Mangrove species and stand mapping in Gazi Bay (Kenya) using Quickbird satellite imagery
- Author
- Griet Neukermans (UGent) , F. Dahdouh-Guebas, J. G. Kairo and N. Koedam
- Organization
- Abstract
- This paper presents an automated method for mangrove stand recognition (delineation and labeling) and species mapping based on fuzzy per-pixel classification techniques of a QuickBird satellite image. The four dominant mangrove species in Gazi Bay (Kenya) are mapped with an overall accuracy of 72 percent, where the two socio-economically most important species are mapped with user accuracies above 85 percent. Mangrove stand maps were compared to visual delineations done by an expert interpreter and the quality was based on the quantity of overlap one has with the other An overall correspondence up to 86 percent was achieved.
- Keywords
- CLASSIFICATION, IKONOS, FORESTS, FUTURE, forestry, remote sensing, GIS, vegetation mapping, visual, interpretation, delineation accuracy assessment, Point-Centred-Quarter-Method
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8674408
- MLA
- Neukermans, Griet, et al. “Mangrove Species and Stand Mapping in Gazi Bay (Kenya) Using Quickbird Satellite Imagery.” JOURNAL OF SPATIAL SCIENCE, vol. 53, no. 1, 2008, pp. 75–86, doi:10.1080/14498596.2008.9635137.
- APA
- Neukermans, G., Dahdouh-Guebas, F., Kairo, J. G., & Koedam, N. (2008). Mangrove species and stand mapping in Gazi Bay (Kenya) using Quickbird satellite imagery. JOURNAL OF SPATIAL SCIENCE, 53(1), 75–86. https://doi.org/10.1080/14498596.2008.9635137
- Chicago author-date
- Neukermans, Griet, F. Dahdouh-Guebas, J. G. Kairo, and N. Koedam. 2008. “Mangrove Species and Stand Mapping in Gazi Bay (Kenya) Using Quickbird Satellite Imagery.” JOURNAL OF SPATIAL SCIENCE 53 (1): 75–86. https://doi.org/10.1080/14498596.2008.9635137.
- Chicago author-date (all authors)
- Neukermans, Griet, F. Dahdouh-Guebas, J. G. Kairo, and N. Koedam. 2008. “Mangrove Species and Stand Mapping in Gazi Bay (Kenya) Using Quickbird Satellite Imagery.” JOURNAL OF SPATIAL SCIENCE 53 (1): 75–86. doi:10.1080/14498596.2008.9635137.
- Vancouver
- 1.Neukermans G, Dahdouh-Guebas F, Kairo JG, Koedam N. Mangrove species and stand mapping in Gazi Bay (Kenya) using Quickbird satellite imagery. JOURNAL OF SPATIAL SCIENCE. 2008;53(1):75–86.
- IEEE
- [1]G. Neukermans, F. Dahdouh-Guebas, J. G. Kairo, and N. Koedam, “Mangrove species and stand mapping in Gazi Bay (Kenya) using Quickbird satellite imagery,” JOURNAL OF SPATIAL SCIENCE, vol. 53, no. 1, pp. 75–86, 2008.
@article{8674408,
abstract = {{This paper presents an automated method for mangrove stand recognition (delineation and labeling) and species mapping based on fuzzy per-pixel classification techniques of a QuickBird satellite image. The four dominant mangrove species in Gazi Bay (Kenya) are mapped with an overall accuracy of 72 percent, where the two socio-economically most important species are mapped with user accuracies above 85 percent. Mangrove stand maps were compared to visual delineations done by an expert interpreter and the quality was based on the quantity of overlap one has with the other An overall correspondence up to 86 percent was achieved.}},
author = {{Neukermans, Griet and Dahdouh-Guebas, F. and Kairo, J. G. and Koedam, N.}},
issn = {{1449-8596}},
journal = {{JOURNAL OF SPATIAL SCIENCE}},
keywords = {{CLASSIFICATION,IKONOS,FORESTS,FUTURE,forestry,remote sensing,GIS,vegetation mapping,visual,interpretation,delineation accuracy assessment,Point-Centred-Quarter-Method}},
language = {{eng}},
number = {{1}},
pages = {{75--86}},
title = {{Mangrove species and stand mapping in Gazi Bay (Kenya) using Quickbird satellite imagery}},
url = {{http://doi.org/10.1080/14498596.2008.9635137}},
volume = {{53}},
year = {{2008}},
}
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