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<p>Effective management of Municipal Solid Waste (MSW) is essential for public health and maintaining urban environmental quality. However, unauthorized dumping remains a critical challenge in many Indian cities, including Kalaburagi City, due to inadequate waste management practices. This study employs Geographically Weighted Regression (GWR) within a Geographic Information System (GIS) framework to analyze the spatial distribution of unauthorized dumpsites and identify key influencing factors. Eight factors, including commercial areas, educational institutions, healthcare facilities, industrial locations, parks and playgrounds, population density, religious places, and road networks, were assessed for their correlation with unauthorized dumpsites. The model exhibited strong predictive capability, attaining an R² of 0.87, signifying that the chosen factors effectively interpret 87% of the spatial variance in unauthorised dumpsite occurrences across wards in the city. The findings reveal that road networks exhibit the highest positive correlation (72.3%), indicating their role in facilitating waste dumping, while parks and playgrounds show the lowest correlation (45.4%). The other factors exhibited varying degrees of positive correlation, highlighting varying degrees of influence on waste disposal behavior. These insights underscore the inefficiency of current waste management practices in Kalaburagi City and emphasize the need for localized, data-driven strategies to mitigate unauthorized dumping. The study’s findings provide valuable input for urban planners and policymakers to develop sustainable Municipal Solid Waste Management (MSWM) approaches tailored to the city’s spatial and socio-economic realities.</p>

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Spatial analysis of unauthorized dumpsites in Kalaburagi City, karnataka: assessing influencing factors using geographically weighted regression for sustainable waste management

  • 期刊论文

  • 发表日期：

    2026年2月9日

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  • Tharayil Irshad,
  • Mahalingam Bose,
  • K. Narmada

摘要

Effective management of Municipal Solid Waste (MSW) is essential for public health and maintaining urban environmental quality. However, unauthorized dumping remains a critical challenge in many Indian cities, including Kalaburagi City, due to inadequate waste management practices. This study employs Geographically Weighted Regression (GWR) within a Geographic Information System (GIS) framework to analyze the spatial distribution of unauthorized dumpsites and identify key influencing factors. Eight factors, including commercial areas, educational institutions, healthcare facilities, industrial locations, parks and playgrounds, population density, religious places, and road networks, were assessed for their correlation with unauthorized dumpsites. The model exhibited strong predictive capability, attaining an R² of 0.87, signifying that the chosen factors effectively interpret 87% of the spatial variance in unauthorised dumpsite occurrences across wards in the city. The findings reveal that road networks exhibit the highest positive correlation (72.3%), indicating their role in facilitating waste dumping, while parks and playgrounds show the lowest correlation (45.4%). The other factors exhibited varying degrees of positive correlation, highlighting varying degrees of influence on waste disposal behavior. These insights underscore the inefficiency of current waste management practices in Kalaburagi City and emphasize the need for localized, data-driven strategies to mitigate unauthorized dumping. The study’s findings provide valuable input for urban planners and policymakers to develop sustainable Municipal Solid Waste Management (MSWM) approaches tailored to the city’s spatial and socio-economic realities.