Modelling built-up land expansion probability using the integrated fuzzy logic and coupling coordination degree model

Area of Science:

• Urban and Regional Planning
• Environmental Science
• Geographic Information Systems

Background:

• Urbanization-induced land use/land cover (LULC) change, particularly built-up area expansion, is a significant global trend.
• Rapid urban sprawl in Indian cities, like Delhi National Capital Region (NCR), raises concerns about unsustainable growth and environmental quality.
• Existing urban growth models often overlook eco-friendly considerations and quality of life.

Purpose of the Study:

• To model built-up expansion probabilities in Delhi NCR using remote sensing and an integrated fuzzy logic and coupling coordination degree model (CCDM).
• To identify areas with very high, high, medium, low, and very low probabilities of future built-up expansion.
• To provide insights for urban planners and policymakers to manage urban sprawl effectively.

Main Methods:

• Land Use/Land Cover (LULC) classification using Random Forest (RF) classifier to extract built-up areas.
• Application of Analytical Hierarchy Process (AHP) integrated fuzzy sets with economic, demographic, proximity, topographic, and utility service parameters.
• Validation of built-up probability predictions using the Coupling Coordination Degree Model (CCDM).

Main Results:

• Built-up expansion probability is highest in the very high and high probability zones within Delhi NCR.
• Between the base year (2018) and future projections, built-up expansion probability increased by 5.72% in the very high zone.
• The study confirmed the robustness of the AHP-integrated fuzzy logic model in predicting built-up expansion probabilities, with a decline in the low probability zone by 14.06%.

Conclusions:

• The developed model effectively predicts built-up expansion probabilities in Delhi NCR, highlighting critical areas for urban planning interventions.
• Findings offer valuable data for policymakers to address the adverse impacts of rapid urban sprawl and promote sustainable development.
• The methodology can be adapted for analyzing urban expansion in other major global cities with similar geographical characteristics.