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Big Data, Complexity Theory and Urban Development: Challenges and Opportunities
We are living in the era of cities: more than 50% of the world population is already living in urban areas, and most forecasts indicate that, by the end of this century, the world’s population will be almost entirely urban. In this context, there is an emerging view that the global challenges of poverty eradication, […]
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The role of data in the new Sustainable Mobility Law in Spain
Following its approval by the Council of Ministers, Spain’s Sustainable Mobility Law (SML) is now in its second attempt to complete its processing. This law brings many innovations, including new planning instruments, financing mechanisms for public transport, test environments for mobility innovations, etc. Beyond these matters, the SML also addresses the growing prominence of data […]
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Short-haul flights in Spain: is high-speed rail an alternative?
The aviation sector accounts for 2-3% of CO2 emissions globally and 4% of CO2 emissions in Europe, according to the “Fly the Green Deal” report, prepared by the European Commission in 2022. Climate change mitigation strategies include measures to reduce emissions from air transport, either by increasing the efficiency of flights or by promoting modal […]
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The least used station of Rodalies in Barcelona: Borgonyà
Earlier this year we started a series of posts looking at the least used stations of the Spanish Renfe commuter railway systems (known as Cercanías Renfe). The aim of this initiative — inspired by the series of Youtube videos from Geoff Marshall — is to illustrate how the combination of different mobility data sources can […]
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The least used station of Cercanías Madrid: San Yago
The combination of different mobility data sources has helped us analyse the least used station in the Madrid commuter railway system: San Yago.
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Using Machine Learning to predict sociodemographic characteristics
Mobile phone data has become a fundamental tool to extract the mobility patterns of the population. However, some sociodemographic information about the mobile phone users is sometimes missing or that available is not always reliable. For instance, many customers do not provide information about their age or gender, while others have been assigned wrong values […]
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Transport models and mobile phone data
Let’s have a look first at the use of mobile phone data on our existing models. We have been operating very consistent types of transport models for the last 50 years with some more recent modest innovations. Classic transport models can operate at different levels of analysis: aggregate and disaggregate trips, tours and activities; all […]
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Specifying mobile phone trip matrices
This section deals with how best to specify the desired trip matrices from mobile phone and other data. In my own experience, with our own mobile phone products and those from other suppliers, a careful specification of what is needed is key to obtain usable trip matrices. All suppliers of this type of trip matrices […]
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The accuracy of mobile phone trip matrices
There have been a number of studies comparing mobile phone based trip matrices with those obtained from other sources, mostly household surveys. Just searching “validation of mobile phone trip matrices” yields a large number of papers and reports. Most of them praise the advantages of mobile phone data to generate mobility information: passive data collection, […]
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The limitations of mobile phone data
Limited granularity First of all, normally, the granularity of the geo-location is limited by the size of the mobile phone cells, and the granularity of the time-stamps is limited by the frequency of the transactions between mobile phone and antennas (BTS). These two constraints make it impossible to accurately identify the start and end time […]