Due to its shape and location (2°N-13°N – 8°E-16°E; proximity of the Atlantic Ocean), Cameroon is characterized by a panel of cross-regional climate encountered widely in tropical Africa. Over the region, the decrease rainfall during the second half of the last century has been shown to be associated with stronger recurrence of drier periods, specifically in the core of the rainy season. These conditions have favored the degradation of vegetation cover, driven by socioeconomic and demographic constraints. The substantial impacts on human activities and local society highlight the need to better understand how climate and environmental dynamics do interact locally. The aim of this study is to diagnose multi-scale rainfall variability and its relationship with vegetation cover (natural and/or grown), which is directly or indirectly associated to the land-cover and land-use dynamics at these latitudes. Using observed rainfall data (Climatic Research Unit/punctual), the spatial modes of rainfall variability at annual and intraseasonal scales are defined through Principal Component Analysis (PCA) and Agglomerative Hierarchical Clustering (AHC). These regionalizations lead to the discretisation of 5 climatic zones, distinguished from each other, by both the amount of rainfall and seasonality (unimodal / bimodal). New intraseasonal dry spells statistics (number, length, period of occurrence) are produced as well as dates of onset and end of the vegetative seasons by sub-regions. Using unsupervised classification methods (such as ISODATA) in Normalized Difference Vegetation Index (NDVI) data at a 8km spatial resolution, vegetation cover spatiotemporal distribution and typology were produced. Then, based on a concomitant use of statistical and GIS approaches, higher resolutions of NDVI (SPOT-1Km) and Global Land-cover data (GLC 2000), allowed to further evaluate both the pluviometric and anthropogenic factors (demography, land use) influencing vegetation dynamics. Analysis were carried out in Northern Cameroon (6°N-13°N – 11°E-16°E), which is the most sensitive region with regards to climatic and environmental variability, that could lead to important socio-economic thread locally.
