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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 (<i>F</i>_opt) and quantum efficiency (<i>α</i>) 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 <i>F</i>_opt and <i>α</i> 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 <i>F</i>_opt were closely related to SIWSI being sensitive to equivalent water thickness, whereas <i>α</i> was closely related to RDVI being affected by chlorophyll abundance. Spatial and inter-annual dynamics in <i>F</i>_opt and <i>α</i> were closely coupled to NDVI and RDVI, respectively. Modelled GPP based on <i>F</i>_opt and <i>α</i> 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 g C m⁻² yr⁻¹. This study indicates the strong applicability of EO as a tool for spatially explicit estimates of GPP, <i>F</i>_opt and <i>α</i>; incorporating EO-based <i>F</i>_opt and <i>α</i> in dynamic global vegetation models could improve estimates of vegetation production and simulations of ecosystem processes and hydro-biochemical cycles.