Digital technologies are valuable tools that may help farmers improve efficiency and make better decisions. Remote sensing has been a key source of data from the early days of digital agriculture and has been linked to crop mapping, biophysical variables, yield forecasting, and prescriptive analytics required to monitor crop growth and agricultural output from the field scale to the global scale. The remote sensing sector has never been more capable of helping deliver on the promises of digital agriculture, thanks to recent developments in machine learning and artificial intelligence. But there are some problems and limitations that need to be fixed before these technologies can be used effectively and agriculture is digitally transformed on a large scale. These include accuracy, interoperability, data storage, computational capacity, and farmers’ reluctance to use them. The seminar will focus on two case studies: retrieval of crop biophysical parameters from UAV hyperspectral imagery and fruit detection using high-resolution UAV RGB imagery.