Remote sensing and GeoAI innovations for understanding Surface Urban Heat Island patterns and climate impacts

Urban climate research is an evolving field that examines the ways in which cities respond to environmental and climatic pressures, particularly urban heating. One of the most prominent phenomena, the Surface Urban Heat Island (SUHI) effect, describes the spatial variation in land surface temperature (LST) between urban and adjacent rural areas. SUHI arises from reduced vegetation cover, extensive impervious surfaces, urban geometry, and anthropogenic heat emissions. Escalating urbanization and global climate change have intensified this effect, leading to urban environments that are hotter and less thermally balanced. Such changes influence not only local microclimates but also air quality, energy consumption, and public health. In recent years, remote sensing has become a principal method for quantifying these dynamics by enabling consistent, synoptic, and repeated observations across temporal and spatial scales. At the same time, advances in GeoAI and geospatial analytics offer powerful new tools for handling the growing volume and complexity of geospatial data.



Despite these advances, challenges persist in harmonizing heterogeneous data, improving the spatial and spectral characterization of SUHI, and translating insights into actionable strategies for urban sustainability. This Research Topic aims to promote advances in integrating remote sensing and GeoAI approaches to enhance the understanding, assessment, and prediction of SUHI dynamics. It seeks to curate high-quality research that deepens scientific knowledge on urban thermal processes through multi-source data integration, advanced modelling, and data-driven interpretation. The overarching goal is to demonstrate how geospatial technologies can improve analytical precision, scalability, and interpretability in assessing urban heat heterogeneity across different geographic and climatic contexts. Through this collaborative initiative, we aim to bridge traditional geospatial analysis with emerging computational innovations and to foster dialogue across the fields of geoinformatics, environmental science, and urban planning.



This Research Topic focuses on remote sensing and GeoAI-based techniques for improved SUHI analysis and climate-related applications. To gather further insights into how geoinformation can inform climate-resilient urban planning and design strategies, we welcome contributions addressing, but not limited to, the following themes:



• Surface Urban Heat Island (SUHI) analysis using geoinformation and remote sensing data

• Retrieval and modelling of Land Surface Temperature (LST) from satellite (e.g., Landsat, MODIS, Sentinel) and UAV platforms

• Extraction of biophysical and environmental variables (NDVI, albedo, emissivity, surface moisture) through remote sensing

• GIS-based spatial analysis of urban thermal environments

• Integration of multisource geoinformation (LiDAR, land cover, urban morphology, vegetation indices) for SUHI modelling

• Application of GeoAI (machine learning and deep learning) for SUHI prediction, classification, and interpretation

• Multi-temporal, multi-scale, and cross-city comparative studies of urban heat phenomena

• Urban morphology–climate interactions derived from geoinformation and Earth Observation data

• Methodological innovations improving accuracy, interpretability, and scalability of SUHI assessment

• Interdisciplinary approaches linking geoinformatics, environmental science, and urban planning



Appendix – Accepted Article Types: Original Research, Methods, Review, Systematic Review, Mini Review, Data Report, Technology and Code, Perspective, Policy and Practice Review, Brief Research Report, Hypothesis and Theory, Opinion, Policy Brief.