REMOTE SENSING TECHNIQUES IN DISASTER MANAGEMENT: AMYNTEON MINE LANDSLIDES, GREECE
- 1Aristotle University of Thessaloniki, School of Civil Engineering, Faculty of Engineering, Lab. of Photogrammetry – Remote Sensing, Thessaloniki, Greece
- 2Aristotle University of Thessaloniki, School of Geology, Lab. of Geology and Palaeontology, Thessaloniki, Greece
Keywords: remote sensing, digital image processing, image interpretation, fault zones, disaster management, landslides
Abstract. Natural or man-made disasters are phenomena that can affect large areas and have many environmental, societal and economic impacts. Landslides are among the major disasters of large scale that may affect the natural environment as well as urban areas, often causing massive destruction, loss of property, or even fatalities worldwide. Developing tools that are effective for disaster management is imperative to monitor and mitigate their effect. Satellite data and remote sensing techniques, combined with geological data and studies can provide valuable information regarding monitoring of natural hazards in general and especially of landslides. This paper concerns the ex ante and ex post study of a complex set of landslides that occurred in the lignite mine of Amynteon in north-western Greece (June 2017), where large masses of Neogene lacustrine and Quaternary fluvial sediments were detached and moved. The study area is located at the transfer zone between the overlapping tips of two large NE-SW trending normal fault zones affecting the overlying sediments: the NW-dipping Anargyri fault and the SE-dipping Vegora fault. The fragmentation caused by these fault zones weakened the material cohesion, which was further degraded by mining activities and hydrogeological factors, leading to the catastrophic event. The landslide occurred in along the south faces of the mine, resulting to extended collapses, destruction of mining machinery, evacuation of the adjacent Anargyri village and a big financial impact that has not yet been determined. Landsat 8 and Sentinel-2 satellite data acquired before and after the event are being used. Digital image processing techniques are applied for change detection. In addition, geological data are being used to provide information about the geological background of the area and landslides vulnerability. Visual interpretation of the area affected by the landslides is also being done, contributing to the overall study.