Delineating Intra-Urban Spatial Connectivity Patterns by Travel-Activities: A Case Study of Beijing, China

Travel activities have been widely applied to quantify spatial interactions between places, regions and nations. In this paper, we model the spatial connectivities between 652 Traffic Analysis Zones (TAZs) in Beijing by a taxi OD dataset. First, we unveil the gravitational structure of intra-urban spatial connectivities of Beijing. On overall, the inter-TAZ interactions are well governed by the Gravity Model $G_{ij} = {\lambda}p_{i}p_{j}/d_{ij}$, where $p_{i}$, $p_{j}$ are degrees of TAZ $i$, $j$ and $d_{ij}$ the distance between them, with a goodness-of-fit around 0.8. Second, the network based analysis well reveals the polycentric form of Beijing. Last, we detect the semantics of inter-TAZ connectivities based on their spatiotemporal patterns. We further find that inter-TAZ connections deviating from the Gravity Model can be well explained by link semantics.Comment: 6 pages, 4 figure

Simulating Fleet Noise for Notional UAM Vehicles and Operations in New York

This paper presents the results of systems-level simulations using Metrosim that were conducted for notional Urban Air Mobility (UAM)-style vehicles analyzed for two different scenarios for New York (NY). UAM is an aviation industry term for passenger or cargo-carrying air transportation services, which are often automated, operating in an urban/city environment. UAM-style vehicles are expected to use vertical takeoff and landing with fixed wing cruise flight. Metrosim is a metroplex-wide route and airport planning tool that can also be used in standalone mode as a simulation tool. The scenarios described and reported in this paper were used to evaluate a fleet noise prediction capability for this tool. The work was a collaborative effort between the National Aeronautics and Space Administration (NASA), Intelligent Automation, Inc (IAI), and the Port Authority of New York and New Jersey (PANYNJ). One scenario was designed to represent an expanded air-taxi operation from existing helipads around Manhattan to the major New York airports. The other case represented a farther term vision case with commuters using personal air vehicles to hub locations just outside New York, with an air-taxi service running frequent connector trips to a few key locations inside Manhattan. For both scenarios, the trajectories created for the entire fleet were passed to the Aircraft Environmental Design Tool (AEDT) to generate Day-Night Level (DNL) noise contours for inspection. Without data for actual UAM vehicles available, surrogate AEDT empirical Noise-Power-Distance (NPD) tables used a similar sized current day helicopter as the Baseline, and a version of that same data linearly scaled as a first guess at possible UAM noise data. Details are provided for each of the two scenario configurations, and the output noise contours are presented for the Baseline and reduced noise DNL cases

African gateways : measuring airline connectivity change for Africa's global urban networks in the 2003-2009 period

This paper studies the globalization of major African cities through their changing insertion in global airline networks. As such, the paper adds to a growing body of literature that analyzes the role of infrastructure in the formation of world-city networks. We draw on a rich data source that provides longitudinal airline booking data, which can be directly linked up to the evolution of inter-urban networks at the African and global scale. Our results indicate that Johannesburg remains the major gateway to Africa, but other regional centers and in particular Cairo, Lagos, Casablanca and Nairobi are rapidly complementing Johannesburg in this role. The globalization of African cities is related to rapid network growth on the African continent, but is outrun by fast growth in terms of non-African connections. Among the latter, connections to Asia and the Middle East are rapidly gaining importance. In the end, the paper argues that SouthSouth connections are crucial for an understanding of the contemporary globalization of African cities

Identifying Urban Functional Areas and Their Dynamic Changes in Beijing: Using Multiyear Transit Smart Card Data

A growing number of megacities have been experiencing changes to their landscape due to rapid urbanisation trajectories and travel behaviour dynamics. Therefore, it is of great significance to investigate the distribution and evolution of a city’s urban functional areas over different periods of time. Although the smart card automated fare collection system (SCAFC) is already widely used, few studies have used smart card data to infer information about changes in urban functional areas, particularly in developing countries. Thus, this research aims to delineate the dynamic changes that have occurred in urban functional areas based on passengers’ travel patterns, using Beijing as a case study. We established a Bayesian framework and applied a Gaussian mixture model (GMM) derived from transit smart card data in order to gain insight into passengers’ travel patterns at station level and then identify the dynamic changes in their corresponding urban functional areas. Our results show that Beijing can be clustered into five different functional areas based on the analysis of corresponding transit station functions, namely: multimodal interchange hub and leisure area; residential area; employment area; mixed but mainly residential area; and a mixed residential and employment area. In addition, we found that urban functional areas have experienced slight changes between 2014 and 2017. The findings can be used to inform urban planning strategies designed to tackle urban spatial structure issues, as well as guiding future policy evaluation of urban landscape pattern use

Global production networks in the passenger aviation industry

The idea behind the paper, as well as the empirical data presented in the paper, originate from the research project on the aviation industry in Central and Eastern Europe that was carried out in 2015. The project was funded by the British Academy/Leverhulme Trust (grant no. SG132857). A partial contribution under the same grant code was also made by the Sir Ernest Cassel Educational Trust Fund. The author is grateful to the funding bodies for supporting his research endeavour. The author would also like to thank Dr Nick Spedding from the University of Aberdeen for proofreading the first draft of the paper and providing valuable comments on its contents and the three anonymous reviewers for offering a number of useful suggestions on how to improve the paper.Peer reviewedPostprin