Geomorphological evolution of landslides near an active normal fault in northern Taiwan, as revealed by lidar and unmanned aircraft system data
Several remote sensing techniques, namely traditional aerial photographs, an unmanned aircraft system (UAS), and airborne lidar, were used in this study to decipher the morphological features of obscure landslides in volcanic regions and how the observed features may be used for understanding la...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2018-03-01
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Series: | Natural Hazards and Earth System Sciences |
Online Access: | https://www.nat-hazards-earth-syst-sci.net/18/709/2018/nhess-18-709-2018.pdf |
Summary: | Several remote sensing techniques, namely traditional
aerial photographs, an unmanned aircraft system (UAS), and airborne lidar,
were used in this study to decipher the morphological features of obscure
landslides in volcanic regions and how the observed features may be used for
understanding landslide occurrence and potential hazard. A morphological
reconstruction method was proposed to assess landslide morphology based on
the dome-shaped topography of the volcanic edifice and the nature of its
morphological evolution. Two large-scale landslides in the Tatun volcano
group in northern Taiwan were targeted to more accurately characterize the
landslide morphology through airborne lidar and UAS-derived digital terrain
models and images. With the proposed reconstruction method, the depleted
volume of the two landslides was estimated to be at least
820 ± 20 × 10<sup>6</sup> m<sup>3</sup>. Normal faulting in the region
likely played a role in triggering the two landslides, because there are
extensive geological and historical records of an active normal fault in this
region. The subsequent geomorphological evolution of the two landslides is
thus inferred to account for the observed morphological and tectonic features
that are indicative of resulting in large and life-threatening landslides, as
characterized using the recent remote sensing techniques. |
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ISSN: | 1561-8633 1684-9981 |