Three-stage inversion improvement for forest height estimation using dual-PolInSAR data

This paper addresses an algorithm for forest height estimation using single frequency single baseline dual polarization radar interferometry data. The proposed method is based on a physical two layer volume over ground model and is represented using polarimetric synthetic aperture radar interferometry (PolInSAR) technique. The presented algorithm provides the opportunity to take advantages of the dual polarimetric data, i.e, better spatial resolution and wider swath width, in comparison with the full polarimetric data, in forest height estimation application. In this research, a polarimetric optimization method is utilized to choose the optimum volume polarization basis in order to improve the results of the three-stage inversion algorithm. For the performance analysis of the proposed approach, the L-band ESAR data of the European Space Agency from BioSAR 2007 campaign (ESA) which is acquired over the Remningstorp test site in southern Sweden, is employed. The experimental result shows the dual PolInSAR HH/HV data capability in the forest height estimation without decreasing the accuracy of the result compared with the full polarimetric data.  The suggested method leads to the average root mean square error (RMSE) of 4.39 m and the determination of coefficient of 0.66 in forest height estimation in the 15 stands against LiDAR reference heights.