Editorial: AI processing of UAV acquired images for pattern monitoring in natural and urban environments

Yago Diez Donoso, Nuno Gracias, Mariano Cabezas, Carsten Juergens, Maximo Larry Lopez Caceres

Abstract: Remote sensing Data, and especially data collected by Unmanned Air Vehicles (UAVs), is currently being used in an increasing number of research areas. These data, together with the new image analysis possibilities that Deep Learning provides, are pushing forward significant advances in research areas as diverse as Traffic Surveillance \cite{bozcan2020air}, Forestry \citep{reviemRemSens}, Agriculture \cite{KP17} or Cultural Heritage inspection \cite{Themistocleous2020}. Our aim in this research topic is to explore how the combination of remote sensing data and AI (and very particularly Deep Learning) can be exploited to further widen their field of application, and to obtain better results in existing applications.We believe that the four articles gathered in this research topic fulfill our goals and provide a very interesting perspective on how much this research area has already advanced in the last few years and how much further it can go. From novel takes on existing technology such as microdrones being used to obtain 3D-reconstructions of industrial buildings, to developments on the way data is collected (for example semantic segmentation) to influence future data collection missions, and, finally, to results in established application areas, such as SLAM for agriculture or underwater natural environment monitoring, that transcend UAV data collection but use the same types of information and analysis approaches. We encourage the readers of this research topic to carefu...