Information about change is necessary for updating Land Use/ Land Cover LULC maps and the management of natural resources (XiaoMei Y, & RongQing L.Q.Y., 1999). The paper aims to map the changes in the LULC using different classification methods and to quantify the land use/ land cover change that took place in the Jordan Valley. The paper promotes the classification of LULC based on remote sensing information (obtained mainly through the utilization of Thematic Mapper TM and Enhance Thematic Mapper ETM scenes) to generate data products that are both appropriate to, and immediately usable within different scientific applications. The advancement of remote sensing technology in the developing countries such as Palestine encouraged the use of remotely sensed data to monitor the land use changes in an effective and more frequent manner. Three classification approaches were deployed and the appropriateness of the classifications to derive accurate land use maps for the pilot area using Landsat scenes were evaluated. The results showed that the use of spectral mixture analysis classification approach enhanced the classification accuracy and the ability to categorize the LULC on the pixel level.