Towards GeoAI Foundation Models: A Multimodal Learning Framework with Geospatial Intelligence
Abstract
Foundation models have transformed natural language processing and computer vision, yet integrating geospatial inductive biases remains an open frontier. This chapter outlines a comprehensive conceptual and architectural framework towards GeoAI Foundation Models. We synthesize key methodologies spanning multimodal self-supervised pre-training, spatial-temporal graph encoders, and vision-language architectures tailored for geographic and Earth observation domains.
Type
Publication
In Geography According to Foundation Models, SAGE Publications, pp. 28–50
Yunus Serhat Bıçakçı
Assistant Professor
Assistant Professor specializing in GeoAI, Multimodal Vision-Language Models, and Spatial Data Science.