Spatial identification and multilevel zoning of land use functions improve sustainable regional management: a case study of the Yangtze River Economic Belt, China.

Abstract

The quantitative identification and zoning management of land use functions (LUFs) are important starting points for solving the problems of resource allocation and sustainable development. In this study, with the Yangtze River Economic Belt (YREB) as the case study area, LUFs were grouped into three primary categories: economic function (ENF), social function (SCF), and ecological function (ELF). The least square error model was adopted to identify the morphological changes of LUFs. A two-dimensional discriminant matrix of the dynamic degree of LUF change and terrain niche index was constructed to explain the terrain gradient effect of LUFs. Bivariate local spatial autocorrelation was used to analyze the trade-offs in 2018 between ELF and ENF, and ELF and SCF. Finally, a new multilevel zoning scheme for LUFs was proposed. The results showed that from 1990 to 2018, ENF increased rapidly in cities along the Yangtze River, the overall level of SCF declined, and ELF in the south of the Yangtze River was better than that in the north. LUFs' morphological zoning exhibited significant regional differences. SCF-ELF combination areas and ELF dominance areas were mainly optimized in the second-level zoning. The areas with weak ELF were concentrated in the east of the YREB. Based on these results, nine kinds of LUF zonings and six kinds of major functional zonings were devised, and policy allocation was arranged for each zoning to improve the efficiency of spatial zoning management. Our research provides a reference for large-scale regional sustainable development and land use zoning management.