Geospatial Landslide Risk Mapping Using AHP and GIS: A Case Study of the Utcubamba River Basin, Peru.

• Autores: Rivera, C.A., Valqui-Reina, S.V., García-Naranjo, L.F., Ocaña-Zúñiga, C.L., Auquiñivín-Silva, E.A., Chapa-Gonza, S.R., Cieza-Tarrillo, D., Vergara, C.G., Vergara, A.J.
• Formato: artículo
• Fecha de Publicación: 2025
• Institución: Universidad Nacional de Cajamarca
• Repositorio: UNC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.unc.edu.pe:20.500.14074/9828
• Enlace del recurso: http://hdl.handle.net/20.500.14074/9828; https://doi.org/10.3390/app15179423
• Nivel de acceso: acceso abierto
• Materia: geospatial analysis; remote sensing; multicriteria analysis; https://purl.org/pe-repo/ocde/ford#2.07.01

This study examines the use of a spatial multi-criteria approach based on GIS and AHP techniques to model landslide risk in the Utcubamba river basin, Peru. The methodology consisted of selecting twelve triggering variables: slope angle, geology, precipitation, distance to faults, drainage density, TWI, relative relief, profile curve, land use, elevation, distance to roads, and distance to population centers. These variables were then analyzed using the AHP method and then integrated into a GIS environment, where the weighted linear combination (WLC) method was used to map landslide risk. The risk was categorized into five classes, ranging from very low (1) to very high (5). The main results indicate that 32.81% of the area analyzed in the Utcubamba river basin presents a high and very high risk of landslides. The high-risk areas are mainly located in the southern part of the basin and coincide with areas with steep slopes, high rainfall, and proximity to population centers or communication routes. The model generated was highly accurate (AUC of 0.82), confirming that the integration of the AHP method with GIS allows for the precise identification of critical areas, which is useful for territorial planning, the prioritization of interventions, and emergency management, making it a reliable and replicable methodology in other parts of Peru.