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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2026
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2601.15675 |
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| _version_ | 1866915746891694080 |
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| author | Usman, Rehinatu Okeke, Onyedikachi J. |
| author_facet | Usman, Rehinatu Okeke, Onyedikachi J. |
| contents | This study develops an integrated, intersectional climate vulnerability assessment for Greensboro, North Carolina, a midsize city in the rapidly changing American Southeast. Moving beyond generalized mapping, we combine demographic, socioeconomic, health, and environmental data at the census tract level to identify neighborhoods where flood exposure, chronic health burdens, and social disadvantage spatially converge. Through k-means and hierarchical clustering, we identify four distinct neighborhood typologies, including a critically high-risk cluster characterized by high flood exposure, extreme poverty, poor respiratory health, and aging housing. The findings demonstrate that climate-related risks are not randomly distributed but systematically cluster in historically marginalized communities, revealing a clear environmental justice disparity. This place-based typology approach provides a targeted framework for policymakers to design integrated interventions that bridge flood management, public health, housing, and social services to build equitable urban resilience |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_15675 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Climate Vulnerability and Community Health: Identifying Greensboro Neighborhoods at Intersectional Risk Usman, Rehinatu Okeke, Onyedikachi J. Applications This study develops an integrated, intersectional climate vulnerability assessment for Greensboro, North Carolina, a midsize city in the rapidly changing American Southeast. Moving beyond generalized mapping, we combine demographic, socioeconomic, health, and environmental data at the census tract level to identify neighborhoods where flood exposure, chronic health burdens, and social disadvantage spatially converge. Through k-means and hierarchical clustering, we identify four distinct neighborhood typologies, including a critically high-risk cluster characterized by high flood exposure, extreme poverty, poor respiratory health, and aging housing. The findings demonstrate that climate-related risks are not randomly distributed but systematically cluster in historically marginalized communities, revealing a clear environmental justice disparity. This place-based typology approach provides a targeted framework for policymakers to design integrated interventions that bridge flood management, public health, housing, and social services to build equitable urban resilience |
| title | Climate Vulnerability and Community Health: Identifying Greensboro Neighborhoods at Intersectional Risk |
| topic | Applications |
| url | https://arxiv.org/abs/2601.15675 |