2008 
1125 
LAND COVER CLASSIFICATION FOR FUTURE-ORIENTED DEVELOPMENT PLAN 
OF MULTIFUNCTIONAL ADMINISTRATIVE CITY OF KOREA 
Han, Seung-Hee a ’ *, Lee, Jin-Duk b 
a *Dept. of Civil & Environmental engineering, Kongju National University, Seoul KOREA - shhan@kongju.ac.kr 
b Dept, of Civil & Environmental engineering, Kumoh National Institute of Technology, Seoul KOREA - 
jdlee@kumoh.ac.kr 
Commission VII, WG VII/6 
KEY WORDS: KOMPSAT2, Land cover classification, Aster, Objected based classification 
ABSTRACT: 
In this study, land cover classification and NDVI evaluation are carried out in surrounding areas of Yeongi-gun, Chungcheongnam- 
do (132km 2 ) where a project for multi-functional administrative city is promoted by the Korean government. Image acquired from 
KOMPSAT 2, LANDSAT and ASTER is utilized and comparative evaluation on limitation in classification based on resolution was 
carried out. The area mainly consists of arable land including mountains, rice fields, ordinary fields, etc thus special attention was 
paid to the classification of rice fields and ordinary fields. For the classification of image acquired from KOMPSAT 2, segmentation 
technique for classification of high-resolution image was applied. To evaluate the accuracy of the classification, field investigation 
was conducted to examine the sample and it was compared with the land usage and classification of land category in land ledger of 
Korea. Acquired results were made into theme map in shape file format and it would be of great help in decision making of policy 
for the future-oriented development plan of multi-functional administrative city. 
1. INTRODUCTION 
1.1 General Instructions 
To acquire recent middle classification land coverage, coverage 
classification using high resolution satellite image is effective 
method. However, in case of applying the high resolution image 
to previously pixel based coverage classification method. In 
case of high resolution panchromatic image or multi-spectral 
image, necessary information shall be extracted based on 
spatial/spectral traits. It is trend to classify using the region of 
interest defined as the spatial/spectral traits and surface traits in 
image, namely, object based classification method. 
In this study, not only classification with previous pixel based 
classification method regarding the Seijong-si, the multi 
functional administrative city, using Aster image but also object 
based coverage classification using high resolution image of 
KOMPSAT2 was carried out. Also, it shall be compared with 
the result of image classification using the naked-eye distinction 
and spectral traits for the verification on coverage classification 
of high resolution image. Also, land use thematic map was 
created using the land category of cadastral map and it was 
compared with result of coverage classification. 
2. OBJECT BASED CLASSIFICATION 
When applying high resolution image to previous pixel based 
classification method, it is difficult to use with variation of each 
trait of pixel since it is classified in scatter. Namely, high 
resolution image has severe spectral variation and there is 
limitation for classification in unit of pixel. Ultimately, previous 
classification algorithm has no meaning in high resolution. 
(Van der Sande, et al.,2003). Therefore, it is a strategy to 
classify large unit in previous unit of pixel and apply spatial 
classification method in unit of shape for small unit. In this 
study, object based classification method as Figure 1 was 
applied. Looking into the stage of classification in Picture 1, 
region of pixel is separated by determining the cluster size to 
classify segment regarding the image, namely resolution. 
Determination of resolution cannot be complete at once and it 
should go through trial & error process based on experience. 
The next stage is to calculate the attributes of each region such 
as spatial, wavelength, band ratio, etc and save the data to 
memory. Supervised classification rule based classification is 
processed after defining the objects within image. Rule based 
classification is the method to grant the attribute by rule set 
intervened of subjectivity of operator with form of segment, 
NDVI, texture, ratio of length and height. 
Figure 1. Workflow for Objected based classification