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Multi-Scale Analysis of Surface Building Density and Land Subsidence Using a Combination of Wavelet Transform and Spatial Autocorrelation in the Plains of Beijing

Author

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  • Shuai Jiao

    (College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
    Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
    CAUPD Beijing Planning & Design Consultants Ltd., Beijing 100037, China)

  • Xiaojuan Li

    (College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
    Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China)

  • Jie Yu

    (College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
    Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China)

  • Mingyuan Lyu

    (College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
    Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China)

  • Ke Zhang

    (College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
    Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China)

  • Yuehui Li

    (CAUPD Beijing Planning & Design Consultants Ltd., Beijing 100037, China)

  • Pengyuan Shi

    (CAUPD Beijing Planning & Design Consultants Ltd., Beijing 100037, China)

Abstract

Land subsidence is a major issue in the Beijing Plain in China, caused by the construction of new buildings and infrastructure combined with groundwater extraction. This study employs a multi-level two-dimensional wavelet decomposition to decompose land subsidence into high- and low-frequency components, and Moran’s I index to analyze the spatial distribution of land subsidence and its main influencing factors. By comparing the spatial distributions of the high- and low-frequency components, we estimate the correlation between land subsidence and influencing factors at different scales. Utilizing a combination of wavelet decomposition and Moran’s I analysis, our study establishes a clear spatial correlation between continuously varying factors such as groundwater and clay layer thickness, and the low-frequency components of land subsidence, allowing for a focused analysis of the relationship between surface building density and the high-frequency components of land subsidence. Quantitatively, the study identifies a significant correlation at specific granularities, particularly at 480 m and 960 m, underscoring the nuanced interaction between urban development and land subsidence patterns. These insights into the spatial distribution of land subsidence and its contributing factors can inform the development of effective strategies to address this issue.

Suggested Citation

  • Shuai Jiao & Xiaojuan Li & Jie Yu & Mingyuan Lyu & Ke Zhang & Yuehui Li & Pengyuan Shi, 2024. "Multi-Scale Analysis of Surface Building Density and Land Subsidence Using a Combination of Wavelet Transform and Spatial Autocorrelation in the Plains of Beijing," Sustainability, MDPI, vol. 16(7), pages 1-23, March.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:2801-:d:1365274
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    References listed on IDEAS

    as
    1. Ye-Shuang Xu & Lei Ma & Yan-Jun Du & Shui-Long Shen, 2012. "Analysis of urbanisation-induced land subsidence in Shanghai," 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. 63(2), pages 1255-1267, September.
    2. Guojian Zhang & Zhiyang Wang & Guangli Guo & Wei Wei & Fugang Wang & Leilei Zhong & Yaqiang Gong, 2022. "Study on Regional Strata Movement during Deep Mining of Erdos Coal Field and Its Control," IJERPH, MDPI, vol. 19(22), pages 1-32, November.
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