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Health condition assessment for vegetation exposed to heavy metal pollution through airborne hyperspectral data

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Abstract

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.

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Acknowledgements

We thank Dr. Ali Shamsoddini and Shiyan Yu for their precedent survey of soil sampling and collection of ground vegetation spectra at Yerrranderie.

Funding

This independent research was funded by the Australian Centre for Sustainable Mining Practices (ACSMP), School of Mining Engineering, UNSW, Australia, as a Ph.D. scholarship for the first author. UNSW is also thanked for providing Taste of Research (TOR) scholarship for the third author.

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Authors and Affiliations

  1. Australian Centre for Sustainable Mining Practices, School of Mining Engineering, University of New South Wales, Sydney, NSW, 2052, Australia

    Bikram Pratap Banerjee & Simit Raval

  2. School of Mining Engineering, University of New South Wales, Sydney, NSW, 2052, Australia

    Bikram Pratap Banerjee, Simit Raval & Hao Zhai

  3. School of Chemical Engineering, University of New South Wales, Sydney, NSW, 2052, Australia

    Patrick Joseph Cullen

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  1. Bikram Pratap Banerjee
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  2. Simit Raval
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  3. Hao Zhai
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  4. Patrick Joseph Cullen
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Correspondence to Simit Raval.

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Banerjee, B.P., Raval, S., Zhai, H. et al. Health condition assessment for vegetation exposed to heavy metal pollution through airborne hyperspectral data. Environ Monit Assess 189, 604 (2017). https://doi.org/10.1007/s10661-017-6333-4

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  • DOI: https://doi.org/10.1007/s10661-017-6333-4

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