In today’s rapidly evolving landscape, the convergence of sensor networks, advanced big data acquisition, and cutting-edge data analysis technologies has given rise to the value of spatiotemporal data applications. Spatiotemporal data encompass a wide array of information, ranging from environmental variables to human behaviors and urban dynamics. Accurately modelling and predicting the evolving trends of physical world and social environment with these spatiotemporal datasets holds immense significance, particularly for enabling well-informed decision-making and enhancing the capacity of governmental management.
The field of Geographic Artificial Intelligence (GeoAI) has emerged as a transformative force in making sense of this wealth of data. By combining geographical information, artificial intelligence, and spatiotemporal data analysis, GeoAI provides the tools and techniques needed to extract valuable insights, make forecasts, and derive actionable intelligence from complex geospatial and temporal datasets.
In this context, this special issue aims to serve as a platform for exploring and showcasing the latest advances in GeoAI and its applications in enhancing spatiotemporal modelling and prediction capabilities across a wide spectrum of application domains. By harnessing the synergy of artificial intelligence, geographical knowledge graph and data analytics, this special issue strives to address the burgeoning demand for enabling robust even interpretable representation, and getting deep insights of the changing trends of our world.
Topics of interest to this issue include, but are not limited to:
- Explainable AI for spatiotemporal modelling of geospatial data
- Knowledge-guided spatiotemporal prediction technologies
- Uncertainty quantification on spatiotemporal AI models
- AI model generalizability across spatiotemporal heterogeneity
- Large models and foundation models in geo-related domains
- Spatiotemporal modelling and prediction applications in intelligent transportation systems, environmental and natural resource management, natural disaster prevention and mitigation, public security, and emergency response, among others.
