Land use zoning at the county level based on a multi-objective particle swarm optimization algorithm: a case study...

Area of Science:

• * Environmental Science
• * Urban Planning
• * Computational Optimization

Background:

• * Comprehensive land-use planning (CLUP) in China mandates land-use zoning for strict land use control, as per the China Land Management Law.
• * Traditional land-use zoning methods often lack the sophistication to handle complex, multi-objective considerations.
• * The need for optimized land-use zoning is critical for balancing development with ecological and spatial considerations.

Purpose of the Study:

• * To treat land-use zoning as a multi-objective optimization problem (MOOP), moving beyond traditional approaches.
• * To develop and apply a particle swarm optimization (PSO) based model integrated with genetic algorithm operators for enhanced land-use zoning.
• * To evaluate the model's effectiveness in maximizing attribute differences, spatial compactness, spatial harmony, and ecological benefits within zoning constraints.

Main Methods:

• * Formulation of land-use zoning as a multi-objective optimization problem (MOOP).
• * Application of a particle swarm optimization (PSO) algorithm enhanced with crossover and mutation operators from genetic algorithms.
• * Maximization of land-use zone attribute differences, spatial compactness, spatial harmony, and ecological benefits, subject to constraints like quantity limitations and minimum parcel area.

Main Results:

• * The PSO model effectively handles land-use zoning, with operators improving performance at the cost of increased computation time.
• * Balancing spatial compactness and harmony optimizes spatial patterns but may reduce attribute differences.
• * Prioritizing ecological benefits slightly increases them while also reducing attribute differences.
• * Adjusting objective weights allows for tailored optimal solutions catering to diverse decision-maker preferences.

Conclusions:

• * The proposed MOOP approach with enhanced PSO is a viable method for complex land-use zoning challenges in China.
• * Trade-offs exist between maximizing attribute differences and achieving optimal spatial and ecological outcomes.
• * The model's flexibility in weight adjustment enables customized zoning plans for various stakeholder needs.