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hess-24-3643-2020.pdf

🔗 Source: hess.copernicus.org

📊 Size: 5.18 MB

📄 Pages: 19 pages

⬇️ Downloads: 144

Summary

Remote sensing imagery provides snapshots of land surface variables like evapotranspiration, land surface temperature, and gross primary productivity, but discontinuous data acquisitions limit its applicability. A dynamic soil-vegetation-atmosphere transfer model, "Soil-Vegetation, Energy, water, and CO2 traNsfer" (SVEN), was developed to interpolate land surface state variables between remote sensing observations. The model combines remote sensing models with a dynamic component for ground heat flux and a water balance model, and was tested using data from an unmanned aerial system at a willow plantation in Denmark. Validation with in situ observations showed that SVEN can estimate daily land surface fluxes with normalized root mean square deviations of 11.77-19.53%. The approach can be applied to fill temporal gaps in satellite observations and estimate rapidly changing land surface variables using few forcing variables.

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Description

Remote sensing imagery provides snapshots of land surface variables like evapotranspiration, land surface temperature, and gross primary productivity, but...

Technical Information

File Format: PDF
File Size: 5.18 MB
Pages: 19
Language: EN
Total Downloads: 144
Last Updated: 1 week ago

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