Earth system modelling (ESM) is essential for understanding past, present and future Earth
processes. Deep learning (DL), with the data-driven strength of neural networks, has …

The past decade has witnessed the rapid development of geospatial artificial intelligence
(GeoAI) primarily due to the ground-breaking achievements in deep learning and machine …

Collaboration between artificial intelligence and Earth science communities for mutual benefit |
Nature Geoscience Skip to main content Thank you for visiting nature.com. You are using a …

Flood visualization plays a pivotal role in understanding and predicting flood disasters, as it
aids in the development of effective disaster mitigation measures and emergency response …

The unprecedented expansion of digital technologies has led to a rapid increase in the
development and application of 3D digital environments for landscape and urban planning …

This research discusses the potential and challenges of integrating Artificial Intelligence (AI)
in geography learning. By considering the fundamentals of AI and the role of geography in …

Despite a history of year-by-year reduction in road-crossing harm and fatality in the United
States, the trend reversed course in 2009 and road-crossing has grown more hazardous …

With the development of geographic simulation methods in recent decades, a great deal of
resources have accumulated to support their implementation. These resources can be …

Reservoir parameters are crucial indicators for reservoir evaluation and development and
provide insights into long-term reservoir behavior. The primary methods for evaluating these …

Geoscientific models have rapidly developed in recent decades as effective tools to
understand the past, perceive the present, and predict the future. However, with the …