• The Korean Journal of Quaternary Research
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• v.20 no.2
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• pp.1-10
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• 2006

Flooding hazard caused by natural and artificial environmental changes is closely associated with change in river bed configuration. This study is aimed at explaining a river-bed change related to soil erosion in the Keum river basin using GIS and RS. The USLE was used to compute soil erosion rate on the basis of GIS. River-bed profiles stretching from Kongju to Ippo were measured to construct a 3D-geomorphological map. The river-bed change was also detected by remote sensing images using Landsat TM during the period of 1982 to 2000 for the Keum river. The result shows that USLE indicates a mean soil erosion rate of $1.8\;kg/m^2/year$, and a net increase of a river-bed change at a rate of $+5\;cm/m^2$/year in the Kangkyeong area. The change in river-bed is interpreted to have been caused by soil erosion in the downstream of the Keum river basin. In addition river-bed change mainly occurred on the downstream of the confluence where tributaries and the main channel meet. Other possible river-bed change is caused by a removal of fluvial sand aggregates, which might have resulted in a net decrease of exposed area of sediment distribution between 1991 and 1995, while a construction of underwater structures, including a bridge, a reclamation of sand bars for rice fields and dikes, resulted in an increase of the exposed area of river-bed due to sediment accumulation.

• 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.

• KCID journal
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• v.18 no.2
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• pp.111-121
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• 2011

This study is to estimate the possible damage area of greenhouse by heavy snowfall event using terra MODIS snow cover area (SCA) and the ground measured snowfall data (GMSD). For the 4 heavy snowfall events of January 2001, March 2004, December 2005 and January 2010, the areas exceeding the design criteria of snowfall depth for greenhouse breaking were extracted by coupling the MODIS SCA and GMSD. The main damaged regions were estimated as Gangwon province in 2001, Chungbuk and part of Gyeongbuk province in 2004, Jeonbuk and Jeonnam province in 2005, and Gangwon and part of Gyeonggi province in 2010 respectively. Comparing with the investigated number of greenhouse damaged data, the estimated areas reflected the statistical data except 2001. The 2001 greenhouse damages were caused by the high wind speed (35.7m/sec) together with snowfall. The results of this study can be improved if the design criteria of wind speed is added.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.240-245
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• 2006

오늘날 도시인구집중화 현상에 따른 대규모 도시개발과 도시역의 확대로 지표면의 피복 변화가 극심하게 이루어지고 있는 한편 이러한 현상으로 인해 도시의 내 외적 경관변화 뿐만 아니라 지형 및 기온상승, 바람장의 변화 등 복합적인 국지기후 변화를 초래하게 되었다. 본 연구에서는 이러한 도시의 기후 변화에 따라 청계천 복원 전의 도시 지표 열 환경 특성을 분석을 수행하고자 한다 도시지역의 열환경 분석을 위하여 기존에는 주로 Landsat TM/ETM+ 위성영상 자료를 사용하였으나 2003년 5월 위성 센서의 고장으로 위성영상 자료의 사용이 불가피하게 되었다. 이에 대체 방안으로 ASTER 영상 열적외 센서에서 취득한 지표온도 값과 현장에서 취득한 AWS자료와의 상관성 분석을 실시하였으며, 이를 기반으로 청계천 주변의 근접성 분석 및 토지이용별 지표온도 분포 패턴 등 도시 열 환경 변화 탐지 및 분석을 위하여 GIS 및 RS 분석을 실시하였다.

• 한국공간정보시스템학회:학술대회논문집
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• 2002.03a
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• pp.45-52
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• 2002

Artificial neural networks (ANN) have been successfully used for classifying remotely sensed imagery. However, ANN still is not the preferable choice for classification over the conventional classification methodology such as the maximum likelihood classifier commonly used in the industry production environment. This can be attributed to the ANN characteristic built-in stochastic process that creates difficulties in dealing with unequally represented training classes, and its training performance speed. In this paper we examined some practical aspects of training classes when using a back propagation neural network model for remotely sensed imagery. During the classification process of remotely sensed imagery, representative training patterns for each class are collected by polygons or by using a region-growing methodology over the imagery. The number of collected training patterns for each class may vary from several pixels to thousands. This unequally populated training data may cause the significant problems some neural network empirical models such as back-propagation have experienced. We investigate the effects of training over- or under- represented training patterns in classes and propose the pattern repopulation algorithm, and an adaptive alpha adjustment (AAA) algorithm to handle unequally represented classes. We also show the performance improvement when input patterns are presented in random fashion during the back-propagation training.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.213-218
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• 2009

에너지 전달 과정과 밀접한 관계가 있는 증발산(Evapotranspiration)은 기후 변화나 육상 생태계 생산성에서 매우 중요한 요소이며, 수문학적 순환과 지역적 물 관리 측면에서 매우 중요하다. 최근 인공위성을 이용하여 증발산을 추정하기 위한 노력이 많이 진행되고 있으며, 특히 MODIS (Moderate Resolution Imaging Spectroradiometer)는 증발산을 추정하기 위한 좋은 정보를 제공하고 있다 하지만, 구름 등에 의한 증발산 입력 자료 결측은 전체 자료의 획득률을 낮추고, 연속적인 증발산 모니터 링을 제한한다. 따라서 본 연구에서는 MODIS 기반의 증발산 입력 자료의 개선하여 서로 다른 식생과 지형 구조를 갖는 플럭스 연구지에 대한 증발산의 추정 및 평가하고, 남한에 대한 MODIS 기반의 증발산 지도 작성하였다. 또한 구름에 의해 결측된 날에 대해서는 MODIS-MM5 4차원 자료동화 기법을 이용한 증발산의 연속적인 모니터링 기법을 개발하였다. MODIS 기반의 증발산을 추정하기 위해 Revised RS-PM 알고리즘을 사용하였다. 증발산을 평가하기 위해 4 곳의 플럭스 연구지(광릉, 해남 이상 대한민국, 타카야마, 토마코아미 이상 일본) 자료와 비교하였고, 매우 신뢰성 있는 결과를 얻을 수 있었다. MODIS 입력 자료의 개선으로 획득률은 2배 가량 증가하였다. 남한에 대한 연간 증발산은 평균적으로 약 35%의 획득률 (365일 중 약 120일)과 함께 산출되었고, 시 공간적인 분포를 잘 나타내었다. 구름 낀 날에 대한 MODIS-MM5 자료 동화 기법의 적용은 증발산의 연속적인 모니터링을 가능하게 하였다.

• Advances in environmental research
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• v.9 no.4
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• pp.251-273
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• 2020

Soil degradation has become a major worldwide environmental problem, particularly in arid and semi-arid climate zones due to irregular rainfall and the intensity of storms that frequently generate heavy flooding. The main objective of this study is the use of geographic information system and remote sensing techniques to quantify and to map the soil losses in the Wadi Saida watershed (624 ㎢) through the revised universal soil loss equation model and a proposed model based on the surface erosive runoff. The results Analysis revealed that the Wadi Saida watershed showed moderate to moderately high soil loss, between 0 and 1000 t/㎢/year. In the northern part of the basin in the region of Sidi Boubkeur and the mountains of Daia; which are characterized by steep slopes, values can reach up to 3000 t/㎢/year. The two models in comparison showed a good correlation with R = 0.95 and RMSE = 0.43; the use of the erosive surface runoff parameter is effective to estimate the rate of soil loss in the watersheds. The problem of soil erosion requires serious interventions, particularly in basins with disturbances and aggressive climatic parameters. Good agricultural practices and forest preservation areas play an important role in soil conservation.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.649-663
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• 2019

The 2018 United Nations Development Programme (UNDP) report announced that deforestation in North Korea is the most extreme situation and in terms of climate change, this deforestation is a global scale issue. To respond deforestation, various study and projects are conducted based on remote sensing, but access to public data in North Korea is limited, and objectivity is difficult to be guaranteed. In this study, the forest detection based on density estimation in statistic using Landsat imagery was conducted in Gangwon province which is the only administrative district divided into South and North. The forest spatial data of South Korea was used as data for the labeling of forest and Non-forest in the Normalized Difference Vegetation Index (NDVI), and a threshold (0.6658) for forest detection was set by Gaussian Probability Density Function (PDF) estimation by category. The results show that the forest area decreased until the 2000s in both Korea, but the area increased in 2010s. It is also confirmed that the reduction of forest area on the local scale is the same as the policy direction of urbanization and industrialization at that time. The Kappa value for validation was strong agreement (0.8) and moderate agreement (0.6), respectively. The detection based on the Gaussian PDF estimation is considered a method for complementing the statistical limitations of the existing detection method using satellite imagery. This study can be used as basic data for deforestation in North Korea and Based on the detection results, it is necessary to protect and restore forest resources.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.835-854
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• 2017

Government regulations and policies are important means of restraining the indiscreet expansion of urban areas. According to the standards from those means, it is clear that the fluctuation of forest green proportion encroached by the increase of urban space is obvious. In this study, we interpreted the changes of urban areas as well as the green ones owing to the urban expansion by the decades from 1996, with focusing on the cities of Seoul and Daegu highly developed in South Korea. The purpose of this study is to analyze the spatial expansion and morphological characteristics of urban land cover using not only satellite imageries (1996, 2006, 2016). but also the urban expansion intensity index (UEII) and GUIDOS program. Ultimately, this study is to compare the changes in the rate of forests due to urban expansions annually analyzed based on areas of forest elevation, slope, and the area of single forest patch. In Seoul, the expansion begun from urban space to suburban areas was comparatively rapid, which led the forest fragmentation and the gradual decline of the single patch. However, when it comes to DEM (Digital elevation model) and slope above a certain standard, by the development regulations, there was little decrease in area by anthropogenic developments. The city of Daegu has increased at a slow speed since 1996 in urban and suburban areas, whereas green forests have greatly increased through green forest conservation campaigns. In this way, as to the government policies and regulations, the quantitative and morphological expansion of cities owing to development could be controlled and forest spaces could be preserved as well. Therefore, regulations and policies by the government should be appropriately utilized for sustainable cities.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.365-373
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• 2012

This study purposed to extract and assess the accuracy of assessment for deforestation area in Wonju city using medium resolution satellite image. The total size of deforestation area during the last nine years (2000-2008) was about 467 ha, and it was occurred annually about 52 ha. The most frequent form of deforestation was settlements (72%). Ninety percent of the size of deforestation was less than 2 ha in size. In addition, 79 percent of deforestation area was found within 500 m from the road network and within 100 m of the Forest/Non-forest boundary. This study compared the deforestation based on the administrative information (GIS deforestationI) with the deforestation (RS deforestation) extracted from the satellite imagery by vegetation indices (NDVI, NBR, NDWI). Extraction accuracy, mean-standard deviation${\times}1.5$ applied 3 by 3 filtering, showed reliable accuracy 35.47% k-value 0.20. However, error could be occurred because of the difference of land-use change and land-cover change. The actual rate of land-cover change deforestation area was 32% on administrative information. The 7.52% of forest management activities area was misjudged as deforestation by RS deforestation. Finally, the comparison of land-cover change deforestation (GIS deforestationII) with the RS deforestation accuracy, as a result NDVI mean-standard deviation${\times}2$ applied 3 by 3 filtering, showed improved accuracy 61.23%, k-value 0.23.