# Downscaling of Remote Sensing Soil Moisture Products That Integrate Microwave and Optical Data
## 2 Materials and Methods
### Data
#### 2.2.2 Auxiliary Data  
MODIS is a medium-resolution imaging spectrometer launched by NASA and mounted on the Aqua and Terra satellites. MODIS obtains mainly target images of land and ocean temperatures, primary productivity, land surface coverage, clouds, aerosols, water vapor, and fire conditions. The MODIS data selected in this study include albedo (ALB), leaf area index (LAI), LST, and NDVI. Among them, NDVI and LAI were synthesized with the maximum value to reduce the impact of missing values and clouds. The remaining data were synthesized by average value to reduce the influence of errors. The details of the dataset are shown in Table 1.  
The SRTM data are terrain elevation data jointly measured by NASA and the Department of Defense's National Survey and Mapping Agency (NGA). Topography has a significant effect on the spatial distribution of soil moisture. This study used the slope calculated from the bands from SRTM as one of the auxiliary data, referred to as SLOPE.  
Sentinel-1 is an Earth observation satellite in the European Space Agency's Copernicus program. This satellite consists of two C-band synthetic aperture radars for land and ocean observation. Sentinel-1 is used mainly to monitor the marine environment, soil moisture content, land changes, and surface conditions, such as earthquakes [26]. The first-level product consists mainly of multi-view intensity data related to the backscattering coefficient, including horizontal polarization (HH), vertical polarization (VV), and cross-polarization (HV/VH), which can reflect the soil moisture changes in time and space [27; 28]. Sentinel-1 can provide high-resolution surface information and can capture soil moisture changes in a small area, especially in complex terrain or land use types. SAR signals are very sensitive to changes in soil moisture, especially when soil moisture is low, and can effectively reflect the moisture status of the soil. The data used in this study include the GRD dataset provided by the GEE, and the data of two polarization methods, \"VV\" and \"VH\", were selected.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dataset** & **Abbreviation** & **Spatial Resolution/m** & **Time Resolution/Day** & **Aggregation** \\ \hline SPL4 SMGP & SMAP\_10 km & 10,000 & 1 & mean \\ MODIS/061/MCD43A3 & ALB & 500 & 1 & mean \\ MODIS/061/MOD15A2H & LAI & 500 & 1 & max \\ MODIS/061/MCD12Q1 & LC & 500 & 365 & mean \\ MODIS/061/MOD11A1 & LST & 1000 & 8 & mean \\ MODIS/061/MOD13A2 & NDVI & 1000 & 16 & max \\ COPERNICUS/S1\_GRD & VV & 10 & 12 & mean \\ COPERNICUS/S1\_GRD & VH & 10 & 12 & mean \\ CGIAR/SRTM90\_V4 & SLOPE & 90 & & mean \\ LANDSAT/LC08/C02/T1\_L2 & NDVI/LST & 100 & 15 & max/mean \\ \hline Periods & & 2019.7–2019.10/2020.7–2020.10 & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: The source, abbreviation, resolution, time range, and data aggregation method of the experimental data selected in this study.  
Landsat is a series of land satellites jointly managed by NASA and the United States Geological Survey (USGS) and is designed to investigate underground mineral deposits, marine resources, and groundwater resources. Landsat 8 was launched in February 2013 and covers the world every 16 days with a spatial resolution of 30 m. In order to obtain auxiliary data with 100 m resolution, this study synthesized and resampled the bands of Landsat 8.