What on Earth is AlphaEarth? Hierarchical structure and functional interpretability for global land cover
Ivan Felipe Benavides-Martinez, Justin Guthrie, Jhon Edwin Arias, Yeison Alberto Garces-Gomez, Angela Ines Guzman-Alvis, Cristiam Victoriano Portilla-Cabrera, Somnath Mondal, Andrew J. Allyn, Auroop R. Ganguly

TL;DR
This paper uncovers a hierarchical and functionally interpretable structure within AlphaEarth geospatial embeddings, showing that a small subset of dimensions suffices for accurate land cover classification, thus enabling more efficient use.
Contribution
It introduces a novel interpretability framework revealing the hierarchical functional organization of AlphaEarth embeddings, guiding dimension selection for land cover classification.
Findings
Embedding dimensions show consistent functional roles.
High classification accuracy with only 2-12 dimensions.
Embeddings exhibit substantial redundancy.
Abstract
Geospatial foundation models generate high-dimensional embeddings that achieve strong predictive performance, yet their internal organization remains obscure, limiting their scientific use. Recent interpretability studies relate Google AlphaEarth Foundations (GAEF) embeddings to continuous environmental variables, but it is still unclear whether the embedding space exhibits a functional or hierarchical organization, in which some dimensions act as specialized representations while others encode shared or broader geospatial structure. In this work, we propose a functional interpretability framework that reverse-engineers the role of embedding dimensions by characterizing their contribution to land cover structure from observed classification behavior. The approach combines large-scale experimentation with a structural analysis of embedding-class relationships based on feature importance…
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Taxonomy
TopicsRemote Sensing in Agriculture · Geographic Information Systems Studies · Land Use and Ecosystem Services
