Abstract
On the basis of the Gaussian vertical backscatter (GVB) model, this paper proposes a new method for extracting pine forest height and forest underlying digital elevation model (FUDEM) from multi-baseline (MB) P-band polarimetric-interferometric radar (PolInSAR) data. Considering the linear ground-to-volume relationship, the GVB is linked to the interferometric coherences of different polarizations. Subsequently, an inversion algorithm, weighted complex least squares adjustment (WCLSA), is formulated, including the mathematical model, the stochastic model and the parameter estimation method. The WCLSA method can take full advantage of the redundant observations, adjust the contributions of different observations and avoid null ground-to-volume ratio (GVR) assumption. The simulated experiment demonstrates that the WCLSA method is feasible to estimate the pure ground and volume scattering contributions. Finally, the WCLSA method is applied to E-SAR P-band data acquired over Krycklan Catchment covered with mixed pine forest. It is shown that the FUDEM highly agrees with those derived by LiDAR, with a root mean square error (RMSE) of 3.45 m, improved by 23.0% in comparison to the three-stage method. The difference between the extracted forest height and LiDAR forest height is assessed with a RMSE of 1.45 m, improved by 37.5% and 26.0%, respectively, for model and inversion aspects in comparison to three-stage inversion based on random volume over ground (RVoG) model.
Highlights
Polarimetric-interferometric radar (PolInSAR) provides a promising remote sensing technique for estimating forest height and ground phase by its sensitivity to the forest vertical structure [1,2,3,4].The complex interferometric coherence has been related to the vertical distribution of the forest scatterers [2,3,4]
The ambiguity space calculate the pure volume coherence (PVC), especially for low frequency data or high frequency data over coherence (PVC), especially for low frequency PolInSAR data or high frequency PolInSAR data over sparse forest forest region, region, because because volume volume and and ground ground scattering scattering contributions contributions are mixed in all the the aa sparse are mixed in all polarization channels
As multiplicative factors of the ground and volume scattering contributions, temporal decorrelation cannot be eliminated by weighted complex least squares adjustment (WCLSA) since the complex least squares adjustment can only reduce the random error
Summary
Polarimetric-interferometric radar (PolInSAR) provides a promising remote sensing technique for estimating forest height and ground phase by its sensitivity to the forest vertical structure [1,2,3,4].The complex interferometric coherence has been related to the vertical distribution of the forest scatterers [2,3,4]. PolInSAR presents the capacity to measure ground and volume scattering contributions, which leads to the possibility of extracting the forest underlying digital elevation model (FUDEM) and forest height [1,2,3,4,5,6,7,8]. At low frequencies (e.g., P-band), the radar wave interacts with the large-scale forest structural elements (e.g., branches and trunks) in the whole forest height extent [11] In this situation, the forest vertical heterogeneity should be considered and integrated in the forest scattering models.
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