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PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules.

Yaolin Liu1,2,3,4, Jinjin Peng1, Limin Jiao1,2,3,4

  • 1School of Resource and Environment Sciences, Wuhan University, 129 Luoyu Road, Wuhan 430079, China.

Plos One
|June 21, 2016
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Summary
This summary is machine-generated.

This study introduces a new land-use allocation model (PSOLA) that uses patch-level operations and planning knowledge to avoid fragmentation. The model significantly improves social, economic, and ecological benefits compared to traditional methods.

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Area of Science:

  • Environmental Science
  • Urban Planning
  • Computational Science

Background:

  • Optimizing land-use allocation is crucial for regional sustainable development, balancing social, economic, and ecological factors.
  • Existing cell-level land-use models often lead to fragmented patches and fail to integrate planning knowledge effectively.

Purpose of the Study:

  • To develop a heuristic land-use allocation model (PSOLA) that utilizes patch-level operations and knowledge-informed rules.
  • To overcome the limitations of traditional cell-level models in land-use planning.

Main Methods:

  • Developed the Patch-level Swarm Optimization Land Allocation (PSOLA) model using particle swarm optimization.
  • Implemented patch-level operations (edge, size, compactness) to control land-use patch characteristics.
  • Integrated knowledge-informed rules (suitability, accessibility, policy, preferences) into the optimization process.

Main Results:

  • The PSOLA model demonstrated superior performance over basic Particle Swarm Optimization (PSO).
  • Achieved significant improvements in social (3.60%), economic (7.10%), ecological (1.53%), and overall benefits (4.06%).
  • Validated through a case study in Gaoqiao Town, Zhejiang Province, China.

Conclusions:

  • The PSOLA model effectively optimizes land-use allocation by avoiding fragmentation and incorporating planning knowledge.
  • The model offers an open architecture for extension as a generic decision-support tool for land-use planning.