Mathematic descriptors for identifying plant species:A case study on urban landscape vegetation

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.