• Spatial Information Research
• /
• v.21 no.5
• /
• pp.15-22
• /
• 2013

The purpose of this work is to investigate correlation between $CO_2$ concentration and NDVI (Normalized Difference Vegetation Index) in North East Asia. Geographically weighted regression techniques were used to evaluate the spatial relationships between GOSAT (Greenhouse Observing SATellite) $CO_2$ measurement and MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation index. The results reveals that $CO_2$ concentration to be negatively associated with NDVI. The analysis of Global Morans' I index and Anselin Local Morasn's I showed spatial autocorrelation between the overall spatial pattern of $CO_2$ and NDVI. Ultimately, there were clustered patterns in both data sets. The results show that carbon dioxide concentration shows non-random distribution patterns in relation to NDVI clusters, which proves that intense development activities such as deforestation are influencing carbon dioxide emission across the area of analysis. However, as the concentration of carbon dioxide varies depending on a variety of factors such as artificial sources, plant respiration, and the absorption and discharge of the ocean, follow-up studies are required to evaluate the correlations among more related variables.

• Archives of design research
• /
• v.17 no.3
• /
• pp.61-70
• /
• 2004

This study is focused on user awareness of avatar character in the cyber space. The purpose of this study is to investigate user preference toward avatar and test their awareness on it. The awareness of avatar is based on the applied degree of self-awareness, and also analyzed by factors using 3 elements such as loyalty, value and confidence in Maurice Wagner's study but self-projection was added to these three variables. The result shows that there is no significant statistical difference among response groups for age and sex classification but the preference and the value variables are significantly dependent on sex and age, respectively. There are strong correlation among each response variables for the awareness of avatar character and the loyalty and the preference variables are mostly correlated. The regression analysis shows that the preference of avatar is mostly affected by loyalty and thus the self awareness of avatar in the Cyberspace is proportional to user preference. It is shown that users do not awareness an avatar as a visual image but identify their avatar as an another selfness since they project themselves into those avatars.

• Journal of Korea Water Resources Association
• /
• v.49 no.9
• /
• pp.761-771
• /
• 2016

The GloSea5 (Global Seasonal forecasting system version 5) is provided and operated by the KMA (Korea Meteorological Administration). GloSea5 provides Forecast (FCST) and Hindcast (HCST) data and its horizontal resolution is about 60km ($0.83^{\circ}{\times}0.56^{\circ}$) in the mid-latitudes. In order to use this data in watershed-scale water management, GloSea5 needs spatial-temporal downscaling. As such, statistical downscaling was used to correct for systematic biases of variables and to improve data reliability. HCST data is provided in ensemble format, and the highest statistical correlation ($R^2=0.60$, RMSE = 88.92, NSE = 0.57) of ensemble precipitation was reported for the Yongdam Dam watershed on the #6 grid. Additionally, the original GloSea5 (600.1 mm) showed the greatest difference (-26.5%) compared to observations (816.1 mm) during the summer flood season. However, downscaled GloSea5 was shown to have only a -3.1% error rate. Most of the underestimated results corresponded to precipitation levels during the flood season and the downscaled GloSea5 showed important results of restoration in precipitation levels. Per the analysis results of spatial autocorrelation using seasonal Moran's I, the spatial distribution was shown to be statistically significant. These results can improve the uncertainty of original GloSea5 and substantiate its spatial-temporal accuracy and validity. The spatial-temporal reproducibility assessment will play a very important role as basic data for watershed-scale water management.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.5D
• /
• pp.507-517
• /
• 2012

The main purpose of this study is to address flooding resilient land use management strategy based on the distributional characteristics of storm damage areas in Gyeonggi-do. The employed methods are 1) Exploratory Spatial Data Analysis (ESDA) to understand the spatial patterns of storm damage areas occurred from 2005 to 2009, 2) Local Indicator of Spatial Association (LISA) to examine spatial autocorrelation existed in storm damage areas for the year of 2009. The results show that 1) crop land damage is very sensitive to heavy precipitation, 2) damaged buildings are found in all over the Gyeonggi areas, but relatively more damages are in the regions closed to the City of Seoul, 3) damaged roads-bridges, streams, and reaches are found in mostly rural areas, 4) building and crop land damage occurs mostly in lowlands with different spatial patterns. These findings imply that 1) it will be useful to consider the average distances and slopes of damaged building and crop lands from streams for the decision making of land use management strategy, 2) further management efforts are required in the north, east, and south regions of Gyeonggi areas to prevent roads-bridge, stream, and reach damages, 3) the present land use pattern needs to be carefully investigated by considering the damage clustered areas for the year of 2009 based on watershed and municipality boundaries.

• Journal of the Economic Geographical Society of Korea
• /
• v.18 no.3
• /
• pp.335-347
• /
• 2015

Music industry is considered as a creative industry, which tends to locate within a city. However, there is very few paper analysing spatial patterns of music industry in Korea. This study aims to understand music industry's value chain and its location pattern; whether it is clustered or dispersed. In detail, music industry contains five sub-industry: planning, manufacturing, distribution, sales and performance. Locational pattern of each sub-industry is tested by GIS and hot spot analysis. There are several findings from this research. First, value chain of music industry make clusters and have a spatial autocorrelation. Second, the result shows that music industry makes a hotspot area at Gangnam, Guro, Mapo and Jongro-Junggu.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.655-657
• /
• 2010

현재 코골이를 방지하는 위한 기구로는 양압 산소호흡기, 스프레이, 전기자극기, 수술, 구강내 보조기구가 있으나 개인용으로 사용하기에는 가격이 너무 고가이어서 일반적인 코골이 환자에게 적용하기에는 무리가 있으며 사용자에 따라 부작용의 위험이 있다. 본 논문에서는 정확하고 안정적인 코골이 신호인식을 위해 시계열 분석방법을 통해서 선형적인 성질보다 비선형적인 성질이 강한 코골이 신호의 카오틱 신호 유무를 해석하였다. 본 논문에서 사용한 시계열 데이터는 30대 성인남자로부터 수면시간 6시간중중 발생하는 코골이 음성신호를 마이크를 통해 샘플링 주파수 22kHz, 모노 형태로 수집한 것이다. 위상공간의 궤적 분석, 매입차원에 의한 상관적분 분석, 파워 스펙트럼과 자기상관함수 분석 등의 정량 및 정성적 분석방법을 통해서 수집한 코골이 신호의 분석결과 신호가 부분적으로 주기적 성질을 가지는 카오스 신호임을 확인하였다.

• Journal of Korea Water Resources Association
• /
• v.32 no.6
• /
• pp.731-740
• /
• 1999

Autocorrelation function is widely used as a tool measuring linear dependence of hydrologic time series. However, it may not be appropriate for choosing decorrelation time or delay time ${\tau}_d$ which is essential in nonlinear dynamics domain and the mutual information have recommended for measuring nonlinear dependence of time series. Furthermore, some researchers have suggested that one should not choose a fixed delay time ${\tau}_d$ but, rather, one should choose an appropriate value for the delay time window ${\tau}_d={\tau}(m-1)$, which is the total time spanned by the components of each embedded point for the analysis of chaotic dynamics. Unfortunately, the delay time window cannot be estimated using the autocorrelation function or the mutual information. Basically, the delay time window is the optimal time for independence of time series and the delay time is the first locally optimal time. In this study, we estimate general dependence of hydrologic time series using the C-C method which can estimate both the delay time and the delay time window and the results may give us whether hydrologic time series depends on its linear or nonlinear characteristics which are very important for modeling and forecasting of underlying system.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2012.05a
• /
• pp.456-456
• /
• 2012

한강유역에 위치한 247개의 강우계에서 관측된 강우 자료를 분석하여 Modified Bartlett-Lewis Retangular Pulse Model (MBLRPM)의 매개변수들을 산정하고, 이들의 지도를 작성한 후, 이들의 정확도 및 매개변수들의 시/공간적 변화 유형을 분석하였다. 이를 위한 첫번째 과정으로, 각 강우 게이지에 대해 MBLRPM의 매개변수에 사용되는 통계치 (각 달에 대한 1, 3, 12, 24시간 누적 수준에서의 평균, 분산, 자기 상관계수, 무강우 확률)들을 계산한다. 이 후, 격자화된 한강유역의 각 셀에 대하여 앞서 계산된 강우 통계치를 Ordinary Kriging 공간 보간법을 통하여 할당한다. 이 후, 각 셀에 할당된 강우 통계치를 사용하여 MBLRPM의 매개변수들을 산정하여 각 매개변수들의 지도를 각 달에 대하여 얻는다. 매개변수 지도를 사용하여 MBLRPM에 의해 생성된 강우 데이터들은 관측치의 통계치를 정확성있게 재현하였으며, 시/공간적 경향성을 분석한 결과, 강우세포의 지속기간과 관련된 매개 변수를 제외한 나머지 5개의 매개변수들은 확연한 공간적 경향성을 보인 한 편, 시간적 경향성은 잘 나타나지 않았다. 본 연구 결과는 매개변수 산정이 힘든 MBLRPM의 특성을 극복하게 해주어 가상 강우 생성을 용이하게 함으로써 강우에 영향을 받는 여러 종류의 연구 주제에 대해 불확실성 분석을 할 수 있게 한다는 점에서 의미를 가질 수 있다.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.3
• /
• pp.77-84
• /
• 2015

The key objective of this research is to review the effectiveness of spatial regression to identify the influencing factors of spatial distribution patterns of floating population. To this end, global and local spatial autocorrelation test were performed using seoul floating population survey(2014) data. The result of Moran's I and Getis-Ord $Gi^*$ as used in the analysis derived spatial heterogeneity and spatial similarities of floating population patterns in a statistically significant range. Accordingly, Geographically Weighted Regression was applied to identify the relationship between land use attributes and population floating. Urbanization area, green tract of land of micro land cover data were aggregated in to $400m{\times}400m$ grid boundary of Seoul. Additionally public transportation variables such as intersection density transit accessibility, road density and pedestrian passage density were adopted as transit environmental factors. As a result, the GWR model derived more improved results than Ordinary Least Square(OLS) regression model. Furthermore, the spatial variation of applied local effect of independent variables for the floating population distributions.

• Journal of the Korean Geographical Society
• /
• v.51 no.2
• /
• pp.219-233
• /
• 2016

In social science fields, statistical models are used almost exclusively for causal explanation, and explanatory modeling has been a mainstream until now. In contrast, predictive modeling has been rare in the fields. Hence, we focus on constructing the predictive non-parametric model, instead of the explanatory model. Gangnam-gu, Seoul was chosen as a study area and we collected single-family house sales data sold between 2011 and 2014. We applied non-parametric models proposed in machine learning area including generalized additive model(GAM), random forest, multivariate adaptive regression splines(MARS) and support vector machines(SVM). Models developed recently such as MARS and SVM were found to be superior in predictive power for house price estimation. Finally, spatial autocorrelation was accounted for in the non-parametric models additionally, and the result showed that their predictive power was enhanced further. We hope that this study will prompt methodology for property price estimation to be extended from traditional parametric models into non-parametric ones.