• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.6
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• pp.73-83
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• 2015

The objective of this study is to establish implications for forest restoration planning in North Korea by analyzing spatio-temporal forest changes and detecting bio-physical factors driving forest degraded. We measured the relationship and spatial distribution between shifting cultivation and sparse forest. We also analyzed between degraded forest land and ecological variables by binary logistic regression to find biophysical drivers of forest degradation and deforestation in North Korea. Between the sparse forest and the shifting cultivation, a positive relationship is found (r=0.91) and scattered discontinuously throughout the country (Moran's I = -1, Z score = -13.46 (p=0.000)). The sparse forest showed a negative relationship with the warmest month(bio 9), the coldest month(bio10), and the minimum of soil water contents (swc_min), while the shifting cultivation had a negative relationship with the warmest month(bio 9) and the minimum of soil water contents(swc_min). However, the most critical drivers convert forests into sloping farmland were the three months rainfall in summer(bio8) and the yearly mean of soil water contents. Such results reflect the growth period of crops which overlaps with the rainy season in North Korea and the recent land reclamation of uplands where the soil water contents are maintained with a dense forest. When South Korea aids forest restoration projects in North Korea, in consideration of food shortage due to North Korea's cropland deficiency, terrace farmlands where soil water contents can be maintained should be excluded from the priority restoration area. In addition, an evaluation method for selecting a potential restoration area must be modified and applied based on multiple criteria including altitude and socio-economic factors in the respective regions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.31-39
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• 2017

The goal of this study was to efficiently analyze the relationships of the number of thefts with related factors, considering the spatial patterns of theft crimes. Theft crime data for a 5-year period (2009-2013) were collected from Haeundae Police Station. A logarithmic transformation was performed to ensure an effective statistical analysis and the number of theft crimes was used as the dependent variable. Related factors were selected through a literature review and divided into social, environmental, and defensive factors. Seven factors, were selected as independent variables: the numbers of foreigners, aged persons, single households, companies, entertainment venues, community security centers, and CCTV (Closed-Circuit Television) systems. OLS (Ordinary Least Squares) and GWR (Geographically Weighted Regression) were used to analyze the relationship between the dependent variable and independent variables. In the GWR results, each independent variable had regression coefficients that differed by location over the study area. The GWR model calculated local values for, and could explain the relationships between, variables more efficiently than the OLS model. Additionally, the adjusted R square value of the GWR model was 10% higher than that of the OLS model, and the GWR model produced a AICc (Corrected Akaike Information Criterion) value that was lower by 230, as well as lower Moran's I values. From these results, it was concluded that the GWR model was more robust in explaining the relationship between the number of thefts and the factors related to theft crime.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

• Journal of Practical Agriculture & Fisheries Research
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• v.8 no.1
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• pp.30-42
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• 2006

This experiment was conducted to investigate current situation and plant grouping by light and watering of mingled several cacti and succulents in a pot. The main 11 cacti are consist of Myrtillocactus geometrizans (Mart.) Cons., Gymnocalycium mihanovichii var. friedrichii Werd., Marginatocereus marginatus(DC.) Backbg., Eriocactus leninghausii (Hge. Jr.) Backbg, Notocactus scopa (Spreng.) Berg., Lobivia nealeana Backbg., Mammillaria elongata var. intertexta (DC.) SD., Pseudoespostoa (Vp1.) Backbg., Mammillaria albilanata Backbg., Mammillaria klissingiana Bod. and Espostoa lanata (HBK.) Br. & R. The main 10 succulents are Kalanchoe thyrsifolia Harv., Portulacaria afra var. foliis-variegatis Jacobs., Crassula perforata Thunbg., Echeveria pulvinata Rose, Aeonium arboreum cv. atropurpureum., Echeveria lauii Moran & J. Meyran, Pachypodium lamerei Drake, Sedum rubrotinctum cv. Aurora Boom., Aloe mitriformis Mill., and Euphorbia coerulescens Haw. The cacti were native to Mexico, Brazil, Peru, Paraguay, Ecuador, etc. The sucullents were native to Mexico, Africa, Gran Canaria, Madagascar, etc. Most of all the cacti and sucullents in the experiment are growing well under full sun or light shade, however Portulacaria afra var. foliis-variegatis Jacobs, and Sedum rubrotinctum cv. Aurora Boom. did not influenced by light. And all the plants require a little or moderate watering. Thus, planting by similar required water and light, when growing in a pot of several cacti and succulents, might be decreased the rate of death causing by their different plant physiology.

• Journal of Preventive Medicine and Public Health
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• v.52 no.1
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• pp.14-20
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• 2019

One of the primary goals of epidemiology is to quantify various aspects of a population's health, illness, and death status and the determinants (or risk factors) thereof by calculating health indicators that measure the magnitudes of various conditions. There has been some confusion regarding health indicators, with discrepancies in usage among organizations such as the World Health Organization the, Centers for Disease Control and Prevention (CDC), and the CDC of other countries, and the usage of the relevant terminology may vary across papers. Therefore, in this review, we would like to propose appropriate terminological definitions for health indicators based on the most commonly used meanings and/or the terms used by official agencies, in order to bring clarity to this area of confusion. We have used appropriate examples to make each health indicator easy for the reader to understand. We have included practical exercises for some health indicators to help readers understand the underlying concepts.

• Journal of Information Technology Services
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• v.22 no.2
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• pp.1-21
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• 2023

Due to the convergence and complexity of the 4th Industrial Revolution, the boundaries between industries have become unclear and ambiguous. Consequently, there is a lack of research on how firms engaged in this industry are changing their location behavior. Recently, some attempts to classify the industrial groups of the 4th Industrial Revolution and their detail occupations have been made, and this study adopts the classification of Lee and Jung (2020) of the Korea Institute for Industrial Economics & Trade. In this study, the 18 detailed industries commonly included in multiple industrial groups are defined as 'core industries' and are classified into manufacturing and service industries to explore the spatial patterns of firms' location. Specifically, this study aims to examine how the location behavior of firms in core industries of the 4th Industrial Revolution has changed from 2010 to 2019 in the Seoul metropolitan area, using the 「National Business Survey」 data. We employed two methods based on spatial auto-correlation: (i) spatial kernel density estimation analysis and (ii) local Moran's I_i analysis. The results indicate that the core industry firms form more distinct and larger clusters in 2019 based on the clusters formed in 2010. Specifically, manufacturing industry firms tended to concentrate in the southern region of Gyeonggi and parts of Seoul, while serivce industry firms were more concentrated in Seoul. These core industries play a critical role in industries and are closely related to the ICT industries, which generate high-added value and increase productivity in the front and rear industries. This study reveals that the agglomeration of these industries in specific regions is intensifying and may exacerbate regional inequality.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.120-132
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• 2022

Recently, the rapid increase in vacant houses in urban areas has caused various problems such as worsening urban landscape, causing safety accidents, crime accidents, and hygiene problems. According to the Statistics Korea Future Population Estimation results, the growth rate of Korean population and households is expected to continue to decrease, which is likely to lead to an increase in the occurrence of vacant houses. If the problem caused by the occurrence of vacant houses is neglected, it causes not only a physical decline such as a deterioration of the residential environment but also a social and economic decline. In order to solve this problem, it is necessary to grasp the spatial distribution characteristics of vacant houses at the local level considering the existence of regional characteristics and spatial influence. Therefore, in this study, in order to measure global spatial autocorrelation, the analysis was conducted centering on the old downtown area of Busan, where there are many vacant houses through Moran's I and Geographically Weighted Regression(GWR). In addition, the distribution of vacant houses in different spatial units in Eup_Myeon_Dong and Census was analyzed to evaluate the possibility of Modifiable Areal Unit Problem(MAUP), which differ in the results of spatial analysis as the spatial analysis units change. As a result of the analysis, the occurrence of vacant houses by Eup_Myeon_Dong in the old downtown area of Busan had spatial heterogeneity, and the spatial analysis results of vacant houses were different as the spatial analysis units were different. Accordingly, in order to understand the exact distribution characteristics of vacant house occurrence, spatial dimensions using the GWR model should be considered, and it is suggested that consideration of the MAUP is necessary.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.77-100
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• 2022

In the era of low growth, many provincial cities are experiencing population decline and aging. Population decline phenomena such as reduction of productive manpower, reduction of finances, deterioration of quality of life, and collapse of the community base are occurring in a chain and are being pushed to the brink of extinction of the cities. This study aims to propose a methodology to objectively estimate the employment creation centers and setting the basic unit of industrial-centered zoning by applying spatial statistical techniques and GIS for the application of the compact city plan as an efficient spatial management policy in a city with a declining population. In details, based on reviewing previous studies on compact city, 'employment complex index(ECI)' were defined considering the number of workers, the number of settlers, and the area of development land, the employment creation center was estimated by applying the 'Local Moran's I' and 'Getis-Ord's Hot-Spot Analysis'. As a case study, changes in the four years of 2013, 2015, 2017, and 2019 were compared and analyzed for Changwon City. As a result, it was confirmed that the employment creation center is becoming compacted and polycentric, which is a significant result that reflects the actual situation well. This results provide the basic data for functional and institutional territorial governance for the regional revitalization platform, and provide meaningful information necessary for spatial policy decision-making, such as population reduction, regional gross domestic product, and public facility arrangement that can respond to energy savings, transportation plans, and medical and health plans.

• Korean Journal of Legislative Studies
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• v.26 no.2
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• pp.113-140
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• 2020

This study is meaningful in that it is the first analysis of Korean elections using the concept of spatial autocorrelation. Spatial autocorrelation means that an event occurring in one location in space has a high correlation with an event occurring in the surrounding area. The voter turnout rate in the 21^st general election of Seoul area was divided into the early-voting turnout and voting-day turnout, and the spatial pattern of the turnout was examined. Most of the previous studies were based on the unit of the precinct and personal data, but this study analyzed on the basis of the lower unit, Eup-myeon-dong, and analyzed using spatial data and aggregate data. Moran I index showed a fairly high spatial autocorrelation of 0.261 in the voting-day turnout, while the index of the early-voting turnout was low at 0.095, indicating that there was little spatial autocorrelation despite statistical significance. The voting-day turnout, which showed strong spatial autocorrelation, was compared and analyzed using the OLS regression model and the spatial statistics model. In the general regression model, the coefficient of determination R² rose from 0.585261 to 0.656631 in the spatial error model, showing an increase in explanatory power of about 7 percentage points. This means that the spatial statistical model has high explanatory power. The most interesting result is the relationship between the early-voting turnout and the voting-day turnout. The higher the early-voting turnout is, the lower the voting-day turnout is. When the early-voing turnout increases by about 2%, the voting-day turnout drops by about 1%. In this study, the variables affecting the early-voting turnout and the voting-day turnout are very different. This finding is different from the previous researches.

• Korea Trade Review
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• v.42 no.6
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• pp.111-129
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• 2017

According to the World Bank statistics, China's contribution to global economic growth during the year of 2013-2016 was estimated at 31.6 percent. This figure is even larger than 29.0 percent, the contribution by summing each contribution of the United States, EU and Japan. The Chinese commodity trade accounts for up to 11.5 percent of world trade volume. Thus, we can consider that the Chinese economy has a strong influence on the global economy. The primary purpose of this study is to analyze the contribution level of Chinese seaborne trade volume on world economy. First, this study conducted a time-lag analysis using Moran test, so we can find that China's level of contribution to global economic growth varies from time to time. The contribution of the first phase (1999-2007) was nearly three times higher than the contributions from the second phase (2008-2016), suggesting that the overall contraction of the global trade volume starting from the subprime mortgage crisis in 2008 has continued until recently and recovery has not even occurred. Second, using the econometrics model, this study conducted an regression analysis of the impact of Chinese imports and exports in chemicals, grain, steel, crude oil, and container on global economic growth. Fixed effects model with time series data has been applied to examine the effect of Chinese seaborne trade volume on global economic growth. According to the empirical analysis of this study, China's exports of steel products, exports of container, imports of containers, imports of crude oil and imports of grain have significant contributions to global economic growth. Estimates of China's exports of steel products, exports of container, imports of containers, imports of crude oil and imports of grain are 1.023, 1.020, 1.019, 1.007 and 1.006, respectively. For example, the estimated value 1.023 of China's exports of steel products means that the growth rate can be 1.023 times higher than the current world GDP growth rate if Chinese seaborne trade volume of exports of steel products increased by one unit (one million tons). This study concludes that the expansion of China's imports and exports should be realized first to increase the global GDP growth rate. The expansion of Chinese trade can lead to a simultaneous stimulus of production and consumption in China, which can even lead to global economic growth ultimately. Thus, depending on how much China's trade will be broaden in the future, the width of global economic growth can be determined.