most citedEarth AI: Unlocking Geospatial Insights with Foundation Models and Cross-Modal Reasoning

3 citations · 3 across the 4 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Google Earth AI Geospatial Reasoning Agent: Capabilities and a Systematic Evaluation

Noam Slonim, Aviv Slobodkin, Gil Fidel +34

Google Earth AI is a family of geospatial AI models, together with an agent that orchestrates them. We present this agent, Google Earth AI's Geospatial Reasoning agent (GRA), a Gem…

cs.LG2026

Planetary Geospatial Foundation Models: A New Paradigm for Global Public Health

Arbaaz Muslim, Aviv Slobodkin, Katherine Wheeler-Martin +35

The efficacy of traditional disease prediction is limited by spatial gaps and temporal lags, which impact the timing and targets of resource deployments. Outbreaks escalate undetec…

cs.AI2026

Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embeddings

Evelyn Ma, Rama Kumar Pasumarthi, Kishwar Shafin +26

Addressing critical global challenges, from food security and disaster risk to disease outbreaks and socio-economic vulnerability, demands high-fidelity geospatial modeling. Howeve…

cs.CL2026

Enabling Intrinsic Reasoning over Dense Geospatial Embeddings with DFR-Gemma

Xuechen Zhang, Aviv Slobodkin, Joydeep Paul +4

Representation learning for geospatial and spatio-temporal data plays a critical role in enabling general-purpose geospatial intelligence. Recent geospatial foundation models, such…

cs.LG2025

Application and Validation of Geospatial Foundation Model Data for the Prediction of Health Facility Programmatic Outputs -- A Case Study in Malawi

Lynn Metz, Rachel Haggard, Michael Moszczynski +14

The reliability of routine health data in low and middle-income countries (LMICs) is often constrained by reporting delays and incomplete coverage, necessitating the exploration of…

cs.AI2025★ 3 cited

Earth AI: Unlocking Geospatial Insights with Foundation Models and Cross-Modal Reasoning

Aaron Bell, Amit Aides, Amr Helmy +57

Geospatial data offers immense potential for understanding our planet. However, the sheer volume and diversity of this data along with its varied resolutions, timescales, and spars…

physics.geo-ph2025

Estimating high-resolution albedo for urban applications

David Fork, Elizabeth Jane Wesley, Salil Banerjee +18

Implementation of cool roofs is a high-impact pathway for mitigating heat at both global and city scales. However, while albedo estimates derived from Sentinel-2 are free and globa…