Abstract

Stack emission and deposition of heavy metals from industrial sites continues to be an environmental concern, and the effects of it on particular ecosystems need to be further investigated. This has become more practicable with recent advancements in information gathering systems and analysis techniques, like those afforded by remote sensors and GIS. The intent of this research was to determine the utility of Landsat multispectral imagery, biogeochemical sampling of black oak trees, and hyperspectral scanning of leaf reflectance for the purpose of assessing forests at the Magnolia Hollow Conservation Area in Missouri and the Fults Hill Nature Preserve in Illinois, both located downwind from a lead smelter facility and a coal fired power plant. Vegetation index models using multiband images were derived to characterize tree health status at the time of leaf sample collection, and change detection analysis was conducted to quantify temporal variations over a 13 year period. Multivariate statistics were used to identify relationships between spectral reflectance, biogeochemistry, and forest attributes. Preliminary results have found relatively high concentrations of several metals (e.g., Hg and Cd) accumulated in leaf tissue. These may be sufficient enough to induce discernible contamination effects in specific reflectance wavelength regions, and change detection has revealed that there is a notable difference in forest coverage that has occurred at these areas during the timeframe assessed.

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