A new approach to spatial risk analysis in the long-term (1950–2020) assessment of natural disasters (avalanche, landslide, rockfall, flood) in Turkey

It would be beneficial to consider the results of the long-term evaluation of natural disasters in the decision-making process for disaster damage reduction/prevention. However, disaster evaluation is a complex and time-consuming process depending on different factors such as data type and data period. In this study, a new approach is proposed to determine the risk groups of the provinces in Turkey according to the disaster types (avalanche, landslide, rockfall, and flood) at regional and national scales. Disaster data between 1950 and 2020 were evaluated by considering the number of disasters in the provinces. The obtained data were subjected to cluster analysis, and then, the cluster groups were converted into risk classes. Finally, the risk weight ratios of the provinces and regions were calculated and thematically mapped by integrating them with GIS methods. According to the results, when four disaster types were considered together, Trabzon is the riskiest province on a provincial basis and the Black Sea is the riskiest region on a regional basis in Turkey. Additionally, the results of the study show that cluster analysis offers an effective solution for the evaluation of long-term large datasets. Furthermore, it was found that the new approach, which is used to minimize the errors that may be caused by surface area differences, makes a significant contribution to the evaluation process. This new approach will make a positive contribution to the analysts at the stage of giving priority to disasters and establishing protective and preventive policies on a national and global scale.