STATE-OF-THE-ART IN UAV REMOTE SENSING SURVEY – FIRST INSIGHTS INTO APPLICATIONS OF UAV SENSING SYSTEMS

Our study showed that stress-related crop response to changing environmental conditions can be detected by monitoring crops using satellite images at the landscape level. This could be useful for farmers to identify when stresses occur. Our results also suggest that satellite imagery can be used to discover soil impacts on crop development at farm fields. The inclusion of soil properties in satellite image analyses could further improve the accuracy of the prediction of drought stress on crops.

We reviewed optical remote sensing time series (TS) studies for monitoring vegetation productivity across ecosystems. Methods were categorized into trend analysis, land surface phenology, and assimilation into statistical or dynamic vegetation models. Due to progress in machine learning, TS processing methods will diversify, while modelling strategies will advance towards holistic processing. We propose integrating methods into a digital twin to improve the understanding of vegetation dynamics.