Neighborhood Dynamics and Long‐Term Change

Abstract

Patterns of change in neighborhoods can be discordantly different, even within the same city district. A little understood factor in how urban neighborhoods form and grow is structural inertia, which is the tendency of an urban area to resist change due to its existing physical and socio‐economic fabric. This study explores how patterns of buildings, plots, blocks, and streets affect change or inertia in neighborhoods over time. We integrate Conzenian morphology and space syntax approaches within a geographic information system (GIS) framework to study two historic neighborhoods in Charlotte and Raleigh, N.C. at four points in time over a 96‐year span. Aerial images, historic maps, and GIS sources help to create spatial configuration and building data for each time period. We then analyze these data to identify statistical and map‐pattern morphological and syntactic relationships both in the aggregate and in detail. Our research finds that most of the independent variables of block size, plot size, building footprint, global integration, local integration, and connectivity predicted long‐term change measured in building inventory in almost every occurrence. Our study also suggests design implications and possible future tools and research for measuring change and its relation to the physical characteristics of our cities.