Abstract
AbstractThe fraction of absorbed photosynthetically active radiation (FPAR) is an essential biophysical parameter that characterizes the structure and function of terrestrial ecosystems. Despite the extensive utilization of several satellite-derived FPAR products, notable temporal inconsistencies within each product have been underscored. Here, the new generation of the GIMMS FPAR product, GIMMS FPAR4g, was developed using a combination of a machine learning algorithm and a pixel-wise multi-sensor records integration approach. PKU GIMMS NDVI, which eliminates the orbital drift and sensor degradation issues, was used as the data source. Comparisons with ground-based measurements indicate root mean square errors ranging from 0.10 to 0.14 with R-squared ranging from 0.73 to 0.87. More importantly, our product demonstrates remarkable spatiotemporal coherence and continuity, revealing a persistent terrestrial darkening over the past four decades (0.0004 yr−1, p < 0.001). The GIMMS FPAR4g, available for half-month intervals at a spatial resolution of 1/12° from 1982 to 2022, promises to be a valuable asset for in-depth analyses of vegetation structures and functions spanning the last 40 years.
Funder
National Natural Science Foundation of China
Shenzhen Science and Technology Innovation Commission
Publisher
Springer Science and Business Media LLC