1. School of Information Engineering, China University of Geosciences(Beijing), Beijing 100083, China 2. Ningxia Geological Survey Institute, Yinchuan 750021, China 3. College of Resources and Environmental Science, Ningxia University, Yinchuan 750021, China 4. Ningxia Institute of Remote Sensing Survey and Mapping(Ningxia Remote Sensing Center), Yinchuan 750021, China
In order to discuss the regional hazard assessment method of geological disaster, the authors, based on the comprehensive study of hazard-formative environments of Yanchi County, extracted twelve conditioning factors, i.e., strata, lithology, soil, land use type, slope, aspect, topographic wetness index (TWI), stream power index (SPI), distance to river, distance to road, normalized difference vegetation index (NDVI) and precipitation in the evaluation and information of factors by employing GIS with remote sensing data and geological data. Then the judgment matrix of conditioning factors and factor classes were constructed by analytic hierarchy process (AHP) method, and geological disaster hazard index (GDHI) was built. Finally the geological disaster hazard of Yanchi County was assessed and the resulted hazard map was classified into five classes, including very low, low, moderate, high and very high hazard. Meanwhile validation of the hazard map was performed using success rate curve and receiver operating characteristics (ROC) technique. The results are as follows: ①The area percentage of very low and low class accounts for 34% and 28% respectively, mainly distributed among the middle and north of hill region; the area percentage of moderate class accounts for 25%, mainly distributed in the area of Mahuang Mountain, western Wanglejing and two sides of the main roads; the area percentage of high and very high class accounts for 12% and 1% respectively, mainly distributed in the area on two sides of rivers and Mahuang Mountain. ②The area under curve (AUC) value of success rate curve and ROC is 0.77 and 0.89 respectively, which shows a reasonable validation accuracy of hazard assessment. At the same time, disaster density shows the characteristics of a continuing increase in the density values from the very low class to the very high class, and the density of the very high hazard class has maximum value with 1.076/km 2. ③AHP method was successfully used to assess the geological disaster hazard of Yanchi County and AHP is suitable for hazard mapping in this region. The evaluation results could provide a reference for the prevention and control of geological disasters in Yanchi County.
Zhang C S, Zhang Y C, Zhang L H . Danger assessment of collapses,landslides and debris flows of geological hazards in China[J]. Journal of Geomechanics, 2004,10(1):27-32.
[2]
Wang H B, Sassa K . Comparative evaluation of landslide susceptibility in Minamata area,Japan[J]. Environmental Geology, 2005,47(7):956-966.
[3]
Saaty T L . The Analytic Hierarchy Process:Planning, Priority Setting,Resource Allocation[M]. New York:McGraw-Hill, 1980.
Yao Y Z, Ren Q Z, Li R F , et al. Application of analytic hierarchy process to the probability assessment of mountain geological disasters:A case study of Lingyuan region,Liaoning Province[J]. Hydrogeology and Engineering Geology, 2010,37(2):130-134.
Chang Q, Liu L, Miao L Y . Geological hazard risk assessment based on fuzzy mathematics in Lintong[J]. China Population,Resources and Environment, 2014,24(3):355-358.
Li J Q, Han H H, Gao T , et al. The application of ZY-3 satellite to geological hazards survey and evaluation:A case study of Baoji loess area[J]. Remote Sensing for Land and Resources, 2017,29(s1):73-80.doi: 10.6046/gtzyyg.2017.s1.12.
Li X X, Ma H J . Risk assessment of earthquke-induced collapses and slides based on Logistic model for the case of Wenchuan County[J]. Earthquake, 2013,33(2):63-70.
Zhang Z, Shen X H, Zou L J , et al. The quantification method in the estimation model for landslide danger:A case study of Yongjia County[J]. Remote Sensing for Land and Resources, 2010,22(3):16-20.doi: 10.6046/gtzyyg.2010.03.04.
Lyu Y Q, Lin D J, Luo W Q . Study on artificial NN method for forecast and risk assessment of regional geologic hazards[J]. The Chinese Journal of Geological Hazard and Control, 2007,18(1):95-98.
[10]
Ying X, Zeng G M, Chen G Q , et al. Combining AHP with GIS in synthetic evaluation of ecoenvironment quality—A case study of Hunan Province,China[J]. Ecological Modelling, 2007,209(2):97-109.
[11]
Pourghasemi H R, Pradhan B, Gokceoglu C . Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran[J]. Natural Hazards, 2012,63(2):965-996.
[12]
Kayastha P, Dhital M R, Smedt F D . Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping:A case study from the Tinau watershed,west Nepal[J]. Computers and Geosciences, 2013,52(52):398-408.
[13]
Kumar R, Anbalagan R . Landslide susceptibility mapping using analytical hierarchy process (AHP) in Tehri reservoir rim region,Uttarakhand[J]. Journal of the Geological Society of India, 2016,87(3):271-286.
Zheng S Y, Zhang X J, Yang Y , et al. The application of analytic hierarchy process to the danger evaluation of collapse and slide in Lujiang basin segment of Nujiang valley,western Yunnan Province[J]. Geological Bulletin of China, 2012,31(2/3):356-365.
Jia G Y, Quan Y Q, Li Z H , et al. Geo-hazards assessment for the Gansu segment in Bailongjiang River basin by using combination weighting method[J]. Journal of Glaciology and Geocryology, 2014,36(5):1227-1236.
Li Y H, Jiang Q G . The estimation of regional geo-hazards based on reinvestigation and GIS analysis[J]. Remote Sensing for Land and Resources, 2006,18(2):57-60.doi: 10.6046/gtzyyg.2006.02.14.
Zhang X D, Liu X N, Zhao Z P , et al. Survey of geological hazards by RS and spatial distribution characteristics analysis in Yanchi County[J]. Hydrogeology and Engineering Geology, 2017,44(1):164-170.
Li F L, Chang Q R, Liu J Q , et al. SVM classification with multi-texture data of ZY-1 02C HR image[J]. Geomatics and Information Science of Wuhan University, 2016,41(4):455-461.
Peng W F, Wang G J, Zhou J M , et al. Dynamic monitoring of fractional vegetation cover along Minjiang River from Wenchuan County to Dujiangyan City using multi-temporal Landsat 5 and 8 images[J]. Acta Ecologica Sinica, 2016,36(7):1975-1988.
Zhang C X, Yang Q K, Li R . Advancement in topographic wetness index and its application[J]. Progress in Geography, 2005,24(6):116-123.
[22]
Thalacker R J . Mapping Techniques for Soil Erosion:Modeling Stream Power Index in Eastern North Dakota[D]. North Dakota:University of North Dakota, 2014.
[23]
Hasekioğulları G D, Ercanoglu M . A new approach to use AHP in landslide susceptibility mapping:A case study at Yenice(Karabuk,NW Turkey)[J]. Natural Hazards, 2012,63(2):1157-1179.
Guo Q . The optimization of AHP in its application of the comprehensive evaluation of ecological environment[J]. Remote Sensing for Land and Resources, 2008,20(3):104-107.doi: 10.6046/gtzyyg.2008.03.23.
[25]
Saaty T L . A scaling method for priorities in hierarchical structures[J]. Journal of Mathematical Psychology, 1977,15(3):234-281.
Li F J, Ma A Q, Ding Y D , et al. Application of RS and GIS to the risk evaluation of geological hazards:A case study on Qingdao Laoshan District[J]. Periodical of Ocean University of China(Natural Science), 2010,40(6):47-52.
[27]
Lee S, Pradhan B . Landslide hazard mapping at Selangor,Malaysia using frequency ratio and logistic regression models[J]. Landslides, 2007,4(1):33-41.
[28]
Pontius R G, Schneider L C . Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts,USA[J]. Agriculture Ecosystems and Environment, 2001,85(1-3):239-248.
Rao P Z, Cao R, Jiang W G . Susceptibility evaluation of geological disasters in Yunnan Province based on geographically weighted regression model[J]. Journal of Natural Disasters, 2017,26(2):134-143.
[30]
Westen C J V, Rengers N, Soeters R . Use of geomorphological information in indirect landslide susceptibility assessment[J]. Natural Hazards, 2003,30(3):399-419.
Du Q, Fan W, Li K , et al. Geohazard susceptibility assessment by using binary Logical regression and information value model[J]. Journal of Catastrophology, 2017,32(2):220-226.