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. Develo** 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 chapter 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). Weakened material cohesion due to fragmentation, further degraded by mining activities and hydrogeological factors led 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. 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.
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Karagianni, A., Lazos, I., Chatzipetros, A. (2019). Remote Sensing Techniques in Disaster Management: Amynteon Mine Landslides, Greece. In: Altan, O., Chandra, M., Sunar, F., Tanzi, T. (eds) Intelligent Systems for Crisis Management. Gi4DM 2018. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-030-05330-7_9
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