一键获取任意时间地点的遥感模型嵌入，打破格式壁垒
Any Model, Any Place, Any Time: Get Remote Sensing Foundation Model Embeddings On Demand
- 统一接口支持多种遥感模型，按区域和时间范围调用
- 单行代码即可获取嵌入，批量处理提升效率
- 适合遥感研究者快速对比不同模型性能
遥感领域正快速发展基础模型，为下游任务提供强大嵌入。然而，由于模型发布格式、平台接口和输入数据规范存在显著差异，实际应用与公平比较仍面临挑战。这些不一致大幅增加了跨模型获取、使用和评估嵌入的成本。为此，我们提出 rs-embed，一个 Python 库，提供以感兴趣区域（ROI）为中心的统一接口：仅需一行代码，用户即可从任意支持模型中获取任意位置、任意时间范围的嵌入。该库还支持高效批量处理，实现大规模嵌入生成与评估。代码已开源：https://github.com/cybergis/rs-embed
原文摘要 · Abstract (English)
The remote sensing community is witnessing a rapid growth of foundation models, which provide powerful embeddings for a wide range of downstream tasks. However, practical adoption and fair comparison remain challenging due to substantial heterogeneity in model release formats, platforms and interfaces, and input data specifications. These inconsistencies significantly increase the cost of obtaining, using, and benchmarking embeddings across models. To address this issue, we propose rs-embed, a Python library that offers a unified, region of interst (ROI) centric interface: with a single line of code, users can retrieve embeddings from any supported model for any location and any time range. The library also provides efficient batch processing to enable large-scale embedding generation and evaluation. The code is available at: https://github.com/cybergis/rs-embed
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