GeoAI & Spatial Statistics
Explainable machine learning, spatial cross-validation, data leakage, spatial econometrics and uncertainty quantification.
Diamond Open Access · Peer-reviewed · International
A peer-reviewed home for research at the intersection of spatial data science, explainable machine learning, urban remote sensing and environmental justice.
Aims & Scope
We publish original articles, reviews and methodological innovations that connect rigorous spatial methods with real urban problems.
Explainable machine learning, spatial cross-validation, data leakage, spatial econometrics and uncertainty quantification.
Earth observation, urban heat islands, microclimate, intra-urban air quality and blue-green infrastructure.
15-minute city, accessibility, walkability, transit connectivity and open geospatial data quality.
Socio-spatial inequity, exposure to hazards, gentrification and evidence-based, climate-resilient planning.
Diamond open access: no APCs, no submission fees and no paywalls, ever.
Editorial screening followed by double-blind review from at least two independent experts.
Published under CC BY 4.0. Authors keep their copyright and publishing rights.