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Updated: May 12, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Integrated ecological and environmental spatial soft constraint mechanism: Urban multi-objective land use
1State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing, 100875, China.
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Addressing the current contradiction between urbanization and ecological environmental issues, developing land use optimization methods, and enriching relevant empirical research to meet national strategic needs are of paramount importance. However, existing studies still face limitations in establishing ecological and environmental spatial soft constraints, dynamically integrating them into models, combining land use quantity structure with spatial layout, and reflecting decision-makers' evaluation preferences. In light of these challenges, this study constructs a multi-objective land use optimization method that integrates ecological and environmental spatial soft constraint mechanism, taking Changchun, a key city in Northeast China, as a case study. Combining the land use quantity structure optimization method with the spatial layout optimization method, this study constructs ecological and environmental spatial soft constraints based on Territorial Spatial Development Suitability (TSDS) and Resource and Environmental Carrying Capacity (RECC). Additionally, it integrates development patterns with decision risk schemes into multiple scenarios for optimization. The study reveals that under the Natural Development (ND) pattern, the built-up land, woodland, and grassland in Changchun by 2030 do not meet the requirements of existing plan. In contrast, the land use quantity structure under the other three development patterns shows the significant optimization compared to 2020, with economic and ecological benefits increasing by at least 1.54 and 4.655 billion yuan, respectively. Among the 12 scenarios, relatively superior scenarios include ED3, EP2, EEB1, and EEB3. This research holds significant scientific importance for the orderly development and optimized layout of land resources, providing guidance for the adjustment of territorial spatial development plan.
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