# Land Cover Classification Using a KOMPSAT-3A Multi-Spectral Satellite Image
## 2 Materials and Methods
### Data  
The high resolution multispectral data used in the study was taken by KOMPSAT-3A on 17 June 2016. The data used in the study was purchased from KARI using the Arirang Satellite Image Search and Order System (ASISOS) portal. The provided data consisted of Blue (B), Green (G), Red (R), Near InfraRed (NIR) and Panchromatic images in GeoTIF format. The spectral wavelength ranges and the spatial resolution bands of KOMPSAT-3A are presented in Table 1. The image quality of the study area was good and cloud-free.  
Initially, the radiometrically corrected satellite image was composited to form a single multiband image and then was geometrically corrected in ArcGIS 10.3 software (Environmental Systems Research Institute, Redlands, CA, USA) through geo-referencing and rectifying. As the data consists of only four bands, for better classification inputs, all possible ratios (B/G, B/R, B/NIR, G/R, G/NIR and R/NIR) and extra Normalized Difference Vegetation Index (NDVI) [9] and Normalized Difference Water Index (NDWI) [10] were derived. Equations (1) and (2) shows the formulae for the calculation of NDVI and NDWI respectively. Again, all the original bands and derived ratio and index bands were composited to form a new multispectral image with 12 bands.  
\[\text{Normalized Difference Vegetation Index (NDVI) = (NIR - Red)/(NIR + Red)}, \tag{1}\] \[\text{Normalized Difference Water Index (NDWI) = (Green - NIR)/(Green + NIR)}, \tag{2}\]  
The high resolution georeferenced natural color image, panchromatic image and expert knowledge were used to derive training data for image classification and validation data for overall accuracy  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Band No.** & **Band Name** & **Spectral Ranges (nm)** & **Spatial Resolution (m)** \\ \hline
1 & Blue (B) & 450–520 & 2.2 \\
2 & Green (G) & 520–600 & 2.2 \\
3 & Red (R) & 630–690 & 2.2 \\
4 & Near Infrared (NIR) & 760–900 & 5.5 \\
5 & Panchromatic & 450–900 & 0.55 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Spectral Bands of Korea Multi-Purpose Satellite (KOMPSAT)-3A.  
Figure 2: Location of the study area in Korea: (**a**) Full KOMPSAT-3A scene in a natural color composite image taken on 17 June 2016; (**b**) False color composite of study area.  
assessment. As the high resolution images have many mixed pixels and it is not efficient in terms of time spent to assign them to a class one by one, we discarded the sampling of points. Hence, polygons were sampled randomly in the study area and classes were assigned to the polygons. All the pixels in the polygon were converted into points and the points were separated into 70% (76,700 pixels) and 30% (32,900 pixels) for training and validation respectively. For even better validation purposes, random pixels were added to the validation dataset outside the polygons that are not spatially influenced. Figure 3 shows all the sampled polygons in the study with zoomed pixels for better understanding of the sampling concept used in the study.  
Figure 3: Sampling for training and validation: (**a**) Sampled polygons in the study area; (**b**) Zoomed view of a water polygon (white box on left-bottom of Figure 3a); (**c**) Zoomed area with training (**red**) and validation (**blue**) pixels.