## 3 Results
### Spatial and Statistical Analysis  
Spatial and statistical analysis provides an opportunity to determine the links between geomorphological and spatial parameters of the territory and changes in forest areas, as well as to analyze the possible influence of topographical and geomorphological factors on changes in forest cover areas. Since the land productivity score, the land surface altitudes, and the slopes create favorable/unfavorable conditions for agricultural activities that gradually replace forests, complex factor analysis allows for highlighting and identification of these links. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **If the Effects of Factors of 2 nd** & **If the Effects of Factors of 1 st** & **If the Effects of Factors of 2 nd** \\
**Elderships** & **Half of the 19 th Century–1 st Half** & **Half of the 20 th Century–2 nd** & **Half of the 20 th Century–1 st Half** \\  & **of the 20 th Century Were** & **Half of the 20 th Century Were** & **of the 21 st Century Were** \\  & **Maintained** & **Maintained** & **Maintained** \\ \hline Erzvilkas & \(-102\) & \(+134\) & \(+469\) \\ GirdZiai & \(-128\) & \(+2165\) & \(-575\) \\ Juodaičiai & \(-79\) & \(+12\) & \(-58,333\) \\ Jurbarkai & \(-216\) & \(+357\) & \(-853\) \\ Jurbarkas city & \(+133\) & \(+180\) & \(+100,078\) \\ Raudone & \(-103\) & \(+95\) & \(-1338\) \\ Seredzius & \(-118\) & \(+53\) & \(+626\) \\ Skirsnemune & \(-116\) & \(+536\) & \(-412\) \\ Smalininkai & \(+127\) & \(+90\) & \(+1258\) \\ Simkačiai & \(-107\) & \(+211\) & \(-650\) \\ Veliuona & \(-124\) & \(+159\) & \(+5479\) \\ Viesvile & \(+1593\) & \(+536\) & \(-178\) \\ Jurbarkas Distr. & \(-141\) & \(+211\) & \(-117\) \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Number of years in which forest cover areas would have disappeared/doubled. A correlation analysis was performed between changes in forest cover determined using historical GIS and land productivity scores in the elderships while analyzing links between changes in forest cover areas and land productivity scores (Table 13). The following periods were selected: the 19 th century-the 1 st half of the 20 th century, the 1 st half of the 20 th century-the 2 nd half of the 20 th century-the 2 nd half of the 20 th century, the 2 nd half of the 20 th century-the 21 st century. Indicators of correlation analysis:  
_i_--change in forest cover areas in a certain period, m\({}^{2}\);  
_j_--the land productivity score. It can be seen from the results of the analysis that there is a statistically significant strong negative correlation between the diminishing of forest cover areas and the productivity score in the first period. In other periods, there are no statistically significant correlations. During the analysis of the dependence of the change in forest cover areas on the slopes of the land surface in relation to the cardinal directions, the slopes of individual elderships were determined with the help of historical GIS, their reclassification was performed, the data with the slope areas were converted into a table, and a correlation analysis was performed (Table 14). Indicators of correlation analysis:  
_i_--change in forest cover areas in the corresponding period, m\({}^{2}\);  
_j_--areas of slopes of the land surface in relation to the cardinal directions, m\({}^{2}\). The results of the correlation analysis presented in Table 14 show that correlation coefficients of moderate significance were obtained between slopes in the east (\(10.401\leq\tau_{\rm ij}\leq\,10.551\)) and west (\((\,1.042\,|\,\leq\tau_{\rm ij}\leq\,10.521\,)\) directions. However, only the correlation coefficients between the change in forest cover areas and the slope of the land surface in the eastern direction have statistical significance (\(0.02\leq p\)-value \(\leq\,0.08\)). Jurbarkas District: The angle is \(30.8^{\circ}\) in the north direction, \(18.4\%\) in the south direction, and more or less the same in the west and east directions--\(20.4\%\) and \(20.3\%\) respectively.