Zijing Liu , Haijun Qiu , Yaru Zhu , Wenchao Huangfu , Bingfeng Ye , Yingdong Wei , Bingzhe Tang , Ulrich Kamp
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引用次数: 0
Abstract
Population growth and agricultural intensification lead to stress on landscapes that are highly sensitive to land-use changes. An increase in irrigation-triggered landslides (ITL) in dry climates has negative impacts on local communities. However, evolution and global impacts of ITL are little-known. Here, we use Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR), vectorization, and differential method to study surface deformation, ground displacement, and changes in headscarp morphology and topography in regions prone to ITL, aiming to uncover the evolution and spatiotemporal distribution of ITL. Findings show that the most severe surface deformation of ITL occurs on the landslide body. Meanwhile, the ITL displacement curve indicates the ITL will maintain continuous movement for at least 7 years, while ancient ITL also poses a threat. Moreover, the headscarp of ITL shows lateral expansion and longitudinal retrogression on the horizontal ground, whereby the scale of expansion is greater than that of retrogression, which transforms landslides into landslide clusters. Finally, the topographic changes further reveal that the main development pattern of ITL is lateral expansion. We suggest that the frequency and disaster-causing ability of ITL will increase greatly with further population growth and related intensification in the agricultural sector.
期刊介绍:
The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.