Optimizing landfill site selection using Fuzzy-AHP and GIS for sustainable urban planning

• Autores: Zabaleta Santisteban, Jhon Antony, Salas López, Rolando, Rojas Briceño, Nilton Beltrán, Gómez Fernández, Darwin, Medina Medina, Angel James, Tuesta Trauco, Katerin Meliza, Rivera Fernandez, Abner Shelser, Lévano Crisóstomo, José, Oliva Cruz, Manuel, Silva López, Jhonsy Omar
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:null:20.500.12955/2574
• Enlace del recurso: https://hdl.handle.net/20.500.12955/2574; http://dx.doi.org/10.28991/CEJ-2024-010-06-01
• Nivel de acceso: acceso abierto
• Materia: Landfill Locations; F-AHP; Remote Sensing; Geographic Information Systems; Suitability Model; https://purl.org/pe-repo/ocde/ford#5.07.01; Landfills; Descarga; Remote sensing; Teledetección; Geographical Information Systems; Sistema de Información Geográfica; Models; Modelo

Careful landfill selection with minimal environmental impact is vital for urban planners. This study aims to identify suitable sites for controlled landfills using Fuzzy-AHP integrated with Remote Sensing and GIS, considering a 20-year projection of population and solid waste generation. Initially, twelve sub-criteria were identified, grouped into environmental, socio-economic, and physical categories, and then weighted using paired comparison matrices involving nine experts. The sub-criteria were rasterized and classified into four suitability levels. The weighted overlay of sub-criteria maps generated a territorial suitability model. Within the Alto Utcubamba Commonwealth (Amazonas, Peru), 0.069%, 41.70%, 66.934%, 0.20%, and 12.4% of the territory are suitable, moderately suitable, less suitable, unsuitable, and restricted, respectively, for landfill establishment. Subsequently, 16 highly suitable sites were selected based on the required area (S4 polygons ≥ 0.505 ha) in line with the projected solid waste generation over 20 years. Of the 16 selected areas, only 15 met the shape index. The model showed high accuracy (AUC = 0.784) during validation. Furthermore, this study provides a comprehensive framework for making decisions about waste management in developing countries, enhancing understanding of key factors in selecting landfill sites. It also offers a deeper insight into global and local factors that determine the suitability of landfill sites.