## 4 Experimental Result and Discussion
### Rice Mapping
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Province/City** & **Statistical Area (ha)** & **Predicted Area (ha)** & **Diff(ha)** & **Diff(\%)** \\ \hline Thai Binh & 79,319 & 80,320 & 1001 & 1.26 \\ Quang Ninh & 16,500 & 27,165 & 10,665 & 64.64 \\ Vinh Phuc & 30,837 & 29,574 & \(-1263\) & \(-4.09\) \\ Bac Ninh & 37,890 & 34,306 & \(-3584\) & \(-9.40\) \\ Ha Noi & 93,314 & 90,675 & \(-2639\) & \(-2.82\) \\ Nam Dinh & 73,936 & 78,868 & 4932 & 6.67 \\ Ninh Binh & 40,600 & 44,615 & 4015 & 9.88 \\ Hai Phong & 34,163 & 34,355 & 192 & 0.56 \\ Hung Yen & 33,374 & 32,433 & \(-941\) & \(-2.81\) \\ Hai Duong & 58,464 & 56,449 & \(-2015\) & \(-3.44\) \\ Ha Nam & 31,270 & 33,451 & 2181 & 6.97 \\
**Total** & **529,667** & **542,211** & **12,544** & \(-2.37\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: A comparison of rice area according to statistics and classification at the provincial level. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Data** & **OA(\%)** & **F1—Rice** & **F1—Non-Rice** & **F1—Average** & **Kappa** \\ \hline VV Time-series & 82.90 & 0.77 & 0.86 & 0.83 & 0.64 \\ VH Time-series & 88.48 & 0.85 & 0.91 & 0.88 & 0.76 \\ \(\frac{VV-VH}{VV+VH}\) Time-series & 78.40 & 0.73 & 0.82 & 0.78 & 0.55 \\ VVVH Time-series & 90.50 & 0.87 & 0.92 & 0.90 & 0.80 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Rice map classification evaluation over four feature datasets. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Data** & **Measures** & **Rice** & **Non-Rice** \\ \hline VV Time-series & Precision & 0.81 & 0.74 \\  & Recall & 0.84 & 0.89 \\ VH Time-series & Precision & 0.86 & 0.90 \\  & Recall & 0.85 & 0.91 \\ \(\frac{VV-VH}{VV+VH}\) Time-series & Precision & 0.71 & 0.83 \\  & Recall & 0.75 & 0.81 \\ VVVH Time-series & Precision & 0.91 & 0.90 \\  & Recall & 0.84 & 0.94 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Precision and recall for rice classification over four feature datasets. Moreover, a comparison of our results with other studies in the RRD was conducted and is shown in Table 7. Most of the previous studies did not consider Quang Ninh province. Unlike other provinces in the region, Quang Ninh has a high and hilly terrain, which should affect the rice classification model more than most of the remaining provinces with the lower terrains. In comparison to the statistics, our rice map difference is 1879 ha which corresponds to 0.3% in total if excluding Quang Ninh province, since the largest error of about 10,665 ha was reported above. Besides, our rice area estimation difference compared to the statistics was more positive than the available studies in the  
Figure 6: Correlation coefficient of estimated rice area to GSO statistics at province level in the RRD. Figure 7: Rice map of winter-spring season in 2018 in the RRD region. RRD [29; 30; 33] (see Table 7). For SAR data, [PERSON] et al. reported that the maximum planted area for all seasons in 5 years from 2007 to 2011 for 10 provinces excluding Quang Ninh with a total difference compared to the statistical database of 67,500 hectares (from 900 hectares to 20,400 hectares) [33]. In the study, rice maps were derived from Envisat ASAR Wide Swath (WS) data using a threshold-based approach with an OA of 83.9%. In 2016, [PERSON] et al. employed an RF classifier to produce a rice map from S1A imagery for 5 provinces in the RRD (i.e., Vinh Yen, Hung Yen, Bac Ninh, Ha Noi, Ha Nam) with the maximum OA of 93.5% with VVVH feature [30]. The estimated rice area reported in the study is 216,784 hectares for 2016, which is about 18,916 hectares of difference in comparison to GSO statistics. Regarding optical satellite images, Landsat 8 was used with the XGBoost classifier to obtain a rice map for the RRD in 4 years from 2013 to 2016 excluding Quang Ninh [29]. The rice maps in the study were underestimated in the statistics (38,216-80,554 hectares from 2013 to 2016). Despite the high accuracy (89.42%-91.53% of OA), the difference is still large, especially for the rice map in 2016.