Investigation of Road Network Connectivity and Accessibility in Less Accessible Airport Regions: The Case of India

Sharma, Shalvi; Ram, Sewa

doi:10.3390/su15075747

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…Connectivity refers to the capacity to establish links between nodes within a transportation network, and is closely related to the robustness of the transportation network [63]. It is crucial for enhancing transportation system accessibility as it directly affects how easily different areas can be reached via road networks [64]. A highly connected traffic network can maintain operational efficiency even when some routes are closed [65].…”

Section: Analysis Of the Structural Significance Of Roadsmentioning

confidence: 99%

A Dual-Layer Complex Network-Based Quantitative Flood Vulnerability Assessment Method of Transportation Systems

Ding,

Wang,

2024

Land

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Evaluating the vulnerability of urban transportation systems to flood disasters can provide scientific support for urban disaster prevention and mitigation. Current methods for assessing the flood vulnerability of urban roads often overlook the internal relationships within the complex spatial composition of road networks and surface structures. In this study, based on the theory of complex networks, a dual-layer network assessment model is established for evaluating the flood vulnerability of urban transportation systems by coupling basic geographic data with road network vector data. Unlike traditional methods, this model considers the complex relationship between road network structures and ground surfaces, uncovering a correlation between road network structure and road flood vulnerability. By utilizing this model, the flood vulnerability of road networks in Shenzhen, as well as the city’s spatial flood vulnerability, are quantitatively assessed. Based on the quantitative results, we create maps illustrating the distribution of road and spatial flood vulnerability in Shenzhen. The study results reflect that roads highly vulnerable to flooding are mainly located in the central urban area of the southwest, with the flood vulnerability spatially concentrated primarily in the northern and western regions. Using data from government reports, news stories, and other sources over the past five years, we compile recorded instances of urban waterlogging. The quantitative results of the model are consistent with the distribution trend in recorded waterlogging points, indicating that the model’s outcomes are authentic and reliable.

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Section: Analysis Of the Structural Significance Of Roadsmentioning

confidence: 99%

A Dual-Layer Complex Network-Based Quantitative Flood Vulnerability Assessment Method of Transportation Systems

Ding,

Wang,

2024

Land

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“…Airport accessibility is mainly categorized into ground transportation accessibility [6] and route network accessibility [7]. The former is mainly measured by the benefit-cost ratio index [8], cost function [9], gravity model [10], graph theory [11], mixed nested logit model [12], and other models that can be used to analyse an airport's industrial radiation to the local area. The latter is mainly measured using descriptive statistical data and related indexes [13][14][15], the shortest path length model [16][17], social network analysis, accessibility evaluation methods [18], the potential energy model, and utility models [19].…”

Section: Composition Of Aic Integrated Accessibilitymentioning

confidence: 99%

Airport–Industry–City Integrated Accessibility Using Big Data Case View from Beijing Capital International Airport

Danyang Shen, Ximeng Liu, Xiudi Li

2024

jes

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Big data technology can help collect, analyze, and process large-scale transportation, population, economic, and other relevant data, which has been proven to be more accurate in assessing the accessibility of different areas. An aerotropolis is composed of the airport as the core, airport-related industry as the link, and the airport-oriented city as the carrier, airport–industry–city (AIC) system. To better grasp the development quality of aerotropolises, an AIC integrated accessibility measurement model is constructed comprising the accessibility of airport route network, airport ground traffic, and airport information coverage. Using big data of traffic, network and information from 2001 to 2020, we apply the model to the Beijing Capital International Airport (PEK) aerotropolis. The results show that PEK’s AIC connectivity exceeded 1 for the first time in 2008, reaching 1.0890, which the range of the scale is [0, +∞]. It fluctuated significantly from 2017 to 2020, showing a double life-cycle S-curve. So, the PEK aerotropolis’ development can be divided into four stages: germination (before 2001), high-speed development (2002–2011), gradual formation (2012–2019), and “seeking change in the process of change” (after 2020). Our model offers a new tool for identifying the development stages of aerotropolises and for improving connectivity—namely, improving the accessibility of the airport node network, the layout of airside-preferring enterprises, and the network structure of new Internet-based airport cities. Obviously, the AIC integrated accessibility can indeed guide the scientific development of an aerotropolis.

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“…David Canca [26] considers how to calculate the frequency of line selection and obtain the most convenient train unit when the demand and transportation allocation are given under the competitive transportation mode. In Shalvi Sharma's [27] work, based on graph theory and network connectivity index, different indices are selected to calculate the road network connectivity of airports with different capacities in their affected areas. Airports were ranked according to the connectivity results to identify the most and least accessible areas of the air traffic network in India.…”

Section: Research On Hsr Network Planningmentioning

confidence: 99%

“…Equation (23) indicates that the main backbone line planning has the highest urgency among all lines in the network. Equation (26) indicates that at least one of the backbone lines in the online network should be the starting point of the selected city i; Equation (27) shows that at least one of the backbone lines in the online network should be the end of the selected city j; Equation (28) indicates that there is at most one planned route between cities i and j; Equations ( 26)-( 28) ensure the continuity of the alignment and geographical location of the backbone line.…”

Section: Main Backbone Line Planning Modelmentioning

confidence: 99%

Urban Agglomeration High-Speed Railway Backbone Network Planning: A Case Study of Beijing-Tianjin-Hebei Region, China

2023

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In order to optimize the network layout of urban agglomerations, improve the comprehensive benefits of transportation networks and promote the sustainable development of urban agglomerations, this paper studies the main trunk line selection model of the Beijing–Tianjin–Hebei high-speed railway (HSR). Firstly, the characteristics of cities in urban agglomeration are analyzed, and the economic capacity, transportation capacity, passenger turnover and network characteristics of urban nodes are selected as evaluation indexes. A node importance model and a line urgency model were established to obtain the value of the importance of urban nodes and the urgency of each line in the urban agglomeration. Secondly, the DBSCAN is used to cluster the city nodes, and the city nodes are divided into four grades. With the goal of maximizing the urgency of the lines and considering the constraints of the urban node level, the optimization model of the Beijing–Tianjin–Hebei backbone network selection is constructed. The backbone lines of the Beijing–Tianjin–Hebei urban agglomeration are obtained, and the selection results of backbone lines are analyzed, which lays a foundation for the design and optimization of the HSR operation scheme in urban agglomeration. The planned backbone network can basically realize the commuting between the important urban nodes in the Beijing–Tianjin–Hebei urban agglomeration to achieve the goal of driving and alleviating the operation of the branch line. It can accelerate the development of the internal traffic of the urban agglomeration. In addition, it has certain practical significance and practical value.

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Investigation of Road Network Connectivity and Accessibility in Less Accessible Airport Regions: The Case of India

Cited by 7 publications

References 13 publications

A Dual-Layer Complex Network-Based Quantitative Flood Vulnerability Assessment Method of Transportation Systems

A Dual-Layer Complex Network-Based Quantitative Flood Vulnerability Assessment Method of Transportation Systems

Airport–Industry–City Integrated Accessibility Using Big Data Case View from Beijing Capital International Airport

Urban Agglomeration High-Speed Railway Backbone Network Planning: A Case Study of Beijing-Tianjin-Hebei Region, China

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