From Rust to Green? Identifying and Analyzing Green Gentrification in Three Mid-size Midwestern Cities
Abstract Code: 22533
Topics:
Keywords: urban greening, gentrification, social justice, ‘Rust Belt’
Session Type: Paper Abstract
Authors:
Kieran Hogan, University of Vermont
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Abstract
My research aims to explore the complex relationship between urban greening projects in revitalizing cities and gentrification trends. The research focuses on three mid-size post-industrial ‘Rust-Belt’ cities: Buffalo, New York; Cleveland, Ohio; and Toledo, Ohio. All of these cities were deeply divided by racist housing practices and disinvestments in their urban centers, along with significant economic and material decline in the late 20th century. Now, all three cities are engaged in ongoing revitalization projects. Urban greening has become a major component of these efforts, with well-publicized benefits of trees and green space for residents, property values, and business growth. However, the expansion of green space may have negative – and unjust – consequences for economically and racially marginalized communities by sparking rising rents, displacement, and the loss of Black and Latinx community ties. This project seeks to understand the impact urban greening in Rust Belt cities has on neighborhoods, specifically regarding the phenomenon of green gentrification.
This research uses mixed-methods, starting with US Census data from two timeframes (2000 to 2010, and 2010 to 2020) and using GIS to identify census tracts in each city that are at greater risk for gentrification. I’m then using qualitative analysis to explore the urban greening processes occurring during each time frame in and near these neighborhoods. My aim is to discover narratives related to urban greening in each city that can help provide a deeper understanding of the social-spatial-racial interactions causing green gentrification.
From Rust to Green? Identifying and Analyzing Green Gentrification in Three Mid-size Midwestern Cities
Category
Paper Abstract
Description
Submitted By: Kieran Hogan,
krhogan@uvm.edu
Abstract Code: 22533
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