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Assessment of Multi-temporal Radar Imagery in Mapping Land System for Rainfed Lowland Rice in Northeast Thailand SAR Image Analysis and Interpretation Temporal Signature Analysis The analysis of temporal backscatter was based on the understanding of the radar scattering mechanism of wave-rice-water interaction. Knowledge of rice plant morphology, cultivating practices and rice field environment at different growth stages are required. In the area of sufficient water supply, the so-called inundated rice field, the radar backscatter generally increases with time after planting rice. During the sowing or transplanting period, rice is detected by radar as water surface. This interaction gives very low radar response due to specular reflection. As the plants develop tillers during the early vegetative stage, they expand both horizontally and vertically and the radar backscatter increases due to direct scattering of rice plants and multiple reflections between the plants and water surface. At the late vegetative stage before full coverage of the rice canopy where penetration of radar waves to the water surface is still possible, the radar backscatter peaks due to volume scattering of rice biomass and multiple reflections as an interaction between vertical plant structures and horizontal water surface. During the reproductive stage, the plants develop heads, forming panicles and flowering. As there is no significant change in plant biomass, height and density, volume scattering dominates; however wave penetration to water underneath the rice plants decreases leading to a slight decrease, in radar responses. As the crop ripens the plants’ water content decreases which causes a further slight decrease in the radar backscatter. Theoretical simulation (Le Toan et al., 1997) shows that the scattering mechanism is dominated by double scattering between the water surface and the rice plants. The backsccattering coefficient is found to increase from –16 dB to about –8 dB at the saturation level in the case of irrigated rice. Temporal backscatter profiles of land system units; floodplain, lower low-terrace, upper low-terrace, middle terrace, and irrigated low terrace rice areas are presented in Figure 1 (a-e).
Temporal Signature Changes The temporal signature changes are evaluated to examine the extent to which they can be used to establish a general rule or to modify the temporal signature profiles and perhaps give better results. The evaluation is made in two periods, within (from July to November) and beyond (June and January) the rice season (Table 2 and Figure 2). Within the rice growing season from July to November, floodplain rice shows high temporal change from –16 to –6 dB (about 10 dB) which coincides with the theoretical curve of irrigated floodplain as in the study of Le Toan et al,.1997. The signature profiles of the lower low-terrace 1 (LL1) and the lower low-terrace 2 (LL2) have moderately high temporal changes from –12 to –6 dB (6 dB) whereas the upper low-terrace 1 (UL1) has moderate temporal change from –12 to –7 dB (5 dB) and the upper low-terrace 2 has moderately low temporal change from –11 to –7 dB (4 dB). All these temporal changes can be considered in general as medium changes (4-6 dB) and can be explained by the increase in the backscatter responses from the planting (flooded condition) to maturity stages. The irrigated low terrace signature profile has less temporal change from –11 to –8 dB (about 3 dB). The irrigated low terrace in the study area does not behave as the usual irrigated rice field because of shallow sandy soil (50 cm depth) that is ineffective in holding water. The rice plants do not benefit much from the irrigation system during the growing season and is largely dependent upon rain water. The middle terrace signature profile has a low temporal change from –9 to –8 dB (1 dB difference) due to lack of image at the planting period. Beyond the rice growing season, after harvest (January), the floodplain and the irrigated low terrace show high backscatter values at –6 and –8 dB, respectively which indicate a wet soil condition. The land preparation in June showed high signature variability due to surface water and cultivation practices. Image Selection Classification scheme is decided based upon the temporal signature pattern of the most appropriate dates of SAR images. The July image can be used to distinguish floodplain and middle terrace from the other classes; January image; floodplain and irrigated low terrace; September image; the lower low-terrace 1 (the early season rice); October image; the lower low-terrace 2; June image; the backscatter values are quite separable and used for the upper low-terrace 2 and also to improve classification accuracy; November image does not give much information (Figure 2). Classification Results and Discussion From the prior discussion, floodplain and middle terrace were easily separable on the July image, lower low-terrace 1 on the September image, lower low-terrace 2 on the October image, irrigated low terrace on the January image, and upper low-terrace 2 on the June image. Upper low-terrace 1 did not show any distinct temporal signature, so it was a class that required separation using temporal pattern. From this point, it can be concluded that the separation into seven land system classes requires at least five SAR images; three images within the rice growing season in July, October and September, and two images, one after harvesting in January and the other at the land preparation period in June. The classified image was assessed using a set of ground truth information derived from the GIS land system map (Figure 4) which was created using the same criteria as defined in the characterization of the land system units (Section 2). The overall accuracy obtained from the error matrix showed 73.8%. The accuracy increased to 84.7% when applied with 6 images. As for practical application to rice growing, it might be more appropriate to map the land system into five units by having two units of low terrace, namely, lower and upper low-terraces with the remaining classes. The accuracies obtained for five classes using five and six SAR images are 88.4% and 91.2% respectively. To generalize the mapping units into broad categories of four classes that focused on one combined unit of low terrace and the remaining classes, the accuracy was higher than 90% either applied with 4, 5 or 6 images. In mapping detailed land system units (seven classes), accuracy for individual units based on four, five, and six images. The floodplain shows high producers’ accuracy but low users’ accuracy due to the main reason that ground truth information derived from GIS land system map at 1:100,000 scale may not be detailed enough to derive the narrow strip shape of floodplain in the area. Mapping accuracy for lower low-terrace 1 does not show much improvement either classified with four, five or six images. The accuracies for lower low-terrace 2 and upper low-terrace 1 improve significantly when classified with five or six images whereas the upper low-terrace 2 also improve significantly when classified with six images. The middle terrace gives similar accuracy either classified with 4, 5 or 6 images. The irrigated low terrace significantly improves when using five or six images. Various classified images based on combination of broad and detailed categories of land system for rice and numbers of multi-temporal ERS-2 data (four, five, and six images) are presented in Figures 3-a, 3-b and 3-c. |
