Analyzing landslide susceptibility of forest roads by analytical hierarchy process (AHP) in of forest planning unit of Turkiye


MUMCU KÜÇÜKER D.

Natural Hazards, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2024
  • Doi Number: 10.1007/s11069-024-06882-w
  • Journal Name: Natural Hazards
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Environment Index, Geobase, INSPEC, Metadex, PAIS International, Pollution Abstracts, Veterinary Science Database, DIALNET, Civil Engineering Abstracts
  • Keywords: Forest roads, Geographical information systems, Multicriteria evaluation method, Risk analysis, Susceptibility mapping, Validation
  • Karadeniz Technical University Affiliated: Yes

Abstract

Forest roads are essential for the management of forest goods and services. The interests in Landslide Susceptibility Maps (LSMs) an important decision basis has become one of the crucial concerns in landslide risk areas in order to determine where to build new roads or to take necessary precautions on existing roads. This study aims to reveal the potential risk of forest roads for landslide in the Of Planning Unit. The forest roads located in Black Sea Region in Turkiye covering this area, suffer from landslides due to geologic and climatic condition. For this purpose, LSM was created by combining the MCDA Analytical Hierarchy Process (AHP) related to expert knowledge and Geographic Information Systems (GIS). Twelve landslide-related criteria, including slope, bedrock type, relative relief, drainage density and frequency, rainfall, and land cover, were fabricated in raster format by ArcGIS domain. After the effects or weights of each factor were calculated by the pairwise comparison matrix in AHP, each layer was assigned to weight. The potential landslide areas were separated into five different categories, including extremely low, low, moderate, high, and extremely high through overlay analysis in ArcMap. Then overlapping analysis with forest roads and LSM was performed to obtain information on what planned roads are located in landslide-prone areas. The results indicated that this area is greatly susceptible to landslides. In addition, 18.45% of all roads are detected to be under high and extremely high risk, 28.7% of all roads are figured out to be under moderate susceptibility classes, and the remains are found to be under low and extremely low susceptibility classes. With respect to the high performance of AUC value (81%), the AHP technique can be used in landslide hazard risk management. The implemented methodology may be an effective tool for local authorities and decision-makers in the planning of road networks.