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Rapid increase in the quantities of municipal solid waste (MSW) generated has become major environmental, public health and economic challenges globally more so in rapidly urbanizing regions such as Sub-Saharan Africa countries and the United Arab Emirates (UAE). In order to sustain a functional waste ecosystem on this planet, we must find quick solutions before 2.8 billion metric tons of global waste output takes place by the year 2050. Population booms along with massive industrial development took place in the UAE and particularly Dubai, contributing to heightened pressure on already existing waste disposal activities that the government planned to decrease. The study uses an integrated Geographic Information System (GIS)—Analytical Hierarchy Process (AHP) methodology to determine the suitable locations for landfill sites in Dubai. Land use/land cover, proximity to built-up areas transportation infrastructure slope and environmental constraints as both spatial and non-spatial, were analysed by Multi-criteria decision making (MCDA) process. Integrating GIS into spatial mapping and AHP for determining the relative importance coefficient of each criteria through expert judgment and comprehensive literature review were two major steps en-route to achieving this goal. According to the findings of the study, about 12.4% of Dubai land area is characterised high landfill development potential and it is viable at bare land and low slope regions, and it depicts more suitable areas for landfill sites in Dubai, backed with cartographical views. Overlay and buffer analysis further screened on the basis of available airports away from existing dumpsites, etc. Therefore, the final suitability map developed provides practical knowledge that can facilitate urban planners and policymakers to make environmentally sound waste disposal solutions with cost-effectiveness and socially suitable approaches. This work shows the potential benefits of AI, IoT and geospatial analysis integration to optimize solid waste management in fast-growing cities.

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Assessment of Solid Waste Management Using Geospatial Techniques and Artificial Intelligence—A Case Study of the United Arab Emirates

  • 章节

  • 发表日期：

    2025年

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  • Mohammed Faiz,
  • Rashid Aziz Faridi,
  • Rakshanda F. Fazli,
  • Areeb Fazli

摘要

Rapid increase in the quantities of municipal solid waste (MSW) generated has become major environmental, public health and economic challenges globally more so in rapidly urbanizing regions such as Sub-Saharan Africa countries and the United Arab Emirates (UAE). In order to sustain a functional waste ecosystem on this planet, we must find quick solutions before 2.8 billion metric tons of global waste output takes place by the year 2050. Population booms along with massive industrial development took place in the UAE and particularly Dubai, contributing to heightened pressure on already existing waste disposal activities that the government planned to decrease. The study uses an integrated Geographic Information System (GIS)—Analytical Hierarchy Process (AHP) methodology to determine the suitable locations for landfill sites in Dubai. Land use/land cover, proximity to built-up areas transportation infrastructure slope and environmental constraints as both spatial and non-spatial, were analysed by Multi-criteria decision making (MCDA) process. Integrating GIS into spatial mapping and AHP for determining the relative importance coefficient of each criteria through expert judgment and comprehensive literature review were two major steps en-route to achieving this goal. According to the findings of the study, about 12.4% of Dubai land area is characterised high landfill development potential and it is viable at bare land and low slope regions, and it depicts more suitable areas for landfill sites in Dubai, backed with cartographical views. Overlay and buffer analysis further screened on the basis of available airports away from existing dumpsites, etc. Therefore, the final suitability map developed provides practical knowledge that can facilitate urban planners and policymakers to make environmentally sound waste disposal solutions with cost-effectiveness and socially suitable approaches. This work shows the potential benefits of AI, IoT and geospatial analysis integration to optimize solid waste management in fast-growing cities.