• 제목/요약/키워드: spatial autocorrelation index

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한국어 트위터 감정의 핫스팟 분석 (Hotspot Analysis of Korean Twitter Sentiments)

  • 임좌상;김진만
    • 한국멀티미디어학회논문지
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    • 제18권2호
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    • pp.233-243
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    • 2015
  • A hotspot is a spatial pattern that properties or events of spaces are densely revealed in a particular area. Whereas location information is easily captured with increasing use of mobile devices, so is not our emotion unless asking directly through a survey. Tweet provides a good way of analyzing such spatial sentiment, but relevant research is hard to find. Therefore, we analyzed hotspots of emotion in the twitter using spatial autocorrelation. 10,142 tweets and related GPS data were extracted. Sentiment of tweets was classified into good or bad with a support vector machine algorithm. We used Moran's I and Getis-Ord $G_i^*$ for global and local spatial autocorrelation. Some hotspots were found significant and drawn on Seoul metropolitan area map. These results were found very similar to an earlier conducted official survey of happiness index.

공간자기상관 지수와 Pearson 상관계수를 이용한 마산만 수질의 공간분포 패턴 규명 (Identifying Spatial Distribution Pattern of Water Quality in Masan Bay Using Spatial Autocorrelation Index and Pearson's r)

  • 최현우;박재문;김현욱;김영옥
    • Ocean and Polar Research
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    • 제29권4호
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    • pp.391-400
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    • 2007
  • To identify the spatial distribution pattern of water quality in Masan Bay, Pearson's correlation as a common statistic method and Moran's I as a spatial autocorrelation statistics were applied to the hydrological data seasonally collected from Masan Bay for two years ($2004{\sim}2005$). Spatial distribution of salinity, DO and silicate among the hydrological parameters clustered strongly while chlorophyll a distribution displayed a weak clustering. When the similarity matrix of Moran's I was compared with correlation matrix of Pearson's r, only the relationships of temperature vs. salinity, temperature vs. silicate and silicate vs. total inorganic nitrogen showed significant correlation and similarity of spatial clustered pattern. Considering Pearson's correlation and the spatial autocorrelation results, water quality distribution patterns of Masan Bay were conceptually simplified into four types. Based on the simplified types, Moran's I and Pearson's r were compared respectively with spatial distribution maps on salinity and silicate with a strong clustered pattern, and with chlorophyll a having no clustered pattern. According to these test results, spatial distribution of the water quality in Masan Bay could be summed up in four patterns. This summation should be developed as spatial index to be linked with pollutant and ecological indicators for coastal health assessment.

도시 공간특성과 Walkability Index의 상관성에 관한 공간통계학적 접근 -부산광역시 2개 구를 대상으로- (A Spatial Statistical Approach on the Correlation between Walkability Index and Urban Spatial Characteristics -Case Study on Two Administrative Districts, Busan-)

  • 최돈정;서용철
    • 한국측량학회지
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    • 제32권4_1호
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    • pp.343-351
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    • 2014
  • 본 연구에서는 최근 들어 그 중요성이 부각되고 있는 도시공간의 보행환경 평가와 관련하여 지역의 보행친화도와 물리적 사회경제적 특성과의 상관관계를 공간통계학적 측면에서 분석 하였다. 이를 위해 부산광역시의 2개 구의 보행성 지수(Walkability Index)를 정량적으로 산출하였고 이에 대한 전역적 국지적 공간 자기상관 측정을 수행하였다. 또한 Walkability Index에 대해 도시환경 변수와의 상관성을 파악하기 위해 지리가중 회귀분석(GWR : Geographically Weighted Regression, 이하 GWR)을 수행하였다. 연구결과 연구지역의 Walkability Index에서 통계적으로 유의한 수준의 공간 자기상관 수치와 군집이 도출되었다. 또한 GWR 분석결과 OLS(Ordinary Least Square Regression, 이하OLS) 회귀모형보다 통계적으로 개선된 추론이 가능 하였으며, 보행 환경변수에 대한 국지적 수준의 영향관계를 도출할 수 있었다. 본 연구의 결과들은 지역의 보행환경 평가 및 그와 연관된 환경변수의 탐색 시 공간 통계학적 접근이 효과적일 수 있음을 시사한다.

무주 남대천에 서식하는 조류의 공간적 분포특성 분석을 위한 공간자기상관 적용 연구 (Application of Spatial Autocorrelation for Analysis of Spatial Distribution Characteristics of Birds Observed in Namdaecheon River, Muju-gun, Jeollabuk-do, Korea)

  • 강종현;김용기;연명훈
    • 환경영향평가
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    • 제22권5호
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    • pp.467-479
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    • 2013
  • This study was conducted to find out characterization of spatial distribution of birds observed in river areas. Our bird survey was carried out 4 times at 31 sites from January to September in 2011. A total of 1,609 accumulated individuals belonging to 59 species, 28 families and 11 orders were observed. In the result of spatial autocorrelation analysis using the richness index of the maximum counts of each sites, we confirmed that the distribution of birds in Namdaecheon river was clustered and the tendency of spatial autocorrelation was apparent. The area of each sites within a 200m radius was classified in four biotope categories such as agricultural land, forest, residential area and water area, and the spatial autocorrelation was analysed about four types. In the result of spatial autocorrelation analysis for four biotope categories, all types were showed the positive spatial autocorrelation, but the type of water area was higher than other types. The positive correlation was found between the water area and water birds in statistical significance. However, the forest birds had non-significance values. Therefore, it is appropriate to focus on water birds except for forest birds, when researches of bird distribution in river ecosystem is conducted. The number of bird species and individuals increased as the riverside of water area was to widen. Thus, if the areas of riverside offering the feeding and roosting area increase, it will be accommodated many birds. Also, the areas of riverside should be maintained naturally because it is an important habitats of birds. Our study area is on the outskirts the city of higher rates of forest and agricultural land, it may be unreasonable to apply our results to the whole rivers. If the research about the river flowing around the city will be conducted, it is expected to be useful to the relation study area such as ecological river's restoration.

공간자기상관분석을 통한 시계열적 경관구조의 변화 분석 - 남양주지역을 대상으로 - (A Time-Series Analysis of Landscape Structural Changes using the Spatial Autocorrelation Method - Focusing on Namyangju Area -)

  • 김희주;오규식;이동근
    • 한국환경복원기술학회지
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    • 제14권3호
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    • pp.1-14
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    • 2011
  • In order to determine temporal changes of the urban landscape, interdependence and interaction among geo-spatial objects can be analyzed using GIS analytic methods. In this study, to investigate changes in the landscape structure of the Namyangju area, the size and shape of landscape patches, and the distance between the patches were analyzed with the Spatial Autocorrelation Method. In addition, both global and local spatial autocorrelation analyses were conducted. The results of global Moran's I revealed that both patch size and shape index transformed to a more dispersed pattern over time. Next, the local Moran's I of patch size in all time series determined that almost all patches were of a high-low pattern. Meanwhile, the local Moran's I of the shape index was found to have changed from a high-high pattern to a high-low pattern in time series. Finally, as time passes, the number of hot spot patches about size and shape index had been decreased according to the results of hot spot analysis. These changes appeared around the development projects in the study area. From the results of this study, degradation of landscape patches in Namyangju were ascertained and their specific areas were delineated. Such results can be used as useful data in selecting areas for conservation and for preparing plans and strategies in environmental restoration.

Phytosociological Study and Spatial autocorrelation on the Forest Vegetation of Mt. Yeonae at Gijang-gun

  • Choi, Byoung-Ki;Huh, Man Kyu
    • 한국환경과학회지
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    • 제22권11호
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    • pp.1373-1381
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    • 2013
  • Mt. Yeonae is at Gijang-gun in Busan and is surrounded by farming lands on three sides. The search for the species composition and dynamics of local communities were studied at Mt. Yeonae of how spatial similarity decays with geographic distance. The index values of Z$\ddot{u}$rich-Montpellier School's phytosociology at the 12 plots was compared to a distribution of similarly using 20 m quadrates at 12 sites. The specific communities were five including Pinus densiflora - Quercus variabilis community. Six species were significant similarity between neighboring sites by using the spatial autocorrelation coefficient, Moran's I. If Mt. Yeonae was destroyed by an artificial action, some spatial correlated species such as P. densiflora and Q. variabilis will be collapsed because of no maintaining the effective population sizes.

도심지역의 범죄 종류와 공간적 특성 관계분석 (Analysis of Relation Between Criminal Types and Spatial Characteristics in Urban Areas)

  • 차경현;김경호;손기준;김상지;이동창;김진영
    • 한국위성정보통신학회논문지
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    • 제10권1호
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    • pp.6-11
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    • 2015
  • 본 논문에서는 콜롬비아 경찰청을 통해 수집 된 데이터를 통해 콜롬비아 A 지역에서 발생하는 범죄 현황과 지리적 구조에 따른 공간적 범죄분포 특성을 분석하였다. 범죄 분석을 위해 2013년 1월부터 12월까지 수집 된 범죄 데이터를 이용하여 글로벌 모란지수와 국지적 모란지수를 이용하여 공간적 상관관계 분석을 실시하였다. 공간적 상관관계 분석 결과는 높은 범죄 빈도수를 가지는 범죄 유형들은 모두 상관관계를 가지고 있었다. 또 글로벌 모란지수를 이용하여 범죄 지역의 공간적 상관관계를 하나의 값으로 표현하고, 국지적 모란지수를 통해 핫스팟을 분석하여 Local Indicators of Spatial Association(LISA) 지도를 구현하였다. LISA 지도를 통해 범죄 유형별 공간적 분포를 파악할 수 있었다.

공간적 자기상관을 활용한 지역안전지수의 공간패턴 분석 - 기초지방자치단체를 중심으로 (An Analysis on the Spatial Pattern of Local Safety Level Index Using Spatial Autocorrelation - Focused on Basic Local Governments, Korea)

  • 이미숙;여관현
    • 한국측량학회지
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    • 제39권1호
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    • pp.29-40
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    • 2021
  • 범죄, 화재, 교통사고 등 국민의 안전을 위협하는 위험인자들은 지역적 맥락과 공간적 특성을 가지고 있다. 지역마다 서로 다른 위험환경을 가지고 있으므로 교통사고, 화재, 범죄, 생활안전 분야별로 위험요소의 공간적 패턴을 분석할 필요가 있다. 본 연구는 전국 기초자치단체를 대상으로 분야(교통사고, 화재, 범죄, 생활안전, 자살, 감염병)별 안전등급을 측정한 지표인 지역안전지수의 공간적 분포 패턴을 분석하는데 연구의 목적이 있다. 지역안전지수의 공간적 자기상관성 분석을 위해 전역적 공간자기상관분석(Global Moran's I)과 Local Moran's I를 활용한 LISA(Local Indicators of Spatial Association) 분석, Getis-Ord's G⁎i 분석을 실시하였다. 분석결과 교통사고, 화재, 자살의 안전지수 분포는 범죄, 생활안전, 감염병의 안전지수보다 공간적으로 집중(clustered) 경향을 보였다. 지역간 유의미한 공간적 연관성을 분석한 LISA 분석결과에 따르면, 수도권 지역이 다른 도시에 비하여 지역안전통합지수를 기준으로 비교적 안전한 지역인 것으로 나타났다. 또한 Getis-Ord's G⁎i 통계값을 활용한 핫스팟분석 결과 안전 취약지역의 군집인 3개의 핫스팟(강원도 삼척시, 경상북도 청송군, 전라북도 김제시)과 전반적인 안전 수준이 높은 군집인 15개의 콜드스팟이 도출되었다. 이러한 연구 결과는 안전 수준 취약지역의 공간적 분포와 패턴을 파악하여 안전 지수 개선을 위한 정책 수립시 기초자료로 활용될 수 있다.

공간자기상관 산출을 위한 인접성 정의 방법 비교 (A Comparison of Neighborhood Definition Methods for Spatial Autocorrelation)

  • 박재문;황도현;윤홍주
    • 수산해양교육연구
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    • 제23권3호
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    • pp.477-485
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    • 2011
  • For the identifying of spatial distribution pattern, Moran's Index(I) which has the range of values from -1 to +1 is common method for the spatial autocorrelation measurement. When I is close to 1, all neighboring features have close to the same value, indicating clustered pattern. Conversely, if the spatial pattern is dispersed, I is close to -1. And I closing to 0 means spatially random pattern. However, this index equation is influenced by how defining the neighboring features for target feature. To compare and understand the difference of neighborhood definition methods, fixed distance neighboring method and Gabriel Network method were used for I. In this study, these two methods were applied to two marine environments with water quality data. One is Gwangyang Bay which has complex geometric coastal structure located in South Sea of Korea. Another is Uljin area adjacent to open sea located in east coast of Korea. The distances between water quality observed locations were relatively regular in Gwangyang Bay, however, irregular in Uljin area. And for the fixed distance method popular Arc GIS tool was used, but, for the Gabriel Network, Visual Basic program was developed to produce Gabriel Network and calculate Moran's I and its Z-score automatically. According to this experimental results, different spatial pattern was showed differently for some data with using of neighboring definition methods. Therefore there is need to choose neighboring definition method carefully for spatial pattern analysis.