Deforestation brings many problems to humanity, so studies started to appear to help reduce the damages done by the root of the problem and restore the health of our forests. In this paper, we present a method that can help identify deforested areas with the intention that deforestation may be monitored automatically using satellite imagery in the future. We analyze satellite images from the Peruvian Amazon in three separate timelines to view change over time. First, we preprocessed the images to remove haze and cloud using the dark channel prior method. Then, we segment the deforested area in the clean images by converting the RGB images to HSV format and later filtering the color corresponding to forested areas. Then we produce three binary images from the HSV conversion. Finally, these images are merged to obtain a single image that shows the change of deforestation over time. The method is compared with methods based on NDVI and NDTS detecting more deforested regions.