A high-resolution global leaf chlorophyll content product using the Sentinel-2 data

利用Sentinel-2数据生成的高分辨率全球叶片叶绿素含量产品

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Abstract

Leaf chlorophyll content (LCC) serves as a critical indicator for quantifying photosynthetic carbon assimilation, providing fundamental data for terrestrial carbon cycle estimation. In the past five years, some global LCC remote sensing products have been generated, but their resolution ranges from 300 m to 500 m. This study employed an empirical relationship method based on the Chlorophyll Sensitive Index (CSI) to produce the Multi-source data Synergized Quantitative Global LCC product (MuSyQ Global LCC) with a resolution from 100 m to 10 m using the Google Earth Engine (GEE) platform. Validation results demonstrate that the 10m-resolution MuSyQ Global LCC product has an RMSE of 13.69 μg/cm(2), R(2) of 0.37, and the RMSE is between 11.28 μg/cm(2) and 15.22 μg/cm(2) for different vegetation types. Its finer resolution reveals more spatial details compared with the existing global products. When upscaled to 500 m, it demonstrates high consistency with the MODIS LCC product, and MuSyQ Global LCC (RMSE = 14.16 μg/cm(2)) exhibits higher accuracy than MODIS LCC (RMSE = 14.74 μg/cm(2)).

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