Remote-sensing–based coal-fire detection with low-resolution MODIS data

C.A. Hecker, Claudia Kuenzer, Jianzhong Zhang

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

17 Citations (Scopus)
127 Downloads (Pure)

Abstract

Remote-sensing imagery is often used for detecting and monitoring coal fires. The Landsat7 Enhanced thematic Mapper Plus (ETM+) sensor and its predecessors of the Landsat family were frequently utilized for that purpose. With Landsat5 quickly approaching the end of its lifetime and the partial malfunction of Landsat7 in 2003, other potential sensors, including Moderate Resolution Imaging Spectrora-diometer (MODIS), merit investigation. One kilometer MODIS data were successfully acquired and analyzed to detect coal fires in China during one summer and two winter night scenes. Band ratios of MODIS bands 20/32 enhanced subpixel-sized hot spots over background values, and an automated thermal anomaly algorithm was an asset in extracting potential coal-fire locations. for areas with known subsurface fires, between 0% and 17% were correctly detected in the three images. Areas with surface fires had success rates of 42% to 49%. These results indicate that MODIS is potentially useful for monitoring large areas for newly developing surface coal fires. Most subsurface coal fires, however, remain undetected.
Original languageEnglish
Title of host publicationGeology of coal fires
Subtitle of host publicationcase studies from around the world
EditorsG.B. Stracher
Place of PublicationBoulder, USA
PublisherGeological Society of America
Pages229-238
ISBN (Print)978-0-8137-4118-5, 978-0-8137-5818-3
DOIs
Publication statusPublished - 2007

Publication series

NameGeological Society of America Reviews in Engineering Geology
PublisherGeological Society of America
Volume18

Keywords

  • ESA
  • ADLIB-ART-249
  • 2023 OA procedure

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