Dynamic Accessibility using Big Data: The Role of the Changing Conditions of Network Congestion and Destination Attractiveness

Moya-Gómez, Borja; Salas-Olmedo, María Henar; Palomares, Juan Carlos García; Gutiérrez, Javier

doi:10.1007/s11067-017-9348-z

Cited by 80 publications

(80 citation statements)

References 41 publications

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“…Regarding the employment rate, people move into the business areas that are defined by higher income rates and more job opportunities [47]. Some researchers believe that the impact of population dynamics indeed comes from the city's economy and urbanisation characteristics [20,48], but some people believe that accessibility incites more changes in the population [49][50][51][52]. Research into population dynamics has also found that the population and employment rate were observed to have a higher growth rate due to HSR services [45].…”

Section: Population Dynamicsmentioning

confidence: 99%

Does High-Speed Rail Influence Urban Dynamics and Land Pricing?

2020

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At present, many countries around the world have significantly invested in sustainable transportation systems, especially for high-speed rail (HSR) infrastructures, since they are believed to improve economies, and regenerate regional and business growth. In this study, we focus on economic growth, dynamic land use, and urban mobility. The emphasis is placed on testing a hypothesis about whether HSRs can enable socio-economic development. Real case studies using big data from large cities in China, namely Shanghai province and Minhang districts, are taken into account. Socio-technical information such as employment rate, property pricing, and agglomeration in the country's economy is collected from the China Statistics Bureau and the China Academy of Railway Sciences for analyses. This research aims to re-examine practical factors resulting from HSR's impact on urban areas by using ANOVA analysis and dummy variable regression to analyse urban dynamics and property pricing. In addition, this study enhances the prediction outcomes that lead to urban planning strategies for the business area. The results reveal that there are various effects (i.e., regional accessibility, city development plans, and so on) required to enable the success of HSR infrastructure in order to enrich urban dynamics and land pricing. This paper also highlights critical perspectives towards sustainability, which are vital to social and economic impacts. In addition, this study provides crucial perspectives on sustainable developments for future HSR projects.

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Section: Population Dynamicsmentioning

confidence: 99%

Does High-Speed Rail Influence Urban Dynamics and Land Pricing?

2020

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“…La variación temporal de este segundo componente ha sido ignorada en la mayor parte de los estudios dinámicos de accesibilidad. La consideración conjunta de las dos fuentes de variación temporal, ya se trate de transporte público (Boisjoly y ElGeneidy, 2016) o privado (Moya-Gómez et al, 2017), ofrece resultados más realistas y permite analizar el impacto de cada uno de los dos componentes (tiempos de viaje y capacidad de atracción de los destinos) por medio de la construcción de escenarios de evaluación.…”

Section: Análisis De Accesibilidadunclassified

Big Data y nuevas geografías: la huella digital de las actividades humanas

Puebla

2018

dag

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ResumenEl término Big Data se ha popularizado en los últimos años y hace referencia a la producción de cantidades ingentes de datos. La actividad humana es captada a través de múltiples redes de sensores y dispositivos, dejando por tanto una huella digital. El análisis de esta huella digital tiene un gran potencial para la investigación geográfica del comportamiento humano. En este artículo se describen las principales características del Big Data y se destaca la importancia de los datos masivos para la ciencia y particularmente para la Geografía, centrando la atención en el estudio de los patrones espacio-temporales de la actividad humana. Palabras clave: Big Data; datos geolocalizados; comportamiento humano Resum. Big Data i noves geografies: l'empremta digital de les activitats humanesEl terme Big Data s'ha popularitzat en els últims anys i fa referència a la producció de quantitats ingents de dades. L'activitat humana és captada a través de múltiples xarxes de sensors i dispositius i, per tant, deixa una empremta digital. L'anàlisi d'aquesta empremta digital té un gran potencial per a la investigació geogràfica del comportament humà. En aquest article es descriuen les principals característiques del Big Data i es destaca la importància de les dades massives per a la ciència i, particularment, per a la Geografia, centrant l'atenció en l'estudi dels patrons espaciotemporals de l'activitat humana. Paraules clau: Big Data; dades geolocalitzades; comportament humà * Este artículo se basa parcialmente en la conferencia «Big Data y nuevas geografías», pronunciada en la Universidad Autónoma de Barcelona en 2017, y en la ponencia «El uso del Big Data en la investigación de la ciudad, la movilidad y el turismo», presentada en el XXV Congreso de la Asociación de Geógrafos Españoles. Résumé. Big Data et nouvelles géographies : l'empreinte digitale des activités humainesLe terme Big Data est devenu populaire ces dernières années et il se réfère à la production d'énormes quantités de données. L'activité humaine est captée par une multitude de réseaux de capteurs et de dispositifs, laissant ainsi une empreinte digitale. L'analyse de cette empreinte présente un grand potentiel pour l'étude géographique du comportement humain. Cet article décrit les principales caractéristiques du Big Data et il souligne l'importance des données massives pour la science et en particulier pour la géographie, en se concentrant sur l'étude des modèles spatio-temporels de l'activité humaine. Mots-clés: Big Data; données géolocalisées; comportement humain Abstract. Big data and new geographies: The digital footprint of human activityThe term 'big data' has become popular in recent years and refers to the production of huge amounts of data. Human activity is captured through multiple networks of sensors and devices, thus leaving a digital footprint. The analysis of this digital footprint has a great potential for geographical research on human behavior. This article describes the main characteristics of big data and highlights the importance of m...

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“…The use of new data sources enables time-sensitive accessibility analysis in ArcGIS (for recent application see Moya-Gómez et al 2017). This trend will be followed with a test implementation of General Transit Feed Specification (GTFS) data in combination with an OSM pedestrian network for the TUM Accessibility Atlas in the near future, allowing for a detailed accessibility analysis at different times of day.…”

Section: Expanding the Scope Of Analysismentioning

confidence: 99%

The TUM Accessibility Atlas: Visualizing Spatial and Socioeconomic Disparities in Accessibility to Support Regional Land-Use and Transport Planning

Büttner

Kinigadner

et al. 2018

Netw Spat Econ

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In recent years, the city of Munich has become more crowded due to its strong job market and its popularity as a tourist destination, resulting in a shortage of affordable housing and a strained transport network. It became evident that the city of Munich could not solve these problems alone, and would need close cooperation with neighboring municipalities that considered the various stakeholders. In 2007, this resulted in the formation of the Metropolitan Region of Munich, home to nearly six million people from 27 counties and 6 large cities, and includes 158 participating institutions. In 2009, the TUM Accessibility Atlas was developed for this newly formed region after numerous discussions with a variety of regional stakeholders who described their needs in assessing land-use and transport measures. The major task of this tool was to meet these needs and support this diverse region find a common regional identity.Keywords Accessibility . Accessibility instruments . PSS . Governance . Decisionmaking . Accessibility planning The TUM Accessibility Atlas brings together various scientific measures of accessibility that have been developed over time and applies them to relevant issues in the field of integrated land use and transport planning. The primary usability issue addressed by this tool is the need for more trust and a shared language between stakeholders. The main planning issue is determining how the region can improve multimodal accessibility, becoming more environmentally sustainable while also identifying spatial and socioeconomic disparities to address. Given these purposes, the TUM Accessibility Atlas was set up as a GIS toolbox, capable of producing maps for specific case studies and their thematic issues. The two major datasets are a multi-modal transport network and the structural land-use layers. The public transport network is based on a VISUM transport model imported into a GIS based accessibility instrument. Initially, the street network was initially provided by the Bavarian State Office for Statistics and Data Processing, but later substituted by OpenStreetMap (OSM), due to the flexibility of the open source data and the greater detail available for non-motorized transport modes. The structural component was provided by numerous sources (e.g. gaining suitable data by web survey) which included geo-referenced data on activities and their respective densities. These datasets have been constantly updated and upgraded in line with the current issues of different areas. Over the course of various research projects, new scales and suitable add-on tools have been added. To help visualize spatial and socioeconomic disparities, the TUM Accessibility Atlas has explored the relative accessibility of the region by public vs private transport, mismatches between the population density and public transport service quality, and the vulnerability of the region to future increases in mobility costs. Different methods and scales have been integrated: from micro-scale accessibility within neighborhood...

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Dynamic Accessibility using Big Data: The Role of the Changing Conditions of Network Congestion and Destination Attractiveness

Cited by 80 publications

References 41 publications

Does High-Speed Rail Influence Urban Dynamics and Land Pricing?

Does High-Speed Rail Influence Urban Dynamics and Land Pricing?

Big Data y nuevas geografías: la huella digital de las actividades humanas

The TUM Accessibility Atlas: Visualizing Spatial and Socioeconomic Disparities in Accessibility to Support Regional Land-Use and Transport Planning

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