## 3 Results and Discussion
### Landscape Metrics Analysis
For 2010, although the NP value for the heathland and shrub class (5) was lower than the NP values for the cropland (2) and grassland (4) classes, the LPI, ED, and TA values were higher than for the other classes. These values showed that compact and related patches were concentrated in this class; however, the values for the area-edge metrics decreased from 2010 to 2020. Urban areas (1) were independently identified as the most passive class in terms of _PD_, _NP_, and _PLAND_ values for the two dates, as their patches were too small and dispersed. In fact, the ENN_AM, which is weighted with respect to the patch size, determines the neighborhood relations of the patches in terms of proximity. According to this metric, patches belonging to urban areas (1) were too far from each other (showing the highest ENN_AM values); however, there was a slight expansion in urban areas between 2010 and 2020. Both cropland (2) and grassland (4) classes showed quite high values for _NP_ and _PD_. When considered along with the low values for _LPI_, these results suggest that these classes are undergoing fragmentation over time. Additionally, cropland (2) and grassland (4) classes, which had the highest LSI values, have complex structures; however, in terms of their _ED_ values, they were lower than the heathland and shrub class (5). This showed that patches from the cropland (2) and grassland (4) classes had started to lose their core properties and their edge relations had been weakened. The woodland and forest class (3) was identified as the class with the highest class fragmentation. Even though the NP values were much higher compared to the urban areas class (1), which covered the smallest surface area in the study area, the woodland and forest class (3) had lower LPI values (0.12 and 0.43 for 2010 and 2020, respectively). These values showed that the patches in the woodland and forest class (3) are small, underdeveloped, and according to the SPLIT and ENN_AM values, they are scattered and not connected. The sparsely vegetated areas class (6) was only identified in 2020. It had the lowest PLAND and LPI metric values. It was the smallest class in terms of area, patch density, and patch number. The overall assessment of the metrics showed that the heathland and shrub class (5) dominated the landscape--its patches are both large and dense. Both cropland (2) and grassland (4) classes were scattered in the region as unconnected small units. Woodland and forest (3) classes were scattered and disjointed. The urban areas class (1) had the lowest values in terms of area, patch density, and patch number. The sparsely vegetated areas class (6) was only mapped in 2020. The invaded grassland (4) and heathland and shrub (5) classes decreased from 2010 to 2020, giving way to the invasion of the sparsely vegetated areas class (6). Multiple linear regression (MLR) methodology was applied in order to both spatially and quantitively correlate (Table 12) the soil erosion rate (dependent variable) with landscape metrics (independent variables). \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Mean Soil Erosion Rate**} & \multicolumn{4}{c}{**Landscape Metrics (2020)**} \\ \cline{2-11}
**Land Cover Classes** & **1** & **2** & **5** & **6** & _PD_ & _ED_ & _LPI_ & **ENN\_AM** & _PLAND_ & **SPLIT** \\ \hline Cropland & 6 & 4.73 & 4.34 & 4.014 & 25.9 & 157.9 & 18.6 & 61.64 & 31.12 & 26.4 \\ \hline Woodland and forest & 0.67 & 2.06 & 0.61 & 2.6 & 5.57 & 20.18 & 0.43 & 81.42 & 2.51 & 41194.35 \\ \hline Grassland & 3.06 & 5.24 & 1.16 & 2.89 & 22.2 & 95.58 & 2.81 & 63.47 & 18.43 & 444.27 \\ \hline Heathland and shrub & 0.1 & 6.62 & 0.06 & 4.33 & 26.5 & 202.5 & 20.6 & 60.44 & 47.14 & 20.22 \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Landscape metrics and mean soil erosion rate for 2020 for each land cover class.