###### Abstract  
Accurate estimation and monitoring of rice phenology is necessary for the management and yield prediction of rice. The radar backscattering coefficient, one of the most direct and accessible parameters has been proved to be capable of retrieving rice growth parameters. This paper aims to investigate the possibility of monitoring the rice phenology (i.e., transplanting, vegetative, reproductive, and maturity) using the backscattering coefficients or their simple combinations of multi-temporal RADARSAT-2 datasets only. Four RADARSAT-2 datasets were analyzed at 30 sample plots in Meishan City, Sichuan Province, China. By exploiting the relationships of the backscattering coefficients and their combinations versus the phenology of rice, HH/VV, VV/VH, and HH/VH ratios were found to have the greatest potential for phenology monitoring. A decision tree classifier was applied to distinguish the four phenological phases, and the classifier was effective. The validation of the classifier indicated an overall accuracy level of 86.2%. Most of the errors occurred in the vegetative and reproductive phases. The corresponding errors were 21.4% and 16.7%, respectively. p 2018 10 340 10.3390/rs10020340 10.  
of spaceborne optical and synthetic aperture radar (SAR) sensors with a high or moderate resolution have been launched, and new approaches for the phenology study have been conceived. Optical data such as the Moderate Resolution Imaging Spectroradiometer (MODIS) [3; 14; 15; 16; 17], and HJ-1 and Landsat data [18] are used to effectively estimate rice phenology. However, an optical sensor is vulnerable to the variation of atmospheric conditions and cloud covers. Compared to the optical sensor, SAR has an all-time and all-weather imaging capability. SAR data are sensitive to surface features [19] and inundated /un-inundated rice fields [20]. Thus, SAR plays an important role in the monitoring of rice in cloudy or foggy areas. Many researchers have obtained successful results in rice planting monitoring using X-band sensors (e.g., COSMO-SkyMed and TerraSAR-X) [13; 21; 22; 23; 24; 25] and C-band sensors (e.g., Envisat-ASAR, RADARSAT-2, and Sentinel-1) [19; 20; 26; 27; 28]. After the successful launch of spaceborne SARs with short revisit periods (compared to the main phenological phases of rice with a short duration, e.g., about 16 days of reproductive phase) or polarimetric mode, the acquisition of timely and accurate information about the rice condition during the growing period became readily possible. [PERSON] et al. [5] used TerraSAR-X data to retrieve rice phenological phases with the correlation and phase difference between co-polar channels and parameters provided by polarimetric decomposition techniques. The potential of TerraSAR-X data for rice phenology monitoring has been well documented [5; 7; 21; 22; 23]. However, the penetration depth into the canopy is shallow for radar energy at a high frequency compared to that at a low frequency [29]. Therefore, the backscattering at X-band may provide less information on the structure of rice plants than that at C-band [29; 30]. [PERSON] et al. [28] have used C-band Sentinel-1A and Landsat-8 data to map multi-season paddy rice based on backscattering coefficients (\(\sigma^{0}\)) and the normalized difference vegetation index (NDVI) with a K-Means unsupervised classifier. The high temporal resolution, six days using the two-satellite constellation of Sentinel-1, makes Sentinel-1 data suitable for rice monitoring. However, Sentinel-1 SAR can only provide single or dual-pol data. Since various polarized radar backscattering coefficients respond to rice plants differently [6; 25; 31], quad-polarized data (e.g., RADARSAT-2) can supply more comprehensive information on rice growth status than single and dual-polarized data.