Solid Waste Management Planning using GIS and Remote Sensing Technologies Case Study Aurangabad City, India

Ahmed, Shafiq; Muhammad, Habeeb Sirajo; Sivertun, Åke

doi:10.1109/icast.2006.313826

Cited by 21 publications

(16 citation statements)

References 2 publications

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“…In most developing countries, including SA, wastes are disposed in landfill sites, which poses environmental risks [8] to nearby communities and more specifically, to the waste pickers themselves. Waste pickers are highly exposed to various hazards as they work through organic waste, including toxic medical waste [9]. Inadequate planning and management of waste disposal such as chemicals, batteries, and medical waste increases the risk of disease and infection among waste pickers [3].…”

Section: Introductionmentioning

confidence: 99%

Illness, Self-Rated Health and Access to Medical Care among Waste Pickers in Landfill Sites in Johannesburg, South Africa

Made

Ntlebi

Kootbodien

et al. 2020

IJERPH

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Waste pickers are exposed to various environmental health hazards, and self-rated health (SRH) could influence their medical care access. This study investigated the association between illness, clinic visits and SRH, and assessed if SRH can increase clinic visits. A cross-sectional study was conducted. SRH was defined as “very good”, “good”, “fair”, and “poor”. The illnesses were mental health, infectious, and chronic diseases. Medical care access included clinic visits in the previous 12 months. An ordinal logistic regression model was fitted to assess the association. There were 361 participants, 265 (73.41%) were males. Median age was 31 years, (interquartile range (IQR): 27–39). SRH: poor (29.89%), fair (15.92%), good (43.30%) very good (10.89%). Ever smoked (adjusted odds ratio (AOR): 1.72; 95% confidence interval (CI): 1.11–2.66), mental health (AOR: 1.87; 95% CI: 1.22–2.84), chronic (AOR: 2.34; 95% CI:1.47–3.68) and infectious (AOR: 2.07; 95% CI: 1.77–3.63) diseases were significantly associated with increased odds of reporting poor health. Clinic visit was not associated with SRH. From 99 (31%) individuals who rated their health as poor and ill, 40% visited a clinic (p = 0.0606). Acute and chronic illnesses were associated with poor SRH but this did not increase clinic visits. Provision of mobile clinic services at the landfill sites could increase access to medical care.

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Section: Introductionmentioning

confidence: 99%

Illness, Self-Rated Health and Access to Medical Care among Waste Pickers in Landfill Sites in Johannesburg, South Africa

Made

Ntlebi

Kootbodien

et al. 2020

IJERPH

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“…As presented in the table, the most widespread use of GIS on SWM lies in the areas of site selection for landfill, trash bin and transfer stations (Chang and Lin, 1997;Kao, 1996;Kao and Lin, 2002;Lotfi et al, 2007;Sener et al, 2011;Tralhão et al, 2010;Vijay et al, 2008) and routing and scheduling optimization based on historical or predicted data (Fan et al, 2010;Ghose et al, 2006;Jovičić et al, 2010;Kanchanabhan et al, 2011;Ozkan et al, 2006;Tavares et al, 2009). Others applications of GIS in SWM includes waste generation estimation by using socioeconomic data and local demographic (Ahmed et al, 2006;Karadimas and Loumos, 2008;Marah and Novotny, 2011), local management planning (Hrebicek and Soukopova, 2010;Macdonald, 1996), integrated SWM establishment (Karadimas et al, 2004;Tao, 2010) …”

Section: Geographical Information System (Gis)mentioning

confidence: 97%

“…Site selection for safe application to compost animal waste (Kao and Lin, 2002) Transfer station's location selection GIS analysis with customized model for shortest service Selection of appropriate location for the placement of waste pickup stations (Karadimas et al, 2004) Integrated SWM establishment GIS with fleet depot tracking using spatiotemporal analysis SWM framework creation to calculate total cost and feasible alternative (Karadimas et al, 2005) Waste generation estimation GIS based spatial analysis with clustering Identification of the ideal number and placement of location for the trash bins (Ghose et al, 2006) Routing and scheduling GIS based network analysis with ant colony system Waste collection route optimization and collection scheduling (Ahmed et al, 2006) Waste generation estimation GIS based spatial analysis Relocation and identification of the ideal number of trash bins (Ozkan et al, 2006) Route optimization GIS based network analysis Solid waste collection route optimization (Karadimas et al, 2006) Waste generation estimation GIS with fuzzy logic Estimation of the amount of solid waste productivity (Lotfi et al, 2007) Site selection GIS based analysis with fuzzy logic Solid waste landfill site selection (Vijay et al, 2008) Trash bin's location selection GIS based spatial analysis with p-median constrained model…”

Section: Referencesmentioning

confidence: 99%

A review on technologies and their usage in solid waste monitoring and management systems: Issues and challenges

et al. 2015

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“…Cities face the problem of limited land resources for waste disposal sites. Moreover, unplanned and mismanaged direct disposal of solid waste leads to environmental degradation and can cause various problems such as water pollution, vectorborne diseases, bad aesthetics and foul smell, combining together into the loss of natural resources and societal displeasure (Ahmed et. al., 2006).…”

Section: Introductionmentioning

confidence: 99%

Geospatial Multi-Criteria Decision Based Site Suitability Analysis for Solid Waste Disposal Using Topsis Algorithm

Jaiswal

Pandey

Kumar

et al. 2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> The problem of Urban Municipal solid waste disposal is a challenging task faced by civic bodies and planning authorities in almost all the cities of rapidly developing countries like India. A similar situation is being faced by Dehradun, the capital, and the fastest growing city of Uttarakhand, India. In the current study, an attempt has been made to find out the suitable sites for waste disposal in the area around Dehradun city using Geospatial Multi-criteria Decision Analysis (MCDA) techniques from remote sensing data. Two different decision rules of MCDA are used, namely, Analytical Hierarchical Process based Weighted Linear Combination (AHP – WLC) and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). WLC has been used previously for similar studies for its ease and simplicity to apply in raster format but TOPSIS has an advantage over WLC, it orders a set of alternatives on the basis of their separation from the ideal point. It defines the best alternative as the one that is simultaneously closest to the ideal alternative and farthest from the negative ideal point. Raster-based suitability analysis has been done and the results obtained by the two methods are compared. Identical results with minor differences identifying best suitable sites outside the eastern boundary of the city where the existing dumping site is located are obtained. Also, new potential sites are identified in the western part of the city which faces the problem of waste disposal more acutely because of expansion of the city in that direction.</p>

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Solid Waste Management Planning using GIS and Remote Sensing Technologies Case Study Aurangabad City, India

Cited by 21 publications

References 2 publications

Illness, Self-Rated Health and Access to Medical Care among Waste Pickers in Landfill Sites in Johannesburg, South Africa

Illness, Self-Rated Health and Access to Medical Care among Waste Pickers in Landfill Sites in Johannesburg, South Africa

A review on technologies and their usage in solid waste monitoring and management systems: Issues and challenges

Geospatial Multi-Criteria Decision Based Site Suitability Analysis for Solid Waste Disposal Using Topsis Algorithm

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