内容来源：https://www.geekwire.com/2025/ai2-loosens-big-techs-grip-on-earth-insights-with-open-source-ai-models-for-climate-and-conservation/

内容总结：

艾伦人工智能研究所近日发布全新开放平台"奥尔莫地球"，该系统能近乎实时分析卫星与传感器数据，为缺乏专业AI技术的组织提供森林砍伐监测、作物健康评估及野火风险预测等功能。该平台通过分析千万级地球观测数据构建，旨在打破专业壁垒，让普通机构也能运用通常仅限于专业实验室的地球观测能力。

平台核心工具包括用于创建数据集和优化模型的"奥尔莫地球工作室"，以及可浏览AI生成地图的网页应用"奥尔莫地球观察器"。研究所首席执行官阿里·法尔哈迪表示，此举将推动前沿环保工作者运用地球AI技术。项目负责人帕特里克·博凯马强调，该平台致力于促进跨学科协作，助力各方共同应对环境挑战。

目前早期应用已显现成效：全球红树林测绘效率提升两倍且准确率达97%，亚马逊流域森林砍伐监测及俄勒冈州植被干旱测绘等应用均取得突破。作为该机构"全面开放"理念在气候科学领域的延伸，该平台不仅提供数据访问，更构建了完整的模型优化与部署系统。

与谷歌地球引擎等需专业技术的平台不同，"奥尔莫地球"提供端到端的开源替代方案。测试显示其优化模型性能显著优于谷歌、Meta等机构的同类产品。观察器功能已向公众开放，完整平台正逐步向合作伙伴开放并持续招募协作机构。

中文翻译：

艾伦人工智能研究所近日发布全新平台，旨在帮助缺乏专业AI技术的机构实时监测森林砍伐、评估作物健康状况、预测野火风险，从而以近实时方式洞察地球生态。这款名为OlmoEarth的端到端开放系统由这家西雅图非营利AI机构于周二发布，能够运用人工智能技术解析实时与历史卫星及传感器数据。

该平台基于新一代AI模型架构运行。研究所透露，这些模型通过处理约千万次地球观测数据（总计达10TB）训练而成，其核心理念是让普通用户也能免费使用通常仅限于专有系统或资源雄厚的AI实验室的高级功能。

平台核心工具包含两大组件：用于创建数据集和优化模型的OlmoEarth Studio工作台，以及可浏览AI生成地图的网页应用OlmoEarth Viewer。研究所首席执行官、华盛顿大学教授阿里·法哈迪在发布会上表示，该计划"让前沿工作者都能运用地球科学AI技术"。项目首席研究员帕特里克·博克玛补充说明，该项目旨在促进跨学科协作，帮助不同团队基于共享数据与工具共同应对环境挑战。

目前早期应用已展现巨大潜力：全球红树林地图更新效率提升两倍且准确率达97%，亚马逊流域 deforestation 监测系统，以及俄勒冈州植被干旱测绘助力野火防控等成功案例。这是研究所推行"全面开放"理念的最新实践，将其在开放权重语言与多模态模型领域的主张延伸至气候科学与生态保护领域。

长期以来，地理空间分析始终由大型科技企业与研究机构主导。虽然谷歌地球引擎和微软行星计算机等平台提供PB级卫星数据的云端访问，但往往需要深厚技术背景且未完全开源。研究所正将OlmoEarth定位为端到端的开放替代方案，不仅提供数据通道，更构建完整的模型优化与部署体系。

在模型层面，研究所正与其他知名实验室的AI专用工具竞争。研究数据显示，经优化的OlmoEarth模型"显著超越谷歌AlphaEarth Foundations"，同时在与Meta、IBM及NASA的模型对比中表现优异。谷歌此前仅发布了模型嵌入组件而非完整开源模型。

OlmoEarth Viewer即日起开放使用，研究所同步在GitHub发布配套代码与技术文档。包含Studio功能在内的完整平台正面向合作伙伴逐步开放，研究所同时诚邀更多机构参与协作开发。

英文来源：

A new platform from the Allen Institute for AI promises to deliver insights into the state of the planet, in near real-time, by giving organizations without deep AI expertise the ability to monitor deforestation, assess crop health, and predict wildfire risk, among other capabilities.
OlmoEarth, announced Tuesday by the Seattle-based nonprofit AI institute, is an open, end-to-end system that uses AI to analyze current and historical satellite and sensor data.
It runs on a new family of AI models, which Ai2 says it trained on millions of Earth observations totaling roughly 10 terabytes of data. The idea is to give anyone free access to the kinds of capabilities typically restricted to proprietary systems or well-resourced AI labs.
The platform includes tools such as OlmoEarth Studio, a workspace for creating datasets and fine-tuning models, and OlmoEarth Viewer, a web app for exploring AI-generated maps.
The initiative is “making Earth AI accessible to those working on the front lines,” said Ali Farhadi, Ai2 CEO and University of Washington professor, in a press release announcing OlmoEarth.
Patrick Beukema, lead researcher on the OlmoEarth team, added that the project is meant to encourage collaboration across scientific and technical fields, helping different groups work together on shared data and tools to better understand and respond to environmental challenges.
Ai2 said early adopters of OlmoEarth are already showing the potential, using it to update global mangrove maps twice as fast with 97% accuracy, detect deforestation across the Amazon, and map vegetation dryness in Oregon to improve wildfire prediction and prevention, for example.
It’s the latest example of Ai2’s push for “true openness” in AI, extending the philosophy behind its open-weight language and multimodal models into climate science and conservation.
Geospatial analysis has long been dominated by major tech and research organizations. Platforms like Google Earth Engine and Microsoft’s Planetary Computer provide cloud access to petabytes of satellite data, but often require significant technical expertise for analysis and are not fully open-source.
Ai2 is positioning OlmoEarth as an end-to-end open alternative, providing not just data access but a complete, usable system for model fine-tuning and deployment.
At the model level, Ai2 is competing with AI-specific tools from other major labs. In its research, Ai2 contrasts OlmoEarth with Google’s AlphaEarth Foundations, noting that Google released “embeddings” rather than the open model itself. Ai2 says a fine-tuned OlmoEarth “outperformed AEF substantially,” and also did well against models from Meta, IBM, and NASA.
The OlmoEarth Viewer is available starting today, and Ai2 has released accompanying code and documentation on GitHub. The full platform, including OlmoEarth Studio, is rolling out to select partners, and Ai2 is inviting additional collaborations.