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Updated: Jan 4, 2026
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
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Land Suitability Evaluation and an Interval Stochastic Fuzzy Programming-Based Optimization Model for Land-Use
Zuo Zhang1, Min Zhou2, Guoliang Ou3
1Collage of Public Administration, Central China Normal University, Wuhan 430079, China.
International Journal of Environmental Research and Public Health
|November 14, 2019
Summary
Rapid population and economic growth create land resource shortages. A new hybrid model optimizes land use quantitatively and spatially, addressing planning challenges and balancing development with environmental protection.
Area of Science:
- Environmental Science
- Urban Planning
- Geographic Information Systems
Background:
- Increasing population and economic growth exacerbate land resource scarcity.
- Existing land-use allocation models face challenges in comprehensive planning.
- Effective land-use allocation is crucial for mitigating resource shortages.
Purpose of the Study:
- To propose a hybrid quantitative and spatial optimization model for land-use allocation.
- To address limitations in current land-use planning methods.
- To integrate diverse factors into a robust land-use allocation framework.
Main Methods:
- Developed a hybrid model combining quantitative and spatial optimization.
- Incorporated land suitability assessment considering geographical, economic, and environmental factors.
- Utilized interval stochastic fuzzy programming for quantitative optimization under uncertainty.
Main Results:
- The model simultaneously optimizes land area and spatial allocation.
- It integrates multiple economic, social, ecological, and environmental constraints.
- A case study in Liannan county, China, demonstrated the model's applicability.
Conclusions:
- The proposed model offers a novel approach to land-use allocation.
- It effectively balances economic development, environmental protection, and land use.
- Findings support improved land management and decision-making in planning.
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