Time series decomposition reveals impact of flooding on C-Band SAR backscatter signal in the Amazon Rainforest

Abstract

In contrast to the prevalent expectation that C-Band backscatter is only sensitive to changes in the geometry and water content of the canopy in dense tropical rain forest, there is a relationship between the Sentinel-1 VH backscatter signal and the flooding frequency of paleovarzea forests in the amazon. We use the empirical mode decomposition (EMD) - a data-driven alternative to the fourier transform - to segment the Sentinel-1 time series into multiple signals with different temporal frequencies. In this analysis we are decomposing the whole Sentinel-1 signal into fast, annual and slow oscillations. Then we analyse the annual subsignal further and compare the original signal and the annual subsignal of Sentinel-1 with the water level of the Jurua river, a nearby tributary of the amazon river. The correlation between the water level and the Sentinel-1 data can be seen as an indicator of a seasonality. We show, that the correlation of Sentinel-1 VH backscatter time series and the water level of a nearby river is higher in seasonally flooded forests than in non-flooded forests. The correlation increases when we use the annual subsignal instead of the original Sentinel-1 signal. This is in one part due to general denoising of the signal, but also due to a common driver of the seasonality in the flooded areas. In the Sentinel-1 VV signal we don't see such a relationship. There the overall correlation to the water level is higher but the correlation is not clustered on the flooded areas. This indicates, that the Sentinel-1 VV signal has an overall higher seasonality, but this seasonality is not driven by the flooding in the forests near the river. These results impact the calibration and validation of the Sentinel-1 data on the amazon forest, because we can't expect the Sentinel-1 VH signal of tropical rain forest to be homogeneous in space and time. It also influences the interpretation of the Sentinel-1 signal in general, because it indicates, that there is some contribution from the ground on the Sentinel-1 backscatter time series. We think of two explanations for the results we got. The first is, that during the flooded state of the forest there is a double bounce between the stem and the standing water from the rest of the signal which is not scattered in the canopy, and the returning waves are then depolarized again in the canopy, which increases the VH component of the signal during the flooded state, compared to the non-flooded state. The other possibility is, that during the flooded state the water content on the canopy is increased because of the standing water underneath and this increases the volume scattering. To distinguish the best explanation further research is necessary.