The spatial layout of the “Production–Living–Ecological” (PLE) function and the spatial optimization of the “Urban–Agricultural–Ecological” (UAE) pattern are the key points and difficulties in territorial space planning. This paper analyzes their spatial concepts and holds that PLE space is a functional space, while UAE space belongs to a regional space. The optimization of the UAE pattern should be guided by the improvement of the PLE function. Therefore, taking Hefei City, China, as an example, this paper analyzes the evolution of the present UAE pattern, evaluates the PLE function under carbon constraint and then determines the improvement direction of the PLE function and finally simulates the future UAE pattern of territory space. The conclusions are as follows: ① From 2011 to 2019, the urban space increased incrementally, while the agricultural space and ecological space decreased continuously, and the urban space expansion squeezed the agricultural and ecological spaces greatly; ② The PLE functions of four districts in the main city are higher than that of five other counties. After the carbon constraint conditions are included, the PLE functions of the main city were reduced due to the relatively strong capacity of carbon source, while the counties’ increased due to a stronger carbon sink capacity; ③ According to the normalized revealed comparative advantage (NRCA) index, it was determined that the functional improvement direction of each district and county are Yaohai District and Shushan District have comprehensive function as a priority, Luyang District and Baohe District give priority to living–ecological function, Changfeng County, Feidong County, Feixi County and Chaohu County give priority to production–ecological function, and Lujiang County gives priority to ecological function; ④ The simulation results show that 2025 is an important node for the evolution of the UAE pattern. The urban spatial expansion during the “14th Five-Year Plan” period will still bring great pressure on agriculture and ecological spaces, and then, the UAE pattern will continue to be optimized and balanced.

Optimization of the territorial spatial patterns can promote the functional balance and utilization efficiency of space, which is influenced by economic, social, ecological, and environmental factors. Consequently, the final implementation of spatial planning should address the issue of sustainable optimization of territorial spatial patterns, driven by multiple objectives. It has two components—the territorial spatial scale prediction and its layout simulation. Because a one-sided study of scale or layout is divisive, it is necessary to combine the two to form complete territorial spatial patterns. This paper took Hefei city as an example and optimized its territorial spatial scale using the multiple objective programming (MOP) model, with four objective functions. A computer simulation of the territorial spatial layout was created, using the patch-generating land use simulation (PLUS) model, with spatial driving factors, conversion rules, and the scale optimization result. To do this, statistical, empirical, land utilization, and spatially driven data were used. The function results showed that carbon accumulation and economic and ecological benefits would be ever-increasing, and carbon emissions would reach their peak in 2030. The year 2030 was a vital node for the two most important land use types in the spatial scale—construction land and farmland. It was projected that construction land would commence its transition from reduced to negative growth after that time, and farmland would start to rebound. The simulation results indicated that construction land in the main urban area would expand primarily to the west, with supplemental expansion to the east and north. In contrast, construction land in the counties would experience a nominal increase, and a future ecological corridor would develop along the route south of Chaohu County–Chaohu Waters–Lujiang County–south of Feixi County.

The comparative advantage of land use efficiency can provide effective support for upgrading the industrial structure and optimizing the allocation of land resources. According to the agricultural industry and non-agricultural industry, the evaluation index system of land use efficiency is constructed by difference. By using China’s provincial panel data in 2010, 2015 and 2019 as an empirical test and comprehensively employing the comparative advantage model, GIS spatial analysis model, geographical weighted regression model and other algorithms, the land use efficiency and the comparative advantage were measured and evaluated to explore the evolution of spatial and temporal patterns and identify the influencing factors. The results showed the following: (1) The overall efficiency of agricultural land grew steadily, with regional differences transforming from expanding to narrowing, forming a gradually decreasing overall trend from the southeast coast to the northwest inland, and from the eastern plain to the western plateau. The overall efficiency of non-agricultural land was generally low, presenting an overall growth trend, and regional differences were progressively expanding, still showing a gradually decreasing trend in the eastern, central and western regions. (2) The overall comparative advantage of agricultural land efficiency showed a gradual decline trend, and the differences between regions were further narrowed. The high-value regions were still concentrated in the regions with superior agricultural resource endowment and showed a dominant advantage of the agricultural industry. The overall comparative advantage of non-agricultural land efficiency showed an increasing trend. The high-value areas were concentrated in urban agglomeration, metropolitan areas and other areas with high non-agricultural land efficiency, as well as the vast remote areas such as the northwest and southwest where the agricultural land efficiency was extremely low and the comparative advantage of non-agricultural land efficiency improved. (3) The spatial concentration of the comparative advantage of agricultural land and non-agricultural land efficiency was not obvious, which indicates that the comparative advantage of industrial land in China has not yet formed a trend of agglomeration development, but there were dense and obvious high-high agglomeration areas or low–low agglomeration areas in some local regions. (4) Significant regional differences were found to exist in the impact of various factors on the comparative advantages of agricultural land efficiency and non-agricultural land efficiency. The comparative advantage of land use efficiency can be relied on to promote the optimization and adjustment of industrial structure and guide the efficient allocation of land resources.