Full Citation

Title: Neighborhood Dynamics with Unharmonized Longitudinal Data

Citation Type: Journal Article

Publication Year: 2021

ISBN:

ISSN: 0016-7363

DOI: 10.1111/gean.12224

NSFID:

PMCID:

PMID:

Abstract: This article proposes a novel method for data‐driven identification of spatiotemporal homogeneous regions and their dynamics, enabling the exploration of their composition and extents. Using a simple network representation, the method enables temporal regionalization without the need for geographical harmonization. To allow for a transparent corroboration of our method, we use it as a basis for an interactive and intuitive interface for the progressive exploration of the results. The interface guides the user through the original data, enabling both experts and nonexperts to characterize broad patterns of stability and change and identify detailed local processes. The proposed methodology is suitable for any region‐based data, and we validate our method with illustrative scenarios from Chicago and Toronto, with results that match the established literature. The system is publicly available, with demographic data for over forty regions in the USA and Canada between 1970 and 2010.

Url: https://onlinelibrary.wiley.com/doi/pdf/10.1111/gean.12224

Url: https://onlinelibrary.wiley.com/doi/full/10.1111/gean.12224

Url: https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12224

User Submitted?: No

Authors: Dias, Fabio; Silver, Daniel

Periodical (Full): Geographical Analysis

Issue:

Volume: 53

Pages: 170-191

Data Collections: IPUMS NHGIS

Topics: Housing and Segregation, Land Use/Urban Organization, Population Mobility and Spatial Demography

Countries: