Landslide susceptibility mapping for Ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis


AKGÜN A., Turk N.

ENVIRONMENTAL EARTH SCIENCES, cilt.61, sa.3, ss.595-611, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 61 Sayı: 3
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1007/s12665-009-0373-1
  • Dergi Adı: ENVIRONMENTAL EARTH SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.595-611
  • Anahtar Kelimeler: Landslide, GIS, Fuzzy logic, Multi-criteria decision analysis, Turkey, ARTIFICIAL NEURAL-NETWORKS, LOGISTIC-REGRESSION, LAND-COVER, INFORMATION-SYSTEM, FREQUENCY RATIO, IMAGE-ANALYSIS, GIS, HAZARD, MULTIVARIATE, ALGORITHMS
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

This paper presents the results of geographical information system (GIS)-based landslide susceptibility mapping in AyvalA +/- k, western Turkey using multi-criteria decision analysis. The methodology followed in the study includes data production, standardization, and analysis stages. A landslide inventory of the study area was compiled from aerial photographs, satellite image interpretations, and detailed field surveys. In total, 45 landslides were recorded and mapped. The areal extent of the landslides is 1.75 km(2). The identified landslides are mostly shallow-seated, and generally exhibit progressive character. They are mainly classified as rotational, planar, and toppling failures. In all, 51, 45, and 4% of the landslides mapped are rotational, planar, and toppling types, respectively. Morphological, geological, and land-use data were produced using existing topographical and relevant thematic maps in a GIS framework. The considered landslide-conditioning parameters were slope gradient, slope aspect, lithology, weathering state of the rocks, stream power index, topographical wetness index, distance from drainage, lineament density, and land-cover and vegetation density. These landslide parameters were standardized in a common data scale by fuzzy membership functions. Then, the degree to which each parameter contributed to landslides was determined using the analytical hierarchy process method, and the weight values of these parameters were calculated. The weight values obtained were assigned to the corresponding parameters, and then the weighted parameters were combined to produce a landslide susceptibility map. The results obtained from the susceptibility map were evaluated with the landslide location data to assess the reliability of the map. Based on the findings obtained in this study, it was found that 5.19% of the total area was prone to landsliding due to the existence of highly and completely weathered lithologic units and due to the adverse effects of topography and improper land use.