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

Dubois, Clémence and Müller, Marlin and Pathe, Carsten and Jagdhuber, Thomas and Cremer, Felix and Thiel, Christian and Schmullius, C. (2020) Characterization of Land Cover Seasonality in Sentinel-1 Time Series Data. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. ISPRS. XXIV ISPRS Congress, 4-10 July 2020, Nice, France. ISSN 2194-9042.

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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.

Item URL in elib:https://elib.dlr.de/140347/
Document Type:Conference or Workshop Item (Speech)
Title:Characterization of Land Cover Seasonality in Sentinel-1 Time Series Data
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Dubois, Clémenceclemence.dubois (at) uni-jena.deUNSPECIFIED
Pathe, CarstenCarsten.Pathe (at) dlr.deUNSPECIFIED
Jagdhuber, ThomasThomas.Jagdhuber (at) dlr.dehttps://orcid.org/0000-0002-1760-2425
Cremer, FelixFelix.Cremer (at) dlr.dehttps://orcid.org/0000-0001-8659-4361
Thiel, ChristianChristian.Thiel (at) dlr.dehttps://orcid.org/0000-0001-5144-8145
Schmullius, C.c.schmullius (at) uni-jena.deUNSPECIFIED
Date:4 July 2020
Journal or Publication Title:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Series Name:Proceedings of ISPRS
Keywords:Sentinel-1, C-band, vegetation, soil, land-cover, time series, seasonality, multi-temporal, phenology
Event Title:XXIV ISPRS Congress
Event Location:Nice, France
Event Type:international Conference
Event Dates:4-10 July 2020
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:other
DLR - Research area:Raumfahrt
DLR - Program:R - no assignment
DLR - Research theme (Project):R - no assignment
Location: Jena
Institutes and Institutions:Institute of Data Science > Citizen Science
Deposited By: Thiel, Christian
Deposited On:12 Jan 2021 15:31
Last Modified:12 Jan 2021 15:31

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