Tropical forest AGB estimation based on structure parameters extracted by TomoSAR

• Published in: International journal of applied earth observation and geoinformation Vol. 121; p. 103369
• Main Authors: Li, Wenmei, Zhang, Yu, Zhang, Jiadong, Chen, Huaihuai, Chen, Erxue, Zhao, Lei, Zhao, Dan
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-07-2023; Elsevier
• Subjects: Canopy height; Forest aboveground biomass; Forest height; Structure parameters; Tomographic SAR; Tropical forest; Structure parameters; Tropical forest; Canopy height; Forest height; Tomographic SAR; Forest aboveground biomass
• ISSN: 1569-8432; 1872-826X
• DOI: 10.1016/j.jag.2023.103369

Forests play a crucial role in quantifying global carbon storage and detecting climate change in the form of aboveground biomass (AGB), which introduces an approach to study carbon cycle, ecology, and biodiversity. The monitoring and estimation of forest AGB are considered very important and of practical value. As we know, forest AGB relates with height, density and diameter at breast height, and how to relate the ecophysical parameters with remote sensing images is vital for forest AGB estimation. In this paper, we aim to explore structure parameters about forest density and height, extracted by tomographic SAR (TomoSAR) techniques, for further improving the precision of AGB estimation models. Firstly, vertical structure profiles are constructed via TomoSAR, and the structure features are extracted. Secondly, the correlation between these features and the in-situ forest maximum height, tree density, and average AGB in plot scale is analyzed. Thirdly, the 8-fold cross-validation and step-wise regression methods were utilized to construct the tropical forest AGB models. Finally, the results of these models have been presented and analyzed. Based on the analysis, it indicates that “Model 7” is the most effective model, and its performance at both plot and pixel scales indicates a high level of accuracy for predicting forest AGB. These findings suggest that the proposed method can be effectively applied to tropical forested areas and has good scalability.
•AGB estimation model built by structure parameters perform well in Mondah forest.•Tree density relates with the 30 m power in ground dominant scattering mechanism.•Canopy height and ScRv backscattering power at 35 m and 45 m are vital for forest AGB estimation.