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Spatial heterogeneity of influencing factors of landslide disasters in Lushan County |
ZHOU Yi, DING Mingtao, HUANG Tao, HE Yufeng |
School of Earth Science and Environmental Engineering, Southwest Jiaotong University, Sichuan Chengdu 611756, China |
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Abstract The geological environment and ecological structure are relatively fragile in Lushan County due to the frequent earthquakes in recent years. The high-frequency landslide disasters restrict the infrastructure construction, economic development, and threaten the safety of people’s lives and properties. The analysis of spatial hete-rogeneity of influencing factors of landslide disasters in Lushan County under static geological environment can provide basic data for land and space planning in the region and data support for landslide disasters prediction and prevention. The relationship between landslide development and 12 influencing factors, such as elevation and slope, were analyzed by information model and geographic detector, and the law of landslide development were summarized. Besides, the spatial heterogeneity characteristics of influencing factors were also studied, and a landslide-prone Sexual Evaluation Chart was generated using GIS weighted superposition. The results show that ① Landslides are mainly concentrated in areas with low elevations ([571,1 300) m), close to the road ([0,300) m) and water system ([0,300) m), small topographic relief ([0,30) m), gentle slope ([0°,30°)) and close to fault ([0,600) m). The landslides occurred in sedimentary rocks of silty mudstone, argillaceous siltstone, mudstone and Quaternary sedimentary, and lands for construction and agriculture. ② Landslide development is mainly controlled by factors such as elevation, distance from road and engineering geological rock group. And the land use type, distance from water system, terrain relief, slope, and distance from fault also have high contribution rates to the landslide. ③ The effects of two different influencing factors on landslide development show two-factors or nonlinear character compared with a single factor. The interaction between the distance from the road, elevation and other factors is the strongest. ④ The landslide-prone areas and extremely high landslide-prone areas are mainly distributed in the middle and low mountain canyons, hilly areas and river valley landforms in the southeastern areas.
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Received: 19 April 2022
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[1] Das S,Sarkar S,Kanungo D P.GIS-based landslide susceptibil-ity zonation mapping using the analytic hierarchy process (AHP) method in parts of Kalimpong Region of Darjeeling Himalaya[J].Environ Monitor Assessm,2022,194(3):234. [2] Liang S Z X,Chen D,Li D H,et al.Spatial and temporal distribution of geologic hazards in Shaanxi Province[J].Remote Sens,2021,13(21):4259. [3] Zou Y,Qi S W,Guo S F,et al.Factors controlling the spatial distribution of coseismic landslides triggered by the MW 6.1 Ludian earthquake in China[J].Eng Geol,2022,296:106477. [4] Hu Q,Zhou Y,Wang S X,et al.Fractal-based spatial distribution analysis of geological hazards and measurement of spatial association with hazard-related predisposing factors[C]//International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,Volume XLII-3/W10,2020 International Conference on Geomatics in the Big Data Era.Guilin:IPRS,2020:125-131. [5] Nath R R,Pareek N,Lal Sharma M.Implications and inclusion of size-dependent scenario earthquakes on landslide hazard zonation:A case study of the Indian Himalayas[J].CATENA,2022,212:106027. [6] Rabby Y W,Li Y K,Abedin J,et al.Impact of land use/land cover change on landslide susceptibility in rangamati municipality of rangamati district,Bangladesh[J].ISPRS Int J Geo-Inform,2022,11(2):89. [7] Xiao T,Yu L B,Tian W M,et al.Reducing local correlations among causal factor classifications as a strategy to improve landslide susceptibility mapping[J].Front Earth Sci,2021,9:781674. [8] Li J Y,Wang W D,Li Y G,et al.Spatiotemporal landslide susceptibility mapping incorporating the effects of heavy rainfall:A case study of the heavy rainfall in August 2021 in Kitakyushu,Fukuoka,Japan[J].Water,2021,13(22):3312. [9] 许冲,戴福初,姚鑫,等.基于GIS的汶川地震滑坡灾害影响因子确定性系数分析[J].岩石力学与工程学报,2010,29(S1):2972-2981. Xu C,Dai F C,Yao X,et al.GIS based certainty factor analysis of landslide triggering factors in Wenchuan earthquake[J].Chin J Rock Mech Eng,2010,29(S1):2972-2981. [10] 王新胜,滕德贵,谢伟,等.山地城市滑坡灾害空间分布特征及影响因素分析[J].重庆大学学报,2020,43(8):87-96. Wang X S,Teng D G,Xie W,et al.Spatial distribution characte-ristics and influencing factors of landslide disasters in mountain cities[J].J Chongqing Univ,2020,43(8):87-96. [11] 杨忠平,李绪勇,赵茜,等.关键影响因子作用下三峡库区堆积层滑坡分布规律及变形破坏响应特征[J].工程地质学报,2021,29(3):617-627. Yang Z P,Li X Y,Zhao Q,et al.Key influencing factors based distribution regularity and deformation and failure response of colluvial land-slides in Three Gorges Reservoir area[J].J Eng Geol,2021,29(3):617-627. [12] 唐尧,马松,王立娟,等.高分辨率遥感技术在地质灾害调查与成灾规律分析中的应用——以攀西米易地区为例[J].中国地质调查,2022,9(3):96-103. Tang Y,Ma S,Wang L J,et al.Application of high resolution remote sensing technology in geological disaster investigation and disaster law analysis:A case study of Panxi Miyi area[J].Geol Survey China,2022,9(3):96-103. [13] 董毅兵,郁文,张仲福.基于GIS的地质灾害易发性分区评价——以甘肃省会宁县为例[J].中国地质调查,2020,7(3):89-95. Dong Y B,Yu W,Zhang Z F.Susceptibility zoning of geological disasters based on GIS:A case of Huining area in Gansu Pro-vince[J].Geol Survey China,2020,7(3):89-95. [14] 王劲峰,徐成东.地理探测器:原理与展望[J].地理学报,2017,72(1):116-134. Wang J F,Xu C D.Geodetector:Principle and prospective[J].Acta Geogr Sin,2017,72(1):116-134. [15] 裴向军,黄润秋.“4·20”芦山地震地质灾害特征分析[J].成都理工大学学报:自然科学版,2013,40(3):257-263. Pei X J,Huang R Q.Analysis of characteristics of geological hazards by “4·20” Lushan earthquake in Sichuan,China[J].J Chengdu Univ Technol:Sci Technol Ed,2013,40(3):257-263. [16] 许冲,肖建章.2013年芦山地震滑坡空间分布分析——以太平镇东北方向的一个典型矩形区为例[J].地震地质,2013,35(2):436-451. Xu C,Xiao J Z.Spatial analysis of landslides triggered by the 2013 MS7.0 Lushan earthquake:A case study of a typical rectangle area in the northeast of Taiping town[J].Earthq Geol,2013,35(2):436-451. [17] 丁明涛,庙成.基于GIS的芦山地震灾区滑坡灾害风险评价[J].自然灾害学报,2014,23(4):81-90. Ding M T,Miao C.GIS-based risk assessment of landslide hazards in Lushan earthquake-stricken areas[J].J Nat Dis,2014,23(4):81-90. [18] 胡凯衡,丁明涛.滑坡泥石流风险评估框架体系[J].中国地质灾害与防治学报,2013,24(2):26-30. Hu K H,Ding M T.Discussion on framework of landslide and debris-flow risk assessments[J].Chin J Geol Hazard Control,2013,24(2):26-30. [19] 王骏,丁明涛,庙成,等.基于GIS和AHP的芦山地震灾区泥石流危险性评价[J].长江流域资源与环境,2014,23(11):1580-1587. Wang J,Ding M T,Miao C,et al.Hazard assessment of debris flow based on GIS and AHP in Lushan earthquake disaster area[J].Resour Environ Yangtze Basin,2014,23(11):1580-1587. [20] 黄涛,丁明涛,蒋林宏,等.基于地理探测器的岷江上游泥石流影响因子相对重要性分析[J].西南师范大学学报:自然科学版,2019,44(9):45-51. Huang T,Ding M T,Jiang L H,et al.Relative importance analysis of debris flow influence factors based on geographical detectors:A case study in the upper reaches of Min River[J].J Southwest China Normal Univ:Nat Sci Ed,2019,44(9):45-51. [21] 兰剑,陈晓利.2008年MS8.0汶川地震诱发滑坡灾害在映秀地区的演化特征[J].地震地质,2020,42(1):125-146. Lan J,Chen X L.Evolution characteristics of landslides triggered by 2008 MS8.0 Wenchuan earthquake in Yingxiu area[J].Earthq Geol,2020,42(1):125-146. [22] Pardeshi S D,Autade S E,Pardeshi S S.Landslide hazard assessment:Recent trends and techniques[J].SpringerPlus,2013,2(1):523. [23] Psomiadis E,Papazachariou A,Soulis K X,et al.Landslide mapping and susceptibility assessment using geospatial analysis and earth observation data[J].Land,2020,9(5):133. [24] He Q,Wang M,Liu K.Rapidly assessing earthquake-induced landslide susceptibility on a global scale using random forest[J].Geomorphology,2021,391:107889. [25] Williams F,McColl S,Fuller I,et al.Intersection of fluvial incision and weak geologic structures cause divergence from a universal threshold slope model of landslide occurrence[J].Geomorphology,2021,389:107795. [26] He Q F,Shahabi H,Shirzadi A,et al.Landslide spatial modelling using novel bivariate statistical based Na?ve Bayes,RBF Classifier,and RBF Network machine learning algorithms[J].Sci Total Environ,2019,663:1-15. [27] Bordoni M,Galanti Y,Bartelletti C,et al.The influence of the inventory on the determination of the rainfall-induced shallow landslides susceptibility using generalized additive models[J].CATENA,2020,193:104630. [28] Zhu A X,Miao Y M,Wang R X,et al.A comparative study of an expert knowledge-based model and two data-driven models for landslide susceptibility mapping[J].CATENA,2018,166:317-327. [29] Schlögel R,Marchesini I,Alvioli M,et al.Optimizing landslide susceptibility zonation:Effects of DEM spatial resolution and slope unit delineation on logistic regression models[J].Geomorphology,2018,301:10-20. [30] Nguyen B Q V,Lee S R,Kim Y T.Spatial probability assessment of landslide considering increases in pore-water pressure during rainfall and earthquakes:Case studies at Atsuma and Mt.Umyeon[J].CATENA,2019,187:104317. [31] Panchal S,Shrivastava At K.Landslide hazard assessment using analytic hierarchy process (AHP):A case study of National Highway 5 in India[J].Ain Shams Eng J,2022,13(3):101626. [32] Chahal P,Rana N,Ray P K C,et al.Identification of landslide-prone zones in the geomorphically and climatically sensitive Mandakini valley,(central Himalaya),for disaster governance using the Weights of Evidence method[J].Geomorphology,2017,284:41-52. [33] Yi Y N,Zhang Z J,Zhang W C,et al.Landslide susceptibility mapping using multiscale sampling strategy and convolutional neural network:A case study in Jiuzhaigou region[J].CATENA,2020,195:104851. |
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