Landside sensitivity model creation based on SMCA-GIS with verification of point coordinate variation


Saygin F., Dengiz O.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s13762-024-05766-7
  • Dergi Adı: INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Compendex, Environment Index, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

The primary goal of the present study was to use Spatial Multi-Criterion Analysis (SMCA) management based on the integration of Analytical Hierarchical Process (AHP) and Geographic Information System (GIS) approaches to construct a landslide susceptibility mapping model for the Central Black Sea region. Four different main indicators (topography, land use-land cover, geology, and soil) were determined in the model, and maps related to them were produced using GIS. According to the present model, 10.0% of the research area was found to be in the high-risk class, whereas 30.3% were in the low and very low-risk classes. On the other hand, the medium-risk class covered more than half of the study area. Moreover, measurements were taken on a control network consisting of fifteen points, and mobility was observed to verify the model in the study area. For this purpose, the coordinates obtained from the measurements made in six different periods were compared, and the results revealed that the coordinate difference values were agreed with the model data. Finally, the landslide susceptibility mapping model showed parallel with field validation. The current study is a guide for reducing the impact of natural disasters by monitoring landslide areas.