The administrative territory of Cluj–Napoca, due to its specific geological and geomorphological characteristics and anthropic activities, has been affected for a long time by landslides. Thus, it becomes necessary to analyse affected areas with different spatial methods, with the aim of generating landslide susceptibility maps. In this research, we studied the most prone area of the city, the Becaș stream watershed, situated in the Southern part of the municipality. The aim of this paper is to generate a valid susceptibility map, to be able to raise awareness about the existing situation: due to human induced activities and rapid urban growth, the peripheral part of Cluj–Napoca becomes more and more prone to mass–movements. We used the maximum entropy (MaxEnt) model, which was fed with accurate information on the existing landslides and seven landslide–causing factors: slope, aspect, land–use, depth of fragmentation, geology and plan– and profile curvature. The results confirm that the most influential factors are the land use and slope–angle, affected in a large degree by human activities. The accuracy of the generated map was verified using the AUC method, proving a very good performance (0.844) of theapplied model.

The last three decades have marked an unprecedented urban expansion of the city of Cluj-Napoca, leading to strong anthropogenic influences on the natural environment and important changes in the land-use. Due to the specific morphology of Cluj area, characterized by limited available plane surfaces which are insufficient to support the urban expansion, more and more territories with slopes between 5°-26° are used for constructions. These areas are marked by high risks of mass movements due to their specific geological and geomorphological characteristics, therefore the present study proposes a more detailed and complex GIS and remote sensing analysis of the western urban part of Cluj-Napoca, in order to highlight the main changes of the city and the consequences of the human actions. One of the most used radar interferometry (InSAR) technique was applied in order to detect land deformations that can threaten the infrastructure and the population. Sentinel-1B SAR imagery were processed by the DInSAR methodology, resulting in a land deformation map, which represents an important support in generating the vulnerability assessment. Based upon this evaluation, we concluded that the most vulnerable neighbourhoods to land deformations from the western part of the city are the peripheral ones, as following: Dâmbul Rotund, Bună Ziua, Europa, Mănăștur, West Iris and Făget, proving that human activity and the geological setting are the main triggering factors of the discussed phenomenon.

In the case of Cluj-Napoca Municipality, the analysis of the landslides is a frequently discussed topic due to its complex geology and urban expansion tendency. In this study, we chose the Gruia Neighbourhood in order to map the landslide evolution and land-use/land-cover (LULC) changes which occured between 2003 and 2021. In order to use the post-classification Change Detection method, we applied the supervised classification technique on three satellite imageries (2003, 2009, 2021), which were validated by high Kappa coefficient values, as it follows: 0,892, 0,879 and 0,931. Comparing the three classified imageries, we could conclude that a transition between agricultural land to urban areas is visible, with a total decrease of the agricultural land by 40,69% and a total increase of the urban area by 24,47%. In the evaluation process of the influence of the LULC change on the landslide evolution, we could observe that the increase of the urban areas led to the increase of the surface of the landslides, moreover, the slided territories on urban areas have increased by 200%.

ABSTRACT. -Relational Analysis of Susceptibility to Landslides of Settlements Situated in the Eastern and Central Part of Alba Iulia Hinterland, Using GIS Technology and MaxEnt Software. Relational analysis is an important method to analyze, generate and to predict relevant data about natural or men-made hazards. In this study, we have chosen to investigate different relations between landslides and landslide causing factors, interpolating the results and their impact on settlements. Urban and rural settlements are highly prone to landsliding because of the increased population which lives in the affected territories. Therefore, an assessment of landslide susceptibility becomes an important phase to predict the most vulnerable settlements of a certain territory in order to implement different disaster mitigation plans/works and land planning strategies. Our study area has a high tendency to landslide due to its lithological and morphological structure. Thus, our purpose is to generate a reliable and accurate analysis of the settlements using the susceptibility map generated by the MaxEnt software, based on 8 identified landslide causing factors: slope angle, slope aspect, profile and plan curvature, terrain roughness, depth of fragmentation, precipitation and temperature. The resulted map indicates a high value of accuracy, the area under the curve (AUC) showing a high performance (0.925) of our analysis.