## 3 Results and Discussion  
### Land-Use Change Results  
The resulting land-use maps from the ENVISAT data are presented in Figure 2. As expected, the most reliable results were based on SAR imagery, the reason being that the SAR data was multitemporal covering the whole year. As an instrument, SAR is sensitive to surface roughness and thus water surfaces such as rice paddies and aquaculture are easily detected. The multitemporal information can be used to separate the classes from each other. \begin{table}
\begin{tabular}{c c c c} \hline  & **ENVISAT Map 2005** & **ENVISAT Map 2009** & **ENVISAT Map 2011** \\ \hline \hline
**Number of images** & 13 & 15 & 9 \\
**Date begin** & 16.12.2004 & 10.1.2009 & 15.12.2010 \\
**Date end** & 4.12.2005 & 26.12.2009 & 28.3.2012 \\
**Pixel size (m)** & & 75 & \\ \hline \end{tabular}
\end{table} 
Table 4: Summary of the land-use maps derived from ENVISAT ASAR images. \begin{table}
\begin{tabular}{c c c} \hline  & **SPOT Maps** & **Landsat Maps** \\ \hline
**Satellite instrument** & SPOT 1, 3 and 4 & Landsat 3 (MSS) and 7 (ETM) \\
**Channels** & 4 & 4 (MSS), 7 (ETM) \\
**Pixel size** & 20 m & 60 m (MSS), 15 m (ETM) \\
**Maps for year** & 1987, 1998, 2005 & 1979, 2002 \\ \hline \end{tabular}
\end{table} 
Table 5: Summary of the land-use maps derived from SPOT and Landsat optical imagery. The land-use maps from SPOT are presented in Figure 3. The results from optical EO data were highly influenced by the dates of the images since the classification was based on a single image only. To get more reliable results, multitemporal (within one year) optical data would be required; however, due to the cloudiness in the area it was impossible to acquire such a data set. In addition, the spatial extent of the SPOT images was limited, which caused missing data in some districts, especially in Ben Tre. The farming practices (number of rice crops per year) might also have changed dramatically in the area when high yielding rice varieties have been adopted [41], and it is possible that the class division was not suitable for the 1979 Landsat image. Figure 2: The land-use classifications from ENVISAT ASAR imagery  
Even though the SAR data was based on multitemporal imagery, the image acquisition dates were not the most optimally distributed throughout the years 2005 and 2011. For the purposes of reliable statistical data analysis, we combined three rice classes to a single class, hereafter: \"All rice\", being the sum of \"2\(\times\) irrigated\", \"2\(\times\) rainfed\" and \"3\(\times\) irrigated rice\" crop classes in order to decrease the influence of variable image acquisition dates within a year. In order to analyze the optical imagery results, \"Rainy season shrimp and rice\" and \"Aquaculture\" were also combined to the \"Aquaculture2\" class. The Landsat results using the combined classes are presented in Figure 4.  
Thematic maps were produced from the classification result based on the SAR data for the classes \"All rice\" and \"Aquaculture\" (Figure 5). The change in hectares in comparison to the total area of a district was calculated and the map was colored accordingly. It can be noted that the most significant  
Figure 4: The land-use classifications from the Landsat imagery. Figure 3: The land-use classifications from the SPOT imagery. changes for rice have taken place in the inland districts. According to our experience during the field survey, it is highly possible that land-use changes in the coastal districts had already taken place before the year 2005. More detailed results on the land-use changes are presented for Ben Tre and Tra Vinh provinces in Figure 6. The 2011 SAR image set was lacking input data in May to December, which may have affected the detection of certain types of rice and the shrimp/rice fields. In Ben Tre, the SAR images show a decrease in the total rice average and increase in the aquaculture acreage. The acreage for \"Settled areas, coconut, sugar cane and orchard\" has increased as well.