With limited land resources and water scarcity, scientifically optimizing crop layouts is essential for ensuring the sustainable development of agricultural systems. This study introduces a hybrid approach to crop layout optimization in Heilongjiang Province, focusing on planting the most suitable crops in appropriate regions. The approach integrates multi-objective interval parameter programming, life cycle assessment, maximum entropy (MaxEnt), and the dynamic conversion of land use and its effects (Dyna-CLUE) model. The results indicate that slope, population density, and mean temperature of the coldest quarter are the main factors influencing the distribution of rice, maize, and soybeans, respectively. Highly suitable areas for rice cultivation account for 10.3 % of the province's land area, primarily in the Three Rivers Plain. Comparisons of the optimal planting structure from the optimized simulation to the 2021 baseline show that although economic benefits may decrease by 1.7% to 4.2 %, the crop carbon footprint could be reduced by 9.3 % to 10.7%. These findings highlight the importance of balancing economic and environmental benefits in optimizing crop structures. Furthermore, the proposed model shifts the focus from quantitative optimization of crop planting to spatial optimization, emphasizing the importance of determining where crops should be planted rather than solely focusing on how much to plant.