ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-7, 75-79, 2014
https://doi.org/10.5194/isprsannals-II-7-75-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
19 Sep 2014
Spectroscopic analysis of soil metal contamination around a derelict mine site in the Blue Mountains, Australia
A. Shamsoddini, S. Raval, and R. Taplin Australian Centre for Sustainable Mining Practices, School of Mining Engineering, University of New South Wales, NSW 2052, Australia
Keywords: Soil, Modelling, Analysis, Prediction, Spectral Abstract. Abandoned mine sites pose the potential threat of the heavy metal pollution spread through streams and via runoff leading to contamination of soil and water in their surrounding areas. Regular monitoring of these areas is critical to minimise impacts on water resources, flora and fauna. Conventional ground based monitoring is expensive and sometimes impractical; spectroscopic methods have been emerged as a reliable alternative for this purpose. In this study, the capabilities of the spectroscopy method were examined for modelling soil contamination from around the abandoned silver-zinc mine located at Yerranderie, NSW Australia. The diagnostic characteristics of the original reflectance data were compared with models derived from first and second derivatives of the reflectance data. The results indicate that the models derived from the first derivative of the reflectance data estimate heavy metals significantly more accurately than model derived from the original reflectance. It was also found in this study that there is no need to use second derivative for modelling heavy metal soil contamination. Finally, the results indicate that estimates were of greater accuracy for arsenic and lead compared to other heavy metals, while the estimation for silver was found to be the most erroneous.
Conference paper (PDF, 486 KB)


Citation: Shamsoddini, A., Raval, S., and Taplin, R.: Spectroscopic analysis of soil metal contamination around a derelict mine site in the Blue Mountains, Australia, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-7, 75-79, https://doi.org/10.5194/isprsannals-II-7-75-2014, 2014.

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