GIS-Based Landslide Susceptibility Modelling in Urbanized Areas: A Case Study of the Tri-City Area of Poland

Abstract

This paper presents the results of landslide prediction modelling for young glacial areas performed using statistical methods. The area in question is urbanized and therefore mass wasting activity is a matter of interest to both the local community and the authorities. The analysis was based on the 2011 “Register of landslides and areas prone to mass movements with a scale of 1:10,000 for the city of Gdańsk” and the 2012 incomplete “Register of landslides and areas prone to mass movements with a scale of 1:10,000 for the city of Gdynia”. The research took into account geological, geomorphological, hydrological, hydrogeological, and anthropogenic conditions. The landslide susceptibility map was created using the statistical landslide index. The calculated indices were used to create a map of Gdańsk’s landslide susceptibility. In Gdańsk, 84.50% of the total diagnosed landslide area belongs to the high susceptibility class, 14.25% to the moderate susceptibility class, and only 1.25% to the low or very low susceptibility class. After extrapolation, the data was also used to create a susceptibility map for the remaining parts of the Tri-City area, Sopot and Gdynia. The difficulty of extrapolating landslide data for neighboring urban areas was indicated. In Gdańsk, which had been covered by geological mapping, the best modelling results were obtained with a large number of causal factors. In Gdynia and Sopot, for which the statistical landslide index value was extrapolated from Gdańsk, the best results were obtained when selected causal factors were considered. In Sopot and Gdynia, 81.6% of the landslide area belongs to the high susceptibility class, 15.1% to the moderate class, and 3.3% to the low susceptibility class. These results emphasize a different role of some causal factor classes in the occurrence of landslides in neighboring urban areas. The resultant maps show the areas in which mass wasting is the most probable in the future.

Mass-Movement Causes and Landslide Susceptibility in River Valleys of Lowland Areas: A Case Study in the Central Radunia Valley, Northern Poland

“…In the current study, the best susceptibility model was obtained using a large number of causal factors, i.e., 25, which suggests that many different factors influence susceptibility in lowlands (young morainic areas). This is confirmed by the results of previous susceptibility assessments in lowland areas: Gda ńsk and Gdynia [20,69] and the Lower Vistula Valley [93].…”

“…The LR method was selected because of its greater reliability compared to other methods of susceptibility assessment; this aspect has been confirmed by many results of verification using ROC curves [66][67][68]. Furthermore, considering other studies on young morainic areas [20,69], it is expected that these models are suitable for achieving highly accurate landslide modelling at the regional level. This method is based on the following formula:…”

“…During the period between 1951 and 2015, the average annual air temperature recorded at Chojnice station was 7.1 • C. However, the seasonal average air temperatures are changeable, corresponding to 16.3 • C in the summer (with a maximum of 21.8 • C and a minimum of 11.4 • C) and −1.9 • C in the winter (with a maximum of 0.6 • C and a minimum of −4.1 • C) [32]. The study area has a fairly large number of mean annual frost (69) and ice (42) days [32]. In terms of geomorphology, the study area is located within a small outwash plain [33,34].…”

“…Topographic attributes developed using a DEM play an important role in the modelling of landslide formation as they depict various geomorphological and hydrogeological processes. The usefulness of topographic attributes in susceptibility analyses has been highlighted by various authors [19,20,59,69,87,95,96,108]. Susceptibility assessments are conducted on a global, European, national, and local scale [93,109,110,110,111].…”

Landslide Susceptibility Assessment and Future Prediction with Land Use Change and Urbanization towards Sustainable Development: The Case of the Li River Valley in Yongding, China

“…Since the economic reforms of 1987, China has experienced a swift phase of urban expansion. Some regions have witnessed a rise in geological hazards due to suboptimal urban planning and risk management practices [1][2][3][4]. Landslide susceptibility (LS) refers to the likelihood of landslide occurrences within a specific region, and landslide susceptibility assessment (LSA) involves forecasting the potential for future landslides by integrating both quantitative and qualitative approaches with pertinent factors that influence landslide events [5,6].…”