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Proceedings Paper

Investigating vegetation spectral reflectance for detecting hydrocarbon pipeline leaks from multispectral data
Author(s): Bashir Adamu; Kevin Tansey; Michael J. Bradshaw
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Paper Abstract

The aim of this paper is to analyse spectral reflectance data from Landsat TM of vegetation that has been exposed to hydrocarbon contamination from oil spills from pipelines. The study is undertaken in an area of mangrove and swamp vegetation where the detection of an oil spill is traditionally difficult to make. We used a database of oil spill records to help identify candidate sites for spectral analysis. Extracted vegetation spectra were compared between polluted and nonpolluted sites and supervised (neural network) classification was carried out to map hydrocarbon (HC) contaminated sites from the sample areas. Initial results show that polluted sites are characterised by high reflectance in the visible (VIS) 0.4μm - 0.7μm, and a lower reflectance in the near-infrared (NIR) 0.7μm - 1.1μm. This suggests that the vegetation is in a stressed state. Samples taken from pixels surrounding polluted sites show similar spectral reflectance values to that of polluted sites suggesting possible migration of HC to the wider environment. Further work will focus on increasing the sample size and investigating the impact of an oil spill on a wider buffer zone around the spill site.

Paper Details

Date Published: 17 October 2013
PDF: 8 pages
Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 889216 (17 October 2013); doi: 10.1117/12.2028907
Show Author Affiliations
Bashir Adamu, Univ. of Leicester (United Kingdom)
Kevin Tansey, Univ. of Leicester (United Kingdom)
Michael J. Bradshaw, Univ. of Leicester (United Kingdom)


Published in SPIE Proceedings Vol. 8892:
Image and Signal Processing for Remote Sensing XIX
Lorenzo Bruzzone, Editor(s)

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