• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.155-166
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• 2008

The quantitative bivariate spatial pattern analysis was applied for the water quality and nutrients data of Masan Bay, and for this analysis Pearson's r as aspatial correlation measurement, Moran's I as spatial association measurement and L index as integration of aspatial and spatial measurement methods were used. To understand the aspatial and spatial characteristics implicated in L index, Pearson's r as well as Moran's I were classified into 3 types respectively, and Pearson's r and Moran's I were combined with 9 types, and also quantile of L index value was used for each of those 9 types. Finally, these types were defined as 5 groups having not overlapped L index range. According to the application result of L index groups, bivariate water quality and nutrients showed no aspatial correlation regardless of spatial association in February and July, but they showed aspatial correlation having clustered spatial pattern in May and November. The result of this study providing the guideline for the interpretation of aspatial correlation and spatial association using L index is expected to be helpful for the marine environment pattern analysis using quantitative index for further study.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.5
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• pp.25-34
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• 2021

Increase in avian species richness is one of the important issues of urban biodiversity policies, since it can promote diverse ecosystem services such as seed dispersal, education, and pollination. However, though human disturbance can significantly affect avian species richness, there are limited studies on the way to reflect the dynamics of floating population. Therefore, this study analyzed the spatial relationship between avian species richness, floating population, and vegetation cover using telecommunications information to identify the areas that requiring targeted monitoring and restoration action. Bivariate Local Moran's I was applied to identify LISA cluster map that showing representative biotopes, which reflect significant spatial relationship between species richness and population distribution. Edge density and distribution of ndvi were identified for evaluating relative adequacy of selected biotopes to strengthen the robust biodiversity network. This study offers insight to consider human disturbance in spatial context using innovative big data to increase the effectiveness of urban biodiversity measures.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1153-1166
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• 2020

The purpose of this study was to analyze the spatial correlation between the heat distribution map of the satellite imaging base and the factors that deepen the heat wave, and to explore the heat concentration area and the space where the risk of future heat wave may increase. The global Moran's I of population, land use, and buildings, which are the causes of heat concentration and heat wave deepening, is found to be high and concentrated in specific spaces. According to the analysis results of local Moran's I, heat concentration areas appeared mainly in large cities such as metropolitan and metropolitan areas, and forests were dominant in areas with relatively low temperatures. Areas with high population growth rates were distributed in the surrounding areas of Gyeonggi-do, Daejeon, and Busan, and the use of land and buildings were concentrated in the metropolitan area and large cities. Analysis by Bivarate Local Moran's I has shown that population growth is high in heat-intensive areas, and that artificial and urban building environments and land use take place. The results of this research can lead to the ranking of heat concentration areas and explore areas with environments where heat concentration is concentrated nationwide and deepens it, so ultimately it is considered to contribute to the establishment of preemptive measures to deal with extreme heat.