A high-resolution satellite-based solar-induced chlorophyll fluorescence dataset for China from 2000 to 2022
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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.
日光诱导叶绿素荧光（Solar-induced chlorophyll fluorescence, SIF）是光合作用的重要替代指标。搭载于哥白尼哨兵5P（Copernicus Sentinel-5P）任务的对流层监测仪（TROPOspheric Monitoring Instrument, TROPOMI）具备近乎全球的覆盖范围与精细的光谱分辨率，可实现可靠的SIF反演。然而，当前已有的卫星反演SIF数据集仅能以粗空间分辨率获取，这限制了其在精细尺度上的应用。本研究采用加权堆叠算法，以天底空间分辨率为3.5 km×5.6~7 km的TROPOMI数据为基础，生成了2000年至2022年中国区域的高空间分辨率SIF数据集（500 m，8天合成，命名为HCSIF）。经验证数据集检验，本算法展现出较高精度（决定系数R²=0.87，均方根误差RMSE=0.057 mW/m²/nm/sr）。研究团队将HCSIF数据集与轨道碳观测卫星2号（OCO-2）SIF数据、基于通量塔的SIF实测数据以及通量塔获取的总初级生产力（Gross Primary Productivity, GPP）数据进行了对比验证。本数据集有望推动对精细尺度陆地生态过程的认知，可用于长期监测生态系统生物多样性，并精准评估作物健康状况、生产力与胁迫水平。数据集缩放因子为0.0001。
