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Mapping Congo Basin forest types from 300 m and 1km multi-sensor time series for carbon stocks and forest areas estimation

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Author(s): A. Verhegghen | P. Mayaux | C. de Wasseige | P. Defourny

Journal: Biogeosciences Discussions
ISSN 1810-6277

Volume: 9;
Issue: 6;
Start page: 7499;
Date: 2012;
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ABSTRACT
This study aimed to contribute to the understanding of the Congo Basin forests by delivering a detailed forest types map with an improved spatial discrimination and coherence for the whole Congo Basin region. A total of 20 land cover classes were described with the standardized Land Cover Classification System (LCCS) developed by the FAO. Based on a semi-automatic processing chain, the forest types map was produced by combining 19 months of observations from the ENVISAT MERIS full resolution products (300 m) and 8 yr of daily SPOT VEGETATION (VGT) reflectances (1 km). Four zones (north, south and two central) were delineated and processed separately according to their seasonal and cloud cover specificities. The discrimination between different vegetation types (e.g. forest and savannas) was significantly improved thanks to the MERIS sharp spatial resolution. This work achieved a better discrimination in cloudy areas by taking advantage of the temporal consistency of the SPOT VGT observations. This resulted in a precise delineation of the spatial extent of the rural complex in the countries situated along the Atlantic coast. Based on this new map, more accurate estimates of the surface areas of forest types were produced for each country of the Congo Basin. The impact of two forest definitions was then assessed in the framework of the reducing emissions from deforestation and degradation (REDD) initiative and carbon stocks were evaluated. Furthermore, the phenology of the different vegetation types was illustrated systematically with EVI temporal profiles. This Congo Basin forest types map reached a satisfactory overall accuracy of 71.5% and even 78.9% when the two savanna classes are aggregated.
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