• Spatial Information Research
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• v.8 no.1
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• pp.85-99
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• 2000

Accurate information on habitat distribution of protected fauna is essential for the habitat management of Korea, a country with very high development pressure. The objectives of this study were to develop a habitat suitability model of wild boar based on GIS and logistic regression, and to create habitat distribution map, and to prepare the basis for habitat management of our country s endangered and protected species. The modeling process of this restudyarch had following three steps. First, GIS database of environmental factors related to use and availability of wild boar habitat were built. Wild boar locations were collected by Radio-Telemetry and GPS. Second, environmental factors affecting the habitat use and availability of wild boars were identified through chi-square test. Third, habitat suitability model based on logistic regression were developed, and the validity of the model was tested. Finally , habitat assessment map was created by utilizing a rule-based approach. The results of the study were as folos. First , distinct difference in wild boar habitat use by season and habitat types were found, however, no difference in wild boar habiat use by season and habitat types were found , however, ho difference by sex and activity types were found. Second, it was found, through habitat availability analysis, that elevation , aspect , forest type, and forest age were significant natural environmental factors affecting wild boar hatibate selection, but the effects of slope, ridge/valley, water, and solar radiation could not be identified, Finally, the habitat at cutoff value of 0.5. The model validation showed that inside validation site had the classification accuracy of 73.07% for total habitat and 80.00% for cover habitat , and outside validation site had the classification accuracy of 75.00% for total habitat.

• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.77-85
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• 2015

The Hedonic Pricing model is the predominant approach used today to model the effect of relevant factors on real estate prices. These factors include intrinsic elements of a property such as floor areas, number of rooms, and parking spaces. Also, The model also accounts for the impact of amenities or undesirable facilities of a property's value. In the latter case, euclidean distances are typically used as the parameter to represent the proximity and its impact on prices. However, in situations where multiple facilities exist, multi-colinearity may exist between these parameters, which can result in multi-regression models with erroneous coefficients. This research uses Variance Inflation Factors(VIF) and Ridge Regression to identify these errors and thus create more accurate and stable models. The techniques were applied to apartments in Guro-gu of Seoul, whose prices are impacted by subway stations as well as a public prison, a railway terminal and a digital complex. The VIF identified colinearity between variables representing the terminal and the digital complex as well as the latitudinal coordinates. The ridge regression showed the need to remove two of these variables. The case study demonstrated that the application of these techniques were critical in developing accurate and robust Hedonic Pricing models.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.3
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• pp.307-324
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• 2011

The culture industry is viewed as a driving industry in the 21th century. Korea has experienced the rapid growth rate of the cultural industry in terms of sale amounts for the period of 2004-2009. The purposes of this study are to analyze the spatial pattern of the cultural industry and to empirically examine the effect of municipalities' cultural industries on regional economy using SUR model. The major findings are as follows: First, cultural industries are concentrated in the capital region and several metropolitan areas. Secondly, the estimated result of SUR model shows that there is inter-relationship between cultural industry and regional economy. The effect of the cultural industry on GRDP is that the cultural industry increased 1%, GRDP increased by 0.46%. In turn, GRDP increased 1%, cultural industry increased by 0.75%. Thirdly, the elasticity of the cultural industry on GRDP is much higher than that of labor or capital stock, showing that the cultural industry has a more powerful influence on its regional economy. Fourth, the elasticity of the cultural industry on GRDP of Gun is higher than that of shi, indicating that it is rational for Gun to develop strategies to promote competitive power of the cultural Industry for regional economic growth.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.1
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• pp.16-23
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• 2000

A topography-precipitation relationship derived from the southern part of Korean Peninsula was applied to North Korea where climate stations are few and widely separated. Two hundred and seventy seven rain gauge stations of South Korea were classified into 8 different groups depending on the slope orientation (aspect) of the region they are located. Monthly precipitation averaged over 10 year period (1986-1995) was regressed to topographical variables of the station locations. A 'trend precipitation' for each gauge station was extracted from the precipitation surface interpolated from the monthly precipitation data of 24 standard stations of the Korea Meteorological Administration and used as a substitute for y-axis intercept of the regression equation. These regression models were applied to the corresponding regions of North Korea, which were identified by slope orientation, to obtain monthly precipitation surface for the aspect regions. 'Trend precipitation' from the 10 year data of 27 North Korean standard stations was also used in the model calculation. Output grids for each aspect region were mosaicked to form the monthly and annual precipitation surface with a 1km$\times$1km resolution for the entire territory of North Korea. Spatially averaged annual precipitation of North Korea was 938 mm with the standard deviation of 246 mm.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.50-50
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• 2016

하천에서 유사 및 오염물질의 이동을 예측하기 위하여 초점을 두는 것에는 두 가지 요소가 있다. 입자의 농도로 나타낼 수 있는 양의 개념과 입자의 위치로 나타낼 수 있는 공간의 개념이 그것이다. 유사 입자와 같이 그 비중이 물보다 큰 경우, 흐름 내에서 침전과 부상의 메커니즘을 반복하게 되는데 최종적으로 바닥에 침적하는 위치는 하상변동, 서식처 등 하천관리의 다양한 측면에서 매우 중요하다. 유사 입자가 바닥에 침적하는 위치를 예측하는 데에는 난류와 지형 같은 많은 불확실한 요소가 내포되어 있어, 같은 크기의 유사 입자라 하여도 하나의 exact point로 도달하지 않는다. 이러한 불확실한 요소를 고려하여 침전 위치를 산정하는 방법에 대한 연구가 필요하다. 따라서 본 연구에서는 침전 위치를 확률밀도함수로 나타내어 분석하고자 한다. 입자의 침전 위치를 확률밀도함수로 나타내기 위하여 입자 기반의 추적 모형을 사용하여 위치 데이터를 얻었으며, 이를 실험데이터와 비교하여 검증 후 확률밀도함수로 나타내었다. 그 결과 입자의 침적 위치에 대한 확률밀도함수는 로그정규분포를 띠고 있음을 확인하였으며, 확률밀도함수를 나타내는 매개변수를 물리 기반 회귀모형식으로 일반화 하여 나타낼 수 있었다.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.1-12
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• 2024

In many real-world data, multiple response variables are often dependent on the same set of explanatory variables. In particular, if several response variables are correlated with each other, simultaneous estimation considering the correlation between response variables might be more effective way than individual analysis by each response variable. In this multivariate regression analysis, least distance estimator (LDE) can estimate the regression coefficients simultaneously to minimize the distance between each training data and the estimates in a multidimensional Euclidean space. It provides a robustness for the outliers as well. In this paper, we examine the least distance estimation method in multivariate linear regression analysis, and furthermore, we present the penalized least distance estimator (PLDE) for efficient variable selection. The LDE technique applied with the adaptive group LASSO penalty term (AGLDE) is proposed in this study which can reflect the correlation between response variables in the model and can efficiently select variables according to the importance of explanatory variables. The validity of the proposed method was confirmed through simulations and real data analysis.

• Journal of the Korean Geographical Society
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• v.36 no.5
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• pp.561-577
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• 2001

Urban spatial structure is closely related to the spatial distribution of urban economic activities. The spatial distribution pattern is no more than an aggregated expression of the location and/or relocation behavior of individual firms and establishments. In this respect, it is important to identify and examine the factors that affect the spatial behavior of individual firms for a more comprehensive understanding of urban space. Agglomeration economies are one of the most prominent urban economic phenomena in the modern metropolitan area. Most firms in an urban space seek external economies through the spatial clustering of their activities. Agglomeration economies feature prominently in the analysis of urban economic structure across urban areas. While the agglomeration economies between cities focus at the macro-scale of analysis, such economies within any given city focus more on the micro geographical scale. There have been a number of researches on agglomeration economies, among which there are relatively few approaches based on an intra-urban context. This proper explores the agglomeration economies at the micro scale and tries to reseal the spatial realization of the agglomeration economies within and between sectors. Three sectors are considered in the analysis; manufacturing, retail and service. The model is based on simultaneous equation systems combined with spatially weighted variables and estimated by the KRP estimators.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.929-933
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• 2009

전 세계적으로 기후변화와 이상기후에 대한 관심이 높아지고 있다. IPCC(2001)는 "기후변화"라는 요소가 기온 증가, 강우강도 및 빈도 변화와 이들로 인한 증발산의 변화, 유출량의 시 공간적 변동을 초래하여 수자원의 효율적 관리 및 안정적인 공급에 어려움을 증대시킬 것으로 전망하였다. 이에 따라 세계 각국은 미래 기후에 대한 보다 정확한 정보를 얻기 위하여 IPCC 권장 시나리오인 SRES(Special Report in Emission Scenario)기반의 GCM(General Circulation Model)과 RCM(Regional Circulation Model)을 이용하고 있으며 특히, 최근에는 고해상도 자료를 생산함으로써 국부지역에 대한 지형학적 특성을 효과적으로 모의할 수 있는 RCM 모형을 이용한 연구가 국외를 중심으로 진행되고 있다(권현한 등, 2008). 본 연구에서는 미래 한강 유역의 수자원 변동성을 평가하기 위하여 CA-Markov Chain 기법으로부터 토지이용변화를, 기온과 강수자료을 독립변수로 이용한 다중 회귀식으로부터 미래 NDVI를 추정하고 기상청에서 제공하는 RegCM3-지역지후모형으로부터 축소기법을 이용하여 추정된 KMA RCM 50set 기후변화시나리오를 SLURP 모형에 입력하였다. 2001년부터 2090년까지 총 90년에 대한 한강 유역의 미래 유출모의를 실시한 후 각 댐별 과거와 미래 유출량을 월별로 비교하고 이들의 유황분석을 실시하였다.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.111-115
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• 2009

본 연구에서는 SWAT 모형에서 모의된 토양수분의 신뢰성을 판단하기 위해 MODIS NDVI의 활용성을 파악하고자 하였다 MODIS 위성영상을 이용하여 시간해상도 16일, 공간해상도 250m의 NDVI를 추출하였으며, 대상유역은 면적이 약 $6661.3km_2$ 이고 그 중 산림이 약 82.2%를 차지하고 있는 충주댐 유역으로 하였다. 보다 신뢰성 있는 자료를 얻기 위해 토양, 토지이용 등 유역의 특성이 다른 상류와 하류로 나누어 다지점 검보정을 수행하였으며, 2003년부터 2006년까지의 유출 자료를 이용하여 모형을 보정하고, 2000, 2001 그리고 2002년에 대하여 검증하였다. 검보정 결과 모형 효율성 계수는 상류와 하류에 대하여 각각 0.91, 0.87, 결정계수는 각각 0.90, 0.80으로 분석되었다. 분석 기간은 2000년부터 2006년까지이고, NDVI의 특성에 따라 봄기간과 가을기간으로 나누어 분석하였으며, 선형회귀 방적식과 결정계수를 이용하여 상관성을 판단하였다. 분석결과 SWAT에서 모의된 토양수분과 MODTS NDVI는 약 55%의 상관성을 나타내었고, 가뭄해인 2001년에 약 85%로 상관성이 매우 높고, 비가 많이 온 해인 2002년에 약 2%로 상관성이 매우 낮아 NDVI는 가뭄 기간 SWAT에서 모의된 토양수분의 신뢰성을 검증할 수 있는 자료로 사용될 수 있다고 판단되었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.276-276
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• 2021

최근 댐과 같은 수공구조물의 건설로 대규모 홍수피해는 급격히 줄어들었지만, 돌발홍수(flash flood)로 인한 저지대 침수 등의 도시홍수 발생빈도가 급증하고 있다. 2020년에는 최장의 장마가 관측되었으며, 전국적으로 홍수로 인한 침수피해가 발생하였다. 홍수에 선제적으로 대응하기 위해서 신뢰성 있는 홍수예·경보가 필요하며, 이를 위해서는 신속하고 정확성있는 강우예측이 선행되어야 한다. 이에 본 연구에서는 초단기 강우예측을 목적으로 둔 레이더 기반의 강우앙상블 예측모형을 개발하였다. 라그랑지안 지속성(Lagrangian persistence)을 기반으로 개발하였으며, 강우장의 이동 패턴은 이류특성을 활용해 추정하였다. 즉, 강우장의 예측정확도를 향상시키기 위해 공간적 규모별 캐스캐이드(cascade) 방법으로 분리해 이동 경로를 추정하였다. 예측시간에 따른 강우량은 각 캐스캐이드에 자기회귀모형을 적용하였다. 레이더 강우량은 2016-2020년 사이에 발생한 강우사상에 대한 환경부 홍수통제소에서 제공한 레이더 합성장을 이용하였다. 예측강우량에 대한 평가는 RMSE, Pearson's Correlation, FSS 등 통계치를 통해 수행하였다. 본 연구에서 소개된 강우예측 모형은 초단기 홍수예측에 정확도 높은 강우 정보를 제공할 수 있으며, 이에 따라 홍수피해를 저감하는데 도움이 될 것으로 판단된다.