Urban-rural income change: Influences of landscape pattern and administrative spatial spillover effect
Urban-rural income change: Influences of landscape pattern and administrative spatial spillover effect
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城乡收入变化：景观格局与行政空间溢出效应的影响
DOI：
10.1016/j.apgeog.2018.06.003
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发表时间：
2018
影响因子：
4.9
通讯作者：
Liu Y
中科院分区：
文献类型：
--
作者：
Zeng C;Song Y;He QS;Liu Y
中国正在经历前所未有的城市化进程，城乡民生正在发生各种变化，城乡收入是一个代表性方面。在此背景下，我们提出了与研究城乡收入变化及其影响因素相关的两个问题，即景观格局是否影响城乡收入以及不同的空间相邻性是否对城乡收入产生不同的影响。本文以武汉城市圈为例，将景观格局指标和行政空间溢出效应纳入空间回归模型，以解决这些问题。我们使用聚集指数（AI）和其他建设用地的比例（CLP）来表示景观格局。然后，通过引入空间放大因子，采用多种策略来适应不同的县域空间毗邻状况，以强化具体的空间互动情景。结果表明，AI和CLP与城镇居民人均可支配收入（UDI）呈显著正相关，但CLP对农村居民人均纯收入（RNI）的影响大于AI。2005-2015年期间，城乡收入存在时空差异，并观察到行政空间溢出效应。2005年和2015年，当城区与UDI相邻时，以及县级市、郊区和县与RNI相邻时，出现了最强大的空间互动。随着城市化和城乡一体化的发展，行政溢出效应对UDI的影响减弱，而对RNI的影响则各不相同。这些结果再次证实了城市化和经济发展对城乡收入的影响，并在未来制定相应的政策含义时考虑地区差异。
China is experiencing unprecedented urbanisation, and urban–rural livelihood is transforming in various ways, with urban–rural income being a representative aspect. In this context, we raised two issues that are related to our study on the changes in urban and rural income and the related influencing factors, that is, whether landscape pattern affects urban–rural income and whether different spatial adjacencies generate various impacts on urban–rural income. We incorporated landscape pattern indicators and the administrative spatial spillover effect into a spatial regression model to address these issues using the Wuhan agglomeration as an example. We used aggregation indexes (AI) and the proportion of other construction lands (CLP) to represent landscape patterns. Then, multiple strategies were used to accommodate different spatial adjacency situations at the county level by introducing the magnified spatial factor for strengthening specific scenarios of spatial interactions. Results revealed that AI and CLP showed a remarkable relationship with per capita urban disposable income (UDI), but CLP was more powerful than AI in affecting per capita rural net income (RNI). Spatiotemporal differences were observed in urban–rural incomes, and an administrative spatial spillover effect was observed in the period of 2005–2015. The most powerful spatial interaction emerged when urban districts were neighbours for UDI and when a county-level city, a suburban district and a county were neighbours for RNI in 2005 and 2015. Coupled with urbanisation and urban–rural integration, the administrative spillover effect weakened for UDI and functioned varyingly for RNI. These results reaffirmed the influence of urbanisation and economic development on urban–rural income, and regional disparity is expected be considered when corresponding policy implications are made in the future.