• 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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• 2002.10a
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• pp.745-745
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• 2002

Both geophysical and geospatial data provide important information in the establishment of the optimal telecommunication systems especially in the mobile telecommunication environment. The objective of this study is to utilize geophysical properties and geospatial information in the analysis of the telecommunication environment through point-to-point wave property modeling. Geophysical properties associated with wave propagation parameters of the earth surface were analyzed based on hierarchical land classification using Landsat ETM＋ and IKONOS images. Three-dimensional geospatial information was obtained by processing stereo aerial images. The results show that the accurate geospatial information and reliable geosphysical property of the surface improve the prediction of receiving power of the receivers located near corners of the buildings where diffractions occur. The wave property model developed from accurate telecommunication environment could be applied to optimal cell planning and delay time analysis.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.315-327
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• 2004

Nowadays, interests in land cover classification using not only multi-sensor images but also thematic GIS information are increasing. Often, although useful GIS information for the classification is available, the traditional MLE (maximum likelihood estimation techniques) does not allow us to use the information, due to the fact that it cannot handle the GIS data properly. This paper propose two extended MLE algorithms that can integrate both remote sensing images and GIS thematic data for land-cover classification. They include modified MLE and Bayesian predictive likelihood estimation technique (BPLE) techniques that can handle both categorical GIS thematic data and remote sensing images in an integrated manner. The proposed algorithms were evaluated through supervised land-cover classification with Landsat ETM+ images and an existing land-use map in the Gongju area, Korea. As a result, the proposed method showed considerable improvements in classification accuracy, when compared with other multi-spectral classification techniques. The integration of remote sensing images and the land-use map showed that overall accuracy indicated an improvement in classification accuracy of 10.8% when using MLE, and 9.6% for the BPLE. The case study also showed that the proposed algorithms enable the extraction of the area with land-cover change. In conclusion, land cover classification results produced through the integration of various GIS spatial data and multi-spectral images, will be useful to involve complementary data to make more accurate decisions.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.57-69
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• 2001

This study propose a image processing system of unsupervised analysis. This system integrates low-level segmentation and high-level classification. The segmentation and classification are conducted respectively with and without spatial constraints on merging by a hierarchical clustering procedure. The clustering utilizes the local mutually closest neighbors and multi-window operation of a pyramid-like structure. The proposed system has been evaluated using simulated images and applied for the LANDSATETM+ image collected from Youngin-Nungpyung area on the Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.75-85
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• 2006

This paper has dealt with a data fusion for the problem of land-cover classification using multisensor imagery. Dempster-Shafer evidence theory has been employed to combine the information extracted from the multiple data of same site. The Dempster-Shafer's approach has two important advantages for remote sensing application: one is that it enables to consider a compound class which consists of several land-cover types and the other is that the incompleteness of each sensor data due to cloud-cover can be modeled for the fusion process. The image classification based on the Dempster-Shafer theory usually assumes that each sensor is represented by a single channel. The evidential approach to image classification, which utilizes a mass function obtained under the assumption of class-independent beta distribution, has been discussed for the multiple sets of mutichannel data acquired from different sensors. The proposed method has applied to the KOMPSAT-1 EOC panchromatic imagery and LANDSAT ETM+ data, which were acquired over Yongin/Nuengpyung area of Korean peninsula. The experiment has shown that it is greatly effective on the applications in which it is hard to find homogeneous regions represented by a single land-cover type in training process.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.198-198
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• 2022

최근 도시화에 따른 토지 피복 변화와 열섬현상 등의 원인으로 상승하는 도시의 기온이 식물 계절에 미치는 영향에 관한 연구들이 다수 진행되고 있다. 본 연구는 수도권인 서울과 경기도 지역을 대상으로 도시 내 열섬현상으로 인한 기온 상승과 도시 지역 내 식생 생장기간 변화의 관계성을 분석하였다. 식물계절 모니터링에 사용한 개량식생지수(Enhanced Vegetation Index, EVI)는 Google Earth Engine (GEE)에서 제공하는 30 m 해상도의 2000-2021년 NASA-USGS Landsat 위성(TM5, ETM+7, OLI8)의 지표면 반사율(surface reflectance, SR) 자료에서 도출하여 생장기간 산정에 사용하였다. 또한 PRISM (Parameter-elevation Regressions on Independent Slopes Model)을 각 기상관측지점의 일별 지상 기온 자료에 적용하여 30 m 해상도로 생성한 격자형 지표면 온도의 공간적 패턴을 분석하였다. 연구 지역 내 도시화 정도(magnitude)를 도심으로부터의 거리와 환경부 토지피복도 및 인구 밀도를 종합하여 특정하였고, 최종적으로 기후변화 및 도시화 정도와 생장기간 변화의 특징을 분석하였다. 비선형 로지스틱 회귀를 사용하여 EVI 데이터를 종합하여 분석한 결과, 수도권 지역에서 전반적으로 식물계절 개엽일(Start of Season)은 앞당겨지며 낙엽일(End of Season, EOS)은 늦춰져 생장기간(Length of Growing Season, LOS)이 길어짐을 발견하였다.

• Journal of the Korean Geographical Society
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• v.41 no.3 s.114
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• pp.331-345
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• 2006

This study deals with geomorphological process of the sand dune landform including the distribution and surface environments, characteristics of sediments, origins and moving processes in lower reach and mouth delta of Duman River, Northeast Korea and China. The methodology of the study includes image analysis of Landsat TM(1992.10) and ETM(2000.9) and Spot(2005.4) for analysis of land cover, 2 times field survey for recognition of landform and acquisition of sediments raw data materials, and grain analysis and exoscopy about raw data materials. The geomorphic elements from satellite image analysis are composed of the delta, sand spit, active and stable dune, sand bar and riparian vegetated zone. Results of the grain analysis indicate the sediments originated from marine coastal zone than riverine one. This means that present sand dune not so much reflect present climatic and geomorphic environments. Result of the exoscopy analysis show that ratio of quartz, which is comparatively resistant to environment, is highest as $65{\sim}83%$ out of sediments. But the surface of the $30{\sim}40%$ of mineral grains was coated by yellow-colored stained materials, due to chemical weathering. Some grains show rough skin, looking as acicular, network structure and etching pits, affected by physical and chemical weathering.

• Korean Journal of Environment and Ecology
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• v.19 no.4
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• pp.375-384
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• 2005

This study was conducted selecting 44 places with a block unit subject to urban area in Gangnam-gu, to analyze a temperature change according to land use and green structure. In this study, it was used the broad-wide urban temperature, supported by Landset TM and ETM+ satellite image 6scene(1999${\~}$2002). The result of the research, the land use pattern has slightly influence on a temperature change of urban area. The result from correlation analysis between temperature and the factors affected by land cover type, such as building-to-land ratio(A correlation coefficient is 0.368${\~}$0.709) have positive correlation and green area ratio(a correlation coefficient is -0.551${\~}$-0.860) have negative correlation. The result from correlation analysis between temperature and green capacity of the land, crown projection area ratio, each factor have negative correlation with temperature, as showing that a correlation coefficient of green capacity of the land is -0.577(June 2006)${\~}$-0.882(June 1999) and crown projection area ratio's is -0.549(June 2001)${\~}$-0.817(June 1999). The result of the regression analysis for establishing urban area temperature change prediction model showed that green capacity of the land of the explanation variable was accepted.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.215-224
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• 2008

The effect of streamflow considering future land use change and vegetation index information by climate change scenario was assessed using SLURP (Semi-distributed Land-Use Runoff Process) model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for the upstream watershed ($260.4km^2$) of Gyeongan water level gauging station. By applying CA-Markov technique, the future land uses (2030, 2060, 2090) were predicted after test the comparison of 2004 Landsat land use and 2004 CA-Markov land use by 1996 and 2000 land use data. The future land use showed a tendency that the forest and paddy decreased while urban, grassland and bareground increased. The future vegetation indices (2030, 2060, 2090) were estimated by the equation of linear regression between monthly NDVI of NOAA AVHRR images and monthly mean temperature of 5 years (1998-2002). Using CCCma CGCM2 simulation result based on SRES A2 and B2 scenario (2030s, 2060s, 2090s) of IPCC and data were downscaled by Stochastic Spatio-Temporal Random Cascade Model (SST-RCM) technique, the model showed that the future runoff ratio was predicted from 13% to 34% while the runoff ratio of 1999-2002 was 59%. On the other hand, the impact on runoff ratio by land use change showed about 0.1% to 1% increase.