Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images
The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon...
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| Format: | Article |
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Elsevier
2015
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| Online Access: | https://eprints.nottingham.ac.uk/29207/ |
| _version_ | 1848793737552986112 |
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| author | Arellano, Paul Tansey, Kevin Balzter, Heiko Boyd, Doreen S. |
| author_facet | Arellano, Paul Tansey, Kevin Balzter, Heiko Boyd, Doreen S. |
| author_sort | Arellano, Paul |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI705) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest. |
| first_indexed | 2025-11-14T19:05:03Z |
| format | Article |
| id | nottingham-29207 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:05:03Z |
| publishDate | 2015 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-292072020-05-04T20:06:44Z https://eprints.nottingham.ac.uk/29207/ Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images Arellano, Paul Tansey, Kevin Balzter, Heiko Boyd, Doreen S. The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI705) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest. Elsevier 2015-10 Article PeerReviewed Arellano, Paul, Tansey, Kevin, Balzter, Heiko and Boyd, Doreen S. (2015) Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images. Environmental Pollution, 205 . pp. 225-239. ISSN 1873-6424 Petroleum pollution; Hyperspectral remote sensing; Amazon forest; Vegetation indices; Yasuni National Park http://www.sciencedirect.com/science/article/pii/S0269749115002754 doi:10.1016/j.envpol.2015.05.041 doi:10.1016/j.envpol.2015.05.041 |
| spellingShingle | Petroleum pollution; Hyperspectral remote sensing; Amazon forest; Vegetation indices; Yasuni National Park Arellano, Paul Tansey, Kevin Balzter, Heiko Boyd, Doreen S. Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images |
| title | Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images |
| title_full | Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images |
| title_fullStr | Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images |
| title_full_unstemmed | Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images |
| title_short | Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images |
| title_sort | detecting the effects of hydrocarbon pollution in the amazon forest using hyperspectral satellite images |
| topic | Petroleum pollution; Hyperspectral remote sensing; Amazon forest; Vegetation indices; Yasuni National Park |
| url | https://eprints.nottingham.ac.uk/29207/ https://eprints.nottingham.ac.uk/29207/ https://eprints.nottingham.ac.uk/29207/ |