## 3 Results
### Validation  
#### 3.2.1 UAVSAR Data Classification  
Sentinel-1 satellites and C-band SAR sensors are limited in their ability to penetrate the vegetation canopy to sample the underlying structure of the vegetation and surface. To validate flood detections and to develop an understanding of C-band capabilities, L-band UAVSAR datasets from Hurricane Harvey were used to compare the C- and L-band observations and to refine the flood detections derived based on Sentinel-1 datasets. Unsupervised classifications based on the Freeman-Durden Polarimetricdecomposition [76] of the UAVSAR acquisitions for Hurricane Harvey were analyzed to validate the detected floodwaters beneath dense vegetation/canopy covers using the Sentinel-1 based datasets and techniques. Two fully polarimetric UAVSAR images adjacent to the courses of the San Jacinto and Brazos rivers and their surrounding areas were selected (Table 1) because of the prevalence of various forms of dense vegetation cover, as noted on the NLCD 2016 product (Figure 1b). Figure 6 shows a comparison of the results of the UAVSAR-based classification and Sentinel-1-derived flood detection for three localities in the study area. Sites I (George Bush Park area), II (Cedar Bayou Woods area), and III (near [PERSON]'s city) are covered with a wide variety of sparse-to-dense vegetation (Figure 1b) with a wood and canopy structure that might limit the penetration depth of the C-band signals.  
The unsupervised classification of the L-band UAVSAR imagery revealed that high values (>0.2) for the Dbl compared to the Odd and Vol components were observed for the selected sites, denoting the presence of floodwaters within and on the outskirts of the vegetated areas. For instance, the polarimetric classification of [PERSON]'s city (Figure 6d) that lies along the course of Brazos River distinctly classified water from Brazos River (near-zero Dbl scattering) from the floodwater beneath vegetation, as demonstrated by high Dbl scattering values (>0.2). Similarly, we analyzed the spatial correlation between the floodwater pixels detected using the CCD- and UAVSAR-based approaches for Site II (Figure 6) after resampling the UAVSAR classification product to the resolution of the CCD product. The analysis showed that close to 62% of the pixels classified by the UAVSAR as flooded (Dbl > 0.2) were detected by the Sentinel-1 based floodwater detection approach. The fact that the UAVSAR classification is based on data acquisition following a single event, while the CCD-based assessment is generated using datasets from two events, could be a plausible reason for the moderate level of correlation observed between the two results. The discrepancy in spatial resolution between the products even though resampling was carried out could have also led to a slight offset between the pixels, thereby reducing the spatial correlation between the products. Potential errors or ambiguity emanating either from the acquisition and calibration of the UAVSAR data [81] or from the misclassification of pixels [82] could have contributed to the observed moderate correlation with the C-band SAR result. A qualitative comparison of the Sentinel-1-derived results with the L-band UAVSAR-based method in the selected sites is shown in Figure 6a-d. In general, the C-band-based flood detection method (for inundated vegetation) largely corresponds well with the L-band UAVSAR-based detection in all of the selected sites (Figure 6a-d), indicating the effectiveness of the developed method for identifying floodwaters, even in the presence of dense-to-sparse vegetation cover over the surface.