## 2 Materials and Methods
### Training Data Generation
#### 2.5.2 Inundated Forest Training Data Mask  
Following the conceptual model outlined in Section 2.4.1, training data for the Inundated Forest class can be defined where there has been an increase in HH backscatter (due to the double bounce backscatter mechanism), but no increase in backscatter in the cross-polarised HV channel [28]. As such, time series metrics were used to generate a measure of inundation potential and a rule base was applied to each image tile to extract training data pixels. First, the normalised polarisation difference ratio of the HH and HV channels was calculated (NPDI) [23; 24], designed to exploit the differences in HH and HV backscatter associated with a double-bounce backscatter signature.  
Inundation potential was defined using the per-pixel NPDI variation through the time series of available ALOS-2 PALSAR-2 data. As per the conceptual model, it is assumed the most variable NPDI pixels through time are a result of seasonal inundation. Consequently, selecting all pixels with a per-pixel NPDI variance greater than the 80 th percentile defined an area where inundation would be expected to occur within wet season imagery. The 80 th percentile was selected using visual sensitivity analysis, being restrictive enough to select 'pure' inundated forest pixels, whilst sampling the range of backscatter characteristics within this class.  
A split-based thresholding technique [24] was applied to the NPDI band of each input ALOS-2 PALSAR-2 tile to calculate a threshold value used to separate areas of low NPDI value (corresponding to inundated forest) from other landcover. This was constrained by the inundation potential layer to ensure that subsequent training data samples include pixels that have a low NPDI value but are also highly variable in backscatter over time.  
The sensitivity of a SAR system to detect inundation underneath a vegetation canopy is also dependent on the angle of incidence, which varies between 25.7\({}^{\circ}\) in the near range and 49.0\({}^{\circ}\) in the far range of a PALSAR-2 ScanSAR swath. Due to the nature of the ALOS-2 orbit characteristics, areas in the overlap zones between neighbouring ScanSAR swaths are imaged twice within 5 days, within the same orbit cycle, at different (10-15\({}^{\circ}\)) incidence angles. Smaller incidence angles (steep) are more suitable than larger incidence angles (shallow), because the radar pulse has less vegetation canopy to travel through and, therefore, has a greater chance of obtaining a strong signal from underneath the canopy [26]. Conversely, at larger (shallower) incidence angles, the radar pulse is more susceptible to attenuation of the signal prior to any double bounce backscatter scattering [26]. As such, the incidence angle has a control on the backscatter values over inundated forests, particularly in the HH channel.  
The influence of larger incidence angles on the ability to detect inundated forests was addressed by increasing the NPDI threshold calculated from the Split Based Thresholding technique by 0.1, where the median incidence angle value within the ALOS-2 PALSAR-2 ScanSAR tile is greater than 40\({}^{\circ}\).