—Satellite-derived time series of the fraction of absorbed photosynthetically active radiation (fAPAR) are widely used to monitor vegetation dynamics and to detect vegetation anomalies. Several global data sets are available for this purpose. They are produced using different algorithms and/or satellite sensors. This paper compares and analyzes three multitemporal fAPAR data sets derived from SPOT-VEGETATION instrument by explicitly distinguishing between spatial and temporal agreement. The first two data sets are currently used by the Joint Research Centre—Monitoring Agricultural ResourceS Unit (JRC-MARS) for operational yield forecasting and food security assessments. The third time series (named GEOV1) is from a new processing algorithm developed within the European FP7 Geoland2 project. The comparative analysis was conducted for the years 2003 and 2004 over three 10 • × 10 • regions with different eco-climatic characteristics (Niger, Brazil, and France). Our study revealed that GEOV1 fAPAR estimates were systematically higher than those of JRC-MARS. The spatial analysis showed moderate to high agreement between data sets with specific seasonality in the three study regions. The temporal agreement showed spatial (and land cover-related) variability spanning from very low to almost perfect. Large differences were observed in regions and periods with large cloud occurrence where GEOV1 provides more reliable and smooth temporal profiles due to improved cloud screening and longer compositing periods. Other sources of disagreement between data sets were identified in differences in the fAPAR retrieval algorithm definitions. Index Terms—CYCLight, fraction of absorbed photosyntheti-cally active radiation (fAPAR), GEOV1-Geoland2, JRC-FAPAR, multitemporal remote sensing (RS) data, SPOT-VEGETATION (VGT).