Various approaches can be used to map bamboo in forested areas, including the use of airborne and space-borne remote sensing data. In remote sensing, thematic maps are created from numerical data collected by sensors that measure the amount of reflected energy from different land cover types. These data are then translated into an image by assigning visible colours to the numerical value. Remote sensing technique has been proven to be effective for mapping timber resource but the use of this technology in the mapping of bamboo resources in Malaysia is still new and yet to be explored. The traditional method of classification in remote sensing is by using supervised classification of mixed pixel; however, the use of sub-pixel classifier is recently gaining momentum. This study applies the sub-pixel classification technique in processing SPOT 5 (path/row: 268/339) satellite data to identify and map bamboo areas in Compartment 26 of Temengor Forest Reserve in Perak. Ground verification was done to check the accuracy of classification from the sub-pixel technique. This study identified about 4.61 ha (15.4%) bamboo areas from the 60 ha of the total area in compartment 26 of Temengor Forest Reserve. The estimated bamboo culms were 4,062 and the accuracy of mapping was 86.6%. This paper demonstrates that remote sensing is capable of identifying bamboo areas through sub-pixel-based technique with acceptable results. In future studies, high resolution satellite remote sensing should be considered for better results.