Integration of a subsidence model and sar interferometry for a coal mine subsidence hazard map in Taebaek, Korea

Jong Kuk Choi, Joong Sun Won, Saro Lee, Sang Wan Kim, Ki Dong Kim, Hyung Sup Jung

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Coal mine subsidence hazard can be effectively evaluated by geographic information system (GIS) analysis if sufficient data is provided. It is, however, difficult to obtain ground-based data, especially in remote and less populated mining areas. In this study, we construct and validate a coal mine subsidence hazard map in Taebaek, Korea, by integration of space-borne L-band synthetic aperture radar (SAR) measurements and a fuzzy-based subsidence model. There is an approximately 15-year time interval between the radar measurements used for the subsidence hazard model and those used to validate the subsidence. A subsidence hazard map was constructed using Japanese Earth Resources Satellite (JERS-1) SAR data from the early 1990s and the subsidence model. For the coal mine subsidence hazard mapping, a certainty factor analysis was used to estimate the relative weights of four control factors influencing coal mine subsidence, and the relative weight of each factor was then integrated to produce a subsidence hazard index by a fuzzy combination operator. The predicted hazard areas were then investigated and validated by comparison with subsidence occurrences observed by Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) interferometry in 2007-2008. The results showed a good agreement between the predicted locations vulnerable to subsidence and the actual subsidence occurrences with a prediction accuracy of about 73% and a root mean square error of about 0.35. These results demonstrate that a map produced by integration of a subsidence model and SAR interferometry can be used to predict and monitor coal mine subsidence hazards, especially in remote regions.

Original languageEnglish
Pages (from-to)8161-8181
Number of pages21
JournalInternational Journal of Remote Sensing
Volume32
Issue number23
DOIs
StatePublished - Dec 2011

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