Spatial–Temporal Pattern and Convergence Characteristics of Provincial Urban Land Use Efficiency under Environmental Constraints in China

Abstract

Revealing the spatial–temporal pattern and convergence characteristics of urban land use efficiency has important guiding significance for adjusting and optimizing the regional urban land use structure. Taking the provincial units in China as the research object, the urban land use efficiency evaluation system considering the unexpected output was constructed, and the slack-based measure (SBA) model was used to quantitatively measure the provincial urban land use efficiency from 2000 to 2020. The exploratory spatial data analysis (ESDA) model and spatial convergence index were combined to reveal the spatial–temporal pattern and convergence characteristics of provincial urban land use efficiency. The results showed that the provincial urban land use efficiency has been continuously improving, with regional differences as shown in eastern region > northeast region > central region > western region. Moran’s I of provincial urban land use efficiency was greater than 0, there was a positive spatial correlation, and the clustering feature became increasingly significant. The spatial form of LISA was characterized by “small agglomeration and large dispersion”; the H(High)-H(High) type was clustered in the Yangtze River Delta and Beijing–Tianjin–Hebei, while the L(Low)-L(Low) type was clustered in Xizang, Xinjiang and Qinghai. There was a σ convergence in provincial urban land use efficiency, and there was significant absolute β convergence and conditional β convergence of provincial urban land use efficiency. The results showed that the differences in provincial urban land use efficiency were shrinking, showing a “catch-up effect”, and converging to their respective stable states over time. Based on the analysis of the spatial–temporal pattern and convergence characteristics of provincial urban land use efficiency in China, we could provide a direction for the optimization of the urban land use structure and efficiency improvement in China, in order to narrow the differences in urban land use efficiency in China’s four major regions.

The coupling coordination between health service supply and regional economy in China: spatio-temporal evolution and convergence

“…This could be attributed to Jiangxi’s regional economy lagging behind neighboring provinces like Jiangsu and Zhejiang, resulting in a greater siphoning effect ( 88 ). Additionally, Jiangxi’s weak economic linkages with adjacent provinces ( 68 ) mean the siphoning effect outweighs the spillover effect, leading to MHSS and its regional economy trailing behind its neighbors. Anhui Province, on the other hand, due to its active integration into the Yangtze River Delta region, has fully embraced the transfer of industries in the YRD region and the diffusion effect of technology expansion in the field of health, realizing the simultaneous enhancement of the economy and the supply of health services.…”

“…It is also used to measure if there is spatial aggregation between variables ( 66 , 67 ). This paper employs the global Moran index and local Moran index to assess spatial correlation and agglomeration, respectively ( 68 ).…”

Influence Mechanism of Polycentric Spatial Structure on Urban Land Use Efficiency: A Moderated Mediation Model

“…In general, the literature in this area consists mainly of the following: (1) The changes of ULUE. Scholars have systematically studied the spatial and temporal characteristics [ 23 ], regional differences [ 24 ] and convergence characteristics [ 25 ] of ULUE on a multi-scale. The object of study included different types of land, such as urban agricultural land [ 26 ], forests [ 27 ] and arable land [ 28 ].…”

Spatiotemporal differences, dynamic evolution and trend of cultivated land use efficiency: Based on three food functional areas

“…By reviewing existing literature, it becomes evident that various scholars have investigated the spatiotemporal evolution characteristics and distributional variances of CLUE from a multidimensional research perspective. A literature survey highlights the analyses conducted by different scholars on the distribution differences in CLUE [ 4 , 5 ] and their exploration of the spatiotemporal evolution of CLUE from a multidimensional standpoint [ 6 , 7 ]. By analyzing the distributional characteristics at the provincial level, the researchers identified clear spatial disparities among Chinese provinces [ [8] , [9] , [10] ].…”