2016 Smart Cities Symposium Prague (SCSP) 2016
DOI: 10.1109/scsp.2016.7501029
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The transportation accessibility and residential mobility in the Prague Metropolitan Area

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Cited by 4 publications
(3 citation statements)
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“…The first, from the urban informatics field, involves the use of data to measure effects on residential mobility or outcomes. This includes using objective indicators such as population, economics, and transportation (e.g., travel time and distance to work) [31]; land use and transportation accessibility [32]; the distance between residential areas and infrastructure [33]; health status [34]; population and population aging; poverty [35]; and income level [36]. Studies using these indicators have the advantage of explaining population movement between cities by way of long-term case studies, and such research has been conducted in multiple cities.…”
Section: Subjective Indicators For the Evaluation Of Neighborhood Envmentioning
confidence: 99%
“…The first, from the urban informatics field, involves the use of data to measure effects on residential mobility or outcomes. This includes using objective indicators such as population, economics, and transportation (e.g., travel time and distance to work) [31]; land use and transportation accessibility [32]; the distance between residential areas and infrastructure [33]; health status [34]; population and population aging; poverty [35]; and income level [36]. Studies using these indicators have the advantage of explaining population movement between cities by way of long-term case studies, and such research has been conducted in multiple cities.…”
Section: Subjective Indicators For the Evaluation Of Neighborhood Envmentioning
confidence: 99%
“…However, discrete-choice models are unable to integrate different sizes and attractiveness of individual targets, as opposed to what is available with gravity models using generalised distance-decay functions (e.g., [27]), sometimes also combined with a Huff model ( [65][66][67]). Both models are based on zones, typically TAZ ( [7,68]). A common shortcoming of zonal models is that they cannot fully utilise individual point-based targets and their properties, such as location, capacity, and time window and constraints, to improve the accuracy of transport modelling.…”
Section: Zonal Model Considerationsmentioning
confidence: 99%
“…Accelerating the construction of a complete and unified modern comprehensive transportation system and forming the main skeleton of a rapid transportation network connecting all urban nodes has become the key to realizing regional economic integration [2] . Currently, scholars at home and abroad have conducted fruitful research on traffic accessibility and network spatial pattern, and their research results mainly focus on the following aspects: ① Spatial coupling analysis of traffic accessibility or traffic network on tourism or other industries [3][4][5] , which provides suggestions for the optimized development of industries in target regions or city clusters by study economic benefits of various industries such as tourism and culture; for example,Jiang, HN and other scholars take Shanghai as the study area and Japanese electronic information manufacturing enterprises as the samples, and use kernel density estimation and Poisson regression model to explore the influence of transportation accessibility on the location choice of enterprises, and they believe that there is a significant spatial coupling between the distribution of enterprises and the transportation accessibility, and that Japanese wholly-owned enterprises are more inclined to select the area with better transportation accessibility compared with the joint-venture enterprises [6] .②Analysis of the influence mechanism of traffic accessibility on the spatial spillover effect or linkage measure of the economy in each region [7][8][9] ; for example, in the study of regional economic performance in Europe by Freiria [10] and other scholars, it was found that the overall traffic road network density and accessibility were positively correlated with regional performance, while there were large differences in local spatial correlations;③Urban layout analysis based on transportation network in order to propose relevant optimization suggestions for urban development [11][12][13] . Hiroyuki [14] and others analyzed the impact of rail accessibility on the distribution of firms in the Washington, D.C., metropolitan area.…”
Section: Introductionmentioning
confidence: 99%