Dataset and methodological framework for land-use change scenario modelling in Uruguay using the Land Change Modeler

This article presents a spatial dataset and methodological workflow for simulating land-system dynamics in Uruguay using the Land Change Modeler implemented in TerrSet v.2020. The dataset combines harmonized land-cover maps for 2000, 2015, and a validation dataset for 2020 with explanatory variables, transition probability matrices, and scenario-based simulations developed through a multi-layer perceptron-Markov chain approach. A key feature of the dataset is the harmonization of heterogeneous national land-use datasets into a consistent modelling framework, combined with a transparent workflow for explanatory variable selection, transition modelling, and scenario parameterization. The dataset provides the final scenario outputs together with the transition probability matrices, conservation constraint and incentive layers, validation outputs, and the methodological workflow required to reproduce the analyses and adaptation of the workflow to other regions. Three land-use policy pathways were implemented: Business-as-Usual (BAU), Multifunctional Landscape (MFL), and Grassland Conservation (GC). The dataset includes high-resolution raster layers, conservation constraint and incentive maps, explanatory variable influence assessments, and model validation outputs supporting reproducible spatial analyses and territorial planning applications. These data complement the associated Land Use Policy article, Balancing Growth and Conservation: Land-Use Policy Scenarios for Uruguay's Grasslands [1], by providing the underlying spatial datasets, methodological details, and validation framework required for reproducibility and reuse. The resources facilitate further research on grassland conservation, agroecological transitions, and scenario-based environmental assessment.