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<div class="csl-entry">Schlaffer, S., Chini, M., Dettmering, D., & Wagner, W. (2016). Mapping Wetlands in Zambia Using Seasonal Backscatter Signatures Derived from ENVISAT ASAR Time Series. <i>Remote Sensing</i>. https://doi.org/10.3390/rs8050402</div>
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This article belongs to the Special Issue "What can Remote Sensing Do for the Conservation of Wetlands?"
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dc.description.abstract
Wetlands are considered a challenging environment for mapping approaches based on Synthetic Aperture Radar (SAR) data due to their often complex internal structures and the diverse backscattering mechanisms caused by vegetation, soil moisture and flood dynamics contributing to the resulting imagery. In this study, a time series of >100 SAR images acquired by ENVISAT during a time period of ca. two years over the Kafue River basin in Zambia was compared to water heights derived from radar altimetry and surface soil moisture from a reanalysis dataset. The backscatter time series were analyzed using a harmonic model to characterize the seasonality in C-band backscatter caused by the interaction of flood and soil moisture dynamics. As a result, characteristic seasonal signatures could be derived for permanent water bodies, seasonal open water, persistently flooded vegetation and seasonally flooded vegetation. Furthermore, the analysis showed that the influence of local incidence angle could be accounted for by a linear shift in backscatter averaged over time, even in wetland areas where the dominant scattering mechanism can change depending on the season. The retrieved harmonic model parameters were then used in an unsupervised classification to detect wetland backscattering classes at the regional scale. A total area of 7800 km2 corresponding to 7.6% of the study area was classified as either one of the wetland backscattering classes. The results demonstrate the value of seasonality parameters extracted from C-band SAR time series for wetland mapping.
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dc.description.sponsorship
National Research Fund of Luxembourg (FNR)
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dc.description.sponsorship
European Space Agency (ESA)
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dc.language
English
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dc.language.iso
en
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dc.publisher
MDPI
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dc.relation.ispartof
Remote Sensing
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
wetlands
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dc.subject
SAR
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dc.subject
time series
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dc.subject
Fourier analysis
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dc.subject
local incidence angle
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dc.subject
radar altimetry
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dc.title
Mapping Wetlands in Zambia Using Seasonal Backscatter Signatures Derived from ENVISAT ASAR Time Series
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dc.type
Article
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dc.type
Artikel
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
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dc.contributor.affiliation
Luxembourg Institute of Science and Technology, Luxembourg