Abstract
This paper discusses the potential and limitations of high-resolution P-band polarimetric synthetic aperture radar (SAR) interferometry (PolInSAR) in underlying topography estimation over forest areas. Time-frequency (TF) analysis in the azimuth direction is utilized to separate the ground scattering contribution from the total PolInSAR signal, without the use of any physical model, because the P-band PolInSAR data have a significant penetration depth and sufficient observation angle interval. To achieve this goal, a one-dimensional polynomial fitting (PF) method is proposed for correcting the residual motion error (RME). The Krycklan catchment test site, which is covered with pine forest, was selected to test the performance of the digital elevation model (DEM) inversion. The results show that the PF method can correct the RMEs for the sub-look interferograms well. When compared to the existing line-fit method, the TF+PF method can provide a more accurate DEM (the accuracy is improved by 26.9%). Moreover, the performance of the DEM inversion is free from the random-volume-over-ground assumption.
Highlights
Digital elevation models (DEMs) play an important role in many applications, such as geohazard prediction [1], resource exploration, and flood inundation simulation [2]
This study proposes underlying DEM inversion for forest areas based on a refined TF method for single-baseline P-band PolInSAR data to overcome the above limitation
A method based on a TF approach combined with a polynomial fitting method to correct the residual motion error (RME) has been proposed for underlying topography estimation in forest areas
Summary
Digital elevation models (DEMs) play an important role in many applications, such as geohazard prediction [1], resource exploration, and flood inundation simulation [2]. Polarimetric interferometric SAR (PolInSAR) can distinguish the phase centers of multiple targets in a common cell over a forest area [6]. This provides the possibility to separate ground scattering contributions from canopy scattering contributions. The inversion method based on the random-volume-over-ground (RVoG) model has been widely used, as it can model a forest with few parameters and connect the PolInSAR complex coherences with the forest biophysical parameters [7,13,14]. In the RVoG model, the forest is assumed to be a homogeneous random volume Based on this assumption, the extinction is independent of the polarization.
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