2026-10-12T13:35:26Z https://www.scidb.cn/oai

10.57760/sciencedb.37650 2026-05-26T14:51:13Z

2026-05-26 FY-4B MultiModal: A Chinese Geostationary Meteorological Satellite Image-Text Retrieval Benchmark Dataset doi:10.57760/sciencedb.37650 en FY-4B MultiModal is the first image-text retrieval benchmark dataset derived  from a geostationary meteorological satellite. It contains 828 RGB composite images (1024x1024 pixels) from the FY-4B AGRI instrument, spanning  13 weather-phenomenon categories: clear sky, cumulus, stratus, cirrus,    cumulonimbus, typhoon, rainstorm clouds, dust storm, fog/low cloud, snow  cover, severe convection, cloud systems, and others. Each category is paired  with two Chinese-language meteorological text descriptions, yielding 26 cross-modal retrieval queries. Images were synthesized from FY-4B AGRI L1  channels 1 (0.47 μm), 2 (0.65 μm), and 3 (0.825 μm) via Lanczos resampling and percentile contrast stretching. Annotations were performed by domain experts at the Yunnan Provincial Meteorological Data Center. The dataset includes annotations.json, text_queries.json, and a README (~943 MB total). Licensed under CC BY 4.0. FY-4B satellite; geostationary meteorological satellite; image-text retrieval; benchmark dataset; Chinese meteorological terminology; cross-modal retrieval Yang Jian PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank