Abstract
The spatio-temporal evolution and influencing mechanism of land ecological efficiency (abbrev. eco-efficiency) are key to achieving optimal land eco-efficiency and ensuring high-quality economic growth. Therefore, based on 287 cities at prefecture-level and above in China, we constructed an efficiency measurement index system by using resource-capital-labor as the input index, economic-resource-social-ecological benefits as the desirable output and carbon emissions as the undesirable output. Besides, Jenks method, Exploratory Spatial Data Analysis (abbrev. ESDA), Trend Analysis and Standard Deviation Elliptic (abbrev. SDE) model were conducted to delve into the spatio-temporal pattern and influencing factors of land eco-efficiency from 2005 to 2019. The results are as follows: (1) under carbon emission constraints, the average values of land eco-efficiency index were showing a rising trend at first and a falling trend thereafter. Spatially, the difference went from large to small in the western, eastern, northeast and central China. (2) The high-efficiency areas were concentrated around Chongqing and gradually extended. The general-efficiency areas were mainly distributed in the Pearl River Delta and urban agglomerations around the middle reaches of the Yangtze River. The low-efficiency areas were widely distributed in the central China. In the trend analysis, the spatial gradient pattern gradually evolved from “flat” to “high in the west, low in the east” in the east-west direction, and from “flat” to a gentle “U-shape” pattern in the north-south direction. (3) The spatial autocorrelation changed from negative to positive and the spatial agglomeration gradually changed to a positive correlation. The main significant correlation types were between High-High (abbrev. HH) areas and Low-Low (abbrev. LL) areas. (4) The standard deviation ellipse of land eco-efficiency always showed the trend of “northeast-southwest”, and the center of gravity moved significantly along Xiangyang-Nanyang-Luohe-Nanyang. In the future, it will continue to integrate the analysis of the relationship between factor input-output, carbon emissions and ecol-efficiency from different perspectives, with a view to providing support for achieving high-quality regional development.
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