Banerjee Bikram Pratap, Raval Simit, Zhai Hao, Cullen Patrick Joseph
Australian Centre for Sustainable Mining Practices, School of Mining Engineering, University of New South Wales, Sydney, NSW, 2052, Australia.
School of Mining Engineering, University of New South Wales, Sydney, NSW, 2052, Australia.
Environ Monit Assess. 2017 Nov 3;189(12):604. doi: 10.1007/s10661-017-6333-4.
Recent advancements in hyperspectral remote sensing technology now provide improved diagnostic capabilities to assess vegetation health conditions. This paper uses a set of 13 vegetation health indices related to chlorophyll, xanthophyll, blue/green/red ratio and structure from airborne hyperspectral reflectance data collected around a derelict mining area in Yerranderie, New South Wales, Australia. The studied area has ten historic mine shafts with a legacy of heavy metals and acidic contamination in a pristine ecosystem now recognised as Great Blue Mountain World Heritage Area. The forest is predominantly comprised of different species of Eucalyptus trees. In addition to the airborne survey, ground-based spectra of the tree leaves were collected along the two accessible heavy metal contaminated pathways. The stream networks in the area were classified and the geospatial patterns of vegetation health were analysed along the Tonalli River, a major water tributary flowing through the National Park. Despite the inflow of contaminated water from the near-mine streams, the measured vegetation health indices along Tonalli River were found to remain unchanged. The responses of the vegetation health indices between the near-mine and away-mine streams were found similar. Based on the along-stream and inter-stream analysis of the spectral indices of vegetation health, no significant impact of the heavy metal pollution could be noticed. The results indicate the possibility of the vegetation having developed immunity towards the high levels of heavy metal pollution over a century of exposure.
高光谱遥感技术的最新进展现在提供了改进的诊断能力,以评估植被健康状况。本文使用了一组与叶绿素、叶黄素、蓝/绿/红比率以及结构相关的13种植被健康指数,这些指数来自于在澳大利亚新南威尔士州耶兰德里一个废弃矿区周围收集的机载高光谱反射数据。研究区域有10个历史悠久的矿井,在一个现在被认定为大蓝山世界遗产区的原始生态系统中遗留有重金属和酸性污染。这片森林主要由不同种类的桉树组成。除了机载调查外,还沿着两条可通行的重金属污染路径收集了树叶的地面光谱。对该地区的河流网络进行了分类,并沿着流经国家公园的主要支流托纳利河分析了植被健康的地理空间模式。尽管有来自矿井附近溪流的受污染水流入,但发现沿着托纳利河测量的植被健康指数保持不变。发现矿井附近溪流和远离矿井溪流之间的植被健康指数反应相似。基于对植被健康光谱指数的沿溪流和溪流间分析,未发现重金属污染有显著影响。结果表明,经过一个世纪的暴露,植被有可能已经对高水平的重金属污染产生了免疫力。