Explore a comprehensive dataset featuring over 14000 labelled urban tree canopies in images from across the globe, specifically curated for advancing tree detection methodologies. The dataset comprises image tiles in both .tif, .jpg and .png formats, following the Pascal VOC and YOLO standards. Additionally, we included a .csv summary file with all annotations. To enhance usability, labels are provided in three formats: .xml, and .txt. The RGB tiles, utilized in this dataset, are openly accessible. The dataset's creation methodology is thoroughly documented in the research paper titled "Implementing Deep Learning Algorithms for Urban Tree Detection and Geolocation with High-Resolution Aerial, Satellite, and Ground-Level Images" by Velasquez-Camacho et al. (2023).