Geospatial AI: Systems, Model, Methods, and Applications

Dear Colleagues,

Geospatial artificial intelligence (GeoAI) is an emerging interdisciplinary field that integrates geospatial data analysis with artificial intelligence (AI) to derive meaningful insights from diverse sources such as satellite imagery, geographic information systems (GIS), and location-based data. By leveraging advanced AI algorithms, GeoAI can uncover patterns, predict trends, and support data-driven decision-making across a wide range of domains. This integration enhances our understanding of spatial relationships and dynamics, enabling more effective responses to complex global challenges.

In today’s world, pressing issues such as climate change, environmental degradation, resource depletion, and rapid urbanization demand innovative solutions. These challenges are deeply interconnected and require advanced, data-intensive approaches. AI’s capacity to process and analyze massive volumes of geospatial data both efficiently and accurately makes it a powerful enabler for addressing these concerns. Through GeoAI, researchers and practitioners can inform policy, improve strategies, and contribute to a more sustainable and resilient future.

This Topics seeks to bring together original research and comprehensive reviews on the latest advances, applications, and challenges in GeoAI. We invite submissions of both review articles and original research papers that explore innovative methodologies, cutting-edge technologies, and novel applications in themes including (but not limited to) the following:

• GeoAI for Smart Cities and Urban Development: Research on how GeoAI can optimize urban planning and enhance smart city initiatives.
• GeoAI applications for Environmental Monitoring: Research on using GeoAI to monitor and mitigate environmental changes, such as climate change, land cover change, water, and wetland management.
• GeoAI for Disaster Management: Research on the role of GeoAI in disaster risk reduction, early warning systems, and post-disaster recovery efforts.
• Intelligent Systems for Transportation and Mobility: Research on using GeoAI to monitor, analyse, and optimize transportation networks, improve traffic management, and enhance mobility solutions.
• GeoAI for Public Health: Research on the use of GeoAI in disease surveillance, health resource allocation, and understanding the spatial dynamics of public health issues.
• Technological Advances in GeoAI: Research on new algorithms, data fusion techniques, and computational methods that enhance the capabilities of GeoAI.

We look forward to receiving your contributions and creating a comprehensive collection of articles that show the potential of GeoAI to drive sustainable development and improve our understanding of the world around us.

Dr. Lirong Yin
Dr. Shan Liu
Dr. Kenan Li
Topic Editors