• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.561-571
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• 2019

In this paper, we analyze the effect of the representative spectral indices, normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI) on classification accuracies of Landsat-8 OLI image.After creating these spectral index images, we propose five methods to select the spectral index images as classification features together with Landsat-8 OLI bands from 1 to 7. From the experiments we observed that when the spectral index image of NDVI or NDWI is used as one of the classification features together with the Landsat-8 OLI bands from 1 to 7, we can obtain higher overall accuracy and kappa coefficient than the method using only Landsat-8 OLI 7 bands. In contrast, the classification method, which selected only NDBI as classification feature together with Landsat-8 OLI 7 bands did not show the improvement in classification accuracies.

• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.293-302
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• 2015

Water body extraction is significant for flood disaster monitoring using satellite imagery. Conventional methods have focused on finding an index, which highlights water body and suppresses non-water body such as vegetation or soil area. The Normalized Difference Water Index (NDWI) is typically used to extract water body from satellite images. The drawback of NDWI, however, is that some man-made objects in built-up areas have NDWI values similar to water body. The objective of this paper is to propose a new method that could extract correctly water body with built-up areas in before and after images of flood. We first create a two-element feature vector consisting of NDWI and a Near InfRared band (NIR) and then select a training site on water body area. After computing the mean vector and the covariance matrix of the training site, we classify each pixel into water body based on Mahalanobis distance. We also register before and after images of flood using outlier removal and triangulation-based local transformation. We finally create a change map by combining the before-flooding water body and after-flooding water body. The experimental results show that the overall accuracy and Kappa coefficient of the proposed method were 97.25% and 94.14%, respectively, while those of the NDWI method were 89.5% and 69.6%, respectively.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.598-601
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• 2007

Urban growth management is essential for sustainable urban growth. Monitoring physical urban built-up area is a task of great significance to manage urban growth. Detecting urbanized area is essential for monitoring urbanized area. Although image classifications using satellite imagery are among the conventional methods for detecting urbanized area, they requires very tedious and hard work, especially if time-series remote sensing data have to be processed. In this paper, we propose an effective urbanized area detecting method based on normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). To verify the proposed method, we extract urbanized area using two methods; one is conventional supervised classification method and the other is the proposed method. Experiments shows that two methods are consistent with 98% in 1998, 99.3% in 2000, namely the consistency of two methods is very high. Because the proposed method requires no more process without band operations, it can reduce time and effort. Compared with the supervised classification method, the proposed method using vegetation indices can serve as quick and efficient alternatives for detecting urbanized area.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.142-154
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• 2010

The purpose of this study is to analyze the effects of various spatial characteristics on the land surface temperature and to grasp the characteristics of thermal environment by types of urban area in Changwon, Gyeongsangnam-do. The spatial data were consisted LST, normalized difference built-up index(NDBI) and normalized difference vegetation index(NDVI) obtained from Landsat 5 TM and land use and land cover map classified from high resolution digital aerial photograph($10cm{\times}10cm$). The unit space for spatial analysis was built by $500m{\times}500m$ Vector GRID. According to the results of estimation of relationship between thermal environment and spatial characteristics, LST had the highest positive correlation with NDBI by 0.929 and had high positive correlation with impervious area ratio by 0.857. In order to analysis of thermal environment on land use, types of urban area were classified by 4 of residential focus area, industrial focus area, green focus area and mixed area. According to the results of analysis, mean LST of industrial focus area was showed the highest by $21.10^{\circ}C$. But mean LST of green focus area was analyzed the lowest by $18.85^{\circ}C$. In conclusion, the results of this study investigated the effects of spatial characteristics on urban thermal environment and can provide methods and basic informations about land use planning and development density restriction for reduction of urban heat.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.54-68
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• 2014

In order to analyze the land surface properties in Seoul and its surrounding metropolitan area, several indices and land surface temperature were calculated by the Landsat satellites (e.g., Landsat 5, Landsat 7, and Landsat 8). The Landsat data came from only in the fall season with Landsat 5 on October 21, 1985, Landsat 7 on September 29, 2003, and Landsat 8 on September 16, 2013. The land surface properties used are the indices that represented Soil Adjusted Vegetation Index (SAVI), Modified Normalized Difference Wetness Index (MNDWI), Normalized Difference Wetness Index (NDWI), Tasseled cap Brightness, Tasseled cap Greenness, Tasseled cap Wetness Index, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) and the land surface temperature of the area in and around Seoul. Most indices distinguish very well between urban, rural, mountain, building, river and road. In particular, most of the urbanization is represented in the new city (e.g., Ilsan) around Seoul. According to NDVI, NDBI and land surface temperature, urban expansion is displayed in the surrounding area of Seoul. The land surface temperature and surface elevation have a strong relationship with the distribution and structure of the vegetation/built-up indices such as NDVI and NDBI. While the NDVI is positively correlated with the land surface temperature and is also negatively correlated with the surface elevation, the NDBI have just the opposite correlations, respectively. The NDVI and NDBI index is closely associated with the characteristics of the metropolitan area. Landsat 8 and Landsat 5 have very strong correlations (more than -0.6) but Landsat 7 has a weak one (lower than -0.5).

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1403-1415
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• 2019

Urban population growth and consequent rapid urbanization involve some thermal environmental problems in the cities. Monitoring of thermal environments in urban areas such as hot spot analysis is required for effective actions to resolve these problems. This study selected 14 dongs and surrounding administrative districts of Sejong city as study areas and analyzed the characteristics of changes in surface temperature due to the urban expansion in the summer from 2013 to 2018. In the study, the surface temperature distributions in the study areas were plotted using surface temperature values from Landsat 8 and NDVI (Normalized Difference Vegetation Index) and NDBI (Normalized Difference Built-up Index) based on KOMPSAT 2/3 data, and the patterns of surface temperature changes with urban expansion were discussed using the estimated NDVI and NDBI. In particular, the distinct urbanization in the study areas were selected for case studies, and the cause of the changes in the hot spots in the regions was analyzed using high-resolution KOMPSAT images. This study results present that hot spots appeared in urbanized regions within the study areas, and it was plotted that the lower the NDVI values and the higher the NDBI values indicate the temperature values are high. The land surface temperature and satellite-based products were used to divide the study areas into continuously urbanized regions and rapidly urbanized regions and to identify the different characteristics depending on land covers. In the regions with distinct surface temperature changes by urbanization, the analysis using high-resolution KOMPSAT images as presented in this study could provide effective information for urban planning and policy utilization in the future.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.53-58
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• 2020

The purpose of this study is to build a database of Spatial information Bigdata of cities using satellite images and spatial information, and to examine the correlations with the surface temperature. Using architectural structure and usage in building information, DEM and Slope topographical information for constructed with 300 × 300 mesh grids for Busan. The satellite image is used to prepare the Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BI), and Land Surface Temperature (LST). In addition, the building area in the grid was calculated and the building ratio was constructed to build the urban environment DB. In architectural structure, positive correlation was found in masonry and concrete structures. On the terrain, negative correlations were observed between DEM and slope. NDBI and BI were positively correlated, and NDVI was negatively correlated. The higher the Building ratio, the higher the surface temperature. It was found that the urban environment DB could be used as a basic data for urban environment analysis, and it was possible to quantitatively grasp the impact on the architecture and urban environment by adding local meteorological factors. This result is expected to be used as basic data for future urban environment planning and disaster prevention data construction.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.129-139
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• 2019

Mapping urban areas using the earth observation satellites is useful for monitoring urban expansions and measuring urban developments. In this research, the different thresholds for detecting the urban areas separately from the remote-sensing index images (normalized-difference built-up index(NDBI) and urban index(UI) images) generated from the Landsat-8 image acquired in Daegu, South Korea were evaluated through the following steps: (1) the NDBI and UI images were separately generated from the given Landsat-8 image; (2) the different thresholds (-0.4, -0.2, and 0) for detecting the urban areas separately from the NDBI and UI images were evaluated; and (3) the accuracy of each detected urban area was assessed. The experiment results showed that the threshold -0.2 had the best performance for detecting the urban areas from the NDBI image, while the threshold -0.4 had the best performance for detecting the urban areas from the UI image. Some misclassification errors, however, occurred in the areas where the bare soil areas were classified into urban areas or where the high-rise apartments were classified into other areas. In the future research, a robust methodology for detecting urban areas, including the various types of urban features, with less misclassification errors will be proposed using the satellite images. In addition, research on analyzing the pattern of urban expansion will be carried out using the urban areas detected from the multi-temporal satellite images.

• Journal of Environmental Impact Assessment
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• v.31 no.4
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• pp.241-249
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• 2022

Humans and wild birds coexist in cities, where habitat fragmentation due to urbanization threatens the habitat and movement of birds. In this study, in order to identify landscape features associated with wild bird collide, we characterized landscape composition within a 500 m radius and points of wild bird carcasses in Suwon-city, South Korea. Dead birds were identified as having a Normalized Difference Vegetation Index (NDVI) of 0.3, Normalized Difference Built-up Index (NDBI) of -0.05, and Normalized Difference Water Index (NDWI) of -0.16 at the points of collide. And there were NDVI of 0.34, NDBI of -0.01, NDWI of -0.18, building height of 13.8 m, and soundproof wall length of 227.3 m within a radius of 500 m. Land cover type was dominated by grassland, used area, and bare land. In particular, the edges of urbanized areas, where apartments bordered forests, reservoirs, and golf courses, were identified as high-risk spaces. In order to minimize bird mortality risk in urban environments, the impact of changes to a vertical landscape should be reviewed from an environmental impact assessment approach. In addition, a preventive management plan that considers the temporal and spatial features that wild animals can safely avoid and adapt to in urbanized spaces should be prepared.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.3
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• pp.61-69
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• 2008

Land-use in northern Cheongju region is changing rapidly because of the increased interactions of human activities with the environment as population increases. Land-use change detection is considered essential for monitoring the growth of an urban complex. The analysis was undertaken mainly on the basis of the multi-temporal Landsat images (1991, 1992 and 2000) and DEM data in a post-classification analysis with GIS to map land-use distribution and to analyse factors influencing the land-use changes for Cheongju city. The area of each land-use category was also calculated for monitoring land-use changes. Land-use statistics revealed that substantial land-use changes have taken place and that the built-up areas have expanded by about $17.57km^2$ (11.47%) over the study period (1991 - 2000). This study illustrated an increasing trend of urban and barren lands areas with a decreasing trend of agricultural and forest areas. Land-use changes from one category to others have been clearly represented by the NDVI composite images, which were found suitable for delineating the development of urban areas and land use changes in northern Cheongju region. Rapid economic developments together with the increasing population were noted to be the major factors influencing rapid land use changes. Urban expansion has replaced urban and barren lands.