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[1] Al-Kouri, O., Al-Fugara, A., Al-Rawashdeh, S., Sadoun, B. & Pradhan, B., Geospatialmodeling for sinkholes hazard map based on GIS&RS data. Journal of GeographicInformation System, 5, pp. 584–592, 2013.
[2] Klimchouk, A., Morphogenesis of hypogenic caves. Geomorphology, 106(1–2), pp.100–117, 2009.
[3] Seoul Metropolitan Government, Investigation of underground cavity mechanism, ResearchReport, 2015.
[4] Galve, J.P., Remondo, J. & Gutierrez, F., Improving sinkhole hazard models incorporatingmagnitude-frequency relationships and nearest neighbor analysis. Geomorphology,134, pp. 157–170, 2011.
[5] Galve, J.P., Gutierrez, F., Lucha, P., Bonachea, J., Remondo, J., Cendrero, A., Gutierrez,M., Gimeno, M.J., Pardo, G. & Sanchez, J.A., Sinkholes in the salt-bearing evaporatekarst of the Ebro River valley upstream of Zaragoza city (NE Spain) – Geomorphologicalmapping and analysis as a basis for risk management. Geomorphology, 108, pp.145–158, 2009.
[6] Myung, I.J., Tutorial on maximum likelihood estimation. Journal of Mathematical Psychology,47, pp. 90–100, 2003.
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Open Access
Research article

Risk Assessment of Railroad for the Presence of Underground Cavities Based on a Statistical Approach

j. oh1,
h. yoo1,
b. park2,
j. kim3,
j. oh4
1
Department of Railroad Facility Engineering, Korea National University of Transportation, Republic of Korea
2
Department of Railroad Management and Logistics, Korea National University of Transportation, Republic of Korea
3
Department of Geotechnical Engineering, Korea Railroad Technical Corporation, Republic of Korea
4
Department of Research and Development, Korea Rail Network Authority, Republic of Korea
International Journal of Transport Development and Integration
|
Volume 1, Issue 3, 2017
|
Pages 552-557
Received: N/A,
Revised: N/A,
Accepted: N/A,
Available online: N/A
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Abstract:

Collapses due to underground cavities have been drastically increasing in urban areas of South Korea. This article establishes a statistical model to assess the risk potential of railroads with respect to under-ground cavities. The authors first identified the risk factors of the event based on case studies where the collapses of underground cavities took place. The database was then established, taking into account the risk factors, to come up with a statistical model that estimates the risk level. In this study, the maximum likelihood estimation (MLE) method was employed to estimate the parameters in a statistical model. Thorough the statistical analysis, the probability of underground cavity occurrences was found to be expressed in terms of the depth of alluvial layer, groundwater level, water and sewage utilities, and their age. Consequently, an attempt was made to generate a preliminary hazard map for a specific railway route by employing the statistical model.

Keywords: database, maximum likelihood estimation, railroad statistical model, underground cavities
Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References
[1] Al-Kouri, O., Al-Fugara, A., Al-Rawashdeh, S., Sadoun, B. & Pradhan, B., Geospatialmodeling for sinkholes hazard map based on GIS&RS data. Journal of GeographicInformation System, 5, pp. 584–592, 2013.
[2] Klimchouk, A., Morphogenesis of hypogenic caves. Geomorphology, 106(1–2), pp.100–117, 2009.
[3] Seoul Metropolitan Government, Investigation of underground cavity mechanism, ResearchReport, 2015.
[4] Galve, J.P., Remondo, J. & Gutierrez, F., Improving sinkhole hazard models incorporatingmagnitude-frequency relationships and nearest neighbor analysis. Geomorphology,134, pp. 157–170, 2011.
[5] Galve, J.P., Gutierrez, F., Lucha, P., Bonachea, J., Remondo, J., Cendrero, A., Gutierrez,M., Gimeno, M.J., Pardo, G. & Sanchez, J.A., Sinkholes in the salt-bearing evaporatekarst of the Ebro River valley upstream of Zaragoza city (NE Spain) – Geomorphologicalmapping and analysis as a basis for risk management. Geomorphology, 108, pp.145–158, 2009.
[6] Myung, I.J., Tutorial on maximum likelihood estimation. Journal of Mathematical Psychology,47, pp. 90–100, 2003.
Cite this:
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GB-T-7714-2015
OH, J., YOO, H., PARK, B., KIM, J., & OH, J. (2017). Risk Assessment of Railroad for the Presence of Underground Cavities Based on a Statistical Approach. Int. J. Transp. Dev. Integr., 1(3), 552-557. https://doi.org/10.2495/TDI-V1-N3-552-557
J. OH, H. YOO, B. PARK, J. KIM, and J. OH, "Risk Assessment of Railroad for the Presence of Underground Cavities Based on a Statistical Approach," Int. J. Transp. Dev. Integr., vol. 1, no. 3, pp. 552-557, 2017. https://doi.org/10.2495/TDI-V1-N3-552-557
@research-article{Oh2017RiskAO,
title={Risk Assessment of Railroad for the Presence of Underground Cavities Based on a Statistical Approach},
author={J. Oh and H. Yoo and B. Park and J. Kim and J. Oh},
journal={International Journal of Transport Development and Integration},
year={2017},
page={552-557},
doi={https://doi.org/10.2495/TDI-V1-N3-552-557}
}
J. Oh, et al. "Risk Assessment of Railroad for the Presence of Underground Cavities Based on a Statistical Approach." International Journal of Transport Development and Integration, v 1, pp 552-557. doi: https://doi.org/10.2495/TDI-V1-N3-552-557
J. Oh, H. Yoo, B. Park, J. Kim and J. Oh. "Risk Assessment of Railroad for the Presence of Underground Cavities Based on a Statistical Approach." International Journal of Transport Development and Integration, 1, (2017): 552-557. doi: https://doi.org/10.2495/TDI-V1-N3-552-557
OH J， YOO H， PARK B， et al. Risk Assessment of Railroad for the Presence of Underground Cavities Based on a Statistical Approach[J]. International Journal of Transport Development and Integration， 2017， 1(3)： 552-557. https://doi.org/10.2495/TDI-V1-N3-552-557