Earth Embeddings Reveal Diverse Urban Signals from Space
Conventional urban indicators derived from censuses, surveys, and administrative records are often costly, spatially inconsistent, and slow to update. Recent geospatial foundation models enable Earth embeddings, compact satellite image representations transferable across downstream tasks, but their utility for neighborhood-scale urban monitoring remains unclear. Here, we benchmark three Earth embedding families, AlphaEarth, Prithvi, and Clay, for urban signal prediction across six U.S. metropolitan areas from 2020 to 2023. Using a unified supervised-learning framework, we predict 14 neighborhood-level indicators spanning crime, income, health, and travel behavior, and evaluate performance...
| Authors | Wenjing Gong, Udbhav Srivastava, Yuchen Wang et al. |
|---|---|
| Primary category | cs.LG |
| Published | 3 April 2026 |
| Last updated at source | 3 April 2026 |
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