Earth Science in the Era of Foundation Models: How AlphaEarth is Reshaping Quantitative Geoscience

摘要

Since the beginning of the 21st century, advances in big data and artificial intelligence have driven a paradigm shift in the geosciences, moving the field from qualitative descriptions toward quantitative analysis, from observing phenomena to uncovering underlying mechanisms, from regional-scale investigations to global perspectives, and from experience-based inference toward data-and model-enabled intelligent prediction. AlphaEarth Foundations(AEF) is a next-generation geospatial intelligence platform that addresses these changes by introducing a unified 64-dimensional shared embedding space, enabling—for the first time—standardized representation and seamless integration of 12 distinct types of Earth observation data, including optical, radar, and lidar. This framework significantly improves data assimilation efficiency and resolves the persistent problem of “data silos” in geoscience research. AEF is helping redefine research methodologies and fostering breakthroughs, particularly in quantitative Earth system science. This paper systematically examines how AEF's innovative architecture—featuring multi-source data fusion, high-dimensional feature representation learning, and a scalable computational framework—facilitates intelligent, precise, and real-time data-driven geoscientific research. Using case studies from resource and environmental applications, we demonstrate AEF's broad potential and identify emerging innovation needs. Our findings show that AEF not only enhances the efficiency of solving traditional geoscientific problems but also stimulates novel research directions and methodological approaches.

关键词

large-scale models / artificial intelligence / mineral prospectivity mapping / AlphaEarth / knowledge graphs / deep and covered mineral exploration