Department of Geography, Environmental Management and Energy Studies, University of Johannesburg, South Africa.
Department of Geography, Environmental Management and Energy Studies, University of Johannesburg, South Africa.
Sci Total Environ. 2018 Mar 15;618:1560-1571. doi: 10.1016/j.scitotenv.2017.09.335. Epub 2017 Oct 21.
The effect of mining on water resources is severe and requires careful monitoring and management. Remote sensing has been used to characterize water quality indicators in efforts to fight mine-induced contamination. Much focus has however been placed on producing a qualitative classification of water qualities. Moreover, the number of variables considered in most studies is relatively small for a large number of hydrochemical constituents common in water bodies associated with gold mining activities. This study is aimed at quantifying a comprehensive list of field- and laboratory-measured chemical constituents of water samples from abandoned mines using remotely-sensed data. Akaike's Information Criterion was used to estimate each of the constituents using statistical values derived from individual bands of ASTER and Landsat data as predictors. Fairly good accuracies were obtained for constituents such as redox potential (Eh), major anions and cations. In contrast, trace elements correlated poorly with ASTER and Landsat bands, due mainly to a sampling anomaly. The performances of the two images in estimating the constituents were comparable. These findings suggest the potential of multispectral, moderate spatial resolution remote sensing for quantifying different hydrochemical properties of water bodies in mining environments. Further studies are however encouraged to enhance accuracies and reliability using a greater number of samples than was used in this study to capture the variability present in the population.
采矿对水资源的影响是严重的，需要仔细监测和管理。遥感技术已被用于描述水质指标，以努力应对矿山污染。然而，大多数研究主要集中在对水质进行定性分类上。此外，对于与金矿开采活动相关的水体中常见的大量水化学成分，大多数研究中考虑的变量数量相对较少。本研究旨在利用遥感数据定量描述废弃矿山水样中一系列实地和实验室测量的化学成分。利用 ASTER 和 Landsat 数据各波段衍生的统计值作为预测因子，通过赤池信息量准则（Akaike's Information Criterion）来估算各成分的含量。对于氧化还原电位（Eh）、主要阴离子和阳离子等成分，获得了相当好的精度。相比之下，由于采样异常，微量元素与 ASTER 和 Landsat 波段相关性较差。两幅图像在估算成分方面的性能相当。这些发现表明，多光谱、中等空间分辨率的遥感技术具有量化采矿环境中水体不同水化学性质的潜力。然而，需要进一步研究，以使用比本研究更多的样本来提高精度和可靠性，以捕捉总体中的变异性。
