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Updated: Jun 9, 2025

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Improving AGB estimations by integrating tree height and crown radius from multisource remote sensing.

Xinyi Liu1, Lili Dong2, Shitong Li3

  • 1College of Resource Environment and Tourism, Capital Normal University, Beijing, China.

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Summary

Estimating forest above ground biomass (AGB) is crucial for carbon stock assessment. This study shows that using tree height and crown radius from remote sensing data provides accurate AGB estimations, especially in mixed forests.

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Area of Science:

  • Forestry
  • Remote Sensing
  • Ecology

Background:

  • Accurate forest above ground biomass (AGB) estimation is vital for ecological functions and carbon stock assessment.
  • Directly measuring diameter at breast height (DBH) using remote sensing is challenging.
  • Alternative features from remote sensing data are needed for precise AGB estimation.

Purpose of the Study:

  • To demonstrate the feasibility of estimating AGB using crown radius (R) and tree height (H) extracted from multi-source remote sensing (RS) data.
  • To compare the performance of allometric growth equations using H, R, or both for AGB estimation in different forest types.
  • To establish a reliable method for high-precision, global-scale forest AGB estimation.

Main Methods:

  • Utilized airborne laser scanning (ALS) and terrestrial laser scanning (TLS) to generate point clouds for extracting tree height (H) and crown radius (R).
  • Applied nine allometric growth equations to fit coniferous (Larix principis-rupprechtii) and broadleaf (Fraxinus chinensis, Sophora japonica) forests.
  • Compared model performance using H alone, R alone, and combined H+R features for AGB estimation.

Main Results:

  • The quadratic polynomial model incorporating both H and R provided the best AGB estimation across all vegetation types.
  • In mixed tall and short coniferous forests, the H+R model achieved R² of 0.9282 and RMSE of 25.30 kg (rRMSE 17.31%).
  • Models using combined H and R significantly outperformed models using only H or R.

Conclusions:

  • Estimating forest AGB using crown radius and tree height derived from high-resolution remote sensing data is feasible and accurate.
  • The combined H+R approach offers a robust method for precise AGB quantification, crucial for ecological and carbon stock assessments.
  • This methodology supports high-precision, global-scale forest AGB estimation, overcoming limitations of traditional DBH measurements.