Multi-Temporal Speckle Filtering of Polarimetric P-Band SAR Data over Dense Tropical Forests: Study Case in French Guiana for the BIOMASS Mission
The purpose of this paper is twofold, considering first the generalization of a multichannel speckle filter in order to handle temporal stacks of polarimetric SLC SAR data, and secondly the development of an ad hoc performance indicator based on the Polarimetric Orientation Angle (POA) in order to b...
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Veröffentlicht in: | Remote sensing (Basel, Switzerland) Switzerland), 2021-01, Vol.13 (1), p.142 |
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Zusammenfassung: | The purpose of this paper is twofold, considering first the generalization of a multichannel speckle filter in order to handle temporal stacks of polarimetric SLC SAR data, and secondly the development of an ad hoc performance indicator based on the Polarimetric Orientation Angle (POA) in order to better estimate the resulting speckle reduction than the standard Equivalent Number of Looks (ENL) over densely vegetated regions, like tropical forests. Being based on the ability of PolSAR measurements to retrieve ground slopes through dense vegetation, this performance indicator requires the use of low frequencies such as P-band, as well as fully polarimetric data. This study has thereby a particular interest in the context of the upcoming BIOMASS spaceborne mission whose launch is scheduled in 2023, and makes use of data from the TropiSAR airborne campaign initiated in the early stage of the mission developments. Conducted over several test sites of tropical dense forests in French Guiana, this campaign gives us the opportunity herein to exploit P-band temporal stacks with repeated time intervals transposable to BIOMASS in terms of signal decorrelation. The application of the generalized multichannel speckle filter to the Paracou test site dataset reveals the limitations of the standard ENL analytical formula to assess speckle reduction in the case of spatially correlated media like dense forests, and for this purpose the interest of the correlation between POA and azimuthal slopes computed from an independent Digital Surface Model. |
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ISSN: | 2072-4292 2072-4292 |
DOI: | 10.3390/rs13010142 |