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Valentine Piroton
Department of Geology, University of Liège, 4000 Liège, Belgium

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Journal article
Published: 01 May 2020 in Geosciences
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Central Asian mountain regions are prone to multiple types of natural hazards, often causing damage due to the impact of mass movements. In spring 2017, Kyrgyzstan suffered significant losses from a massive landslide activation event, during which also two of the largest deep-seated mass movements of the former mining area of Mailuu-Suu—the Koytash and Tektonik landslides—were reactivated. This study consists of the use of optical and radar satellite data to highlight deformation zones and identify displacements prior to the collapse of Koytash and to the more superficial deformation on Tektonik. Especially for the first one, the comparison of Digital Elevation Models of 2011 and 2017 (respectively, satellite and unmanned aerial vehicle (UAV) imagery-based) highlights areas of depletion and accumulation, in the scarp and near the toe, respectively. The Differential Synthetic Aperture Radar Interferometry analysis identified slow displacements during the months preceding the reactivation in April 2017, indicating the long-term sliding activity of Koytash and Tektonik. This was confirmed by the computation of deformation time series, showing a positive velocity anomaly on the upper part of both landslides. Furthermore, the analysis of the Normalized Difference Vegetation Index revealed land cover changes associated with the sliding process between June 2016 and October 2017. In addition, in situ data from a local meteorological station highlighted the important contribution of precipitation as a trigger of the collapse. The multidirectional approach used in this study demonstrated the efficiency of applying multiple remote sensing techniques, combined with a meteorological analysis, to identify triggering factors and monitor the activity of landslides.

ACS Style

Valentine Piroton; Romy Schlögel; Christian Barbier; Hans-Balder Havenith. Monitoring the Recent Activity of Landslides in the Mailuu-Suu Valley (Kyrgyzstan) Using Radar and Optical Remote Sensing Techniques. Geosciences 2020, 10, 164 .

AMA Style

Valentine Piroton, Romy Schlögel, Christian Barbier, Hans-Balder Havenith. Monitoring the Recent Activity of Landslides in the Mailuu-Suu Valley (Kyrgyzstan) Using Radar and Optical Remote Sensing Techniques. Geosciences. 2020; 10 (5):164.

Chicago/Turabian Style

Valentine Piroton; Romy Schlögel; Christian Barbier; Hans-Balder Havenith. 2020. "Monitoring the Recent Activity of Landslides in the Mailuu-Suu Valley (Kyrgyzstan) Using Radar and Optical Remote Sensing Techniques." Geosciences 10, no. 5: 164.

Preprint content
Published: 10 March 2020
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Landslides are recurrent in most mountainous areas of the world where they frequently have catastrophic consequences. Around the Fergana Basin and in the Maily-Say Valley (Kyrgyzstan), landslides are often reactivated due to intense rainfalls, especially during spring, and as a consequence of the high seismicity characterizing the region. In spring 2017, Kyrgyzstan suffered a massive activation event which caused 160 emergency situations, including the reactivation of Koytash, one of the largest deep-seated mass movements of the Maily-Say area. In this region, risks related to landslides are accentuated by the presence of uranium tailings, remnants of the former nuclear mining activity. In this study, we used multiple satellite remote sensing techniques to highlight deformation zones and identify displacements prior to the collapse of Koytash. The comparison of multi-temporal digital elevation models (DEMs; satellite and UAV-based) enabled us to highlight areas of depletion and accumulation, in the scarp and foothill zones respectively. A differential synthetic aperture radar interferometry (D-InSAR) analysis and the computation of deformation time series allowed us to identify slope displacements and estimate the evolution of the displacement rates over time. This analysis identified slow displacements during the months preceding the reactivation, indicating the long-term sliding activity of Koytash, well before the reactivation in April 2017. This was confirmed by the computation of deformation time series, showing a positive velocity anomaly on the upper part of Koytash. Furthermore, the use of optical imagery, through the difference of NDVIs (Normalized Difference Vegetation Index), revealed landcover changes associated to the sliding process. In addition to remote sensing techniques, we performed a meteorological analysis to identify the conditions that triggered the massive failure of Koytash. In-situ data from a local station highlighted the important contribution of precipitations as a trigger of the landslide movement. Indeed, despite a relative decrease in annual rainfall in 2017 compared to the previous years, the month of April 2017 was characterised by heavy rains, including a major peak of rainfall the day of Koytash’s failure. The multidirectional approach used in this study, demonstrated the efficiency of using multiple remote sensing techniques, combined to a meteorological analysis, to identify triggering factors and monitor the activity of landslides.

ACS Style

Valentine Piroton; Romy Schlögel; Hans-Balder Havenith. Monitoring recent activity of the Koytash Landslide (Kyrgyzstan) using radar and optical remote sensing techniques. 2020, 1 .

AMA Style

Valentine Piroton, Romy Schlögel, Hans-Balder Havenith. Monitoring recent activity of the Koytash Landslide (Kyrgyzstan) using radar and optical remote sensing techniques. . 2020; ():1.

Chicago/Turabian Style

Valentine Piroton; Romy Schlögel; Hans-Balder Havenith. 2020. "Monitoring recent activity of the Koytash Landslide (Kyrgyzstan) using radar and optical remote sensing techniques." , no. : 1.