• Journal of Environmental Science International
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• v.17 no.6
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• pp.679-687
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• 2008

In this study, we implemented landslide distribution of Jeju Island using ANN and GIS, respectively. To do this, we first get the counter line from 1:2,5000 digital map and use this counter line to make the DEM. for the evaluate the land slide susceptibility. Next, we abstracted slop map and aspect map from the DEM and get the land use map using ISODATA classification method from Landsat 7 images. In the computation processes of landslide analysis, we make the class to the soil map, tree diameter map, Isohyet map, geological map and so on. Finally, we applied the ANN method to the landslide one and calculated its weighted values. GIS results can be calculated by using Acrview program and produced Jeju landslide susceptibility map by usign Weighted Overlay method. Based on our results, we found the relatively weak points of landslide ware concentrated to the top of Halla mountains.

• Asian Journal of Atmospheric Environment
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• v.6 no.2
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• pp.127-135
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• 2012

Urbanization has led to a reduction in green spaces and thus transformed the spatial pattern of urban land use. An increase in air temperature directly affects forest vegetation, phenology, and biodiversity in urban areas. In this paper, we analyze the changing land use patterns and urban heat distribution (UHD) in Seoul on the basis of a spatial assessment. It is necessary to monitor and assess the functions of green spaces in order to understand the changes in the green space. In addition, we estimated the influence of green space on urban temperature using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery and climatic data. Results of the assessment showed that UHD differences cause differences in temperature variation and the spatial extent of temperature reducing effects due to urban green space. The ratio of urban heat area to green space cooling area increases rapidly with increasing distance from a green space boundary. This shows that urban green space plays an important role for mitigating urban heating in central areas. This study demonstrated the importance of green space by characterizing the spatiotemporal variations in temperature associated with urban green spaces.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.181-188
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• 1997

Vegetation is an important factor in EIA(Environmental Impact Assessment) and it is assessed according to DGN(Degree of Green Naturality) in EIS(Environmental Impact Statement) preparation. But DGN has room for improvement of assessing vegetation Status. This study introduced NDVI(Normalized Difference Vegetation Index) for improving status assessment method that subjects to DGN. For the application of NDVI, Landsat TM data of Chunchon on May 2, 1989 and June 1, 1994, and data of Ulsan on November 5, 1984, November 2, 1992 and May 9, 1994 were used. It compared NDVI with DGN according to season and location. The correlation coefficient value for the spring image (1994, 0.7, p=0.01) was proved to be higher than that of autumn (1984, 0.5, p=0.01).

• Journal of Korean Society of Rural Planning
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• v.12 no.1 s.30
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• pp.75-83
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• 2006

본 연구에서는 최대우도법과 인공신경망 모형에 의해 카테고리 분류를 수행하고 각각의 분류 성능을 비교 평가하였다. 인공신경망 모형은 오류역전파 알고리즘을 이용한 것으로서 학습을 통한 은닉층의 최적노드수를 결정하여 카테고리 분류를 수행하도록 하였다. 인공신경망 최적 모형은 입력층의 노드수가 7개, 은닉층의 최적노드수가 18개, 그리고 출력층의 노드수가 5개인 것으로 구성하였다. 위성영상은 1996년에 촬영된 Landsat TM-5 영상을 사용하였고, 최대우도법과 인공신경망 모형에 의한 카테고리 분류를 위하여 각각의 카테고리에 대한 분광특성을 대표하는 지역을 절취하였다. 분류 정확도는 인공신경망 모형에 의한 방법이 90%, 최대우도법이 83%로서, 인공신경망 모형의 분류 성능이 뛰어난 것으로 나타났다. 카테고리 분류 항목인 토지 피복 상태에 따른 분류는 두 가지 방법에서 밭과 주거지의 분류오차가 큰 것으로 나타났다. 특히, 최대우도법에 의한 밭에서의 태만오차는 62.6%로서 매우 큰 값을 보였다. 이는 밭이나 주거지의 특성이 위성영상 촬영시기에 따라 나지의 형태로 분류되거나 산림, 또는 논으로도 분류되는 경향이 있기 때문인 것으로 보인다. 차후에 카테고리 분류를 위한 각각의 클래스의 보조적인 정보를 추가한다면, 카테고리 분류 향상이 이루어질 것으로 기대된다.

• Proceedings of the KSRS Conference
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• v.1
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• pp.436-440
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• 2006

Diffuse pollution has been considering as a major source of the quality deterioration of water resources. The establishment of riparian vegetation strips of buffers along those areas of water bodies is used to reduce the threat of diffuse pollution. Remote sensing offers a means by which critical areas could be identified, so that subsequent action toward the establishment of riparian zones can be taken. Even though the principal purpose of this research comes from the feasibility of the imagery of KOMPSAT-2 satellite, Landsat TM satellite data, which has 7 bands, are used to characterize the land cover for the study area on the behalf of KOMPSAT-2. This investigation focuses on the assessment of the existing riparian buffer zones for a portion of the upper Geum river watershed from the viewpoint of pollution mitigation by riparian vegetation strip establishment. Through comparing the delineation of riparian buffer zones developed with the existing zones established by the government, we can find the critical distortion points of the existing riparian buffer zone.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.683-691
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• 2012

High resolution satellite images are now widely used for a variety of mapping applications including photogrammetry, GIS data acquisition and visualization. As the spectral and spatial data size of satellite images increases, a greater processing power is needed to process the images. The solution of these problems is parallel systems. Parallel processing techniques have been developed for improving the performance of image processing along with the development of the computational power. However, conventional CPU-based parallel computing is often not good enough for the demand for computational speed to process the images. The GPU is a good candidate to achieve this goal. Recently GPUs are used in the field of highly complex processing including many loop operations such as mathematical transforms, ray tracing. In this study we proposed a technique for parallel processing of high resolution satellite images using GPU. We implemented a spectral radiometric processing algorithm on Landsat-7 ETM+ imagery using CUDA, a parallel computing architecture developed by NVIDIA for GPU. Also performance of the algorithm on GPU and CPU is compared.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.189-197
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• 2012

This research attempted to find possibilities of the practical use utilizing geospatial methods for the balanced promotion of sustainable coastal development and preservation through a case study of Jekyll Island, one of Georgia's barrier islands. In response, this research provided ways for practical use in sustainable development and preservation plans. First this research thoroughly investigated the 1996 master plan of Jekyll Island and tried to recalculate developed and undeveloped areas. Second, new estimations for developed areas were investigated through field survey. Third, this research proposed the use of the satellite images with different levels of spatial resolutions and tested different classification schemes to find possibilities for practical use. For these purposes, first, we classified developed and undeveloped features by manual digitization using an aerial photo image with 0.5m spatial resolution. Second, a Landsat 7 ETM+ and a QuickBird satellite images with mid- and high-levels of spatial resolutions were applied to identify developed and undeveloped areas using both the National Land Cover Data (NLCD) and the Coastal Change Analysis Program (CCAP) classification schemes. Also, GEOBIA (Geographic Object-Based Image Analysis) was conducted to accurately identify developed and undeveloped areas.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1430-1432
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• 2003

Agricultural areas in the north region of Bangladesh suffer from water shortages during the dry season as well as dry spells in the monsoon period. The Teesta Barrage was constructed in 1990 to provide supplemental irrigation water during the monsoon period. After completion of the project high yielding variety of crops were introduced more in the project area. Due to this reason unforeseen needs of irrigation water during the dry season has emerged. This study reviews the current irrigation status and related constraints to a full development of the project and provides suggestions for future improvement of the project. Also suggested is to apply remote sensing technique for the management of the system as a whole. Use of remote sensing technique for the management of irrigation water resources is a new approach in Bangladesh. Application of such a powerful tool will provide better management options for large-scale irrigation projects in the country.

• Korean Journal of Remote Sensing
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• v.6 no.2
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• pp.115-133
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• 1990

Study was made on the spectral characteristics of rock samples including bentonites collected from the northern Ulsan area. The geology of the area consists mainly of sediments of the Kyongsang Series and Bulguksa granite, the Tertiary volcanics, andesites and tuffs. Relative reflectances of meshed samples(2.5~10mm) to BaSO$_4$ are measured at 6 Landsat TM spectral windows (excluding the thermal band) with HHRR, and their reflection charactristics were analysed. In addition, three different data selection schemes including the Eulidean distance, multiple regression, and PCA weight methods were applied to the 30 TM ratio channels, derived from the above 6 bands. The selected data sets were subject to two unsupervised classification techniques(FA and ISODATA) in order to compare the effectiveness for classification of particularly bentonite from others. As a result, in ISODATA analysis the multiple regression model shows the best, followed by the Euliean distances one. The PCA weight model seems to show some confusion. In FA, though difficult for quantitative analysis, the best still seems to be the regression model. Among ratio bands, rations of band 7 or 5 against other bands represent the best contribution in classification of bentonites from others.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.25-33
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• 2008

To investigate the hydrologic impacts of climate changes on dam inflow for Soyanggangdam watershed $(2694.4km^2)$ of northeastern South Korea, SLURP (Semi-distributed Land Use-based Runoff Process) model and the climate change results of CCCma CGCM2 based on SRES A2 and B2 were adopted. By the CA-Markov technique, future land use changes were estimated using the three land cover maps (1985, 1990, 2000) classified by Landsat TM satellite images. NDVI values for 2050 and 2100 land uses were estimated from the relationship of NDVI-Temperature linear regression derived from the observed data (1998-2002). Before the assessment, the SLURP model was calibrated and verified using 4 years (1998-2001) dam inflow data with the Nash-Sutcliffe efficiencies of 0.61 to 0.77. In case of A2 scenario, the dam inflows of 2050 and 2100 decreased 49.7 % and 25.0 % comparing with the dam inflow of 2000, and in case of B2 scenario, the dam inflows of 2050 and 2100 decreased 45.3 % and 53.0 %, respectively. The results showed that the impact of land use change covered 2.3 % to 4.9 % for the dam inflow change.