Using airborne laser scanning data to estimate structural attributes of natural eucalypt regrowth forests

Summary

Airborne laser scanning (lidar) data provide the means to measure the vertical and horizontal structure of forest vegetation. The aim of this study was to investigate how metrics derived from laser scanning data could be used in simple regression models to estimate eucalypt top height, basal area and stems per hectare on 20 m x 20 m field plots. The study area was located in the Central Forest Management Area in Victoria. The target population was younger regrowth forests aged 20–60 y dominated by mountain ash (Eucalyptus regnans) and other ash species. A linear regression function was able to provide precise estimates of eucalypt top height (r ² = 0.87; root mean square error (RMSE) = 3.9 m) using a single height percentile variable. On the strength of this result it should be possible to predict top height with a precision that is close to traditional field measurement methods. Regression estimates of eucalypt stand basal area were less precise (r ² = 0.56; RMSE = 14.7 m²) than those of the top height model. The model included both a height percentile and intensity variable. Regression modelling was able to provide an estimate of (eucalypt stems per hectare)⁻² using height percentiles, laser intensity and canopy structure as predictor variables (r ² = 0.41; RMSE = 5.6).

Keywords:

• airborne laser scanner data
• lidar
• canopy distribution metrics
• eucalypt regrowth forest