## 3 Results
### Binary Tree Cover
#### 3.2.2 Lidar  
Validation of the final binary tree cover map against the lidar derived reference revealed very similar accuracies to the visual assessment (Table 1), with an overall accuracy of 88% a TPR of 74%, a user's accuracy of 89%, and a false positive rate (FPR) of 5%. FPR is the percentage of reference pixels incorrectly classified as tree cover. The lidar derived accuracies have more errors from false positive \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**High Resolution Imagery Validation of the Tree Cover with Threshold Map (_n_ = 6648)**} \\ \hline  & & **Tree** & **Not Tree** & **Total** & **User’s Accuracy** \\ \hline \multirow{3}{*}{Classification} & Tree & 25.4 & 4.6 & 30.0 & 85 (0.99) \\  & Not tree & 8.6 & 61.4 & 70.0 & 88 (0.65) \\ \multirow{3}{*}{Total} & Total & 34.0 & 66.0 & 100.0 & \\  & Producer’s accuracy & 75 (1.21) & 93 (0.49) & \multicolumn{2}{c}{Overall = 87 (0.56)} \\ \hline \multicolumn{2}{c}{**High Resolution Imagery Validation of the Final Tree Cover Map (_n_ = 6648)**} \\ \hline  & & **Reference** & & & \\ \cline{2-6}  & & **Tree** & **Not Tree** & **Total** & **User’s Accuracy** \\ \hline \multirow{3}{*}{Classification} & Tree & 24.9 & 2.8 & 27.7 & 90 (0.73) \\  & Not tree & 9.1 & 63.2 & 72.3 & 87 (0.64) \\ \multirow{3}{*}{Total} & Total & 34.0 & 66.0 & 100.0 & \\ \multirow{3}{*}{Producer’s accuracy} & 73 (1.21) & 96 (0.32) & \multicolumn{2}{c}{Overall = 88 (0.51)} \\ \hline \multicolumn{2}{c}{**Airborne Lidar Validation of the Tree Cover with Threshold Map (_n_ = 13,884,067)**} \\ \hline  & & **Reference** & & & \\ \cline{2-6}  & & **Tree** & **Not Tree** & **Total** & **User’s Accuracy** \\ \hline \multirow{3}{*}{Classification} & Tree & 24.5 & 5.5 & 30.0 & 82 \\  & Not tree & 8.4 & 61.6 & 70.0 & 88 \\ \multirow{3}{*}{Total} & Total & 32.9 & 67.1 & 100.0 & \\ \multirow{3}{*}{Producer’s accuracy} & 75 & 92 & \multicolumn{2}{c}{Overall = 86} \\ \hline \multicolumn{2}{c}{**Airborne Lidar Validation of the Final Tree Cover Map (_n_ = 13,884,067)**} \\ \hline  & & **Reference** & & & \\ \cline{2-6}  & & **Tree** & **Not Tree** & **Total** & **User’s Accuracy** \\ \hline \multirow{3}{*}{Classification} & Tree & 24.1 & 3.0 & 27.1 & 89 \\  & Not tree & 8.7 & 64.2 & 72.9 & 88 \\ \multirow{3}{*}{Total} & Total & 32.7 & 67.3 & 100.0 & \\ \multirow{3}{*}{Producer’s accuracy} & 74 & 95 & \multicolumn{2}{c}{Overall = 88} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Validation matrices for the binary tree cover map using high resolution imagery and airborne lidar validation data. The “tree cover with threshold map” represents the binary classification of the probability surface using manual thresholds, while the “final tree cover map” represents the map after manual editing. As the lidar data was only sampled from the areas of NSW for which it was available it is not representative of the entire state. Also, as the lidar points are clustered the standard errors of the accuracy measures were not calculated. tree pixels and the omission of tree pixels, however the errors were not uniformly distributed across the state. The greatest omission errors were observed in arid shrulands, semi-arid woodlands and grasslands in the west, as well as cleared landscapes. The greatest commission errors were observed in, heathlands and wet sclerophyll forests, in the east. For the full accuracy assessment by vegetation formation see the supplementary material. Analysing the errors according to various lidar-derived vegetation categories revealed that omission errors decreased with increasing PPC and increasing height (Table 2). This explains the omission errors observed in the west of the state, where the arid and semi-arid vegetation is generally shorter, has thinner canopies and greater spacing between trees. Commission errors increased as the maximum vegetation height approached 2 m (Table 2), explaining the commission errors that were observed in areas of tall shrubs, such as heathlands, saline wetlands and dry sclerophyll forests with shrubby understory.