Landslide susceptibility mapping by using statistical analysis in the North Anatolian Fault Zone (NAFZ) on the northern part of Suşehri Town, Turkey

Gökhan Demir ()
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Gökhan Demir: Ondokuz Mayıs University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 92, issue 1, No 7, 133-154

Abstract: Abstract The main purpose of this study is to obtain the landslide susceptibility mapping and compare the models of logistic regression (LR), analytical hierarchy process (AHP), and frequency ratio (FR) applied in a part of Suşehri a long the North Anatolian Fault Zone (NAFZ, Sivas, Turkey). At first, a landslide inventory map was created from various sources such as aerial photographs, field studies, and satellite images. Then, the inventory map was randomly separated into an analysis dataset 65% for practicing the models, and the rest 35% was used for validation purpose. In analysis for landslide susceptibility, the following factors were used: lithology, slope aspect, topographical elevation, distance to stream, distance to roads, slope gradient, and distance to faults. To get speed and facility in our analysis, all descriptive and spatial information was entered into GIS system and consequently, landslide susceptibility maps were produced using models in GIS. At last for validation, the landslide susceptibility maps, the rest of the analysis dataset, which was not used in the modeling process, was considered and accomplished with operating characteristic curves and area under the curve. The results showed that the area under the curves obtained using the AHP, LR, and FR methods are 0.884, 0.837, and 0.835, respectively. In general, all three models were reasonably accurate. The resultant maps would be useful for regional spatial planning as well as for safe construction areas planning.

Keywords: Landslide susceptibility; Frequency ratio (FR); Analytical hierarchy process (AHP); Logistic regression (LR); North Anatolian Fault Zone (NAFZ); Turkey (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11069-018-3195-1

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