Remote Sensing of Maize Physiological and Nutrient Dynamics in Response to Fall Armyworm Infestation

Water hyacinth (WHY) are one of the most costly aquatic invasive species. Regular monitoring of WHY would the management of infested waterboddies. We present an algorithm to derive daily maps of WHY from satellites, featuring an interpolation scheme, which led to 55% more daily WHY maps of Hartbeespoortdam Reservoir. The algorithm is light-weight and can be run on a cloud-computing platform. This allows applications in (sub-)tropical regions with limited access to computing power and/or funding.

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.