## 2 Study Area and Dataset  
The study area is located in Gongju province, South Korea, as shown in Figure 1. Gongju is 864.29 km\({}^{2}\) in area, about 0.95% of the total area of South Korea (99,407.9 km\({}^{2}\)). The area of cultivated land is 185.82 km\({}^{2}\), accounting for 19.76% of the total area. Forests constitute 70% of the area and there are many hills mountainous areas of 200-300 m above sea level. The average temperatures are around 11.8 \({}^{\circ}\)C in spring, 24.7 \({}^{\circ}\)C in summer, 14.0 \({}^{\circ}\)C autumn, and \(-\)0.9 \({}^{\circ}\)C in winter. The average annual precipitation is 1466 mm. The soils are loamy soils and clay loans and at the bottom it has sand soils. The image of the study area covers a 3.25 km\({}^{2}\) area that is 2344.8 m in length and 1385.76 m in width. The RGB aerial orthophoto shows the spatial distribution of forests in the study area. Most forests are present on steep-sloped mountains and the types of forest include coniferous/broad-leaved forests and artificial/natural forests. Figure 2 shows the three types of forest classification map that are based on vertical structure, dominant species' leaf type, and whether the forest is natural or artificial. These maps were classified based on field survey measurements collected as a part of the Korean 3 rd natural environment conservation master plan. The measurements were collected for the whole country over a period of six years from 2006 to 2012. The field survey of the study area was performed in 2009. The fourth masterplan started in 2014 and is due to be completed in 2018. The database construction for the fourth masterplan has not been completed. Figure 2a shows that triple-layered forests were dominant in the study area, and hence the natural forests are shown to be dominant in Figure 2c because the artificial forests are generally single- or double-layered. The study area includes a variety of different forest types including: (i) single-, double-, and triple-layered forests (Figure 2a); (ii) broad-leaved, coniferous, and mixed forests (Figure 2b); and, (iii) natural and artificial forests (Figure 2c). Figure 3 shows examples of single-, double-, and triple-layered forests. Figure 3a shows an example of a single-layered forest. The forest is a chestnut plantation that the image shows to have been uniformly planted. Thus, it can be understood that it is an artificial forest. In Figure 3b, the image was acquired from a double-layered forest. It is a coniferous forest and the nut pine is dominant. The red reflectance value of coniferous trees was lower than that of broad-leaved trees based on analysis of the RGB image. This confirmed that the brightness is dependent upon species. Considering that coniferous forests are mainly single- or double-layered, species identification could be an important part of the classification of vertical structure. Figure 3c shows an example of a triple-layered forest. The forest is broad-leaved and oak is dominant tree type. Natural forests are a mixture of various species, and may contain coniferous and broad-leaved trees. Therefore, it is expected that it will be more useful to analyze height differences between trees rather than the identification of tree species in the classification of triple-layered forests. As mentioned above, single- and double-layered forests are mostly artificial forests. Artificial forests in the study area include broad-leaved forests, such as the chestnut tree forest, as well as coniferous forests such as the nut pine forest. The RGB orthophoto was obtained using a DMC II airborne digital camera at an altitude of 1300 m (above sea level) with a redundancy rate of 63% in October 2015. The low-resolution RGB and high-resolution panchromatic (PAN) images were merged to create a high-resolution RGB image. The high-resolution RGB image was then orthorectified and mosaicked. The final mosaicked RGB orthophoto was used for this study.