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

Abstract

The main purpose of this study is to develop a new hazard evaluation technique considering the current limitations, particularly for shallow landslides. For this purpose, the Buyukkoy catchment area, located in the East Black Sea Region in the east of Rize province and the south of Cayeli district, was selected as the study area. The investigations were executed in four different stages. These were (1) preparation of a temporal shallow landslide inventory of the study area, (2) assessment of conditioning factors in the catchment, (3) susceptibility analyses and (4) hazard evaluations and mapping. A total of 251 shallow landslides in the period of 1955-2007 were recognised using different data sources. A 'Sampling Circle' approach was proposed to define shallow landslide initiation in the mapping units in susceptibility evaluations. To accomplish the susceptibility analyses, the method of artificial neural networks was implemented. According to the performance analyses conducted using the training and testing datasets, the prediction and generalisation capacities of the models were found to be very high. To transform the susceptibility values into hazard rates, a new approach with a new equation was developed, taking into account the behaviour of the responsible triggering factor over time in the study area. In the proposed equation, the threshold value of the triggering factor and the recurrence interval are the independent variables. This unique property of the suggested equation allows the execution of more flexible and more dynamic hazard assessments. Finally, using the proposed technique, shallow landslide initiation hazard maps of the Buyukkoy catchment area for the return periods of 1, 2, 5, 10, 50 and 100years were produced.

Automated Spatiotemporal Landslide Mapping over Large Areas Using RapidEye Time Series Data

“…Against this background, landslide hazard and risk assessment is of great importance requiring the assessment of past process activity in the form of landslide inventories containing spatiotemporal information about occurrence and characteristics of landslides [4][5][6][7][8]. Since such inventories have to be as complete and precise as possible in time and space, multi-temporal inventories are needed, especially in regions of frequently occurring landslides [6].…”

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.…”

“…Considering the seven continuous variables, nine aspect classes, 13 lithological units, and 14 land-cover classes in binary format, a total of 43 independent variables was used in the logistic regression analyses. Of the presence (1) data, 20 % was separated for testing, with the remaining 80 % used as training data sets for both sampling strategies (Nefeslioglu et al 2011Oh and Pradhan 2011). Three different random samplings (Rnd1, Rnd2, Rnd3) were generated for each model in the separation process; 80 % of the presence (1) data was separated, and the training sets were generated by also separating 80 % of the non-presence (0) data, which is equal to 80 % of the presence (1) data in number for each random sampling.…”

“…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.…”

Identification of landslide hazard and risk ‘hotspots’ in Europe

“…Van Den Eeckhaut and Hervas (2012) present a review on available national landslide databases in Europe and use the data in a new approach to landslide susceptibility for Europe based on logistic regression modeling, . On a national or regional scale similar studies were conducted for Cuba (Castellanos Abella and Van Westen 2007), Pakistan (Peduzzi 2010), Serbia (Marjanovic et al 2011) and Turkey (Nefeslioglu et al 2011) to mention some recent examples.…”