Literature DB >> 34283882

Spatiotemporal pattern and coordination relationship between urban residential land price and land use intensity in 31 provinces and cities in China.

Xingran Cai1,2, Yanqing Liang3,4,5, Zhiying Huang6, Jingfeng Ge3,5.   

Abstract

The trend towards efficient and intensive use of land resources is an inevitable outcome of current social development. The rational matching of urban land prices and land use intensity has become an important factor under accelerating urbanization, and promotes the healthy development of the social economy. Using data on residential land price and on land use intensity for 31 provinces and cities in China, we employ the E-G cointegration test and quadrant map classification to determine the coordination relationship between land price and land use intensity. We then employ HR coordination to calculate the coordination degree of land price and land use intensity, and classify the coordination type accordingly. Our results are as follows. (1) The spatio-temporal distribution of urban land price shows high variability with multiple maxima, and follows a decreasing trend from the southeast coastal area to the northwest inland area and the northeast. (2) The overall land use intensity is at or above the middle level, and shows large spatial differences between provinces, but the agglomeration between provinces is increasing. (3) From the perspective of the relationship between urban land price and land use intensity at the inter-provincial scale, we find that the land price and land use intensity are well coordinated, and the number of provinces has been dynamically changing during different development periods. There is an east-west difference in the spatial distribution of land price and land use intensity coordination level. Different provinces and cities with the same coordination stage show differences in their land price and land use intensity level.

Entities:  

Year:  2021        PMID: 34283882     DOI: 10.1371/journal.pone.0254846

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  3 in total

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Authors:  Liang Zhou; Xuewei Dang; Haowei Mu; Bo Wang; Shaohua Wang
Journal:  Sci Total Environ       Date:  2021-02-14       Impact factor: 7.963

2.  Spatial influence of ecological networks on land use intensity.

Authors:  Jing Yang; Chen Zeng; YiJiao Cheng
Journal:  Sci Total Environ       Date:  2020-02-05       Impact factor: 7.963

3.  Study on the relationship between PM2.5 concentration and intensive land use in Hebei Province based on a spatial regression model.

Authors:  Jingjing Shao; Jingfeng Ge; Xiaomiao Feng; Chaoran Zhao
Journal:  PLoS One       Date:  2020-09-18       Impact factor: 3.240

  3 in total

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