In this paper, we propose the principle, methods and calculating formulas for determining the certainty factors of earthquake precursory anomaly evidences CF (E). Based on the guidebooks for earthquake prediction, we ...In this paper, we propose the principle, methods and calculating formulas for determining the certainty factors of earthquake precursory anomaly evidences CF (E). Based on the guidebooks for earthquake prediction, we give the methods of determining the CF values of 22 evidences (including seismic gap, belt, b-value, c-value, velocity ratio, strengthen of anomalous activities, quiet of anomalous activities, seismic window, earthquake swarm,earthquake sequence, coda wave, initial motion of P wave, stress drop, geoelectricity, geomagnetism, stress,ground tilt, ground water level, radon and hydrochemistry, gravity, space environment and macroscopic anomalies), and show three examples. The purposes are to use the Expert System for Earthquake Prediction (ESEP) further.展开更多
A new approach combining the certainty factor(CF) and analytic hierarchy process(AHP) methods was proposed to assess landslide susceptibility in the Ziyang district, which is situated in the Qin-Ba Mountain region, Ch...A new approach combining the certainty factor(CF) and analytic hierarchy process(AHP) methods was proposed to assess landslide susceptibility in the Ziyang district, which is situated in the Qin-Ba Mountain region, China. Landslide inventory data were collected based on field investigations and remote sensing interpretations. A total of 791 landslides were identified. A total of 633 landslides were randomly selected from this data setas the training set, and the remaining landslides were used for validation as the test set. Nine factors, including the slope angle, slope aspect, slope curvature, lithology, distance to faults, distance to streams, precipitation, road network intensity degree and land use were chosen as the landslide causal factors for further susceptibility assessment. The weight of each factor and its subclass were calculated by AHP and CF methods. Landslide susceptibility was compared between the bivariate statistical method and the proposed CF-AHP method. The results indicate that the distance to streams, distance to faults and lithology are the most dominant causal factors associated with landslides. The susceptibility zonation was categorized into five classes of landslide susceptibility, i.e., very high, high, moderate, low and very low level. Lastly, the relative operating characteristics(ROC) curve was used to validate the accuracy of the new approach, and the result showed a satisfactory prediction rate of 78.3%, compared to 69.2% obtained with the landslide susceptibility index method. The results indicate that the CF-AHP combined method is more appropriate for assessing the landslide susceptibility in this area.展开更多
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...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.展开更多
文摘In this paper, we propose the principle, methods and calculating formulas for determining the certainty factors of earthquake precursory anomaly evidences CF (E). Based on the guidebooks for earthquake prediction, we give the methods of determining the CF values of 22 evidences (including seismic gap, belt, b-value, c-value, velocity ratio, strengthen of anomalous activities, quiet of anomalous activities, seismic window, earthquake swarm,earthquake sequence, coda wave, initial motion of P wave, stress drop, geoelectricity, geomagnetism, stress,ground tilt, ground water level, radon and hydrochemistry, gravity, space environment and macroscopic anomalies), and show three examples. The purposes are to use the Expert System for Earthquake Prediction (ESEP) further.
基金financial support from National Natural Science Foundation of China (Grant No. 41272282)National Natural Science Foundation of China-Youth Foundation (Grant No. 41402254)+1 种基金geological disaster survey projects of China Geological Survey (Grant No. 1212011220135, Grant No. DDW2016-01)the Fundamental Research Funds for the Central Universities (Grant No. 310826175030)
文摘A new approach combining the certainty factor(CF) and analytic hierarchy process(AHP) methods was proposed to assess landslide susceptibility in the Ziyang district, which is situated in the Qin-Ba Mountain region, China. Landslide inventory data were collected based on field investigations and remote sensing interpretations. A total of 791 landslides were identified. A total of 633 landslides were randomly selected from this data setas the training set, and the remaining landslides were used for validation as the test set. Nine factors, including the slope angle, slope aspect, slope curvature, lithology, distance to faults, distance to streams, precipitation, road network intensity degree and land use were chosen as the landslide causal factors for further susceptibility assessment. The weight of each factor and its subclass were calculated by AHP and CF methods. Landslide susceptibility was compared between the bivariate statistical method and the proposed CF-AHP method. The results indicate that the distance to streams, distance to faults and lithology are the most dominant causal factors associated with landslides. The susceptibility zonation was categorized into five classes of landslide susceptibility, i.e., very high, high, moderate, low and very low level. Lastly, the relative operating characteristics(ROC) curve was used to validate the accuracy of the new approach, and the result showed a satisfactory prediction rate of 78.3%, compared to 69.2% obtained with the landslide susceptibility index method. The results indicate that the CF-AHP combined method is more appropriate for assessing the landslide susceptibility in this area.
文摘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.
