## 2 Materials and Methods
### Data Sources and Preprocessing  
We used digitally georeferenced orthorectified aerial photographs taken by the Geospatial Information Authority of Japan (GSI) that were purchased from the Japan Map Center ([[https://www.jmc.or.jp/](https://www.jmc.or.jp/)]([https://www.jmc.or.jp/](https://www.jmc.or.jp/)), accessed on 18 June 2019). Orthorectification was applied only to the RGB bands; data in the form of 30\({}^{\prime\prime}\)\(\times\) 30\({}^{\prime\prime}\) tiles were available. The orthophoto tiles use the JGD2000 or JDG2011 datum geographical coordinate system. The entire study area is covered by three blocks of GSI aerial photographs collected in different years. Four image tiles were acquired on 25 November 2012 over the Katsuura Tateyama district at a height of 2000 m. The size of each photograph was 3750 \(\times\) 4650 pixels and the ground sample distance (GSD) was 0.2 m. One hundred image tiles were acquired on 27 October 2017 over the Katsuura Otaki district at a height of 4000 m. The size of each photograph was \(1875\times 2325\) pixels and the GSD was 0.4 m. Finally, 144 image tiles were acquired on 15 July 2017 over the Minami Boso district at a height of 2350 m. The size of each photo  
Figure 1: Location of the study area and views of typical forest sites. NMX, NBL, and CP indicate natural mixed forest, natural broadleaved forest, and conifer plantation, respectively. The aerial photographs form three datasets collected at different times in the Katsuura Tateyama, Katsuura Otaki, and Minami Boso districts. The aerial photographs were taken by Geospatial Information Authority of Japan.  
graph was 1875 \(\times\) 2325 pixels and the GSD was 0.2 m. We resampled all photographs to a resolution of 0.2 m using the nearest neighbour algorithm [82], mosaicked them into a single tile, and ensured compatibility of the data with JGD_2011_Japan_Zone_9 projection using ArcGIS software version 10.8 (Esri Inc., Redlands, CA, USA). We used TNTmips for linear raster contrast enhancement of the mosaicked image. Since 1970, the NMXs have not been logged, except to remove obstructive trees [83]. Until the early 1960s, the NBLs were used as fuelwood forests, but logging has been minimal since 1980 [83]. Although the aerial photographs were taken in 2012 and 2017, we assumed that the boundaries between forest types did not change greatly over this period.  
The fully annotated ground truth classification map was used as the forest type map of the entire UTCBF (Figure 2). This was produced by UTCBF staff in vector format based on a forest map compilation, forest register, inventory data, and aerial photograph interpretations. The original map had a scale of 1:10,000 and was converted into a raster format tiff file that covered 35,152 \(\times\) 41,152 pixels using the 'polygon to raster' method in ArcGIS. We reclassified the original classes into three types: NMX, NBL, and CP; other categories, such as the nursery and forest museum [81] used for education and research, covered very small areas and were not considered in this study. The images of these areas were removed, set as non-forest background (BG), and assigned a value of 255. The ground truth map was processed using the raster extraction boundary of UTCBF and then overlapped with the mosaic aerial photograph using the 'extract by mask' routine of ArcGIS to create an aerial photographic image of the same scale and spatial resolution as the ground truth map.  
The aerial photograph and ground truth map, both of which are 35,152 \(\times\) 41,152 in size, were cropped into 512 \(\times\) 512 tiles without any repetition or overlap to ensure that each image was completely unique. Tiles lacking pixel values were removed. We randomly separated the remaining image and ground truth maps into three parts into training, evaluation, and test datasets at a ratio of 8:1:1 (1981, 248, and 248 image tiles, respectively).