Inversion of Forest above Ground Biomass in Mountainous Region Based on PolSAR Data after Terrain Correction: A Case Study from Saihanba, China

Abstract

Accurate retrieval of forest above ground biomass (AGB) based on full-polarization synthetic aperture radar (PolSAR) data is still challenging for complex surface regions with fluctuating terrain. In this study, the three-step process of radiometric terrain correction (RTC), which includes polarization orientation angle correction (POAC), effective scattering area correction (ESAC), and angular variation effect correction (AVEC), is adopted as the technical framework. In the ESAC stage, a normalized correction factor is introduced based on local incidence angle and radar incidence angle to achieve accurate correction of PolSAR data information and improve the inversion accuracy of forest AGB. In order to verify the validity and robustness of this research method, the full-polarization SAR data of ALOS-2 and the ground measured AGB data collected in the Saihanba research area in 2020 were used for experiments. Our findings revealed that in the ESAC phase, the introduction of the normalized correction factor can effectively eliminate the ESA phenomenon and improve the correlation coefficients of the backscatter coefficient and AGB. Taking the data of 25 July 2020 as an example, ESAC increases the correlation coefficients between AGB and the backscattering coefficients of HH, HV, and VV polarization channels by 0.343, 0.296, and 0.382, respectively. In addition, the RTC process has strong robustness in different AGB statistical models and different date PolSAR data.

Inversion of Forest Aboveground Biomass in Regions with Complex Terrain Based on PolSAR Data and a Machine Learning Model: Radiometric Terrain Correction Assessment

“…Moreover, compared with C-band, L-band has stronger penetration and can more accurately reveal the details of the forest internal structure, which is conducive to improving the accuracy of forest AGB. In this study, the Sentinel Application Platform (SNAP_v9.0.0) software developed by the European Space Agency completed the pre-processing steps for the PolSAR data: crosschannel SNR correction, Faraday rotation correction, and radiometric calibration for complex data (Equation (2), derived from radiometric calibration of real data; Equation (1)) [35,40], multi-look averaging of 4 × 9 (range × azimuth), refined LEE filter, and range doppler terrain correction). The ensemble average size for the covariance matrix is crucial, especially when studying natural vegetation.…”

“…All plots were located using differential GPS (Unistrong RTK-G10, Unistrong, Beijing, China), and plot information such as plot type, plant number, and slope, as well as individual information of trees with a diameter at breast height (DBH) ≥ 5.0 cm, was recorded, including DBH, tree height, and tree species. Finally, the biomass per plant was calculated separately according to the allometric equation of different tree species (Table 2); then the total forest AGB of the plot was obtained by summing (Equation ( 3)) [40] all the biomass per plant. Table 3 provides statistical details of the field data for this study.…”

“…However, due to the difference in terrain slope, ground units of the same SAR data in the geographical coordinate system correspond to different effective scattering areas. Therefore, effective scattering area correction (ESAC) takes flat land as a reference to correct the area effect of SAR data under different slope conditions so as to eliminate the influence of terrain slope on scattering information [39,40]. The C 3 matrix can be corrected using Equation ( 5):…”

“…At present, the radiometric terrain correction (RTC) process designed for PolSAR data is a relatively complete solution for terrain correction [39], which includes polarization orientation angle correction (POAC), effective scattering area correction (ESAC), and angular variation effect correction (AVEC). We introduce normalized ESAC factors on the basis of RTC to further improve the RTC process [40]. Although the RTC method has shown excellent performance in the correction of backscattering coefficient and its effectiveness and robustness have been widely recognized [41,42], there is a lack of in-depth research on the correction effect and quantitative analysis of the polarization decomposition parameters of PolSAR data by RTC.…”

“…In addition, in the inversion of forest AGB based on PolSAR characteristics, a widely accepted view is that forest AGB has the best correlation with the backscattering coefficient of HV polarization channels, but there is no direct and simple linear relationship between the two; in fact, a logarithmic function may be the more appropriate relationship [58]. Moreover, our previous research focused on the potential of RTC processes to improve the accuracy of forest AGB inversion based on univariate models [40]. Therefore, this study will not focus on the construction of monadic linear or nonlinear models, but instead will seek multivariate and high-level nonlinear model structures that can capture this complex relationship.…”