This paper presents an unsuccessful attempt to identify different mangrove species from the DigitalGlobe's QuickBird high-resolution multispectral image data for a coastal estuary located in the north of South China Sea. A conventional supervised classification was conducted with 102 signatures trained for five cover classes, with 32 of the signatures being used to separate up to five mangrove species. The results indicated that spectral characteristics alone as provided by the QuickBird's four spectral bands were not sufficient for the discrimination among mangrove species, other information such as textual and structural characteristics of mangrove species would be needed to enhance the discrimination power. In addition, the confusion between upland forests and mangroves render a removal of uplands from the classification process. Finally, the shadow effect within the mangrove patches suggested the use of NDVI in the future classification attempts.