Optimization of production-living-ecological space based on Markov-FLUS-MCR model in Jinzhong, Shanxi of China

Abstract: An accurate and rapid optimization of "production-living-ecological" space has been one of the most important steps to implement territorial spatial planning at all levels, particularly for the better rational development and protection of land. Taking the Jinzhong City, Shanxi Province of China as the research object, the status quo of "production-living-ecological" space was first identified to establish the Markov-FLUS model. The number and distribution of "production-living-ecological" space were also predicted for the study area in 2025. Then, seven resistance factors were selected to evaluate the suitability of land development using the MCR model, in order to determine the threshold and zoning. Among them, the towns and residential areas were taken as the source of construction expansion, and the most important area for ecological protection was the ecological source. At last, the prediction and evaluation of development suitability were spatially superimposed to optimize the "production-living-ecological" space, according to the compound partitions. Subsequently, specific control measures were proposed for each partition. The research showed that: 1) The accuracy of the Markov-FLUS model was 97.17%, compared with the actual data. Thus, the model was very feasible to simulate the spatial changes of "production-living-ecological" in the study area in 2018. There was also an increasing trend for the production and living space in the study area in 2025. Specifically, the production space increased significantly, with an increase of 813.53 km2, whereas, the ecological space decreased by 892.65 km2. 2) The land space was divided into five types of zones: ecological protection, ecological optimization, restricted development, optimized development, and suitable development, from the perspective of development suitability using the MCR model. The ecological optimization zone presented the largest area of 4 994 km2, accounting for 30.59% of the total. Meanwhile, the suitable development zone behaved the smallest area of 1 546 km2. 3) Seven types of space after optimization were then divided: production, ecological, living, production-living, production-ecological, living-ecological, and production-living-ecological space. The spatial distribution was characterized by "the overall agglomeration, the local scattered", of which the ecological space area was the largest proportion, accounting for 41.20%. As such, a recommendation was proposed for the management and control strategies, according to the different space uses. Consequently, the Markov-FLUS-MCR coupling model can balance the Markov-FLUS and MCR models at the same time, indicating the demand quantity and the spatial changes of "production-living-ecological" space with high precision. Land spatial suitability can also be evaluated using an ecological process. The ecological security was integrated during optimization to fully consider the evolution process of the quantity scale and spatial distribution of the "production-living-ecological" space over time. The finding can greatly contribute to promoting the "production-living-ecological" space optimization, particularly for the scientific guidance to the rational development and protection of land space in Jinzhong City, Shanxi Province, China.