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An Assessment of Mangroves in Guinea, West Africa, Using a Field and Remote Sensing Based Approach

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Abstract

We provide a baseline account as to the type of mangrove that is typical for Guinea, Africa using field based and remotely sensed data. Specifically, the mangroves of the estuarine islands of Mabala and Yélitono were classified using satellite and airborne optical remote sensing data. Mangroves were mapped according to four classes: tall red (Rhizophora racemosa), medium red (R. racemosa), dwarf red (R. mangle and R. harisonii), and black mangrove (Avicennia germinans). Producer’s and user’s accuracies for the mapping of mangrove from non-mangrove areas were both 98%. When separating amongst the mangrove classes most of the confusion resulted from the medium red mangrove class. Of the 10,442 ha of mangrove mapped, approximately 30% were classified as riverine, dominated by tall R. racemosa. The remaining mangrove areas were dominated by dwarf mangrove of either Rhizophora or A. germinans. Biophysical parameter data collected from 56 transects varied considerably amongst the classes. For the tallest mangrove class, the mean values of height, DBH, estimated LAI, stem density and basal area recorded were 13 m, 15.1 cm, 4.3, 838 stems/ha, and 25.9 m2/ha, respectively. In contrast, for A. germinans, values of 3 m, 4.6 cm, 1.5, 2,877 stems/ha, and 6.0 m2/ha were calculated, respectively.

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Acknowledgments

Funding for this investigation was provided by Rio Tinto Iron Ore as part of an environmental baseline survey for a potential deep water port in the Simandou iron ore exploration and mining project. We are indebted to Richard Fontaine of SNC–Lavalin Environment for his selection and support of Environnement Illimité Inc. for this project. Michel Bureau, also of SNC–Lavalin Environment, was instrumental in on-site assistance and support during the field data collection.

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Correspondence to John M. Kovacs.

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Kovacs, J.M., de Santiago, F.F., Bastien, J. et al. An Assessment of Mangroves in Guinea, West Africa, Using a Field and Remote Sensing Based Approach. Wetlands 30, 773–782 (2010). https://doi.org/10.1007/s13157-010-0065-3

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  • DOI: https://doi.org/10.1007/s13157-010-0065-3

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