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Unplanned urban expansion accompanied by a decline in green infrastructure poses significant challenges for sustainable land-use planning in semi-arid, water-constrained secondary cities. Quetta, Pakistan, exemplifies these challenges due to rapid population growth, ecological degradation, water scarcity, and the absence of an updated master plan. This study develops a GIS-based spatial decision-support framework to evaluate residential development and green infrastructure priorities and to identify areas of conflict, synergy, and balanced planning opportunities. Sentinel-2A imagery acquired in May 2023 was used to generate a land-use/land-cover map, while residential and green-infrastructure suitability factors were standardized using fuzzy membership functions and integrated through an AHP Weighted Linear Combination approach. The resulting Residential Suitability Index (RSI) and Green-Infrastructure Suitability Index (GSI) were normalized and combined through a rule-based Residential–Green Infrastructure Trade-off Index (RGTI). Unlike conventional suitability assessments that evaluate development and ecological priorities independently, the proposed framework explicitly identifies zones of residential dominance, ecological dominance, and shared planning potential. Five planning-priority categories were delineated, comprising Very High Green Infrastructure Priority, Moderate Green Infrastructure Priority, Shared Zone, Moderate Residential Expansion Priority, and Very High Residential Expansion Priority. A spatial consistency assessment demonstrated that the identified planning zones correspond closely with existing land-use patterns and available land resources, supporting the plausibility of the proposed framework. The results provide a practical basis for delineating ecological conservation areas, residential development zones, and integrated planning zones capable of balancing urban growth and environmental sustainability. The framework offers a transparent and transferable approach for supporting land-allocation decisions in arid, data-scarce, and rapidly urbanizing cities facing competing development and ecological pressures.
Kamal et al. (Mon,) studied this question.