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Vegetation bias removal and underlying topography estimation using polarimetric SAR interferometry

Authors: LISENO, ANGELO; K. P. Papathanassiou; I. Hajnsek; R. Scheiber; S. R. Cloude;

Vegetation bias removal and underlying topography estimation using polarimetric SAR interferometry

Abstract

Vegetation affects the possibility of providing global surface mapping based on Synthetic Aperture Radar Interferometry (InSAR). The estimation of ground topography in vegetated areas is an important task both, for scientific and commercial applications. Therefore, the need of quantifying and removing the vegetation bias arises. In this paper, these two points are investigated with reference to the penetration capabilities of L-band over forests. More in detail, an already developed model-based estimation technique is applied to experimental, fully polarimetric data. This provides a first experimental validation of such a technique and a way to quantify the bias introduced at L-band.

Countries
Italy, Germany
Keywords

underlying topography, vegetation, Pol-InSAR, PolInSAR; vegetation, PolInSAR, vegetation bias

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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