SCOPE model inversion for Sentinel-3 data retrieval

Prikaziuk, Egor; Tol, Christiaan van der

The SCOPE is a coupled radiative transfer and energy balance model used for simulation of vegetation optical properties and temperature at leaf and canopy level over a spectral range from 0.4 to 50 μm. Inversion of the model allows retrieving a number of plant traits: pigments (Cab, Car, Cant), dry matter content (Cdm), water content (Cw), leaf area index (LAI) and others. Subsequent forward simulation can calculate photosynthesis, evapotranspiration (ET) and a fraction of absorbed photosynthetically active radiation (fAPAR) that can be used further for integrated water use efficiency (WUE) and light use efficiency (LUE) calculations, respectively. The higher the accuracy in retrieved parameters is achieved the higher precision in calculated ecosystem functional properties will be. This work aimed to develop a model-based retrieval algorithm from multispectral satellite data. The initial retrieval algorithm used numerical optimization of residuals squared sum and operated over the spectral range from 0.4 to 2.4 μm. First, the algorithm was extended to the thermal domain (up to 50 μm) and validated against open-source spectral measurement datasets (SPECCHIO). As the SCOPE model operates at both leaf and canopy levels, we had to use different cost functions and constraints for each level. Having validated the hyperspectral retrieval algorithm, we tried to make a convolution to the multispectral case of Sentinel-3 satellite sensors: ocean and land colour instrument (OLCI) and sea and land surface temperature radiometer (SLTR). Finally, parameter retrieved with the algorithm from Sentinel-3 images were used for a forward simulation of the SCOPE model and calculation of integrated WUE and LUE at few selected FLUXNET towers. The results of the simulation were validated against data from FLUXNET eddy-covariance towers.



Prikaziuk, Egor / van der Tol, Christiaan: SCOPE model inversion for Sentinel-3 data retrieval. Jena 2018.


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