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

Lina Hao,Xiaoxia Yang,Zhi Zhang

doi:10.1007/s12665-019-8439-1

Lina Hao, Xiaoxia Yang + Show 1 more

Open Access

https://doi.org/10.1007/s12665-019-8439-1

Copy DOI

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.

Highlights

In recent years, lasting environmental problems caused by the exploitation of mineral resources, such as abandoned open mining pits, dumps, and tailing pools, are attracting increasing scientific concern
The tailing extraction model (TEM) proposed in this paper can successfully and rapidly extract mine tailings information with an extraction precision of 84% in the research area
Research shows that the spectral features of secondary iron oxide lie between the visible and near-infrared band (0.43–1.3 μm) and exhibit strong reflection in the red band and strong absorption in the near-infrared, blue, and green bands (Sklute et al 2018; Wang et al 2011)

Summary

Introduction

In recent years, lasting environmental problems caused by the exploitation of mineral resources, such as abandoned open mining pits, dumps, and tailing pools, are attracting increasing scientific concern. Mining-related environmental problems are clearly illustrated by surface landscape destruction, land form changes, ecological degradation, heavy metal pollution of soils, and water body pollution (Chevrel et al 2002). Secondary Fe-bearing mineral oxides and acidic mine drainage water left behind by mining activities have resulted in vegetation, soil, and water pollution. Research shows that the spectral features of secondary iron oxide lie between the visible and near-infrared band (0.43–1.3 μm) and exhibit strong reflection in the red band and strong absorption in the near-infrared, blue, and green bands (Sklute et al 2018; Wang et al 2011). The spectral features of the secondary pollutants of carbonate and hydroxyl minerals lie in shortwave-infrared wavelengths (1.9–2.4 μm) and exhibit weak absorption near 2.3 μm.

Objectives

Methods

Findings

Discussion

Conclusion