Study on spatial tropism distribution of rural settlements in the Loess Hilly and Gully Region based on natural factors and traffic accessibility.
The keys to realizing spatial restructuring in rural areas are the optimization of the spatial pattern of rural settlements and the integration of rural resources. Based on a 2015 Google Earth remote sensing image, this study employed kernel density estimation (KDE), the minimum cumulative resistanc...
| Publicado en: | Journal of Rural Studies Vol. 93; pp. 441 - 449 |
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| Autores principales: | , , , , |
| Formato: | Resumen |
| Publicado: |
Elsevier B.V.
Jul2022
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=157389320&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 157389320 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07430167 JL8 jtl: Journal of Rural Studies issn: 07430167 maglogo: N pubinfo: dt: Jul2022 vid: 93 pid: 2410 pub: Elsevier B.V. artinfo: ui: 157389320 10.1016/j.jrurstud.2019.02.014 ppf: 441 ppct: 8 formats: tig: atl: Study on spatial tropism distribution of rural settlements in the Loess Hilly and Gully Region based on natural factors and traffic accessibility. aug: au: Chen, Zongfeng Liu, Yansui Feng, Weilun Li, Yurui Li, Linna affil: Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, 100101, China su: China Probability density function Industrial clusters Industrial districts Tropisms Loess Logistic regression analysis sug: subj: China Probability density function Industrial clusters Industrial districts Tropisms Loess Logistic regression analysis keyword: Ecological security Rural China Rural settlements Spatial distribution characteristics Traffic accessibility Ecological security Rural China Rural settlements Spatial distribution characteristics Traffic accessibility ab: The keys to realizing spatial restructuring in rural areas are the optimization of the spatial pattern of rural settlements and the integration of rural resources. Based on a 2015 Google Earth remote sensing image, this study employed kernel density estimation (KDE), the minimum cumulative resistance (MCR) method, and a logistic regression model to apply quantitative analysis to the spatial distribution characteristics and influencing factors of a rural area. The results revealed that the density of rural settlements is significantly spatially different in Baota District; the density core area in the district was located in the valley area with industrial agglomeration. Rural settlements in Baota District were located near the county seat and township seat, near a river, farmland and county-level road, on sunny slopes. Traffic accessibility to the townships had a greater impact on the spatial distribution of rural settlements than the traffic accessibility to the county. Thus, county-level road development plays a more important role in the optimization of town-village systems. Hence, we suggest constructing a complete transportation network system in the optimization of the town-village spatial pattern in the county, thereby improving the central service functions of towns to strengthen the spatial connection between townships and the central agglomeration effects of towns. • Rural settlement density is significantly spatially different in Baota District. • The minimum cumulative resistance model was used to refine the study of rural settlements' spatial tropism distribution. • Logistic regression model effectively identify the driving forces of rural settlement distribution. • Strengthening township and transportation construction is conducive to rural development. pubtype: Academic Journal doctype: Abstract src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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