ABSTRACT Evapotranspiration (ET) estimates based on remote sensing are constrained by the spatial and temporal resolution of spaceborne observations. Therefore, the choice to be made is whether modelling at high… Click to show full abstract
ABSTRACT Evapotranspiration (ET) estimates based on remote sensing are constrained by the spatial and temporal resolution of spaceborne observations. Therefore, the choice to be made is whether modelling at high temporal resolution with geostationary satellites at the cost of the spatial detail, or spatially detailed instantaneous modelling at overpass-time with polar-orbit satellites. This study aimed at exploiting the strength of both modelling approaches and derive daily ET estimates with cell size 1.0 km. The study was conducted in four sites with different land cover arrangements and catalogued as wetlands. The methodological approach was based on the algorithm behind the operational ET product of the Satellite Application Facility on Land Surface Analysis (LSA-SAF) initiative. The examined period comprised the end of the Spot-Végétation (Spot-V) mission and the first year of Proba-V operational modus. Two aspects were investigated: 1. The adequacy of combining observations from geostationary and Spot-V and Proba-V satellite missions for obtaining the target product; and, 2. The intercompatibility of ET estimates based on Spot-V and Proba-V so that continuous series over the operational period of both missions could be built. The comparison of simulated ET with in situ measured fluxes (eddy covariance) showed that the introduction of more spatial detail through polar-satellite observations resulted in the reduction of bias and root-mean-square error in ET estimates, as compared with estimations where Earth observation data were taken from geostationary satellites only. Moreover, the signals derived from Spot-V and Proba-V exhibited similarity during the period of operational overlap; especially in non-cultivated surfaces. This suggests that continuity objective of these two missions can be exploited in the estimation of ET time series.
               
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