The transition to renewable energy depends on reliable resource assessment and sustainable planning across diverse geographical and environmental settings. Geospatial data, advanced modelling and artificial intelligence offer valuable tools to integrate different data sources, assess resource potential, address uncertainty and support informed decision-making. Combining geological, geophysical, meteorological, hydrogeological and environmental data with satellite imagery, terrain models and operational records can improve both resource assessment and spatial planning.
This session welcomes contributions on geospatial data, GIS, remote sensing and modelling for geothermal, solar, wind and hydropower. Topics include resource mapping, multi-source data integration, spatial suitability analysis, environmental and numerical modelling, data interoperability, uncertainty assessment and the use of AI and machine learning for spatial prediction and automated interpretation.
We also welcome contributions on the use of geospatial information in municipal and regional planning, site selection, land-use assessment and energy infrastructure development. Particular interest lies in approaches that connect spatial data and physical models with practical planning and decision-making, including monitoring, forecasting and operational optimization.
Open datasets, reproducible workflows and open-source tools are encouraged, as are studies assessing model performance and transferability across regions and renewable energy technologies. The session aims to bring together geoscientists, geospatial specialists, planners, engineers and energy researchers to advance the use of geospatial data and digital technologies for renewable energy assessment, planning and sustainable development.