# Extraction of Visible Boundaries for Cadastral Mapping Based on UAV Imagery
## 3 Results  
Resampling the UAV orthoimage to a lower spatial resolution, i.e., a larger value of GSD, resulted in fewer and faster extractions of object boundaries compared to the number of extracted object boundaries generated at the original size of the UAV orthoimage. The processing time for one boundary map was 1-2 min. A larger GSD, at the same scale and merge values, resulted in fewer boundary extractions (Table 2, Figures 4 and 5). \begin{table}
\begin{tabular}{c c c} \hline \hline
**GSD [cm]** & **Pixels** & **Resampling Method** \\ \hline
25 & \(2856\times 2498\) & Pixel average \\
50 & \(1428\times 1249\) & Pixel average \\
100 & \(714\times 625\) & Pixel average \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Ground sample distance (GSD) and number of pixels after image pre-processing. Figure 3: Object-based accuracy assessment method—buffer overlaying method. (**a**) Matched reference. (**b**) Matched extraction. (**a**,**b**) Calculation of boundary lengths of true positives (TP), false positives (FP) and false negatives (FN) (Adapted from [50]). Figure 2: Cadastral mapping workflow based on the automatic detection and extraction of visible boundaries from UAV imagery. Figure 4: Scale/merge level and number of extracted objects from the resampled UAV orthoimages (**a**) ground sample distance (GSD) 25 cm, (**b**) GSD 50 c, and (**c**) GSD 100 cm. (**a–c**) Grey labels—number of extracted objects outside the range, black labels—the lowest number of extracted objects per scale and merge parameter value. A lower scale level and merge level resulted in a higher number of extracted object boundaries for each resampled UAV image. A higher scale and merge level resulted in fewer extracted boundaries (Figure 4). In general, for all resampling, the biggest drop in the number of extracted object boundaries was at scale level values within the range from 70 to 80, and merge level values within the range from 95 to 99 (Figure 4). The incremental value of 1, for merge level 95-99, turned out to be very sensitive in dropping the number of extracted object boundaries (Figure 4a-c). The optimal scale and merge levels for an automatic boundary delineation were investigated by filtering out the total number of extracted objects with the minimum area of objects from the reference data. The results of this filtering approach are presented in Figure 6. The results showed that for the UAV orthoimages of higher spatial resolutions, namely a GSD of 25 cm, the optimal algorithm values for cadastral mapping resulted in 80 for scaling and from 95 to 99 for merging. In contrast, for the UAV orthoimages having a GSD of 50 cm and a GSD of 100 cm, the common optimal scale level values were 70-80 and merge level 95-98 (Figure 6). Some exceptions were observed for a GSD of 50 cm, where the scale level was 50, 60, and merge level to its maximum. In general, the results showed that the optimal scale and merge level values suitable for cadastral mapping range from 70 to 80 and from 95 to 99, respectively (examples in Figure 5). The optimal scale and merge level values appeared similar as in the investigation of the influence of different GSDs in extracting objects. Figure 5: (**a–i**) Examples of extracted boundary maps. (**a–c**) GSD 25 cm; (**d–f**) GSD 50 cm, and (**g–i**) GSD 100 cm. (**a,d,g**) Extracted objects at scale 70 and merge 99. (**b,e,h**) Extracted objects at scale 75 and merge 99. (**c,f,i**) Extracted objects at scale 80 and merge 99. For further analysis, optimal extracted objects with scale level 80 and merge level 95 for three GSDs of UAV orthoimages were selected (Figure 7a,c,e). The selection was based on common scale and merge levels for three GSDs as well on the highest number of filtered objects per GSD (Figure 6). The filtering approach was additionally applied to the selected optimal extracted objects, i.e., with scale level 80 and merge level 95, to remove objects under the minimum reference object area (Figure 7b,d,f).