Application of a fuzzy operator to susceptibility estimations of coal mine subsidence in Taebaek City, Korea

Jong Kuk Choi, Ki Dong Kim, Saro Lee, Joong Sun Won

Research output: Contribution to journalArticle

56 Citations (Scopus)

Abstract

Quantitative determination of locations vulnerable to ground subsidence at mining regions is necessary for effective prevention. In this paper, a method of constructing subsidence susceptibility maps based on fuzzy relations is proposed and tested at an abandoned underground coal mine in Korea. An advantage of fuzzy combination operators over other methods is that the operation is mathematically and logically easy to understand and its implementation to GIS software is simple and straightforward. A certainty factor analysis was used for estimating the relative weight of eight major factors influencing ground subsidence. The relative weight of each factor was then converted into a fuzzy membership value and integrated as a subsidence hazard index using fuzzy combination operators, which produced coal mine subsidence susceptibility maps. The susceptibility maps were compared with the reported ground subsidence areas, and the results showed high accuracy between our prediction and the actual subsidence. Based on the root mean square error and accuracy in terms of success rates, fuzzy γ-operator with a low γ value and fuzzy algebraic product operator, specifically, are useful for ground subsidence prediction. Comparing the results of a fuzzy γ-operator and a conventional logistic regression model, the performance of the fuzzy approach is comparative to that of a logistic regression model with improved computational. A field survey done in the area supported the method's reliability. A combination of certainty factor analysis and fuzzy relations with a GIS is an effective method to determine locations vulnerable to coal mine subsidence.

Original languageEnglish
Pages (from-to)1009-1022
Number of pages14
JournalEnvironmental Earth Sciences
Volume59
Issue number5
DOIs
Publication statusPublished - 2010 Jan

All Science Journal Classification (ASJC) codes

  • Global and Planetary Change
  • Environmental Chemistry
  • Water Science and Technology
  • Soil Science
  • Pollution
  • Geology
  • Earth-Surface Processes

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