本文简要概述了现有的地理基础模型（GeoFM）与地理人工智能（GeoAI）模型，以及用于评估这些模型的核心数据集与基准测试。地理基础模型仍是一个新兴且快速发展的研究领域。依据基础模型（FM）或地理基础模型（GeoFM）在各项研究中所起的作用，可将现有GeoFM相关研究大致分为以下三类：1）通过提示工程（prompt engineering）与任务特定微调（task-specific fine-tuning），将现有基础模型适配至地理空间任务；2）构建面向地理空间任务的先进大语言模型（LLM）智能体框架；3）通过具备地理感知能力的模型训练与微调，开发新型地理基础模型。

Here we provide a brief overview of existing GeoFM and GeoAI models as well as core datasets and benchmarks for evaluating these models. Geo-foundation models are still a new and rapidly evolving research field. Based on the role FMs or GeoFMs play in each study, we can roughly classify the existing GeoFM-related research into the following categories: 1) adapting existing FMs on geospatial tasks via prompt engineering and task-specific fine-tuning; 2) developing advanced LLM agent frameworks for geospatial tasks; and 3) developing novel geo-foundation models via geo-aware model training and fine-tuning.