Remote sensing the radionuclide contaminated Belarusian landscape: A potential for imaging spectrometry?

D. S. Boyd, Jane Entwistle, Alan Flowers, R. P. Armitage, P. C. Goldsmith

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

The 1986 Chernobyl accident resulted in radionuclide contamination (dominated by 137Cs) across large areas of Belarus. Consequences of this accident continue to affect Belarus long after initial contamination, which in turn has placed strain upon social, economic and political infrastructures. One method to reduce this strain and remediate contamination is to return areas of land no longer posing a risk, back to an appropriate use. As a method of remediation, this requires regular and accurate monitoring of the landscape at which existing ground based techniques have not been entirely well-suited. Remote sensing, specifically the use of imaging spectrometry offers the potential to monitor the Belarusian landscape at opportune spatial and temporal resolutions. Vegetation has been shown to be an important agent in the cycling of radioactive isotopes in the environment and therefore a useful indicator of radionuclide contamination. This pilot research has focused on assessing the spectral response from Pinus sylvestris (dominant on the Belarusian landscape) at differing ages and with varying levels of 137Cs contamination. Continuum removal was applied to the spectra showing that for older forests (c. 35 years) significant spectral differences between low and high contaminated sites exist at wavelengths that are causally related to foliar biochemicals. This was not the case for young forests (c. 15 years) where no significant differences were found. The results signify the potential to infer contamination levels from spectra of forests, partitioned by age, thus indicating the possibility of using imaging spectrometry to monitor radionuclide contamination, a possibility warranting further investigation.
Original languageEnglish
Pages (from-to)1865-1874
JournalInternational Joural of Remote Sensing
Volume27
Issue number10
DOIs
Publication statusPublished - May 2006

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