IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i7p1038-d1432706.html
   My bibliography  Save this article

Landslide Distribution and Development Characteristics in the Beiluo River Basin

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/7/1038/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/13/7/1038/
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ning Zhang & Ying Mao, 2021. "Spatial Effects of Environmental Pollution on Healthcare Services: Evidence from China," IJERPH, MDPI, vol. 18(4), pages 1-21, February.
    2. Mehmet Ronael & Tüzin Baycan, 2022. "Place-based factors affecting COVID-19 incidences in Turkey," Asia-Pacific Journal of Regional Science, Springer, vol. 6(3), pages 1053-1086, October.
    3. Thomas M. Koutsos & Georgios C. Menexes & Andreas P. Mamolos, 2021. "The Use of Crop Yield Autocorrelation Data as a Sustainable Approach to Adjust Agronomic Inputs," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    4. Cláudia M. Viana & Dulce Freire & Patrícia Abrantes & Jorge Rocha, 2021. "Evolution of Agricultural Production in Portugal during 1850–2018: A Geographical and Historical Perspective," Land, MDPI, vol. 10(8), pages 1-18, July.
    5. Felipe Santos‐Marquez & Carlos Mendez, 2021. "Regional convergence, spatial scale, and spatial dependence: Evidence from homicides and personal injuries in Colombia 2010–2018," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(4), pages 1162-1184, August.
    6. Jianwei Qi & Yayan Lu & Fang Han & Xuankai Ma & Zhaoping Yang, 2022. "Spatial Distribution Characteristics of the Rural Tourism Villages in the Qinghai-Tibetan Plateau and Its Influencing Factors," IJERPH, MDPI, vol. 19(15), pages 1-21, July.
    7. Cuixia Yan & Lucang Wang & Qing Zhang, 2021. "Study on Coupled Relationship between Urban Air Quality and Land Use in Lanzhou, China," Sustainability, MDPI, vol. 13(14), pages 1-21, July.
    8. María-Jesús Perles & Juan F. Sortino & Matías F. Mérida, 2021. "The Neighborhood Contagion Focus as a Spatial Unit for Diagnosis and Epidemiological Action against COVID-19 Contagion in Urban Spaces: A Methodological Proposal for Its Detection and Delimitation," IJERPH, MDPI, vol. 18(6), pages 1-24, March.
    9. Xiang-Zhou Xu & Wen-Zhao Guo & Ya-Kun Liu & Jian-Zhong Ma & Wen-Long Wang & Hong-Wu Zhang & Hang Gao, 2017. "Landslides on the Loess Plateau of China: a latest statistics together with a close look," 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. 86(3), pages 1393-1403, April.
    10. Li, Xiaoliang & Wu, Kening & Yang, Qijun & Hao, Shiheng & Feng, Zhe & Ma, Jinliang, 2023. "Quantitative assessment of cultivated land use intensity in Heilongjiang Province, China, 2001–2015," Land Use Policy, Elsevier, vol. 125(C).
    11. Huxiao Zhu & Xiangjun Ou & Zhen Yang & Yiwen Yang & Hongxin Ren & Le Tang, 2022. "Spatiotemporal Dynamics and Driving Forces of Land Urbanization in the Yangtze River Delta Urban Agglomeration," Land, MDPI, vol. 11(8), pages 1-21, August.
    12. Jifei Zhang & Shuai Zhang, 2022. "Assessing Integrated Effectiveness of Rural Socio-Economic Development and Environmental Protection of Wenchuan County in Southwestern China: An Approach Using Game Theory and VIKOR," Land, MDPI, vol. 11(11), pages 1-17, October.
    13. Hamidreza Rabiei-Dastjerdi & Gavin McArdle, 2021. "Novel Exploratory Spatiotemporal Analysis to Identify Sociospatial Patterns at Small Areas Using Property Transaction Data in Dublin," Land, MDPI, vol. 10(6), pages 1-16, May.
    14. Rauner, Sebastian & Eichhorn, Marcus & Thrän, Daniela, 2016. "The spatial dimension of the power system: Investigating hot spots of Smart Renewable Power Provision," Applied Energy, Elsevier, vol. 184(C), pages 1038-1050.
    15. Muhammad Basharat & Muhammad Tayyib Riaz & M. Qasim Jan & Chong Xu & Saima Riaz, 2021. "A review of landslides related to the 2005 Kashmir Earthquake: implication and future challenges," 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. 108(1), pages 1-30, August.
    16. Michael Manton & Evaldas Makrickas & Piotr Banaszuk & Aleksander Kołos & Andrzej Kamocki & Mateusz Grygoruk & Marta Stachowicz & Leonas Jarašius & Nerijus Zableckis & Jūratė Sendžikaitė & Jan Peters &, 2021. "Assessment and Spatial Planning for Peatland Conservation and Restoration: Europe’s Trans-Border Neman River Basin as a Case Study," Land, MDPI, vol. 10(2), pages 1-27, February.
    17. Xiaofang Chen & Wenlei Xia & Yuan Huang & Mingze Li & Wei Wan, 2021. "Evolution of the Spatial Pattern of the Assets and Environmental Liabilities Conversion Rate and Its Influencing Factors," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    18. Guorui Gao & Futao Wang & Zhenqing Wang & Qing Zhao & Litao Wang & Jinfeng Zhu & Wenliang Liu & Gang Qin & Yanfang Hou, 2024. "Multi-Scale Earthquake Damaged Building Feature Set," Data, MDPI, vol. 9(7), pages 1-20, June.
    19. Jun Jia & Xiangjun Pei & Xiaopeng Guo & Shenghua Cui & Pingping Sun & Haoran Fan & Xiaochao Zhang & Qi Gu, 2024. "Laboratory Model Tests on the Deformation and Failure of Terraced Loess Slopes Induced by Extreme Rainfall," Land, MDPI, vol. 13(10), pages 1-22, October.
    20. Kahsar, Rudy, 2021. "The soft path revisited: Policies that drive decentralization of electric power generation in the contiguous U.S," Energy Policy, Elsevier, vol. 156(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:13:y:2024:i:7:p:1038-:d:1432706. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.