The organizing committee invites the submission of full papers for presentation at the EO4CUR 2026 workshop at ACM SIGSPATIAL 2026.

We welcome original research contributions addressing the use of Earth Observation data for climate adaptation and urban resilience, with a particular emphasis on big data analytics, machine learning, and scalable geospatial processing.

EO4CUR welcomes applied and theoretical contributions, position papers, demonstrations, and benchmarking studies on, but not limited to:

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-EO data infrastructure: multi-sensor fusion, atmospheric correction, pansharpening, cloud-native pipelines using STAC/COG/Zarr

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-Benchmarks and reproducibility: open pipelines, curated EO datasets, FAIR principles

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-Climate and urban risk: flood, wind, heat, wildfire mapping; exposure and vulnerability modeling; critical-infrastructure monitoring

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-Causal and spatial modeling: what-if scenarios, urban thermal-stress modeling, hazardous-material detection

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-Decision support: early-warning systems, EO-driven digital twins, evidence-based adaptation policy

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-Foundation models for EO

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-Demonstrations of EO/GIS toolchains