TY - JOUR
T1 - Vegetation Index Differencing for Estimating Foliar Dust in an Ultra-Low-Grade Magnetite Mining Area Using Landsat Imagery
AU - Ma, Baodong
AU - Pu, Ruiliang
AU - Wu, Lixin
AU - Zhang, Song
PY - 2017/5/1
Y1 - 2017/5/1
N2 - A supply of minerals is critical to socioeconomic development. However, such a supply also induces negative impacts on environment and ecology, e.g., leading to dust emission and deposition. An ultra-low-grade magnetite has been exploited as a new iron type since 2001 in China. In this paper, two Landsat images were used for monitoring foliar dust in Changhe River Mining Area, China. First, models were established to estimate foliar dust using vegetation indices (VIs) differences according to laboratory spectral measurements; normalized differenced VI was selected as an optimal VI for estimating foliar dust amount based on both field and laboratory spectral measurements (RMSE = 6.58 g/m2), and finally, the spatial patterns of foliar dust were analyzed by using ancillary high-resolution data. The result showed that most foliar dust distributed near ore transportation roads and around mining sites and tailings ponds, which was related to ultra-low-grade characteristics of the iron ore due to large-area extraction and tailings occupation, and large-amount dust emission released from ore transportation. The remote sensing method for estimating foliar dust may be beneficial for environmental management in mining areas.
AB - A supply of minerals is critical to socioeconomic development. However, such a supply also induces negative impacts on environment and ecology, e.g., leading to dust emission and deposition. An ultra-low-grade magnetite has been exploited as a new iron type since 2001 in China. In this paper, two Landsat images were used for monitoring foliar dust in Changhe River Mining Area, China. First, models were established to estimate foliar dust using vegetation indices (VIs) differences according to laboratory spectral measurements; normalized differenced VI was selected as an optimal VI for estimating foliar dust amount based on both field and laboratory spectral measurements (RMSE = 6.58 g/m2), and finally, the spatial patterns of foliar dust were analyzed by using ancillary high-resolution data. The result showed that most foliar dust distributed near ore transportation roads and around mining sites and tailings ponds, which was related to ultra-low-grade characteristics of the iron ore due to large-area extraction and tailings occupation, and large-amount dust emission released from ore transportation. The remote sensing method for estimating foliar dust may be beneficial for environmental management in mining areas.
UR - https://digitalcommons.usf.edu/geo_facpub/1355
UR - https://doi.org/10.1109/ACCESS.2017.2700474
U2 - 10.1109/ACCESS.2017.2700474
DO - 10.1109/ACCESS.2017.2700474
M3 - Article
VL - 5
JO - IEEE Access
JF - IEEE Access
ER -