%0 Dataset
%T A high-resolution satellite-based solar-induced chlorophyll fluorescence dataset for China from 2000 to 2022
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/ef1309aa-2564-4d5f-9c64-3259351c0179
%W NCDC
%R 10.57760/sciencedb.16910
%A Zhaoying Zhang
%K SIF;photosynthesis;remote sensing;machine learning
%X Solar induced chlorophyll fluorescence (SIF) is an important substitute for photosynthesis. The TROPOSphere Monitoring Instrument (TROPOMI) carried by the Copernicus Sentinel-5P mission provides almost global coverage of fine spectral resolution, enabling reliable SIF retrieval. However, the SIF dataset currently obtained by satellites only has a relatively coarse spatial resolution, which limits its application at fine scales. Here, we used the weighted superposition algorithm to generate the Chinese High Spatial Resolution SIF dataset (500 meters, 8 days) (HCSIF) from TROPOMI satellite from 2000 to 2022, with a spatial resolution of 3.5 kilometers by 5.6-7 kilometers. Our algorithm demonstrates high accuracy on the validation dataset (R2=0.87, RMSE=0.057 mW/m2/nm/sr). The HCSIF dataset was evaluated against OCO-2 SIF, tower based SIF measurements, and total primary productivity (GPP) of flux towers. Our dataset can facilitate the understanding of fine scale terrestrial ecological processes, enabling the monitoring of biodiversity in ecosystems and accurate long-term assessments of crop health, productivity, and stress levels. The scaling factor is 0.0001.