Global OMI HCHO Level-3 oversampling dataset: high spatial resolution and lightweight uncertainty.
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| Title: | Global OMI HCHO Level-3 oversampling dataset: high spatial resolution and lightweight uncertainty. |
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| Authors: | Xia H; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China.; Institute of Aerospace Remote Sensing Innovations, Guangzhou University, Guangzhou, 510006, China., Wang D; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China. wangdk@gzhu.edu.cn.; Institute of Aerospace Remote Sensing Innovations, Guangzhou University, Guangzhou, 510006, China. wangdk@gzhu.edu.cn., Yang X; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China.; Institute of Aerospace Remote Sensing Innovations, Guangzhou University, Guangzhou, 510006, China., Li X; School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China., Zhu L; School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China., Lu T; College of Science, Northeastern University, Boston, MA02115, USA., Song Z; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China.; Institute of Aerospace Remote Sensing Innovations, Guangzhou University, Guangzhou, 510006, China., Mo Y; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China.; Institute of Aerospace Remote Sensing Innovations, Guangzhou University, Guangzhou, 510006, China., Yan C; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China.; Institute of Aerospace Remote Sensing Innovations, Guangzhou University, Guangzhou, 510006, China., Pu D; School of Architecture & Urban Planning, Shenzhen University, Shenzhen, 518060, China., Zuo X; Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands.; Department of Geoscience & Remote Sensing, Delft University of Technology (TUD), Delft, the Netherlands., Sun W; Division of Atmospheric Composition, Royal Belgian Institute for Space Aeronomy (BIRAIASB), Brussels, 1180, Belgium., Wang J; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China.; Institute of Aerospace Remote Sensing Innovations, Guangzhou University, Guangzhou, 510006, China., Gu X; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China.; Institute of Aerospace Remote Sensing Innovations, Guangzhou University, Guangzhou, 510006, China. |
| Source: | Scientific data [Sci Data] 2026 Jan 19; Vol. 13 (1), pp. 253. Date of Electronic Publication: 2026 Jan 19. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101640192 Publication Model: Electronic Cited Medium: Internet ISSN: 2052-4463 (Electronic) Linking ISSN: 20524463 NLM ISO Abbreviation: Sci Data Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2052-4463 |
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| DOI: | 10.1038/s41597-026-06577-w |
