@Article{Tao2024,
author="Tao, Shiyu
and Chen, Jing M.
and Zhang, Zhaoying
and Zhang, Yongguang
and Ju, Weimin
and Zhu, Tingting
and Wu, Linsheng
and Wu, Yunfei
and Kang, Xiaoyan",
title="A high-resolution satellite-based solar-induced chlorophyll fluorescence dataset for China from 2000 to 2022",
journal="Scientific Data",
year="2024",
month="Nov",
day="26",
volume="11",
number="1",
pages="1286",
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{\thinspace}m, 8-day) in China (HCSIF) from 2000 to 2022 from the TROPOMI with a spatial resolution at a nadir of 3.5{\thinspace}km by 5.6--7{\thinspace}km. Our algorithm demonstrated high accuracy on validation datasets (R2{\thinspace}={\thinspace}0.87, RMSE{\thinspace}={\thinspace}0.057{\thinspace}mW/m2/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.",
issn="2052-4463",
doi="10.1038/s41597-024-04101-6",
url="https://doi.org/10.1038/s41597-024-04101-6"
}