From global models to local indicators: Assessing land-use transitions and conflicts

This study proposes a spatial downscaling framework to generate fine-resolution (500 m) future land-use projections for Taiwan using LUH2-based datasets under the Shared Socioeconomic Pathways (SSPs). The framework integrates historical transition probabilities, national land-use survey data, and scenario-specific spatial allocation rules to bridge the resolution gap between global models and local policy needs. To evaluate spatial and temporal consistency, short-term land-use transition probabilities were derived from national surveys and used to identify conflict zones where long-term projections diverge from recent trends. To facilitate local implementation, four indicators, including early onset, concentration, variability, and pace of change, were developed to assess scenario-driven land-use dynamics across 19 subnational divisions of Taiwan. Results revealed that SSP1–1.9, while aligned with sustainability goals, involves abrupt land-use shifts that may challenge local implementation, whereas SSP2–4.5 offers more gradual transitions but greater cumulative impacts. Furthermore, following the same spatial downscaling procedure with spaceborne images of 6-meters resolution, site-specific land-use map was projected. It was demonstrated that this framework provides a transferable method for embedding global scenarios into local planning contexts and offers practical insights for risk detection, land-use prioritization, and adaptive governance under long-term development pathways.