• 자원ㆍ환경경제연구
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• 제23권4호
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• pp.553-581
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• 2014

This paper analyzes competition among service stations in the Korean gasoline market. We consider spatial differentiation as a source of product differentiation as well as the characteristics of the stations and vertical contracts between refiners and retailers as factors causing changes in equilibrium prices in the Korean gasoline retail market. The effect of the government's price disclosure policy on the retail market competition is also analyzed. Moran's I test indicates that the prices of neighboring gas stations are spatially correlated in the market. It is also found that gasoline prices for vertically integrated stations are much lower than those for independent stations. In addition, unbranded stations charge lower prices than branded stations but also induce branded stations to price more competitively. Meanwhile, the government's price disclosure policy did intensify price competition in the retail gasoline market. It is inferred that the price disclosure policy contributed to retailers gaining more bargain power in price negotiation with refiners, causing an eventual increase in retail prices.

• 한국측량학회지
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• 제33권6호
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• pp.579-587
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• 2015

Landslides are major natural geological hazards that result in a large amount of property damage each year, with both direct and indirect costs. Many researchers have produced landslide susceptibility maps using various techniques over the last few decades. This paper presents the landslide susceptibility results from the geographically weighted regression model using remote sensing and geographic information system data for landslide susceptibility in the Inje area of South Korea. Landslide locations were identified from aerial photographs. The eleven landslide-related factors were calculated and extracted from the spatial database and used to analyze landslide susceptibility. Compared with the global logistic regression model, the Akaike Information Criteria was improved by 109.12, the adjusted R-squared was improved from 0.165 to 0.304, and the Moran’s I index of this analysis was improved from 0.4258 to 0.0553. The comparisons of susceptibility obtained from the models show that geographically weighted regression has higher predictive performance.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.835-844
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• 2003

A difficulty in spatial data analysis is to choose a suitable theoretical variogram. Generally mean squares error(MSE) is used as a criterion of selection. However researchers encounter the case that the values of MSE are almost the same whereas the estimates of parameters are different. In this case, the selection criterion based on MSE should take into account the parameter estimates. In this paper we study on the method of selecting a variogram using spatial correlation.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.637-645
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• 2003

Small area estimation had been studied using data-based methods such as Direct, Indirect, Synthetic methods. However recently, model-based such as based on regression or time series estimation methods are applied to the study. In this paper we investigate a model-data based small area estimation which takes into account the spatial relation among the areas. The Economic Active Population Survey in 2001 are used for analysis and the results from the model based and model-data based estimation are compared with using MSE(Mean squared error), MAE(Mean absolute error) and MB(Mean bias).

• The Korean Journal of Ecology
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• 제22권6호
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• pp.349-354
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• 1999

The spatial distributions of allelic frequencies and ecological traits by randomization were studied in the natural population of two species (Pinus rigida and Pyrola japonica). Both species showed significant positive spatial autocorrelation as measured by Moran's I. In P. rigida, the genetic similarity was shown in individuals within up to a scale of 18 m distance and this is partly due to combination of pollen and seed dispersal by wind or men. In P. japonica, significant spatial autocorrelation was consisted of a scale of 8 m intervals. These population structure in the distribution of allelic frequencies is related to mating systems such as outcrossing and vegetative spread. The results also indicate that positive species associations between P. rigida and P. japonica can occur when both species select the same habitat or require the same environmental conditions.

• Journal of Ecology and Environment
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• 제37권2호
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• pp.53-60
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• 2014

The arctic tundra is an important ecosystem in terms of the organic carbon cycle and climate change, and therefore, detailed analysis of vegetation distribution patterns is required to determine their association. We used grid-sampling method and applied geostatistics to analyze spatial variability and patterns of vegetation within a two-dimensional space, and calculated the Moran's I statistics and semivariance to assess the spatial autocorrelation of vegetation. Spatially autocorrelated vegetation consisted of moss, Eriophorum vaginatum, Betula nana, and Rubus chamaemorus. Interpolation maps and cross-correlograms revealed spatial specificity of Carex aquatilis and a strong negative spatial correlation between E. vaginatum and C. aquatilis. These results suggest differences between the species in water requirements for survival in the arctic tundra. Geostatistical methods could offer valuable information for identifying the vegetation spatial distribution.

• 한국측량학회지
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• 제32권6호
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• pp.571-580
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• 2014

To address unsolved issues of change detection in animated choropleth maps, we proposed the concept of 'gross change detection' and performed an experiment that empirically verifies the incidence of change blindness stems from the 'magnitude of change (MOC)', spatial distribution in animated choropleth maps. We generated experimental materials using the change-characterization arrays and the global Moran's I. Participants had 108 cases of changing maps with time duration (1 to 3 sec) and had questions. The results showed that MOC and duration affect gross change detection, but the most interesting result from our experiment was that different spatial distributions between two adjacent choropleth maps may lead the map reader to under- or over-estimate the level of gross change in the map. It implies that we should consider spatial distribution of change when we design animated choropleth maps.

• 한국기후변화학회지
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• 제7권1호
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• pp.69-75
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• 2016

Recently, many countries all over the world have been suffered from disaster caused by climate change. Especially in case of developed countries, the disaster is concentrated in the industry sector. In this research, we analyzed industrial vulnerable homogeneous hotspot for the climate change using spatial autocorrelation analysis on the south Korea. Homogeneous hot spot areas through autocorrelation analysis indicate the spatial pattern of areas interacted each other. Industry sector have responsibility of green house gas emissions, and should adapt to the climate change caused by greenhouse gas already released. So, we integrated the areas sensitive to mitigation option with the areas hardly adapt to climate change because of vulnerable infrastructure. We expected that the result of this research could contribute to the decision-making system of climate change polices.

• 한국지리정보학회지
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• 제15권4호
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• pp.162-174
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• 2012

공간적으로 3차원의 특성을 지닌 해양에서 수직적인 수온 자료의 특성을 가시화하기 위해서는 각 수심층별 수평 수온분포도와 같은 2차원적 주제도나 3차원적 공간보간을 통한 입체 모델을 사용하게 된다. 이러한 방법은 해양 현상을 시각적으로 이해하는데 유용하지만, 수직적 수온분포의 공간 패턴 분석이나 수직적 수온의 특성과 다른 해양 요인(해양화학, 해양생물, 기후변화 등)과의 관계분석에는 한계가 있다. 따라서 본 연구는 수온 수직구조의 주요 파라미터인 혼합층의 깊이, 최대수온구배, 수온약층의 두께를 추출하는 알고리즘을 이용하여, 수온의 수직구조 특성을 정량화함으로써 제주남부 해역의 수온 수직구조의 공간분포 특성을 밝히고자 한다. 이를 위해 수온 수직구조를 대표하는 세 가지 파라미터에 대한 공간분포지도 제작을 비롯해 공간자기상관 지수(Moran's I)를 계산하였다. 아울러, 세 가지 파라미터에 대한 군집분석을 수행하여 제주 남부해역을 4개 지역으로 그룹핑하고, 각 지역에 대한 수직 수온구조의 특성을 정의하였다.

• 한국조경학회지
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• 제48권5호
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• pp.67-79
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• 2020

도시열섬 완화를 위한 계획을 세울 때 가장 먼저 해결해야 할 문제는 도시 내 어느 곳이 열 환경에 가장 취약한 곳인지를 파악하는 것이다. 즉, 도시 내 온도가 상대적으로 더 높은 지역과 낮은 지역(핫스팟과 콜드스팟)이 존재하는지 여부를 파악해야 한다. 본 연구는 전주시를 공간적 범위로 도시열섬의 공간적 밀집지역을 도출하고, 밀집요인을 알아보는데 목적이 있다. 먼저 도시열섬이 밀집해서 발생하는 지역을 알아보기 위해 2017년 Landsat 8 위성영상을 활용해 지표면온도(Land Surface Temperature : LST)를 추출한 뒤 국지적 Moran's I 분석과 Getis-Ord Gi^* 분석을 통해 핫스팟 분석을 실시하였다. 그 결과, 통계적으로 유의한 밀집지역은 전주시 원도심이라 불리는 중심부와 공업지역으로 나타났다. 또한 높은 LST를 유발하는 요인을 알아보고자 토지피복도 중 시가화·건조지역의 상세분류로 상관분석과 회귀분석을 진행한 결과, 주거지역의 단독주거시설, 공업지역의 공업시설, 상업지역의 상업·업무시설이 LST를 높이는 요인으로, 별도의 항목이 존재하지 않는 녹지율을 대신해 변수로 선정한 NDVI가 LST를 낮추는 요인으로 작용하고 있었다. 본 연구의 결과는 도시열섬 저감 정책이 어느 곳을 중심으로 이루어져야 하는지, 가장 먼저 고려해야 할 요인은 무엇인지를 판단하고자 할 때 근거가 된다는 점에서 의의를 찾을 수 있다.