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Remote Sensing Techniques in Disaster Management: Amynteon Mine Landslides, Greece

  • Aikaterini KaragianniEmail author
  • Ilias Lazos
  • Alexandros Chatzipetros
Conference paper
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

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 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.

References

  1. Chatzipetros A (1998) Palaeoseismological and morphotectonic study of the Mygdonia, Eastern Halkidiki and Kozani-Grevena active fault systems. PhD thesis, Aristotle University of Thessaloniki (in Greek)Google Scholar
  2. Copernicus Open Access Hub (2018). https://scihub.copernicus.eu. Accessed 23 Sept 2018
  3. Deng JS, Wang K, Deng YH, Qi GJ (2008) PCA-based land-use change detection and analysis using multitemporal and multisensor satellite data. Int J Remote Sens 29(16):4823–4838CrossRefGoogle Scholar
  4. Dimitrakopoulos D, Koumantakis I (2017) Hydrodynamic regime of Amynteon basin. Influence of open lignite mines. Paper presented at the 11th international hydrogeological congress of Greece, Athens, Greece, 4–6 Oct 2017Google Scholar
  5. Dong Y, Fu B, Ninomiya Y (2009) Geomorphological changes associated with underground coal mining in the Fushun area, northeast China revealed by multitemporal satellite remote sensing data. Int J Remote Sens 30(18):4767–4784CrossRefGoogle Scholar
  6. EarthExplorer (2018). http://earthexplorer.usgs.gov. Accessed 23 Sept 2018
  7. ERDAS Field Guide™ (2013) Intergraph Corporation, Erdas Inc., U.S.A 405, 440–445, 453–454Google Scholar
  8. Gili JA, Corominas J, Rius J (2000) Using Global Positioning System techniques in landslide monitoring. Eng Geol 55(3):167–192CrossRefGoogle Scholar
  9. Google Earth (2018). https://www.google.com/intl/el/earth. Accessed 23 Sept 2018
  10. Gungor O, Shan J (2004) Evaluation of satellite image fusion using wavelet transform. Paper presented at the XX th ISPRS Congress, Istanbul, Turkey, 12–23 July 2004Google Scholar
  11. Gupta RP, Tiwari RK, Saini V, Srivastava N (2013) A simplified approach for interpreting principal component images. Adv Remote Sens 2:111–119CrossRefGoogle Scholar
  12. Hervás J, Barredo JI, Rosin PL, Pasuto A, Mantovani F, Silvano S (2003) Monitoring landslides from optical remotely sensed imagery: the case history of Tessina landslide, Italy. Geomorphology 54:63–75CrossRefGoogle Scholar
  13. Interactive database Meteosearch (2018). http://meteosearch.meteo.gr/data/amyntaio/2017-06.txt. Accessed 23 Sept 2018
  14. Joyce KE, Belliss SE, Samsonov SV, McNeill SJ, Glassey PJ (2009) A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters. Prog Phys Geogr 33:183–207CrossRefGoogle Scholar
  15. Karagianni A, Lazaridou M (2017) Fusion of multispectral and panchromatic satellite images in environmental issues. Int J Eng Res Appl 7(7):47–50Google Scholar
  16. Kilias A, Mountrakis D (1989) The tectonic nappe of Pelagonian zone: tectonics, metamorphism and magmatism. Bull Geol Soc Greece 23:29–46 (in Greek)Google Scholar
  17. Landsat 8 Mission (2018). http://landsat.usgs.gov/landsat8.php. Accessed 23 Sept 2018
  18. Li Y, Zhao H, Fan J (2015) Application of remote sensing technology in mine environment monitoring. Paper presented at the international conference on engineering technology and application (ICETA), Taipei, Taiwan, 22–24 April 2015CrossRefGoogle Scholar
  19. Lillesand TM, Kiefer RW (1987) Remote sensing and image interpretation, 2nd edn. John Wiley and Sons, New YorkGoogle Scholar
  20. Mantovani F, Soeters R, Van Westen CJ (1996) Remote sensing techniques for landslide studies and hazard zonation in Europe. Geomorphology 15:213–225CrossRefGoogle Scholar
  21. Metternicht G, Hurni L, Gogu R (2005) Remote sensing of landslides: an analysis of the potential contribution to geo-spatial systems for hazard assessment in mountainous environments. Remote Sens Environ 98:284–303CrossRefGoogle Scholar
  22. Mountrakis D (1986) The pelagonian zone in Greece: a polyphase-deformed fragment of the cimmerian continent and its role in the geotectonic evolution of the eastern Mediterranean. J Geol 94:335–347CrossRefGoogle Scholar
  23. Navi K (2017) Satellite image processing. In: Proceedings of the fourth international conference on signal processing, communication and networking (ICSCN), Chennai, India, 16–18 March 2017Google Scholar
  24. Paull D, Banks G, Ballard C, Gillieson D (2006) Monitoring the environmental impact of mining in remote locations through remotely sensed data. Geocarto Int 21:33–42CrossRefGoogle Scholar
  25. Pavlides S (1985) Neotectonic evolution of Florina–Vegoritida–Ptolemais basin. PhD thesis, Aristotle University of Thessaloniki (in Greek)Google Scholar
  26. Pavlides S, Mountrakis D (1987) Extensional tectonics of northwestern Macedonia, Greece, since the Late Miocene. J Struct Geol 9:385–392CrossRefGoogle Scholar
  27. Pavlides SB, Zouros NC, Chatzipetros AA, Kostopoulos DS, Mountrakis DM (1995) The 13 May 1995 western Macedonia, Greece (Kozani-Grevena) earthquake; preliminary results. Terra Nova 7:544–549CrossRefGoogle Scholar
  28. Scaioni M, Longoni L, Melillo V, Papini M (2014) Remote sensing for landslide investigations: an overview of recent achievements and perspectives. Remote Sens 6:5909–5937CrossRefGoogle Scholar
  29. Sentinel-2 Mission (2018). https://sentinel.esa.int/web/sentinel/missions/sentinel-2. Accessed 23 Sept 2018
  30. STEP-Scientific Toolbox Exploitation Platform (2018). https://step.esa.int. Accessed 23 Sept 2018
  31. Tsapanos T (2005) Seismicity and seismic hazard in western Macedonia. Bull Geol Soc Greece 37:232–244Google Scholar
  32. Tzampoglou P, Loupasakis C (2016) New data regarding the ground water level changes at the Amyntaio basin–Florina Prefecture, Greece. Bull Geol Soc Greece 50:1006–1015CrossRefGoogle Scholar
  33. Tzampoglou P, Loupasakis C (2017a) Mining geohazards susceptibility and risk mapping: the case of the Amyntaio open-pit coal mine, West Macedonia, Greece. Environ Earth Sci 76:542CrossRefGoogle Scholar
  34. Tzampoglou P, Loupasakis C (2017b) Updated ground water piezometry data of the Amyntaio sub-basin and their effect on the manifestation of the land subsidence phenomena. Paper presented at the 11th international hydrogeological congress of Greece, Athens, Greece, 4–6 Oct 2017Google Scholar
  35. Tzampoglou P, Loupasakis C (2018) Evaluating geological and geotechnical data for the study of land subsidence phenomena at the perimeter of the Amyntaio coalmine, Greece. Int J Min Sci Technol 28:601–612CrossRefGoogle Scholar
  36. USGS (2018) U.S. Geological Survey. https://pubs.usgs.gov. Accessed 23 Sept 2018
  37. van Westen C (2000) Remote sensing for natural disaster management. Int Arch Photogramm Remote Sens XXXIII(Part B7):1609–1617Google Scholar
  38. Wang Q, Guo H, Chen Y, Lin Q, Li H (2013) Application of remote sensing for investigating mining geological hazards. Int J Digit Earth 6(5):449–468CrossRefGoogle Scholar
  39. Zhang Y (2004) Understanding image fusion. Photogramm Eng Remote Sens 657–661Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Aikaterini Karagianni
    • 1
    Email author
  • Ilias Lazos
    • 2
  • Alexandros Chatzipetros
    • 2
  1. 1.Laboratory of Photogrammetry – Remote Sensing, School of Civil Engineering, Faculty of EngineeringAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Laboratory of Geology and Palaeontology, School of GeologyAristotle University of ThessalonikiThessalonikiGreece

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