It has been shown that vegetation growth in semi-arid regions is important to the global terrestrial CO₂ sink, which indicates the strong need for improved understanding and spatially explicit estimates of CO₂ uptake (gross primary production; GPP) in semi-arid ecosystems. This study has three aims: (1) to evaluate the MOD17A2H GPP (collection 6) product against GPP based on eddy covariance (EC) for six sites across the Sahel; (2) to characterize relationships between spatial and temporal variability in EC-based photosynthetic capacity (F_opt) and quantum efficiency (α) and vegetation indices based on earth observation (EO) (normalized difference vegetation index (NDVI), renormalized difference vegetation index (RDVI), enhanced vegetation index (EVI) and shortwave infrared water stress index (SIWSI)); and (3) to study the applicability of EO upscaled F_opt and α for GPP modelling purposes. MOD17A2H GPP (collection 6) drastically underestimated GPP, most likely because maximum light use efficiency is set too low for semi-arid ecosystems in the MODIS algorithm. Intra-annual dynamics in F_opt were closely related to SIWSI being sensitive to equivalent water thickness, whereas α was closely related to RDVI being affected by chlorophyll abundance. Spatial and inter-annual dynamics in F_opt and α were closely coupled to NDVI and RDVI, respectively. Modelled GPP based on F_opt and α upscaled using EO-based indices reproduced in situ GPP well for all except a cropped site that was strongly impacted by anthropogenic land use. Upscaled GPP for the Sahel 2001-2014 was 736 ± 39 gCm^-2yr^-1. This study indicates the strong applicability of EO as a tool for spatially explicit estimates of GPP, F_opt and α incorporating EO-based F_opt and α in dynamic global vegetation models could improve estimates of vegetation production and simulations of ecosystem processes and hydro-biochemical cycles.