MTBF-33: A multi-temporal building footprint dataset for 33 counties in the United States (1900 - 2015)

Despite abundant data on the spatial distribution of contemporary human settlements, historical datasets on the long-term evolution of human settlements at fine spatial and temporal granularity are scarce, limiting our quantitative understanding of long-term changes of built-up areas. This is because commonly used large-scale mapping methods (e.g., computer vision) and suitable data sources (i.e., aerial imagery, remote sensing data, LiDAR data) have only been available in recent decades. However, there are alternative data sources such as cadastral records that are digitally available, containing relevant information such as building construction dates, allowing for an approximate, digital reconstruction of past building distributions. We conducted a non-exhaustive search of open and publicly available data resources from administrative institutions in the United States and gathered, integrated, and harmonized cadastral parcel data, tax assessment data, and building footprint data for 33 counties, wherever building footprint geometries and building construction year information was available. The result of this effort is a unique dataset that we call the Multi-Temporal Building Footprint Dataset for 33 U.S. Counties (MTBF-33). MTBF-33 contains over 6.2 million building footprints including their construction year, and can be used to derive retrospective depictions of built-up areas from 1900 to 2015, at fine spatial and temporal grain. Moreover, MTBF-33 can be employed for data validation purposes, or to train statistical learning models aiming to extract historical information on human settlements from remote sensing data, historical maps, or similar data sources.

Towards the automated large-scale reconstruction of past road networks from historical maps

Transportation infrastructure, such as road or railroad networks, represent a fundamental component of our civilization. For sustainable planning and informed decision making, a thorough understanding of the long-term evolution of transportation infrastructure such as road networks is crucial. However, spatially explicit, multi-temporal road network data covering large spatial extents are scarce and rarely available prior to the 2000s. Herein, we propose a framework that employs increasingly available scanned and georeferenced historical map series to reconstruct past road networks, by integrating abundant, contemporary road network data and color information extracted from historical maps. Specifically, our method uses contemporary road segments as analytical units and extracts historical roads by inferring their existence in historical map series based on image processing and clustering techniques. We tested our method on over 300,000 road segments representing more than 50,000 km of the road network in the United States, extending across three study areas that cover 42 historical topographic map sheets dated between 1890 and 1950. We evaluated our approach by comparison to other historical datasets and against manually created reference data, achieving F-1 scores of up to 0.95, and showed that the extracted road network statistics are highly plausible over time, i.e., following general growth patterns. We demonstrated that contemporary geospatial data integrated with information extracted from historical map series open up new avenues for the quantitative analysis of long-term urbanization processes and landscape changes far beyond the era of operational remote sensing and digital cartography.

Historical dataset of mills for Galicia in the Austro-Hungarian Empire/southern Poland from 1880 to the 1930s

In this article, we present the dataset of mills from 1880 and 1920s-1930s in the area of the former Galicia (78,500 km2), now in Ukraine and Poland. The data was obtained as a result of manual vectorisation from 162 map sheets at scales of 1:115,200 and 1:100,000, according to the map legends. We found 4022 mill locations for 1880 and 3588 for the 1920s-1930s. We present them as vector points in shapefile, GML, GeoJSON, KML formats with attributes for seven types of mills for 1880 and ten types of mills for 1920s-1930s, and mills counted in a 10 km grid. The data can be used in economic, demographic and environmental reconstructions, e.g. to estimate historical anthropopressure related to settlement, agriculture and forestry. Mills are often associated with river structures such as floodgates, dams, and millraces and therefore they are a good example of human interference in river ecosystems. They can also be one criteria for identifying areas where the local population used traditional environmental knowledge. It can be useful for a contemporary assessment of the environment's suitability for devices using renewable energy sources. Finally, the data on the remains of former mills is suitable for the protection of cultural heritage sites that are technical monuments related to traditional food processing and industry.

Demographic and social context of deaths during the 1854 cholera outbreak in Soho, London: a reappraisal of Dr John Snow's investigation

Deaths from cholera in Soho, London (late July to end of September 1854) exposed the epidemiology of the disease and demonstrated applied geospatial analysis by highlighting the shortest path principle followed by local residents when they obtained drinking water from a contaminated pump. The present investigation explores if households and individuals with different demographic and socio-economic characteristics were more or less likely to obtain their water from the pump and succumb to the disease. It combines information from the 1851 Population Census and topographic databases with the digital deaths and water pump data to reveal the risk of exposure and the mortality rate were greater for certain occupations, age groups and people living at high residential density irrespective of proximity to the contaminated water pump.

Mid-19th century road network dataset for Galicia and Austrian Silesia, Habsburg Empire

In this paper, we present the vector dataset of the historical road network of Galicia and Austrian Silesia (>80 000 km²) in the mid-19th century – two regions of the former Habsburg Empire, located in Central Europe. The data were acquired manually from 455 map sheets of the Austrian second military survey map (1:28,800) for the four main road categories, according to the map legend. All the road categories present the roads passable at any time of the year, which was strategic information from the military point of view and build a network of 15 461 km. Currently, the data can be used by various researchers studying migrations, regional development, but also human impact on the environment, like land use change, invasive species introduction or landscape fragmentation. The dataset presents the times just before the most dynamic economic changes of the 19th century, which had a great impact on the region. On the other hand, the road network presented here was developed in the conditions of one country, the Habsburg Empire, which collapsed after the First World War, triggering the rise of new states and remodelling the transport network connections in Central Europe. Additionally, the data are accompanied by the layer of towns and villages with more than 2000 inhabitants, based on the 1857 Austrian census data.

The co-evolution of residential segregation and the built environment at the turn of the 20th century: a Schelling model

To what degree does the built environment of cities shape the social environment? In this paper we use a Schelling-like agent based model to consider how changes to the built environment of cities relate to changes in residential segregation by income and ethnicity. To develop this model we exploit insights from a high resolution historical GIS which maps 100% of the population of Newark, NJ in 1880. Newark in 1880 had a complex social landscape characterized by areas of significant social and economic segregation and areas of relative integration. We develop a Schelling model capable of reproducing these residential patterns. We use this model to explore the decentralization of housing, a specific phenomenon associated with the demise of the walking city in the late 19th century. Holding agent preferences constant, but allowing the landscape of the Schelling model to evolve in ways that reflect historical changes to the built environment produces changes to the social landscape that are also consistent with history. Our work suggests that changes in residential segregation do not necessarily imply changes to individual attitudes and preferences. Changes in residential segregation can be generated by changes to the built environment, specifically the geographic distribution of housing.

Two steps back, one step forward: reconstructing the dynamic Danube riverscape under human influence in Vienna

As part of an interdisciplinary project on the environmental history of the Viennese Danube, the past river landscape was reconstructed. This article describes the different types of historical sources used for the GIS-based reconstruction, the underlying methodological approach and its limitations regarding reliability and information value. The reconstruction was based on three cornerstones: (1) the available historical sources; (2) knowledge about morphological processes typical for the Austrian Danube prior to regulation; and (3) the interpretation of past hydraulic measures with respect to their effectiveness and their impact on the river's behaviour. We compiled ten historical states of the riverscape step-by-step going backwards in time to the early 16th century. After one historical situation had been completed, we evaluated its relevance for the temporally younger situations and whether corrections would have to be made. Such a regressive-iterative approach allows for permanent critical revision of the reconstructed time segments already processed. The resulting maps of the Danube floodplain from 1529 to 2010 provide a solid basis for interpreting the environmental conditions for Vienna's urban development. They also help to localise certain riverine and urban landmarks (such as river arms or bridges) relevant for the history of Vienna. We conclude that the diversity of approaches and findings of the historical and natural sciences (river morphology, hydrology) provide key synergies.