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Abstract
Homelessness is a complex and diverse social issue that affects many urban areas in the United States. Robust knowledge of how and where homeless individuals subsist is essential for an assessment of the granular spatiotemporal context of homelessness in a given locale. Common means for surveying homeless rest sites are resource intensive and conducted infrequently, which warrants investigations into complementary approaches. In this article, we examine the spatial patterns of homeless campsites in Portland, Oregon, and their relationship to urban features based on a three-year data set of reports volunteered by members of the public. Our quantitative analysis employs a combination of spatial analysis, statistical methods, and cartographic mapping to determine prevailing spatial patterns and proximity relationships. In that context, we assess the characteristics of the volunteered data in terms of their suitability for capturing expected local patterns of homeless campsites. The data indicate concentrations of reported campsites and significant spatial proximity relationships between campsite locations, zoning, transit stops, and homelessness support services. Our findings evidence the utility of the volunteered data for the analysis of urban homeless campsite locations on an annual basis. We further discuss the limitations of the data and provide suggestions for improvements and future research.
无家可归是一个复杂多样的社会问题, 影响着美国许多城市地区。充分了解无家可归者如何生存以及在何处生存, 对于评估某地无家可归的时空背景至关重要。调查无家可归者休息场所的常用方法需要大量资源并且很少开展这样的调查, 这就需要通过补充方法开展调查。在这篇文章中, 基于公众自愿提供的三年报告数据, 我们研究了俄勒冈州波特兰市无家可归者营地的空间分布, 以及它们与城市特征的关系。我们的定量分析结合空间分析、统计方法和制图, 确定主要空间模式和邻近关系。在此背景下, 我们评估了自愿数据是否适用于获取无家可归者营地的预期局部模式的特点。数据显示了营地的集中度, 以及营地位置、区划、中转站和无家可归者服务站之间的显著空间邻近关系。我们的发现, 证明了用自愿数据去分析每年城市无家可归者营地位置的效用。我们进一步讨论了数据的局限性, 提出了改进和未来研究的建议。
La carencia de hogar es un problema social diverso y de mucha complejidad, que afecta muchas áreas urbanas de los Estados Unidos. Es esencial un conocimiento sólido de cómo y dónde logran subsistir los habitantes de la calle, para evaluar el contexto espaciotemporal granular de la carencia de hogar en una determinada localidad. Los medios comunes para explorar los lugares de acomodación de quienes carecen de techo demandan muchos recursos y son de aplicación infrecuente, lo cual justifica la consideración de enfoques complementarios. En este artículo, examinamos los patrones espaciales de los campamentos adaptados por habitantes de la calle en Portland, Oregón, y la relación que esos lugares tienen con los rasgos urbanos, a partir de un conjunto de datos de tres años de informes contribuidos por miembros del público. Nuestro análisis cuantitativo emplea una combinación de análisis espacial, métodos estadísticos y cartografía para determinar los patrones espaciales prevalentes y las relaciones de proximidad. En ese contexto, evaluamos las características de los datos contribuidos voluntariamente en términos de su idoneidad para captar los patrones locales que se anticipan sobre los campamentos de esa gente sin hogar. Los datos indican concentraciones de campamentos declarados y relaciones de proximidad significativas entre las locaciones de los campamentos, la zonificación, los paraderos del tránsito y los servicios de ayuda para los habitantes de la calle. Nuestros hallazgos demuestran la utilidad de los datos contribuidos voluntariamente en el análisis de las locaciones de campamentos urbanos de quienes carecen de techo sobre una base anual. Discutimos un poco más sobre las limitaciones de los datos y presentamos sugerencias para su mejora, y para investigaciones futuras.
Acknowledgments
We thank the editor and two anonymous reviewers for their support and constructive comments throughout the peer review process. Their substantial feedback helped us to improve the clarity and overall quality of the article and provided valuable considerations for future research.
Notes
1 This is further described at https://www.portlandoregon.gov/toolkit/article/562214.
2 For the time period considered here, 2017 was a PIT count year.
3 Contributions by the public have increased over the years, as follows: 4,663 reports in 2016, 21,105 reports in 2017, and 27,439 reports in 2018.
5 As of 4 October 2020.
12 Drive Away Hunger; see https://www.driveawayhunger.org/.
14 A peak in statistical significance yet lower spatial autocorrelation occurred at 10,500 feet, about two miles (Moran’s I = 0.11, z = 87.79, p < 0.001).
16 It is worth noting that chi-square statistics are exhibiting sensitivity to both small and large sample sizes (Bergh Citation2015), which warrants moderation in terms of the reliance on results with high statistical significance, which we aimed at applying throughout our analysis.
17 The factors reported here are based on the quotient of observed counts and expected counts for the MUR zoning category and the quotient of expected counts and observed counts for the SFR zoning category.
Additional information
Notes on contributors
Martin Swobodzinski
MARTIN SWOBODZINSKI is an Assistant Professor in the Department of Geography at Portland State University, Portland, OR 97201. E-mail: [email protected]. His scholarship explores individual choice making at the intersection of spatial technology, information, and data. His current research focuses on empirical evaluations of human wayfinding in the specific context of visual impairment and blindness.
Krystle Harrell
KRYSTLE HARRELL is an Instructor in the Department of Geography and Environmental Engineering, United States Military Academy at West Point, West Point, NY 10996. E-mail: [email protected]. Her research interests include cartography, GIScience, and the application of spatial analysis to urgent questions of human and urban geography.