Accurate field-scale crop yield prediction is essential for sustainable agricultural management under increasing climate variability. Process-based crop growth models such as WOFOST provide a physically consistent framework for simulating crop development and biomass accumulation, yet their predictive performance is often constrained by uncertainties in parameterization, inputs, and canopy representation. To address these limitations, this study integrates satellite-derived biophysical parameters into WOFOST using an Ensemble Kalman Filter (EnKF) to improve canopy dynamics and yield estimation for green maize and winter barley in the Netherlands. Sentinel-2–retrieved Leaf Area Index (LAI), Canopy Chlorophyll Content (CCC), and Canopy Water Content (CWC) were individually assimilated at the parcel scale during the 2022 growing season. Model performance was validated against independent provincial statistics. Results show that LAI assimilation significantly enhanced model performance for maize, reducing the mean yield bias from -3.78 t ha⁻¹ (-27.6%) to -0.11 t ha⁻¹ (-0.81%) and lowering RMSE from 3.89 t ha⁻¹ to 0.99 t ha⁻¹. CCC and CWC contributed less due to their dependence on fixed biochemical coefficients but highlighted challenges and opportunities for incorporating physiological constraints. Sensitivity analyses emphasized the importance of observation density, timing, and uncertainty, with the greatest impact observed during canopy expansion and peak growth. Overall, this study demonstrates the potential of remote sensing data assimilation to enhance process-based yield prediction and provides a foundation for advancing operational crop monitoring under diverse agricultural conditions.

In order to improve the climate resilience and liveability of Curaçao’s Inner-City, various
interventions are proposed for Wilhelminaplein in Punda to mitigate the problem of heat stress, along with socioeconomic issues. This is done while keeping the problem of water scarcity in mind. Among various problem locations in the Inner-City, Wilhelminaplein was chosen as a development site because of its high potential and advantageous location. The main problems facing Wilhelminaplein are found to be extreme heat and lack of clear function, shade and maintenance.
Various possible solutions are proposed and discussed with experts, including a landscape architect and urban planner. Following this, the interventions are finalized and presented to various stakeholders, including representatives of relevant government agencies. Through a workshop, the stakeholders provided feedback on their preferred set of interventions.
The proposed interventions are subdivided into ’quick wins’, cool spots and additional interventions.
To quantify the effectiveness of the interventions, PET reductions of the proposed interventions are modelled using the modelling software RayMan. Along with the PET reduction, the initial cost, water usage, required level of maintenance and implementation time frame, are analysed for each proposed intervention.
To facilitate the practical implementation of the proposed interventions, an overview is given of which steps the relevant government agencies still need to take in terms of research, designs, and applying for permits.