With the availability of high-resolution satellite data, much research has been focused on the automatic detection and classi cation of individual tree crowns. Most of these studies were applied to temperate climates of the northern hemisphere, especially for forests of coniferous. Very few studies have been applied to the detection of trees in the tropical regions, least of all in the urban environment. Urban trees play a major role in maintaining or even improving the quality of life in cities by their contribution to the quality of the air, by absorbing rain water, by refreshing the air through transpiration and providing shadow. In this study we explored the potential of high-resolution WorldView-2 satellite data for the identi cation of urban individual tree crowns in the city of Belo Horizonte, Minas Gerais, Brazil, through an object-oriented approach. Irrelevant areas were masked (e.g. buildings, asphalt, shadows, exposed soil) using a threshold of NDVI. Three di erent approaches were tested to isolate and delineate individual tree crowns: region growing, watershed and template matching. For the rst two approaches several parameters were tested to nd the best result for the isolation of the individual tree crowns. An in-house program has been developed for template matching using a set of seven di erent templates of di erent species. A set of 300 individual tree crowns were visually interpreted in the WorldView-2 image to serve as validation and to compare the performance of the three di erent approaches. Then, the comparison was performed between the visual interpretation and the results of each approach by calculating the di erence between the areas as a ratio of the validated area. Our results show that the region growing approach provided the best results, with an accuracy of over 80%.