Spatio-temporal evolution and spatial spillover effects of urban land use efficiency in Yangtze River Economic Belt

Authors: Cong Xia*, China University of Geosciences, Shougeng Hu, China University of Geosciences, Si Wu, China University of Geosciences, De Yu, China University of Geosciences
Topics: Land Use, Economic Geography, Urban Geography
Keywords: Urban land use efficiency, Yangtze River Economic Belt, Spatio-temporal evolution, Spatial spillover effects
Session Type: Paper
Day: 4/9/2020
Start / End Time: 3:20 PM / 4:35 PM
Room: Agate C, Hyatt Regency, Third Floor
Presentation File: No File Uploaded

Urban land use efficiency (ULUE) is a vital indicator to measure the level of land resource management and the quality of regional development. As the demonstration area with the leading role of high-quality development in China, Yangtze River Economic Belt faces enormous challenge to promote the economic transition from extensive growth to extensive growth. One of the pivotal measures is to control urban sprawl and improve ULUE. This study calculates ULUE of 127 cities in Yangtze River Economic Belt from 2007-2016 used Super-SBM-Undesirable-Window model, and attempts to demonstrate the spatio-temporal evolution and spatial spillover effects. We established an indicator system of “input-output-undesirable output” to estimate ULUE considering the demand for urban development. The Theil index, Kernel Density Estimation, and Moran' I index were applied to describe the evolution of regional differences and spatial pattern of ULUE. Moreover, the spatial spillover effects discussed based on the Spatial Markov Chain method. The results shows that ULUE of Yangtze River Economic belt has steadily increased from 0.49 in 2007 to 0.70 in 2016, and shows a pattern of rising ladder growth. The overall difference among cities had shown a shrinking trend during the decades, while the gap among the three reaches decreased first, and then had increased after 2012. Spatially, ULUE increased from the lower reaches to middle reaches, and further to the upper reaches during 2007-2012, totally opposite to that of 2012-2016. There is an evident concentration of cities with high-level and low-level ULUE, indicating a significant influence of regional correlation.

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