Mapping Forest Height with Multifrequency SAR, InSAR, and Multispectral Datasets

Remote Sensing has been widely used for monitoring forests, namely for the retrieval of structural parameters such as the Forest Height (FH). The reason behind the use of remote sensing is the fact that measuring the FH through field campaigns is expensive and non-scalable. The resort to Airborne Laser Scanning campaigns, despite its high accuracy, have the same limitations. Therefore, Synthetic Aperture Radar (SAR) and Multispectral sensors carried by spaceborne platforms are widely used to address this problem. This paper evaluates the effects of combining a dataset that includes multifrequency backscatter (L and C bands) and multispectral variables, with Interferometric SAR (InSAR) variables (Coherence and Phase) for FH mapping resorting to a locally calibrated regression methodology. To make it more suitable for operational scenarios, only free access data is used, and the calibration sets are small. The scope of this study is the Mediterranean forests, and it has achieved a R2/RMSE ranging from 50.33–72.01%/1.55–2.50m in the validation and 56.22–75.48%/0.77–2.34 m for the operational scenarios. The addition of the InSAR variables leads to an improvement of 0.63% in the R2 and 0.02m in the RMSE.