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Landslide Distribution and Development Characteristics in the Beiluo River Basin

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  • Fan Liu

    (School of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
    Key Laboratory of Mine Geological Hazards Mechanism and Control, Ministry of Natural Resources, Xi’an 710054, China
    Shaanxi Hygrogeology Engineering Environment Geology Survey Center, Xi’an 710068, China)

  • Yahong Deng

    (School of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
    Key Laboratory of Mine Geological Hazards Mechanism and Control, Ministry of Natural Resources, Xi’an 710054, China)

  • Tianyu Zhang

    (Shaanxi Institute of Geological Survey, Xi’an 710068, China)

  • Faqiao Qian

    (School of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
    Key Laboratory of Mine Geological Hazards Mechanism and Control, Ministry of Natural Resources, Xi’an 710054, China)

  • Nan Yang

    (School of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
    Key Laboratory of Mine Geological Hazards Mechanism and Control, Ministry of Natural Resources, Xi’an 710054, China)

  • Hongquan Teng

    (Shaanxi Hygrogeology Engineering Environment Geology Survey Center, Xi’an 710068, China)

  • Wei Shi

    (Shaanxi Hygrogeology Engineering Environment Geology Survey Center, Xi’an 710068, China)

  • Xue Han

    (Shaanxi Hygrogeology Engineering Environment Geology Survey Center, Xi’an 710068, China)

Abstract

The Beiluo River Basin, situated in the central region of the Loess Plateau, frequently experiences landslide geological disasters, posing a severe threat to local lives and property. Thus, establishing a detailed database of historical landslides and analyzing and revealing their development characteristics are of paramount importance for providing a foundation for geological hazard risk assessment. First, in this study, landslides in the Beiluo River Basin are interpreted using Google Earth and ZY-3 high-resolution satellite imagery. Combined with a historical landslide inventory and field investigations, a landslide database for the Beiluo River Basin is compiled, containing a total of 1781 landslides. Based on this, the geometric and spatial characteristics of the landslides are analyzed, and the relationships between the different types of landslides and landslide scale, stream order, and geomorphological types are further explored. The results show that 50.05% of the landslides have a slope aspect between 225° and 360°, 68.78% have a slope gradient of 16–25°, and 38.97% are primarily linear in profile morphology. Areas with a high landslide density within a 10 km radius are mainly concentrated in the loess ridge and hillock landform region between Wuqi and Zhidan Counties and in the loess tableland region between Fu and Luochuan Counties, with a significant clustering effect observed in the Fu County area. Loess–bedrock interface landslides are relatively numerous in the northern loess ridge and hillock landform region due to riverbed incision and the smaller thickness of loess in this area. Intra-loess landslides are primarily found in the southern loess tableland region due to headward erosion and the greater thickness of loess in this area. Loess–clay interface landslides, influenced by riverbed incision and the limited exposure of red clay, are mainly distributed in the northern part of the southern loess tableland region and on both sides of the Beiluo River Valley in Ganquan County. These results will aid in further understanding the development and spatial distribution of landslides in the Beiluo River Basin and provide crucial support for subsequent landslide susceptibility mapping and geological hazard assessment in the region.

Suggested Citation

  • Fan Liu & Yahong Deng & Tianyu Zhang & Faqiao Qian & Nan Yang & Hongquan Teng & Wei Shi & Xue Han, 2024. "Landslide Distribution and Development Characteristics in the Beiluo River Basin," Land, MDPI, vol. 13(7), pages 1-28, July.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:7:p:1038-:d:1432706
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    References listed on IDEAS

    as
    1. Zemin Gao & Mingtao Ding, 2022. "Application of convolutional neural network fused with machine learning modeling framework for geospatial comparative analysis of landslide susceptibility," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(2), pages 833-858, September.
    2. Qingkai Meng & Qiang Xu & Baocun Wang & Weile Li & Ying Peng & Dalei Peng & Xing Qi & Dongdong Zhou, 2019. "Monitoring the regional deformation of loess landslides on the Heifangtai terrace using the Sentinel-1 time series interferometry technique," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(2), pages 485-505, September.
    3. Siyuan Ma & Chong Xu, 2019. "Assessment of co-seismic landslide hazard using the Newmark model and statistical analyses: a case study of the 2013 Lushan, China, Mw6.6 earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 96(1), pages 389-412, March.
    4. Fabio Luino & Mariano Barriendos & Fabrizio Terenzio Gizzi & Ruediger Glaser & Christoph Gruetzner & Walter Palmieri & Sabina Porfido & Heather Sangster & Laura Turconi, 2023. "Historical Data for Natural Hazard Risk Mitigation and Land Use Planning," Land, MDPI, vol. 12(9), pages 1-21, September.
    5. Arthur Getis & J. Keith Ord, 2010. "The Analysis of Spatial Association by Use of Distance Statistics," Advances in Spatial Science, in: Luc Anselin & Sergio J. Rey (ed.), Perspectives on Spatial Data Analysis, chapter 0, pages 127-145, Springer.
    6. Y. Tang & Q. Xue & Z. Li & W. Feng, 2015. "Three modes of rainfall infiltration inducing loess landslide," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(1), pages 137-150, October.
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