Characterizing AlphaEarth Embedding Geometry for Agentic Environmental Reasoning
Earth observation foundation models encode land surface information into dense embedding vectors, yet the geometric structure of these representations and its implications for downstream reasoning remain underexplored. We characterize the manifold geometry of Google AlphaEarth's 64-dimensional embeddings across 12.1 million Continental United States samples (2017--2023) and develop an agentic system that leverages this geometric understanding for environmental reasoning. The manifold is non-Eucl
Record details
Published: 20 April 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy · Environment
Retrieved: 14 July 2026
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ethics.ai (20 April 2026), “Characterizing AlphaEarth Embedding Geometry for Agentic Environmental Reasoning,” evidence record 5587, https://ethics.ai/record/5587 (originally published by arXiv).
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