Improving the performance of remote sensing models for capturing intra- and inter-annual variations in daily GPP: An analysis using global FLUXNET tower data

Accurate and reliable estimates of gross primary productivity (GPP) are required for monitoring the global carbon cycle at different spatial and temporal scales. Because GPP displays high spatial and temporal variation, remote sensing plays a major role in producing gridded estimates of GPP across spatiotemporal scales. In this context, understanding the strengths and weaknesses of remote sensing-based models of GPP and improving their …