• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.3
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• pp.1-12
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• 2004

Nowadays, a satellite image is widely utilized in identifying and predicting urban spatial growth. It provides essential informations on horizontal expansion of urbanized areas. However, its usefulness becomes very limited in analyzing density of urban development. On the contrary, zonal data, typically census data, provides various density information such as population, number of houses, floor information within a given zone. The problem of the zonal data in analyzing urban growth is that the size of the zone is too big. The minimum administration unit, Dong, is too big to match the satellite images. This study tries to derive synergy effects by matching the merits of the two information sources-- image data and zonal data. For this purpose, basic statistical unit (census block size) is utilized as a zonal unit. By comparing the image and zonal data of 1985 and 2000 of Daegu metropolitan area, this study concludes that urban growth pattern is better explained when the two types of data are properly used.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.1-9
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• 2014

The interest group and corporation in Korea have cultivated Suaeda grass in the source area every year as a plan to prevent the yellow dust due to Chinese desertification. It needs the afforestation analysis about the research area to plan the greenbelt environment development in the region of yellow dust origin. Thus, this research analyzed the greenbelt environment based on Landsat 5 TM satellite image and Landsat 8 image to grasp and analyze the present of greenbelt environment development. And this research analyzed the inside of the salt desert to understand the detailed greenbelt environment and vegetation index. As a result, it represents that the afforestation was accomplished efficiently between 2009 and 2011, while the greenbelt area was decreased rapidly and bare soil was increased between 2011 and 2013. Through these results, we could recognize that it is in trouble about the greenbelt environment development after 2011 and it needs the project implementation using satellite image when the next afforestation project is planned henceforth.

• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.99-108
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• 1998

In order to represent the surface characteristics in local meteorological model, soil type, vegetation index, surface roughness length, surface albedo and leaf area index should be prescribed on the surface process parameterization. In this study, the $1^{\circ}/1^{\circ}leaf$ area index, surface roughness length, and snow free surface albedo and fine mesh NDVI with seasonal variation derived from the satellite observation were applied to the land surface process parameterization. From comparison between with and without satellite data in the interactions between biosphere and atmosphere, land and atmosphere, the sensitivity of the simulated heat, energy and water vapor fluxes, ground temperature, wind, canopy water content, specific humidity, and precipitation fields were investigated.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.28-37
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• 2008

In this study, we perform land surface monitoring of NDVI (Normalized Difference Vegetation Index) variation by using remote sensing data during 1999-2005 over North Korea, which can't easily access to measure directly land surface characteristics due to one of the world's most closed societies. North Korea forest region has most abundant forest vegetation - so called Lungs of Korea in the Korea peninsula. NDVI represents vegetation activity used in many similar studies. In this study, we detect vegetation variation and analysis factors of the change over North Korea. By using variation of NDVI, we can infer that effect of drought over North Korea, and reduced vegetation indices by typhoon in North Korea. Land surface type except barren ground with decreased NDVI value is considered as when North Korea region was suffering from drought and typhoon effects, which show lower than mean of 7-year NDVI value. Especially, in recently, the food production of North Korea with political and economical issues can be inferred indirectly these trends by using estimated output data from this study.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.73-86
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• 2000

This study focused on extracting an efficient method in the fruit cropping distribution mapping with various classification methods using multi-temporal satellite images and Geographic Information Systems(GIS). For this study, multi-temporal Landsat TM images, in observation data and existing fruit cropping area statistics were used to compare and analyze the properties of fruit cropping and seasonal distribution per classification method. As a result, this study concludes that Maximum Likelihood Method with earlier autumn satellite image was most efficient for the fruit cropping mapping using Landsat TM image. In addition, it was clarified that cropping area per administrative boundary was prepared and distribution pattern was identified efficiently using GIS spatial analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.1-10
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• 2000

Satellite remote sensing images have much more information compared to a paper map. But these images are generally handled as particular image format gained from optical sensor, and must be processed and analyzed by computer with high priced digital image processing system. For the extraction of digital elevation model(DEM) from satellite image, we used the overlay image by SPOT-3 of Chuncheon area at the Kangwon province. According to the image condition, the precious geometric correction, the bundle adjustment for ortho-image generation and the stereo image mapping by several technical approaches were processed. So that we developed the methods of automatic DEM extraction and efficient stereo image map generation which can improve the digital image processing steps. Also, we applied the multiple direction birdeye view image for modeling and analysis using the remotely sensed overlay images with high resolution.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.465-476
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• 2013

The outgoing longwave radiation (Rlu) for estimation of evapotranspiration is essential to understand energy balance of earth. However, the ground measurement based Rlu has a limitation that the observation can just stand for the exact site, not for an area. In this study, remote sensing technique is adopted to compensate the limitation of ground observation using the geostationary satellite. We calculated Rlu using Communication, Ocean and Meteorological Satellite (COMS). We validated Rlu from COMS with Cheongmicheon (CFK) and Sulmacheon (SMK) flux tower observations controlled by Hydrological Survey Center. The results showed that Rlu from COMS represented reasonable correlation with ground based measurement. Based on the results in this study, COMS will be able to be used for estimation of evapotranspiration.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.6-6
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• 2016

최근 전 지구적인 기후 변화에 따라 수문 순환을 이루고 있는 다양한 수문 기상 인자들의 변동성에 영향을 미치고 있다. 특히, 증발산은 수문순환을 구성하는 중요한 인자로서 대기와 지표간의 상호 작용을 파악하기 위해서는 이에 대한 정확한 이해 및 산정이 필수적이다. 일반적으로 증발산량을 산정하기 위해서 증발 접시 및 에디 공분산 기반 플럭스 타워에서 관측된 지점 자료만을 이용하여 증발산량의 변동성을 파악하는 연구들이 수행되어왔다. 그러나 지점 자료만을 이용하여 증발산량을 산출하게 되면 공간적인 변동성을 파악하는데 있어서 한계점이 발생하게 된다. 이러한 제약 사항을 해결하기 위해서, 인공위성 기반의 수문 기상인자를 물리식 기반 증발산량 산정식의 입력 자료로 구축하여 증발산량을 산정하고 이에 대한 시 간적인 변동성을 파악하는 연구들이 활발히 이루어지고 있다. 인공위성 기반 증발산량 산정 알고리즘의 대표적인 예로 공기동역학적 항과 에너지 수지 항들을 동시에 고려할 수 있는 Penman-Monteith 방법을 근간으로 수정하여 만들어낸 Remote Sensing based Penman-Monteith (RS-PM) 알고리즘이 있다. 그러나 RS-PM 기반의 증발산량 경우 태양복사열, 풍속, 온도, 습도와 같은 많은 수문기상인자들이 입력 자료를 요구한다. 이에 따라, 본 연구에서는 기존의 방법에 비해 상대적으로 적은 입력 자료를 사용하는 Modified Satellite-Based Priestley-Taylor (MS-PT) algorithm의 적용성을 평가하기 위해 MODerate-Resolution Imaging Spectroradiometer (MODIS) 자료를 이용하여 한반도에서 순복사에너지 (Net radiation) 및 실제 증발산량 (Actual evapotranspiration)을 산정하였다. 또한, 이에 대한 검증을 위해 청미천 유역에 설치되어있는 에디 공분산 기반 플럭스 타워에서 관측된 순복사 에너지 및 실제 증발산량에 대한 통계적 검증을 실시하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.218-237
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• 2018

The purpose of this study is to propose a mid - range low - orbit water disaster monitoring satellite development plan to revolutionize water disaster management infrastructure through securing an independent and leading observation infrastructure and to secure safety against disaster prepared for climate change. Water and water disaster satellites should be able to detect changes in the surface of the ground and observe hydrological factors during daytime, nighttime, and bad weather. In addition, independent technology development should be possible. To do this, we selected C-band image radar payload considering domestic technology and water resources management, and suggested detailed development plan. In this way, it is reflected in the national next-generation mid-satellite 2-phase project plan to secure the basis for building a disaster monitoring system related to wide-area water.

• Journal of The Geomorphological Association of Korea
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• v.28 no.1
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• pp.83-99
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• 2021

Burn severity analysis using satellite imagery has high capabilities for research and management in inaccessible areas. We extracted the forest fire area of the DMZ (Demilitarized Zone) in the western Imjin Estuary which is restricted to access due to the confrontation between South and North Korea. Then we analyzed the forest fire severity and recoverability using atmospheric corrected Surface Reflectance Level-2 data collected from Landsat-8 OLI (Operational Land Imagery) / TIRS (Thermal Infrared Sensor). Normalized Burn Ratio (NBR), differenced NBR (dNBR), and Relative dNBR (RdNBR) were analyzed based on changes in the spectral pattern of satellite images to estimate burn severity area and intensity. Also, we evaluated the recoverability after a forest fire using a land cover map which is constructed from the NBR, dNBR, and RdNBR analyzed results. The results of dNBR and RdNBR analysis for the six years (during May 30, 2014 - May 30, 2020) showed that the intensity of monthly burn severity was affected by seasonal changes after the outbreak and the intensity of annual burn severity gradually decreased after the fire events. The regrowth of vegetation was detected in most of the affected areas for three years (until May 2020) after the forest fire reoccurred in May 2017. The monthly recoverability (from April 2014 to December 2015) of forests and grass fields was increased and decreased per month depending on the vegetation growth rate of each season. In the case of annual recoverability, the growth of forest and grass field was reset caused by the recurrence of a forest fire in 2017, then gradually recovered with grass fields from 2017 to 2020. We confirmed that remote sensing was effectively applied to research of the burn severity and recoverability in the DMZ. This study would also provide implications for the management and construction statistics database of the forest fire in the DMZ.