This manuscript has the merits of providing a useful means to identify plant species of urban landscape vegetation from high-resolution remote sensing images.The study designed and selectively tested an array of quantitative descriptors calculated using spectral

textural

and shape characteristics of image objects.These descriptors

theoretically independent of image types and acquisition environment

may significantly improve the capacity of machine learning and discrimination of some classifiers.The demo cases indicated that with a combination of four such descriptors to identify plant species

the error rate is no more than 5.8% while comparing 25.9% with the conventional spectrum-based approach.