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

Abstract

Abstract. This study aims to contribute to the understanding of the Congo Basin forests by delivering a detailed map of vegetation types 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 Congo Basin vegetation 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 VEGE-TATION (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. A better discrimination was achieved 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. Carbon stocks of the Basin were evaluated to a total of 49 360 million metric tons. The regional scale of the map was an opportunity to investigate what could be an appropriate tree cover threshold for a forest class definition in the Congo Basin countries. A 30 % tree cover threshold was suggested. 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 some classes are aggregated. The values of the Cohen's kappa coefficient, respectively 0.64 and 0.76 indicates a result significantly better than random.

Characterizing Land Cover Impacts on the Responses of Land Surface Phenology to the Rainy Season in the Congo Basin

“…We chose the Global Land Cover 2000 product instead of other products [14,26,27] due to the following considerations. First, the Global Land Cover 2000 product relies on knowledge from local experts and remotely sensed data from both optical and microwave sensors, which is more suitable for cloud-prone regions such as the Congo Basin, rather than the products derived from data mainly acquired by optical sensors, such as the Moderate Resolution Imaging Spectroradiometer and the Medium Resolution Imaging Spectrometer [14,21,27]. The Global Land Cover 2000 product has an overall accuracy of 68.6% according to sample sites collected around the world [28], and it has the highest overall accuracy (56%) among five satellite-derived land cover products in Africa [29].…”

“…This is caused by challenges in characterizing rainforest LSP due to persistent cloud cover and poor understanding of rainfall seasonality. LSP in the Congo Basin rainforest has been previously generated in studies using data acquired by sensors such as the Moderate Resolution Imaging Spectroradiometer and Satellite Pour l'Observation de la Terre Vegetation, in which the observations were averaged over multiple years to reduce cloud contamination [13,14]. However, the inter-annual variations in Congo Basin rainforest LSP have not been retrieved until recently, when the observations from the METEOSAT Second Generation series of geostationary satellites become available [15][16][17].…”

“…The characteristics of LSP across the Congo Basin vary across different ecosystems [13,14,16,21]. Results from previous studies have shown that the phenology of rainforest trees is highly asynchronous, and characterized by the simultaneous abscissions of old leaves and emergences of new leaves [22][23][24].…”

Congo Basin peatlands: threats and conservation priorities

“…30.6 petagrams (Pg; 1 × 10 15 g) of carbon (Dargie et al 2017). This makes the Cuvette Centrale-spanning both the Republic of Congo (ROC) and Democratic Republic of Congo (DRC)-the single largest peatland complex known in the tropics (Dargie et al 2017), with a belowground carbon stock equivalent to that of the aboveground tropical forest carbon stocks for the entire Congo Basin (Saatchi et al 2011;Verhegghen et al 2012). The discovery of so much peat in the Congo Basin has forced a re-evaluation of the role of Congolese swamps in the global carbon cycle.…”

Comparison between Vegetation and Rainfall of Bioclimatic Ecoregions in Central Africa

“…The classification of African ecosystems at a 1-km resolution using multiannual Satellite Pour l'Observation de la Terre Vegetation (SPOT/VEGETATION) data and a hybrid clustering approach has been carried out by Kaptué et al [15]. Verhegghen et al [16] have made a map of Congo Basin forest types from 300-m and 1-km multi-sensor time series for carbon stocks and forest area estimation.…”