Abstract
The Loess Plateau is a region in China prone to frequent geological disasters, where thousands of loess landslides can be found. Conventional field survey methods are inadequate for the requirements of fine spatial analysis of landslides. Due to its numerous advantages (fast, efficient, low cost, safe, and able to acquire high-resolution data), structure from motion (SfM) technique to photogrammetric orientation of flights and modeling applied to photographs taken by unmanned aerial vehicles (UAVs) equipped with a camera has become a powerful new tool for the generation of high-resolution topography that has emerged in recent years, which has become a powerful new technique for acquiring high-resolution topographic data. In this study, we conducted nearly two months of field UAV surveys of loess landslides on the Loess Plateau, eventually established 3D digital models for 11 loess landslides, and produced high-resolution digital orthophoto maps (DOMs) and digital elevation models (DEMs). High-resolution spatial analysis of the loess landslides (mainly including characteristic parameter extraction, topography profile analysis, surface feature analysis, and hydrologic analysis) was performed using Agisoft PhotoScan, ArcGIS 10.2, Global Mapper 17, and Origin Pro 9.0. The UAV technique allows us to further understand the micro-level internal spatial and structural characteristics of loess landslides. Moreover, not only does it allow us to accurately measure the characteristic geometric parameters but also enables us to detect the surface details of loess landslides (e.g., textures, fissures, and micro-landforms). Manifestly, we can also deduce the original structural characteristics and possible inducement mechanism of landslides based on a combination of high-resolution data acquired by UAVs, proper ground surveys, and theoretical knowledge. In summary, the low-cost UAVs are highly and especially suitable for surveys and digital terrain analysis of landslides on the Loess Plateau with sparse vegetation.
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Funding
This research was funded by the National Natural Science Foundation of China (Grant No. 41771539), International Partnership Program of Chinese Academy of Sciences (Grant No. 131551KYSB20160002), and the China Postdoctoral Science Foundation (Grant No. 2016M602743).
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Hu, S., Qiu, H., Wang, X. et al. Acquiring high-resolution topography and performing spatial analysis of loess landslides by using low-cost UAVs. Landslides 15, 593–612 (2018). https://doi.org/10.1007/s10346-017-0922-8
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DOI: https://doi.org/10.1007/s10346-017-0922-8