## 4 Discussion  
### Targeted ROI Processing Approach  
Mapping rice fields at a fine resolution is challenging when applied to large areas such as Peninsular Malaysia. A targeted ROI processing approach was applied to reduce computational costs. This approach also allows the running of the algorithm in parallel. Rice field locations can be obtained from agricultural statistics such as those of the local government [46] or international organizations--for example, rice maps in Asia from the International Rice Research Institute (IRRI) [40]. As the rice-growing areas in Malaysia \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multicolumn{10}{c}{**Selangor cropping calendar—Granary area schedule from government agency**} \\ \hline Rice & \multirow{2}{*}{1/20} & \multirow{2}{*}{2/20} & \multirow{2}{*}{3/20} & \multirow{2}{*}{4/20} & \multirow{2}{*}{5/20} & \multirow{2}{*}{6/20} & \multirow{2}{*}{7/20} & \multirow{2}{*}{8/20} & \multirow{2}{*}{9/20} & \multirow{2}{*}{10/20} & \multirow{2}{*}{11/20} & \multirow{2}{*}{12/20} \\ Group & & & & & & & & & & & \\ \hline
1 & & T & V & R & M & & T & V & R & M & \\ \hline
2 & T & V & R & M & & T & V & R & M & & \\ \hline
3 & & & & T & V & R & M & & & T & V & R \\ \hline
4 & & & T & V & R & M & & T & V & R & M \\ \hline \multicolumn{10}{c}{**Selangor cropping calendar—This study data**} \\ \hline
1 & & T & V & R & M & & T & V & R & M & \\ \hline
2 & T & V & R & M & & & T & V & R & M & \\ \hline
3 & M & & & T & V & R & M & & T & V & R \\ \hline
4 & & & T & V & R & M & & T & V & R & M \\ \hline \multicolumn{10}{c}{**Kedah cropping calendar—Granary area schedule from government agency**} \\ \hline
1 & & & & T & V & R & M & & T & V & R \\ \hline
2 & & & T & V & R & M & & T & V & R \\ \hline \multicolumn{10}{c}{**Kedah cropping calendar—This study data**} \\ \hline
1 & R & M & & T & V & R & M & & T & V1 & V2 \\ \hline
2 & M & & T & V1 & V2 & R & M & & T & V1 & V2 \\ \hline \end{tabular}
\end{table} 
Table 4: Comparison of cropping calendars from granary area schedules and this study. Table 4 corresponds to Figure 6a,b. Table 4 corresponds to Table S1. T = Tillage, V = Vegetative-1, V2 = Vegetative-2, R = reproductive, M = Maturity, F (blank) = Fallow. Orange colour is the main season and green colour is the off season. Figure 7: Aggregated planted and harvested rice area in Peninsular Malaysia. Figure 7 corresponds to Table S1. are known, the ROI can be generated for every known area. This approach significantly reduced the processing time as the classification process focused on the known rice areas to pinpoint and refine rice fields. The targeted ROI processing approach also reduced commission errors and \"salt and pepper\" effects. Conventionally, non-rice areas are masked using heuristic rules to reduce the salt and pepper effect. For example, masking areas with a slope greater than 5\({}^{\circ}\) to remove steep terrain areas that are unsuitable for rice [40; 62]; masking forest lands using Global PALSAR Forest Map 2017 [63; 64]; excluding wetlands because paddy rice fields and wetlands have similar characteristics in flooding signals [65; 66]; or masking sparse and natural vegetation using annual maximum vegetation index values that are less than 0.3 [35]. Although non-rice areas were reduced, other land covers may still be included in the data processing. As a result, the resulting maps still had a large amount of noise, as demonstrated by a comparison between the rice map of this study and that of NESEA-Rice10 [40] in Selangor State, Malaysia (Figure 8d). The map produced in this study shows a clearer separability between rice and non-rice areas such as roads, irrigation channels, built-up areas, and other vegetation covers (Figure 8a,b). The salt and pepper effects were significantly reduced (Figure 8c). We can see that in NESEA-Rice10, some waterbody and other vegetation covers were misclassified as rice fields (Figure 8d), which led to an overestimation of rice field extent. The targeted ROI processing approach also reduced the image processing time.