## 3 Results and Discussion
\begin{table}
\begin{tabular}{c|c c c c c c c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Urban**} & \multicolumn{4}{c}{**Transitional**} & \multicolumn{4}{c}{**Suburban**} \\ \cline{2-13}
**LULC** & **2009** & **2015** & **2018** & **2009** & **2015** & **2018** & **2009** & **2015** & **2018** & **2009** & **2015** & **2018** \\ \cline{2-13}
**CLASS** & **HRC** & **HRC** & **HRC** & **HRC** & **HRC** & **HRC** & **HRC** & **HRC** & **HRC** & **HRC** & **HRC** & **HRC** & **HRC** \\  & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** & **HRC\_e** \\ \hline
**Building** & 39.1 & 36.4 & 34.6 & 35.4 & 33.0 & 34.6 & 15.4 & 14.1 & 23.4 & 20.8 & 25.7 & 22.3 & 1.9 & 0.1 & 2.0 & 2.0 & 3.5 & 3.2 \\
**Paved** & 3.0 & 6.7 & 0.0 & 6.3 & 1.1 & 7.1 & 0.0 & 4.2 & 0.0 & 5.2 & 1.6 & 5.7 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 \\
**Unpaved** & 0.0 & 0.3 & 0.0 & 0.3 & 0.4 & 0.5 & 0.0 & 1.5 & 0.7 & 1.5 & 0.0 & 0.9 & 1.4 & 2.0 & 4.1 & 5.3 & 2.0 & 4.4 \\
**Baze land** & 2.5 & 6.1 & 10.6 & 12.6 & 10.6 & 12.3 & 9.8 & 14.5 & 9.8 & 17.7 & 36.6 & 8.3 & 2.8 & 2.9 & 15.2 & 18.0 & 14.8 & 13.3 \\
**HighVeg** & 38.9 & 44.6 & 32.8 & 35.5 & 37.4 & 38.4 & 44.4 & 48.7 & 37.8 & 45.4 & 49.2 & 49.3 & 67.6 & 78.0 & 6.2 & 64.2 & 56.5 & 56.9 \\
**LowVeg** & 2.5 & 5.9 & 8.5 & 9.8 & 4.8 & 6.9 & 17.6 & 20.1 & 5.0 & 9.2 & 6.5 & 13.2 & 151.1 & 17.0 & 8.5 & 10.5 & 14.7 & 22.2 \\
**Shadow** & 14.1 & 0.0 & 13.6 & 0.0 & 12.7 & 0.0 & 10.9 & 0.0 & 23.2 & 0.0 & 13.4 & 0.0 & 11.2 & 0.0 & 7.6 & 0.0 & 8.6 & 0.0 \\
**Water** & 0.0 & 0.0 & 0.0 & 0.1 & 0.0 & 0.2 & 0.0 & 0.7 & 0.0 & 0.2 & 0.0 & 0.3 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 \\
**Cloud** & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 2.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Land use/land cover (LULC) classification obtained for each land cover class, study area, and image year. The columns for each year show the percentages obtained in the high resolution classification (HRC) and edited high resolution classification (HRC_e), respectively. three study sites. A visual examination indicates that small patches of vegetation or even single trees can be distinguished from man-made infrastructures. It demonstrates the potential of the classification methodology to define and analyze, from a spatial perspective, the distribution of different spaces in urban areas. An initial approach for the quantification of urbanized and vegetated areas can be done based on the HRC. The resulting percentages indicate the most prominent LULC classes for each year and study site. In contrast, these values are not sufficient to interpret certain aspects. For example, the area covered by paved streets is not congruent with the reality, but was, only after obtaining the HRC_e. The diversity of elements, and therefore, the color pixels of houses and streets tend to be classified in  
Figure 3: Study area ‘Urban’ in 2009 (**Top**), and its corresponding HRC (**bottom-left**) and HRC_e (**bottom-right**) LULC classifications. several LULC classes, in some cases mixing them. Another issue is observed in the temporal variation of a specific class. In the 'Urban' area, the buildings seem to have been reduced in number during the last decade, but in fact, this result is a consequence of the training input set by the user. As observed in Figure 3, the user initially classified clouds as buildings, provided that a post-edition is created. This was due to the similar colors of white roofs and clouds, which led to an inevitable misclassification. As a result, the values given in Table 2 do not show the real area covered by clouds, but increase the buildings' area intentionally. That subject influences the analysis of a land use change from the HRC. Therefore, only a general distribution of LULC can be derived from HRC, making post-processing necessary, in order to obtain correct interpretations. The HRC_e provides more reliable results.