Sentence examples for mean canopy surface from inspiring English sources
Figure 6 Aboveground biomass estimates in submontane and montane classes and across all nine permanent plots (mean ± standard deviation) for different data densities predicted with a linear model based on mean canopy surface height.
Figure 5 Mean canopy surface heights associated with the field plot locations (submontane Plots F - J and montane Plots K - L) based on CHMs generated from original and thinned lidar data (D20, D8, D4, D2 and D1 indicate the different data density levels).
A linear model was developed to predict AGB based on plot-level mean canopy surface heights derived from the full-density lidar data.
We used this regression equation to generate biomass estimates based on the thinned lidar datasets with mean canopy surface height as the predictor, and compared the resulting values across the different data densities.
Geometric mean for turbidity was highest at site 2, possibly due to erosion and compaction of the soil surface by cattle (Table 2), and lowest geometric mean canopy cover % directly above site 2 (Table 4).
We characterized the horizontal heterogeneity of the canopy surface by calculating the coefficient of variation (CV; standard deviation divided by the mean) of LOCH for each plot.
Mean canopy profile height.
The mean canopy depth is L ¯ = H ¯ − z ∗ + d.
Stand basal area, mean canopy height, and canopy cover index all declined with increase in elevation.
cover, inside air, canopy surface and bare soil surface.
