Towards Healthy and Equitable Cities: Assessing the Built Environment's Impact Through GeoAI and Big Data

Rapid urbanisation has brought the relationship between the built environment and public health to the forefront of research. Urban elements such as land use, transport systems, and ecological spaces shape residents’ physical activity and environmental exposure. Studies indicate that the built environment is linked to physical and mental health through complex mechanisms, while the lack of green space, poor spatial quality, and urban heat island effects create spatial inequalities in health risks. The rise of big data and geospatial artificial intelligence (GeoAI) offers powerful tools for advancing this interdisciplinary field. To build more inclusive and healthy cities, it is necessary to promote a shift in research paradigms, using big data and GeoAI to precisely characterise the spatiotemporal patterns of environmental exposure and to identify how the built environment affects population health. Such evidence can underpin targeted interventions and support the creation of community environments that promote health equity.

This Research Topic aims to systematically analyse the urban “built environment–public health” coupling system through emerging big data and GeoAI methods, to accurately identify the complex spatial environmental factors influencing residents’ physical and mental health, ultimately providing quantifiable decision-making support for healthy city planning and policies.

The implementation path includes multi-source big data fusion and high-precision built environment measurement, GeoAI-driven complex mechanism analysis and modelling, and policy scenario simulation and optimisation based on “digital twins.”

This Research Topic welcomes contributions that address the following themes:

• Urban Built Environment Quality Assessment Based on Multi-source Big Data Fusion
• Environmental Exposure and Health Effects Analysis Based on GeoAI
• Mechanisms of the Impact of Complex Urban Built Environments on Residents' Physical Activity
• Health City Policy Analysis and Effectiveness Evaluation
• Application of GenAI in Health City Planning

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review

Keywords: GeoAI, Big Data, Built Environment, Urban Health, Environmental Exposure, Health Equity

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.