## 2 Study Area and Data
### Radarsat-2 Data  
Radarsat-2 has a C-band (approximately 5.6 cm wavelength) quad-polarized SAR sensor onboard with multiple configuration and polarization modes. Two SAR images were acquired on 4 August (descending orbit 29,446, center incidence angle of 37.2\({}^{\circ}\)) and 7 August 2013 (ascending orbit 29,482, center incidence angle of 31.1\({}^{\circ}\)), over the study area. The acquisition mode was fine quad polarization, right looking, and with a nominal spatial resolution of 8 m. The impact of different orbits is construed  
\begin{table}
\begin{tabular}{c c c c} \hline HJ-1A CCD1 & \(\alpha\) & \(L_{o}\) & \(E_{sun\lambda}\) \\ \hline
**Band 1** & 0.7696 & 7.3250 & 1914.324 \\
**Band 2** & 0.7815 & 6.0737 & 1825.419 \\
**Band 3** & 1.0914 & 3.6123 & 1542.664 \\
**Band 4** & 1.0281 & 1.9028 & 1073.826 \\ \hline \end{tabular}
\end{table}
Table 1: Absolute radiometric calibration coefficient and exoatmospheric solar irradiance for HJ-1A CCD1.  
as minimal due to the relatively flat terrain in the sampling sites. Radiometric calibrations of the Radarsat-2 images were performed using calibration tools included in the Next ESA SAR toolbox (NEST), which were provided by the European Space Agency. The images were then projected using the Universal Transverse Mercator (UTM) (Zone 48N, World Geodetic System (WGS) 84). These products were then geometrically corrected using a set of 40 control points taken from the HJ-1 CCD image, which had been accurately corrected. The control points were evenly distributed, and the RMSE was less than 1.5 pixels for both Radarsat-2 SAR images. For speckle reduction, the SAR images were filtered using the 5 \(\times\) 5 refined Lee speckle filter [29]. Finally, the pixel sizes of the Radarsat-2 fine quad images were resampled to a 30 m \(\times\) 30 m resolution to facilitate integration with the HJ-1 CCD data.  
Topography has a significant influence on the radiometric properties of SAR images [30]. In this study, 30 m resolution DEM data were used to correct terrain-induced distortions in the Radarsat-2 data. Based on the method introduced by [PERSON] [31], the backscattering coefficient of the SAR image was corrected to a reference surface:  
\[\sigma^{o}_{cor}=\sigma^{o}\times\frac{\sin\eta\cos\theta_{a}}{\sin\eta_{0}} \tag{3}\]  
where \(\sigma^{o}_{cor}\) is the topographically corrected backscattering of each pixel. \(\eta\) is the local incidence angle, \(\theta_{a}\) is the azimuth slope, and \(\eta_{0}\) is the SAR incidence angle recorded in the metadata.  
\(\eta\) was calculated as follows [32]:  
\[\cos\eta=\cos\theta\cos\eta_{0}+\sin\theta\sin\eta_{0}\cos\Delta\varphi \tag{4}\]  
where \(\theta\) is the local slope angle and \(\Delta\varphi\) is the relative azimuth angle between the local aspect and SAR azimuth.  
The azimuth slope \(\theta_{a}\) can be determined from the following relationship [19]:  
\[\tan\theta_{a}=\tan\theta\sin\Delta\varphi \tag{5}\]  
Radar shadows and layovers occur in areas with high relief and steep slopes when \(\theta>\eta_{0}\) or \(\eta>90^{\circ}\)[19]. The topographic effects were irreversible in areas with layovers and shadows. These areas (less than 3.5% in this study area) were masked out in the process.