Abstract
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 to retrieve 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 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.
The aim of this work was to develop a model-based retrieval algorithm from multispectral satellite data. The initial retrieval algorithm used numerical optimisation 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 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 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.
The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 721995.
The aim of this work was to develop a model-based retrieval algorithm from multispectral satellite data. The initial retrieval algorithm used numerical optimisation 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 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 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.
The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 721995.
| Original language | English |
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| Pages | 197 |
| Number of pages | 1 |
| Publication status | Published - Sep 2018 |
| Event | 10th International Conference on Ecological Informatics, ICEI 2018: Translating Ecological Data into Knowledge and Decisions in a Rapidly Changing World - Jena, Germany Duration: 24 Sep 2018 → 28 Sep 2018 Conference number: 10 https://icei2018.uni-jena.de/ |
Conference
| Conference | 10th International Conference on Ecological Informatics, ICEI 2018 |
|---|---|
| Abbreviated title | ICEI 2018 |
| Country | Germany |
| City | Jena |
| Period | 24/09/18 → 28/09/18 |
| Internet address |
Keywords
- Sentinel-3
- SCOPE model
- retrieval
- remote sensing