Spatial Analysis of Green Streets in the City of Portland, Oregon
Start Date
February 2018
End Date
February 2018
Abstract
We seek to explain the spatial distribution of Green Streets, a type of Stormwater Green Infrastructure (SGI), within the City of Portland. SGI offers multiple benefits, such as improved water quality, runoff regulation, and reduction of combined sewer overflows. This is complemented by SGI’s ability to improve perceived aesthetic and economic value within urban areas. We used sociodemographic and physical variables acquired from a variety of governmental agencies to investigate the relationship between the density of green streets and the explanatory variables. Sociodemographic variables are based on tax lots and census data and include population characteristics (income, education) and building structural characteristics (building size, building age, and building value). Physical parameters include elevation, slope, impervious surfaces, and soil type and are derived at the lot scale and the census block group scale. Our results showed that there is a distinct spatial pattern of green street density, and a combination of these physical and sociodemographic variables influence placement of green streets throughout the city. Additionally, the determinants of green street density vary over space, suggesting that different local spatial processes are related to the placement of green streets. This research offers decision-relevant information for future urban spatial planning. To ensure the ideal placement of SGI projects throughout the city, it is necessary for municipalities to consider both biophysical constraints and sociodemographic settings of different neighborhoods within the City.
Subjects
Land use planning, Hydrology, GIS / modeling
Persistent Identifier
https://archives.pdx.edu/ds/psu/25638
Spatial Analysis of Green Streets in the City of Portland, Oregon
We seek to explain the spatial distribution of Green Streets, a type of Stormwater Green Infrastructure (SGI), within the City of Portland. SGI offers multiple benefits, such as improved water quality, runoff regulation, and reduction of combined sewer overflows. This is complemented by SGI’s ability to improve perceived aesthetic and economic value within urban areas. We used sociodemographic and physical variables acquired from a variety of governmental agencies to investigate the relationship between the density of green streets and the explanatory variables. Sociodemographic variables are based on tax lots and census data and include population characteristics (income, education) and building structural characteristics (building size, building age, and building value). Physical parameters include elevation, slope, impervious surfaces, and soil type and are derived at the lot scale and the census block group scale. Our results showed that there is a distinct spatial pattern of green street density, and a combination of these physical and sociodemographic variables influence placement of green streets throughout the city. Additionally, the determinants of green street density vary over space, suggesting that different local spatial processes are related to the placement of green streets. This research offers decision-relevant information for future urban spatial planning. To ensure the ideal placement of SGI projects throughout the city, it is necessary for municipalities to consider both biophysical constraints and sociodemographic settings of different neighborhoods within the City.
