## 2 Materials and Methods
### DLSS Data Construction  
#### 2.2.1 TSUI Acquisition  
The UAV image acquisition was carried out in good weather conditions with low cloud cover, and the shooting time was from 10:00 a.m. to 3:00 p.m., taking into account the effect of mountain shading due to the altitude of the sun. The image data acquired in this study were collected using the KD-2 Mapper as a fixed-wing UAV and the RedEdge-M camera of Mica Sense (Table 2). RedEdge-M has 5 bands of blue, green, red, red-edge and near infra-red. To improve the radiometric quality of the imagery, a downwelling light sensor (DLS) is mounted on the top of the drone with the RedEdge-M. The DLS is a 5-band incident light sensor that connects directly to a MicaSense RedEdge-M camera. The DLS measures the ambient light during a flight for each of the five bands of the camera and records this information in the metadata of the TIFF images captured by the camera [24]. Before shooting, we used the Automatic Calibration Panel provided by Mica Sense to place the RedEdge sensor 1 m above the calibration panel, and then acquired metadata related to the calibration and corrected the reflection value by detecting the QR code and the panel to avoid shadows. With this information, PIX4 Dmapper S/W (ver.4.7.5) [25] was used to correct for global lighting changes in the middle of a flight, such as those that can happen due to clouds covering the sun.  
The flight altitude for image acquisition was set to approximately 350 m sea level [26], taking into account the surrounding topography, target site altitude above sea level, battery power, and wind impact. All of the sites analyzed are mountainous, with summits around 200-250 m above sea level. For example, the summit of Maebong Mt. in Bonghan-ri is 220 m, and Hyung Mt. in Jungmyeong-ri is 257.1 m. Therefore, we took into account the altitude of the mountainous terrain and adjusted the flight altitude to match the ground sample distance of 5.00-6.50 cm for each destination.  
Figure 1: Study sites.  
For overlap and sidelap, the rate was set high at 80% to prevent blind spots in forest regions. Prior to imaging, the automatic calibration panel provided by Mica Sense was used, and the RedEdge sensor was positioned 1 m above the calibration panel. Next, to prevent shading, the QR code and panel detection were used to collect the meta data regarding calibration and correct the reflectance. The acquired image data were merged using the PIX4 Dmapper S/W (ver.4.7.5). Orthophotos were produced through the matching between the collected images and the ground control point determined based on the GRS80 TM coordinates obtained from the global navigation satellite system (GNSS) measurements. In addition, the accurate positional data of PWDT were obtained from the Korea Forestry Promotion Institute. The respective data were in relation to the central datum point determined based on the GRS80 TM coordinates. Next, the acquired TSUI were standardized for the positional data of PWDT with varying central points towards the central datum point using the QGIS S/W (ver.3.16.10) [27]. In addition, to minimize the coordinate errors between each TSI image, the UAV Imagery was calibrated. In this process, the coordinate reference function of the QGIS S/W (ver.3.16.10) was used to calibrate the images based on the primary TSI images. This was due to potential fine differences even among TSI images obtained in identical conditions as the wind speed could have had an influence, and as such microscopic differences on small-scale images could underlie substantial differences on larger scales of actual size.