A high-resolution satellite-based solar-induced chlorophyll fluorescence dataset for China from 2000 to 2022
Solar-induced chlorophyll fluorescence (SIF) serves as a valuable proxy for photosynthesis. The TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5P mission offers nearly global coverage with a fine spectral resolution for reliable SIF retrieval. However, the present satellite-derived SIF datasets are accessible only at coarse spatial resolutions, constraining its applications at fine scales. Here, we utilized a weighted stacking algorithm to generate a high spatial resolution SIF dataset (500 m, 8-day) in China (HCSIF) from 2000 to 2022 from the TROPOMI with a spatial resolution at a nadir of 3.5 km by 5.6-7 km. Our algorithm demonstrated high accuracy on validation datasets (R<sup>2</sup> = 0.87, RMSE = 0.057 mW/m<sup>2</sup>/nm/sr). The HCSIF dataset was evaluated against OCO-2 SIF, GOME-2 SIF tower-based measurements of SIF, and gross primary productivity (GPP) from flux towers. We expect this dataset can potentially advance the understanding of fine-scale terrestrial ecological processes, allowing for monitoring of ecosystem biodiversity and precise assessment of crop health, productivity, and stress levels in the long term.
Authors
- Jing M. Chen (ORCID: https://orcid.org/0000-0002-8682-1293)
- Shiyu Tao (ORCID: https://orcid.org/0000-0003-2600-3309)
- Weimin Ju (ORCID: https://orcid.org/0000-0002-0010-7401)
- Yunfei Wu (ORCID: https://orcid.org/0000-0002-0833-7148)
- Xiaoyan Kang (ORCID: https://orcid.org/0000-0002-1203-8140)
- Tingting Zhu (ORCID: https://orcid.org/0000-0003-3141-1884)
- Linsheng Wu (ORCID: https://orcid.org/0000-0002-8484-407X)
- Yongguang Zhang (ORCID: https://orcid.org/0000-0001-8286-300X)
- Zhaoying Zhang
Institutions
- Fujian Normal University (CN)
- University of Toronto (CA)
- Chinese Academy of Sciences (CN)
- Ministry of Natural Resources (CN)
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (CN)
- Institute of Geographic Sciences and Natural Resources Research (CN)
- Nanjing University (CN)
Publication Details
- Journal
- Scientific Data
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1038/s41597-024-04101-6
- Citations
- 20
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 9.18