基于加权信息量和加权确定性系数的藏东南滑坡易发性评价

doi:10.19388/j.zgdzdc.2024.03.14

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (13811 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract The southestern Tibet is a plateau region with steep mountains. The complex topography and geomorphology would easily induce geological disasters and increase the difficulty of engineering construction. In order to analyze the landslide susceptibility in this area, the authors in this paper selected eight evaluation factors as quantitative indexes, including distance from road, distance from water system, elevation, slope, slope direction, engineering geological rock group, soil type, and surface cover. The weighted value was determined by analytic nierardty process, and weighted informativeness model and weighted certainty factor (CF) were obtained by ArcGIS. Finally, the receiver operate curve was adopted to verify the accuracy of the results. The research vesullts are as follows (1) The AUC value of the weighted CF model is higher than the AUC value of the weighted informative ness model, and the covered landslide points from the weighted CF model the than those from the weighted informative ness model. So, the weighted CF model is more reliable in assessment of landslide susceptibility in this area. (2) The susceptibility zone is divided into high, relatively nigh, medium-high, relatively low, and low susceptibility zones by weighted CF model. The high susceptibility zone is mainly distributed in Mutuo and Gongjue counties, and relatively high susceptibility zone is distributed in Karuo and Mangkang counties. The medium-high susceptibility zone is distributed in Qiangwuqi, Dinching, and Janda counties, and the relatively low and low susceptibility zones are distributed in Bayi and Lang counties. The delineation of landslide-prone areas could provide some decision-making basis for the engineering construction in the region.

Key words： weighted informativeness model weighted certainty factor model the southeastern Tibet landslide susceptibility assessment

Received: 08 March 2023

ZTFLH:

P642.22

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	HUANG Yongfang
	GUO Yonggang
	HUANG Yanting

Cite this article:

HUANG Yongfang,GUO Yonggang,HUANG Yanting. Landslide susceptibility assessment in the southeastern Tibet based on weighted informativeness and weighted certainty factor[J]. , 2024, 11(3): 108-116.

URL:

http://journal25.magtechjournal.com/Jwk_dzdc/EN/10.19388/j.zgdzdc.2024.03.14 OR http://journal25.magtechjournal.com/Jwk_dzdc/EN/Y2024/V11/I3/108

[1] Wu C S,Guo Y G,Su L B.Risk assessment of geological disasters in Nyingchi,Tibet[J].Open Geosciences,2021,13(1):219-232.
[2] 黄艳婷,郭永刚.考虑降雨敏感度的泥石流危险性评价——以藏东南地区为例[J].中国地质灾害与防治学报,2023,34(1):129-138.
Huang Y T,Guo Y G.Debris flow risk assessment considering different rainfall sensitivity:A case study in southeast Tibet[J].The Chinese Journal of Geological Hazard and Control,2023,34(1):129-138.
[3] 胡磊,胡玉乾,孙鹏,等.藏东南地区降雨型滑坡致灾阈值及滑坡危险性量化分析[J].灾害学,2021,36(4):194-199.
Hu L,Hu Y Q,Sun P,et al.A quantitative analysis of disaster threshold and landslide risk of rainfall-type landslide in Southeast Tibet[J].Journal of Catastrophology,2021,36(4):194-199.
[4] 韩用顺,孙湘艳,刘通,等.基于证据权-投影寻踪模型的藏东南地质灾害易发性评价[J].山地学报,2021,39(5):672-686.
Han Y S,Sun X Y,Liu T,et al.Susceptibility evaluation of geological hazards based on evidence weight-projection pursuit model in Southeast Tibet,China[J].Mountain Research,2021,39(5):672-686.
[5] 王盈,金家梁,袁仁茂.藏东南地区地质灾害空间分布及影响因素分析[J].地震研究,2019,42(3):428-437.
Wang Y,Jin J L,Yuan R M.Analysis on spatial distribution and Influencing factors of geological disasters in southeast Tibet[J].Journal of Seismological Research,2019,42(3):428-437.
[6] 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.
Zhao X Y,Li Y P,Tan S C.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.
[7] 刘福臻,戴天宇,王军朝,等.耦合Random Forest算法与信息量模型的地质灾害易发性评价——以西藏自治区工布江达县为例[J].安全与环境学报,2023,23(7):2428-2438.
Liu F Z,Dai T Y,Wang J C,et al.Geological hazard susceptibility evaluation by coupled Random Forest and information model:A case study of Gongbujiangda county,Tibet autonomous region[J].Journal of Safety and Environment,2023,23(7):2428-2438.
[8] 赵晓东,徐振涛,刘福,等.基于极端梯度提升算法的滑坡易发性评价模型[J].科学技术与工程,2022,22(23):10347-10354.
Zhao X D,Xu Z T,Liu F,et al.Landslide susceptibility evaluation model based on XGBoost[J].Science Technology and Engineering,2022,22(23):10347-10354.
[9] 张虹,辜庆渝,孙诚彬,等.基于可解释性机器学习的丘陵缓坡地区滑坡易发性区划研究[J].重庆师范大学学报:自然科学版,2022,39(3):78-92.
Zhang H,Gu Q Y,Sun C B,et al.Landslide susceptibility mapping in hilly and gentle slope region based on interpretable machine learning[J].Journal of Chongqing Normal University:Natural Science,2022,39(3):78-92.
[10] 杨灿,刘磊磊,张遗立,等.基于贝叶斯优化机器学习超参数的滑坡易发性评价[J].地质科技通报,2022,41(2):228-238.
Yang C,Liu L L,Zhang Y L,et al.Machine learning based on landslide susceptibility assessment with Bayesian optimized the hyperparameters[J].Bulletin of Geological Science and Technology,2022,41(2):228-238.
[11] 常志璐,黄发明,蒋水华,等.基于多尺度分割方法的斜坡单元划分及滑坡易发性预测[J].工程科学与技术,2023,55(1):184-195.
Chang Z L,Huang F M,Jiang S H,et al.Slope unit extraction and landslide susceptibility prediction using multi-scale segmentation method[J].Advanced Engineering Sciences,2023,55(1):184-195.
[12] 吴先谭,邓辉,张文江,等.基于斜坡单元自动划分的滑坡易发性评价[J].山地学报,2022,40(4):542-556.
Wu X T,Deng H,Zhang W J,et al.Evaluation of landslide susceptibility based on automatic slope unit division[J].Mountain Research,2022,40(4):542-556.
[13] 吴明堂,薛正海,崔振华,等.基于斜坡单元和证据权-Logistic回归的滑坡易发性评价[J].人民长江,2022,53(10):87-94.
Wu M T,Xue Z H,Cui Z H,et al.Landslide susceptibility evaluation of reservoir banks by evidence weight-logistic regression coupling model based on GIS slope unit[J].Yangtze River,2022,53(10):87-94.
[14] 王盈,金家梁,袁仁茂.藏东南地区地质灾害空间分布及影响因素分析[J].地震研究,2019,42(3):428-437.
Wang Y,Jin J L,Yuan R M.Analysis on spatial distribution and Influencing factors of geological disasters in southeast Tibet[J].Journal of Seismological Research,2019,42(3):428-437.
[15] 王存智,张炜,李晨冬,等.基于GIS和层次分析法的沙溪流域滑坡地质灾害易发性评价[J].中国地质调查,2022,9(5):51-60.
Wang C Z,Zhang W,Li C D,et al.Susceptibility evaluation of landslide hazards of Shaxi river basin based on GIS and AHP[J].Geological Survey of China,2022,9(5):51-60.
[16] 李萍,叶辉,谈树成.基于层次分析法的永德县地质灾害易发性评价[J].水土保持研究,2021,28(5):394-399,406.
Li P,Ye H,Tan S C.Evaluation of geological hazards in Yongde county based on analytic hierarchy process[J].Research of Soil and Water Conservation,2021,28(5):394-399,406.
[17] 焦伟之,张明,谢鑫鹏,等.基于GIS与加权信息量模型的城镇地质灾害易发性评价——以大新镇为例[J].安全与环境工程,2022,29(4):119-128.
Jiao W Z,Zhang M,Xie X P,et al.Susceptibility evaluation of urban geological disaster based on GIS and weighted information value model:A case study of Daxin town[J].Safety and Environmental Engineering,2022,29(4):119-128.
[18] 张琪,侯晓亮,马雷,等.基于GIS与IIVM的桐城市地质灾害易发性评价[J].合肥工业大学学报:自然科学版,2021,44(7):958-964.
Zhang Q,Hou X L,Ma L,et al.Evaluation of the susceptibility of geological hazards in Tongcheng City based on GIS and IIVM[J].Journal of Hefei University of Technology:Natural Science,2021,44(7):958-964.
[19] 张钟远,徐世光,李超,等.基于GIS和加权信息量模型的绿春县城地质灾害易发性评价[J].地质灾害与环境保护,2022,33(1):37-43.
Zhang Z Y,Xu S G,Li C,et al.Evaluation of geological hazard susceptibility in Luchun County based on GIS and weighted information model[J].Journal of Geological Hazards and Environment Preservation,2022,33(1):37-43.