Mine tailing extraction indexes and model using remote-sensing images in southeast Hubei Province

Abstract

Southeast Hubei province is an important iron–copper production base in China, which has produced a large number of mine tailings from mining activities. Although they contain a certain amount of iron or copper as secondary mineral resources, the mine tailings and related acid wastewater can lead to environmental pollution through sand blowing or seepage. For effective resource utilization and environmentally conscious development, rapid evaluations of the spatial distribution, type, and age of mine tailings are of national importance. Using spectral features, which are determined by the structure and composition of tailings, we develop an all-band tailing index, a modified normalized difference tailing index (MNTI), and a normalized difference tailings index for Fe-bearing minerals (NDTIFe). The all-band tailings index reflect the micro-structure and overall high reflectivity of mine tailings by comprehensively utilizing information from each band of Landsat 8 data. The MNTI and NDTIFe provide enhanced tailings composition information from the perspective of anion (carbanion and hydroxy) and cation (mainly ferric ion) contents, respectively. A tailing extraction model (TEM) is built using these three indexes to extract mine tailing information in Huangshi city. The TEM proposed in this paper can successfully and rapidly extract mine tailings information with an extraction precision of 84% in the research area.