# Soil Erosion Assessment and Prediction in Urban Landscapes: A New G2 Model Approach
## 3 Results
### G2 Model Results  
In order to deal with different representations and spatial resolutions of the used input data, first the conversion to 30-m spatial resolution rasters of some datasets was necessary. The 30-m spatial resolution is chosen to match the spatial resolution of the Landsat images and corresponding LC maps. Table 5 lists the overview of all preprocessing procedures performed on input data and corresponding G2 model inputs calculated using them. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Land Cover** & **2001** & **2019** & **Change in Area (km2)** & **Change in Area (\%)** \\ \hline Agricultural areas & 309.10 & 251.41 & \(-57.69\) & \(-18.66\) \\ Grasslands & 88.75 & 67.14 & \(-21.62\) & \(-24.36\) \\ Shrubs & 77.26 & 111.07 & 33.80 & 43.75 \\ Forests & 73.12 & 75.35 & 2.23 & 3.06 \\ Artificial surfaces & 190.87 & 234.88 & 44.00 & 23.05 \\ Water bodies & 39.40 & 38.69 & \(-0.71\) & \(-1.80\) \\ Total & 778.51 & 778.51 & 0.0 & 25.04 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Land cover changes in km2 and percentages. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**2019** & \multicolumn{8}{c}{**Reference [Pixels]**} \\ \hline \multirow{4}{*}{**Plant**} & **Class ID** & **1** & **2** & **3** & **4** & **5** & **6** & **Total** & **UA (\%)** \\  & **1** & 1087 & 2 & 0 & 0 & 0 & 0 & 1089 & 99.82 \\  & **2** & 0 & 76 & 0 & 10 & 0 & 0 & 86 & 88.37 \\  & **3** & 0 & 0 & 4646 & 40 & 5 & 10 & 4701 & 98.83 \\  & **4** & 0 & 14 & 99 & 1040 & 0 & 0 & 1153 & 90.20 \\  & **5** & 0 & 10 & 19 & 109 & 915 & 231 & 1284 & 71.26 \\  & **6** & 0 & 12 & 2 & 12 & 21 & 10,935 & 10,982 & 99.57 \\  & **Total** & 1087 & 114 & 4766 & 1211 & 941 & 11,176 & 19,295 & **OA (\%)** \\  & **PA (\%)** & 100 & 66.67 & 97.48 & 85.88 & 97.24 & 97.84 & & ** Kappa** \\  & & & & & & & & 0.95 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Confusion matrix (pixel-based) of land cover classification map for 2019 (legend for class ID: 1—water bodies, 2—artificial surfaces, 3—forests, 4—shrubs, 5—grasslands, 6—agricultural areas). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Input Dataset** & **Spatial Representation** & **Preprocessing** & **G2 Model** \\  & **Procedure** & **Inputs** \\ \hline Climate data & Location of the meteorological stations & IDW & Factor R \\ EU-DEM & \multirow{2}{*}{Raster (25 m)} & \multirow{2}{*}{Bilinear resampling} & Factor T \\ Pedological map & Polygons obtained from scanned and & & & \\ georeferenced map (scale 1:20,000) & & & \\
**Soil samples** & 47 sites in study area & IDW & Factor S \\ Landsat satellite images and LC maps & \multirow{2}{*}{Raster (30 m)} & \multirow{2}{*}{/} & Factor V \\  & & & & & Factor L \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Preprocessing procedures performed and corresponding G2 model inputs. The spatial distribution of climatic characteristics over the study area was obtained by applying the Inverse Distance Weighted (IDW) interpolation method. The IDW method is chosen because it is fast, simple and commonly used for interpolation of climate variables [82; 83; 84]. The EU-DEM used to describe physical-geographical characteristics also had to be resampled to a 30-m spatial resolution. This was done using the bilinear resampling technique. The last input dataset which required preprocessing is pedological map, available in scale 1:20,000. The vectorized pedology polygons were rasterized, where the output raster is also in 30-m spatial resolution. For detailed determination of the value of factor S, the IDW method was applied to soil samples. It can be considered that polygons can be converted to such spatial resolutions because various sources of errors present in the map (error of primary data acquisition, scanning and georeferencing errors, etc.) do not exceed output spatial resolution. After the input data have been successfully preprocessed, the inputs of G2 model are calculated using the previously described methodology. The results for both time periods were defined and analyzed in the following paragraphs.