Assessing Land Use Conflict in the Yangtze River Middle Reaches Megalopolis for 2030: Integrating Landscape Pattern Analysis and Scenario Simulation to Address Uncontrolled and Severe Conflict Zones

ABSTRACT Land use conflicts (LUCs) significantly impact regional food security and ecological security. Identifying LUCs helps cut down ecological risks. This study focuses on the Yangtze River Middle Reaches Megalopolis (YRMRM) as a case, employing a landscape pattern approach to construct a land use conflict measurement model. The study thoroughly explores the spatiotemporal evolution of LUCs and employs the PLUS model to simulate their future trends under multiple scenarios. The results indicate: (1) From 2005 to 2020, LUCs in the YRMRM exhibited an overall uncontrollable trend, with over 64% of spatial units in an uncontrolled state. The proportion of Severely Uncontrollable conflict areas increased from 11.85% to 12.11%. The predominantly uncontrolled regions are located in the urban–rural transition zones, while severely uncontrolled areas are concentrated in economically developed zones. (2) Under four scenarios—Cropland Protection, Natural Development, Economic Development, and Ecological Protection—it is projected that by 2030, both cropland and grassland in the YRMRM will experience a loss. Cropland loss is most significant under the Economic Development scenario, reaching 3488.56 km 2 , while grassland decreases the most under Cropland Protection. Built‐up land will significantly increase across all four scenarios, with the largest expansion occurring under the Economic Development scenario, up by 24.1%. (3) The Cropland Protection scenario is the most effective in alleviating LUCs by 2030, while the Economic Development scenario is the least favorable for mitigating such conflicts. This study systematically reveals the spatiotemporal differentiation patterns of LUCs in the YRMRM at the grid scale. Through the coupling of the landscape pattern‐based conflict measurement model with the PLUS model, this research realizes refined quantitative predictions of future conflict patterns, thereby providing a scientific basis for optimizing land use structure and establishing an early warning system for LUCs.