Reduction planning has been implemented to mitigate urban sprawl in Chinese megacities. However, few studies have focused on the spatial implementation of urban land consolidation, and tools to estimate and simulate urban land consolidation are still lacking. To address the critical gap in urban land consolidation modeling, this study develops a bidirectional cellular automata model as a novel geospatial tool for quantifying consolidation potential and simulating future construction land dynamics under reduction planning. Our framework uniquely integrates high-resolution (30 m) simulation of simultaneous construction land expansion and reduction, overcoming limitations of conventional unidirectional models like the Future Land Use Simulation (FLUS) system, with validation confirming better accuracy. Using Beijing as a case study, the model identifies hotspots for land consolidation and, based on neighborhood-scale land transformation probabilities, delineates the spatial distribution of expansion and reduction zones, highlighting priority areas for consolidation. This provides the first operational tool for evidence-based urban reduction planning and land consolidation, offering a transferable methodology for optimizing land use efficiency and curbing disorderly expansion in megacities globally.