Accessibility based on Gravity-Radiation model and Google Maps API: A case study in Australia

Xia, Nan; Cheng, Liang; Chen, Song; Wei, Xiaoyan; Zong, Wenwen; Li, Manchun

doi:10.1016/j.jtrangeo.2018.09.009

Cited by 81 publications

(55 citation statements)

References 61 publications

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“…Travel time is the most common indicator for measuring access through traditional methods of origin-destination (O–D) matrices in GIS analysis. However, the navigation and web-mapping platforms provide more substantial and accurate geographical data [ 51 , 63 ]. Online sources such as Google Maps, Here We Go, and Bing Maps are useful tools in the evaluation of the shortest routes in terms of time and distance for the public [ 64 ].…”

Section: Methodsmentioning

confidence: 99%

“…More recently, researchers use web-based mapping services, like Google Maps Application Programming Interface (API), to measure the overall accessibility at multiple scales, saving significant time for data collection and complex calculations [ 51 ]. Scholars have developed tools to accurately estimate the travel time between origins and destinations, highlighting the many advantages in using API compared to the ArcGIS Network Analyst approach [ 52 ].…”

Section: Introductionmentioning

confidence: 99%

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Modelling Potential Geographical Access of the Population to Public Hospitals and Quality Health Care in Romania

Dumitrache

Nae

Simion

et al. 2020

IJERPH

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The geographical accessibility to hospitals relies on the configuration of the hospital network, spatial impedance and population distribution. This paper explores the potential geographic accessibility of the population to public hospitals in Romania by using the Distance Application Program Interface (API) Matrix service from Google Maps and open data sources. Based on real-time traffic navigation data, we examined the potential accessibility of hospitals through a weighted model that took into account the hospital competency level and travel time while using personal car transportation mode. Two scenarios were generated that depend on hospitals’ level of competency (I–V). When considering all categories of hospitals, access is relatively good with over 80% of the population reaching hospitals in less than 30 min. This is much lower in the case of hospitals that provide complex care, with 34% of the population travelling between 90 to 120 min to the nearest hospital classed in the first or second category of competence. The index of spatial accessibility (ISA), calculated as a function of real travel time and level of competency of the hospitals, shows spatial patterns of services access that highlight regional disparities or critical areas. The high concentration of infrastructure and specialised medical personnel in particular regions and large cities limits the access of a large part of the population to quality health services with travel time and distances exceeding optimal European level values. The results can help decision-makers to optimise the location of health services and improve health care delivery.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling Potential Geographical Access of the Population to Public Hospitals and Quality Health Care in Romania

Dumitrache

Nae

Simion

et al. 2020

IJERPH

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“…4. Assigning the data on travel times to the road network makes it possible to connect all destinations within the city and perform time calculations (Calabrese et al 2011;Toole et al 2015;Xia et al 2018). .…”

Section: Individual Transport Modelsparametersmentioning

confidence: 99%

“…However, if a regular user wants to download real-time data and create a model of a travel time matrix for several different destinations, it is not a simple procedure. In order to download data from Google Maps® API, a special application generating real-time map loads and saving them is required (García-Albertos et al 2019;Xia et al 2018). Such an application has to be written in a programming language.…”

Section: Introductionmentioning

confidence: 99%

GIS tools and programming languages for creating models of public and private transport potential accessibility in Szczecin, Poland

Goliszek

2021

J Geogr Syst

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This article presents the results of public and private (car) transport accessibility modelling, which gives the room for the comparison of two types of transport throughout the whole day as well as the rush hours. Both public and private transport models are based on public available data, accessible via the Internet which is downloaded using a programming language and processed using the GIS tools. The public transport model is based on the GTFS data (General Transit Feed Specification), while the car model has been created from data on driving times derived from Google Maps® API. Both models presented in the article have been constructed for a specified period of time, namely from 5.00 am to 10.00 pm in 15-min intervals. The analysis of the above-mentioned models has allowed the comparison of differences in potential accessibility and its deviations at different times of the day. The disparities revealed by the study have indicated that there are certain times of the day when public transport is actually competitive with the private means of transport. The results of potential accessibility analysis are visualised with the use of maps, including the choropleth ones.

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“…Rahmi et al [49] consolidated MySQL as the main data storage space, and used Firebase to store additional data, where Firebase's real-time database processes chat data to provide corresponding notifications, along with Google Maps API to support GIS to explore and construct relevant technologies to meet the needs of mobile Android and web applications between doctors and patients. Xia et al [50] introduced population grid data into a new gravity radiation model, used Google Maps API to obtain grid-level travel costs, and explored relevant technologies for population flow estimation. Tan et al [51] adopted SPARQL (SPARQL Protocol and RDF Query Language) to query useful data from the DBpedia LOD database to acquire related data nodes and used the page rank algorithm to calculate the importance of each data node in order to build a concept map for awareness training in cybersecurity.…”

Section: Literature Review and Development Technologiesmentioning

confidence: 99%

A Balance Interface Design and Instant Image-based Traffic Assistant Agent Based on GPS and Linked Open Data Technology

Chen

Yang

2019

Symmetry

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Taiwan is a highly informational country, and a robust traffic network is not only critical to the national economy, but is also an important infrastructure for economic development. This paper aims to integrate government open data and global positioning system (GPS) technology to build an instant image-based traffic assistant agent with user-friendly interfaces, thus providing more convenient real-time traffic information for users and relevant government units. The proposed system is expected to overcome the difficulty of accurately distinguishing traffic information and to solve the problem of some road sections not providing instant information. Taking the New Taipei City Government traffic open data as an example, the proposed system can display information pages at an optimal size on smartphones and other computer devices, and integrate database analysis to instantly view traffic information. Users can enter the system without downloading the application and can access the cross-platform services using device browsers. The proposed system also provides a user reporting mechanism, which informs vehicle drivers on congested road sections about road conditions. Comparison and analysis of the system with similar applications shows that although they have similar functions, the proposed system offers more practicability, better information accessibility, excellent user experience, and approximately the optimal balance (a kind of symmetry) of the important items of the interface design. Symmetry 2020, 12, 1 2 of 24 Development Council [2], the mobile Internet usage rate among Taiwanese grew from 41.9% in 2009 to 98.2% in 2018, and mobile Internet usage has long been the main trend of Taiwanese Internet usage.The survey also pointed out that 84.9% of Taiwanese people over 12 years old use mobile Internet, while more than 60% of Taiwanese people under sixty-five years old use mobile Internet; therefore, the use of information systems or applications on various mobile devices by Taiwanese people via the Internet is undoubtedly a fairly mature digital skill. Thus, appropriate, convenient, and correct mobile or cloud information systems or applications are in great demand.Taiwan is a highly informational country, and transportation is one of the most important issues related to people on a daily basis. The transportation network is critical to the national economy, and is the benchmark index of public construction. Building a sound, smooth traffic network is an important infrastructure for the country's economic development, while traffic has a negative association with a large influx of vehicles, road construction, and traffic accidents [3][4][5][6], which are the reasons for road congestion. However, Taiwan is a country with dense population and heavy traffic, which is one of the main causes of road congestion. Therefore, there is a growing demand for information systems that can facilitate real-time and dynamic queries, and present current traffic information, especially for mobile application users.With the preva...

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Accessibility based on Gravity-Radiation model and Google Maps API: A case study in Australia

Cited by 81 publications

References 61 publications

Modelling Potential Geographical Access of the Population to Public Hospitals and Quality Health Care in Romania

Modelling Potential Geographical Access of the Population to Public Hospitals and Quality Health Care in Romania

GIS tools and programming languages for creating models of public and private transport potential accessibility in Szczecin, Poland

A Balance Interface Design and Instant Image-based Traffic Assistant Agent Based on GPS and Linked Open Data Technology

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