Abstract
Landslide susceptibility mapping is a practical tool in natural and urban planning; it can be applied for determining land use zones, in construction design and planning of a variety of projects. In this study, two different GIS based landslide susceptibility maps were generated in the mountainous part of the Trikala Prefecture in Thessaly, Central Greece. This was accomplished by using different methods for correlating factors, which have an effect on landslide occurrences. The instability factors taken into account were: lithology, tectonic features, slope gradients, road network, drainage network, land use and rainfall. A frequency distribution of the half number of the landslide events of the study area in each class of the instability factors was performed in order to rate the classes. Two models have been used to combine the instability factors and assess the overall landslide susceptibility, namely: the Weight Factor Model (WeF), which is a statistical method, and the Multiple Factor Model (MuF) that is a logical method. The produced maps were classified into four zones: Low, Moderate, High and Very High susceptible zones and validated using the other half number of the landslide events of the area. Evaluation of the results is optimized through a Landslide Models Indicator (La.M.I.).
Highlights
Landslide is a major and common natural hazard
The lithological formations were classified upon their geotechnical characteristics
The landslide susceptibility map is necessary for the definition of the land use zones and for the design of future construction projects
Summary
Landslide is a major and common natural hazard. In Greece, natural disasters such as earthquakes, floods, and especially landslides, are widespread having sizable impact on rural (or national) economy. The use of landslide susceptibility and hazard maps for land use planning has drastically increased. The aim of these maps is to rank different sections of land surface according to the degree of actual or potential landslide hazard. Planners are capable of selecting favorable sites for urban and rural development to prevent landslide hazards. The reliability of those maps depends mostly on the applied methodology as well as the available data used for the hazard risk estimation (Parise, 2001)
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