Evaluation of MODIS Gross Primary Production across Multiple Biomes in China Using Eddy Covariance Flux Data

MOD17A2 provides near real-time estimates of gross primary production (GPP) globally. In this study, MOD17A2 GPP was evaluated using eddy covariance (EC) flux measurements at eight sites in five various biome types across China. The sensitivity of MOD17A2 to meteorological data and leaf area index/fractional photosynthetically active radiation (LAI/FPAR) products were examined by introducing site meteorological measurements and improved Global Land Surface Satellite (GLASS) LAI products. We also assessed the potential error contributions from land cover and maximum light use efficiency (epsilon(max)). The results showed that MOD17A2 agreed well with flux measurements of annual GPP (R-2 = 0.76) when all biome types were considered as a whole. However, MOD17A2 was ineffective for estimating annual GPP at mixed forests, evergreen needleleaf forests and croplands, respectively. Moreover, MOD17A2 underestimated flux derived GPP during the summer (R-2 = 0.46). It was found that the meteorological data used in MOD17A2 failed to properly estimate the site measured vapor pressure deficits (VPD) (R-2 = 0.31). Replacing the existing LAI/FPAR data with GLASS LAI products reduced MOD17A2 GPP uncertainties. Though land cover presented the fewest errors, epsilon(max) prescribed in MOD17A2 were much lower than inferred epsilon(max) calculated from flux data. Thus, the qualities of meteorological data and LAI/FPAR products need to be improved, and epsilon(max) should be adjusted to provide better GPP estimates using MOD17A2 for Chinese ecosystems.