3rd Place Winner in I-GUIDE's 2025-26 Spatial AI Challenge!

The GeoSocial Downscaling Model (GSDM), a Spatial AI framework, reconstructs fine-scale (~500 m) accessibility patterns from coarse human mobility data. Tested in São Paulo, GSDM uses a physics-guided U-Net architecture to downscale aggregated mobility flows while enforcing macro-micro consistency via physical constraints. It integrates national mobility metrics with socioeconomic and built-environment covariates, without relying on social media or behavioral traces. Validation includes aggregate consistency, distributional fidelity, and spatial error analysis. Outputs include high-resolution accessibility surfaces, containerized workflows, pre-trained models, and a Spatial AI Model Card with documentation and ethical guidance. All workflows are executed on the I-GUIDE Platform using Jetstream2 GPUs. GSDM provides actionable insights for resilience planning, environmental justice, and equitable service provision, addressing a critical gap in micro-scale urban accessibility modeling and directly advancing I-GUIDE’s mission of reproducible, spatially informed AI for social good.