This is the first large-scale, very-high-resolution SAR-optical-language dataset with complex-valued SAR data and pixel-level alignment, unlocking new benchmarks for multimodal foundation models that can learn from radar imagery the way they learn from optical images.
SARLO-80 is a large-scale dataset of 119,566 aligned SAR-optical-text triplets at 80cm resolution covering 257 locations worldwide. It preserves complex-valued SAR measurements and native acquisition geometry—unlike existing low-resolution datasets—enabling physically grounded multimodal learning for radar and optical image understanding.