EELGRASS MAPPING IN ATLANTIC CANADA USING WORLDVIEW-2 IMAGERY
Eelgrass (<i>Zostera marina</i> L.) is a marine angiosperm plant that grows throughout coastal areas in Atlantic Canada. Eelgrass meadows provide numerous ecosystem services, and while they have been acknowledged as important habitats, their location, extent, and health in Atlantic Canad...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2020-08-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/685/2020/isprs-archives-XLIII-B3-2020-685-2020.pdf |
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| author | D. Forsey B. Leblon A. LaRocque M. Skinner A. Douglas |
| author_facet | D. Forsey B. Leblon A. LaRocque M. Skinner A. Douglas |
| author_sort | D. Forsey |
| collection | DOAJ |
| description | Eelgrass (<i>Zostera marina</i> L.) is a marine angiosperm plant that grows throughout coastal areas in Atlantic Canada. Eelgrass meadows provide numerous ecosystem services, and while they have been acknowledged as important habitats, their location, extent, and health in Atlantic Canada are poorly understood. This study examined the effectiveness of WorldView-2 optical satellite imagery to map eelgrass presence in Tabusintac Bay, New Brunswick (Canada), an estuarine lagoon with extensive eelgrass coverage. The imagery was classified using two supervised classifiers: the parametric Maximum Likelihood Classifier (MLC) and the non-parametric Random Forests (RF) classifier. While Random Forests was expected to produce higher classification accuracies, it was shown not to be much better than MLC. The overall validation accuracy was 97.6% with RF and 99.8% with MLC. |
| first_indexed | 2024-12-13T11:05:21Z |
| format | Article |
| id | doaj.art-a5197f769e5c4a0c9a150d4334e9e2c0 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-13T11:05:21Z |
| publishDate | 2020-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-a5197f769e5c4a0c9a150d4334e9e2c02022-12-21T23:49:02ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B3-202068569210.5194/isprs-archives-XLIII-B3-2020-685-2020EELGRASS MAPPING IN ATLANTIC CANADA USING WORLDVIEW-2 IMAGERYD. Forsey0B. Leblon1A. LaRocque2M. Skinner3A. Douglas4Faculty of Forestry and Environmental Management, University of New Brunswick, Fredericton (NB), E3B 5A3, CanadaFaculty of Forestry and Environmental Management, University of New Brunswick, Fredericton (NB), E3B 5A3, CanadaFaculty of Forestry and Environmental Management, University of New Brunswick, Fredericton (NB), E3B 5A3, CanadaStantec Consulting Ltd., 40 Highfield Park Drive 102-40, Dartmouth (NS), B3A 0A3, CanadaSouthern Gulf of St. Lawrence Coalition on Sustainability, Stratford (PEI), C1B 1L1, CanadaEelgrass (<i>Zostera marina</i> L.) is a marine angiosperm plant that grows throughout coastal areas in Atlantic Canada. Eelgrass meadows provide numerous ecosystem services, and while they have been acknowledged as important habitats, their location, extent, and health in Atlantic Canada are poorly understood. This study examined the effectiveness of WorldView-2 optical satellite imagery to map eelgrass presence in Tabusintac Bay, New Brunswick (Canada), an estuarine lagoon with extensive eelgrass coverage. The imagery was classified using two supervised classifiers: the parametric Maximum Likelihood Classifier (MLC) and the non-parametric Random Forests (RF) classifier. While Random Forests was expected to produce higher classification accuracies, it was shown not to be much better than MLC. The overall validation accuracy was 97.6% with RF and 99.8% with MLC.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/685/2020/isprs-archives-XLIII-B3-2020-685-2020.pdf |
| spellingShingle | D. Forsey B. Leblon A. LaRocque M. Skinner A. Douglas EELGRASS MAPPING IN ATLANTIC CANADA USING WORLDVIEW-2 IMAGERY The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | EELGRASS MAPPING IN ATLANTIC CANADA USING WORLDVIEW-2 IMAGERY |
| title_full | EELGRASS MAPPING IN ATLANTIC CANADA USING WORLDVIEW-2 IMAGERY |
| title_fullStr | EELGRASS MAPPING IN ATLANTIC CANADA USING WORLDVIEW-2 IMAGERY |
| title_full_unstemmed | EELGRASS MAPPING IN ATLANTIC CANADA USING WORLDVIEW-2 IMAGERY |
| title_short | EELGRASS MAPPING IN ATLANTIC CANADA USING WORLDVIEW-2 IMAGERY |
| title_sort | eelgrass mapping in atlantic canada using worldview 2 imagery |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/685/2020/isprs-archives-XLIII-B3-2020-685-2020.pdf |
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