Towards LLM Agents for Earth Observation
Chia Hsiang Kao ⋅ Wenting Zhao ⋅ Shreelekha Revankar ⋅ Samuel Speas ⋅ Snehal M Bhagat ⋅ Rajeev Datta ⋅ Cheng Perng Phoo ⋅ Utkarsh Mall ⋅ Carl Vondrick ⋅ Kavita Bala ⋅ Bharath Hariharan
2025 Spotlight
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Workshop: TerraBytes: Towards global datasets and models for Earth Observation
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Workshop: TerraBytes: Towards global datasets and models for Earth Observation
Abstract
Earth Observation (EO) provides critical planetary data for environmental monitoring, disaster management, climate science, and other scientific domains. Here we ask: Are AI agents ready for reliable Earth Observation? We introduce UnivEARTH, a benchmark of 140 yes/no questions from NASA Earth Observatory articles across 13 topics and 17 satellite sensors. Using Google Earth Engine API as a tool, LLM agents can only achieve an accuracy of 33% because the code fails to run over 58% of the time. Taken together, our findings identify significant challenges to be solved before AI agents can automate Earth observation and suggest paths forward.
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