2026-10-13T00:23:30Z https://www.scidb.cn/oai

10.57760/sciencedb.16910 2025-04-03T16:03:50Z

2025-04-03 A high-resolution satellite-based solar-induced chlorophyll fluorescence dataset for China from 2000 to 2022 doi:10.57760/sciencedb.16910 en 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 (R2 = 0.87, RMSE = 0.057 mW/m2/nm/sr). The HCSIF dataset was evaluated against OCO-2 SIF, tower-based measurements of SIF, and gross primary productivity (GPP) from flux towers. Our 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. The Scale factor is 0.0001. SIF; photosynthesis; remote sensing; machine learning Shiyu Tao Jingming Chen Zhaoying Zhang Yongguang Zhang Weimin Ju Tingting Zhu Linsheng Wu Yunfei Wu Xiaoyan Kang PUBLIC https://creativecommons.org/publicdomain/zero/1.0/ dataset http://www.doi.org/10.1038/s41597-024-04101-6 Science Data Bank