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Automated derivation and spatio-temporal analysis of landslide properties in southern Kyrgyzstan

Author

Listed:
  • Darya Golovko

    (GFZ German Research Centre for Geosciences)

  • Sigrid Roessner

    (GFZ German Research Centre for Geosciences)

  • Robert Behling

    (GFZ German Research Centre for Geosciences)

  • Birgit Kleinschmit

    (Technical University Berlin)

Abstract

The study area located in southern Kyrgyzstan is affected by high and ongoing landslide activity. To characterize this activity, a multi-temporal landslide inventory containing over 2800 landslide polygons was generated from multiple data sources. The latter include the results of automated landslide detection from multi-temporal satellite imagery. The polygonal representation of the landslides allows for characterization of the landslide geometry and determination of further landslide attributes in a way that accounts for the diversity of conditions within the landslide, e.g., at the landslide main scarp opposed to its toe. To perform such analyses, a methodology for efficient geographic information system (GIS)-based attribute derivation was developed, which includes both standard and customized GIS tools. We derived a number of landslide attributes, including area, length, compactness, slope, aspect, distance to stream and geology. The distributions of these attributes were analyzed to obtain a better understanding of landslide properties in the study area as a preliminary step for probabilistic landslide hazard assessment. The obtained spatial and temporal attribute variations were linked to differences in the environmental characteristics within the study area, in which the geological setting proved to be the most important differentiating factor. Moreover, a significant influence of the different data sources on the distribution of the landslide attribute values was found, indicating the importance of a critical evaluation of the landslide data to be used in landslide hazard assessments.

Suggested Citation

  • Darya Golovko & Sigrid Roessner & Robert Behling & Birgit Kleinschmit, 2017. "Automated derivation and spatio-temporal analysis of landslide properties in southern Kyrgyzstan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(3), pages 1461-1488, February.
    • Handle: RePEc:spr:nathaz:v:85:y:2017:i:3:d:10.1007_s11069-016-2636-y
    DOI: 10.1007/s11069-016-2636-y
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    References listed on IDEAS

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    1. Gabriel Legorreta Paulín & Solène Pouget & Marcus Bursik & Fernando Aceves Quesada & Trevor Contreras, 2016. "Comparing landslide susceptibility models in the Río El Estado watershed on the SW flank of Pico de Orizaba volcano, Mexico," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(1), pages 127-139, January.
    2. Sigrid Roessner & Hans-Ulrich Wetzel & Hermann Kaufmann & Aman Sarnagoev, 2005. "Potential of Satellite Remote Sensing and GIS for Landslide Hazard Assessment in Southern Kyrgyzstan (Central Asia)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 35(3), pages 395-416, July.
    3. Cheng Su & Lili Wang & Xizhi Wang & Zhicai Huang & Xiaocan Zhang, 2015. "Mapping of rainfall-induced landslide susceptibility in Wencheng, China, using support vector machine," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 76(3), pages 1759-1779, April.
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