Abstract: Urban–rural integration has emerged as one of the most important strategies for coordinated regional development in recent years. The rational and scientific allocation of territorial spatial resources can be promoted to mitigate the spatial conflicts among production, living, and ecological functions. A case study was taken as the urban–rural integration pilot zone in Chongqing, China. A complex spatial landscape was shaped by rapid urbanization, ecological fragility, and the demand for sustainable agriculture. The Patch-generating Land Use Simulation (PLUS) model was employed to explore future land use dynamics. Three representative scenarios of the land use evolution were constructed and simulated: The Natural Development Scenario (NDS), which followed historical trends; the Ecological Protection Scenario (EPS), which emphasized environmental preservation; and the Farmland Protection Scenario (FPS), which prioritized agricultural security. These patterns of project land use were simulated for the year 2030. A scientific basis was provided to evaluate the trade-offs among competing land demands. A three-dimensional framework of spatial regulation was developed after scenario simulations using spatial overlay analysis with a Python-based multi-condition automated trade-off algorithm. This framework consisted of three core control layers: the "Farmland Protection Red Line," which safeguarded the essential agricultural areas; the "Ecological Security Baseline," which preserved the vital ecological spaces; and the "Development Flexibility Zone," which accommodated the regional growth needs within defined boundaries. Together, these elements aimed to reconcile the tensions among ecological conservation, farmland preservation, and development flexibility. Three key findings emerged from the analysis. 1) Land Use Dynamics: All three scenarios revealed that the farmland was under dual pressure from both urban expansion and ecological protection. Significant farmland loss was observed in each case: 22.57 km² under NDS, 18.83 km² under EPS, and 10.42 km² under FPS. Similarly, the forested areas shared the degradation under scenarios. Construction land expanded most notably under NDS (30.7 km²), followed by EPS (19.7 km²) and FPS (17.42 km²), indicating the varying impacts of policy priorities. 2) Spatial Conflict Patterns: 107 types of spatial conflict overlays were identified among land patches, indicating the pronounced regional heterogeneity. There were the high-conflict areas, such as Jiangjin District (26 687 conflict patches) and Yongchuan District (12 100 patches). In contrast, there were the sharply lower-conflict zones, like Tongnan District (3 674 patches). These patterns were closely aligned with the disparities in the local development strategies and resource endowments. 3) Integrated Regulation Effectiveness: The spatial regulation was offered a robust multi-objective optimization. Compared with NDS, there was a 106.57 km² increase in the protected farmland, a 112.16 km² reduction in construction land expansion, and a 2.6% improvement in forest retention. The framework shared a better-balanced growth with ecological and food security imperatives. The framework was empirically validated for the synergistic "quantity–quality–space" optimization in land use. A replicable model was provided for the territorial spatial planning in the transitional and rapidly urbanizing regions. Future work should focus on the ecological compensation, real-time data streams with simulation models, as well as the legal and institutional safeguards. Additionally, machine learning techniques were incorporated to improve the parameter calibration, thereby enhancing the framework’s adaptability against diverse regional contexts. This finding can thus offer valuable theoretical insights and practical strategies for the sustainable urban–rural transformation at multiple scales.