The objective of this project is to apply to some optical data, an object oriented classification approach for monitoring and detecting the changes of land cover in the north of Cote dIvoire where cashew is spreading. Two Landsat images TM (1986)/ETM+ (2002) and a Sentinel-2 (2022) are used in this research. The method is achieved through the monitoring of land cover from an object-oriented approach based on fuzzy logic. For this specific methodological approach, we resort to texture analysis and principal component analysisa change detection through a post classification method and the integration of the resulting map in a GIS. By this approach, we produced the lands cover of 1986 2002 and 2022 with Kappa coefficients at 86 88 and 87 % respectively. For the period of concern (1986-2022), the method allows spatializing and quantifying the land cover changes in this complex environment dominated by cashew.