We evaluated the applicability of the Visible and Near Infrared bands (15 m spatial resolution) of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery in mapping land use/cover in the drylands of northern Ethiopia. Ground Control Points were collected from the field using Geographic Positioning System in which half of them were used for classification and the remaining for accuracy assessment. The image was classified into four dominant land use/cover types that represent the major habitats of the study site. Image classification was done using pixel-based supervised classification with the Maximum Likelihood Classification algorithm. The accuracy of classification was evaluated using error matrix and Kappa statistics. Finally, we found an overall classification accuracy of 80% and this implies that ASTER imagery can be used as a good source of data in mapping biodiversity at habitat scale in data scarce drylands of northern Ethiopia.