# A Quantitative Evaluation of UAV Flight Parameters for SfM-Based 3D Reconstruction of Buildings
## 4 Validation
### Single Shooting Pattern
#### 4.1.3 Random Forest Feature Importance  
To address the inherent limitations of multiple regression analysis, which assumes linear relationships, and to more comprehensively understand the complex interactions and nonlinear relationships between shooting variables and their impact on SfM result metrics, we performed feature importance analysis using Random Forest, a machine learning technique. This analysis aims to evaluate the relative importance of each shooting variable in predicting specific SfM result metric values by quantifying their contribution as importance values (Table 6). The results of the Random Forest analysis for surface capture patterns showed that the two variables related to image overlap, Forward overlap and Side overlap, had a combined importance of 0.9 or higher in predicting the Final Points and Reconstruction Completeness metrics, indicating that they exert an absolute influence. This trend aligns with the regression analysis results, reaffirming that ensuring overlap is the most critical factor for the number of points and completeness of the model. On the other hand, in the Computation Time prediction model, the three variables Forward overlap, Side overlap, and Tilt angle all showed relatively similar and high importance levels between 0.3 and 0.4, suggesting that computation time is influenced by a combination of multiple variables. Interestingly, in the Reprojection Error prediction, Tilt angle was found to be significantly more important than Forward overlap and Side overlap  
In the case of the Circular shooting pattern, the importance of variables showed a distinct difference depending on the target result indicator. Camera tilt angle was the most important variable, with an importance of approximately 0.71 in the prediction of the final number of points and approximately 0.59 in the prediction of computation time. On the other hand, shooting radius showed the highest importance, with approximately 0.82 in reprojection error prediction and approximately 0.60 in reconstruction completeness prediction. The importance of camera height offset was evaluated as relatively low or moderate, ranging from 0.06 to 0.30, in most of the analyzed result indicators. It is particularly noteworthy that the Tilt angle variable of the Surface pattern, which did not show a statistically significant linear relationship with Reprojection Error and Computation Time in multiple regression analysis or had a small influence, was evaluated as an important variable in the random forest analysis. This strongly suggests that Tilt angle may influence \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Shooting Type** & **Dependent Variable** & **1 st Feature** & **2 nd Feature** & **3 rd Feature** & **Importance** \\  & & **(Importance\(\approx\))** & **(Importance\(\approx\))** & **(Importance\(\approx\))** & **Distribution** \\ \hline \multirow{4}{*}{Circular} & Computation Time & Tilt angle (0.59) & Distance (0.30) & Radian (0.12) & High-Mid-Low \\  & Final Points & Tilt angle (0.71) & Distance (0.22) & Radian (0.07) & High-Mid-Low \\  & Reconstruction Completeness & Radian (0.60) & Distance (0.28) & Tilt angle (0.14) & High-Mid-Low \\  & Reprojection Error & Radian (0.82) & Tilt angle (0.12) & Distance (0.06) & Very High \\ \hline \multirow{4}{*}{Surface} & Computation Time & Tilt angle (0.39) & Forward overlap (0.31) & Side overlap (0.30) & Similar High-Mid \\  & Final Points & Forward Overlap (0.52) & Side overlap (0.45) & Tilt angle (0.03) & Two High, One Low \\ \cline{1-1}  & Reconstruction Completeness & Forward Overlap (0.50) & Side overlap (0.46) & Tilt angle (0.04) & Two High, One Low \\ \cline{1-1}  & Reprojection Error & Tilt angle (0.59) & Side overlap (0.21) & Forward overlap (0.20) & High, Two Mid \\ \hline \hline \end{tabular}  
* Importance Scale: High (\(>\)0.40), Mid (0.10–0.40), Low (\(<\)0.10).  
\end{table} 
Table 6: Random forest feature importance ranking and distribution by shooting type and result indicator.