PhD Oral Exam - Omar Ortiz Meraz, Geography, Urban and Environmental Studies

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

Abstract Title: Inherited residential landscapes and accessibility to essential services in Montréal: An analytical framework for detection, characterization and classification of residential spatial configurations and their impacts on accessibility by foot to daily necessities. Omar Ortiz Meraz Concordia University, 2026 In North America and beyond, forms of urbanization predicated on automobility have prevailed over the last century. Such context favoured large-scale dispersion of low-intensity urban functions over vast territories and the alteration of preexisting spatial and functional dynamics, which entailed a heavy environmental toll. Understanding the webs of interactions between urban and land-use spatial configurations and transportation is crucial in the fight against and adaptation to climate change and other environmental crises. Using the Montréal metropolitan area as a field of study, and mobilizing methods from urban morphology, geographic information science, and spatial analysis, this research develops a new interpretative framework aimed, firstly, at detecting characterizing and classifying internally cohesive residential regions based on their street network and block geometry. Then, secondly, to experiment with that spatial framework while analyzing regions' behaviour and performance in granting potential access to essential services on foot within 15 minutes. An algorithm informed by means of network analysis, linear algebra, and multivariate analysis supports a largely automated regionalization procedure predicated on the behaviour of a reduced set of geometrical indicators to generate Morphological Neighbourhood Regions (MNR). MNR detection (MNRDet) produces an empirically informed partitioning that addresses important theoretical and methodological limitations that restrain the ability to account for urban form specificities and variability, including within the same city. Montréal’s diverse residential landscape was characterized against the MNR framework. Street network morphological indicators were processed using principal component analysis and a probabilistic classification, which unveiled 8 eight classes. Street networks constitute a spatial structure that informs the ways in which space is practised by the inhabitants, notably by enabling or constraining mobility, including walkability, hence conditioning access to services and amenities on the local scale and beyond. MNR accessibility performance was measured within and across classes, while assessing the morphological conditions in which high accessibility is observed. The novel spatial framework proved a potent tool to help untangle how specific morphological characteristics are interacting with land-use composition and spatial distribution whilst impacting accessibility, hence opening new avenues towards a better and more specific understanding of these complex urban spatial dynamics.