• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.109-120
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• 1994

The study is aimed at the extraction of the groundwater potential areas utilizing the remotely sensed data from satellites. The results of the study are summarized as follows. Analyses of the existing operational wells for groundwater supply indicate that 81% of them are related with lineaments and 51% of them are located at the intersections of lineameters. Thus the features of lineaments are considered to be one of the most important parameters to extract a high potertial area of groundwater. Taking into acount features of lineament, high potential points were extracted from Landsat TM data based on the theory developed in this research, then verifications were made through actual drilling. The result of verification indicates that 9 points produces more 200 cubic meter/day which is the amount required from economical point of view for an operational use. Since the actual boring was not made on the recommended points for 4 points due to the difficulty of access to the exact points and of the approval for boring, they did not yield enough output. The result might have been improved if the exact points were bored and if the boring bad been made deeper, since the maximum depth of boring was limited to 62 meters.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.325-335
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• 2006

This paper evaluates and maps the quality of life in the Atlanta, Georgia metropolitan area in 2000. Three environmental variables from Landsat TM data, four socioeconomic variables from census data, and a hazard-related variable from toxic release inventory (TRI) database were integrated into a geographic information system (GIS) environment for the quality of life assessment. To solve the incompatibility problem in areal units among different data, the four socioeconomic variables aggregated by zonal units were spatially disaggregated into individual pixels. Principal components analysis (PCA) was employed to integrate and transform environmental, socioeconomic, and hazard-related variables into a resultant quality of life score for each pixel. Results indicate that the highest quality of life score was found around Sandy Springs, Roswell, Alphretta, and the northern parts of Fulton County along Georgia 400 whereas the lowest quality of life score was clustered around Smyma of Cobb County, the inner city of Atlanta, and Hartsfield-Jackson International Airport. The results also reveals that normalized difference vegetation index (NDVI) and relative risk from TRI facilities are two versatile indicators of environmental and socioeconomic quality of an urban area in the United States.

• 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.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.35-43
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• 2008

The purpose of this study is to evaluate the hydrological impact due to temporal land cover change by gradual urbanization of upstream watershed of Pyeongtaek gauging station of Anseong-cheon. WMS HEC-1 was adopted, and OEM with 200 m resolution and hydrologic soil group from 1:50,000 scale soil map were prepared. Land covers of 1986, 1990, 1994 and 1999 Landsat TM images were classified by maximum likelihood method. The watershed showed a trend that forest & paddy areas decreased and urban/residential area gradually increased during the four selected years. The model was calibrated at 2 locations (Pyeonglaek and Gongdo) by comparing observed with simulated discharge results for 5 summer storm events from 1998 to 2001. The watershed average CN values varied from 61.7 to 62.3 for the 4 selected years. To identify the impact of streamflow by temporal area change of a target land use, a simple evaluation method that the CN values of areas except the target land use are unified as one representative CN value was suggested. By applying the method, watershed average CN value was affected in the order of paddy, forest and urban/residential, respectively.

• 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 Korea Water Resources Association
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• v.38 no.4 s.153
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• pp.301-311
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• 2005

The purpose of this study is to assess the quantitative effect of stream discharge due to land use changes. The upstream watershed of Pyeongtaek gauging station of Anseong-cheon ($592.6\;km^2$) was adopted. To accomplish the purpose, firstly, trace land use changes for the selected watershed which have some changes of land use by using Landsat images of 1986 and 1999 of the watershed and secondly, analyse the quantitative effect of stream discharge due to land use changes by applying GIS- based distributed hydrologic model KIMSTORM. The model was calibrated and verified at 2 locations (Pyeongtaek and Gongdo) by comparing observed with simulated discharge results for 7 storm events from 1998 to 2003. Model output was designed to provide information of land use impact on runoff components in the watershed and the sensitivity of impact level of each land use category on storm runoff. Land use impact was evaluated with the land use data sets for 1986 and 1999 for the same rainfall condition (160.5 mm). Area decrease of 4.8 percent of forest and 4.0 percent of paddy field during 13 years (1986 - 1999) within the watershed caused a 30.3 percent increase of peak runoff and a 9.3 percent increase of runoff volume.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.51-55
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• 2003

본 연구는 조사대상지역인 전라남도 해남군 전역에 대해 현장조사된 지질 및 지하수 양수량 자료등과 같은 수리정보를 종합적으로 분석하고 이를 Landsat 영상자료과의 영상융합 과정을 통해 지하수 부존가능성에 대한 수리 지질 지표정보로 추출함으로서 지하수 특성정보를 위성영상정보와 연계하여 효과적으로 도시하고자 하였다. 현장조사시 획득된 자료는 해남지역을 11개 소유역으로 구분한 후 각 구역에 대한 2000여개 관점에서 측정된 양수량과 안정지하수위를 이용하여 산출한 비용출량 자료(groundwater specific capacity)와 각 소 유역 (unit watershed)에 대한 선구조 분석자료, 지질별 분포, 정밀고도자료를 추출하여 산출한 고도, 경사도 분포, 수계패턴과 수계밀도로서 이를 통합적으로 분석하여 해남지역에 대한 지하수 특성을 파악하고자 하였다. 위성영상자료의 처리과정은 Landsat 5 TM 영상자료는 '86. 12. 11 및 '98. 12. 28에 촬영된 WRS(World Reference System) Row-Path116-36로서, 1986년 영상은 12년 차이의 해남의 변화지역을 탐지하기 위한 영상자료로서 활용하였으며 98년 영상을 주요 분석 자료로 이용하였으며 지표 이용정보 추출은 크게 수역추출, 식생분포추출, 지표분류도, 변화탐지영역추출로 구분된다. 본 연구방법은 크게 위성영상분석을 통해 추출된 정보와 지표조사를 통해 획득된 선구조 및 지하수 정보를 Data fusion 방식으로 이용되고 있는 IHS 변환 기법을 통해 본 역에 대한 지하수 정보 및 간척지 등에 의한 지표 개발에 따른 지하수 부존 가능성을 탐색하기 위한 현황을 효과적인 자료로 표현하고자 하였다.및 스페클 잡영 제거 정도에 있어 다른 필터들과 큰 차이가 없지만 경계선보존지수는 다른 필터들에 비하여 가장 우수함을 확인할 수 있었다.rbon 탐식효율을 조사한 결과 B, D 및 E 분획에서 유의적인 효과를 나타내었다. 이상의 결과를 종합해볼 때, ${\beta}$-glucan은 고용량일 때 직접적으로 또는 $IFN-{\gamma}$ 존재시에는 저용량에서도 복강 큰 포식세로를 활성화시킬 뿐 아니라, 탐식효율도 높임으로써 면역기능을 증진 시키는 것으로 나타났고, 그 효과는 crude ${\beta}$-glucan의 추출조건에 따라 달라지는 것을 알 수 있었다.eveloped. Design concepts and control methods of a new crane will be introduced in this paper.and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be simplified considering a steady state of the process. On th

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.603-612
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• 2022

The study aims were to evaluate a machine-learning, algorithm-based, forest biomass-estimation model to estimate subnational forest biomass and to comparatively analyze REDD+ forest reference emission levels. Time-series Landsat satellite imagery and ESA Biomass Climate Change Initiative information were used to build a machine-learning-based biomass estimation model. The k-nearest neighbors algorithm (kNN), which is a non-parametric learning model, and the tree-based random forest (RF) model were applied to the machine-learning algorithm, and the estimated biomasses were compared with the forest reference emission levels (FREL) data, which was provided by the Paraguayan government. The root mean square error (RMSE), which was the optimum parameter of the kNN model, was 35.9, and the RMSE of the RF model was lower at 34.41, showing that the RF model was superior. As a result of separately using the FREL, kNN, and RF methods to set the reference emission levels, the gradient was set to approximately -33,000 tons, -253,000 tons, and -92,000 tons, respectively. These results showed that the machine learning-based estimation model was more suitable than the existing methods for setting reference emission levels.

• 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.

• 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.