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Remote Sens. 2016, 8(5), 402; doi:10.3390/rs8050402

Mapping Wetlands in Zambia Using Seasonal Backscatter Signatures Derived from ENVISAT ASAR Time Series

1
Department of Geodesy and Geoinformation, Vienna University of Technology, Gusshausstr. 27–29, 1040 Vienna, Austria
2
Luxembourg Institute of Science and Technology (LIST), 41, Rue du Brill, 4367 Belvaux, Luxembourg
3
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München, Arcisstr. 21, 80333 Munich, Germany
Current address: Luxembourg Institute of Science and Technology (LIST), 41, rue du Brill, 4367 Belvaux, Luxembourg
*
Author to whom correspondence should be addressed.
Academic Editors: Javier Bustamante, Alfredo R. Huete, Patricia Kandus, Ricardo Díaz-Delgado, Nicolas Baghdadi and Prasad S. Thenkabail
Received: 3 March 2016 / Revised: 18 April 2016 / Accepted: 21 April 2016 / Published: 12 May 2016
(This article belongs to the Special Issue What can Remote Sensing Do for the Conservation of Wetlands?)
View Full-Text   |   Download PDF [51155 KB, uploaded 12 May 2016]   |  

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. View Full-Text
Keywords: wetlands; SAR; time series; Fourier analysis; local incidence angle; radar altimetry wetlands; SAR; time series; Fourier analysis; local incidence angle; radar altimetry
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Schlaffer, S.; Chini, M.; Dettmering, D.; Wagner, W. Mapping Wetlands in Zambia Using Seasonal Backscatter Signatures Derived from ENVISAT ASAR Time Series. Remote Sens. 2016, 8, 402.

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