Mapping estuarine vegetation using satellite imagery: The case of the invasive species Baccharis halimifolia at a Natura 2000 site. (15th February 2019)
- Record Type:
- Journal Article
- Title:
- Mapping estuarine vegetation using satellite imagery: The case of the invasive species Baccharis halimifolia at a Natura 2000 site. (15th February 2019)
- Main Title:
- Mapping estuarine vegetation using satellite imagery: The case of the invasive species Baccharis halimifolia at a Natura 2000 site
- Authors:
- Calleja, F.
Ondiviela, B.
Galván, C.
Recio, M.
Juanes, J.A. - Abstract:
- Abstract: The invasive shrub Baccharis halimifolia is a threat to the environmental health of many estuarine protected areas throughout Europe. It displaces saltmarsh vegetation and creates monospecific stands that diminish the natural diversity. This work aims to develop a procedure to map this invasive species using satellite imagery. Landsat-8 and Sentinel 2A images are compared, along with three classification approaches (pixel-based, object-based, a mixture of both), to determine which combination yields the best B. halimifolia mapping results. All calculations were made using open-source software, including the ORFEO toolbox for the segmentations in the object-based approach, and the Scikit-learn package for the Support Vector Machines classification algorithm. The pixel-based classifications mapped the invasive species with an accuracy of 70% or higher for both images. The Landsat image had higher accuracy in the overall classification of the vegetation, but the Sentinel image proved better suited for mapping B. halimifolia specifically, due to its higher spatial and spectral resolution. In addition, the procedure was implemented using a Landsat image from 2005, and mapped the invasive species with an accuracy of 72% and 88% for producers and users accuracy respectively. The developed procedure represents a valuable tool for restoration projects, allowing for retrospective analyses or relatively low-cost monitoring of B. halimifolia's current distribution. GraphicalAbstract: The invasive shrub Baccharis halimifolia is a threat to the environmental health of many estuarine protected areas throughout Europe. It displaces saltmarsh vegetation and creates monospecific stands that diminish the natural diversity. This work aims to develop a procedure to map this invasive species using satellite imagery. Landsat-8 and Sentinel 2A images are compared, along with three classification approaches (pixel-based, object-based, a mixture of both), to determine which combination yields the best B. halimifolia mapping results. All calculations were made using open-source software, including the ORFEO toolbox for the segmentations in the object-based approach, and the Scikit-learn package for the Support Vector Machines classification algorithm. The pixel-based classifications mapped the invasive species with an accuracy of 70% or higher for both images. The Landsat image had higher accuracy in the overall classification of the vegetation, but the Sentinel image proved better suited for mapping B. halimifolia specifically, due to its higher spatial and spectral resolution. In addition, the procedure was implemented using a Landsat image from 2005, and mapped the invasive species with an accuracy of 72% and 88% for producers and users accuracy respectively. The developed procedure represents a valuable tool for restoration projects, allowing for retrospective analyses or relatively low-cost monitoring of B. halimifolia's current distribution. Graphical abstract: fx1 Highlights: Baccharis halimifolia is mapped in a small estuary with Landsat and Sentinel images. Images and classification approaches are compared to select the best combination. Analysis are made using open source software (ORFEO toolbox, Scikit-learn). Sentinel image and a pixel-based classification shows the best result. Procedure is successfully applied on a past image for retrospective analysis. … (more)
- Is Part Of:
- Continental shelf research. Volume 174(2019)
- Journal:
- Continental shelf research
- Issue:
- Volume 174(2019)
- Issue Display:
- Volume 174, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 174
- Issue:
- 2019
- Issue Sort Value:
- 2019-0174-2019-0000
- Page Start:
- 35
- Page End:
- 47
- Publication Date:
- 2019-02-15
- Subjects:
- Bay of Biscay -- Landsat -- Sentinel -- Support vector machines -- Remote sensing -- Mapping
Continental shelf -- Periodicals
Submarine geology -- Periodicals
551.41 - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/02784343 ↗ - DOI:
- 10.1016/j.csr.2019.01.002 ↗
- Languages:
- English
- ISSNs:
- 0278-4343
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3425.640000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9446.xml