MuSyQ Global 5km/8-day and 500m/4-day Spatio-temporal Continuous Fractional Vegetation Cover Product (1981-2020)

Based on the gap probability theory, this study utilized the global GLASS leaf area index (LAI) product and the clumping index priori knowledge to generate the global FVC product with 5km/8-day from 1981 to 2000; and also utilized the spatio-temporal continuous global MuSyQ LAI and clumping index products to generate the global FVC product with 500m/4-day from 2001 to 2020.

By incorporating the clumping index to account for the vegetation structure and spatial distribution characteristics, the product can effectively decrease the FVC overestimation for dense canopy. Based on the FVC ground-measurements obtained from the VALERI and IMAGINES projects, the accuracy of FVC product with the root mean square error (RMSE) of 0.16, mean relative error of 13.42%, and overall accuracy exceeding 85%.