Abstract Urban neighborhoods with locations of environmental contamination, known as brownfields, impact entire neighborhoods, but corrective environmental remedial action on brownfields is often tracked on an individual property basis, neglecting the larger neighborhood-level impact. This study addresses this impact by examining spatial differences between brownfields with unmitigated environmental concerns (open site) and sites that are considered fully mitigated or closed in urban neighborhoods (closed site) on the US census tract scale in Wayne County, MI. Michigan’s Department of Environment, Great Lakes, and Energy’s leaking underground storage tank (LUST) database provided brownfield information for Wayne County. Local indicators of spatial association (LISA) produced maps of spatial clustering and outliers. A McNemar’s test demonstrated significant discordances in LISA categories between LUST open and closed sites ( p < 0.001). Geographically weighted regressions (GWR) evaluated the association between open and closed site spatial density (open-closed) with socioeconomic variables (population density, proportion of White or Black residents, proportion of college educated populations, the percentage of owner-occupied units, vacant units, rented units, and median household value). Final multivariate GWR showed that population density, being Black, college education, vacant units, and renter occupied units were significantly associated ( p < 0.05) with open-closed, and that those associations varied across Wayne County. Increases in Black population was associated with increased open-closed. Increases in vacant units, renter-occupied units, and college education were associated with decreased open-closed. These results provide input for environmental justice research to identify inequalities and discover the distribution of environmental hazards among urban neighborhoods.
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Evaluating the Effects of Landscape on Housing Prices in Urban China
The rapid urbanisation of China has received growing attention regarding its urban residential environments. In this article, we model the spatial heterogeneity of housing prices and explore the spatial discrepancy of landscape effects on property values in Shenzhen, a large Chinese city. In contrast to previous studies, this paper integrates the official housing transaction records and housing attributes from open data along with field surveys. Then, the results using the hedonic price model (HPM), geographically weighted regression (GWR) without landscape metrics and GWR with landscape metrics are compared. The results show that GWR with landscape metrics outperforms the other two models. In summary, this research provides new insights into landscape metrics in real estate studies and can guide decision‐makers plan and design cities while also providing guidance to regulate and control urban property values based on local conditions.
more » « less- NSF-PAR ID:
- 10073655
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Tijdschrift voor Economische en Sociale Geografie
- Volume:
- 109
- Issue:
- 4
- ISSN:
- 0040-747X
- Page Range / eLocation ID:
- p. 525-541
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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