Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Fig 1.

Study Sites.

Location of the three study sites in Southeastern Brazil, which are included in two Brazilian biomes (Cerrado and Atlantic Forest).

More »

Fig 1 Expand

Table 1.

Field data summary.

More »

Table 1 Expand

Fig 2.

Diameter versus total height scatterplot.

Diameter at breast height and total height relationships of trees used as data set in Cerrado, semi-deciduous and rainforest.

More »

Fig 2 Expand

Table 2.

Taper equations.

More »

Table 2 Expand

Table 3.

Taper models performance.

More »

Table 3 Expand

Table 4.

Modelling techniques performance.

More »

Table 4 Expand

Fig 3.

Root mean square error.

The root mean squared error (RMSE) distribution of diameter (d) and accumulated volume (Vac) for both training (black line) and validation (grey line) data sets, considering five hundred iterations for Artificial Neural Network (NN), Random Forest (RF) and taper model (TM).

More »

Fig 3 Expand

Fig 4.

Bias distribution.

The bias distribution of diameter (d) and accumulated volume (Vac) for both training (black line) and validation (grey line) data sets, considering five hundred iterations for Artificial Neural Network (NN), Random Forest (RF) and taper model (TM).

More »

Fig 4 Expand

Fig 5.

Diameter predictions residuals.

Residuals of diameter predictions (cm) versus tree stem diameters (cm) in the upper plots, as well as residuals of accumulated volume predictions (m³) versus tree stem diameters (cm) in the lower plots. Residuals were calculated using the model with the lowest RMSE along 500 iterations using Artificial Neural Network (NN), Random Forest (RF) and taper model (TM) techniques.

More »

Fig 5 Expand

Fig 6.

Stem taper predictions.

Measured diameters (black dots) of trees with regular (Xylopia aromatica) and irregular (Bathysa australis) stem taper with the respective predictions fitted by Neural Network (NN), Random Forest (RF) and taper model (TM).

More »

Fig 6 Expand