Numerous studies have utilized the 8-day MODIS Terra Surface Reflectance Product (MOD09, 500 m) to calculate EVI to obtain a higher temporal resolution, rather than directly using the MODIS EVI product [46; 47; 48]. Besides, the MTCI is one of the VIs, and [PERSON] and [PERSON] [49] concluded that the MTCI could replace EVI for estimating GPP across different biomes. However, MTCI products were discontinued in 2012 [50]. The success of launching an Ocean and Land Colour Instrument (OLCI) onboard the Sentinel-3 satellite offers a new possibility for GPP estimation. This instrument provides a higher spatial and temporal resolution of FAPAR and MTCI products than MODIS. Sentinel-3 OLCI was the push-broom imaging spectrometer used to measure the Earth's solar radiation in 21 spectral bands [51; 52]. Moreover, the double satellite system (Sentinel-3A and -3B) mean that the OLCI revisiting period is less than two days [53]. OLCI products are mainly divided into two levels, namely level-1 and level-2 (land and water), with spatial resolutions of about 300 m and 1200 m, respectively [54]. The OLCI Global Vegetation Index (OGVI) and OLCI Terrestrial Chlorophyll Index (OTCI) (the proxy of MTCI [55]) are two of the OLCI level-2 full-resolution land and atmosphere geophysical products, providing an estimate of the FAPAR in the plant canopy and the chlorophyll index, respectively. Compared with the MODIS FAPAR product (MOD15) and surface reflectance composite data (MOD09), OGVI and OTCI use the actual value for each day rather than cumulative eight-day values. Moreover, the spatial resolution is also better than that of MOD15 and MOD09 [56]. Several studies have used Sentinel-3 satellite products for GPP evaluation. For example, [PERSON] et al. [34] explored the relationship between the products of satellite FAPARand solar-induced chlorophyll fluorescence (SIF). They proved the potential correlation between FAPAR products and GPP. [PERSON] et al. [49] demonstrated that OTCI might be an effective substitute for MODIS to estimate GPP. [PERSON] et al. [50] combined OLCI FAPAR with in situ meteorological data to drive the MODIS GPP algorithm to estimate GPP across several biomes. The results indicated that the Sentinel-3 OLCI FAPAR products performed better than MODIS FAPAR products at the site scale in estimating GPP and demonstrated a significant correlation between OTCI and GPP. Nevertheless, the studies mentioned above were all based on the site scale, and the estimation of GPP on a large scale was not involved. Moreover, only a single LUE model was adopted, or only a simple relationship between in situ GPP and FAPAR was established. None of these studies utilized multiple LUE or VI models to estimate GPP. This paper aims to demonstrate the potential of combining Sentinel-3 OLCI FAPAR and OTCI with meteorology reanalysis data in estimating GPP with multiple models at multiple scales. Specifically, this study has four objectives (1) integrating Sentinel-3 OLCI FAPAR and MERRA2 meteorology reanalysis data into the MODIS GPP algorithm and EC-LUE model to estimate GPP, (2) combining Sentinel-3 OTCI and MERRA2 meteorology reanalysis data with the GR and VI models to estimate GPP, (3) comparing the GPP obtained from four RS-driven models with on-site measured GPP and MODIS GPP products, and (4) applying Sentinel-3 OLCI FAPAR and meteorology reanalysis to estimate GPP at the regional scale and compare it with MODIS GPP products.