mining activities, complex geological structures, fragile ecological environment, and frequent mine geological disasters. Based on the remote sensing monitoring and investigation data of the mineral development environment in the north reaches of the three rivers (Nujiang River, Langcangjiang River and Jinshajiang River) in 2019, the relationship between the development law and influencing factors of mine geological disasters are analyzed. Meanwhile, seven evaluation factors are selected, such as slope, engineering geological petrofabric, the distance from the faults, precipitation, vegetation coverage, the distance from the river, and the distance from the mining activities. Furthermore, with the help of ArcGIS software platform, the susceptibility evaluation of mine geological disasters in Panzhihua City is carried out by using the deterministic coefficient Certainty Factor (CF), information quantity model and the coupling model of CF and information quantity. The results show that engineering geological rock group, vegetation coverage, and distance from mining areas are the controlling factors affecting the distribution of geological disasters. After Receiver Operating Characteristic (ROC) curve test, the Area Under the Curve (AUC) value of the coupling model of CF and information quantity is as high as 0.909, indicating that the evaluation accuracy of the coupling model is higher than that of the single model, and the accuracy is as follows: coupling model > information quantity model > deterministic coefficient model. The vulnerability zones of the coupling model are extremely high (5.24%), high (11.67%), medium (41.66%) and low (41.43%). Among them, the extremely high and high vulnerability zones are mainly distributed in coal mines, iron mines and granite mines with high mining activity intensity; and those zones are mainly located in Renhe District, Eastern District, Yanbian County and Miyi County.

     

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