The research was done on synthetic data, i.e. the data was generated by models: RTMo, 6S, SCOPE and SCOPE emulator, based on gaussian process regression (gp_emulator). The results were analyzed with SALib Python package. For the sake of storage space we do not provide intermediate results. The provided data is input parameters, final results (top of atmosphere (TOC) radiance in optical domain, top of canopy (TOC) thermal radiance, land surface temperature (LST)) and sensitivity indices. Should you have any interest in the intermediate data (TOC reflectance factors, 6S atmospheric coefficients), please, contact the corresponding author
[email protected]. Links to all software packages are available in the article and are also duplicated here. SCOPE v.1.73 https://github.com/Christiaanvandertol/SCOPE docs: https://scope-model.rtfd.io RTMo retrieval algorithm https://github.com/Prikaziuk/retrieval_rtmo docs: https://scope-model.rtfd.io/en/latest/retrieval.html Py6S https://github.com/robintw/Py6S docs: https://py6s.readthedocs.io SALib https://github.com/SALib/SALib docs: https://salib.rtfd.io gp_emulator https://github.com/jgomezdans/gp_emulator docs: https://gp-emulator.rtfd.io
Global sensitivity analysis of the radiative transfer model SCOPE