A dataset of 16m/10-day Gross Primary Productivity of MuSyQ GF-series (2018–2020, China)

Gross Primary Productivity (GPP) refers to the total amount of organic matter produced by green plants through photosynthesis per unit area per unit time. It is an important ecological indicator for evaluating the sustainable development of terrestrial ecosystems. This dataset provides GPP remote sensing products for China at a 16-meter/10-day resolution for the years 2018-2020. The product is based on the China 16m/10-day MuSyQ GF-1 NDVI and LAI products, as well as ERA5 meteorological data and the Köppen climate classification map, and it constructs a GPP inversion algorithm that distinguishes between natural vegetation and croplands. For natural vegetation, 42 light-use efficiency algorithms specific to different vegetation climate zones and their corresponding GPP responses were developed. For cropland ecosystems, an empirical model based on vegetation index and photosynthetically active radiation (VI-PAR-GPP) was used for estimation. This product effectively reduces estimation errors caused by spatial heterogeneity and simplified physiological-ecological processes, providing more reliable data support for monitoring carbon cycle dynamics in terrestrial ecosystems, scientific research, and government decision-making.