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This work deals with the evaluation of the potential of multi-temporal and multi-sensor (optical and radar) images of the satellites Sentinel-1 and Sentinel-2 satellites for land cover mapping and coastline evolution monitoring in a tropical ecosystem over the period 2015 to 2020. The study area chosen is the Cameroon Estuary. This area represents a major ecological transition in the sub-region with the presence of protected natural reserves (mangroves, dense forest, wetlands) but also a strong anthropic activity (construction, agriculture, degraded forest). The methodological approach consisted of a chain of pre-processing and visual image analysis, followed by a combination of the bands from each sensor, a supervised Random Forest classification to draft a land use map and finally a digitization of the coastline. Overall, the results show that the classification with the Sentinel- 2 images using 10 bands and adding 4 vegetation indices is slightly more accurate (95.75 %) than the classification with the 13 initial bands (91.78 %). The classification performed with the Sentinel-1A multi-temporal image series (dual polarization (VV, VH) and VV/VH ratio) leads to an accuracy of 78.44 %. The combination of Sentinel-2 A&B bands (10 bands and 4 indices) and Sentinel-1 improves the results and leads to an accuracy of 98.76 %. Our results also show that the use of multi-temporal image time series significantly improves the classification accuracy compared to the use of a single image (mono-date), and this for both sensors, i.e. an additional gain of 13 % and 10 % respectively for Sentinel-2 and Sentinel-1. However, this gain remains small for temporally stable classes. The results of the coastline evolution analysis show that the Cameroon estuary is disturbed by different levels of erosion (Cape Cameroon, North Manoka Island, Sanaga River mouth), and accretion (Limbe, and South Manoka Island) and also by weak internal variations. The fusion of optical and radar remote sensing data in the discrimination of land use classes, has shown that the construction zones are the most vulnerable to coastal erosion. On the other hand, the presence of vegetation (mangrove, forest) stabilizes and protects the coast from possible risks of this nature. [ABSTRACT FROM AUTHOR]