 This paper provides a comprehensive overview of recent advances in the field of automatic tree classification and segmentation using unmanned aerial vehicles. It summarizes the most relevant studies published between 2013 and 2023 focusing on the use of different sensors and data structures as well as the application of various machine learning algorithms for the purpose of tree identification and segmentation. The paper also discusses the latest trends in the field such as the use of multi-sensor data fusion, 3D information, and artificial intelligence techniques. This article was authored by Babic Chara, Alexandra Mutunhoe, and Carlos Vigas.