Investigating spatially varying relationships between the distribution of rural settlements and related influences
The distribution of rural settlements is a complex outcome of human adaptation to natural conditions and socioeconomic development throughout history. Scientifically revealing the spatially varying relationships between the distribution of rural settlements and the related factors is fundamental for...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Sustainable Food Systems |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fsufs.2024.1519194/full |
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| author | Chenzhao Yuan Guanglong Dong Zheng Liu |
| author_facet | Chenzhao Yuan Guanglong Dong Zheng Liu |
| author_sort | Chenzhao Yuan |
| collection | DOAJ |
| description | The distribution of rural settlements is a complex outcome of human adaptation to natural conditions and socioeconomic development throughout history. Scientifically revealing the spatially varying relationships between the distribution of rural settlements and the related factors is fundamental for effective planning and management. In this study, we focus on the North China Plain to analyze the spatially varying relationships between the distribution of rural settlements and the related factors using both traditional statistical and geographically weighted regression models. Our findings reveal that both the number and the area of rural settlements at the county level are increasing from north to south and from west to east. The results of the traditional regression model suggest that total area, total population, road density, precipitation, road length, slope, longitude, and temperature significantly influence the rural settlement area, while those influencing the number of rural settlements are longitude, latitude, road length, road density, river length, and river density. Moreover, the regression coefficients are constant in the global model, while both the magnitude and the sign of the corresponding parameters in the local model are spatially varying. However, the value of the coefficients in the global model are within the range of the coefficients in the local model and most coefficients in the local model share the same sign with that the global model. Our results also reveal that the local model outperforms the global model with the same explanatory variables, indicating a smaller Akaike’s information criterion (AIC) and a reduced Moran’s I in model residual. Finally, this study also highlights the importance of the cautious and scientific interpretation of the varying relationships, especially when the unexpected results are obtained. |
| format | Article |
| id | doaj-art-5cd7ea6ba0a645079069c3fc9b037db0 |
| institution | Kabale University |
| issn | 2571-581X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Sustainable Food Systems |
| spelling | doaj-art-5cd7ea6ba0a645079069c3fc9b037db02025-01-03T04:13:34ZengFrontiers Media S.A.Frontiers in Sustainable Food Systems2571-581X2025-01-01810.3389/fsufs.2024.15191941519194Investigating spatially varying relationships between the distribution of rural settlements and related influencesChenzhao Yuan0Guanglong Dong1Zheng Liu2Faculty of Arts, The University of Melbourne, Melbourne, VIC, AustraliaSchool of Management Engineering, Shandong Jianzhu University, Jinan, ChinaShandong Institute of Territorial and Spatial Planning, Jinan, ChinaThe distribution of rural settlements is a complex outcome of human adaptation to natural conditions and socioeconomic development throughout history. Scientifically revealing the spatially varying relationships between the distribution of rural settlements and the related factors is fundamental for effective planning and management. In this study, we focus on the North China Plain to analyze the spatially varying relationships between the distribution of rural settlements and the related factors using both traditional statistical and geographically weighted regression models. Our findings reveal that both the number and the area of rural settlements at the county level are increasing from north to south and from west to east. The results of the traditional regression model suggest that total area, total population, road density, precipitation, road length, slope, longitude, and temperature significantly influence the rural settlement area, while those influencing the number of rural settlements are longitude, latitude, road length, road density, river length, and river density. Moreover, the regression coefficients are constant in the global model, while both the magnitude and the sign of the corresponding parameters in the local model are spatially varying. However, the value of the coefficients in the global model are within the range of the coefficients in the local model and most coefficients in the local model share the same sign with that the global model. Our results also reveal that the local model outperforms the global model with the same explanatory variables, indicating a smaller Akaike’s information criterion (AIC) and a reduced Moran’s I in model residual. Finally, this study also highlights the importance of the cautious and scientific interpretation of the varying relationships, especially when the unexpected results are obtained.https://www.frontiersin.org/articles/10.3389/fsufs.2024.1519194/fullrural settlementsspatial distributiongeographically weighted regressiongeographically weighted Poisson regressionNorth China plain |
| spellingShingle | Chenzhao Yuan Guanglong Dong Zheng Liu Investigating spatially varying relationships between the distribution of rural settlements and related influences Frontiers in Sustainable Food Systems rural settlements spatial distribution geographically weighted regression geographically weighted Poisson regression North China plain |
| title | Investigating spatially varying relationships between the distribution of rural settlements and related influences |
| title_full | Investigating spatially varying relationships between the distribution of rural settlements and related influences |
| title_fullStr | Investigating spatially varying relationships between the distribution of rural settlements and related influences |
| title_full_unstemmed | Investigating spatially varying relationships between the distribution of rural settlements and related influences |
| title_short | Investigating spatially varying relationships between the distribution of rural settlements and related influences |
| title_sort | investigating spatially varying relationships between the distribution of rural settlements and related influences |
| topic | rural settlements spatial distribution geographically weighted regression geographically weighted Poisson regression North China plain |
| url | https://www.frontiersin.org/articles/10.3389/fsufs.2024.1519194/full |
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