• Survey Research
• /
• v.10 no.3
• /
• pp.1-19
• /
• 2009

This study investigates the utilities of spatial analysis in the context of survey research using Geographical Information System(GIS) and Geographically Weighted Regression (GWR) which take account of spatial heterogeneity. Many social phenomena involve spatial dimension, and with the development of GIS, GPS receiver, and online location-based services, spatial information can be collected and utilized more easily, and thus application of spatial analysis in the survey research is getting easier. The traditional OLS regression models which assume independence of observations and homoscedasticity of errors cannot handle spatial dependence problem. GWR is a spatial analysis technique which utilizes spatial information as well as attribute information, and estimated using geographically weighted function under the assumption that spatially close cases are more related than distant cases. Residential survey data from a Primary Autonomous District are used to estimate a model of public service satisfaction. The findings show that GWR handles the problem of spatial auto-correlation and increases goodness-of-fit of model. Visualization of spatial variance of effects of the independent variables using GIS allows us to investigate effects and relationships of those variables more closely and extensively. Furthermore, GIS and GWR analyses provide us a more effective way of identifying locations where the effect of variable is exceptionally low or high, and thus finding policy implications for social development.

• Communications for Statistical Applications and Methods
• /
• v.18 no.1
• /
• pp.23-34
• /
• 2011

Property auctions have become a new method for real estate investment because the property auction market grows in tandem with the growth of the real estate market. This study focused on the statistical model for predicting bid price rates which is the main index for participants in the real estate auction market. For estimating the monthly bid price rate, we proposed a new method to make up for the mean of regions and terms as well as to reduce the prediction error using a decision tree analysis. We also proposed a linear regression model to predict a bid price rate for individual auction property. We applied the proposed model to apartment auction property and tried to predict the bid price rate as well as categorize individual auction property into an auction grade.

• The Korean Journal of Applied Statistics
• /
• v.28 no.2
• /
• pp.325-334
• /
• 2015

Elderly suicide rates tend to be high in Korea. Suicide by the elderly is no longer a personal problem; consequently, further research on risk and regional factors is necessary. Disease mapping in epidemiology estimates spatial patterns for disease risk over a geographical region. In this study, we use a simultaneous conditional autoregressive model for spatial correlations between neighboring areas to estimate standard mortality ratios and mapping. The method is illustrated with cause of death data from 2006 and 2010 to analyze regional patterns of elderly suicide in Korea. By considering spatial correlations, the Bayesian spatial models, mean educational attainment and percentage of the elderly who live alone was the significant regional characteristic for elderly suicide. Gibbs sampling and grid method are used for computation.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.3
• /
• pp.118-128
• /
• 2016

As the rural areas have experienced the population reduction and the aging, the service level of public transit decreases. This study analyzes the effecting factor to user satisfaction of demand response transport(DRT) as alternative to rural public transit by the quantile regression that aims at estimating either the conditional median or other quantiles of the response variable. Jeonbuk Province tested DRT operations in Dongsang of Wanju County and Sannae of Jeongup City each in 2015. The user DRT satisfaction of Wanju was higher than one of Jeongup in basic statistics analysis. The difference in satisfaction between higher quantile and lower quntile of Wanju is smaller than one of Jeongupy as a result of quantile regression analysis. Also, Wanju DRT continues the second test operation of DRT as satisfaction from Ordinary Least Squares(OLS) close to higher satisfaction quantile.

• Journal of Korea Water Resources Association
• /
• v.45 no.10
• /
• pp.1023-1034
• /
• 2012

Linear regression technique has been used widely in water resources field as well as various fields such as economics and statistics, and so on. Using fuzzy regression technique, it is possible to quantify uncertainty and reflect them to the regression model. In this study, fuzzy regression model is developed to compute design floods in any place in Pyeongchang River basin. In ungaged basins, it is usually difficult to obtain data required for flood discharge analysis. In this study, basin characteristics elements are analyzed spatially using GIS and the technique of estimating design flood in ungaged mountainous basin is studied based on the result. Fuzzy regression technique is applied to Pyeongchang River basin which has mountainous basin characteristics and well collected rainfall and runoff data through IHP test basin project. Fuzzy design flood estimation equations are developed using the basin characteristics elements for Pyeongchang River basin. The suitability of developed fuzzy equations are examined by comparing the results with design floods computed in 9 locations along the river. Using regional regression method and fuzzy regression analysis, the uncertainties of the design floods occurred from the data monitoring can be quantified.

• Journal of Cadastre & Land InformatiX
• /
• v.48 no.2
• /
• pp.65-77
• /
• 2018

It is very important to understand the factors affecting the occurrence of vacant houses in research on them. The purpose of this study is to analyze the factors affecting the rural vacancy occurrence. This study set 121 research areas and selected eight independent variables (Aged house rate, housing transaction rate, house diffusion ratio, local extinction index, net migration rate, regional aging index, the ratio of the number of employees to population and financial independence rate) and one dependent variable (vacant house rate). As a result of the study, first, both Model 1 for the entire general agricultural fishing village area and Model 2 for the county (gun) area were statistically significant, there was no problem with the independence of residual. Second, local extinction index and aged house rate had a statistically significant positive (+) relationship in both Model 1 and Model 2. Third, diffusion ratio of house had a statistically significant positive (+) relationship only in Model 1, and housing transactions rate had a statistically significant negative (-) relationship in Model 2. The implications of the study were drawn as follows: First, the increase in the house diffusion ratio without growth in households and population suggests the increase of the probability of the vacancy occurrence in the area, and the higher the aged house rate, the higher the probability of the vacancy occurrence. Second, for the revitalization of housing transactions, it is necessary to have an investment inflow in the area for mid- to long-term development. Third, local extinction index has a significant relationship with vacant house rate, it is necessary to introduce a local revitalization policy from a long-term perspective for the permanence of the area.

• The Journal of Engineering Geology
• /
• v.32 no.4
• /
• pp.585-596
• /
• 2022

This study determined major factors influencing landslide occurrence along a forest road near Sangsan village, Sancheok-myeon, Chungju-si, Chungcheongbuk-do, South Korea. Within a 2 km radius of the study area, landslides occur intensively during periods of heavy rainfall (August 2020). This makes study of the area advantageous, as it allows examination of the influence of only geological and tomographic factors while excluding the effects of rainfall and vegetation. Data for 82 locations (37 experiencing landslides and 45 not) were obtained from geological surveys, laboratory tests, and geo-spatial analysis. After some data preprocessing (e.g., error filtering, minimum-maximum normalization, and multicollinearity), structural equation model (SEM) and logistic regression (LR) analyses were conducted. These showed the regolith thickness, porosity, and saturated unit weight to be the factors most influential of landslide risk in the study area. The sums of the influence magnitudes of these factors are 71% in SEM and 83% in LR.

• Journal of Korean Society of Forest Science
• /
• v.100 no.3
• /
• pp.402-407
• /
• 2011

The objectives of this study were to analyze the crown vertical structure, crown bulk density, and to develop regression models for predicting crown fuel load using the data from 10 destructively sampled Pinus densiflora trees in Bonghwa, Gyeongbuk. The fuel loads were observed higher in the middle portion of the vertical distribution of crown followed by the lower portion and upper portion of Pinus densiflora, respectively. Approximately 25% crown fuel load was found in the needle while 33% was observed in the branches with <1 cm diameter with a total of 58% available fuel loads. The average crown bulk density was $0.45kg/m^3$, and $0.27kg/m^3$ of this was available in the needles and branches with <1 cm diameters. The resulting models in linear equations were able to account for 84% and 88% of the observed variation, while the allometric equations with diameter at breast height as the single predictor showed better results to account for 90% and 95% of the observed variation in the available crown fuel loads and total crown fuel loads, respectively. The suggested equations in this study could provide quantitative fuel load attributes for crown fire behavior models and fire management of red pine stands in Bonghwa areas.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.3
• /
• pp.189-204
• /
• 2018

This study has developed a forest fire occurrence probability model for inaccessible areas such as North Korea and Demilitarized Zone and we have developed a real-time forest fire danger rating system that can be used in fire-related works. There are limitations on the research that it is impossible to conduct site investigation for data acquisition and verification for forest fire weather index model and system development. To solve this problem, we estimated the fire spots in the areas where access is impossible by using MODIS satellite data with scientific basis. Using the past meteorological reanalysis data(5㎞ resolution) produced by the Korea Meteorological Administration(KMA) on the extracted fires, the meteorological characteristics of the fires were extracted and made database. The meteorological factors extracted from the forest fire ignition points in the inaccessible areas are statistically correlated with the forest fire occurrence and the weather factors and the logistic regression model that can estimate the forest fires occurrence(fires 1 and non-fores 0). And used to calculate the forest fire weather index(FWI). The results of the statistical analysis show that the logistic models(p<0.01) strongly depends on maximum temperature, minimum relative humidity, effective humidity and average wind speed. The logistic regression model constructed in this study showed a relatively high accuracy of 66%. These findings may be beneficial to the policy makers in Republic of Korea(ROK) and Democratic People's Republic of Korea(DPRK) for the prevention of forest fires.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.195-195
• /
• 2021

최근 기후변화, 과도한 지하수 이용 등으로 유역 환경이 변화하고 있으며, 이에 따른 부작용으로 하천의 건천화, 지표유출량 증가, 증발산량 감소 등 물순환 구조가 왜곡되고 있다. 물순환 과정은 지역적 조건에 따라 다르게 나타나며, 모의 요소와 해석 기법도 다르다. 따라서 지속가능하고 건전화된 물순환을 위해 해당 유역의 물순환계를 정확히 파악하고 고려하여 객관적으로 정량화할 수 있어야 한다. 현재 우리나라 농업유역은 논, 용·배수로, 농업용 저수지가 존재하며, 종합적인 농촌용수 물순환 해석을 위해 농촌용수 요소별 해석 기술 및 모듈 개발, 모델링 기법 등을 이용하여 농촌수자원의 체계적·과학적 해석 및 관리 시스템 개발이 이루어져야 한다. 본 연구에서는 강원도 원주시에 위치한 흥업저수지를 대상으로 농촌용수의 물순환 과정을 정립하였으며, 저수지 시점부·말단부, 농업용 저수지, 저수지 유역으로 구분하여 물순환 분석을 수행하였다. 물순환 모의 요소로 저수지 수위, 유역 유출량, 수로부 공급량 및 배수량, 회귀수량 등으로 선정하였으며, 수로 네트워크 기반의 SWMM (Storm Water Management Model) 모형을 이용하여 종합적인 농촌용수 물순환 해석을 수행하였다. 또한, 물순환 해석 기법의 적용성 검증을 위해 모의 요소별 모니터링을 수행하였으며, SWMM 모형과 모니터링을 비교하여 적용성을 평가하였다. 본 연구 결과를 통해 농촌지역 특성 및 기후변화를 고려한 농촌수자원의 안정적인 공급과 국가 청정 수자원 확보를 위한 통합 물관리 정책을 실현하는데 기초 자료로써 활용 가능할 것이라 사료된다.