Evaluating public ambulance service levels by applying a GIS based accessibility analysis approach

Baloyi, Ethel; Mokgalaka, H; Green, Cheri A; Mans, Gerbrand G

doi:10.4314/sajg.v6i2.3

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…Most recently, Baloyi et al (2017) evaluated the accessibility of EMS by consulting with city officials to define road speeds, and Szymon (2017) used the 2SFCA method to assess the accessibility of fire services by assuming vehicles to travel at maximum permitted speeds. Neither considered the impact of traffic congestion on the road network.…”

Section: Introductionmentioning

confidence: 99%

Impact of traffic on the spatiotemporal variations of spatial accessibility of emergency medical services in inner-city Shanghai

Hu¹,

Tan²,

Li³

et al. 2018

Environment and Planning B: Urban Analytics and City Science

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Variability in spatial accessibility of emergency medical services has become a major concern in evaluating the quality of emergency medical services in China. Unlike some other public services, response time is critical in the provision of emergency medical services. Traffic congestion may significantly affect response time, especially in large cities. This study uses a transportation simulation model to estimate the travel time under free-flow and congested road conditions and measure the corresponding spatial accessibility of emergency medical services for various hours of a day in inner-city Shanghai. When traffic congestion is considered, the overall spatial accessibility is significantly reduced, and the effect is further magnified in certain congested areas. The results help policy makers in planning the emergency medical services resource that is sensitive to the spatiotemporal variation of its accessibility.

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Section: Introductionmentioning

confidence: 99%

Impact of traffic on the spatiotemporal variations of spatial accessibility of emergency medical services in inner-city Shanghai

Hu¹,

Tan²,

Li³

et al. 2018

Environment and Planning B: Urban Analytics and City Science

View full text Add to dashboard Cite

show abstract

“…Geographic information system (GIS) technology is being used more in analysing patterns in many areas of applications, including renewable energy (RE) (Aydin et al, 2010;Resch et al, 2014;Wei-Chieh et al, 2019). The use of GIS-based trend analysis provides useful insights into the spatial distribution and temporal fluctuations in renewable energy consumption and production across various countries in Africa (Baloyi et al, 2017;Duvenhage et al, 2020;Mentis et al, 2017;Mokgalaka et al, 2013). This methodology enables the detection of regions with significant capacity for generating renewable energy, as well as regions experiencing a growing need for renewable energy sources.…”

Section: Introductionmentioning

confidence: 99%

GIS-based Spatial Autocorrelation Queen Contiguity Order-One Analysis of the Renewable Energy Consumption and Production of African Countries with Economic and Environmental Indices

Gwani,

Kun

2024

Preprint

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The worldwide undertaking to achieve sustainable energy solutions has emphasized the need to comprehend the patterns of renewable energy consumption (REP), and production (REC), and socioeconomic and environmental variables. This work utilizes geographic information system (GIS) methodologies and spatial autocorrelation analysis, specifically Queen contiguity order 1 (Q1), to examine the spatial pattern of renewable energy consumption across African nations. This research seeks to reveal regional patterns, detect clusters of comparable renewable energy consumption behaviors, and assess the economic and environmental consequences linked to these patterns, REP, REC, economic indicators, and environmental indices such as African countries' gross domestic product (GDP) and carbon dioxide emissions (CO2) using data from 57 countries from 1990 to 2020. This study measured the similarities of these variables between neighbouring nations using the Q1 spatial autocorrelation methodology. The findings show concentrated areas with high and low REP, REC, and GDP, revealing regional patterns and inequities. This study also analysed trends to determine the eco-nomic and environmental evolution as well as the REP and REC patterns. Additional related variables, including the ecological footprint (EF), economic complexity index (ECI), and global index (GI), were used in Moran’s I statistical analysis. These findings can help policymakers, researchers, and stakeholders establish strategies for sustainable energy, economic growth, and environmental protection across the continent. This multidisciplinary method uses GIS, spatial analysis, economics, and environmental elements to fully comprehend the complex relationships between the variables under investigation. Furthermore, the study recommends an econometric regression model approach to evaluate the link between these variables, with the hope that this technique will facilitate a more thorough understanding of the influence of renewable energy use on the economic and environmental welfare of African nations.

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“…Geographic Information System (GIS) technology is being used more in analyzing patterns in many areas of applications including Renewable Energy (RE) (Aydin et al, 2010;Resch et al, 2014;Wei-Chieh et al, 2019). Utilizing GIS-based trend analysis allows for useful insights into the spatial distribution and temporal fluctuations in renewable energy consumption and production across various countries in Africa (Baloyi et al, 2017;Duvenhage et al, 2020;Mentis et al, 2017;Mokgalaka et al, 2013). This methodology enables the detection of regions with significant capacity for generating renewable energy, as well as regions experiencing a growing need for renewable energy sources.…”

Section: Introductionmentioning

confidence: 99%

GIS-based Spatial Autocorrelation Queen Contiguity Order-One Analysis on African Countries Renewable Energy Consumption and Production with Economic and Environmental Indices

Sek,

Gwani,

Gwani

2024

Preprint

View full text Add to dashboard Cite

The worldwide undertaking to achieve sustainable energy solutions has emphasized the need to comprehend the patterns of renewable energy consumption (REP), renew-able energy production (REC), and their socioeconomic and environmental variables. This work utilizes Geographic Information System (GIS) methodologies and spatial autocorrelation analysis, specifically Queen contiguity order 1 (Q1), to examine the spatial pattern of renewable energy consumption across African nations. The research seeks to reveal regional patterns, detect clusters of comparable renewable energy consumption behaviours, and assess the economic and environmental consequences linked to these patterns, REP, REC, economic indicators, and environmental indices such as African countries' gross domestic product (GDP) and carbon dioxide emissions (CO2) using 57 countries data from 1990 to 2020. The study measured these variables' similarities between neighbouring nations using the Q1 spatial autocorrelation methodology. The findings show concentrated areas with high and low REP, REC, and GDP, revealing regional patterns and inequities. The study also analyses trends to determine eco-nomic and environmental evolution as well as REP and REC patterns. Additional related variables, including ecological footprint (EF), economic complexity index (ECI), and global index (GI), were used in Moran’s I statistics analysis. These findings can help policymakers, researchers, and stakeholders establish strategies for sustainable energy, economic growth, and environmental protection across the continent. This multidisciplinary method uses GIS, spatial analysis, economics, and environmental elements to fully comprehend the complex relationships between the variables under investigation. Furthermore, the study recommends an econometric regression model approaches to evaluate the link between these variables, with the hope that this technique facilitates a more thorough comprehension of the influence of renewable energy use on the economic and environmental welfare of African nations.

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Evaluating public ambulance service levels by applying a GIS based accessibility analysis approach

Abstract: Abstract

Cited by 8 publications

References 4 publications

Impact of traffic on the spatiotemporal variations of spatial accessibility of emergency medical services in inner-city Shanghai

Impact of traffic on the spatiotemporal variations of spatial accessibility of emergency medical services in inner-city Shanghai

GIS-based Spatial Autocorrelation Queen Contiguity Order-One Analysis of the Renewable Energy Consumption and Production of African Countries with Economic and Environmental Indices

GIS-based Spatial Autocorrelation Queen Contiguity Order-One Analysis on African Countries Renewable Energy Consumption and Production with Economic and Environmental Indices

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