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

Article

Banerjee, Bikram Pratap, Raval, Simit, Zhai, Hao and Cullen, Patrick Joseph. 2017. "Health condition assessment for vegetation exposed to heavy metal pollution through airborne hyperspectral data." Environmental Monitoring and Assessment. 189 (12). https://doi.org/10.1007/s10661-017-6333-4
Article Title

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

ERA Journal ID5880
Article CategoryArticle
AuthorsBanerjee, Bikram Pratap, Raval, Simit, Zhai, Hao and Cullen, Patrick Joseph
Journal TitleEnvironmental Monitoring and Assessment
Journal Citation189 (12)
Article Number604
Number of Pages11
Year2017
Place of PublicationNetherlands
ISSN0167-6369
1573-2959
Digital Object Identifier (DOI)https://doi.org/10.1007/s10661-017-6333-4
Web Address (URL)https://link.springer.com/article/10.1007/s10661-017-6333-4
AbstractRecent 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.
KeywordsVegetation stress; Heavy metal pollution; Hyperspectral remote sensing; Abandoned mines
ANZSRC Field of Research 2020410402. Environmental assessment and monitoring
401304. Photogrammetry and remote sensing
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Byline AffiliationsUniversity of New South Wales
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