Abstract: In this paper, the vegetation information of Macao was quantificationally extracted from Landsat ETM+ data of 2003 by using linear spectral un-mixing approach (LSMM). At the same time, the Normalized Difference Vegetation Index (NDVI) image and greenness image (TC2) which was obtained by the Tasseledcap Trasform. These two images, also obtained based on the ETM+ image (2003) of Macao, were used to as two important comparison indexes to evaluate the extracted vegetation information by LSMM. The result shows that the three images have high correlation. At the same time, the vegetation areas extracted by LSMM, NDVI and TC2 are 4.19 km2, 8.26 km2 and 8.68 km2 respectively. The areas by LSMM are closer the actual vegetable areas (5.79 km2). The results prove the linear spectral un-mixing approach is not only an efficient way to extract vegetation information but also a more accurate measure than routine pixel-based remote sensing methods. LSMM provides a novel way for monitoring vegetation more accurately and efficiently.