Harmonization of GEOV2 fAPAR time series through MODIS data for global drought monitoring

摘要

The temporal consistency of the fAPAR GEOV2 full time series (constituted by data derived from SPOT-VGT1/2 and PROBA-V) is analyzed against the single-sensor MODIS dataset, with a particular focus on the most recent fAPAR anomalies (z-scores) produced from PROBA-V in the period 2014-2017. The intercomparison highlights a systematic overestimation of GEOV2 fAPAR z-scores when compared to MODIS fAPAR, likely related to the observed positive bias (over 90% of the domain) in the PROBA-V vs. SPOT-VGT1/2 relationship. A simple two-step harmonization procedure has been proposed to remove this discrepancy, based on two separate linear corrections of SPOT-VGT1/2 (2001-2013) and PROBA-V (2014-2017) data with respect to MODIS, followed by a time lag correction. The harmonized GEOV2 time series preserves the overall dynamic of fAPAR, while removing the sensor bias and improving the consistency with MODIS data. The fAPAR anomalies from the harmonized GEOV2 time series provide unbiased estimates of z-scores that are overall well correlated (R = 0.55 +/- 0.25) with the MODIS fAPAR anomalies.