Modelling High-Resolution Actual Evapotranspiration through Sentinel-2 and Sentinel-3 Data Fusion

Abstract

The Sentinel-2 and Sentinel-3 satellite constellation contains most of the spatial, temporal and spectral characteristics required for accurate, field-scale actual evapotranspiration (ET) estimation. The one remaining major challenge is the spatial scale mismatch between the thermal-infrared observations acquired by the Sentinel-3 satellites at around 1 km resolution and the multispectral shortwave observations acquired by the Sentinel-2 satellite at around 20 m resolution. In this study we evaluate a number of approaches for bridging this gap by improving the spatial resolution of the thermal images. The resulting data is then used as input into three ET models, working under different assumptions: TSEB, METRIC and ESVEP. Latent, sensible and ground heat fluxes as well as net radiation produced by the models at 20 m resolution are validated against observations coming from 11 flux towers located in various land covers and climatological conditions. The results show that using the sharpened high-resolution thermal data as input for the TSEB model is a sound approach with relative root mean square error of instantaneous latent heat flux of around 30% in agricultural areas. The proposed methodology is a promising solution to the lack of thermal data with high spatio-temporal resolution required for field-scale ET modelling and can fill this data gap until next generation of thermal satellites are launched.

Feasibility of Using the Two-Source Energy Balance Model (TSEB) with Sentinel-2 and Sentinel-3 Images to Analyze the Spatio-Temporal Variability of Vine Water Status in a Vineyard

“…In this study, the PT approach was compared using LST obtained by sharpening Sentinel-2 and Sentinel-3 images (TSEB-PT S2+3 ) and from very high-resolution airborne thermal images (TSEB-PT airb ). The data sharpening method used in this study was based on the data mining sharpener (DMS) introduced by Gao et al [16] and used by Guzinski et al [13,17] with Sentinel 2 and Sentinel 3 data. This approach was also used by the European Space Agency (ESA) to develop the evapotranspiration plugin for the Sentinel Application Platform (SNAP) (www.esa-sen4et.org).…”

“…These techniques involve empirically relating TIR to VISNIR spectral signals within the same scene, at the coarse pixel resolution of the thermal band, and then applying this relationship to the fine pixel resolution VISNIR bands in order to produce sharpened thermal band imagery at the same, with high resolution [16]. Guzinski et al [17] evaluated the feasibility of sharpening daily Sentinel-3 (SLSTR sensor~1000 m TIR data) satellite data with Sentinel-2 MIS (20 m VISNIR data). They obtained an acceptable level of accuracy and improvements in the estimates of fluxes, with respect to low-resolution satellite data.…”

Editorial for the Special Issue “Remote Sensing Monitoring of Land Surface Temperature”

“…The combination of the state-of-the-art in the thermal infrared (TIR) domain [1][2][3] with the recent advances in the capabilities provided by operating and new satellites [4][5][6][7][8][9][10], UAVbased [11] or aerial remote sensing are boosting the use of land surface temperature (LST) in a variety of research fields [5,8,9,11,12]. LST plays a key role in soil-vegetation-atmosphere processes and becomes crucial in the estimation of surface energy flux exchanges, actual evapotranspiration, or vegetation and soil properties [8,9]. The latest advances in data fusion, downscaling and disaggregation techniques provide a new dimension to LST applications in water resource and agronomic management thanks to the improvement in both the temporal and spatial resolution of thermal products [8][9][10].…”

“…LST plays a key role in soil-vegetation-atmosphere processes and becomes crucial in the estimation of surface energy flux exchanges, actual evapotranspiration, or vegetation and soil properties [8,9]. The latest advances in data fusion, downscaling and disaggregation techniques provide a new dimension to LST applications in water resource and agronomic management thanks to the improvement in both the temporal and spatial resolution of thermal products [8][9][10]. However, at the same time, continuous research into LST estimation algorithms, as well as continuous calibration and validation, are still required to improve the accuracy of ground LST data and satellite LST products [1][2][3][4][5]13,14].…”

“…Published papers cover a wide range of topics, which can be classified in five groups: algorithms, calibration and validation [1][2][3][4], improving long-term consistency in satellite LST [5][6][7], downscaling LST [8][9][10], LST applications [11,12] and land surface emissivity research [13,14].…”