## Appendix A Multifactorial Statistic Factor Selection (MFS) Process
(2011) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) for quantifying uncertainties in coarse resolution satellite and model products. _Hydrol. Earth Syst. Sci._**2011**, _15_, 2303-2316. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Status of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009-2019) surface soil moisture dataset. _Earth Syst. Sci. Data_**2021**, _13_, 3075-3102. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. Rebuilding a Microwave Soil Moisture Product Using Random Forest Adopting AMSR-E/AMSR2 Brightness Temperature and SMAP over the Qinghai-Tibet Plateau, China. _Remote Sens._**2019**, _11_, 683. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. Uncertainty analysis of eleven multisource soil moisture products in the third pole environment based on the three-corned hat method. _Remote Sens. Environ._**2021**, _255_, 112225. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. Global Land Surface Fractional Vegetation Cover Estimation Using General Regression Neural Networks From MODIS Surface Reflectance. _IEEE Trans. Geosci. Remote Sens._**2015**, _53_, 4787-4796. [CrossRef]
* [PERSON] et al. (2016) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Long-Time-Series Global Land Surface Satellite Leaf Area Index Product Derived From MODIS and AVHRR Surface Reflectance. _IEEE Trans. Geosci. Remote Sens._**2016**, _54_, 5301-5318. [CrossRef]
* [PERSON] et al. (2013) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Preliminary evaluation of the long-term GLASS albedo product. _Int. J. Digit. Earth_**2013**, \(6\), 69-95. [CrossRef]
* [PERSON] and [PERSON] (2012) [PERSON]; [PERSON] A microwave-optical/infrared disaggregation for improving spatial representation of soil moisture using AMSR-E and MODIS products. _Remote Sens. Environ._**2012**, _124_, 259-269. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A method based on temporal component decomposition for estimating 1-km all-weather land surface temperature by merging satellite thermal infrared and passive microwave observations. _IEEE Trans. Geosci. Remote Sens._**2019**, _57_, 4670-4691. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON] A practical reanalysis data and thermal infrared remote sensing data merging (RTM) method for reconstruction of a 1-km all-weather land surface temperature. _Remote Sens. Environ._**2021**, _260_, 112437. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON] A framework for the retrieval of all-weather land surface temperature at a high spatial resolution from polar-orbiting thermal infrared and passive microwave data. _Remote Sens. Environ._**2017**, _195_, 107-117. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A Thermal Sampling Depth Correction Method for Land Surface Temperature Estimation From Satellite Passive Microwave Observation Over Barren Land. _IEEE Trans. Geosci. Remote Sens._**2017**, _55_, 4743-4756. [CrossRef]
* [PERSON] and [PERSON] (2015) [PERSON]; [PERSON] [PERSON]; [PERSON] Evaluation of soil moisture downscaling using a simple thermal-based proxy--The REMEDHUS network (Spain) example. _Hydrol. Earth Syst. Sci._**2015**, _19_, 4765-4782. [CrossRef]
* [PERSON] et al. (2016) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Impact of day/night time land surface temperature in soil moisture disaggregation algorithms. _Eur. J. Remote Sens._**2016**, _49_, 899-916.