Advances in Geoinformatics and AI for Dynamic Earth System Monitoring

Geoinformatics has become a transformative field in Earth science and GIScience, fueled by rapid advancements in Earth observation, remote sensing, GIS technologies, and big data analytics. Despite these technological leaps, researchers still face significant barriers when working with increasingly vast, complex, and heterogeneous geospatial datasets. These challenges are especially pronounced in efforts to monitor and predict dynamic Earth system processes and human-environment interactions. Recent studies have demonstrated that integrating machine learning, deep learning, and advanced spatio-temporal analytics into geoinformatics can substantially enhance our ability to interpret environmental trends, map hazards, and understand urban and social dynamics. However, there is an ongoing debate about the most effective models, optimal data fusion techniques, and evaluation metrics, as well as a need for real-world validation and effective operationalization of these approaches.This Research Topic aims to foster interdisciplinary advances by promoting the integration of geoinformatics, artificial intelligence, and GIScience in addressing urgent challenges in Earth science and environmental management. Central objectives include the development of robust, scalable techniques that enable accurate monitoring, forecasting, and assessment of natural and anthropogenic hazards, as well as long-term environmental changes. The goal is to bridge the gap between rapid technological innovation and actionable geoscientific insights that inform decision-making. Such synergy could further improve the effectiveness of AI infrastructure development, including water-energy efficiency in data centers and semiconductor manufacturing. Contributors are encouraged to explore novel theories, methods, and real-world applications, particularly approaches that address the limitations of current analytical workflows or confront previously intractable geospatial problems.The scope of this Research Topic includes innovative methods and applications at the intersection of geoinformatics, AI, and Earth science, while focusing on real-world challenges and scalable solutions. Submissions may address advances in theory, methodology, or application but should emphasize the integration of diverse data sources and analytics.We welcome articles on, but not limited to, the following themes:• AI and machine learning methods for interpreting Earth observation and geospatial big data.• Remote sensing and geoinformatics applications in natural hazard detection and environmental change monitoring.• Data-driven integration of climatic, hydrological, and social variables for predictive modelling and early-warning systems.• Groundwater, land-subsidence, and hydro-environmental assessment using advanced analytics.• Automated extraction and classification of geospatial features from multi-source imagery and sensor networks.• Spatio-temporal modelling, satellite time series analysis, and deep learning for dynamic Earth system understanding.• Geoinformatics–AI Synergies for Effective AI Factory Development Topic editors: Hwa-Lung Yu, HoneJay Chu, Yu-Feng Forrest Lin, Ping-Yu Chang, Alejandro García-Gil Source: https://www.frontiersin.org/research-topics/76550/advances-in-geoinformatics-and-ai-for-dynamic-earth-system-monitoring