An efficient method for estimating tropical forest canopy height from airborne PolInSAR data

• We explore simplified solution approaches for two temporal decorrelation models based on PolInSAR forest height estimation. Additionally, we investigate a more efficient model solving method. • The research shows that the simplification of the model has increased efficiency by 20 times while maintaining accuracy. • For temporal decorrelation in PolInSAR, we comprehensively analyze several effective methods and give model selection schemes in different scenarios. The study on PolInSAR forest canopy height(FCH) inversion is an essential branch within the SAR field, where the temporal decorrelation(TD) inherent in the interferometric complex coherence of repeat-pass Polarization Interferometric Synthetic Aperture Radar (PolInSAR) data significantly impacts the precision of FCH estimation.This study is grounded in airborne multi-baseline PolInSAR data, employing Random Volume over Ground (RVoG) + VTD and Random Motion over Ground(RMoG) as the FCH inversion models. The classical RVoG three-stage method(TS) process was used to simplify the solution of RVoG+VTD and RMoG, and a novel, more efficient method was attempted to further streamline the solution of the RVoG+VTD model(RVoG+VTDs). The results demonstrate that the RVoG+VTDs model obtains the most satisfactory results, and the efficiency of the RVoG+VTDs model is 23 times more efficient than that of the RVoG+VTD; 19 times more efficient than that of the RMoG model, and 22 times more efficient than that of the RVoG model, respectively; and the inversion time consumed by the four models is 1.5 min, 35 min, 28 min, and 33 min, respectively. In the accuracy validation, the estimation accuracy of RVoG+VTDs still keeps the best accuracy, with corresponding R 2 values for the four methods (RVoG+VTDs, RVoG+VTD, RMoG, and RVoG) equal to 0.813, 0.774, 0.804, and 0.770, respectively. The RMSE values are 6.626 m, 7.277 m, 6.774 m, and 7.335 m.The study’s conclusions illustrate the feasibility of solving the RVoG+VTD and RMoG model by fixing the extinction coefficients in the model, with RVoG+VTDs taking precedence over the model selection, which can provide a valuable reference for the application of spaceborne PolInSAR data.

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Publication Details

Journal
Ecological Indicators
Published
2024-09-01
DOI
https://doi.org/10.1016/j.ecolind.2024.112566
Citations
2
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
Field-Weighted Citation Impact
2.60
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article

An efficient method for estimating tropical forest canopy height from airborne PolInSAR data

Xiaoli Zhang, Cairong Yue, Hongbin Luo, Chi Lu et al.
2 citations
Ecological Indicators
Synthetic Aperture Radar (SAR) Applications and Techniques
2.60
article

An efficient method for estimating tropical forest canopy height from airborne PolInSAR data

Xiaoli Zhang, Cairong Yue, Hongbin Luo, Chi Lu, Guanglong Ou, Yong Wu
article en
2 citations

Abstract

• We explore simplified solution approaches for two temporal decorrelation models based on PolInSAR forest height estimation. Additionally, we investigate a more efficient model solving method. • The research shows that the simplification of the model has increased efficiency by 20 times while maintaining accuracy. • For temporal decorrelation in PolInSAR, we comprehensively analyze several effective methods and give model selection schemes in different scenarios. The study on PolInSAR forest canopy height(FCH) inversion is an essential branch within the SAR field, where the temporal decorrelation(TD) inherent in the interferometric complex coherence of repeat-pass Polarization Interferometric Synthetic Aperture Radar (PolInSAR) data significantly impacts the precision of FCH estimation.This study is grounded in airborne multi-baseline PolInSAR data, employing Random Volume over Ground (RVoG) + VTD and Random Motion over Ground(RMoG) as the FCH inversion models. The classical RVoG three-stage method(TS) process was used to simplify the solution of RVoG+VTD and RMoG, and a novel, more efficient method was attempted to further streamline the solution of the RVoG+VTD model(RVoG+VTDs). The results demonstrate that the RVoG+VTDs model obtains the most satisfactory results, and the efficiency of the RVoG+VTDs model is 23 times more efficient than that of the RVoG+VTD; 19 times more efficient than that of the RMoG model, and 22 times more efficient than that of the RVoG model, respectively; and the inversion time consumed by the four models is 1.5 min, 35 min, 28 min, and 33 min, respectively. In the accuracy validation, the estimation accuracy of RVoG+VTDs still keeps the best accuracy, with corresponding R 2 values for the four methods (RVoG+VTDs, RVoG+VTD, RMoG, and RVoG) equal to 0.813, 0.774, 0.804, and 0.770, respectively. The RMSE values are 6.626 m, 7.277 m, 6.774 m, and 7.335 m.The study’s conclusions illustrate the feasibility of solving the RVoG+VTD and RMoG model by fixing the extinction coefficients in the model, with RVoG+VTDs taking precedence over the model selection, which can provide a valuable reference for the application of spaceborne PolInSAR data.

Ecological IndicatorsVol. 166
Southwest Forestry University (CN)
Life in Land
Openalex Percentile: Top 8%
Synthetic Aperture Radar (SAR) Applications and Techniques
2.60
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