Abstract
Skid Row in Los Angeles serves as a poignant illustration of “asocial forms” within our urban landscapes. Historically isolated from the larger city fabric, Skid Row exemplifies housing inequalities and the challenges of fostering social interactions amid predominant urban isolation. Policies over the decades have further entrenched this isolation, resulting in a neighborhood marked by transient tent settlements and pronounced homelessness. This study, rooted in a social justice perspective, employs machine learning to analyze satellite imagery from 2010 to present, tracing the evolving spatial patterns of these tent formations. Through this lens, we gain a nuanced understanding of how the community utilizes space, marking areas that have become focal points for tents and shelters. Complemented by an in-depth review of housing policies, police raids, and on-ground interviews, the research paints a comprehensive picture of Skid Row’s spatial dynamics. The findings underscore a stark narrative: despite the city’s growth and development, Skid Row’s tent settlements have proliferated, underscoring the failure of interventions to address root causes of homelessness. As urban designers and policymakers grapple with “asocial forms,” Skid Row stands as a testament to the urgent need for reimagined urban spaces that foster social connections, inclusivity, and spatial justice.
Presenters
Taraneh MeshkaniAssistant Professor, Architecture and Urban Design, Kent State University, Ohio, United States
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
2024 Special Focus—Asocial Forms: Reconfiguring Possibilities of Urban Space
KEYWORDS
Skid Row, Asocial forms, Machine learning, Housing inequalities, Spatial justice
Digital Media
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