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Turkish Journal of Agriculture and Forestry

DOI

10.3906/tar-1303-12

Abstract

Forest roads are one of the biggest investments in forest management. Their possible adverse effect on the environment is becoming an important issue for administrators due to a recent increase in public awareness. Especially in the Black Sea Region of Turkey, road-related landslides are common in forested areas because the roads are located in hilly regions with steep slopes. In addition to their impact on forests, landslides can cause damage to roadbeds which requires immediate maintenance. Landslide-susceptibility maps are widely used for different purposes such as reducing the effects of landslides, decision making, and planning. These maps can easily be generated by utilizing the advanced features of Geographical Information Systems (GIS) and computer technologies. Logistic regression (LR) is a widely used technique for mapping landslide susceptibility; landslide conditioning parameters such as topography, lithology, land use, distance to streams and roads, and curvature can be mapped by GIS tools. In this study a fieldwork-generated inventory of 288 landslides was used to produce a landslide-susceptibility map for the Yığılca Forest Directorate (Turkey). This map was generated by applying a GIS-based LR method. Land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature were considered as the landslide conditioning parameters. After the landslide-susceptibility map was divided into 5 classes of susceptibility (very low, low, moderate, high, and very high), it was overlapped with a road network map in order to evaluate forest road conditions in terms of landslide susceptibility. For a quantitative analysis of forest road-landslide interaction, 2 new parameters were determined: a landslide frequency index (divided into general and real) and a road-landslide index (divided into general and real). Real landslide frequency and general landslide frequency on the roads were found to be 0.42 and 0.18, respectively. The results showed that the real road-landslide index and the general road-landslide index in the area were 0.10 and 0.04, respectively.

Keywords

Forest road networks, landslide frequency, landslide susceptibility, logistic regression, road-landslide index, Yığılca

First Page

281

Last Page

290

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