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Les auteurs utilisent une combinaison de microdonnées nationales tirées des séries IPUMS ( Integrated Public Use Microdata Series) et de microdonnées sur la population et la santé au niveau régional, spatialisées à l’échelon des ménages, et ils se servent d’un SIG historique (SIGH) pour suivre la transmission de l’infection grippale entre les enfants des écoles publiques de la péninsule nord du Michigan durant la pandémie de 1918. Les microdonnées sont des données non agrégées d’un extrême degré de précision. Les auteurs décrivent trois avantages importants de l’utilisation de microdonnées historiques dans le contexte du SIGH : la contextualisation des données dans l’espace et le temps en correspondance avec la période, l’esquive de l’erreur écologique et la capacité de naviguer librement entre les échelles micro et macro. Ils montrent le potentiel qu’offre l’étude historique des pandémies au moyen de microdonnées historiques en procédant à une analyse spatiotemporelle de cette maladie respiratoire infectieuse dans trois écoles, d’avril à juin 1918.

While the use of geographic information systems (GIS) has become commonplace within the discipline of archaeology, the potential of a big-data approach to GIS is yet to be fully exploited within historical archaeology. Archaeologists inspired by developments in the social sciences and humanities have recently called for new ways of conceptualizing GIS as a process that is more theoretically satisfying and methodologically effective in its applications to archaeology. We respond to these calls by proposing a new approach for GIS in historical archaeology, an historical spatial-data infrastructure (HSDI). We outline the progression from historical GIS to the construction of an HSDI and present a series of case studies that demonstrate how using a spatiotemporal big-data-based approach expands the scale of archaeological inquiry to studying the postindustrial city.

While a vibrant and growing research literature exists on the value of GIS to archaeology in general, the application of geospatial digital data to the subfield of historical archaeology is less well developed, especially in North America. This is particularly true for the era of industrialization, where the archaeological record is accompanied by a comparatively rich historical record. Historical and industrial archaeology are fundamentally bound up in the interplay between material and historical data, and it is in enhancing the dialogue between these two evidentiary bodies that interdisciplinary geospatial approaches are most fruitful to these subdisciplines. Drawing on recent discussions in digital archaeology and Historical GIS (HGIS), which has a robust history in the social sciences and humanities, we present an approach to modelling, visualizing, and analyzing longitudinal physical and social environment data for historical and industrial archaeology: a Historical Spatial Data Infrastructure (HSDI). Our HSDI, which is data-rich and highly flexible in scale, is especially well-adapted to facilitating this dialogue within archaeological research, as well as having important applications to heritage management and public engagement, as demonstrated in our case study.

The archaeology of postindustrial landscapes is still relatively undeveloped. The impact of economic, social, and urban development efforts on both tangible and intangible heritage complicate our a...

Building historical geographic information system (HGIS) datasets is time consuming and very expensive, especially when built at the scales that permit analysis of the lived experiences of individu...

The daily commute to work and its related social histories have long been of interest to historical geographers and urban historians. This article revisits the existing scholarship on the nineteenth-century journey to work and outlines a new methodological framework that uses a historical GIS to overcome many of the challenges identified in previous studies. These challenges include a reliance on small, atypical samples of workers, approximations of the spatial relationship between home and work, and unrealistic interpretations of journeys travelled by using only Euclidean paths. Combining city directories and decennial censuses through the use of probabilistic record linkage techniques uncovers the relationship between work and home for over 5,000 workers in London, Ontario in 1881. A GIS network-derived journey to work model re-creates more realistic journey that considers the many natural and built environment barriers that influenced the paths and distances workers travelled on a daily basis. Empirical results of the journey to work along the lines of occupational class, coincident home–work location, and gender are presented and contextualized to studies in other cities. The results highlight that the experiences of commuting differ widely along the lines of social class and gender.

Purpose The purpose of this paper is to create a longitudinal data-driven model of change over time in a postindustrial landscape, using the “Copper Country” of Michigan’s Upper Peninsula as a case study. The models resulting from this project will support the heritage management and public education goals of the contemporary communities and Keweenaw National Historical Park that administer this nationally significant mining region through accessible, engaging, and interpretable digital heritage. Design/methodology/approach The paper applies Esri’s CityEngine procedural modeling software to an existing historical big data set. The Copper Country Historical Spatial Data Infrastructure, previously created by the HESA lab, contains over 120,000 spatiotemporally specific building footprints and other built environment variables. This project constructed a pair of 3D digital landscapes comparing the built environments of 1917 and 1949, reflecting the formal and functional evolution of several of the most important copper mining, milling, and smelting districts of Michigan’s Keweenaw Peninsula. Findings This research discovered that CityEngine, while intended for rapid 3D modeling of the contemporary urban landscape, was sufficiently robust and flexible to be applied to modeling serial historic industrial landscapes. While this novel application required some additional coding and finish work, by harnessing this software to existing big data sets, 48,000 individual buildings were rapidly visualized using several key variables. Originality/value This paper presents a new and useful application of an existing 3D modeling software, helping to further illuminate and inform the management and conservation of the rich heritage of this still-evolving postindustrial landscape.

Historians engage with the nonacademic public in diverse ways, from blogging their research, to public-friendly periodicals, to the art and practice of public historians. Within this special issue ...

Formal historic preservation is a professional and sanctioned approach to the conservation of our historically significant built cultural heritage. Postindustrial landscapes are, by definition, functionally and materially obsolete, and in many cases derelict and decaying. While they hold historical significance, these sites are often not widely perceived as valuable contributors to our heritage. Yet these landscapes persist. We argue that the material persistence of these features is the result of generally unrecognized processes of informal material conservation. In this paper, we outline a new framework, vernacular preservation , an ontology for heritage professionals to use in considering how to approach and recognize nonformal interventions that result in the protection of heritage resources. Here, we use the postindustrial landscape of Michigan's Keweenaw Peninsula—a former copper-mining district—to illustrate how vernacular preservation differs from formal historic preservation, reviewing the process of vernacular preservation and how it is activated in practice. Vernacular preservation constitutes perhaps the most traditional, common, and widespread mechanism of material conservation of the historical built environment yet has been largely invisible, little discussed, and undertheorized by the heritage preservation community. Understanding this preservation process begins by acknowledging its existence and by extending the heritage dialogue to include these underrepresented historical properties and their important role in defining postindustrial landscapes. We conclude the paper with a discussion on how this novel approach to thinking about preservation extends broadly to the field and should be given greater attention.

For decades, the Lake Superior Iron District produced a significant majority of the world’s iron used in steel production. Chief among these was the Mesabi Range of northern Minnesota, a vast deposit of hematite and magnetic taconite ores stretching for over 100 miles in length. Iron ore mining in the Mesabi Range involved three major phases: direct shipping ores (1847–1970s), washable ores (1907–1980s), and taconite (1947–current). Each phase of iron mining used different technologies to extract and process ore. Producing all of this iron yielded a vast landscape of mine waste. This paper uses a historical GIS to illuminate the spatial extent of mining across the Lake Superior Iron District, to locate where low-grade ore processing took place, and to identify how and where waste was produced. Our analysis shows that the technological shift to low-grade ore mining placed new demands on the environment, primarily around processing plants. Direct shipping ore mines produced less mine waste than low-grade ore mines, and this waste was confined to the immediate vicinity of mines themselves. Low-grade ore processing, in contrast, created more dispersed waste landscapes as tailings mobilized from the mines themselves into waterbodies and human communities.

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 import...

This paper examines the water quality legacies of historic and current iron mining in the Mesabi Range, the most productive iron range in the history of North America, producing more than 42% of the world’s iron ore in the 1950s. Between 1893 and 2016, 3.5 × 10(9) t of iron ore were shipped from the Mesabi Range to steel plants throughout the world. We map historic sites and quantities of iron mining, ore processing, water use, and tailings deposition within subwatershed boundaries. We then map the locations of impaired lakes within HUC-12 subwatershed boundaries within the Mesabi Range, using government datasets created for US federal Clean Water Act reporting. Comparing watersheds with and without historic mining activity, watersheds with historic mining activity currently contain a greater percentage of impaired lakes than control watersheds within the same range. These results suggest that historic iron ore mining and processing in the Mesabi Range affected water quality on a landscape scale, and these legacies persist long after the mines have closed. This paper outlines a novel spatial approach that land managers and policy makers can apply to other landscapes to assess the effects of past mining activity on watershed health.

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.

We combine the Historical Spatial Data Infrastructure (HSDI) concept developed within spatial history with elements of archaeological predictive modeling to demonstrate a novel GIS-based landscape model for identifying the persistence of historically-generated industrial hazards in postindustrial cities. This historical big data approach draws on over a century of both historical and modern spatial big data to project the presence of specific persistent historical hazards across a city. This research improves on previous attempts to understand the origins and persistence of historical pollution hazards, and our final model augments traditional archaeological approaches to site prospection and analysis. This study also demonstrates how models based on the historical record, such as the HSDI, complement existing approaches to identifying postindustrial sites that require remediation. Our approach links the work of archaeologists more closely to other researchers and to municipal decision makers, permitting closer cooperation between those involved in archaeology, heritage, urban redevelopment, and environmental sustainability activities in postindustrial cities.

An interdisciplinary team of researchers were challenged to create a model of a deep map during a three-day charette at the NEH Institute on Spatial Narratives and Deep Maps. Through a reflexive process of ingesting data, probing for fruitful research questions, and considering how a deep map might be used by different audiences, we created a wireframe model of a deep map and explored how it related to spatial narratives. We explored the tension between interfaces for exploratory and structured views of data and sources, and devised a model for the intersections between spatial narratives and deep maps. The process of creating wireframes and prototype screens—and more importantly, the discussions and debates they initiated—helped us understand the complex requirements for deep maps and showed how a deep map can support a humanistic interpretation of the role of space in historical processes.

Researchers of our past have long used historical maps to place events and to uncover the physical form of an area. A series of maps may be employed to understand a region beyond the extent of a single map. However, rarely are these maps included in publications of research findings. At best, a modern cartographic reproduction will be created to depict the research area. Our maps, created for a historical atlas of Sandwich, Ontario, Canada, are noteworthy for their use of original historical maps in a mosaic to recreate the past. Our objective was to overcome the international boundary between Canada and the United States, a borderland that has succumbed to vast generalizations on the part of the cartographers of the nineteenth and early twentieth centuries. Through the use of ArcGIS, we georectified and fixed the extent of our maps, creating a series of maps that depict the changing urban growth of Sandwich over 200 years. This methodology can be extended to allow for the cartographic visualization of economic, political, social and spatial relationships that exist beyond a single map.