Social Sensing for Urban Land Use Identification

Exploring the Temporal and Spatial Evolution Laws of County Green Land-Use Efficiency: Evidence from 11 Counties in Sichuan Province

With rapid urbanisation in China, sustainable urban development faces a major obstacle due to insufficient consideration of land-use efficiency. Currently, despite progress in analysing land-use efficiency, not every land manager has enough knowledge of green land use from a county perspective. Therefore, the objective of this research is to explore the spatiotemporal evolution law focused on county green land-use efficiency (CGLUE), which can support sustainable county development. Based on 10 specific CGLUE factors identified through a content-mining tool, this study explored the temporal and spatial evolution law of 11 counties in Sichuan Province using the ultra-efficient slacks-based measure (SBM), kernel density estimation, and Moran’s I statistic. The study found that (1) CGLUE factors cover the administrative area, total investment in fixed assets by region, the number of employed persons in secondary and tertiary industries, gross domestic product in secondary and tertiary industries, the average wage of staff and workers, basic statistics on per capita park green area, carbon emissions of land, the volume of industrial wastewater discharged, the volume of industrial sulphur dioxide emission, and the volume of industrial soot (dust) emission; (2) from a time-evolution perspective, CGLUE shows an increasing trend of time series evolution as a whole, and its dynamic evolution process has obvious differences in time. CGLUE increased, and the difference in CGLUE became larger from 2010 to 2012. CGLUE also increased, and the difference in CGLUE became smaller from 2013 to 2016. CGLUE also increased, and the difference in CGLUE became larger from 2017 to 2020; (3) from a spatial evolution perspective, the global spatial evolution laws of CGLUE show that the spatial agglomeration state has gone from strong to weak. Overall, however, Sichuan Province CGLUE maintains a high spatial agglomeration effect. The local spatial evolution laws show that the CGLUE of the 11 counties is positively correlated. The high–low CGLUE agglomeration areas are mainly distributed in Chengdu, Mianyang, Meishan and Yibin; the low–low CGLUE agglomeration areas are mainly distributed in Deyang, Yaan, and Zigong. The novelty of the research lies in these aspects: (1) the carbon emissions of land should be considered the undesired output of CGLUE; (2) CGLUE in Sichuan Province has various growing stages from a time perspective; (3) CGLUE in Sichuan Province has a high spatial concentration in Chengdu from spatial view, and these counties’ resources flow and interact at high speed. These findings offer a solid reference for the sustainable development of these 11 counties in Sichuan Province.