A global downstream approach to mapping surface urban heat islands using open data and collaborative technology

This paper presents a fully automated, open-source workflow for mapping and analysing Surface Urban Heat Island Intensity (SUHII) in urban areas. The method integrates freely available Earth Observation datasets, including Landsat imagery and SRTM elevation data, and ensures generalizability across diverse landscapes by analysing homogeneous altitudinal zones. This avoids over- or underestimation of thermal anomalies due to elevation differences. The pipeline requires only a city name and a local folder path as inputs, producing standardized warm-season Land Surface Temperature and SUHII maps in GeoTIFF format with full metadata. Developed in modular R and Python environments, the code supports easy adaptation, dataset integration, and deployment in web or desktop applications. Designed to lower technical barriers, the platform merges technical and experiential knowledge through citizen participation, enabling non-experts to explore urban thermal anomalies and their social and health implications. This approach fosters equitable climate adaptation and environmental justice by making climate-relevant spatial data accessible and actionable for citizens, researchers, and decision-makers.