arXiv cs.AI· Haoran Zhang, Huizhen Sun, Hanbin Wen, Jie Leng, Jiaxin Zhu, Zhaohua Sun·· 10 小时前AI 评分42
EarthRecord：用多模态智能体从四十年卫星影像中分析土地变化
EarthRecord: From Pixels to Land Change with Multimodal Agents over Four Decades of Satellite Imagery
AI 导读
EarthRecord 是一个基于 56 个站点原始卫星影像档案的基准，涵盖四十年 Landsat、MODIS、VIIRS 和 Sentinel-2 数据，云掩膜与跨传感器协调均交由智能体完成，包含十类分析任务共 238 个土地变化问题。对十二个多模态智能体的评测显示，领先智能体能端到端完成多数分析，但在需要从影像映射答案时表现不佳；当某一卫星数据被篡改时，一半正确答案会跟随篡改结果。
正文 · 原文
Abstract:While multimodal agents now carry out complex data analysis with tools, their ability to turn decades of satellite imagery into reliable land-change analysis, crucial for Earth observation science, remains unmeasured. Existing benchmarks fall short: they pose questions on curated images or give agents preprocessed inputs, leaving out the raw multi-sensor archives where such analysis begins. We introduce EarthRecord, a benchmark built on the raw record of 56 sites: four decades of Landsat, MODIS, VIIRS, and Sentinel-2 data, with cloud masking and cross-sensor harmonization left to the agent. It poses 238 land-change questions across ten analysis tasks, scored against withheld references from global products, agreement among methods, and visual interpretation. Two controls test what answers rest on: the closed book removes the record, and instrument pairs alter one satellite's data while nothing changes on the ground. Evaluations of twelve multimodal agents reveal that leading agents complete most analyses end to end but falter when an answer requires mapping from imagery. Further analysis shows that the record moves answers from prior knowledge to the pixels but not yet to the real change on the ground: when one satellite's data are altered, half of the right answers follow the alteration. EarthRecord thus provides a principled platform for measuring and advancing agents from pixels to land change.
| Comments: | 23 pages, 9 figures, 18 tables. Project page: this https URL |
| Subjects: | Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2611.12934 [cs.AI] |
| (or arXiv:2611.12934v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2611.12934 arXiv-issued DOI via DataCite |
Submission history
From: Haoran Zhang [view email]
[v1]
Fri, 6 Nov 2026 09:08:21 UTC (12,081 KB)
来源：arXiv cs.AI · arxiv.org