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dc.contributor.authorZabaleta Santisteban, Jhon Antony-
dc.contributor.authorSalas López, Rolando-
dc.contributor.authorRojas Briceño, Nilton Beltrán-
dc.contributor.authorGómez Fernández, Darwin-
dc.contributor.authorMedina Medina, Angel James-
dc.contributor.authorTuesta Trauco, Katerin Meliza-
dc.contributor.authorRivera Fernandez, Abner Shelser-
dc.contributor.authorLévano Crisóstomo, José-
dc.contributor.authorOliva Cruz, Manuel-
dc.contributor.authorSilva López, Jhonsy Omar-
dc.date.accessioned2024-09-13T21:14:32Z-
dc.date.available2024-09-13T21:14:32Z-
dc.date.issued2024-06-01-
dc.identifier.citationZabaleta-Santisteban, J.A.; Salas-López, R.; Rojas-Briceño, N.B; Gómez-Fernández, D.; Medina-Medina, A.J.; Tuesta-Trauco, K.M.; Rivera-Fernandez, A.S.; Lévano-Crisóstomo, J.; Oliva-Cruz, M.; & Silva López, J.O. (2024). Optimizing Landfill Site Selection Using Fuzzy-AHP and GIS for Sustainable Urban Planning. Civil Engineering Journal, 10(6).doi:10.28991/CEJ-2024-010-06-01es_PE
dc.identifier.issn2476-3055-
dc.identifier.urihttps://hdl.handle.net/20.500.12955/2574-
dc.description.abstractCareful 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.es_PE
dc.description.sponsorshipThis research was funded by the Public Investment Project “Creación de un Laboratorio de Geomática y Teledetección de la Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas” GEOMATICA, (CUI N° 2255626). The APC was funded by the Vice Rectorate of Research of the National University Toribio Rodriguez de Mendoza of Amazonas.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherSalehan Institute of Higher Educationes_PE
dc.relation.ispartofurn:issn: 2476-3055es_PE
dc.relation.ispartofseriesCivil Engineering Journales_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es_PE
dc.sourceInstituto Nacional de Innovación Agrariaes_PE
dc.source.uriRepositorio Institucional - INIAes_PE
dc.subjectLandfill Locationses_PE
dc.subjectF-AHPes_PE
dc.subjectRemote Sensinges_PE
dc.subjectGeographic Information Systemses_PE
dc.subjectSuitability Modeles_PE
dc.titleOptimizing landfill site selection using Fuzzy-AHP and GIS for sustainable urban planninges_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#5.07.01es_PE
dc.publisher.countryIRes_PE
dc.identifier.doihttp://dx.doi.org/10.28991/CEJ-2024-010-06-01-
dc.subject.agrovocLandfillses_PE
dc.subject.agrovocDescargaes_PE
dc.subject.agrovocRemote sensinges_PE
dc.subject.agrovocTeledetecciónes_PE
dc.subject.agrovocGeographical Information Systemses_PE
dc.subject.agrovocSistema de Información Geográficaes_PE
dc.subject.agrovocModelses_PE
dc.subject.agrovocModeloes_PE
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