Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system

被引:0
|
作者
Hyun-Joo Oh
Saro Lee
机构
[1] Korea Institute of Geoscience and Mineral Resources (KIGAM),Geoscience Information Center
来源
关键词
Landslide; Susceptibility map; Weight-of-evidence; GIS; Philippines;
D O I
暂无
中图分类号
学科分类号
摘要
For landslide susceptibility mapping, this study applied, verified and compared the Bayesian probability model, the weights-of-evidence to Panaon Island, Philippines, using a geographic information system. Landslide locations were identified in the study area from the interpretation of aerial photographs and field surveys, and a spatial database was extracted from SRTM (Shuttle Radar Topographic Mission) DEM (Digital Elevation Model) imagery, aerial photograph, topographic map, and geological map. The factors that influence landslide occurrence, such as slope, aspect, curvature, topographic wetness index and stream power index of topography, were calculated from SRTM imagery. Distance from drainage was extracted from topographic database. Lithology and distance from fault were extracted and calculated from geological database. Terrain mapping unit was classified from aerial photographs. The spatial association between the factors and the landslides was calculated as the contrast values, W+ and W− using the weights-of-evidence model. Tests of conditional independence were performed for the selection of the factors, allowing the large number of combinations of factors to be analyzed. For each factor rating, the contrast values, W+ and W− were overlaid for landslide susceptibility mapping. The results of the analysis showed that contrast rating (78.60%) for each factor’s multiclass had better accuracy of 5.90% than combinations of factor assigned to binary class with W+ and W− (72.70%).
引用
收藏
页码:935 / 951
页数:16
相关论文
共 50 条
  • [41] Landslide Susceptibility Mapping Using Fuzzy-AHP
    Mokarram M.
    Zarei A.R.
    Geotechnical and Geological Engineering, 2018, 36 (6) : 3931 - 3943
  • [42] Mapping landslide susceptibility and types using Random Forest
    Taalab, Khaled
    Cheng, Tao
    Zhang, Yang
    BIG EARTH DATA, 2018, 2 (02) : 159 - 178
  • [43] Landslide Susceptibility Mapping Based on Deep Learning Algorithms Using Information Value Analysis Optimization
    Ji, Junjie
    Zhou, Yongzhang
    Cheng, Qiuming
    Jiang, Shoujun
    Liu, Shiting
    LAND, 2023, 12 (06)
  • [44] Landslide Susceptibility Mapping using Machine Learning Algorithm
    Hussain, Muhammad Afaq
    Chen, Zhanlong
    Wang, Run
    Shah, Safeer Ullah
    Shoaib, Muhammad
    Ali, Nafees
    Xu, Daozhu
    Ma, Chao
    CIVIL ENGINEERING JOURNAL-TEHRAN, 2022, 8 (02): : 209 - 224
  • [45] Spatial Landslide Susceptibility Assessment Based on Novel Neural-Metaheuristic Geographic Information System Based Ensembles
    Moayedi, Hossein
    Osouli, Abdolreza
    Dieu Tien Bui
    Foong, Loke Kok
    SENSORS, 2019, 19 (21)
  • [46] LANDSLIDE SUSCEPTIBILITY MAPPING BY USING AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)
    Choi, J.
    Lee, Y. K.
    Lee, M. J.
    Kim, K.
    Park, Y.
    Kim, S.
    Goo, S.
    Cho, M.
    Sim, J.
    Won, J. S.
    2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 1989 - 1992
  • [47] Incorporating Landslide Spatial Information and Correlated Features among Conditioning Factors for Landslide Susceptibility Mapping
    Yang, Xin
    Liu, Rui
    Yang, Mei
    Chen, Jingjue
    Liu, Tianqiang
    Yang, Yuantao
    Chen, Wei
    Wang, Yuting
    REMOTE SENSING, 2021, 13 (11)
  • [48] Geographic Information Rapid Mapping System for Emergency
    Zhu X.
    Zhao Y.
    Liu W.
    Li R.
    Zhao T.
    Peng Y.
    Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2020, 45 (08): : 1303 - 1311
  • [49] THE CONCEPT OF GEOGRAPHIC INFORMATION SYSTEM FOR KING GEORGE ISLAND
    Marczak, Sylwia
    Fijalkowska, Anna
    Osinska-Skotak, Katarzyna
    INFORMATICS, GEOINFORMATICS AND REMOTE SENSING CONFERENCE PROCEEDINGS, SGEM 2016, VOL III, 2016, : 495 - 502
  • [50] The Long Island Geographic Information System (LI GIS).
    Lynch, S.
    Anderson, L.
    Pickle, L.
    Barr, T.
    Winn, D.
    AMERICAN JOURNAL OF EPIDEMIOLOGY, 2006, 163 (11) : S26 - S26