• Title/Summary/Keyword: MGWR

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Environmental Equity Analysis of Fine Dust in Daegu Using MGWR and KT Sensor Data (다중 스케일 지리가중회귀 모형과 KT 측정기 자료를 활용한 대구시 미세먼지에 대한 환경적 형평성 분석)

  • Euna CHO;Byong-Woon JUN
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.4
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    • pp.218-236
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    • 2023
  • This study attempted to analyze the environmental equity of fine dust(PM10) in Daegu using MGWR(Multi-scale Geographically Weighted Regression) and KT(Korea Telecom Corporation) sensor data. Existing national monitoring network data for measuring fine dust are collected at a small number of ground-based stations that are sparsely distributed in a large area. To complement these drawbacks, KT sensor data with a large number of IoT(Internet of Things) stations densely distributed were used in this study. The MGWR model was used to deal with spatial heterogeneity and multi-scale contextual effects in the spatial relationships between fine dust concentration and socioeconomic variables. Results indicate that there existed an environmental inequity by land value and foreigner ratio in the spatial distribution of fine dust in Daegu metropolitan city. Also, the MGWR model showed better the explanatory power than Ordinary Least Square(OLS) and Geographically Weighted Regression(GWR) models in explaining the spatial relationships between the concentration of fine dust and socioeconomic variables. This study demonstrated the potential of KT sensor data as a supplement to the existing national monitoring network data for measuring fine dust.

Exploring Spatial Variations and Factors associated with Walking Practice in Korea: An Empirical Study based on Geographically Weighted Regression (지리적 가중회귀모형을 이용한 지역별 걷기실천율의 지역적 변이 및 영향요인 탐색)

  • Kim, Eunjoo;Lee, Yeongseo;Yoon, Ju Young
    • Journal of Korean Academy of Nursing
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    • v.53 no.4
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    • pp.426-438
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    • 2023
  • Purpose: Walking practice is a representative indicator of the level of physical activity of local residents. Although the world health organization addressed reduction in prevalence of insufficient physical activity as a global target, the rate of walking practice in Korea has not improved and there are large regional disparities. Therefore, this study aimed to explore the spatial variations of walking practice and its associated factors in Korea. Methods: A secondary analysis was conducted using Community Health Outcome and Health Determinants Database 1.3 from Korea Centers for Disease Control and Prevention. A total of 229 districts was included in the analysis. We compared the ordinary least squares (OLS) and the geographically weighted regression (GWR) to explore the associated factors of walking practice. MGWR 2.2.1 software was used to explore the spatial distribution of walking practice and modeling the GWR. Results: Walking practice had spatial variations across the country. The results showed that the GWR model had better accommodation of spatial autocorrelation than the OLS model. The GWR results indicated that different predictors of walking practice across regions of Korea. Conclusion: The findings of this study may provide insight to nursing researchers, health professionals, and policy makers in planning health programs to promote walking practices in their respective communities.