Abstract:
Objective When polarimetric SAR data are used to invert tree height, time decorrelation factor is the main factor affecting inversion accuracy. Random-Motion-over-Ground (RMoG) model is one of the most effective models, but it has the disadvantages of difficult inversion and long time-consuming. Here, a simplified RMoG model is proposed.
Method In this study, the ground motion was neglected, the vegetation canopy motion was retained, and the vegetation volume scattering formula was rewritten. Then, the ground phase was judged by linear fitting of multiple coherence coefficients, and the decoherence value of pure volume scattering was estimated by PD polarization coherence optimization method. Finally, the rewritten vegetation volume scattering formula was used to establish a survey. Based on the fixed extinction coefficient, the height of vegetation can be retrieved by looking-up table. To verify the validity of this method, the remote sensing data of BioSAR 2007 project were tested in Remingstorp, southern Sweden. The inversion results of the four models were compared and evaluated with the determination coefficient (R2) and the root mean square error (RMSE).
Result This method can improve the overestimation problem of three-stage algorithm. In terms of accuracy comparison, the R2 of three-stage algorithm is 0.78 and RMSE is 8.52; the R2 of RMoG model is 0.47 and RMSE is 4.17; the R2 of RMoGL model is 0.48 and RMSE is 2.50; the R2 of this method is 0.53 and RMSE is 6.24. It is showed that this method is better in accuracy compared with three-stage algorithm, and can effectively reduce the inversion time compared with RMoG model and RMoGL model.
Conclusion It is effective to eliminate time-related effects by adding vegetation canopy movement. Compared with three-stage algorithm, RMoG model and RMoGL model, the simplified RMoG model has the advantages of high accuracy and less time-consuming.