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

YİLMAZ C., Topal T., Suzen M. L.

ENVIRONMENTAL EARTH SCIENCES, cilt.65, sa.7, ss.2161-2178, 2012 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 65 Sayı: 7
  • Basım Tarihi: 2012
  • Doi Numarası: 10.1007/s12665-011-1196-4
  • Dergi Adı: ENVIRONMENTAL EARTH SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2161-2178
  • Anahtar Kelimeler: 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
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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.