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Author: search.filters.author.Eduardo Graells-GarridoSubject: search.filters.subject.urban planning

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    Adoption-Driven Data Science for Transportation Planning: Methodology, Case Study, and Lessons Learned
    (2020)
    Eduardo Graells-Garrido
    ;
    Vanessa Peña-Araya
    ;
    BRAVO CELEDÓN, MARÍA LORETO  
    The rising availability of digital traces provides a fertile ground for data-driven solutions to problems in cities. However, even though a massive data set analyzed with data science methods may provide a powerful and cost-effective solution to a problem, its adoption by relevant stakeholders is not guaranteed due to adoption barriers such as lack of interpretability and interoperability. In this context, this paper proposes a methodology toward bridging two disciplines, data science and transportation, to identify, understand, and solve transportation planning problems with data-driven solutions that are suitable for adoption by urban planners and policy makers. The methodology is defined by four steps where people from both disciplines go from algorithm and model definition to the development of a potentially adoptable solution with evaluated outputs. We describe how this methodology was applied to define a model to infer commuting trips with mode of transportation from mobile phone data, and we report the lessons learned during the process.
    Scopus© Citations 6  3
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    A physiology-inspired framework for holistic city simulations
    (2022)
    Irene Meta
    ;
    Fernando M. Cucchietti
    ;
    Diego Navarro-Mateu
    ;
    Eduardo Graells-Garrido
    ;
    Vicente Guallart
      7Scopus© Citations 10
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    Measuring the local complementarity of population, amenities and digital activities to identify and understand urban areas of interest
    (2022)
    Eduardo Graells-Garrido
    ;
    Rossano Schifanella
    ;
    OPITZ OPITZ, DANIELA PIERINA  
    ;
    Francisco Rowe
    Identifying and understanding areas of interest are essential for urban planning. These areas are normally defined from static features of the resident population and urban amenities. Research has emphasised the importance of human mobility activity to capture the changing nature of these areas throughout the day, and the use of digital applications to reflect the increasing integration between material and online activities. Drawing on mobile phone data, this paper develops a novel approach to identify areas of interest based on the degree of complementarity of digital activities, available amenities and population levels. As a case study, we focus on the largest urban agglomeration of Chile, Santiago, where we identify three distinctive groups of areas: those concentrating (1) high availability of amenities; (2) high diversity of amenities and digital activities; and (3) areas lacking amenities, yet, presenting high usage of digital leisure and mobility applications. These findings identify areas where digital activities and local amenities play a complementary role in association with local population levels, and provide data-driven insights into the structure of material and digital activities in urban spaces that may characterise large Latin American cities.
      3Scopus© Citations 6