Mapping urban tree coverage using object-oriented image analysis method: A case study

This research proposed an object-oriented method to obtain the distribution of tree coverage in urban environment using 0.6 m aerial multi-spectral images. With the support of eCognition Software, the whole tree coverage mapping process included the following steps. Firstly, selecting a set of appropriate parameters by trial and error process to obtain an optimal segmentation result for tree coverage. Then, a two-level class hierarchy was constructed combining the Nearest-Neighbor Classifier and the Fuzzy logic classifier. After classification, we created two abstract classes (tree and non-tree) and selected Error Matrix Based on Samples to perform accuracy assessment for tree coverage mapping. The result of accuracy assessment showed that the proposed method had produced 96.4% overall accuracy and 92.6% KIA. Finally, we calculated the tree coverage rate based on the statistical result of sum area of tree coverage classification.