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Nevin Manimala Statistics

Analyzing the relationship between municipal solid waste generation and urban land use using integrated geospatial and spatial statistical techniques

Integr Environ Assess Manag. 2025 Sep 16:vjaf128. doi: 10.1093/inteam/vjaf128. Online ahead of print.

ABSTRACT

Understanding the spatial variability of municipal solid waste (MSW) generation is critical for informed urban planning and sustainable waste management. This study examines the relationship between land use patterns and MSW generation across the urban ecosystem of Kota City, India, to identify spatial clusters and assess the influence of urban form and density. An integrated geospatial-statistical approach was applied to 146 urban wards using Hotspot Analysis (Getis-Ord Gi*), Global and Local Moran’s I, overlay analysis, and zonal statistics. Waste generation data were spatially linked with land use typologies and population density to detect statistically significant patterns. Daily waste generation ranged from 0.43 to 11.13 metric tons (t/day) across wards. High-intensity hotspots were found in densely populated and mixed-use zones, such as Ward 15 (0.61 kg/person/day) and Ward 5 (0.88 kg/person/day). Spatial autocorrelation analysis confirmed significant clustering (Global Moran’s I = 0.056, z = 2.59, p = 0.009), with prominent hotspots identified in Wards 12, 13 (Kota-North) and Wards 16, 17 (Kota-South) at 99% confidence. Residential zones contributed the highest MSW load (541.97 t/day), followed by industrial (55.69 t/day) and commercial areas (50.20 t/day). Urban land use, population density, and mixed-use zoning significantly influence waste generation patterns. The spatial-statistical framework developed herein provides a scalable decision-support tool for waste planning, zoning policy, and sustainable resource management in rapidly urbanizing cities.

PMID:40971982 | DOI:10.1093/inteam/vjaf128

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