Literature DB >> 33804475

Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region-A Case Study of 17 Cities in Hubei Province, China.

Shukui Tan1, Maomao Zhang1, Ao Wang2, Qianlin Ni1.   

Abstract

With the rapid development of the social economy, factors of social and economic development in China's rural areas have been continuously reorganized, and the pattern and distribution of rural residential areas have undergone significant changes. In rural areas, there have been many peculiar phenomena of "reducing people but not reducing land in rural areas, which has caused tremendous pressure on land resource protection. We used geographic detectors and a geographically temporally weighted regression model (GTWR) to explore the rural settlements' evolution and driving mechanism in Hubei Province from 1990 to 2015. The results show that the kernel density of rural settlements decreased from 1.62 villages/km2 in 1990 to 1.60 villages/km2 in 2015. The scale of rural residential patches has obvious regional differentiation characteristics. From southeast to northwest, there is a wave-like distribution structure of "high-low-high-low-high", and the clustering characteristics of "cold and hot spots" are strengthened with time. Based on GTWR analysis, the total rural population, total power of agricultural machinery, and rural electricity consumption have promoted the expansion of rural settlements, with the regression coefficients 0.096, 0.484, and 0.878, respectively. Cultivated land, agricultural output value, and rural labor force have negative impacts on the expansion, the regression coefficients of the village were -0.584, -0.510, and -0.109, respectively.

Entities:  

Keywords:  Hubei Province; driving forces; geographic detectors; geographically temporally weighted regression model (GTWR); rural settlements; spatio-temporal evolution

Year:  2021        PMID: 33804475      PMCID: PMC7967727          DOI: 10.3390/ijerph18052387

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   3.390


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