Determining the location of postal centers in B&amp;H using machine learning clustering method and GIS

Kosovac, Amel; Muharemović, Ermin; Begovic, Muhamed; Simic, Edvin

doi:10.23919/mipro48935.2020.9245087

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Geographic information system (GIS)-based network analyses provide an excellent tool set for analysing the geographic or 'spatial' components of logistics optimisation as a part of the supply chain with graphical network data, such as routable geographic models of route networks (Miller & Shaw, 2015). The analytical framework is largely applied to centralised delivery or collection types of study settings (see Bosona et al, 2011;Korhonen et al, 2017;Kosovac et al, 2020;Kotavaara et al, 2017;Yu et al, 2021), including also logistic optimisation of rural side stream flows (Lemire et al, 2019). There are also several studies applying location optimisation for rural cases in Finland such as accessibility of local and organic food (Kotavaara et al, 2014), bale wrapping waste from farms in North Karelia, Finland (Tepponen et al, 2020) and location optimisation for cattle and pig manure-based biogas reactors in Northern Ostrobothnia, Finland (Kotavaara et al, 2022).…”

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confidence: 99%

Measuring Accessibility and Optimising Logistics of Marginal Land Grass Biomass in the Case of Northern Ostrobothnia, Finland

Ollila,

Kotavaara

2023

European Countryside

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Grass biomass originating from marginal agricultural land unsuitable for food production can be utilised in variety of bio-based productions. The key profitability constraints for such productions are regional availability and transport costs. The aim of this paper is to methodologically test open access agricultural field parcel data – enabled by the EU INSPIRE directive – integrated with the road network in measuring biomass accessibility and optimising collection and transport using geographic information system (GIS) technology in two Finnish case areas. The analytical framework applies closest facility and vehicle routing analyses for tractor and truck transport scenarios. The key finding is that the area of field parcels and the amount of biomass accumulating within an observed area are not the only important factors influencing transport efficiency: cost-effectiveness of collection routes can be equally high in regions with scarce and abundant biomass areas.

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Section: /646mentioning

confidence: 99%

Measuring Accessibility and Optimising Logistics of Marginal Land Grass Biomass in the Case of Northern Ostrobothnia, Finland

Ollila,

Kotavaara

2023

European Countryside

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A study on geospatially assessing the impact of COVID-19 in Maharashtra, India

Das

Bebortta

2022

The Egyptian Journal of Remote Sensing and Space Science

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The emergence of 2019 novel corona virus disease (COVID-19) raised global health concerns throughout the world. It has become a major challenge for healthcare personnel and researchers throughout the world to efficiently track and prevent the transmission of this virus. In this paper, the role of geographic information system (GIS) based spatial models for tracking the spread of COVID-19 and discovery of testing centres in Maharashtra, India was studied. The datasets collected from diverse sources were geocoded to make it geospatially compatible. A three-tiered framework was proposed to practically realize the impact of COVID-19 in a cartographic fashion. Initially, choropleth maps labeled with testing centres, number of confirmed cases and casualties were visualized in a district-wise manner. Heatmaps for visualizing the spatial density of confirmed cases and casualties were presented. The visualization of spatial K-means clustering for optimal value of “k” estimated using the heuristic-based Elbow method was provided along with zonal analysis of the districts. Map showing spatial autocorrelation was also presented to identify spatial hotspots and coldspots. The districts of Pune and Thane reported respective scores of 3.424 and 3.347 along with values of 0.006 and 0.001 respectively. It was inferred from the generated results that Pune and Thane districts in Maharashtra were identified as COVID-19 hotspots. Based upon this analysis, certain effective mitigation strategies can be devised in order to check the uncontrolled spread of COVID-19 in the identified hotspot areas.

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Determining the location of postal centers in B&H using machine learning clustering method and GIS

Cited by 2 publications

References 14 publications

Measuring Accessibility and Optimising Logistics of Marginal Land Grass Biomass in the Case of Northern Ostrobothnia, Finland

Measuring Accessibility and Optimising Logistics of Marginal Land Grass Biomass in the Case of Northern Ostrobothnia, Finland

A study on geospatially assessing the impact of COVID-19 in Maharashtra, India

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