###### Abstract  
Unmanned Aerial Vehicles (UAVs) have transformed the process of data collection and analysis in a variety of research disciplines, delivering unparalleled adaptability and efficacy. This paper presents a thorough examination of UAV datasets, emphasizing their wide range of applications and progress. UAV datasets consist of various types of data, such as satellite imagery, images captured by drones, and videos. These datasets can be categorized as either unimodal or multimodal, offering a wide range of detailed and comprehensive information. These datasets play a crucial role in disaster damage assessment, aerial surveillance, object recognition, and tracking. They facilitate the development of sophisticated models for tasks like semantic segmentation, pose estimation, vehicle re-identification, and gesture recognition. By leveraging UAV datasets, researchers can significantly enhance the capabilities of computer vision models, thereby advancing technology and improving our understanding of complex, dynamic environments from an aerial perspective. This review aims to encapsulate the multifaceted utility of UAV datasets, emphasizing their pivotal role in driving innovation and practical applications in multiple domains. U  
12 December 202412  
A significant application of UAV datasets is in aerial surveillance, which facilitates advanced research by the convergence of computer vision, robotics, and surveillance. The datasets facilitate event recognition in aerial videos, contributing to the monitoring of urban environments and traffic systems. The application of pre-trained models and transfer learning techniques enhances the effectiveness of UAV datasets, facilitating the swift implementation of advanced models for event recognition and tracking. UAV datasets improve object recognition in urban surveillance by offering extensive top-down and side views. This enables tasks including categorization, verification, object detection, and tracking of individuals and vehicles. UAV datasets play a critical role in the understanding and management of forest ecosystems by facilitating the segmentation of individual trees, an essential aspect of sustainable forest management. The versatility of UAV datasets encompasses multiple domains, such as the development of speech recognition systems for UAV control through video capture and object tracking in low-light conditions, which is crucial for nighttime surveillance operations. Innovative UAV designs, including bionic drones with flapping wings, have resulted in specialized video datasets utilized for single object tracking (SOT) [2]. This illustrates the extensive scope and potential of UAV datasets in improving real-time object tracking across diverse lighting conditions. UAV datasets serve as a fundamental resource for advanced research and practical applications in various fields. This review examines the specific applications and advantages of these datasets, emphasizing their contribution to technological advancement and enhancing our comprehension of complex, dynamic environments from an aerial viewpoint. The subsequent sections provide a comprehensive exposition of the contributions made by our study, which can be stated as follows:  
* Our study is driven by the increasing importance of UAV datasets in several research domains such as object detection, traffic monitoring, action identification, surveillance in low-light conditions, single object tracking, and forest segmentation utilizing point cloud or LiDAR point process modeling. Through an in-depth analysis of current datasets, their uses, and prospects, this paper intends to provide valuable insights that will assist researchers in harnessing these resources for creative solutions. Furthermore, they will acquire knowledge of existing constraints and prospective opportunities, enhancing their research endeavors. * We conduct an extensive analysis of a dataset consisting of 15 UAVs, showcasing its diverse applications in research.