An integrated GIS-based interval-probabilistic programming model for land-use planning management under...

Area of Science:

• Environmental Science
• Urban Planning
• Geographic Information Science

Background:

• Existing land-use allocation models often fail to integrate land suitability and uncertainty.
• Factors like land availability, demand, and ecological needs introduce significant variability.
• A comprehensive approach is needed for effective land-use planning management.

Purpose of the Study:

• To develop and apply an integrated model for land-use planning management (IPP-LUPM) that incorporates Geographic Information System (GIS) and interval-probabilistic programming (IPP).
• To address uncertainties in land-use factors and consider land suitability in optimization.
• To provide a framework for balancing economic development with environmental and ecological constraints.

Main Methods:

• Utilized GIS for data assembly and suitability mapping based on physical features and spatial analysis.
• Employed interval-probabilistic programming (IPP) to handle uncertainties in discrete intervals and probability distributions.
• Integrated land suitability outcomes, socioeconomic demands, and eco-environmental constraints into the IPP-LUPM model for optimization.

Main Results:

• The IPP-LUPM model effectively examined constraint satisfaction reliability under uncertainty.
• Identified a quantitative relationship between land suitability and system benefits.
• Demonstrated that prioritizing highly suitable land reduces environmental conflicts but may lower economic benefits, while developing less suitable land increases economic gains but elevates ecological risks.

Conclusions:

• The developed model provides a robust tool for land-use planning management under uncertainty.
• Decision-makers must carefully consider trade-offs between economic objectives and environmental/ecological considerations.
• The model aids in understanding the complex interrelations within land-use planning systems.