An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product
Abstract Solar-induced chlorophyll fluorescence (SIF) is an indicator of vegetation photosynthesis, and multiple satellite SIF products have been generated in recent years. However, current SIF products are limited for applications toward vegetation photosynthesis monitoring because of low spatial r...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-04325-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832586054923714560 |
|---|---|
| author | Siyuan Chen Liangyun Liu Lichun Sui Xinjie Liu Yan Ma |
| author_facet | Siyuan Chen Liangyun Liu Lichun Sui Xinjie Liu Yan Ma |
| author_sort | Siyuan Chen |
| collection | DOAJ |
| description | Abstract Solar-induced chlorophyll fluorescence (SIF) is an indicator of vegetation photosynthesis, and multiple satellite SIF products have been generated in recent years. However, current SIF products are limited for applications toward vegetation photosynthesis monitoring because of low spatial resolution or spatial discontinuity. This study uses a spatial downscaling method to obtain a redistribution of the original TROPOspheric Monitoring Instrument (TROPOMI) SIF (OSIF). As a result, a downscaled SIF dataset (TroDSIF) with fine spatio-temporal resolutions (500 m, 16 days) was generated. Compared with a machine learning (ML) SIF product and OSIF, TroDSIF can better reproduce the OSIF signals with higher R2, lower root mean square error (RMSE), and nearly zero residuals at different latitudes. Direct validation on TroDSIF using tower-based SIF measurements demonstrated a good consistency between them. However, TroDSIF is dependent on the linear hypothesis between OSIF and the ML-predicted SIF used in the redistribution process. Nonetheless, we believe TroDSIF is anticipated to be beneficial to conducting global vegetation photosynthesis and climate change studies at precise scales. |
| format | Article |
| id | doaj-art-4e175b004ddd46a09c8bfa5c1bedece6 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-4e175b004ddd46a09c8bfa5c1bedece62025-01-26T12:14:53ZengNature PortfolioScientific Data2052-44632025-01-0112111210.1038/s41597-024-04325-6An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI productSiyuan Chen0Liangyun Liu1Lichun Sui2Xinjie Liu3Yan Ma4PowerChina Northwest Engineering Corporation LimitedInternational Research Center of Big Data for Sustainable Development GoalsCollege of Geological Engineering and Geomatics, Chang’ an UniversityInternational Research Center of Big Data for Sustainable Development GoalsZhejiang Academy of Surveying and MappingAbstract Solar-induced chlorophyll fluorescence (SIF) is an indicator of vegetation photosynthesis, and multiple satellite SIF products have been generated in recent years. However, current SIF products are limited for applications toward vegetation photosynthesis monitoring because of low spatial resolution or spatial discontinuity. This study uses a spatial downscaling method to obtain a redistribution of the original TROPOspheric Monitoring Instrument (TROPOMI) SIF (OSIF). As a result, a downscaled SIF dataset (TroDSIF) with fine spatio-temporal resolutions (500 m, 16 days) was generated. Compared with a machine learning (ML) SIF product and OSIF, TroDSIF can better reproduce the OSIF signals with higher R2, lower root mean square error (RMSE), and nearly zero residuals at different latitudes. Direct validation on TroDSIF using tower-based SIF measurements demonstrated a good consistency between them. However, TroDSIF is dependent on the linear hypothesis between OSIF and the ML-predicted SIF used in the redistribution process. Nonetheless, we believe TroDSIF is anticipated to be beneficial to conducting global vegetation photosynthesis and climate change studies at precise scales.https://doi.org/10.1038/s41597-024-04325-6 |
| spellingShingle | Siyuan Chen Liangyun Liu Lichun Sui Xinjie Liu Yan Ma An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product Scientific Data |
| title | An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product |
| title_full | An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product |
| title_fullStr | An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product |
| title_full_unstemmed | An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product |
| title_short | An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product |
| title_sort | improved spatially downscaled solar induced chlorophyll fluorescence dataset from the tropomi product |
| url | https://doi.org/10.1038/s41597-024-04325-6 |
| work_keys_str_mv | AT siyuanchen animprovedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct AT liangyunliu animprovedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct AT lichunsui animprovedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct AT xinjieliu animprovedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct AT yanma animprovedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct AT siyuanchen improvedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct AT liangyunliu improvedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct AT lichunsui improvedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct AT xinjieliu improvedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct AT yanma improvedspatiallydownscaledsolarinducedchlorophyllfluorescencedatasetfromthetropomiproduct |