In this research wok, three different techniques of change detection were used to detect changes in forest areas. One of the techniques used a local similarity measure approach to detect changes. This new approach of change detection technique, which used mutual information to measure the similarity between two multi-temporal images, was developed based on correspondence of the pixel values, rather than the difference in their intensity. Pixels suffering any changes will be maximally dissimilar. The study was conducted using multi-temporal SPOT 5 satellite images, with the resolution of 10 m x10 m on 5th August 2005 and 13th June 2007. The experimental results show that local mutual information provides more reliable results in detecting changes of the multitemporal images containing different lighting condition compared to the image differencing and NDVI technique, specifically in areas with less plant growth. In addition, it can also overcome the problem on selecting the threshold value. Besides, the findings of this study have also shown that band 3, which is sensitive to vegetation biomass, gave the best result in detecting area of changes compared to the others.