Assessing the current solid waste management system and selecting new landfill site using Geospatial Technology: A case of Chole Town, Oromia, Ethiopia

Abstract

This study aims to enhance the solid waste management (SWM) system in Chole Town, Oromia Regional State, Ethiopia, through the application of geospatial technologies. Driven by rapid urbanization, population growth, and increasing wastes generation, Chole Town faces major environmental, infrastructural, and institutional challenges in solid waste management. The research integrates geospatial technologies like Geographic Information Systems (GIS), Remote Sensing (RS), and the Analytic Hierarchy Process (AHP) with socio economic data and environmental data to identify the best locations for solid waste dumping. 380 household respondents were sampled using stratified random sampling, and data were collected using questionnaires, interviews, field observation, and spatial data. The significant determining factors that were identified as applicable are inadequate institutional coordination, poor public awareness, absence of infrastructure, and proximity to slope, water body, and land use. Multi-criteria decision-making techniques were employed to rank eight crucial spatial factors including land use/land cover, slope, proximity to roads, proximity to built-up, soil type, distance to surface and ground water, and sensitive area proximity. The geospatial analysis indicated that 14% of the study area was highly suitable for landfill development, 28% was moderately suitable, 18% was less suitable, and 38% was unsuitable according to environmental and social limitations. The study confirms that integrating spatial and non-spatial data improves well-informed decision-making for sustainable waste management. It concludes that the application of geospatial tools not only enhances the efficiency of SWM practices but also promotes resource optimization, environmental sustainability, and long-term urban development. It suggests improving institutional capacity, investing in infrastructure, adopting segregation and recycling, and mainstreaming GIS-based planning for future development.