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

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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.

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Acknowledgements

The research presented in this paper has been funded by the German Ministry of Research and Technology (BMBF) as part of the Tian Shan-Pamir Monitoring Program (TIPTIMON) and PROGRESS Projects. We kindly thank our colleagues from the Ministry of Emergency Situations of Kyrgyzstan and the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek and Hans-Ulrich Wetzel for providing the geological map.

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Authors and Affiliations

  1. GFZ German Research Centre for Geosciences, Section 1.4 – Remote Sensing, Telegrafenberg, 14473, Potsdam, Germany

    Darya Golovko, Sigrid Roessner & Robert Behling

  2. Institute for Landscape Architecture and Environmental Planning, Technical University Berlin, Straße des 17. Juni 145, 10623, Berlin, Germany

    Birgit Kleinschmit

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  1. Darya Golovko
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  2. Sigrid Roessner
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  3. Robert Behling
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  4. Birgit Kleinschmit
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Correspondence to Darya Golovko.

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Golovko, D., Roessner, S., Behling, R. et al. Automated derivation and spatio-temporal analysis of landslide properties in southern Kyrgyzstan. Nat Hazards 85, 1461–1488 (2017). https://doi.org/10.1007/s11069-016-2636-y

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