Qualitative-quantitative identification and functional zoning analysis of production-living-ecological space: a case study of Urban Agglomeration in Central Yunnan, China

Territorial space exhibits multiple functional attributes, which comprise production, living, and ecological functions usually. Optimizing the production-living-ecological space (PLES) has become the key to territorial and spatial planning; the scientific identification of the PLES lays a foundation for space optimization and has important guiding significance in territorial spatial zoning. To achieve the integration of macro-scale and micro-scale PLES, with the Urban Agglomeration in Central Yunnan as the research area in this study, the PLES functional identification systems from the administrative unit scale and the grid scale are constructed. The types of PLES are determined by integrating qualitative and quantitative evaluation results and using an improved primacy index model from a composite spatial perspective. On that basis, the division of comprehensive zoning is achieved for land use functions through kernel density analysis. As indicated by the results, the model is capable of reflecting the macro background of the PLES functions in administrative regions while characterizing the micro differences at the grid level in administrative units. There are significant differences in the production, living, and ecological functional spaces in the Urban Agglomeration. Production functions are concentrated in the central and northeastern, living functions are concentrated in the central, and ecological functions are concentrated in the western and northeastern, with significantly consistent or complementary spatial distributions of each other. The PLES of Urban Agglomeration includes production space (PS), ecological space (ES), production-living space (P-LS), production-ecological space (P-ES), living-ecological space (L-ES), and production-living-ecological space (P-L-ES), placing a focus on ES, P-ES, and P-L-ES, which marks significant differences in spatial distribution among different spatial types. The study area is divided into 24 functional zones, which are classified into 6 categories, and optimization paths are proposed. This study will provide a reference for territorial and spatial planning in spatial functional zoning, spatial pattern optimization, and land management applications.