Rapid urbanization is intensifying heat-related challenges in global cities, with significant impacts on human health, energy demand, urban infrastructure systems, and long-term urban sustainability. This session emphasizes the critical role of geospatial data including remote sensing, numerical modeling, in-situ measurements, spatial statistics, and socio-economic datasets in advancing the characterization, monitoring, and mitigation of urban heat.
We invite contributions from geospatial science, urban climatology, environmental science, data science, artificial intelligence, and urban studies. The session seeks to highlight innovative approaches that use geospatial data and analytics to quantify urban heat dynamics, evaluate environmental and societal impacts, and support strategies for resilience and sustainability in cities.
Topics of interest include (but are not limited to):
1. AI based methods to monitor, model, and predict urban heat patterns,
2. Geospatial approaches for monitoring and mitigating the urban heat island (UHI) effect,
3. Integrated analysis of urban heat with air quality, health, energy use, and socio-economic factors,
4. Spatial modeling of cooling demand, carbon emissions, and resource efficiency under heat stress,
5. Geospatial analytics for evaluating green infrastructure and nature-based cooling solutions,
6. Climate resilience and adaptation strategies centered on heat-risk reduction,
7. Integration of multi-source datasets (satellite, airborne, in-situ, and socio-economic) for comprehensive assessments of urban heat impacts and responses.
We particularly encourage discussions on the challenges and opportunities of combining advanced geospatial analytics with AI to deliver deep insights into urban climate, resilience pathways, and sustainable planning strategies.