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
A.S. NICULA1, KEREKES ANNA‐HAJNALKA2, V. V. POP2, GH. ROȘIAN3
1 Babeș‐Bolyai University, Faculty of Geography, Centre for Research on Settlements and Urbanism, Cluj‐Napoca, Romania, email@example.com
2 Babeș‐Bolyai University, Faculty of Geography, Cluj‐Napoca, Romania
3 Babeș‐Bolyai University, Faculty of Environmental Science and Engineering, Cluj‐Napoca, Romania
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.
Keywords: vulnerability, settlements, GIS, MaxEnt, Alba Iulia, hinterland, ROC curve.