• 한국지리정보학회지
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• 제19권3호
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• pp.75-88
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• 2016

본 연구는 도시성장 시나리오와 CLUE-s 모형을 이용해 한반도의 시공간적인 미래 토지이용 변화를 예측하였다. 이를 위한 CLUE-s 모형의 입력 자료로 2008년 환경부 토지이용도와 국가수자원관리종합시스템(WAMIS)에서 1980년부터 2011년까지 5년 간격의 토지이용 통계 자료를 구축하였다. 토지이용 항목은 총 6개(수역, 시가지, 논, 밭, 산림, 초지)로 분류하였으며, 다양한 토지 변화요소(Driving Factor)와 특별토지이용 정책 자료로 환경부의 국토환경성평가 지도를 적용하였다. 시나리오 예측 결과는 각 도별로 2008년의 토지피복 통계와 비교를 통해 검증하였다. 시가지를 대상으로 한 실측값과의 오차율은 경기도(9.47%), 강원도(9.96%), 충청북도(10.63%), 충청남도(7.53%), 전라북도(9.48%), 전라남도(6.92%), 경상북도(2.50%), 경상남도(8.09%)로 나타났다. 이러한 오차의 원인은 미래 도시성장을 수학적으로 예측하기 위해 모형 내에서 조정된 성장률과 국가 정책으로 인한 실제 성장률의 차이로 인한 것으로 판단된다. 2100년의 미래 토지이용 변화 예측 결과 시가지는 2008년에 비해 28.24% 상승할 것으로 예측되었으며 논, 밭, 산림은 각각 8.27%, 6.72%, 1.66% 감소할 것으로 예측되었다.

• Korean Journal of Geomatics
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• 제1권1호
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• pp.61-67
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• 2001

This study aims to develop the Extended Urban Land Information System (EULIS) which can support the sustainable urban management. Although the existing Urban Land Use Information system (ULUIS) that aids the micro-level land use information is a good means for the understanding of urban spatial structure and district-level planning and management (such as urban design, redevelopment planning and district-level transportation planning, etc.), it has some limitations in supplying the information for sustainable urban management, such as environmental and traffic analysis, urban infrastructure's carrying capacity analysis, etc. The EULIS is designed to efficiently supply the information for sustainable urban management. For the successful construction of EULIS, the followings have to be considered. 1) the integration of topographic maps which contain the building's footprints and cadastral maps which contain the parcel's boundary, 2) the integration of EULIS and FM (Facility Management) system for the full utilization of information about capacity analysis of infrastructure, 3) the construction of standardized georeferencing system and spatial unit for the combined use of environment and traffic census data. This study shows 1) why EULIS is needed for the sustainable urban management and which elements are needed for the system,2) the E-R data model for the EULIS, 3) the strategies for the construction of EULIS and 4) the conclusion.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.361-364
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• 2005

The use of remotely sensed data and geographic information system (GIS) to develop conservation-oriented watershed management strategies on Imha Dam, Korea, is presented. The change of land use for study area was analyzed using multi-temporal Landsat imagery. A soil loss model was executed within a GIS environment to evaluate watershed management strategies in terms of soil loss. In general, remotely sensed data provide efficient means of generating the input data required for the soil loss model. Also, GIS allowed for easy assessment of the relative erosion hazard over the watershed under the different land use change options. The soil loss model predicted substantial declines in soil loss under conservation-oriented land management compared to current land management for Imha Dam. The results of this study indicate that soil loss potential (5,782,829 ton/yr) on Imha Dam in 2003 is approximately 1.27 times higher than that (4,557,151 ton/yr) in 1989. This study represents the first attempt in the application of GIS technology to watershed conservation planning for Imha Dam. The procedures developed will contribute to the evolution of a decision support system to guide the land planning and dam management in Imha Dam.

• Journal of the Korean Data and Information Science Society
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• 제22권4호
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• pp.691-699
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• 2011

현재까지 우리나라뿐만 아니라 세계적으로 급경사지 붕괴는 대표적인 자연재해로 알려져 있다. 급경사지 붕괴 피해를 방지하기 위해 행해진 많은 선행 연구를 바탕으로 일부 국내기관에서는 급경사지 평가표를 만들어 붕괴 예측에 활용하고 있다. 하지만, 대부분의 기존 연구는 비통계전문가들에 의해 행해졌기 때문에 평가표 구성의 통계적 타당성을 제시하지 못했다. 본 연구는 전국 지역을 대상으로 급경사지 (암반사면, 토사사면) 붕괴에 영향을 미칠 것으로 예상되는 인자들의 자료를 수집하고 그 인자들의 가중치를 판정하기 위하여 로지스틱 회귀분석 방법을 사용하였다. 선행연구들 중에 로지스틱 회귀분석을 이용한 기존의 연구들이 있었지만 다중공선성을 전혀 고려하지 않았기 때문에 결과가 신뢰할 만하지 못하다. 본 연구에서는 다중공선성을 제거된 급경사지 붕괴 예측모형을 제시하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.159-162
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• 1998

Land cover and land use classification on a huge scale, e.g. national or continental scale, has become more and more important because environmental researches need land cover: And land use data on such scales. We developed a crop field extraction method, which is one of the steps in our land cover classification system for a huge area. Firstly, a crop field model is defined to characterize "crop field" in terms of NDVI value and textual information Textual information is represented by the density of straight lines which are extracted by wavelet transform. Secondly, candidates of NDVI threshold value are determined by "scale-space filtering" method. The most appropriate threshold value among the candidates is determined by evaluating the line density of the area extracted by the threshold value. Finally, the crop field is extracted by applying level slicing to Landsat TM image with the threshold value determined above. The experiment demonstrates that the extracted area by this method coincides very well with the one extracted by visual interpretation.

• 대한원격탐사학회지
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• 제24권1호
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• pp.45-55
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• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• 대한원격탐사학회지
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• 제19권5호
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• pp.381-392
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• 2003

Multi-temporal approaches using sequential data acquired over multiple years are essential for satisfactory discrimination between many land-cover classes whose signatures exhibit seasonal trends. At any particular time, the response of several classes may be indistinguishable. A harmonic model that can represent seasonal variability is characterized by four components: mean level, frequency, phase and amplitude. The trigonometric components of the harmonic function inherently contain temporal information about changes in land-cover characteristics. Using the estimates which are obtained from sequential images through spectral analysis, seasonal periodicity can be incorporates into multi-temporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 ～ 2000 using a dynamic technique. Land-cover types were then classified both with the estimated harmonic components using an unsupervised classification approach based on a hierarchical clustering algorithm. The results of the classification using the harmonic components show that the new approach is potentially very effective for identifying land-cover types by the analysis of its multi-temporal behavior.

• 산업경영시스템학회지
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• 제46권3호
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• pp.251-258
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• 2023

This study (1) explored spatio-temporal population distribution patterns in Jeonju by using emerging hot spot analysis and (2) identified the influential factors to determine the spatio-temporal patterns by using multinomial logit model. The major findings are as follows. First, the results of emerging hot spot analysis indicated that the 100*100m grid in the urban area of Jeonju was found to have a category of hot spots, whereas most of the cold spot series was concentrated in the outskirts of the city. Also, new towns such as Jeonju Eco City, Jeonbuk Innovation City, and Hyocheon District were persistent or intensifying hot spots, Third, the results of multinomial logit model revealed that the factors influencing deterrmining the spatio-temporal patterns were accessibility to schools, hospitals, parks, and walfare services. This study offered a deeper understanding of urbanization and regional changes in Jeonju, and important information for urban planning.

• 지적과 국토정보
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• 제47권1호
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• pp.143-160
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• 2017

공시지가 제도가 도입된 이후, 부동산정책에 대한 제반 행정의 기준으로 기능해 왔다. 그러나 최근 공시지가의 적정성에 대한 문제가 제기되고 있다. 토지특성항목이 너무 많아 통계모형 수립이 어렵고, 지역적 경제적 환경이나 개발계획 등이 지가평가모형에 반영되기 어렵기 때문이었다. 이에 본 연구에서는 분석 모형으로 시계열적인, 횡단면적인 변수들을 고려하여 패널 모형 중에서 이원오차성분 모형을 적용하였다. 분석 모형에 토지특성변수, 거시경제변수, 개발사업을 반영하는 변수를 포함시켰다. 분석 지역으로는 파주 LCD 산업단지를 선정한 후, 실증분석을 수행하였다. 분석 결과 토지특성변수들 중에서 14개(31%) 변수만이 유의한 것으로 나타났다. 거시경제적 변동성은 지가에 영향을 미치는 것으로 나타났다. 개발사업을 반영하는 연도변수는 산업단지 지정 이후 지속적으로 유의한 것으로 분석되었다. 이러한 결과들은 지가평가모형을 개선할 때 토지특성항목들은 단순화하고, 거시 경제 변수들과 지역 경제 변수들은 모형에 포함시켜야 한다는 것을 의미한다고 하겠다.

• 한국재난정보학회 논문집
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• 제9권1호
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• pp.30-49
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• 2013

본 연구에서는 토지이용에 기반을 두는 새로운 교통사고 예측모형을 개발하였다. 다양한 지역의 특성을 반영할 수 있는 변수에 대한 시장분할 및 추가변수 도입을 토대로 Data Mining 기법의 하나인 의사나무결정법(Classification and Regression Tree)을 활용하여 새로운 유형별 교통사고 예측모형을 개발하였다. 분석결과를 살펴보면 주민등록인구수, 통근 등 활동변수와 활동의 대상이 되는 도로규모, 유발시설 등이 교통사고를 설명하는 변수로 도출되었다.