# Mapping Irrigated and Rainfed Wheat Areas Using Multi-Temporal Satellite Data
## 4 Results
### Spatial Distribution of Irrigated and Rainfed Wheat in South Central Shanxi Province  
The spatial distribution of irrigated and rainfed wheat was scattered and staggered in most regions of south central Shanxi Province. This pattern is primarily due to the high fragmentation in wheat fields, which is different from the continuous distribution of wheat in plains (Figure 6). Furthermore, topography and water resources also influence irrigation activities. In this study, the classification results derived from satellite imagery were quantitatively evaluated against the ground reference information. First, we evaluated the ratio of irrigated-to-rainfeed wheat area. The Second Agricultural Census of Shanxi Province provides the areas of irrigated and rainfed arable land, but does not distinguish different crop types. Moreover, these census datasets were manually collected, and only the available water resources and irrigation facilities were considered, which are not equivalent to the actual irrigated area. In this case, the ratio of irrigated-to-rainfeed wheat area was used to verify the accuracy of the SVM classification result. According to census data from agricultural sectors in Shanxi Province, the ratio of irrigated-to-rainfeed wheat area was approximately 4:6, whereas our result was 4.4:5.6. Second, our classification results of irrigated and rainfed wheat in the survey sites agreed with the ground-based photographs taken from 26 to 31 May 2011. The survey photos showed that irrigated wheat is stout with dark green leaves, whereas rainfed wheat is shorter with yellow leaves and significantly slower in growth. Third, the regional spatial distribution of irrigated and rainfed wheat from this study is consistent with a visual interpretation of high spatial resolution Google Earth images, which reflect wheat growth conditions (Figure 6a,b). The discrepancies between irrigated and rainfed wheat are mainly due to water availability. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Data Sources**} & \multicolumn{6}{c}{**Google Earth Additional Testing Samples**} \\ \hline Feature vectors & \multicolumn{4}{c}{NDVI time series} & \multicolumn{4}{c}{Peak NDVI and TIN} \\ \hline Classification & Irrigated & Rainfed & Total & \
\begin{tabular}{c} User’s \\ accuracy \\ (\%) \\ \end{tabular} & Irrigated & Rainfed & Total &
\begin{tabular}{c} User’s \\ accuracy \\ (\%) \\ \end{tabular} \\ \cline{2-9} Irrigated & **349** & 20 & 369 & 94.6 & **377** & 20 & 397 & 95.0 \\ Rainfed & 39 & **366** & 405 & 90.4 & 11 & **366** & 377 & 97.1 \\ Total & 388 & 386 & 774 & & 388 & 386 & 774 & \\ Producer’s & 89.9 & 94.8 & & & 97.2 & 94.8 & & \\ Overall accuracy (\%) & 92.4 & & & & 96.0 & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Error matrix for SVM classification. TIN, time-integrated. Figure 6: Spatial distribution of irrigated and rainfed wheat in south central Shanxi Province. (**a**) is the classification of irrigated and rainfed areas for a region that containing three survey sites; (**b**) is the Google Earth image of the same region that corresponding to (**a**). Google Earth multi-spectral imagery provides topography and land cover/land use information. Water availability is influenced by topography and thus results in different wheat growth conditions. These discrepancies were clearly reflected through visual interpretation of Google Earth imagery (Figure 6b). The growth conditions of wheat planted in the majority of the northwest region were worse due to scarce water resources compared to wheat planted in the southeast. Irrigated wheat generally benefits from better growth conditions and a longer growth period compared to the rainfed wheat and, hence, has higher NDVI and TIN values (Figure 7). The spatial distribution patterns of peak NDVI and TIN agree well with the distribution of irrigated and rainfed wheat.