2018
DOI: 10.1016/j.compenvurbsys.2018.05.001
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Beyond residential segregation: A spatiotemporal approach to examining multi-contextual segregation

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Cited by 79 publications
(69 citation statements)
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“…These characteristics offer an important context for examining how racial segregation contributes to the disparity in exposure to traffic-related air pollution. Multi-contextual segregation is measured using the individual-level spatiotemporal proximity index (i-STP index) [5]. The i-STP index, a modified version of Grannis's [21] residential segregation index, measures the relative spatial proximity of activity locations among multiple groups during a specific time using an inverse distance function.…”
Section: Methodsmentioning
confidence: 99%
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“…These characteristics offer an important context for examining how racial segregation contributes to the disparity in exposure to traffic-related air pollution. Multi-contextual segregation is measured using the individual-level spatiotemporal proximity index (i-STP index) [5]. The i-STP index, a modified version of Grannis's [21] residential segregation index, measures the relative spatial proximity of activity locations among multiple groups during a specific time using an inverse distance function.…”
Section: Methodsmentioning
confidence: 99%
“…There are several advantages of this index over Grannis's index and other similar residential segregation indices (e.g., White's [22] spatial proximity index). First, it is an individual-level index that uses the exact activity locations at which an individual stayed, unlike Grannis's index that often relies on centroids of spatial units (e.g., census tract) to represent individuals' residential locations [5]. Therefore, it is less subject to aggregation errors that arise from aggregating point data into areal units [23].…”
Section: Methodsmentioning
confidence: 99%
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