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高分辨率卫星观测的中国 2000-2022 年太阳诱导叶绿素荧光数据集。

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

机构信息

International Institute for Earth System Sciences, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing University, Nanjing, Jiangsu, China.

Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, 210023, China.

出版信息

Sci Data. 2024 Nov 26;11(1):1286. doi: 10.1038/s41597-024-04101-6.

DOI:10.1038/s41597-024-04101-6
PMID:39592634
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11599385/
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 = 0.87, RMSE = 0.057 mW/m/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.

摘要

太阳诱导叶绿素荧光（SIF）可作为光合作用的一个有价值的替代指标。哥白尼哨兵-5P 任务上的对流层监测仪（TROPOMI）具有精细的光谱分辨率，几乎可以实现全球覆盖，非常适合可靠的 SIF 反演。然而，目前卫星衍生的 SIF 数据集只能以粗空间分辨率获得，限制了其在细尺度上的应用。在这里，我们利用加权堆叠算法从 2000 年到 2022 年，利用空间分辨率为 3.5 公里乘 5.6-7 公里的 TROPOMI 生成了一个在中国（HCSIF）的高空间分辨率 SIF 数据集（500 米，8 天）。我们的算法在验证数据集上表现出很高的精度（R=0.87，RMSE=0.057 mW/m/nm/sr）。HCSIF 数据集与 OCO-2 SIF、GOME-2 SIF 塔基 SIF 测量和通量塔的总初级生产力（GPP）进行了比较。我们预计，该数据集有可能推进对细尺度陆地生态过程的理解，从而长期监测生态系统生物多样性，并精确评估作物健康、生产力和胁迫水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/2790ae57b110/41597_2024_4101_Fig12_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/464ca6d43ce0/41597_2024_4101_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/8ed8205dd200/41597_2024_4101_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/2d307f81b3b3/41597_2024_4101_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/38c45e7f94df/41597_2024_4101_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/f01888f6a03b/41597_2024_4101_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/50b46e5e3741/41597_2024_4101_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/c5e3e75b5d72/41597_2024_4101_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/079a138151ad/41597_2024_4101_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f33e/11599385/2790ae57b110/41597_2024_4101_Fig12_HTML.jpg

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