Related Experiment Video
Updated: Jun 1, 2026

Computer Vision-Based Biomass Estimation for Invasive Plants
Published on: February 9, 2024
[ALOS PALSAR estimation of vegetation biomass in Daxing' anling region]
1School of Forestry, Northeast Forestry University, Harbin 150040, China. songqianwin999@sohu.com
Abstract:
Based on field survey data, the correlations between the ALOS PALSAR L-band HH (L-HH) polarization data and the parameters of forest components in Daxing' anling region were systematically analyzed, and by adopting forest biomass estimation models, including simple linear model, exponential model, and model with terrain factors, optimal inversion was conducted. The results showed that backscattering coefficient had the greatest correlation with total forest biomass, and secondly, with trunk biomass, suggesting that the L-HH data could be used to estimate the total forest aboveground biomass. Among the three models adopted, the model with terrain factors could greatly reduce the biomass estimation error, with the accuracy reached 0.851, and the inversion result coincided best with the actual situation. It was forecasted that under the 41.5 degrees incidence angle L-HH polarization, the vegetation biomass saturation point within the Tahe and Amuer forest bureaus of Daxing' anling was at about 15.4 kg x m(-2).

