AI 中文总结
本研究针对89个地理空间基础模型（GeoFMs），结合生态学家需求与人机交互理论构建七维度评估框架，发现近三分之一模型除源代码外无从业者支持，为GeoFM的可用性优化提供了诊断依据。
AI 中文摘要
地理空间基础模型（GeoFMs）为环境监测提供了变革性潜力，但生态学家对其采用程度参差不齐。大多数评估以模型为中心，聚焦于架构和基准精度，却忽略了目标受众是否能使用这些系统。为解决这一差距，我们首先开展了一项针对生态与保护科学家的试点专家征询调查，帮助我们确定当前GeoFM开发重点与科学家需求之间的不一致。基于这些发现并结合人机交互（HCI）理论，我们创建了涵盖访问与部署、交互与定制、信任与透明度、社区与支持、科学持久性、多语言支持及离线可用性七个维度的评估框架。随后，两名评分者使用该框架对89个GeoFMs进行评估。我们发现存在明显的可访问性差距：近三分之一的模型除源代码外，未为从业者提供任何支持。评分高度一致的维度可作为领域层面的诊断工具，揭示当前GeoFMs仍有改进空间。
英文摘要
Geospatial foundation models (GeoFMs) offer transformative potential for environmental monitoring, yet adoption among ecologists is uneven. Most evaluations are model-centric, focusing on architecture and benchmark accuracy, which overlooks whether the systems are usable by their intended audiences. To address this gap, we first conducted a pilot expert elicitation survey with ecology and conservation scientists that helped us identify misalignments between current GeoFM development priorities and their needs. Informed by these findings and based on HCI theory, we created a seven-dimension evaluation covering Access & Deployment, Interaction & Customization, Trust & Transparency, Community & Support, Scientific Permanence, Multilingual Support, and Offline Usability. Then, two raters applied this rubric to 89 GeoFMs. We found distinct accessibility gaps where nearly a third provide no support to practitioners beyond their source code. Dimensions along which ratings were highly consistent function as field-level diagnostics, revealing where there is room for improvement for current GeoFMs.
