Abstract

Enhancing CityGML with the Built Environment End-users’ Inputs

Farzaneh Zarei, Ph.D.
Concordia University, 2025

Digitalization of infrastructure (also known as smart infrastructure or ‘smart city’) is based upon capturing and analyzing urban data and providing decision-makers with real-time analytics and insights. However, since some features of the built environment, such as citizens’ comfort, cannot be solely measured by physical sensors, there is a need for alternative tools and methods to evaluate such aspects and record the results. This exposes a key gap in current digital infrastructure models: the lack of integration between physical infrastructure data and the subjective experiences of service users.
To address this gap, this dissertation explores the following research questions:
1. How can end-user perspectives be systematically integrated into 3D city models to better represent the performance of urban infrastructure?
2. What kind of data schema and semantic structure are required to link social, technical, and spatial data in a standardized, extensible manner?
3. Can such integration support practical, socially-aware decision-making in urban planning?
With these questions in mind, the dissertation proposes a new Application Domain Extension (ADE) —the Social ADE — that enables the integration of urban data streams from both internal (e.g., decision-makers) and external (e.g., infrastructure users) stakeholders into 3D city models. The Social ADE is designed to be universal and applicable across various domains of the built environment. However, this dissertation focuses on two transportation-related case studies to validate the approach, primarily due to the availability of relevant, high-quality data.
The first case study examines acoustic comfort at bus stops by integrating static (geometrical and spatial), dynamic (noise levels via mobile phones), and subjective (survey-based comfort ratings) data. The second case study presents a GIS-based method for prioritizing pothole repairs by combining technical road condition data with citizen-reported concerns to uncover latent patterns in past decision-making.
The results demonstrate that the Social ADE enables meaningful linkage between the built environment and user experiences, supporting the generation of socially-informed, human-centered insights. This research contributes a novel data integration framework that enhances the capacity of city digital twins to support inclusive and adaptive urban infrastructure planning, especially in the transportation sector.