The purpose of this study is to present a Bayesian approach (weight-of-evidence

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The main objective of this paper is to classify landforms in Kimi municipality area of Euboea Island, Greece using advanced spatial techniques. Landform categories were determined by conducting morphometric analysis through the use of advanced GIS functions. In particular, the process of classifying the landscape into landform categories was based on Topographic Position Index (TPI). The main topographic elements such as slope inclination, aspect, slope shape (curvature), topographic wetness index and stream power index were obtained from the DEM file of the study area. Landform classification was obtained using TPI grids and the classes were related with the geological pattern and the land cover by sophisticated spatial analysis function. The knowledge obtained from the present study could be useful in identifying areas prone to land degradation and instability problems in which landforms are identified as an essential parameter

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The  paper  attempts  to  illustrate  the  value  of  Geological  data,  information  and knowledge in studies that investigate landslide phenomena and how this is reflected in the production of landslide susceptibility maps. In particular, the concepts  of data, information, knowledge and wisdom are defined and also the process of converting data into information and information into knowledge. The presented study continuous with a summary that introduces landslide phenomena and the available techniques and methods for identifying and classifying these natural phenomena. It describes the significance of landslide analysis and how this process is essential in order to orient intelligence decisions regarding strategies for regional and urban development. The susceptibility maps that are considered as the outcomes of the over mentioned process, reflects the Geological Knowledge that has been produced by involving expert knowledge and processing data.

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