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A Low-Cost Web Application System for Monitoring Geometrical Impacts of Surface Subsidence

Author

Listed:
  • Nixon N. Nduji

    (Centre for Environmental Management and Control (CEMAC), University of Nigeria (UNN), Enugu P.O. Box 410001, Nigeria)

  • Christian N. Madu

    (Centre for Environmental Management and Control (CEMAC), University of Nigeria (UNN), Enugu P.O. Box 410001, Nigeria
    Department of Management and Management Science, Lubin School of Business, Pace University, 1 Pace Plaza, New York, NY 10038, USA)

  • Chukwuebuka C. Okafor

    (Centre for Environmental Management and Control (CEMAC), University of Nigeria (UNN), Enugu P.O. Box 410001, Nigeria)

Abstract

This paper develops a low-cost web application system for monitoring geometrical impacts of surface subsidence. In many of the developing countries, the method of extraction of minerals such as coal is often impractical and uneconomical, especially with surface mining. With global warming, rapid population growth, and fast-growing urbanization with a disregard for sustainability, the overall subsidence risk has significantly increased. Despite the maturity of Differential Interferometric Synthetic Aperture Radar (DInSAR) for timely monitoring of subsidence hazards, the potential of SAR constellations has been under-exploited, as most applications focus mainly on mapping unstable areas. The developed web application system exploits Sentinel-1 SAR constellation and Small-BAseline Subset (SBAS-DInSAR) technique, to provide new streamlines of information for monitoring solutions and improve disaster risk decision making. We illustrate the model by investigating and measuring potential surface subsidence caused by underground hard coal mining activities and exponential urban population growth within a major coalmine in Nigeria. Results of the yearly cumulative amount of horizontal and vertical deformation between 2016 and 2020 range from −25.487 mm to −50.945 mm and −24.532 mm to −57.161 mm, for high and low risks, respectively. Under the influence of external factors such as rising poverty and fast-growing urbanization, the destruction of in situ stress distributions will likely increase nonlinear deformations.

Suggested Citation

  • Nixon N. Nduji & Christian N. Madu & Chukwuebuka C. Okafor, 2022. "A Low-Cost Web Application System for Monitoring Geometrical Impacts of Surface Subsidence," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14240-:d:959371
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    References listed on IDEAS

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    1. Karatzoglou, Alexandros & Feinerer, Ingo, 2010. "Kernel-based machine learning for fast text mining in R," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 290-297, February.
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    Cited by:

    1. Yanhui Guo & Luo Luo & Rui Ma & Shunyin Li & Wei Zhang & Chuangye Wang, 2023. "Study on Surface Deformation and Movement Caused by Deep Continuous Mining of Steeply Inclined Ore Bodies," Sustainability, MDPI, vol. 15(15), pages 1-23, August.

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