SARLANG-1M: 1 Million SAR Image-Text Pairs from 59 Cities

SARLANG-1M is a large-scale benchmark for multimodal synthetic aperture radar image understanding. It comprises more than 1 million high-quality SAR image-text pairs collected from over 59 cities worldwide. The dataset was created by YiminJimmy and was last updated on February 10, 2026.

Use Cases

• Training multimodal vision-language models based on SAR imagery and textual descriptions.
• Benchmarking SAR image captioning models based on the provided concise and detailed captions.
• Developing models for fine-grained object recognition in remote sensing based on the 1,696 object categories.
• Analyzing the impact of image resolution on SAR interpretation based on hierarchical resolutions from 0.1 to 25 meters.

Strengths

• Contains more than 1 million image-text pairs, indicating a substantial scale.
• Covers a diverse geographic scope with data from over 59 cities worldwide.
• Offers hierarchical image resolutions ranging from 0.1 to 25 meters.
• Includes fine-grained semantic descriptions with both concise and detailed captions.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Freshness should be verified as the last update date is in the future (2026-02-10).

Provenance

Source

huggingface

Collection Method

Collected from over 59 cities worldwide; specific collection method is not detailed.

Freshness

Last updated 2026-02-10 07:11:24

Geography

Global coverage, with data from over 59 cities worldwide.