UrbanTree3D Dataset

The UrbanTree3D dataset consists of 152 individual urban trees, generated through the integration of airborne LiDAR data, field inventory records, and in-situ field verification. This multi-source approach ensures a high level of annotation reliability and spatial accuracy, making the dataset suitable for advanced machine learning and deep learning applications.

Following preprocessing and data cleaning procedures, six distinct urban tree species were retained, providing a representative diversity for classification tasks in complex urban environments.

The UrbanTree3D includes the following species:

• (0) Aesculus hippocastanum : 62 trees
• (1) Prunus serrulata : 12 trees
• (2) Pyrus calleryana ‘Chanticleer’ : 15 trees
• (3) Salix alba : 23 trees
• (4) Tilia platyphyllos : 25 trees
• (5) Tilia × europaea ‘Pallida’ : 15 trees

UrbanTree3D is designed to support a wide range of applications, including urban tree species classification, advanced 3D point cloud analysis, and the benchmarking of deep learning models applied to urban vegetation. It also serves as a valuable resource for research in urban ecology and smart city applications, enabling more accurate and data-driven management of urban green infrastructure.