# Comparison of Land Cover Categorical Data Stored in OSM and Authoritative Topographic Data
## 4 Results
### Regional CCI Diversity and Sensitivity Analysis  
As the region's area expands, the range of regional CCI values increases, and the local differences between the data become blurred. The variance, standard deviation and interquartile range decrease, which proves that \(\rm{CCI_{R7}}\) values are less diverse than \(\rm{CCI_{R6}}\), \(\rm{CCI_{R5}}\) and \(\rm{CCI_{R4}}\) (Table 4). Regardless of the region's extent, the \(\rm{CCI_{Rn}}\) mean value is greater than the median and slightly lower than the standard deviation, indicating a predominance of values smaller than the mean, i.e., maximum and moderate compliance between BDOT10k and OSM. Nevertheless, \(\rm{CCI_{Rn}}\) is characterized by a large disparity, based on cv, which takes values above 100%. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Statistics** & **[PERSON]** & **[PERSON]** & **[PERSON]** & **[PERSON]** & **[PERSON]** & **[PERSON]** & **Miedzyrzecki** \\ \hline Mean & 0.0915 & 0.0390 & 0.0678 & 0.0414 & 0.0427 & 0.0989 & 0.0353 \\ Median & 0.0754 & 0.0304 & 0.0533 & 0.0313 & 0.0314 & 0.0832 & 0.0271 \\ Minimum & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ Maximum & 0.4828 & 0.5329 & 0.4995 & 0.4764 & 0.5765 & 0.5069 & 0.5899 \\ Q1 & 0.0420 & 0.0159 & 0.0315 & 0.0165 & 0.0181 & 0.0542 & 0.0129 \\ Q3 & 0.1196 & 0.0499 & 0.0790 & 0.0507 & 0.0538 & 0.1246 & 0.0427 \\ Variance (\(\sigma^{2}\)) & 0.0052 & 0.0015 & 0.0039 & 0.0018 & 0.0017 & 0.0046 & 0.0016 \\ Std. Dev. (\(\sigma\)) & 0.0723 & 0.0386 & 0.0627 & 0.0426 & 0.0406 & 0.0680 & 0.0405 \\ Coeff. of variation & 78.9755 & 98.8908 & 92.3641 & 103.0427 & 95.1072 & 68.7311 & 114.7669 \\ Interquartile range (IQR) & 0.0775 & 0.0340 & 0.0475 & 0.0342 & 0.0357 & 0.0704 & 0.0298 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Descriptive \(\rm{CCI_{L}}\) statistics. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Class** & **Description** & **Range** & \multicolumn{6}{c}{**Percentage of the County’s Area (\%)**} \\ \cline{3-10}  & & & **Piaseczno** & **Sokólski** & **Sanocki** & **Slupski** & **Ostrowski** & **Ostrowski** & **Ostrowski** & **Miedzyrzecki** \\ \hline
1 & maximum & \(-0.50\)\(\sigma\)\(<\)\(\rm{CCI_{L}}\) & 35.5 & 32.1 & 30.6 & 30.6 & 33.2 & 34.1 & 29.1 \\
2 & moderate & \(-0.5\)\(\sigma\)\(\leq\)\(\rm{CCI_{L}}\)\(\leq\) & 42.3 & 49.6 & 52.2 & 52.9 & 46.5 & 43.5 & 56.2 \\  & compliance & \(0.5\)\(\sigma\)\(\leq\)\(\rm{CCI_{L}}\)\(\leq\) & 13.1 & 12.7 & 10.6 & 10.3 & 13.3 & 13.1 & 9.6 \\
3 & semi-compliance & \(1.5\)\(\sigma\)\(\leq\)\(\rm{CCI_{L}}\)\(\leq\) & 5.6 & 2.7 & 3.1 & 3.1 & 4.6 & 9.3 & 2.5 \\
4 & noncompliance & \(2.5\)\(\sigma\) & & 3.4 & 2.9 & 3.5 & 3.2 & 2.5 & - & 2.6 \\
5 & noncompliance & \(\rm{CCI_{L}}\)\(>\)\(2.5\)\(\sigma\) & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The percentage of a county’s area in \(\rm{CCI_{L}}\) classes. Figure 3: CCl\({}_{\rm L}\) in analyzed counties: (**a**) Piaseczno, (**b**) Sokólski, (**c**) Sanocki, (**d**) Slupski, (**e**) Ostrowski, (**f**) Otwocki, (**g**) Miedzyrzecki. The standard deviation of \(\mathrm{CCI_{R4}}\) (0.0343) is smaller than that of \(\mathrm{CCI_{L}}\) in Sokolski county (\(\mathrm{CCI_{L}}\)\(\sigma\) = 0.0386), with the lowest \(\mathrm{CCI_{L}}\) value, which value is less than half that of the highest value in Piaseczno county (\(\mathrm{CCI_{L}}\)\(\sigma\) = 0.0723). Additionally, in terms of variance, the value of \(\mathrm{CCI_{R4}}\) (0.0012) is noticeably smaller than that of \(\mathrm{CCI_{L}}\), whereas, in Piaseczno county, the variance is four times higher (\(\mathrm{CCI_{L}}\)\(\sigma^{2}\) = 0.0052) (see also Table 2). The maximum compliance between BDOT10k and OSM oscillates around 32% of the entire region area. In contrast, moderate compliance, with \(\mathrm{CCI_{Rn}}\) values in the range of \(-0.5\)\(\sigma\) to 0.5\(\sigma\), represents just over 50% (Table 5). The maximum disagreement between the data is basically negligible. The area where both BDOT10k and OSM data have the lowest correspondence between geospatial objects varies between 3.6 and 6.3%.