## Material and Method  
### Study Site and Data  
The north China region belongs to a natural geographic region, referring to the northern part of the Qinling Mountains-Huaihe River Line and the southern part of the Great Wall. The study area was in north China between 109\({}^{\circ}\)39\({}^{\prime}\)03\({}^{\prime\prime}\)-120\({}^{\circ}\)54\({}^{\prime}\)40\({}^{\prime}\) E and 34\({}^{\circ}\)20\({}^{\prime}\)17\({}^{\prime\prime}\)-46\({}^{\circ}\)40\({}^{\prime}\)48\({}^{\prime\prime}\) N. The study area includes five provinces (Beijing, Tianjin, Hebei, Shanxi, and Central Inner Mongolia) and covers a total area of 386,401.77 km\({}^{2}\) (Figure 1). With a semi-humid climate, light conditions in north China are abundant; the winter is cold, dry, and long; the surface temperature in summer is high; and precipitation is relatively heavy [21]. The soil type in this area is brown soil, which mainly produces wheat. The land-use type in the research area is mostly grassland and cropland, accounting for more than 70% of the total area. Cropland is distributed in the North China Plain, whereas grassland is mainly distributed on the Loess Plateau. Woodland appears in the central part of Hebei province and southern part of Shanxi Province. Construction land is mainly distributed around the capital cities of Beijing and Tianjin (Table 1). The image layer was set to the Universal Transverse Mercator (UTM) coordinate system, which is the coordinate system for all of the data that is used in this study. The land-use image was divided into 500 \(\times\) 500 m grids, which were used to analyze the spatial distribution characteristics of temperature and vegetation cover. The land use in each grid was determined by the dominant land-use type, because the type of land in a grid may contain multiple land uses. In this study, SMAP Level-3 (L3) soil moisture product from May 2016 to May 2017 were obtained as a baseline for data downscaling, which provided a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer. In order to cover the study area, three days of synthetic images were used as the basic data [22]. SMAP observations further improved soil moisture assimilation estimates, because SMAP operates at the L-band, whereas Advanced Microwave Scanning Radiometer (AMSRE) and Advanced Scattermeter (ASCAT) retrievals are based on the X-band (10.7 GHz) and C-band (5.3 GHz), respectively. SMAP offers observations at higher resolutions that are less affected by radiofrequency interference than those from soil moisture and ocean salinity (SMOS) [23]. Project for On-Board Autonomy (_PROBA-V_) data and Moderate Resolution Imaging Spectroradiometer (_MODIS_) data were used to calculate the downscaling factor in the downscaling process. This study used annual average of Daily composite (S1) Top of Canopy _PROBA-V_ (TOC) data on between 1-3 May in 2016 and 2017 in the soil moisture downscaling process, which registered in four spectral bands: blue (centered at 0.463 \(\upmu\)m), red (0.655 \(\upmu\)m), near-infrared spectrum (NIR; 0.837 \(\upmu\)m), and shortwave (length) infrared spectral bands (SWIR; 1.603 \(\upmu\)m). Observations were taken at resolutions between 100-180 m at nadir up to 350 m and 660 m at the swath extremes for the VNIR (visible and near-infrared) and SWIR channels, respectively [24]. Table 2 lists the radiometric characteristics of the _PROBA-V_ spectral bands. Intersensor differences in the individual band reflectance and the Normalized Difference Vegetation Index (_NDVI_) are summarized in Table 3.  
Differences were identified between the individual spectra, which were largest for the SWIR band. For the NIR and red bands, differences between _PROBA-V_ and VGT-1 were of the same order of magnitude as those of VGT2-VGT1, leading to similar _NDVI_ differences.