# Detection of Temporary Flooded Vegetation Using Sentinel-1 Time Series Data
## 4 Results  
### Multi-Temporal Characteristics and Patterns of Backscatter Intensities  
The analysis of multi-temporal characteristics and patterns was performed based on preprocessed SAR time series data (see Section 3.1). For this purpose, pixels of the time series layer stacks were combined into objects using clustering methods (see Section 3.3). Objects are less susceptible to noise than pixels, and they can be used to create spatial contextual time series profiles, which allow one to derive object-related characteristics and patterns. Examples of object-based time series profiles for TOW and TFV, which were identified from the training data set acquired on 8 April 2017, are shown in Figures 5 and 6. These objects contain 1148 pixels for TOW and 1054 pixels for TFV, respectively. The box plots represent a range of the backscatter values within the segment for each date. The time series are shown for the two single polarizations VV (Figures 5a and 6a), VH (Figures 5b and 6b), and their ratio VV/VH (Figures 5c and 6c) for the same segment. In addition, the multi-temporal behaviour of the NDVI and NDWI values for the same time-period is displayed in Figures 5d and 6d and in Figures 5e and 6e, which serve as a comparison to the SAR time series data. These ratios are not integrated in the methodology as a data set. The analysed flood event image (6 April 2017) is indicated by a blue bar. Figure 5 shows the multi-temporal characteristics and patterns of the backscatter values for TOW. Compared to all other dates in the time series, a significant decrease of the backscatter values can be observed at the analysed date during the flood event (blue bar) (Figure 5a,b). The ratio of the two polarizations (Figure 5c) shows no change at the analysed date of the flood event. This indicates a similar or equal change in both polarizations. As a comparison to the SAR time series data, NDVI values were used, which were derived from the S-2 data sets. Despite the cloud-related data gap between November 2016 and March 2017, there is a comparable reduction in the NDVI values for the analysed date at the flood event. In combination with the decrease of the backscatter values, this confirms the occurrence of water at the analysed date. In addition, the NDWI shows an increase in the values at the date of flooding, which indicates the occurrence of water. Figure 6 shows an example of multi-temporal characteristics and patterns for TFV areas. Compared to TOW, TFV is characterized by an increase in the backscatter values at the analysed date in VV polarization. In contrast to the increase of the backscatter values in VV polarisation, a decrease of the backscatter values occurs in VH polarisation during the flood event (Figure 6b). The ratio between these two polarizations shows an increase for TFV at the analysed date (Figure 6c). As a comparison to the SAR time series data, NDVI values for TFV were derived from the S-2 data and are displayed for the same period (Figure 6d). At the analysed date, there is only a very slight change in the NDVI values. In addition, NDWI shows a slight increase in values, which indicates the occurrence of water in the vegetated areas. Nevertheless, the NDWI values remain in the negative range, and it seems that there are no open water areas but a mixture of standing water and vegetation. Accordingly, it can be confirmed that the increase in backscatter values in VV polarization is caused by flooding and not by any phenological changes. Overall, the increase in backscatter values for TFV in VV polarization is significantly lower compared to the decrease in the backscatter values for TOW areas. Figure 5: Multi-temporal behaviour of the backscatter intensity for TOW areas for VV (**a**), VH (**b**), the ratio VV/VH (**c**), NDVI values (**d**), and NDWI values (**e**). The blue bars mark the analysed date at the flood event. Figure 6: Multi-temporal behaviour of the backscatter intensity for TFV areas for VV (**a**), VH (**b**), the ratio VV/VH (**c**), NDVI values (**d**), and NDWI values (**e**).