I’m happy to have taught and coordinated another session of the Remote Sensing for Plant Health course for the EU Better Training for Safer Food initiative. This year the course featured a stronger UAV (drone) focus, with extensive hands-on demonstrations of aerial sampling of plant material, automated missions and hyper-spectral hardware setups.
In addition, the basic theoretical background of remote sensing was provided including an understanding of the physics of the electromagnetic spectrum in the visible and near-infrared and its relation to vegetation indices.
This is a contribution of by Benjamin William Barrett who is a PhD student at the Health and Biomedical Informatics track of Northwestern University Feinberg School of Medicine’s Health Sciences Integrated PhD (HSIP) program. He was geocoding healthcare encounters within a singular, privacy-preserving, environment via containerization and Docker but struggled to get the {appeears} R package authentication working.
I provided some guidance, mainly the use of a pre-created or spoofed keying, to avoid any user interaction in such a non-interactive setup.
A new paper summarizes methods, data sources and proximal remote applications. It gives guidance on best practices and valuable directions for future research.