AI RESEARCH
No One Knows the State of the Art in Geospatial Foundation Models
arXiv CS.CV
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ArXi:2605.12678v1 Announce Type: new Geospatial foundation models (GFMs) have been proposed as generalizable backbones for disaster response, land-cover mapping, food-security monitoring, and other high-stakes Earth-observation tasks. Yet the published work about these models does not give reviewers or users enough information to tell which model fits a given task. We argue that nobody knows what the current state of the art is in geospatial foundation models. The methods may be useful, but the GFM literature does not standardize evaluations.