Academic Journal
A participatory geographic information system-based route optimisation for decentralised municipal solid waste management system: A case study from a flood-prone town in Kerala, India.
| Τίτλος: | A participatory geographic information system-based route optimisation for decentralised municipal solid waste management system: A case study from a flood-prone town in Kerala, India. |
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| Συγγραφείς: | Suresh R; Ashank Desai Centre for Policy Studies, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India., Vadakkan AGZ; Department of Architecture and Planning, National Institute of Technology Calicut, Kozhikode, Kerala, India., P R A; Department of Architecture and Planning, National Institute of Technology Calicut, Kozhikode, Kerala, India., Narayanan NC; Ashank Desai Centre for Policy Studies, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India. |
| Πηγή: | Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA [Waste Manag Res] 2026 Sep; Vol. 44 (9), pp. 1515-1530. Date of Electronic Publication: 2026 May 20. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Sage Publications Country of Publication: England NLM ID: 9881064 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1096-3669 (Electronic) NLM ISO Abbreviation: Waste Manag Res Subsets: MEDLINE |
| Imprint Name(s): | Publication: Original Publication: London ; New York : Academic Press, c1983- |
| Ιατρικοί όροι (MeSH): | Refuse Disposal*/methods , Solid Waste*/analysis , Waste Management*/methods , Geographic Information Systems*, India ; Floods ; Cities ; Transportation |
| Περίληψη: | Municipal solid waste management (MSWM) remains a critical challenge in India due to rapid urbanisation, increasing waste volumes, and limited institutional capacity. Although urban local bodies (ULBs) allocate up to 80% of their MSWM budgets to collection and transport, inefficiencies persist due to unoptimised routes and poor alignment with local conditions. Most geographic information system (GIS)-based optimisation models remain top-down, failing to reflect on-the-ground realities and are rarely implementable. This study presents a participatory GIS-based routing methodology for decentralised MSWM system in a flood-prone town in Kerala, India. It integrates standard geospatial data with tacit knowledge from ULB officials and frontline sanitation workers through participatory mapping and ground-truthing, producing spatial layers on waste generation, transport conditions, flood-prone roads, and existing collection clusters, pick-up points, and storage facilities. Based on this, the study proposes operational changes, including new pick-up points, mini-material collection facilities (intermediary storage hubs), and a three-tier vehicle system tailored to local constraints. ArcGIS Network Analyst is used to identify optimal routes, incorporating flood-prone roads as network barriers. Compared to the current system, the optimised plan is flood-resilient and achieves a 32% reduction in travel distance, 35% cut in fuel use and emissions, and a 62% increase in collection capacity and 100% household coverage, along with better working conditions. The study offers a scalable framework that merges technical optimisation with context specificity, enabling ULBs in resource-constrained settings to co-produce climate-resilient transport solutions. |
| Competing Interests: | Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. |
| Contributed Indexing: | Keywords: bottom-up planning; geographic information systems; participatory methodology; route optimisation; solid waste management; waste transportation |
| Substance Nomenclature: | 0 (Solid Waste) |
| Entry Date(s): | Date Created: 20260521 Date Completed: 20260901 Latest Revision: 20260901 |
| Update Code: | 20260901 |
| DOI: | 10.1177/0734242X261437538 |
| PMID: | 42163444 |
| Βάση Δεδομένων: | MEDLINE |
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