• 생명과학회지
• /
• 제22권11호
• /
• pp.1435-1443
• /
• 2012

거제도 안골 골짜기와 뱃골 골짜기에서 식물 군락의 변화를 조사하였다. 알파-다양도와 감마-다양도는 서식지 단절의 크기와 정도에 따라 감소하였다. 우세종의 평균 종수도 서식지 단절에 따라 감소하였다. 상수리나무를 비롯한 참나무과 종들은 붉은토끼풀 같은 도입된 귀화식물의 증가에 따라 주요도가 감소하였다. 교란이 일어나지 않은 숲에서 성체 생존율의 몫이 증가함에 따라 탄력 예상치의 절대적 비는 2003년부터 2011년까지 증가하였다. 그러나 교란 집단에서는 비가 낮았다. Moran의 I값은 전반적으로 서식지 단절지역과 서식지전환 시기에서는 감소하였다. 결국 거제도에서 도시화에 따른 식물 군락은 환경이 교란되었을 때 보편종의 감소를 유발하였다.

• Journal of Korea Trade
• /
• 제26권1호
• /
• pp.99-112
• /
• 2022

Purpose - This paper empirically investigates via a spatial lag model from the perspective of space economy to find the influencing factors of South Korea's OFDI along with 60 countries. Design/methodology - In the study of regional economic phenomena, we must first test the corresponding spatial correlation, and on this basis, complete the construction of the spatial model. For the target research object, after testing the spatial correlation, if there is spatial correlation, a spatial measurement model is needed. This paper uses the global Moran's I index for calculation. Based on the characteristics and research needs of the research object, this paper selects the spatial lag model to verify the existence of the spatial effect and factors affecting OFDI. Findings - Our results show that export scale, infrastructure, technology level, political stability, resource endowment, market size, distance and labor cost have a certain impact on Korea's OFDI, but at present the distance and market size factors are the most important influencing factors for South Korea's OFDI, The technical level and political stability have little effect on South Korea's OFDI, and are not main factors determining South Korea's OFDI. Originality/value - Through spatial measurement verification, it was found that the spatial effect has a significant impact on OFDI, along with more than 60 countries. On this basis, relevant suggestions are put forward, which have strong practical significance for South Korea's OFDI to achieve healthy and sustainable development.

• 한국GIS학회:학술대회논문집
• /
• 한국GIS학회 2010년도 추계학술대회
• /
• pp.68-71
• /
• 2010

본 논문에서는 서울대도시권의 1990년 이후 공간구조 변화에 대하여 도시 간 공간적 연관성에 초점을 맞추어 분석하였다. 서울대도시권을 포함하고 있는 서울시와 인천 및 경기도 도시들 간의 1990년에서 2005년에 이르는 15년의 통근 통학자 자료를 바탕으로 통근 통학비율과 Moran's I를 통하여 서울대도시권 내 도시들의 공간적 연관성을 분석한 결과, 서울대도시권 내에서 서울시의 인구는 경기지역으로 분산되고 있으며 외곽지역으로 이동하는 경향을 보이고 있다. 이는 서울대도시권의 교외화 확산이 심화되고 있다는 것을 의미하며, 또한 인접지역 간 매우 강한 공간적 연관성을 보임이 확인되었다. 분석 결과는 서울대도시권 관리와 정책수립을 뒷받침하는 기초자료로 활용될 수 있을 것이다.

• 한국측량학회지
• /
• 제33권6호
• /
• pp.579-587
• /
• 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
• /
• 제10권3호
• /
• pp.637-645
• /
• 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
• /
• 제22권6호
• /
• pp.349-354
• /
• 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
• /
• 제37권2호
• /
• pp.53-60
• /
• 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
• /
• 제32권6호
• /
• pp.571-580
• /
• 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.

• 한국조경학회지
• /
• 제48권5호
• /
• pp.67-79
• /
• 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.

• The Journal of Asian Finance, Economics and Business
• /
• 제9권2호
• /
• pp.419-426
• /
• 2022

The digital economy is becoming an increasingly important source of regional competitiveness enhancement. The purpose of this research is to examine the spatial distribution characteristics of China's digital economy from 2016 to 2019. Moran's I analysis was performed to see if China's digital economy has spatial self-correlation. The Getis-Ord General G test was used to determine the clustering type of China's digital economy. In addition, we used OLS and GWR methodologies to figure out what drives China's digital economy level. The findings show that the digital economy is rapidly expanding throughout China; yet, there is a significant regional imbalance in the digital economy level in China, and the agglomeration of the digital economy is increasing over time. Furthermore, the findings reveal that human capital, information staff, telegram income, and Internet access are vital factors in the development of the digital economy. To close the digital economy gap, policymakers must invest in human capital and technology innovation. Simultaneously, the government must speed up the development and implementation of electronic information services.