Comparing PolSAR, SAR and Optical Imagery Integration for Forest Canopy Height Estimation in Interior British Columbia, Canada

LiDAR-extracted canopy height values served as ground truth for both model training and validation. We compared between using SAR backscatter and PolSAR parameters, as well as between using SAR backscatter from Sentinel-1 and ALOS-2. Results show that PolSAR parameters outperforms SAR backscatter in predicting canopy height, while ALOS-2 achieved better accuracy in canopy height estimation than Sentinel-1.

Optical indices and bands were capable of enhancing model accuracy in all scenarios. To conclude, Sentinel-1 PolSAR parameters were the best predictor variables due to PolSAR’s ability to capture different scattering mechanisms under different canopy heights. Future studies should examine the potential of polarimetric synthetic aperture radar interferometry (PolInSAR) and ALOS-2 PolSAR to yield more accurate canopy height estimation over interior coniferous forests.