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https://github.com/opendatalab/earth-agent


https://github.com/opendatalab/earth-agent

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 Image Alt Text Earth-Agent: Unlocking the Full Landscape of Earth Observation with Agents

 






[Peilin Feng](https://peilin-ff.github.io/)1*, 

[Zhutao Lv](https://scholar.google.com/citations?user=aGJ7T4YAAAAJ&hl=zh-CN&oi=ao)1,2*,

[Junyan Ye](https://yejy53.github.io/)1,2, 

[Xiaolei Wang](https://scholar.google.com/citations?user=8wbcPvcAAAAJ&hl=zh-CN&oi=sra)2, 


[Xinjie Huo](https://scholar.google.com/citations?user=0osg1poAAAAJ&hl=zh-CN&oi=ao)2, 

[Jinhua Yu](https://scholar.google.com/citations?user=radsfXwAAAAJ&hl=zh-CN&oi=ao)2, 

[Wanghan Xu](https://scholar.google.com/citations?user=lmCL5xQAAAAJ&hl=zh-CN&oi=ao)1, 

[Wenlong Zhang](https://wenlongzhang0517.github.io/)1, 

[Lei Bai](http://leibai.site/)1, 

[Conghui He](https://conghui.github.io/)1, 

[Weijia Li](https://liweijia.github.io/)1,2†



1Shanghai Artificial Intelligence Laboratory, 2Sun Yat-sen University






[![arXiv](https://img.shields.io/badge/Arxiv-2503.14905-AD1C18.svg?logo=arXiv)](https://arxiv.org/pdf/2509.23141) 

[![](https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2Fopendatalab%2FFakeVLM&count_bg=%23C25AE6&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=Visitor&edge_flat=false)](https://hits.seeyoufarm.com)

[![Dataset](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Dataset-yellow)](https://huggingface.co/datasets/Sssunset/Earth-Bench)






This repository contains the evaluation framework for Earth Agent: Unlocking the Full Landscape of Earth Observation with Agents



## 📰 News 

- **[2025.10.17]**: 🤗 We are excited to release the Earth-Bench dataset. Check out [on huggingface](https://huggingface.co/datasets/Sssunset/Earth-Bench).

- **[2025.9.27]**: 🔥 We have released **Earth-Agent: Unlocking the Full Landscape of Earth Observation with Agents**. Check out the [paper](https://arxiv.org/pdf/2509.23141). We present Earth-Agent and Earth-Bench.



## Project Earth-Agent Overview





framework




We introduce Earth-Agent, an EO agent framework cast as a **ReAct-style** Partially Observable Markov Decision Process (POMDP). The LLM serves as the policy, iterating a loop of tool calling, memory update, deliberation, and action to solve tasks conditioned on goal and interaction history. Besides, Earth-Agent integrates **104** specialized tools across five functional kits, i.e. *Index*, *Inversion*, *Perception*, *Analysis*, and *Statistics*, spanning perceptual and spectral analysis. To evaluate both outcomes and reasoning, we adopt a **dual-level protocol**: *end-to-end* assessment of final Accuracy and trajectory Efficiency, and *step-by-step* checks of Tool-Any-Order, Tool-In-Order, Tool-Exact-Match, and Parameter Accuracy to characterize the completeness and fidelity of reasoning trajectories.



##  Contributions



- We propose Earth-Agent, a revolutionary paradigm shift from traditional MLLMs to agentic EO analysis, unifying RGB and spectral EO data within an MCP-based tool ecosystem

- In order to comprehensivly evaluate Earth-Agent, we propose Earth-Bench, which covers *Spectrum*, *Products* and *RGB* modality for scientific workflows requring tool interaction,

- Earth-Agent substantially outperforms general agents and surpasses remote sensing MLLMs on remote sensing benchmarks, demonstrating both effectiveness and potential for advancing EO research



## 📦 Data Preparation



### 1. Download Dataset from Hugging Face



Download the benchmark dataset from Hugging Face:



```bash

# Install huggingface-hub if not already installed

pip install huggingface-hub



# Download the dataset

huggingface-cli download Sssunset/Earth-Bench --local-dir ./benchmark/data --repo-type dataset

``` -->