We present a new inventory of large rock slope instabilities and an extensive structural data set for northwestern Bhutan. Our data set is largely based on satellite observations, such as optical images and high-resolution digital surface models, complemented with field observations. Kinematic analyses over seven different structural domains recognized in the study region were carried out to investigate structural control over the landslide distribution at a regional scale. In order to account for the sampling heterogeneity in the different data sets, a weighting system to the structural data is proposed. The results show that structural control exists in five out of seven domains, with foliation strongly influencing the sliding mechanisms. A lithological control appears also evident, with sedimentary rocks showing the highest landslide densities in the region. This study demonstrates how methodologies built on remote sensing data are suitable to investigate landslide predisposition at regional scales especially in largely inaccessible areas.
Dini, B., Aaron, J., Manconi, A., De Palezieux, L., Leith, K., Loew, S. (2020). Regional-Scale Investigation of Preconditioning Factors of Rock Slope Instabilities in NW Bhutan. JOURNAL OF GEOPHYSICAL RESEARCH. EARTH SURFACE, 125(9) [10.1029/2019JF005404].
Regional-Scale Investigation of Preconditioning Factors of Rock Slope Instabilities in NW Bhutan
Dini, B;
2020
Abstract
We present a new inventory of large rock slope instabilities and an extensive structural data set for northwestern Bhutan. Our data set is largely based on satellite observations, such as optical images and high-resolution digital surface models, complemented with field observations. Kinematic analyses over seven different structural domains recognized in the study region were carried out to investigate structural control over the landslide distribution at a regional scale. In order to account for the sampling heterogeneity in the different data sets, a weighting system to the structural data is proposed. The results show that structural control exists in five out of seven domains, with foliation strongly influencing the sliding mechanisms. A lithological control appears also evident, with sedimentary rocks showing the highest landslide densities in the region. This study demonstrates how methodologies built on remote sensing data are suitable to investigate landslide predisposition at regional scales especially in largely inaccessible areas.| File | Dimensione | Formato | |
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