AUTHOR=Yuan Chenzhao , Dong Guanglong , Liu Zheng 

TITLE=Investigating spatially varying relationships between the distribution of rural settlements and related influences

JOURNAL=Frontiers in Sustainable Food Systems

VOLUME=Volume 8 - 2024

YEAR=2025

URL=https://www.frontiersin.org/journals/sustainable-food-systems/articles/10.3389/fsufs.2024.1519194

DOI=10.3389/fsufs.2024.1519194

ISSN=2571-581X

ABSTRACT=The distribution of rural settlement is the comprehensive results of human adapting to the natural condition and socioeconomic development in the long history. Scientifically revealing the spatially varying relationships between the distribution of rural settlement and related factors is the fundament for planning and management. In this study, with north China plain as the study area, we analyze the spatially varying relationship between the distribution of rural settlement and related factors using both traditional statistic model and geographic weighted regression model. Results reveal that both the number and the area of rural settlement at county level are increasing from north to south and from west to east. The results of traditional regression model suggest that total area, total population, road density, precipitation, road length, slope, longitude and temperature are the significant influences of the rural settlement area, while those of the number of rural settlements is longitude, latitude, road length, road density, river length, and river density. Besides, the regression coefficients are constant in the global model, while both the magnitude and the sign of the corresponding parameters in local model are spatially varying. However, the value of the coefficients in global model fall into the range of the coefficients in local model and most coefficients in local model share the same sign with that in global model. Our results also reveal that the local model outperform the global model with the same explanatory variables, indicating by the smaller AIC and the 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 is detected.