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.

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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
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article

A high-resolution satellite-based solar-induced chlorophyll fluorescence dataset for China from 2000 to 2022

Jing M. Chen, Shiyu Tao, Weimin Ju, Yunfei Wu et al.
20 citations
Scientific Data
Remote Sensing in Agriculture
9.18
article

A high-resolution satellite-based solar-induced chlorophyll fluorescence dataset for China from 2000 to 2022

Jing M. Chen, Shiyu Tao, Weimin Ju, Yunfei Wu, Xiaoyan Kang, Tingting Zhu, Linsheng Wu, Yongguang Zhang, Zhaoying Zhang
article en
20 citations

Abstract

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.

Scientific DataVol. 11(1)
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)
Affordable and clean energy
Openalex Percentile: Top 2%
Remote Sensing in Agriculture
9.18
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