Research Topic

Emerging Data and Urban Modelling

About this Research Topic

Urbanization has increased around the world. According to the United Nations Secretariat, 55% of the global population has been living in cities since 2018. Cities are not only complex systems, but also face constant challenges in planning, transportation, energy, and the environment. To ensure sustainable urban development, scholars from different disciplines have conducted research to address such issues. But no agreed theory and method have been proposed.

In recent years, the growing popularity of the internet and location-based service (LBS) has led to the convergence of the virtual and physical world. Individual-level, multi-source and spatio-temporal data have been produced. Such data include points of interest, GPS trajectories, smart cards, mobile phones, social media, street view images, and so on. They offer a new solution in bottom-up modelling for urban research. Urban computing utilizes spatio-temporal big data and integrates multi-disciplinary fields to explore frameworks to solve problems in cities. The intersection of computer science, data science, remote sensing science, and geographic information science has made urban computing possible, offering a new paradigm for big data research to realize scientific, social, and commercial values.

The objective of this Research Topic is to model complex urban systems and to solve problems in cities using novel data and intelligent approaches. We welcome contributions that explore the following:
- Novel model development for the urban dynamic system;
- Machine learning and artificial intelligence in urban computing;
- Innovative patterns of urban mobility, urban residents’ mobility and activities;
- Environmental problems related to urban systems and residents;
- Intra-urban and extra-urban transportation demand and patterns;
- Emerging urban variable acquisition and quantification, multidimensional urban sensing;
- High-performance spatial intelligence computing approaches for increasing computational accuracy and efficiency.


Keywords: Urban Computing, Computer Science, Data Science, Remote Sensing, Big Data, Data and Intelligence, Urban Dynamic System, Machine Learning, Artificial Intelligence, Geographic Information Science, Urban Mobility, Urban Transport


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Urbanization has increased around the world. According to the United Nations Secretariat, 55% of the global population has been living in cities since 2018. Cities are not only complex systems, but also face constant challenges in planning, transportation, energy, and the environment. To ensure sustainable urban development, scholars from different disciplines have conducted research to address such issues. But no agreed theory and method have been proposed.

In recent years, the growing popularity of the internet and location-based service (LBS) has led to the convergence of the virtual and physical world. Individual-level, multi-source and spatio-temporal data have been produced. Such data include points of interest, GPS trajectories, smart cards, mobile phones, social media, street view images, and so on. They offer a new solution in bottom-up modelling for urban research. Urban computing utilizes spatio-temporal big data and integrates multi-disciplinary fields to explore frameworks to solve problems in cities. The intersection of computer science, data science, remote sensing science, and geographic information science has made urban computing possible, offering a new paradigm for big data research to realize scientific, social, and commercial values.

The objective of this Research Topic is to model complex urban systems and to solve problems in cities using novel data and intelligent approaches. We welcome contributions that explore the following:
- Novel model development for the urban dynamic system;
- Machine learning and artificial intelligence in urban computing;
- Innovative patterns of urban mobility, urban residents’ mobility and activities;
- Environmental problems related to urban systems and residents;
- Intra-urban and extra-urban transportation demand and patterns;
- Emerging urban variable acquisition and quantification, multidimensional urban sensing;
- High-performance spatial intelligence computing approaches for increasing computational accuracy and efficiency.


Keywords: Urban Computing, Computer Science, Data Science, Remote Sensing, Big Data, Data and Intelligence, Urban Dynamic System, Machine Learning, Artificial Intelligence, Geographic Information Science, Urban Mobility, Urban Transport


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

25 January 2021 Manuscript
24 February 2021 Manuscript Extension

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

25 January 2021 Manuscript
24 February 2021 Manuscript Extension

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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