A hybrid AHP-SWARA-Fuzzy GIS framework for sustainable landfill site suitability assessment incorporating environmental, socio-economic, and climate-air quality indicators

Abstract

Identifying environmentally sustainable landfill sites is increasingly challenging in rapidly urbanizing regions due to competing land-use demands and stringent environmental constraints. This study develops an integrated GIS-based multi-criteria decision-making (MCDM) framework that combines AHP, SWARA, fuzzy logic, and a hybrid AHP-SWARA-fuzzy model, using 19 criteria across environmental, socio-economic, infrastructure, terrain, and climate air quality domains. Thematic layers were standardized, weighted using expert-driven AHP and SWARA, and transformed through fuzzy membership functions to capture uncertainty. Results show that moderate suitability zones dominate, while very high suitability areas are limited, indicating strong spatial constraints. The hybrid model identified 1043.91 km2 of suitable land, with environmental factors accounting for over 40% of the total weight, led by proximity to water, groundwater depth, and slope. Spatial validation confirmed strong model reliability, with waterbody overlap <5% across models, while built-up overlap ranged from 2.815% (AHP) to 8.574% (Hybrid). The hybrid model provided a reliable output by integrating consistency, expert prioritization, and uncertainty handling. Overall, 3-8% of land was highly suitable, highlighting severe siting constraints. The framework offers a strong, scalable decision-support tool for sustainable landfill planning. Future research should focus on incorporating higher-resolution datasets, machine-learning-based weighting techniques, dynamic urban growth scenarios, and field-based validation, thereby further improving the precision and applicability of landfill suitability assessments across diverse geographic contexts. © 2026 Elsevier Ltd.