Global Leaf Chlorophyll Content Dataset (GLCC) from 2003–2012 to 2018–2020 Derived from MERIS and OLCI Satellite Data: Algorithm and Validation

Leaf chlorophyll content (LCC) is a prominent plant physiological trait and proxy for leaf photosynthetic capacity. The acquisition of LCC data over large spatial temporal scales facilitates vegetation growth monitoring terrestrial carbon cycle modeling. In this study, global 500 m weekly dataset (GLCC) was produced from ENVISAT MERIS Sentinel-3 OLCI satellite using physical radiative transfer modeling approach that considers the influence canopy structure soil background. Firstly, five look-up-tables (LUTs) were generated PROSPECT-D+4-Scale PROSAIL-D models woody non-woody plants. For four LUTs applicable to plants, each LUT contains three sub-LUTs corresponding types crown height. one type includes 25 kinds structures backgrounds. final retrieval considered aggregation inversion results all function (PFT). Then, GLCC validated field measurements, yielding an overall accuracy R2 = 0.41 RMSE 8.94 μg cm−2. Finally, presented acceptable consistency with existing dataset. OLCI, as successor data, used first time co-produce 2003–2012 2018–2020 in conjunction data. This new spanning nearly 20 years will provide valuable opportunity analyze variations dynamics.