“…Individual tree extraction using spectral and textural information derived from the optical data has been studied extensively over the past two decades [32,51,57,60]. However, despite the impressive developments in the algorithms for processing optical imagery as well as in the methods for incorporating spectral and contextual information for ITC detection/delineation, several factors still negatively affect tree detection performance, particularly in the urban context, including the complexity and heterogeneity of urban environments, the low spectral separability between tree crowns, and other types of understory vegetation (e.g., shrubs, grass), the large within-crown spectral variance in VHR imagery, the limited spatial resolution of satellite imageries with regard to the size of tree crowns, and the limitations for conducting fieldwork and providing ground reference datasets for the supervised ITC detection/delineation algorithms (particularly on private properties) [32,53,56,66,67].…”