Editorial for the special issue “Advances in object and activity detection in remote sensing imagery”

Advances in data collection and accessibility, such as unmanned aerial vehicle (UAV) technology, the availability of satellite imagery, and the increasing performance of deep learning models, have had significant impacts on solving various remote sensing problems and proposing new applications ranging from vegetation and wildlife monitoring to crowd monitoring. This Special Issue contains seven high-quality papers [1,2,3,4,5,6,7] approaching problems relating to object detection, semantic segmentation, and multi-modal data alignment. In terms of the methods utilized, it is not surprising that six of the seven papers on this issue involve the application of deep learning. The papers also attest to the powerful aspect of the field where researchers can collaborate and validate their work on open-source models and datasets.