Analysis of forest backscattering characteristics based on polarization coherence tomography

Luo, Hongyu; Li, Xiao Wen; Chen, Erxue; Cheng, Jian; Cao, Chunxiang

doi:10.1007/s11431-010-3242-y

Cited by 11 publications

(9 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Traditional studies on the PCT technology usually focus on forest vertical profile generation [59,61], with rare consideration of the relationship between the vertical profile and the forest parameters. In this study, all the parameters for AGB inversion were extracted by analyzing the geometric characteristics of the average vertical profiles within the forest stand [55,56].…”

Section: Discussionmentioning

confidence: 99%

“…f (Z) is the vertical structure function, which physically represents the vertical variations of the scattering signal at a point in the SAR image [61]. It is bounded from the underlying surface to the top of the vegetation layer and can be developed efficiently in a Fourier-Legendre series as shown in (2): f Z = ∑ n a n P n Z , a n = 2n + 1 2…”

Section: Polarization Coherence Tomographymentioning

confidence: 99%

See 1 more Smart Citation

Forest Above-Ground Biomass Estimation Using Single-Baseline Polarization Coherence Tomography with P-Band PolInSAR Data

Zhang

Wang

Zhu

et al. 2018

Forests

View full text Add to dashboard Cite

Abstract:Forest above ground biomass (AGB) extraction using Synthetic Aperture Radar (SAR) images has been widely used in global carbon cycle research. Classical AGB inversion methods using SAR images are mainly based on backscattering coefficients. The polarization coherence tomography (PCT) technology which can generate vertical profiles of forest relative reflectivity, has the potential to improve the accuracy of biomass inversion. The relationship between vertical profiles and forest AGB is modeled by some parameters defined based on geometric characteristics of the relative reflectivity distribution curve. But these parameters are defined without physical characteristics. Among these parameters, tomographic height (TomoH) is considered as the most important one. However, TomoH only corresponds to the highest volume relative reflectivity, which is lower than the actual forest height, affecting the accuracy of forest height and AGB inversion. In this paper, we introduce a new parameter, the canopy height (H ac ), for AGB inversion by analyzing the vertical backscatter power loss. Then, we construct an inversion model based on the combination of the new parameter (H ac ) and other parameters from the tomographic profile. The P-band polarimetric SAR datasets of the European Space Agency (ESA) BioSAR 2008 campaign acquired over Krycklan Catchment are selected for the verification experiment at two different flight directions. The results show that H ac performs better in estimating forest height and AGB than TomoH does. The inversion root mean square error (RMSE) of the proposed method is 18.325 t ha −1 , and the result of using TomoH is 21.126 t ha −1 .

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Polarization Coherence Tomographymentioning

confidence: 99%

Forest Above-Ground Biomass Estimation Using Single-Baseline Polarization Coherence Tomography with P-Band PolInSAR Data

Zhang

Wang

Zhu

et al. 2018

Forests

View full text Add to dashboard Cite

show abstract

“…Based on polarization coherence tomography (PCT), Luo et al [43] analyzed forest structure parameters from three perspectives, namely numerical simulation of Random Volume Ground model (RVoG), PolInSAR data at L-band of the test site Traunstein and Polarimetric SAR interferometry (PolInSAR) simulation of forest scene. The initial results of this research reflect high sensitivity of the vertical distribution of forest relative backscattering intensity to the forest type and density as well as polarization.…”

Section: Information Processing Technologies For Dementioning

confidence: 99%

Methodologies and applications in Digital China

2012

View full text Add to dashboard Cite

show abstract

“…(2) The method using forest height as features to estimate forest AGB. Forest height could be directly estimated from the interferometric SAR (InSAR) or polarimetric interferometric SAR (Pol-InSAR) data, while forest AGB could be calculated from forest heights using empirical allometric equations [16][17][18]. Taking forest height as a feature to estimate forest AGB can ensure that biomass can be estimated over a wider value range.…”

Section: Introductionmentioning

confidence: 99%

Forest Aboveground Biomass Estimation Using Multi-Features Extracted by Fitting Vertical Backscattered Power Profile of Tomographic SAR

Wan

Chen

et al. 2021

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Forest aboveground biomass (AGB), which plays an important role in the study of global carbon cycle, is one of the most important indicators in forest resource monitoring. Thus, how to estimate and map regional forest AGB quickly and accurately attracts more interests of researchers. Tomographic SAR (TomoSAR) is an advanced SAR technique developed in recent years, which has a wide range application in forest AGB estimation. In this paper, we proposed a multi-feature-based modeling method to estimate forest AGB by fitting backscattered power of TomoSAR vertical profile. The procedure of the proposed method includes four parts: (1) Processing TomoSAR data to obtain the backscattered power of vertical profile. (2) Fitting the backscattered power of the vertical profile. (3) Analyzing the fitted backscattered power distribution characteristic of the vertical profile. (4) Extracting the TomoSAR vertical profile features according to the forest AGB measurement factors based on the dendrometry theory. In this paper, we proposed two new features like the forest average height weighted by backscattered power (BPFAH) and the total length of the backscattered power curve (LBPC) as supplement features to estimate forest AGB by TomoSAR technique. We also used the traditional TomoSAR features including backscattered power at specific height layer of vertical power profile (BPV) and forest average height (FAH) for AGB estimation. After the feature selection, the selected features and the ground field data of the forest AGB were used for regression and modeling. Then the forest AGB was estimated and the accuracy was validated. The results showed that the accuracy of proposed method is 90.73%, and RMSE is 42.45 t/ha. Finally, we discussed the performance of our proposed method compared with traditional methods.

show abstract

Analysis of forest backscattering characteristics based on polarization coherence tomography

Cited by 11 publications

References 7 publications

Forest Above-Ground Biomass Estimation Using Single-Baseline Polarization Coherence Tomography with P-Band PolInSAR Data

Forest Above-Ground Biomass Estimation Using Single-Baseline Polarization Coherence Tomography with P-Band PolInSAR Data

Methodologies and applications in Digital China

Forest Aboveground Biomass Estimation Using Multi-Features Extracted by Fitting Vertical Backscattered Power Profile of Tomographic SAR

Contact Info

Product

Resources

About