Wetlands represent 6% of the Earth's land cover surface. They are of crucial importance in the global water cycle and climatic dynamics. Nowadays, wetlands are the most threatened land cover type, nevertheless their spatial distribution and ecological functions are poorly documented. Despite the need for more detailed information, wetland mapping is a rare activity. Few data are available mainly because of the complexity of obtaining good field data. We therefore propose a method based on multisensor imagery analysis to characterize land cover patterns of the second largest wetland area of the world (The Cuvette Centrale of the Congo River Basin). The time series of moderate resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) images are used to map land cover types based on their phenological differences. Flooded areas in the Congo basin have been mapped during different seasons using $L$-band synthetic aperture radar (PALSAR) imagery. The associated model has been improved upon by the addition of elevation data as well as mean canopy heights acquired with light detection and ranging (LIDAR) data. The result of this study is the first detailed spatial distribution of four forested wetland types within the Cuvette Centrale of the Congo River Basin. This study demonstrates that the spatial organization of the floodplain landscape depends on the extent of flooding. The results also show that land cover phenology is closely related to the time period of flooding and solar intensity for this region, similarly to what is observed in the extensive floodplain of the Amazon basin.