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Application of GIS spatial regression methods in assessment of land subsidence in complicated mining conditions: case study of the Walbrzych coal mine (SW Poland)

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  • Jan Blachowski

    (Wroclaw University of Science and Technology)

Abstract

Land subsidence in the area of the city of Walbrzych (SW Poland) has been a consequence of underground mining of hard coal. Exploitation of multiseam deposit took place for several 100 years and ended in the late 90’ties of the twentieth century. During this time, many buildings and constructions were affected by subsidence-related damages and new landforms including mining waste dumps have developed on the surface in a consequence of underground extraction of coal. Previous studies indicated that cumulative subsidence calculated with the empirical Knothe theory reached −22 m, whereas calculations based on results of cartographic data processing showed more than −30 m (± 3 m) pointing to insufficient reliability of traditional methods when applied in complex and complicated conditions (multiseam and steeply inclined deposits). Present-day height of manmade landforms in areas affected by subsidence reaches 63 m (± 3 m). Therefore, in the presented research, a weighted spatial regression method has been proposed for analysis and modelling of mining induced land subsidence. The study concerned the former Walbrzych coal mine area and the 1886–2009 period. The subsidence modelling has been done in geographic information systems with geographically weighted regression (GWR) method that allows for spatial variability of subsidence factors. Four, out of the analysed seven, subsidence factors were identified as significant (thickness, inclination and depth of coal levels and surface slope) and used as independent (explanatory) variables in construction of the subsidence model with the GWR method. The validated model was used to estimate subsidence in up to now unmapped areas transformed by manmade landforms. The maximum predicted subsidence in these parts for the 1886–2009 period reaches −10.5 m. In the result, a spatial representation (hybrid map) of subsidence for the entire Walbrzych coal mine has been produced.

Suggested Citation

  • Jan Blachowski, 2016. "Application of GIS spatial regression methods in assessment of land subsidence in complicated mining conditions: case study of the Walbrzych coal mine (SW Poland)," 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. 84(2), pages 997-1014, November.
    • Handle: RePEc:spr:nathaz:v:84:y:2016:i:2:d:10.1007_s11069-016-2470-2
    DOI: 10.1007/s11069-016-2470-2
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    References listed on IDEAS

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    1. Agnieszka Malinowska, 2014. "Classification and regression tree theory application for assessment of building damage caused by surface deformation," 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. 73(2), pages 317-334, September.
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    2. Zhiheng Yang & Chenxi Li & Yongheng Fang, 2020. "Driving Factors of the Industrial Land Transfer Price Based on a Geographically Weighted Regression Model: Evidence from a Rural Land System Reform Pilot in China," Land, MDPI, vol. 9(1), pages 1-21, January.
    3. Hamed Noori & Hojat Karami & Saeed Farzin & Seyed Mostafa Siadatmousavi & Barat Mojaradi & Ozgur Kisi, 2018. "Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion," 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. 91(1), pages 221-238, March.
    4. Chenxi Li & Kening Wu, 2017. "Driving forces of the villages hollowing based on geographically weighted regression model: a case study of Longde County, the Ningxia Hui Autonomous Region, China," 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. 89(3), pages 1059-1079, December.

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