期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2020
卷号：V-3-2020
页码：97-104
DOI：10.5194/isprs-annals-V-3-2020-97-2020
语种：English
出版社：Copernicus Publications
摘要：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.
