This review is aimed at exploring the use of remote sensing technology with a focus on Unmanned Aerial Vehicles (UAVs) in monitoring and management of palm pests and diseases with a special focus on date palms. It highlights the most common sensor types, ranging from passive sensors such as RGB, multispectral, hyperspectral, and thermal as well as active sensors such as light detection and ranging (LiDAR), expounding on their unique functions and gains as far as the detection of pest infestation and disease symptoms is concerned. Indices derived from UAV multispectral and hyperspectral sensors are used to assess their usefulness in vegetation health monitoring and plant physiological changes. Other UAVs are equipped with thermal sensors to identify water stress and temperature anomalies associated with the presence of pests and diseases. Furthermore, the review discusses how LiDAR technology can be used to capture detailed 3D canopy structures as well as volume changes that may occur during the progressing stages of a date palm infection. Besides, the paper examines how machine learning algorithms have been incorporated into remote sensing technologies to ensure high accuracy levels in detecting diseases or pests. This paper aims to present a comprehensive outline for future research focusing on modern methodologies, technological improvements, and direction for the efficient application of UAV-based remote sensing in managing palm tree pests and diseases.

UAV photogrammetry plays an essential role in applications such as disaster management, food security, and mapping due to its adaptability, scalability, and accuracy in data collection. Consequently, the increasing popularity of the UAV photogrammetry domain has led to a growing demand for comprehensive education accessible through academic institutions. Meanwhile, the flexibility and freedom associated with online education have sparked significant demand for online learning programs. Different users actively seek online courses and materials to delve into the intricacies of UAV photogrammetry. However, the abundance of online resources in this area poses challenges in finding such reliable courses.To address this challenge, the ITC team from the UAV centre and EOS Department at the University of Twente investigated the current online education courses related to UAV Photogrammetry offered globally. They compiled an inventory of these courses, categorizing them according to different educational levels- introductory, intermediate, and advanced—to align with the needs of key photogrammetry user categories. The project also investigated the currently available UAV datasets and software packages supporting technical training and professional applications. Further details are available on the project website.Besides, the project gathers insights into gaps in UAV photogrammetry knowledge areas and UAV applications in geoscience by designing, distributing, and analysing a UAV Gap survey.