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

Abstract

Abstract. In this study, we analyze Sentinel-1 time series data to characterize the observed seasonality of different land cover classes in eastern Thuringia, Germany and to identify multi-temporal metrics for their classification. We assess the influence of different polarizations and different pass directions on the multi-temporal backscatter profile. The novelty of this approach is the determination of phenological parameters, based on a tool that has been originally developed for optical imagery. Furthermore, several additional multitemporal 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 polarization during summer, an increase of the backscatter in VH polarization is observed for coniferous forest. The observed seasonality is discussed together with meteorological information (precipitation and air temperature). Furthermore, a dependence of the backscatter of the pass direction (ascending/descending) is observed particularly for the urban land cover classes. Multi-temporal metrics indicate a good separability of principal land cover classes such as urban, agricultural and forested areas, but further investigation and use of seasonal parameters is needed for a distinct separation of specific forest sub-classes such as coniferous and deciduous.

Sentinel-1 Backscatter Time Series for Characterization of Evapotranspiration Dynamics over Temperate Coniferous Forests

“…It is located in the southeast of the Free State of Thuringia in central Germany. While the northwestern and southeastern regions are dominated by agricultural land cover, the center and southwest regions consist mainly of coniferous forests in the lower mountain ranges of the Thuringian Forest [35]. Four areas of interest (AOI) were defined within the study site (blue circles in Figure 1), with a radius of 5 km each.…”

European Wide Forest Classification Based on Sentinel-1 Data

“…Recently, a number of studies exploited the short revisit time of Sentinel-1 data and analysed the annual seasonality of backscatter time series over forests [15,16,24,28,29]. For instance, Dubois et al [28] described different annual seasonality for coniferous, broadleaf and mixed forest types; while the VH backscatter of the broadleaf forest decreases in spring and summer, coniferous forest showed the highest values during summer months. The same patterns were also described in [15,16].…”

“…In the case of the coniferous forests, the increase in backscattering coefficient in summer is explained twofold, depending on the canopy cover, i.e., open forest and dense forest. First, the higher water content in needles during the summer months might explain the stronger backscatter observed in this period, and second, the more developed understory layer might increase the vegetation volume scattering component [28]. The observed differences in backscatter behaviour were used for forest type mapping, showing overall accuracies of 86% in test areas in Switzerland [15], 85% in Austria and 65% to 77% in Sweden [16].…”

Investigation of Sentinel-1 Time Series for Sensitivity to Fern Vegetation in an European Temperate Forest

“…Particularly in Europe, the dense time series with a short revisit time of at least 6 days enable analyses of bio-physical vegetation dynamics at unprecedented temporal scale. Since then, seasonal behavior of Sentinel-1 backscatter time series of different natural land cover types has been observed and analyzed (Dubois et al 2020;Vreugdenhil et al 2018). The observed periodicity in signal variation can be related to different plant and soil properties that have individual (diurnal to yearly) cycles (Monteith and Ulander 2018).…”