Detection of oil pollution along the pipeline routes in tropical ecosystem from multi-spectral data
Detection of oil pollution along the pipeline routes in tropical ecosystem from multi-spectral data
The study was conducted in an oil producing environment dominated by mangrove and swamp vegetation in Niger Delta, Nigeria. Ancillary data including oil pipeline map and GPS of spill points were used in selecting sample sites to identify and detect polluted locations. A number of polluted and non-polluted sites were selected and vegetation spectral reflectance and indices for these sample sites were extracted from TM data of January and December 1986. A statistical T-test was used to test for significant differences between vegetation spectral reflectance and indices from polluted and non-polluted sites. The initial results from the analysis of spectral reflectance between polluted and non-polluted did not show any significant difference in all the six spectral bands with p-value <0.005. The results from analysis of various vegetation indices some did not show any significance differences between the polluted and non-polluted sites (e.g. the SRI, SAVI and EVI2). Other VIs (NDVI, MSAVI2 and ARVI2) showed significant differences between the polluted and non-polluted sites. From these preliminary results we can conclude that pollution from oil spills may result to the changes in leaf biochemistry of the Mangroves in the Niger Delta which are detectable from remote sensing data. Future work will focus on undertaking further temporal analysis of additional spill sites to determine what quantity of spilt oil arises in spectral changes of vegetation. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only
978-1628410587
91210D
Adamu, Bashir
2cdf36a9-7e18-4ed4-94a9-a21d1fb348f4
Tansey, Kevin
a363e5c7-b369-415d-8c38-dcb871109198
Ogutu, Booker
4e36f1d2-f417-4274-8f9c-4470d4808746
22 May 2014
Adamu, Bashir
2cdf36a9-7e18-4ed4-94a9-a21d1fb348f4
Tansey, Kevin
a363e5c7-b369-415d-8c38-dcb871109198
Ogutu, Booker
4e36f1d2-f417-4274-8f9c-4470d4808746
Adamu, Bashir, Tansey, Kevin and Ogutu, Booker
(2014)
Detection of oil pollution along the pipeline routes in tropical ecosystem from multi-spectral data.
In,
Braun, Jerome J.
(ed.)
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014.
(Proceedings of SPIE, 9121)
Bellingham, US.
SPIE, .
(doi:10.1117/12.2049590).
Record type:
Book Section
Abstract
The study was conducted in an oil producing environment dominated by mangrove and swamp vegetation in Niger Delta, Nigeria. Ancillary data including oil pipeline map and GPS of spill points were used in selecting sample sites to identify and detect polluted locations. A number of polluted and non-polluted sites were selected and vegetation spectral reflectance and indices for these sample sites were extracted from TM data of January and December 1986. A statistical T-test was used to test for significant differences between vegetation spectral reflectance and indices from polluted and non-polluted sites. The initial results from the analysis of spectral reflectance between polluted and non-polluted did not show any significant difference in all the six spectral bands with p-value <0.005. The results from analysis of various vegetation indices some did not show any significance differences between the polluted and non-polluted sites (e.g. the SRI, SAVI and EVI2). Other VIs (NDVI, MSAVI2 and ARVI2) showed significant differences between the polluted and non-polluted sites. From these preliminary results we can conclude that pollution from oil spills may result to the changes in leaf biochemistry of the Mangroves in the Niger Delta which are detectable from remote sensing data. Future work will focus on undertaking further temporal analysis of additional spill sites to determine what quantity of spilt oil arises in spectral changes of vegetation. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only
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Published date: 22 May 2014
Organisations:
Global Env Change & Earth Observation
Identifiers
Local EPrints ID: 374474
URI: http://eprints.soton.ac.uk/id/eprint/374474
ISBN: 978-1628410587
PURE UUID: 29667a71-475f-4bac-92cc-4c38329d78fd
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Date deposited: 20 Feb 2015 08:41
Last modified: 15 Mar 2024 03:33
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Author:
Bashir Adamu
Author:
Kevin Tansey
Editor:
Jerome J. Braun
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