Spatio-temporal analysis of socioeconomic neighborhoods: The Open Source Longitudinal Neighborhood Analysis Package (OSLNAP)

Abstract

The neighborhood effects literature represents a wide span of the social sciences broadly concerned with the influence of spatial context on social processes. From the study of segregation dynamics, the relationships between the built environment and health outcomes, to the impact of concentrated poverty on social efficacy, neighborhoods are a central construct in empirical work. From a dynamic lens, neighborhoods experience changes not only in their socioeconomic composition, but also in spatial extent; however, the literature has ignored the latter source of change. In this paper, we discuss the development of a novel, spatially explicit tool: the Open Source Longitudinal Neighborhood Analysis Package (OSLNAP) using the scientific Python ecosystem.

Multivariate Neighborhood Trajectory Analysis: An Exploration of the Functional Data Analysis Approach

“…This increased attention stimulated the development of neighborhood trajectory models that identify longitudinal patterns of neighborhood change observed in the time series of multivariate census data. Such models include sequence analysis models (Wei and Knox 2014;Delmelle, 2015Delmelle, , 2016Li and Xie 2018;Patias, Rowe, and Cavazzi 2019) and Markov chain models (Delmelle and Thill 2014;Nilsson and Delmelle 2018;Rey et al 2018). Both approaches examine the stochastic or sequential switching of cross-sectional cluster memberships of tracts across decades by stacking cross-sectional neighborhood clustering results on time-series multivariate census data.…”

NDS: an interactive, web-based system to visualize urban neighborhood dynamics in United States

“…A neighborhood's position on this grid is traced over time to depict its trajectory of change. In sum, the visualization methods implemented in this system depict the state of the art in terms of neighborhood change analysis (Rey, Knaap, Han, Wolf, & Kang, 2018), but expands this line of research by enabling interactivity with the data and results.…”

Neighborhood Dynamics with Unharmonized Longitudinal Data

“…Recent interest has at least partly been rekindled through newly available longitudinal demographic data sets (Logan, Xu, and Stults 2014;Manson et al 2017), convenient computational tools (Rey et al 2018), and new sources of data (Poorthuis 2018).…”

“…This involves interpolating existing measurements into a common set of regions (Logan, Xu, and Stults 2014;Hallisey et al 2017;Allen and Taylor 2018). Recent computational tools have somewhat simplified this process (Rey et al 2018), but it still involves nontrivial questions: which geometry to use as target, how to apportion the variables, or how to combine data from different sources. Further, these questions do not necessarily have optimal answers.…”

“…Recent computational tools have somewhat simplified this process (Rey et al. 2018), but it still involves nontrivial questions: which geometry to use as target, how to apportion the variables, or how to combine data from different sources. Further, these questions do not necessarily have optimal answers.…”