Developing and upscaling land use intensity metrics for Dutch production environments in Annual Crops and Grasslands​

Agricultural systems are undergoing increasing pressure to transition toward more sustainable and regenerative practices. A central challenge in this transition is the ability to quantify land use intensity (LUI) in a way that captures the complexity of agricultural management. Existing approaches often rely on simplified proxies, that fail to capture the multi-dimensional nature of LUI. This PhD project aims to develop a multi-level framework for assessing LUI from the field to the landscape scale. The framework will be developed through three main steps: (1) constructing an expert-validated LUI index using detailed management questionnaires; (2) testing the extent to which LUI dimensions can be predicted using multi-source remote sensing and explainable machine learning; and (3) embedding the resulting LUI index within its landscape context by analysing how LUI interacts with landscape structure to shape ecosystem functioning and service outcomes, including biodiversity, soil health and water quality. By integrating management data, remote sensing, and spatial modeling, this research addresses key gaps in the operationalization, observability and scalability of LUI. The resulting framework will provide spatially explicit, policy-relevant indicators to support the monitoring of agricultural systems and evaluate transitions toward regenerative practices. Ultimately, the project contributes to advancing data-driven approaches for sustainable lan management in agriculturally dominated landscapes.