Statistical Landslide Prediction Map As A Basis For A Risk Map
Free (open access)
Issues connected with unwanted natural occurrences, such as landslides, floods or earthquakes, are a source of concern around the world and Slovenia is no exception. Today, we cannot envisage spatial modelling and prediction of various events without information technology. GIS is also used to analyse the landslide data and satellite images can serve as a support to the ground reconnaissance. Using the methods of univariate statistics, the influences of individual spatial factors in a form of different spatial data, on the different landslide types and on landslides generally were tested. Using multivariate statistical methods (Factor and Regression analysis), the interactions between factors and landslide distribution were tested, and the importance of individual factors on landslide occurrence was defined. Having combined all the spatial data available, several models were developed. Those that produced the best results were then used to determine and locate the potentially hazardous areas and to produce a landslide hazard map. The landslide hazard map enabled the assessment of the risk to the inhabitants and roads on the tested area. It was determined that on the tested area where roughly 135,000 people live, around 3% of the population live in the high risk areas, and 20–25% of the population live in areas that are considered to be landslide-prone. More than half of the roads lie in areas subject to ground mass movement and 5% of all roads lie in high-risk areas. Keywords: geology, landslide prediction, multivariate statistics, landslide risk map, Slovenia. 1 Introduction As a result of the recent natural disasters in Europe, like floods in 2002, the need for a better understanding of natural phenomena has arisen. Independently of
geology, landslide prediction, multivariate statistics, landslide risk map, Slovenia.