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Comparative Changes of Influence Factors of Rural Residential Area Based on Spatial Econometric Regression Model: A Case Study of Lishan Township, Hubei Province, China

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  • Xuesong Zhang

    (The College of Urban & Environmental Sciences, Central China Normal University, Wuhan 430079, China
    Key Laboratory of Hubei Province, Analysis and Simulation of Geographic Process, Central China Normal University, Wuhan 430079, China
    These authors contributed equally to this work.)

  • Ju He

    (The College of Urban & Environmental Sciences, Central China Normal University, Wuhan 430079, China
    Key Laboratory of Hubei Province, Analysis and Simulation of Geographic Process, Central China Normal University, Wuhan 430079, China
    These authors contributed equally to this work.)

  • Zhen Deng

    (The College of Urban & Environmental Sciences, Central China Normal University, Wuhan 430079, China
    Key Laboratory of Hubei Province, Analysis and Simulation of Geographic Process, Central China Normal University, Wuhan 430079, China)

  • Jiyue Ma

    (The College of Foreign Languages, Zhongnan University of Economics and Law, Wuhan 430073, China)

  • Guangping Chen

    (The College of Urban & Environmental Sciences, Central China Normal University, Wuhan 430079, China
    Key Laboratory of Hubei Province, Analysis and Simulation of Geographic Process, Central China Normal University, Wuhan 430079, China)

  • Maomao Zhang

    (The College of Urban & Environmental Sciences, Central China Normal University, Wuhan 430079, China
    Key Laboratory of Hubei Province, Analysis and Simulation of Geographic Process, Central China Normal University, Wuhan 430079, China)

  • Deshou Li

    (The College of Urban & Environmental Sciences, Central China Normal University, Wuhan 430079, China
    Key Laboratory of Hubei Province, Analysis and Simulation of Geographic Process, Central China Normal University, Wuhan 430079, China)

Abstract

The influencing factors of rural residential areas have always been a key research direction in addressing rural problems in China. By introducing a spatial regression model combined with Kernel Density Estimation and Buffer Analysis, this study made a comparative study on the quantification of the influencing factors of rural residential areas in 2009, 2012, and 2015 in Lishan Township, Hubei Province, China. The results showed that the elevation and slope of Lishan Township have always played a decisive role in the distribution of rural residential areas, that the influence of the water system is abnormal, and that the influence of roads and townships has been strengthened based on the spatial statistical analysis. Then, based on spatial econometric regression analysis, the coefficients of “Topographic indices” (CTI) were 0.666, 0.719, and 0.439 in 2009, 2012, and 2015, respectively. The coefficients of Road (CR) were 0.170, 0.112, and 0.108, respectively. The coefficients of Town (CT) were 0.120, 0.127, and 0.166, respectively. The coefficients of Water system (CWS) were 0.166, 0.124, and 0.173, respectively. With the change of time, the influence of road decreased and the influence of town increased gradually. Furthermore, the influence of the water system and topography showed volatility.

Suggested Citation

  • Xuesong Zhang & Ju He & Zhen Deng & Jiyue Ma & Guangping Chen & Maomao Zhang & Deshou Li, 2018. "Comparative Changes of Influence Factors of Rural Residential Area Based on Spatial Econometric Regression Model: A Case Study of Lishan Township, Hubei Province, China," Sustainability, MDPI, vol. 10(10), pages 1-14, September.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3403-:d:171787
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    References listed on IDEAS

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    1. Barry, Ronald P. & McIntyre, Julie, 2011. "Estimating animal densities and home range in regions with irregular boundaries and holes: A lattice-based alternative to the kernel density estimator," Ecological Modelling, Elsevier, vol. 222(10), pages 1666-1672.
    2. Shan, Zhengying & Feng, Changchun, 2018. "The Redundancy of Residential Land in Rural China: The evolution process, current status and policy implications," Land Use Policy, Elsevier, vol. 74(C), pages 179-186.
    3. Tian, Wei & Song, Jitian & Li, Zhanyong, 2014. "Spatial regression analysis of domestic energy in urban areas," Energy, Elsevier, vol. 76(C), pages 629-640.
    4. Ma, Wenqiu & Jiang, Guanghui & Zhang, Ruijuan & Li, Yuling & Jiang, Xiaoguang, 2018. "Achieving rural spatial restructuring in China: A suitable framework to understand how structural transitions in rural residential land differ across peri-urban interface?," Land Use Policy, Elsevier, vol. 75(C), pages 583-593.
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    Cited by:

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    5. Qindong Fan & Fengtian Du & Hu Li, 2020. "A Study of the Spatial Form of Maling Village, Henan, China," Sustainability, MDPI, vol. 12(18), pages 1-24, September.
    6. Jingyu Liu & Qiong Song & Xiaomin Wang, 2023. "Spatial Morphology Evolution of Rural Settlements in the Lower Yellow River Plain: The Case of Menggang Town in Changyuan City, China," Land, MDPI, vol. 12(6), pages 1-19, May.
    7. Xiaowei Yao & Di Wu, 2023. "Spatiotemporal Changes and Influencing Factors of Rural Settlements in the Middle Reaches of the Yangtze River Region, 1990–2020," Land, MDPI, vol. 12(9), pages 1-23, September.
    8. Xuesong Zhang & Maomao Zhang & Ju He & Quanxi Wang & Deshou Li, 2019. "The Spatial-Temporal Characteristics of Cultivated Land and Its Influential Factors in The Low Hilly Region: A Case Study of Lishan Town, Hubei Province, China," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    9. Marta Sylla & Tadeusz Lasota & Szymon Szewrański, 2019. "Valuing Environmental Amenities in Peri-Urban Areas: Evidence from Poland," Sustainability, MDPI, vol. 11(3), pages 1-15, January.

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