# A Novel Index to Detect Vegetation in Urban Areas Using UAV-Based Multispectral Images
## 5 Conclusions  
Accurate vegetation data are vital in various fields, such as urban planning, landscaping, and water quality analysis. In recent years, in order to effectively promote urban regeneration projects, research efforts have attempted to quantitatively analyze the distribution of vegetation in cities using satellite images or UAV images. In particular, vegetation indices, such as NDVI, are widely used for vegetation analysis using remote sensing technologies, such as satellite images and UAV images.  
Various types of land cover, such as long-run steel roofing, waterproof coated roofs, and urethane-coated areas, exist in urban areas, and this study found that existing vegetation indices assign inappropriately high values to such areas. Therefore, in this study,  
Figure 13: Vegetation map and validation points based on the squared Red-Blue NDVI index.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Ground Truth**} & \multicolumn{2}{c}{**Squared Blue-Green NDVI Index**} & \multicolumn{2}{c}{**Squared Red-Green NDVI Index**} & \multicolumn{2}{c}{**Squared Red-Blue NDVI Index**} \\ \cline{2-7}  & **Vegetation** & **Non-Vegetation** & **Vegetation** & **Non-Vegetation** & **Vegetation** & **Non-Vegetation** \\ \hline Vegetation & 20 & 0 & 20 & 0 & 20 & 0 \\ (20 points) & 5 & 25 & 5 & 25 & 0 & 30 \\ \hline Kappa & 0.8 & & 0.8 & & 1.0 \\ coefficient & & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 8: Kappa coefficient analysis for vegetation classification.  
existing vegetation indices, such as NDVI, GNDVI, BNDVI, RGBVI, GRVI, and SAVI, were used to quantitatively analyze the vegetation index values of different types of land cover. This was done based on high-resolution multispectral images taken by a UAV equipped with a Micasense RedEde MX camera.  
As mentioned above, the vegetation index values of long-run steel roofing, waterproof coated roofs, and urethane-coated areas were similar to or higher than those of grass with a slightly low degree of vitality. To address the problem of misclassification according to the characteristics of urban land cover, a test was conducted by combining multiple spectral bands. Finally, three equations were selected and analyzed.  
According to a kappa coefficient analysis, the squared Red-Blue NDVI index, which was created by combining information from the blue, red, and near-infrared bands, most accurately reflected the characteristics of urban land cover. The novel vegetation index presented in this study is expected to be very useful in analyzing the vegetation in regions with various types of land cover when conducting urban regeneration projects in the future.  
Conceptualization, G.-S.L. and S.-H.C.; methodology, G.-S.L. G.H. and S.-H.C.; investigation, G.-S.L. and S.-H.C.; writing--original draft preparation, G.-S.L. G.H. and S.-H.C.; writing--review and editing, G.-S.L. G.H. and S.-H.C.; visualization, G.-S.L. and S.-H.C.; supervision. G.H. and S.-H.C.; project administration, G.H. and S.-H.C. All authors have read and agreed to the published version of the manuscript  
This research was supported by a grant (21 TSRD-B151228\(-\)03) from the Urban Declining Area Regenerative Capacity-Enhancing Technology Research Program funded by the Ministry of Land, Infrastructure and Transport of the Korean government.  
Not applicable.  
The authors declare no conflict of interest.