# Vegetation Classification in Urban Areas by Combining UAV-Based NDVI and Thermal Infrared Image
## 3 Result and Discussion
### Vegetation Classification by Combining UAV-Based NDVI and Thermal Infrared Image  
As a result of trying to send ideas to solve the problem of basketball courts and waterproof-coated roofs misclassified as vegetation, images were taken using a thermal infrared ThermoMAP camera by paying attention to the temperature distribution characteristics of the urethane-coated area. Thermal infrared images taken with a thermoMAP camera were merged using Pix4D Mapper S/W, and then a temperature map was created using ArcGIS S/W, as shown in Figure 15. In order to remove basketball courts and waterproof coating roofs that are incorrectly classified as vegetation based on the temperature information analyzed by UAV, it is necessary to set the temperature threshold between artificial structures and vegetation. The study by [PERSON] et al. (2021) [52] analyzed the temperature distribution characteristics according to the roof material and the type of roof coating. [PERSON] et al. (2021) [52] analyzed the temperature characteristics of the urethane coating area when the average cloud cover was 8.5, and the maximum temperature was 31 \({}^{\circ}\)C. The average temperature of the urethane \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Land Cover**} & \multicolumn{5}{c}{**Reflectance**} & \multirow{2}{*}{**NDVI**} \\ \cline{2-2} \cline{4-6}  & **Blue** & **Green** & **Red** & **Nir** & \\ \hline Tree & \multirow{2}{*}{0.0098} & \multirow{2}{*}{0.0523} & \multirow{2}{*}{0.0133} & \multirow{2}{*}{0.4039} & \multirow{2}{*}{0.9362} \\ (vegetation: high) & & & & & \\ \hline Grass & \multirow{2}{*}{0.0311} & \multirow{2}{*}{0.0778} & \multirow{2}{*}{0.0489} & \multirow{2}{*}{0.2825} & \multirow{2}{*}{0.7048} \\ (vegetation: medium) & & & & & \\ \hline Grass & \multirow{2}{*}{0.0291} & \multirow{2}{*}{0.0661} & \multirow{2}{*}{0.0903} & \multirow{2}{*}{0.2317} & \multirow{2}{*}{0.4391} \\ (vegetation: slightly low) & & & & & \\ \hline Basketball court & \multirow{2}{*}{0.1363} & \multirow{2}{*}{0.2097} & \multirow{2}{*}{0.1093} & \multirow{2}{*}{0.2733} & \multirow{2}{*}{0.4286} \\ \hline Waterproof & \multirow{2}{*}{0.0776} & \multirow{2}{*}{0.1017} & \multirow{2}{*}{0.0519} & \multirow{2}{*}{0.1276} & \multirow{2}{*}{0.4217} \\ Coating roof & & & & & \\ \hline Road & \multirow{2}{*}{0.3766} & \multirow{2}{*}{0.4349} & \multirow{2}{*}{0.4722} & \multirow{2}{*}{0.4429} & \multirow{2}{*}{\(-\)0.0320} \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Reflectance by bands (R, G, B and Nir) and NDVI for each land cover using ASD Field-Spec4 spectrometer. Figure 15: Temperature map analyzed from UAV-based thermal infrared image. coating area showed a difference of about 5 \({}^{\circ}\)C from the day's highest temperature. In this study, when the thermal image was taken, the average cloudiness was 8.1, the maximum temperature was 30 \({}^{\circ}\)C, and the basketball court and waterproof coating roof were coated with urethane. Accordingly, the highest temperature on the measurement day was set to 30 \({}^{\circ}\)C as the temperature threshold for classification with vegetation by referring to the literature. Figure 16 shows the vegetation map classified by combining NDVI and thermal infrared image. It was confirmed that the basketball court and the waterproof coating roof coated with urethane were well classified as non-vegetation areas. Table 8 shows the results of analyzing the vegetation and non-vegetation area for each apartment complex from the vegetation map finally generated using NDVI and thermal infrared images. To evaluate the accuracy of the vegetation map analyzed using only the NDVI index and the vegetation map analyzed by combining the NDVI vegetation index with the thermal image, a validation point was selected as shown in Figure 17. For the target area, 4409 verification points were selected at 5 m intervals, and classified into vegetation and non-vegetation through field surveys.