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In particular, the lower relative height metrics were more sensitive to biomass (p10, p30, p40) than the higher height metrics.
In particular, the first relationship analysed was between lidar height metrics and field-measured height.
At this point RMSE was ca. 0.5 m for all three height metrics (Figure 4).
The corresponding RMSE in the height metrics for the pulse densities at which 95% of the maximum R2 (see Table 4) was reached was greater for H95 than the other two height metrics.
Of the 40 predictor variables, the percentile height metrics were the most strongly correlated with above ground biomass.
Assuming that height metrics for the highest pulse density are correct the RMSE for each of these regressions was determined.
Similar(33)
FC and height related metrics, except maximum height and P25H, did not show statistically significant differences (p value >0.05).
For each plot we extracted height distribution metrics of the two main ALS echo types (first and last), including height percentiles, cumulative canopy density above certain thresholds, coefficient of variation and mean.
Previous studies have successfully estimated AGB or tree volume from lidar-derived vegetation-height statistical metrics in different boreal and temperate forests (Næsset 1997; Magnussen and Boudewyn 1998; Means et al. 2000; Popescu et al. 2004; Hall et al. 2005; Popescu 2007; Alberti et al. 2012).
From the three types of metrics, height based point cloud metrics show the most significant separation by treatments and stand-types, followed by canopy volume profiles.
Height and density metrics derived from the ALS data has been reported to be highly correlated with AGB see e.g. [8,9].
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