## 3 Results
### Objective III: Significance Testing  
A two-tailed \(t\)-test assuming equal variances was conducted between the average overall accuracies of each disturbance type to determine whether the difference in overall accuracy between the disturbance types/vegetation cover was significant at a 95% confidence interval (0.05) (Table 16). Because the GEOBIA process used in this study was mostly the same between the two types of disturbances and land covers, the variances were assumed to be equal. Furthermore, by conducting this particular type of \(t\)-test, the objective effectiveness of this method could be tested for the two types of NDBM treatments commonly employed in the CHF region. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Consideration** & **Subject** & **Recommendation** & **Justification** \\ \hline Atmospheric & Sun Angle/Time of Collection & Mid-day & Tall objects and dense canopy restricted times of collection to highest sun angle possible. \\ Conditions & & & Tall vegetation height was more sensitive to overexposure if too bright and view into canopy gaps was better with diffuse overcast lighting. \\  & Brightness/Cloud Cover & Diffuse/Overcast & Motion blur more common with tall vegetation, wind needed to be minimal. \\  & Wind & \(\leq\)5 mph (low) & Properly exposed image with sharp detail for given lighting conditions. \\  & Shutter Speed & 1/3200–1/4000 & Wide field of view for high image overlap. \\  & Aperture and & f/3.5 and 21 mm & Wide field of view for high image overlap. \\  & Focal Length & ISO and Zoom & Auto and \(\infty\) & Auto-balanced gain and focused images. \\  & Flight Altitude & 152 m AGL (500 ft) & Sufficient depth of field for sharp detail. \\ Mission & Overlap/Sidelap & 80\% \(\times\) 80\% & Ensured thorough coverage of study area. \\ Planning & Number of Boundary & \(\geq\)2 images & Commonly less visible ground cover than prairie \\  & Images & & sites necessitated larger outside image buffer. \\ \hline \hline \end{tabular}
\end{table} 
Table 13: Optimal data collection parameters for surveying Volz selective timber harvest site. Figure 8: (**a–d**) PWA prairie burn orthomosaics. UAS flight area shown in yellow; study area for land cover classification shown in green. Figure 9: (**a–d**) Volz harvest orthomosaics. Study area for land cover classification shown in yellow. Figure 10: (**A**) RB (**B**) PB (**C**) PB 2 (**D**) PB 3, RB = pre-burn, PB = post-burn. PWA prairie burn land cover classification. Burn plots shown in red outline. Figure 11: (**A**) pre-cut (**B**) mid-cut (**C**) post-cut (**D**) post-cut 2. Volz timber harvest land cover classification. Harvest area shown in yellow outline. To have a statistically significant difference between the two types of disturbances and land covers, the \(p\)-value (0.133) would need to be less than the confidence interval (0.05). In this case, the \(p\)-value is _not_ less than the confidence interval, and therefore, there is _not_ a statistically significant difference between the overall accuracies of the PWA prescribed prairie burn and the Volz selective timber harvest land cover classifications. This means that while PWA did have higher overall and individual class accuracies, they were not significantly better than Volz, so both the collection and classification methods employed in this study were effective for both the disturbance and land cover type.