• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.22-24
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• 2007

Waterline extraction is the one of widely used methods for studying changes in tidal flat environment and coastlines using multi-temporal optical images such as Landsat TM and Landsat ETM+. High dynamics of tidal currents and land reclamation which accelerate sedimentation and/or erosion cause waterline change in tidal flats. The amount of sediment deposited or eroded can be evaluated by precisely estimating waterline changes in tidal flats. The objective of this study is to detect the change of waterlines during 17 years and analyze the trends of erosion and sedimentation in the study areas. The Ganghwado tidal flat on the west coast of the Korean Peninsula was selected. The study area is famous for high dynamics of tidal currents and vast tidal flats. Land reclamation which has been carried out on a large scale is also considered as one of elements that have accelerated the environmental changes in this tidal flat. In this study, we acquired 26 waterlines from Landsat TM and Landsat ETM+ images. We extracted the waterline from each satellite image to generate a digital elevation map (DEM) which was used for reference and to compare with the other waterline which was extracted from DEM having a same tide. The result of comparison well depicted the areas of dominant sedimentation and erosion, and general trends of sedimentation and erosion according to sub-regions are also revealed during the investigation time. Results showed that erosion during a decade was dominant at the west of the Southern Ganghwado tidal flat, while sedimentation was dominant at the wide channel between the Southern Ganghwado tidal flat and the Yeongjongdo tidal flat. This area has been commonly affected by high currents and sedimentation energy. Although we were not able to verify the accuracy of the waterline changes, this result clearly showed the waterline change and therefore, the waterline extraction method used in this study has proven as an effective tool for long term tidal change estimation.

• Journal of Environmental Impact Assessment
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• v.11 no.4
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• pp.247-258
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• 2002

This study aimed at verifying the grain-sized distribution of surface deposits in a tidal flat using multi-spectral Landsat TM. In this study, we employed the grain-sized analysis, PCA and unsupervised classification techniques for analyzing the distribution of deposits. As a result in this study, the unsupervised classification method using PCA image was found to be most useful in classifying tidal flat deposits using satellite data. This method is considerably effective in analyzing not only the aspects of distribution in terms of accumulated deposits and erosion, but also the changes in seaside topography and shoreline. The grain-sized distribution analysis indicates that the mud flat inside the Cheonsu-bay tidal flat is distributed, the mixed flat located in the middle, and the sand flat distributed near the sea. The sand flat is dominant around the southern part of Seomot isle and its beach. On the other hand, the mud and mixed flat is dominant on the western part. Likewise, the western coast of Seomot isle and its beach is significantly affected by waves facing the offshore. However, the eastern side of the bay could be a site for the evolution of tidal flat made of fine materials where it is less affected by ocean waves. These results show that multi-spectral satellite data are effective for the classification of distribution materials and environmental impact assessment and continuous monitoring. In particular, the research on environmental deposits can provide important decision-supporting information for decision-making on seaside development, by analyzing the progress of deposits and environmental changes.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.39-48
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• 2011

Global warming causes the climate change and makes severe damage to ecosystem and civilization Carbon dioxide greatly contributes to global warming, thus many studies have been conducted to estimate the forest biomass carbon stock as an important carbon storage. However, more studies are required for the selection and use of technique and remotely sensed data suitable for the carbon stock estimation in Korea In this study, the aboveground forest biomass carbon stocks of Danyang-Gun in South Korea was estimated using $k$NN($k$-Nearest Neighbor) algorithm and regression model, then the results were compared. The Landsat TM and 5th NFI(National Forest Inventory) data were prepared, and ratio images, which are effective in topographic effect correction and distinction of forest biomass, were also used. Consequently, it was found that $k$NN algorithm was better than regression model to estimate the forest carbon stocks in Danyang-Gun, and there was no significant improvement in terms of accuracy for the use of ratio images.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.15-23
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• 2004

In order to utilize remote sensed images effectively, it is necessary to correct geometric distortion. Geometric correction is a critical step to remove geometric distortions in satellite images. For geometric correction, Ground Control Points (GCPs) have to be chosen carefully to guarantee the quality of geocoded satellite images, digital maps, GPS surveying or other data. Traditional approach to geometric correction used GCPs requires substantial human operations. Also that is necessary much time and manpower. In this paper, we presented an on-line automatic geometric correction by constructing GCP Chip database. The Proposed on-line automatic geometric correction system is consists of four part. Input image, control the GCP Chip, revision of selected GCP, and output setting part. In conclusion, developed system reduced the processing time and energy for tedious manual geometric correction and promoted usage of Landsat imagery.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.327-333
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• 2014

To improve thermal environments in urban area, the structural characteristic analysis of thermal environments of the certain area should be preceded to analyze and supplement its problems. With Landsat-8, we measured the centrality estimation, the distribution map, and the spatial statistical analysis of Daegu Metropolitan City in January and August, which of data applied in analyzing the structure of thermal environments following to its spatial property. The thermal infrared band of satellite images has been used to analyze the standard normal deviated scores, which extract the centrality, while the cluster map, based upon Local Local Moran's I, has composed for understanding the autocorrelation of local spatial within environment space structure. Understanding the distribution features as well as the pivot center of thermal environments with satellite images provides principle database for updating urban thermal environments' policies and plans; because those are reference materials that should have precedence over for diverse thermal environment policies.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.11-20
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• 2009

Due to increasing frequency of yellow dust, not to mention high rate of precipitation and cloud formation in summer season of Korea, atmospheric correction of satellite remote sensing is necessary. This research analyzes the effect of atmospheric correction has on imagery classification by comparing DN distribution before and after atmospheric correction. The image used in the research is LANDSAT-5 TM. As for atmospheric correction module, commercial product ATCOR, FLAASH as well as COST model released on the internet, were used. The result of experiment shows that class separability increased in building areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.1-13
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• 2007

We make image that accumulate two principal component after change picture to use GLCM(Gray Level Co-Occurrence Matrix)'s texture feature information. And then these images use preprocess to achieved corner detection and area detection. Experiment results, two principle component conversion accumulation images had most informations about six kind textures by Eigen value 94.6%. When compared with red tide area that uses sea color and red tide area of image that have all principle component, displayed the most superior result. Also, we creates Euclidian space using Euclidian distance measurement about red tide area and clear sea. We identify of red tide area by red tide area and clear sea about random sea area through Euclidian distance and spatial distribution.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.1 s.24
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• pp.13-19
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• 2003

In this paper we discussed the processing procedures of histogram equalization(HE) method and brightness preserving bi-histogram equalization(BBHE) method in the contrast enhancement methods for the performance comparison. With remotely sensed image data of Landsat TM we compared the performances of three methods of Min-Max method, HE method, BBHE method. The experimental results demonstrate that the HE method and BBHE method are more effective in the contrast enhancement performances than the Min-Max method. In the HE method the mean brightness of the resultant output images approached to the middle gray level with regardless of input image mean. In the BBHE method, it is capable of preserving the mean brightness of a original image compared to the HE method while enhancing the contrast of original image effectively. Thus BBHE method is provided more natural enhancement effect than the HE method.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.339-342
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• 2007

불투수도는 도시화, 환경변화를 추정하기 위한 중요한 지수로서 도시 기후 변화, 홍수기철 도시 범람의 증가, 홍수 모델링에 영향 등 도시의 홍수 기상학과 수문학적인 변화와 매우 밀접한 관계가 있다. 본 연구에서는 안성지역 일대를 대상으로 하여 Landsat ETM+ 영상을 이용한 불투수도 작성을 시도하였다. 학습자료 및 검수자료 구축은 고해상도 영상인 IKONOS 영상을 이용하였으며, Landsat ETM+ 영상에 대한 위성반사율을 이용하여 tasseled cap과 NDVI로 전환하고 다양한 변수들이 불투수도에 미치는 영향을 분석하였다. 그리고 Regression Tree 알고리즘에 따라 불투수도 추정식을 개발하여 지도화하였다.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.407-410
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• 2005

We used a series of Landsat images acquired from 1984 to 2001 to observe decadal changes of the research forest of Kangwon National University. Tree NDVI images of November in 1984, 1986 and 2001 were displayed in RGB color composite. This image enabled us to identify historical change of conifer types and their approximate ages. Conifers were classified into 'old conifer aged more than 25 years', 'young conifer aged 20-25 years' 'very young conifer aged less than 20 years', and recently deforested areas. The results coincide with in situ data very well. Archives of higher resolution images should be used to monitor the change of area for various tree types.