Grassland cover near Lake Qinghai in western China was mapped into nine percentage classes from a TM-derived Normalised Difference Bareness Index (NDBI) image based on 178 in situ samples collected within 1 m2 sites. Their ground coordinates logged with a GPS unit were used to locate their pixel values on the NDBI image. A new method, in which the in situ samples and their pixel NDBI values were independently ranked prior to the establishment of their linear regression relationship, was applied to converting the NDBI image into a map of grass coverage. This relationship enabled the NDBI image to be translated into a map of grassland cover with a meaningful spatial pattern. Assessed against visually interpreted results, grassland cover was mapped at an overall accuracy of 80%. In order for this method to generate satisfactory results, image pixel NDBI values have to be normalized so that they have the same standard deviation as that of the ground samples. This proposed method should be applicable to any grassland where grassland cover varies subtly at the pixel scale of the image used.