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https://hdl.handle.net/20.500.14279/36389| Title: | A GIS-based multi-criteria decision analysis framework for landslide risk assessment: a case study in Amathounta, Limassol, Cyprus | Authors: | Doukanari, Marina Tzouvaras, Marios Fotiou, Kyriaki Stylianou, Neophytos Mettas, Christodoulos Hadjimitsis, Diofantos G. |
Major Field of Science: | Natural Sciences | Field Category: | NATURAL SCIENCES | Keywords: | GIS;Multi-Criteria Decision Analysis;Analytic Hierarchy Process;Landslide Risk Assessment;Predictive Modeling;Hazard Zonation | Issue Date: | 19-Sep-2025 | Source: | Proceedings of SPIE, 2025, vol. 13816, pp. 138161Q‑7 | Volume: | 13816 | Project: | ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment | Conference: | Eleventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2025) | Abstract: | Landslides pose significant risks to both infrastructure and environmental systems, making efficient risk assessment and management strategies essential. This research combines Multi-Criteria Decision Analysis (MCDA) with Geographic Information Systems (GIS) to assess landslide susceptibility in the Amathounta region of Limassol Cyprus. Nine key factors influencing slope stability were selected, including slope, aspect, relief, precipitation, land use, proximity to roads, lithology, faults, and streams—sourced from both national agencies and open datasets. A 5-meter resolution Digital Elevation Model (DEM) supported the extraction of terrain-related parameters, while geological and meteorological data were obtained from official sources. Remote sensing and spatial analysis techniques were used to prepare the input layers, and the Analytic Hierarchy Process (AHP) was employed to weight each criterion based on expert judgment and regional studies. These weighted layers were integrated using a structured overlay approach in ArcGIS Pro to generate a detailed landslide susceptibility map. The final output categorizes the study area into five hazard levels, from very low to very high risk. Validation using a local landslide inventory showed strong spatial agreement with the high-risk zones, confirming the robustness of the approach. The research provides important findings for Amathounta land-use planning and hazard mitigation and establishes a transferable method for other areas in Cyprus. The upcoming research will concentrate on expanding the model across the national territory and adding soil characteristics together with socio-economic data and real-time monitoring systems to boost predictive accuracy. | URI: | https://hdl.handle.net/20.500.14279/36389 | DOI: | 10.1117/12.3075513 | Type: | Conference Paper | Affiliation : | ERATOSTHENES Centre of Excellence Cyprus University of Technology |
Funding: | This study was conducted in the framework of ‘EXCELSIOR’ : ERATOSTHENES: EXcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programmeunder Grant Agreement No. 857510, from the Government of the Republic of Cyprus through the Directorate General forthe European Programmes, Coordination and Development and the Cyprus University of Technology. The authors also acknowledge the AI-OBSERVER project that received funding from the European Union’s Horizon Europe Framework Programme HORIZON-WIDERA-2021-ACCESS-03 (Twinning) under the Grant Agreement No. 101079468. | Publication Type: | Peer Reviewed |
| Appears in Collections: | EXCELSIOR H2020 Teaming Project Publications |
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| 138161Q.pdf | 691.18 kB | Adobe PDF | View/Open |
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