Abstract
This paper proposes a new method for forest height estimation using single-baseline single frequency polarimetric synthetic aperture radar interferometry (PolInSAR) data. The new algorithm estimates the forest height based on the random volume over the ground with a volume temporal decorrelation (RVoG+VTD) model. We approach the problem using a four-stage geometrical method without the need for any prior information. In order to decrease the number of unknown parameters in the RVoG+VTD model, the mean extinction coefficient is estimated in an independent procedure. In this respect, the suggested algorithm estimates the mean extinction coefficient as a function of a geometrical index based on the signal penetration in the volume layer. As a result, the proposed four-stage algorithm can be used for forest height estimation using the repeat pass PolInSAR data, affected by temporal decorrelation, without the need for any auxiliary data. The suggested algorithm was applied to the PolInSAR data of the European Space Agency (ESA), BioSAR 2007 campaign. For the performance analysis of the proposed approach, repeat pass experimental SAR (ESAR) L-band data, acquired over the Remningstorp test site in Southern Sweden, is employed. The experimental result shows that the four-stage method estimates the volume height with an average root mean square error (RMSE) of 2.47 m against LiDAR heights. It presents a significant improvement of forest height accuracy, i.e., 5.42 m, compared to the three-stage method result, which ignores the temporal decorrelation effect.
Highlights
Forest height is an important parameter in quantitative analysis of the carbon cycle at regional and global scales
The random volume over ground (RVoG) model addresses the complex coherence in each polarization state as a function of the volume thickness, the ground underlying phase, the mean extinction coefficient, and the surface-to-volume backscattering ratio
The three-stage method can be applied for the inversion of the RVOG+VTD model, the accuracy of the inversion results depends on how well the extinction value is determined from an auxiliary data [10,11]
Summary
Forest height is an important parameter in quantitative analysis of the carbon cycle at regional and global scales. The phase centers of two selected polarization states depend on the propagation properties, such as wave extinction and the vertical structure of the canopy In this regard, a physical model has been developed to invert the PolInSAR measurement into the forest height, taking into account the effective parameters of the wave and forest [5]. In order to overcome the above-mentioned disadvantages, a simple geometrical three-stage method was proposed [4] This method can estimate the ground phase, the forest height and the mean extinction coefficient without the need for a priori information and a time consuming iterative procedure. The RVoG+VTD model can be inverted using the three-stage method by fixing the mean extinction coefficient to a predefined value In this framework, the accuracy of the estimated forest height depends on the particular value chosen for the mean extinction coefficient. It should be noted that, by tweaking the mean extinction coefficient value in the RVoG+VTD model, we are able to achieve an estimation performance similar to the ones of the RMoG result [11]
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