An Overview on the Landslide Susceptibility Assessment Techniques

被引:0
|
作者
Ercanoglu, Murat [1 ]
机构
[1] Hacettepe Univ, Geol Engn Dept, TR-06800 Beytepe, Turkey
关键词
Landslide; landslide susceptibility; GIS; hazard; risk; remote sensing;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Natural disasters and their consequences have considerable and destructive effects on human life, properties, infrastructures, and, of course, on environment. One of the most important natural hazards, landslide plays a very important role in these effects throughout the world. Therefore, many countries, particularly the developed ones, invest huge amount of money either in mitigation or in prevention of landslides. The first, and probably the most important, stage of mitigation and/or prevention efforts is to assess landslide susceptibility by obtaining data related to landslides, i.e. preparation of landslide inventory and database. If taken into consideration, results of these assessments, i.e. landslide susceptibility maps, will provide useful information and economic benefits for urban planning, development plans, engineering applications, land use potential planning, and so on. When international scientific literature related to landslide assessments is examined, there has been an increasing interest in landslide susceptibility mapping studies in the last decades, instead of evaluating hazard and/or risk. Particularly, in recent years, depending upon the breakthroughs in computer technology, GIS (Geographic Information System), and RS (Remote Sensing) techniques, very important developments were achieved in these studies. This can be concluded as one of the most promising efforts with respect to combat with natural hazards since they opened wide range of opportunities for analyzing, evaluating, and assessing earth processes, notably for landslides. Thus, there are a multitude of studies carried out by different researchers in different parts of the world with the aid of these technological items. In this study, it was aimed at assessing landslide susceptibility techniques by means of a detailed literature survey based on an overview including twenty years' experiences. The techniques were categorized into two distinct groups such as qualitative and quantitative ones, and briefly examined individually. By doing so, a historical development of the techniques and actual trends in landslide susceptibility assessments were evaluated. It was revealed that some traditional methods seemed to have disappeared, while the new ones, particularly included in the GIS software, became very popular. However, at present, there seems to be no agreement on these techniques which can be the most effective one among the researchers.
引用
收藏
页码:131 / 134
页数:4
相关论文
共 50 条
  • [1] Assessment of shallow landslide susceptibility by means of statistical techniques
    Baeza, C
    Corominas, J
    [J]. LANDSLIDES-BK, 1996, : 147 - 152
  • [2] Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview
    van Westen, Cees J.
    Castellanos, Enrique
    Kuriakose, Sekhar L.
    [J]. ENGINEERING GEOLOGY, 2008, 102 (3-4) : 112 - 131
  • [3] Assessment of shallow landslide susceptibility by means of multivariate statistical techniques
    Baeza, C
    Corominas, J
    [J]. EARTH SURFACE PROCESSES AND LANDFORMS, 2001, 26 (12) : 1251 - 1263
  • [4] Landslide susceptibility assessment in multiple urban slope settings with a landslide inventory augmented by InSAR techniques
    Chen, Li
    Ma, Peifeng
    Yu, Chang
    Zheng, Yi
    Zhu, Qing
    Ding, Yulin
    [J]. ENGINEERING GEOLOGY, 2023, 327
  • [5] Application of Artificial Intelligence and machine learning techniques for landslide susceptibility assessment
    Ospina-Gutierrez, Juan Pablo
    Aristizabal, Edier
    [J]. REVISTA MEXICANA DE CIENCIAS GEOLOGICAS, 2021, 38 (01): : 43 - 54
  • [6] Effects of Variable Selection on the Landslide Susceptibility Assessment using Machine Learning Techniques
    Park, Soyoung
    Son, Sanghun
    Han, Jihye
    Lee, Seonghyeock
    Kim, Seongheon
    Kim, Jinsoo
    [J]. EARTH RESOURCES AND ENVIRONMENTAL REMOTE SENSING/GIS APPLICATIONS X, 2019, 11156
  • [7] Overview Landslide Hazard Assessment of China
    Yin Kunlong Zhang Guirong Faculty of Engineering
    [J]. Journal of Earth Science, 2004, (03) : 67 - 72
  • [8] Landslide susceptibility assessment and mapping using state-of-the art machine learning techniques
    Pourghasemi, Hamid Reza
    Sadhasivam, Nitheshnirmal
    Amiri, Mahdis
    Eskandari, Saeedeh
    Santosh, M.
    [J]. NATURAL HAZARDS, 2021, 108 (01) : 1291 - 1316
  • [9] Landslide risk assessment and management: an overview
    Dai, FC
    Lee, CF
    Ngai, YY
    [J]. ENGINEERING GEOLOGY, 2002, 64 (01) : 65 - 87
  • [10] Landslide susceptibility assessment and mapping using state-of-the art machine learning techniques
    Hamid Reza Pourghasemi
    Nitheshnirmal Sadhasivam
    Mahdis Amiri
    Saeedeh Eskandari
    M. Santosh
    [J]. Natural Hazards, 2021, 108 : 1291 - 1316