S. Gokool

TL;DR: In this article , the authors evaluated the utility of multispectral UAV imagery using the random forest machine learning algorithm to estimate the chlorophyll content of maize through the various growth stages.

TL;DR: In this article, the authors used the satellite-based surface energy balance system (SEBS) model with stable isotope analysis to map and quantify the contribution of groundwater to transpiration (ETg), along the lower reaches of a perennial river system, in the semi-arid north-eastern region of South Africa.

TL;DR: In this paper, two infilling approaches, the K cact approach and a linear interpolation approach, were evaluated by comparing their respective values against in-situ ET measurements, as well as SEBS ET estimates derived using MODIS.

TL;DR: In this paper , the authors evaluated the utility of optical and thermal infrared UAV imagery, in combination with a random forest machine-learning algorithm, to estimate the maize foliar temperature and stomatal conductance as indicators of potential crop water stress and moisture content over the entire phenological cycle.

TL;DR: In this article, the state-of-the-art in ecosystem service modelling can be implemented to guide decision making with regards to investments in EI to improve the delivery of specific hydrological ecosystem services (HES) within the uMngeni catchment.