Neighborhoods are the key analytical unit of cities, and while neighborhoods change over time, the lines used to study them generally do not. Standard units stabilize analysis and administration but implicitly conflate analytical or administrative convenience with the structuring forces of the city. Material urban form tells a different story. Street networks, plot arrangements, enclosure patterns, and building configurations cohere into a durable (though mutable) urban morphology that sorts accessibility, capital flows, and opportunity. The defining features of urban form (edges, corridors, districts, etc.) often align with social, political, and economic divergence, but the correspondence is uneven because state policy and capital concentrate where returns and political feasibility are highest. The result is an urban palimpsest in which obdurate urban form interacts with fluid governance and finance to produce urban change (such as gentrification) in regularized patterns.
Urban research lacks an integrated methodological and conceptual framework that can empirically distinguish when (and to what degree) neighborhood change is structured by urban morphology and when it is produced by political-economic processes, particularly at the level of neighborhood boundaries and edges. This proposed dissertation extends case-based morphometric findings by making boundaries the primary object of study and by modeling how urban form and the real estate state co-produce outcomes at neighborhood edges.
Two strands of scholarship anchor this project. First, quantitative work that delineates areal units from urban form shows that morphologically defined clusters and their edges frequently coincide with demographic and socioeconomic contrasts. Second, the fringe-belt tradition offers a robust explanation for the persistence of certain urban edges: growth pauses at the urban edge produce fringe belts along “fixation lines” that accumulate morphologically distinct elements. Together these literatures justify treating edges not only as cartographic or administrative artifacts but as structural urban formations that shape (and are shaped by) flows of policy intervention and capital investment.
Empirically, this dissertation asks: how do quantitative measures of urban form in Chicago – operationalized via Fleischmann et al.’s Hierarchical Morphotope Classification (HiMoC) – delineate neighborhood boundaries, and what do the resultant boundary patterns reveal about the relationship between morphology, neighborhood stability/change, and political–economic processes?
The study proceeds in three steps. The first compares HiMoC-derived boundaries with administrative and conceptual areal units to test whether built form provides a more accurate basis for analyzing change. The second evaluates correspondence by testing whether minimally aggregated socioeconomic indicators align more clearly within HiMoC boundaries than within administrative units, clarifying when patterns follow morphological boundaries versus cutting across them. The third interprets the preceding outcomes to identify when the built environment structures trajectories and when state policy and capital—Stein's “real estate state”—reinforce, redirect, or erode them.
The expected contributions of this project are also threefold. Conceptually, the project integrates urban morphometrics with political economy to show how historically constituted areal delineations condition the reach and efficacy of real estate state policy instruments. Empirically, it distinguishes where patterns of neighborhood change in Chicago are more tightly coupled to inherited (structural) urban form vs. state policy and its related coalitions. Methodologically, it advances a boundary analysis framework, combining morphology-aligned units, edge detection, and multi-scale sensitivity tests. The result will be a clearer account of where and under what configurations some boundaries persist as “fault lines” while others blur under spatially selective state action, and an applied toolkit for measuring boundary agreement, edge effects, and aggregation bias.
