“They Didn’t See It Coming”: Green Resilience Planning and Vulnerability to Future Climate Gentrification
Open accessAbstract
As cities strive to protect vulnerable residents from climate risks and impacts, recent studies have identified a challenging link between these measures and gentrification processes that reconfigure, but do not necessarily eliminate, climate insecurities. Green resilient infrastructure (GRI) may especially increase the vulnerability of lower income communities of color to gentrification, an issue that remains underexplored. Drawing on the forerunner green city of Philadelphia, Pennsylvania, as our case study, this article adopts a novel intersectional approach to assess overlapping and interdependent factors in generating vulnerability and resilience using spatial quantitative data and qualitative interviews with community-based organizers, nonprofits, and municipal stakeholders. More specifically, this article develops a new methodology to assess vulnerability to future climate gentrification and contributes to debates on the role of urban development, housing, and sustainability practices in climate justice dynamics. It also informs strategies that can reduce social and racial inequities in the context of climate adaptation planning.
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The majority of FEMA-funded buyouts were found to be located outside of zones that HOLC had assessed. For the areas HOLC had graded in historic urban cores, most buyouts were located in redlined districts.
“In another study, the majority of FEMA-funded buyouts were found to be located outside of zones that HOLC had assessed.For the areas HOLC had graded in historic urban cores, most buyouts were located in redlined districts.201”
From NPCC4: Advancing climate justice in climate adaptation strategies for New York City (2024) · cites this paper as [201]
Researchers have found significant links between climate risks, adaptation investments, housing, socioeconomic inequalities, and residential migration and displacement.
“Researchers have found significant links between climate risks, adaptation investments, housing, socioeconomic inequalities, and residential migration and displacement.”
From NPCC4: Advancing climate justice in climate adaptation strategies for New York City (2024) · cites this paper as [251]
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NPCC4: Advancing climate justice in climate adaptation strategies for New York City
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A Multi-Hazard Climate, Displacement and Socio-Vulnerability Score for New York City
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- Authors
- Shokry, G., Anguelovski, I., Connolly, J. J. T., Maroko, A., & Pearsall, H.
- Affiliations
- Universitat Autònoma de Barcelona (ES)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- The Graduate Center, CUNY (US)
- Temple University (US)
- Corresponding author
- Shokry, Galia
- Venue
- Housing Policy Debate
- Publisher
- Informa UK Limited
- Published
- 2021-09-10
- Volume
- 32
- Issue
- 1
- Pages
- 211-245
- ISSN
- 1051-1482 (ISSN-L)
- 2152-050X
- OpenAlex
- W3201059507
- Cited by
- 89
- References
- 162
- Citations by year
- 2026: 21 · 2025: 24 · 2024: 21 · 2023: 13 · 2022: 9 · 2021: 1
- FWCI
- 15.24
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Housing Policy Debate (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona) (submittedVersion, cc-by)
- Funders
- European Research Council (GA678034)
- Horizon 2020 Framework Programme (730243, 822357)
- Topics
- Social Sciences › Sociology and Political Science › Environmental Justice and Health Disparities
- Social Sciences › Urban Studies › Urban Planning and Governance
- Physical Sciences › Environmental Science › Global and Planetary Change › Sustainability and Climate Change Governance
- Keywords
- climate gentrification, climate change vulnerability, climate justice, intersectionality, communities of color, low-income communities, climate adaptation planning, urban development, housing, Philadelphia, racial inequity, social inequities
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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