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- W2086088802 abstract "본 연구는 동북아시아 지역의 이산화탄소 분포와 식생지수의 상관성 규명을 목적으로 한다. 이를 위해 지리가중치 분석기법을 활용하여 GOSAT 이산화탄소 측정자료와 MODIS 식생지수에 대해 다중공간회귀 분석을 시행하였다. 그 결과 이산화탄소와 식생지수 사이에는 전체적인 (-)의 상관관계가 나타나고 있음을 확인할 수 있었다. 공간적 자기상관성 측정을 위한 Global Morans'I지수와 Anselin Local Morans'I 통계 분석 결과에서는 이산화탄소는 일정한 군집성을 보이며 분포하고 있는 것으로 나타나났다. 이러한 결과는 산림파괴와 같은 개발 활동이 이산화탄소의 배출에 영향을 미쳐 일정한 군집을 형성하게 된 것으로 추정된다. 그러나 이산화탄소의 분포는 인위적 배출원과 식생의 호흡, 해양의 배출과 흡수 등의 다양한 요인과 결부되어 달라지기 때문에 이산화탄소 분포에 개입되는 다양한 변수와 상관성을 평가하는 후속연구가 필요할 것으로 사료된다. The purpose of this work is to investigate correlation between <TEX>$CO_2$</TEX> concentration and NDVI (Normalized Difference Vegetation Index) in North East Asia. Geographically weighted regression techniques were used to evaluate the spatial relationships between GOSAT (Greenhouse Observing SATellite) <TEX>$CO_2$</TEX> measurement and MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation index. The results reveals that <TEX>$CO_2$</TEX> concentration to be negatively associated with NDVI. The analysis of Global Morans' I index and Anselin Local Morasn's I showed spatial autocorrelation between the overall spatial pattern of <TEX>$CO_2$</TEX> and NDVI. Ultimately, there were clustered patterns in both data sets. The results show that carbon dioxide concentration shows non-random distribution patterns in relation to NDVI clusters, which proves that intense development activities such as deforestation are influencing carbon dioxide emission across the area of analysis. However, as the concentration of carbon dioxide varies depending on a variety of factors such as artificial sources, plant respiration, and the absorption and discharge of the ocean, follow-up studies are required to evaluate the correlations among more related variables." @default.
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- W2086088802 date "2013-10-31" @default.
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- W2086088802 title "Evaluating Cross-correlation of GOSAT CO2Concentration with MODIS NDVI Patterns in North-East Asia" @default.
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- W2086088802 doi "https://doi.org/10.12672/ksis.2013.21.5.015" @default.
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