a department of Family Medicine, Michigan state university, Flint, Mi, usA; b department of social sciences, Michigan technological university, Houghton, Mi, usA ABSTRACT Racial dynamics and discrimination have been extremely important in influencing decline in the American Rust Belt. The mid-twentieth century departure of white and middle-class populations from cities was precipitated by a breakdown of discriminatory housing practices. This study examines the relationship among housing condition, vacancies, poverty, and demographics in Flint, Michigan, from 1950 to 2010. Historical census data from the National Historical GIS and housing condition data from the City of Flint government are aggregated to neighborhoods defined by economic condition factor (n = 102). Results of rank-difference correlation and geographically weighted regression indicate that, across neighborhoods with the greatest decline in housing condition, the strongest correlate was most often the increase in vacancy rates driven initially by racially motivated suburbanization -suggesting that demographic change alone is not primarily responsible for neighborhood decline. This research is important to understanding the long-term and ongoing consequences of mid-twentieth century racist housing practices, particularly as it relates to the implications of maintaining legacy infrastructure.

This article presents a methodological model for the study of the space-time patterns of everyday life. The framework utilizes a wide range of qualitative and quantitative sources to create two environmental stages, social and built, which place and contextualize the daily mobilities of individuals as they traverse urban environments. Additionally, this study outlines a procedure to fully integrate narrative sources in a GIS. By placing qualitative sources, such as narratives, within a stage-based GIS, researchers can begin to tell rich spatial stories about the lived experiences of segregation, social interaction, and environmental exposure. The article concludes with a case study utilizing the diary of a postal clerk to outline the wide applicability of this model for space-time GIS research.These daily time-space patterns have provided countless lines of enquiry for geographers over the past half-century, with topics ranging from racial and ethnic segregation to labor markets, and from health outcomes to community cohesion. Kwan (2013) has recently argued that we need to expand our analytical focus from the static residential spaces captured in census-based studies to other places and times in people's daily lives. She suggests that a deeper understanding of a population's spatio-temporal experiences could be established if we study "where and when people work, eat, play, shop, and socialize" (Kwan 2013, p.6). Congruent with her theoretical framework, this article will outline a methodological framework to study the space-time patterns of everyday life using a wide range of qualitative and quantitative sources.We argue in this article that when studying the spatio-temporal patterns of individuals, a stage must first be set in which to place and contextualize the space-time paths and social interactions. This means going beyond merely putting one layer of space-time data atop another, or placing the paths against a backdrop such as Google Earth, as these common approaches decontextualize the data. Instead, we argue that space-time data should be contextualized on a set of rich environmental stages constructed using a wide range of qualitative and quantitative sources such as temporally representative maps, social surveys, photographs, and local property data. We advocate the creation of a GIS where sources are fully integrated with the contextualizing stage, going beyond the simple recognition that they share the same geographic and temporal space.This article provides a detailed framework for the creation of two environmental stages, built and social. A built environment stage comprises data sources that allow for the modeling of the human-made spaces in cities, including the structures, land uses, transportation systems and parks. These are the physical spaces in which people live, work, play, and the domain with which researchers of individual space-time patterns have largely been concerned. A social environment stage comprises a dataset of all residents of the city, at the scale of the individual, complete ...

No abstract

introductionThis article discusses the processes and discussion undertaken over a threeday charette during the NEH Institute on Spatial Narratives and Deep Maps. The challenge was to construct a deep map and to explore how digital tools and interfaces can support ambiguous, subjective, uncertain, imprecise, rich, experiential content alongside the highly structured data at which GIS systems excel. Through a reflexive process of ingesting data, probing for fruitful research questions, and considering how a deep map might be used by different audiences

No abstract