• Journal of Forest and Environmental Science
• /
• v.33 no.3
• /
• pp.161-171
• /
• 2017

Global environmental changes have the capacity to make dramatic alterations to floral and faunal composition, and elucidation of the mechanism is important for predicting its outcomes. Studies on global climate change have traditionally focused on statistical summaries within relatively wide scales of spatial and temporal changes, and less attention has been paid to variability in microclimates across spatial and temporal scales. Microclimate is a suite of climatic conditions measured in local areas near the earth's surface. Environmental variables in microclimatic scale can be critical for the ecology of organisms inhabiting there. Here we examine the effect of spatial and temporal changes in microclimates on those of carabid beetle communities in Hyangnobong, Korea. We found that climatic variables and the patterns of annual changes in carabid beetle communities differed among sites even within the single mountain system. Our results indicate the importance of temporal survey of communities at local scales, which is expected to reveal an additional fraction of variation in communities and underlying processes that has been overlooked in studies of global community patterns and changes.

• Geomechanics and Engineering
• /
• v.24 no.2
• /
• pp.167-178
• /
• 2021

Spatial variability is an inherent uncertainty of soil properties. Current reliability analyses generally incorporate random field theory and Monte Carlo simulation (MCS) when dealing with spatial variability, in which the computational efficiency is a significant challenge. This paper proposes a KL-FORM algorithm to improve the computational efficiency. In the proposed KL-FORM, Karhunen-Loeve (KL) expansion is used for discretizing random fields, and first-order reliability method (FORM) is employed for reliability analysis. The KL expansion and FORM can be used in conjunction, through adopting independent standard normal variables in the discretization of KL expansion as the basic variables in the FORM. To illustrate the effectiveness of this KL-FORM, it is applied to a case study of a strip footing in spatially variable unsaturated soil under rainfall, in which the bearing capacity of the footing is computed by numerical simulation. This case study shows that the KL-FORM is accurate and efficient. The parametric analyses suggest that ignoring the spatial variability of the soil may lead to an underestimation of the reliability index of the footing.

• The Korean Journal of Applied Statistics
• /
• v.29 no.5
• /
• pp.873-885
• /
• 2016

Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.2
• /
• pp.35-45
• /
• 2012

Existing studies on land values tend to show the use of simple euclidean distances as the accessibility variable and OLS as the analysis method. However, applying such euclidean distance-based accessibility to dense CBD areas has limitations in the incorporating the characteristics of network structure whereas using OLS, the typical method for non-spatial data, tends to exclude spatial effects of spatial data. In this study, we analyzed land values focusing on the revised accessibility variables and the analytical technique that can include spatial effects. First, we adopted space syntax theory in order to consider not simple shortest distances along the streets but distances based on street network structure. Second, we compared OLS with GWR that includes spatial effects. Third, we used different size grid-cells for the spatial units considering MAUP theory and applied them to Gangnam-gu area. Each cell was analyzed for overall influence of independent variables using OLS, and coefficients were presented by GWR which enables local analysis and visualization. As a result, we found that suggested accessibility variables have a meaningful effects for land value analyses, and we were able to verify that GWR produces improved results compared to OLS. Also, we observed that the resulting values vary depending on the sizes of spatial units.

• Korean Journal of Remote Sensing
• /
• v.32 no.3
• /
• pp.331-337
• /
• 2016

Water vapor is main absorption factor of outgoing longwave radiation. So, it is essential to monitoring the changes in the amount of water vapor and to understanding the causes of such changes. In this study, we monitor temporal variability of Total Precipitable Water (TPW) which observed by satellite. Among climate variables, precipitation play an important part to analyze temporal variability of water vapor because it is produced by water vapor. And El $Ni{\tilde{n}}o$ is one of climate variables which appear regularly in comparison with the others. Through them, we analyze relationship between temporal variability of TPW and climate variable. In this study, we analyzed long-term change of TPW from Moderate-Resolution Imaging Spectroadiometer (MODIS) data and change of precipitation in middle area of Korea peninsula quantitatively. After these analysis, we compared relation of TPW and precipitation with El $Ni{\tilde{n}}o$. The aim of study is to research El $Ni{\tilde{n}}o$ has an impact on TPW and precipitation change in middle area of Korea peninsula. First of all, we calculated TPW and precipitation from time series analysis quantitatively, and anomaly analysis is performed to analyze their correlation. As a result, TPW and precipitation has correlation mostly but the part had inverse correlation was found. This was compared with El $Ni{\tilde{n}}o$ of anomaly results. As a result, TPW and precipitation had inverse correlation after El $Ni{\tilde{n}}o$ occurred. It was found that El $Ni{\tilde{n}}o$ have a decisive effect on change of TPW and precipitation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.4
• /
• pp.295-304
• /
• 2020

The IPCC (Intergovernmental Panel on Climate Change) recommended the importance of preventive measures against extreme weather, and heat waves are one of the main themes for establishing preventive measures. In this study, we tried to analyze the heat vulnerable areas by considering not only spatial characteristics but also social characteristics. Energy consumption, popu lation density, normalized difference vegetation index, waterfront distance, solar radiation, and road distribution were examined as variables. Then, by selecting a suitable model, SLM (Spatial Lag Model), available variables were extracted. Then, based on the Fuzzy theory, the degree of vulnerability to heat waves was analyzed for each variable, and six variables were superimposed to finally derive the heat vulnerable area. The study site was selected as the Daegu area where the effects of the heat wave were high. In the case of vulnerable areas, it was confirmed that the existing urban areas are mainly distributed in Seogu, Namgu, and Dalseogu of Daegu, which are less affected by waterside and vegetation. It was confirmed that both spatial and social characteristics should be considered in policy support for reducing heat waves in Daegu.

• Journal of Korean Society for Geospatial Information Science
• /
• v.24 no.2
• /
• pp.63-70
• /
• 2016

A housing market in an urban area is not just a single market but a combination of regionally different submarkets. This study begins with a critical mind that previous researches did not consider the spatial autocorrelation of each area where the housings are located. The clustering analysis of housing submarket which considers spatial autocorrelation is performed as it follows. First, 4 housing market attribute variables are reducted to 1 variable by principle component analysis. Then, after calculating $Gi^*max$ by AMOEBA, 7 housing submarkets which have similar characteristics based on $Gi^*max$ are classified. The characteristics of each submarket are investigated, then political implication is deduced as the following. Different level of housing policy should be made to each cluster because each cluster has different level of spatial autocorrelation.

• International Journal of Advanced Culture Technology
• /
• v.9 no.2
• /
• pp.32-38
• /
• 2021

The purpose of this study is to examine the spatial characteristics of violent and burglary crimes in South Korea. Violent crimes and burglary crimes depend on a spatial setting with good conditions for their criminal purposes. This study defines population density, racial heterogeneity, types of houses, and density of commercial facilities as variables of place affecting crime in cities and counties. The study collects data from 229 cities in Korea to analyze the effect of spatial characteristics on crime. We conduct additional analyses to meet the statistical requisites of the spatial econometrics model using the open-source software R and GeoDa 1.12.1.129. From the analytical result, population density, racial heterogeneity, apartments, and commercial areas relate to crime occurrence. We suggest the implication of the theoretical and practical contributions to the relationship between place and crime.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.1
• /
• pp.31-39
• /
• 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 Korean Society for Geospatial Information Science
• /
• v.18 no.2
• /
• pp.69-78
• /
• 2010

The hydrological-geomorphic character is closely related with runoff in basin. A development of GIS greatly helps investigating about mechanism between theirs. We analyze local slope and hillslope length which are related with hydrological response. But variation of these geomorphic variables has very wide range at each pixel. So there's a limit as to use directly. Therefore we investigate a relation between hydrological response and distributed geomorphic variables according to statistical character of distributed map considering spatial correlation. As a result, the local slope affects peak discharge, and the hillslope length affects peak discharge and time, mean and variance of hydrological response. Henceforth these hydrological-geomorphic analyze methods can be improved that hydrology response is directly analogized with DEM data.