Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1237-1239, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1237-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1237-1239, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1237-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

REMOTE SENSING EXTRACTION OF STOPES AND TAILINGS PONDS IN AN ULTRA-LOW-GRADE IRON MINING AREA

B. Ma1, Y. Chen1, X. Li1, and L. Wu2 B. Ma et al.
  • 1Institute for Geoinformatics & Digital Mine Research, Northeastern University, Shenyang 110819, P. R. China
  • 2School of Geoscience and Info-Physics, Central South University, Changsha, 410083, P.R. China

Keywords: Ultra-low-grade iron, mining area, remote sensing, spectral and thermal characteristics, stope and tailings pond

Abstract. With the development of economy, global demand for steel has accelerated since 2000, and thus mining activities of iron ore have become intensive accordingly. An ultra-low-grade iron has been extracted by open-pit mining and processed massively since 2001 in Kuancheng County, Hebei Province. There are large-scale stopes and tailings ponds in this area. It is important to extract their spatial distribution information for environmental protection and disaster prevention. A remote sensing method of extracting stopes and tailings ponds is studied based on spectral characteristics by use of Landsat 8 OLI imagery and ground spectral data. The overall accuracy of extraction is 95.06 %. In addition, tailings ponds are distinguished from stopes based on thermal characteristics by use of temperature image. The results could provide decision support for environmental protection, disaster prevention, and ecological restoration in the ultra-low-grade iron ore mining area.