Improved urban flood mapping: dependence of SAR double scattering on building orientation.

Urban flood mapping using SAR is an important tool for emergency flood incident management and improved flood forecasting. We have recently developed a method for detecting urban flooding using Sentinel-1 and WorldDEM data¹. This is a change detection technique that estimates flood levels using pre- and post-flood images. It searches for increased backscatter in the post-flood image due to double scattering between water and adjacent buildings, compared to that in the pre-flood image where double scattering is between unflooded ground and buildings. If φ is the angle between building and satellite direction of travel, double scattering is strongest for low φ, and falls off as φ increases. It also depends on the building height and length, the depth of flooding, the roughness of the ground surface, and the complex dielectric constants of the building wall and ground surface.

Ref. 2, modelling X-band data, concluded that the increase of double scattering was only high if buildings were roughly parallel to the flight direction. The modelling assumed isolated buildings, and in a complex urban environment any increase would be further masked due to adjacent buildings. This implies a limitation in our method, since if the falloff with φ is very rapid, this could reduce the number of flooded double scatterers detected.

We used the model of ref. [3] to estimate the post- to pre-flood radar cross section (RCS) ratio for double scatterers in Sentinel-1 C-band images. In agreement with ref. [2], this predicted that high ratios would only be obtained from building walls with φ < 10°.

However, there are limitations in the models, and as a result it was decided to carry out an empirical study to examine the relationship between the RCS ratio and φ. This was based on S-1 data from the UK floods of winter 2019/2020, using flooding in Fishlake as an example of flooding in moderate housing density, and flooding in Pontypridd as an example of flooding in dense housing. A LiDAR DSM was used to allow accurate measurement of φ.

Our results showed that, as well as flooded double scatterers (DSs) with φ < 10°, a significant number of flooded DSs with 10° < φ < 30° also produced a high RCS ratio. Our method also benefited from the predilection for building houses facing south in the northern hemisphere. As the S-1 sensor is in polar orbit, descending/ascending passes image the east/west walls of a house at low φ values. Similar arguments hold in the southern hemisphere and tropics. These effects combined to provide a sufficient density of high ratio DSs from flooded buildings to estimate an accurate average flood height for a local region. In areas of high housing density, the density of high ratio DSs from flooded buildings did fall, probably due to adjacent buildings, but was still sufficient to estimate an accurate local flood height.

1 Mason et al., JARS 15(3), 032003, (2021).

2 Pulvirenti et al., IEEE TGRS, 54(30), 1532-1544. (2016).

3 Franceshetti et al., IEEE TGRS, 40(8), 1787, 1801. (2002).