Characterization of Land Cover Seasonality in Sentinel-1 Time Series Data

Abstract

In this study, we analyse Sentinel-1 time series in order to characterise the observed seasonality of different land -cover classes in East-Thuringia, Germany and identify multi-temporal metrics for their classification. We consider different polarisations and different pass directions in order to assess their influence onf the multi-temporal backscatter profile. The observed seasonality is discussed together with meteorological information (precipitation & air temperature). The novelty of this approach is the determination of phenological parameters, like xxx, based on a tool that has been originally developed for optical imagery. Furthermore, several additional multi-temporal metrics are determined for the different classes, in order to investigate their separability for potential multi-temporal classification schemes. The results of the study show a seasonality for vegetation classes, which differs depending on the considered class: whereas pastures and broad-leaved forests show a decrease of the backscatter in VH polarisation during summer, an increase of the backscatter in VH polarisation is observed for coniferous forest in summer. Furthermore, a dependence of the backscatter of the pass direction (ascending /descending) is observed particularly for the urban land cover classes, whereas no difference is observed for other land-cover classes. Multi-temporal metrics indicate a good separability of principal land-cover classes, but further investigation and use of seasonal parameters is needed for a distinct separation of specific sub-classes. Theis analysis of the multi-temporal signature of Sentinel-1 backscatter data is a preliminary requisite for further physical modelling, i.e. quantify the respective impact of all influence factors on the Sentinel-1 backscatter signal using e.g. radiative transfer models.