GIS-based landslide susceptibility mapping using bivariate statistical analysis in Devrek (Zonguldak-Turkey)

被引:116
|
作者
Yilmaz, Cagatay [1 ]
Topal, Tamer [1 ]
Suzen, Mehmet Lutfi [1 ]
机构
[1] Middle E Tech Univ, Dept Geol Engn, TR-06531 Ankara, Turkey
关键词
Bivariate analysis; GIS; Landslide susceptibility mapping; Seed cell; Devrek; Turkey; ARTIFICIAL NEURAL-NETWORKS; BLACK-SEA REGION; LOGISTIC-REGRESSION ANALYSIS; CONDITIONAL-PROBABILITY; FREQUENCY RATIO; SAMPLING STRATEGIES; AERIAL PHOTOGRAPHS; HAZARD EVALUATION; LESSER HIMALAYA; NATURAL SLOPES;
D O I
10.1007/s12665-011-1196-4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Devrek town with increasing population is located in a hillslope area where some landslides exist. Therefore, landslide susceptibility map of the area is required. The purpose of this study was to generate a landslide susceptibility map using a bivariate statistical index and evaluate and compare the results of the statistical analysis conducted with three different approaches in seed cell concept resulting in different data sets in Geographical Information Systems (GIS) based landslide susceptibility mapping applied to the Devrek region. The data sets are created from the seed cells of (a) crowns and flanks, (b) only crowns, and (c) only flanks of the landslides by using ten different causative parameters of the study area. To increase the data dependency of the analysis, all parameter maps are classified into equal frequency classes based directly on the percentile divisions of each corresponding seed cell data set. The resultant maps of the landslide susceptibility analysis indicate that all data sets produce fairly acceptable results. In each data set analysis, elevation, lithology, slope, aspect, and drainage density parameters are found to be the most contributing factors in landslide occurrences. The results of the three data sets are compared using Seed Cell Area Indexes (SCAI). This comparison shows that the crown data set produces the most accurate and successful landslide susceptibility map of the study area.
引用
收藏
页码:2161 / 2178
页数:18
相关论文
共 50 条
  • [21] Landslide Susceptibility Mapping Using Bivariate Statistical Models and GIS in Chattagram District, Bangladesh
    Chowdhury, Md Sharafat
    Hafsa, Bibi
    GEOTECHNICAL AND GEOLOGICAL ENGINEERING, 2022, 40 (07) : 3687 - 3710
  • [22] GIS-based landslide susceptibility mapping for a part of the North Anatolian Fault Zone between Resadiye and Koyulhisar (Turkey)
    Demir, Gokhan
    CATENA, 2019, 183
  • [23] Landslide susceptibility mapping (LSM) of Swat District, Hindu Kush Himalayan region of Pakistan, using GIS-based bivariate modeling
    Islam, Fakhrul
    Riaz, Salma
    Ghaffar, Bushra
    Tariq, Aqil
    Shah, Safeer Ullah
    Nawaz, Muhammad
    Hussain, Mian Luqman
    Ul Amin, Naz
    Li, Qingting
    Lu, Linlin
    Shah, Munawar
    Aslam, Muhammad
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [24] GIS-based landslide susceptibility zonation using bivariate statistical and expert approaches in the city of Constantine (Northeast Algeria)
    Hamid Bourenane
    Youcef Bouhadad
    Mohamed Said Guettouche
    Massinissa Braham
    Bulletin of Engineering Geology and the Environment, 2015, 74 : 337 - 355
  • [25] A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping
    Kamran, Khalil Valizadeh
    Feizizadeh, Bakhtiar
    Khorrami, Behnam
    Ebadi, Yousef
    APPLIED GEOMATICS, 2021, 13 (04) : 837 - 851
  • [26] Gully erosion susceptibility mapping: the role of GIS-based bivariate statistical models and their comparison
    Omid Rahmati
    Ali Haghizadeh
    Hamid Reza Pourghasemi
    Farhad Noormohamadi
    Natural Hazards, 2016, 82 : 1231 - 1258
  • [27] GIS-based landslide susceptibility mapping using logistical regression method with LiDAR data in nature slopes
    Wang Liangjie
    Kazuhide, Sawada
    Shuji, Moriguchi
    DISASTER ADVANCES, 2012, 5 (04): : 258 - 263
  • [28] Landslide susceptibility mapping using GIS-based statistical and machine learning modeling in the city of Sidi Abdellah, Northern Algeria
    Hamid, Bourenane
    Massinissa, Braham
    Nabila, Guessoum
    MODELING EARTH SYSTEMS AND ENVIRONMENT, 2023, 9 (02) : 2477 - 2500
  • [29] GIS-based landslide susceptibility modeling using data mining techniques
    Xia, Liheng
    Shen, Jianglong
    Zhang, Tingyu
    Dang, Guangpu
    Wang, Tao
    FRONTIERS IN EARTH SCIENCE, 2023, 11
  • [30] GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method
    Chen, Wei
    Xie, Xiaoshen
    Peng, Jianbing
    Shahabi, Himan
    Hong, Haoyuan
    Dieu Tien Bui
    Duan, Zhao
    Li, Shaojun
    Zhu, A-Xing
    CATENA, 2018, 164 : 135 - 149