Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey)

Abstract

In the international literature, although considerable amount of publications on the landslide susceptibility mapping exist, geomorphology as a conditioning factor is still used in limited number of studies. Considering this factor, the purpose of this article paper is to implement the geomorphologic parameters derived by reconstructed topography in landslide susceptibility mapping. According to the method employed in this study, terrain is generalized by the contours passed through the convex slopes of the valleys that were formed by fluvial erosion. Therefore, slope conditions before landsliding can be obtained. The reconstructed morphometric and geomorphologic units are taken into account as a conditioning parameter when assessing landslide susceptibility. Two different data, one of which is obtained from the reconstructed DEM, have been employed to produce two landslide susceptibility maps. The binary logistic regression is used to develop landslide susceptibility maps for the Melen Gorge in the Northwestern part of Turkey. Due to the high correct classification percentages and spatial effectiveness of the maps, the landslide susceptibility map comprised the reconstructed morphometric parameters exhibits a better performance than the other. Five different datasets are selected randomly to apply proper sampling strategy for training. As a consequence of the analyses, the most proper outcomes are obtained from the dataset of the reconstructed topographical parameters and geomorphologic units, and lithological variables that are implemented together. Correct classification percentage and root mean square error (RMSE) values of the validation dataset are calculated as 86.28% and 0.35, respectively. Prediction capacity of the different datasets reveal that the landslide susceptibility map obtained from the reconstructed parameters has a higher prediction capacity than the other. Moreover, the landslide susceptibility map obtained from the reconstructed parameters produces logical results.

Modification of seed cell sampling strategy for landslide susceptibility mapping: an application from the Eastern part of the Gallipoli Peninsula (Canakkale, Turkey)

“…Actually, this suggestion directly points out the necessity to determine the pre-failure conditions of landslides because it is not always possible to reach exact topographical conditions at the time of landslide occurrence in particular. However, few studies investigating this research topic have been published in recent literature (Suzen and Doyuran 2004;Clerici et al 2006;Gorum et al 2008;Nefeslioglu et al 2011). For this reason, research into the determination of the pre-failure conditions of landslides remains crucial in spite of its limitations.…”

“…For example, Nefeslioglu et al (2008) stated that the conceptual differentiation of different sampling strategies applied during susceptibility evaluations is commonly ignored and is no longer event stated. In the literature, a few researchers (Suzen and Doyuran 2004;Clerici et al 2006;Gorum et al 2008;Nefeslioglu et al 2008;Yilmaz 2010;Nefeslioglu et al 2011) have taken differences in sampling strategies into account and have suggested different sampling strategy methods in their studies. Suzen and Doyuran (2004) proposed a seed cell sampling strategy, creating buffer zones to the crown and the flanks of landslides; Clerici et al (2006) suggested a shell script and took into account selected factor cells defined on the upper edge of the main scarps of landslides; Gorum et al (2008) concluded the utility of geomorphological parameters derived from the reconstructed topography, and Nefeslioglu et al (2011) proposed a sampling circle approach for determination of the conditioning factors of shallow and small sized landslides that cannot be mapped at medium scale.…”

Gis-Based Determination of Landslide Properties in Regional Scale: Karabuk Province (NW Turkey)

“…Databased bivariate and multivariate statistical analysis methods were studied about landslides (Suzen and Doyuran, 2004a). Geomorphological parameters were also used to determine landslide susceptibility maps and properties (Gorum et al, 2008). Another study is conducted to investigate the parameter effects in preparing landslide susceptibility maps with a data-driven approach and adaptation of this approach to analytical hierarchy process (AHP) (Hasekiogullari and Ercanoglu, 2012).…”

Medium-scale hazard mapping for shallow landslide initiation: the Buyukkoy catchment area (Cayeli, Rize, Turkey)

“…Considering the extent of the study area and the areal distribution of the shallow landslides, the mapping unit for the study was selected as grid cells with a spatial resolution of 10×10 m 2 (100 m 2 ). In the event that areal mapping of landslides can be established, different approaches from recent literature (Suzen and Doyuran 2004;Clerici et al 2006;Gorum et al 2008) can be applied to extract pre-failure conditions. However, there has been no suggestion in the literature to extract conditioning factors in cases where areal 1990; b 1990-2000; c 2000-2004; d 2004-2007 Original Paper…”