The Spatial Effect of Administrative Division on Land-Use Intensity

Abstract

Land-use intensity (LUI) is one of the most direct manifestations of regional land use efficiency. The study of cross-administrative LUI in urban agglomerations is of great importance for the sustainable development of land, new urbanization, and territorial spatial planning. In this study, the urban agglomeration in the middle reaches of the Yangtze River in China was used as the case study area to explore the spatial spillover effect through the administrative division, underlying driving mechanism, and spatial interactions or constraints of LUI. First, LUI was measured using the index of the proportion of construction land to the total area of the administrative region. Second, the adjacency relationship of the county-level administrative units was identified on the basis of the queen-type adjacency criterion under the county-level administrative division system. Thereafter, spatial weight matrix for spatial modeling was constructed. Last, a spatial model using the “Spatial adjacency matrix” was devised to examine the influencing factors and the potential spatial interactions or constraints of administrative units. Results revealed that the level of LUI of different county-level administrative units were quite different, and the gap of LUI among county-level administrative units widened from 2010 to 2017. The fixed asset investment per land (FAIL), gross domestic product per capital (PGDP), and proportion of tertiary sector (PTS) are the driving factors of LUI. County-level administrative units not only had a significant and increasing spatial interaction effect based on the relationship of cooperation, but also had an influence of restraint mutually which was caused by the competition. The direct spatial spillover effect was remarkable. In the future, the effect of interaction among administrative units under the administrative division should be considered to promote the reasonable use and optimal layout of regional urban land to realize the optimal allocation of land resources.