JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2021, Vol. 45 ›› Issue (6): 185-192.doi: 10.12302/j.issn.1000-2006.202101016

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Based polarization orientation angle compensation for Pinus kesiya var. langbianensis forest aboveground biomass estimation

ZHANG Guofei(), YUE Cairong*(), LUO Hongbin, GU Lei, ZHU Bodong   

  1. College of Forestry, Southwest Forestry University, Kunming 650224,China
  • Received:2021-01-14 Accepted:2021-03-23 Online:2021-11-30 Published:2021-12-02
  • Contact: YUE Cairong E-mail:info1979@163.com;1207709049@qq.com

Abstract:

【Objective】Polarimetric synthetic aperture radars have been widely used in forest remote sensing monitoring. Owing to Faraday rotation, the polarization orientation angle (POA) of the electromagnetic wave is displaced, leading to ambiguity in the scattering characteristics. In this study, the effects of polarization orientation angle compensation on the volume scattering component and aboveground biomass (AGB) retrieval were analyzed.【Method】 The influence of Faraday rotation on SAR data was analyzed using ALOS PALSAR full polarimetric SAR images as the data source. Based on the L-band scattering characteristics and considering the dihedral scattering contribution between the ground and the tree trunk, an extended polarization water cloud model (EPWCM) was proposed. Based on the Yamaguchi four-component decomposition parameters and field survey data, the aboveground biomass of Pinus kesiya var. langbianensis forest was estimated by EPWCM.【Result】 Through the unitary transformation of the coherence matrix to compensate for the polarization orientation angle deviation, the overestimation of the volume scattering component was corrected, and the regression with aboveground biomass was improved (R 2 increased from 0.214 to 0.332). The estimated aboveground biomass had a strong correlation with the observed AGB (R2 = 0.644) and a relatively high accuracy (RMSE as 23.11 t/hm2). 【Conclusion】 Before polarimetric decomposition, SAR data should be compensated for polarimetric orientation angle correction to reduce the ambiguity of scattering characteristics and increase the retrieval accuracy of AGB. The semi-empirical model has a good potential for estimating forest aboveground biomass.

Key words: Pinus kesiya var. langbianensis forest, aboveground biomass (AGB), polarization orientation angle(POA), Faraday rotation, extended polarization water cloud model(EPWCM)

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