Optimizing the spatial relocation of hospitals to reduce urban traffic congestion: A case study of Beijing

Wang, Yuxia; Tong, Daoqin; Liu, Weimin; Liu, Yu

doi:10.1111/tgis.12524

Cited by 18 publications

(8 citation statements)

References 89 publications

(99 reference statements)

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“…Future work will focus on combining large datasets to validate and apply the multilevel hospital accessibility framework to multiple cities proposed in this research. The availability of mass spatial temporal data offers a major opportunity to evaluate the characteristics of public facilities, including medical services [43,44]. Further research on detailed medical service distributions and utilities should be performed next.…”

Section: Discussionmentioning

confidence: 99%

Evaluating the Spatial Accessibility and Distribution Balance of Multi-Level Medical Service Facilities

Jin

Liu

Tong

et al. 2019

IJERPH

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Public medical service facilities are among the most basic needs of the public and are directly related to residents’ health. The balanced development of medical service facilities is of great significance. Public medical service facilities can be divided into different levels according to their medical equipment, service catchment, and medical quality, which is very important but has been ignored for a long time in accessibility evaluations. In this research, based on the hospital and population datasets of Shenzhen, we propose a hierarchical two-step floating catchment area (H2SFCA) method to evaluate the spatial accessibility of public medical resources considering the factors at different levels of medical resources. In the proposed method, the spatial accessibility of each level of public medical service facilities are evaluated using different distance attenuation functions according to the medical service’s scope. In addition, a measurement is proposed to evaluate the equity of medical service facilities based on accessibility and population density distributions. To synthesize the general spatial accessibility and the distribution balance of public medical service facilities, we standardize the spatial accessibility of public medical service facilities at each level and then calculate the weighted sums of the accessibility of each level. The general spatial equity of public medical service facilities is also evaluated. The results show that the accessibility and distribution balance of medical resources performs dissimilarly at the three levels and can be discriminated within different regions of the city. The accessibility of citywide medical facilities in Shenzhen decreases from the city center to the suburban area in a radial pattern and the accessibility and distribution balance in the suburban areas needs improvement.

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Section: Discussionmentioning

confidence: 99%

Evaluating the Spatial Accessibility and Distribution Balance of Multi-Level Medical Service Facilities

Jin

Liu

Tong

et al. 2019

IJERPH

Self Cite

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“…Healthcare services have a positive impact on the travel speed of road segments. Large general hospitals usually have a negative impact on the surrounding road traffic [54], but because the healthcare services referred to in this paper include general hospitals, specialty hospitals, clinics, pharmacies, medical checkups and healthcare institutions, etc., the number of these healthcare services other than large general hospitals is larger and more widely distributed, and their traffic impact is much less than that of large general hospitals. The sports and leisure service density and the parking entrance and exit density also have a positive impact on the travel speed.…”

Section: Resultsmentioning

confidence: 99%

Exploring the Effects of Urban Built Environment on Road Travel Speed Variability with a Spatial Panel Data Model

Nian

Sun

Huang

2021

IJGI

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Road traffic congestion is a common problem in most large cities, and exploring the root causes is essential to alleviate traffic congestion. Travel behavior is closely related to the built environment, and affects road travel speed. This paper investigated the direct effect of built environment on the average travel speed of road traffic. Taxi trajectories were divided into 30 min time slot (48 time slots throughout the day) and matched to the road network to obtain the average travel speed of road segments. The Points of Interest (POIs) in the buffer zone on both sides of the road segment were used to calculate the built environment indicators corresponding to the road segment, and then a spatial panel data model was proposed to assess the influence of the built environment adjacent to the road segment on the average travel speed of the road segment. The results demonstrated that the bus stop density, healthcare service density, sports and leisure service density, and parking entrance and exit density are the key factors that positively affect the average road travel speed. The residential community density and business building density are the key factors that negatively affect the average travel speed. Built environments have spatial correlation and spatial heterogeneity in their influence on the average travel speed of road segments. Findings of this study may provide useful insights for understanding the correlation between road travel speed and built environment, which would have important implications for urban planning and governance, traffic demand forecasting and traffic system optimization.

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“…The methodological framework of STA-PCS can offer implications for policymakers and planners regarding the dynamic accessibility of healthcare services. Typical application directions include optimizing the spatial relocation of hospitals to reduce urban traffic congestion (Yuxia Wang, Tong, Li, & Liu, 2019), optimizing healthcare services location-allocation problems (Smith, Fry, Anderson, Maguire, & Hayward, 2017;W. Zhang, Cao, Liu, & Huang, 2016), reducing the spatial inequity of multilevel healthcare services (Wei Hu, Li, & Su, 2019), and improving the spatial equity of multilevel healthcare in the metropolis (S. Zhang et al, 2019), which will facilitate movement to optimize the allocation and equity of medical facilities.…”

Section: Discussionmentioning

confidence: 99%

Measuring spatiotemporal accessibility for pediatric clinical services with multimodal transport modes: an exploratory analysis in Nanjing, China

Zhou¹,

Li²,

Chen³

et al. 2020

Preprint

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Background: Healthcare accessibility research is developing towards a focus on multimodal transport modes (MTM) and spatiotemporal variation. Dynamic traffic conditions lead residents to make distinct traveling decisions in different timepoints, which has an impact on the spatiotemporal accessibility of healthcare. Pediatric clinic services (PCS) are one of the typical healthcare services that require a diagnosis through a professional physician clinic.Results: This paper aims to examine a methodological framework for the spatiotemporal accessibility of PCS (STA-PCS) and obtains its spatiotemporal variation characteristics. We design a spatial time impedance of multimodal transport modes (STI-MTM) model, which considers residential transport mode choices and adopt a gravity model based on web mapping data and population spatial distribution data to measure STA-PCS. We selected Nanjing, China, as the study area to estimate the STA-PCS value at four timepoints. The results indicate that the spatial aggregate of PCS is evident, and dynamic traffic factors influence the volatility of STA-PCS.Conclusions: This work holds pragmatic implications for policymakers on the STA-PCS considered travel characteristics based on georeferenced social media data.

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Optimizing the spatial relocation of hospitals to reduce urban traffic congestion: A case study of Beijing

Cited by 18 publications

References 89 publications

Evaluating the Spatial Accessibility and Distribution Balance of Multi-Level Medical Service Facilities

Evaluating the Spatial Accessibility and Distribution Balance of Multi-Level Medical Service Facilities

Exploring the Effects of Urban Built Environment on Road Travel Speed Variability with a Spatial Panel Data Model

Measuring spatiotemporal accessibility for pediatric clinical services with multimodal transport modes: an exploratory analysis in Nanjing, China

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