## Materials and Methods
### Data Preparation
#### 2.2.2 Time-Series Sentinel-1 SAR Data  
Current Sentinel-1 is a satellite constellation composed of Sentinel-1A and Sentinel-1B. These two satellites have the same orbital plane, and carry the same dual-polarization synthetic aperture radar (SAR) sensors. The working band and the frequency of these SAR are the C-band, and 5.4 GHz, respectively [60]. The Sentinel-1 satellites are the important part of the Global Monitoring for Environment and Security program (GMES, a set of earth observation missions by ESA). Two additional satellites of Sentinel-1C and Sentinel-1D will be launched to provide better all-weather, day-and-night, and continuous Earth observation services [53,61]. With a high spatial resolution (10 m) and short revisit period (12 days for one satellite, and 6 days for two satellites), Sentinel-1 is an attractive option for frequent, effective mapping of rice paddies at a large regional level.  
The Sentinel-1 satellite products covering the Mun River watershed can be obtained from the Copernicus Open Access Hub [61]. The Sentinel-1 Level-1 ground range detected (GRD) products could also be used via the Google Earth Engine platform [62] after the scenes had been preprocessed as a backscatter coefficient in decibels (dB) using the Sentinel-1 Toolbox in this study. The operations included: (1) applying the precise orbit ephemerides file to update the orbit metadata to reduce the impact of satellite orbit errors on imagery; (2) a SAR border noise removal function to remove the invalid values on imagery edges and the low intensity noise; (3) a thermal noise removal operator to reduce additive thermal noise effects; (4) a radiometric calibration step to convert the digital signal to radiometrically calibrated backscatter; and (5) orthorectification to remove the effects of scenes perspective and terrain, and get the backscatter coefficient of each pixel by using the NASA shuttle radar topography mission (SRTM) global digital elevation model (DEM) products [54,63]. To further reduce the short-term influence of speckle, high frequency signals, and other noise inherent in the Sentinel-1 data, and to further aid the extraction of the key phenological characteristics of paddy rice, the obtained time-series backscattering imagery were filtered using a multitemporal speckle filter named a Gaussian filter [52,64].  
The Sentinel-1 data ultimately used in the study had a high spatial resolution of 10 m for the study area with dual-polarization of VV (vertical transmit and vertical receive) and VH (vertical transmit and horizontal receive) in the mode of \"Interferometric Wide Swath (IW)\". The VV polarized and VH polarized data were selected for potential water information and rice mapping, respectively, because of  
Figure 2: Location of field plot data.  
their accuracy in detecting water and rice paddies [52; 53]. Finally, 402 available Sentinel-1 SAR images were acquired over the study area in 2017. The coverage frequency of the acquired data is shown in Figure 3. The high temporal resolution and wide range of dense data coverage of the Sentinel-1 mission increased and improved the mapping of rice paddies in our study.