Mapping of Wood Carbon Stocks in the Classified Forest of Wari-Maro in Benin Center (West Africa) - HAL Accéder directement au contenu
Article dans une revue International Journal of Forest, Animal and Fisheries Research Année : 2018

Mapping of Wood Carbon Stocks in the Classified Forest of Wari-Maro in Benin Center (West Africa)

Résumé

—The Emissions Reducing program related to Deforestation and Forest Degradation (Redd +) calls for the development of approaches to quantify and spatialize forest carbon in order to design more appropriate forest management policies. The mapping of carbon stocks was done in the Wari-Maro Forest Reserve. To achieve this, forest inventory data (in situ) and remotely sensed data (Landsat 8 image) were used to construct a wood carbon stock forecasting model. Simple linear regression was used to test the correlation between these two variables. In situ surveys indicate that 64% of carbon stocks are contributed by forest formations, 32.72% are provided by savannah formations and 3.27% are from anthropogenic formations. The quantitative relationship between NDVI and carbon in situ shows a very good correlation with a high coefficient of determination R² = 91%. The carbon map generated from the model identified fronts of deforestation through their low carbon content. This remote sensing approach indicates that forest formations sequester 60% of forest carbon. The savannah formations reserve 33%, the anthropic formations bring only 6% of the stocks. Mapping has further captured the spatial variability among land use types, thus providing arguments to fully meet the objectives of Redd +.

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Géographie
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Dates et versions

halshs-01792517, version 1 (15-05-2018)

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Paternité - Pas d'utilisation commerciale - Pas de modification - CC BY 4.0

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Yaya Issifou Moumouni, Soufouyane Zakari, Omer A. B. Thomas, Ismaïla Toko Imorou, Mama Djaouga, et al.. Mapping of Wood Carbon Stocks in the Classified Forest of Wari-Maro in Benin Center (West Africa). International Journal of Forest, Animal and Fisheries Research, 2018, 2 (2), pp.64 - 73. ⟨10.22161/ijfaf.2.2.3⟩. ⟨halshs-01792517⟩
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