Model with BIN Sample Clauses

Model with BIN. An alternative model was also developed using each plot’s bin from the stratification process described in Appendix A. Using the 80th percentile height and percent cover values calculated in CloudMetrics, each plot was classified into its true bin. A linear regression model using the bin value as a factor was built. Adding this information slightly improved the model performance over the standard linear regression approach. Because there are 12 bins and 12 interaction terms in this model, an equation with all 24 of the coefficients is not written here. However, it’s simplified form and performance metrics are presented below. Table 21. Stand Density Linear Regression Model with Bin. Metric Model R2 RMSE Density sqrt(density) ~ A + sqrt(B) 0.49 67.12 Table 22: Model variables. Model Variable Fusion CloudMetrics Variable Variable Explanation A the bin of each plot as a factor see Appendix B B number of individual tree objects (ITOs) identified in the 6ft canopy height model see Appendix D Figure 34. Predicted vs. plot density with the line of equality; model including bin.
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