How have cities evolved during the 20th century?

We leverage 150 million cadastral parcel & tax records to reconstruct historical urban extents and settlement distributions in the United States since the early 1800s, enabling us to analyze how the size and morphology of U.S. cities have changed over long time periods and at unprecedented detail.

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The real estate company Zillow has assembled county-level cadastral and tax assessor data to an impressive, U.S.-wide database (ZTRAX), holding over 400 million assessment and transaction records, including detailed parcel-level information on building age, size, usage, value, and physical characteristics ( Zillow has made these data available for researchers through data share agreements. Since 2017, we work with this dataset and have developed methods to ingest ZTRAX into efficient relational databases and to extract geospatial datasets, which we can then aggregate into US-wide, high-resolution gridded data for any attribute of interest. Based on the “year built” reported in ZTRAX for a large majority of building records we are able to generate time series of such gridded surfaces representing the built environment at different point in times.

First built-up year (FBUY) surface from the Historical settlement data compilation for the U.S. (HISDAC-US). Beige and green colors indicate early built-up areas, blue color more recently developed areas (Figure created by Johannes Uhl, data source:

These gridded surfaces enable the long-term mapping of U.S. urbanization at unprecedented coverage and detail:

Built-up areas from the HISDAC-US, shown for 35 U.S. cities from 1810 to 2015, arranged in pseudo-geographic space (upper right = Northeast). Source: Johannes Uhl ( See this on YouTube:

All gridded datasets are publicly available at

Methods & results

From the HISDAC-US gridded datasets we generated multivariate time series for over 300 metropolitan areas, describing the size, shape, and structural characteristics of each urban area, in 5-year intervals from 1910 to 2010 (get the data here: In our publication "A century of decoupling size and structure of urban spaces in the United States" ( we used multivariate statistical methods such as t-distributed neighbor embedding and cluster analysis to characterize the trajectories of urban areas over time, and to identify similarities between urban areas. We observed an increasing disentanglement of size- and structure-related characteristics over time, and identified a recently emerging cluster of urban areas characterized by high levels of contiguity, as a result of growing and merging processes, connecting built-up areas that initially were spatially disconnected. Such an disentanglement indicates that while cities show similar changes in size, their inner structure (urban form) might evolve in different ways. This can be significant for our urban life because changing structures would require different policies for transportation planning or public and health service supply.

These datasets do not only open up new pathways for analytical, quantitative assessments of urban growth and long-term land development, but also allow for effective visualization of land development and urban growth, at unprecedented spatial detail and spatio-temporal coverage. We generated aspatial and spatial data animations based on our city-level time series and the time series of gridded surfaces. The animation below illustrates the dynamics of city sizes (measured by the total built-up area) during the 20th century:

See here some HISDAC-US movies:

See more in our HISDAC-US YouTube channel (

US-wide land development trends over the long term

Besides these insights into urban spatial development, the HISDAC-US data also provides vast opportunities to study land development across the United States as a whole, including sparsely settled rural areas. The fine spatial detail allows us to divide land development into components such as expansion, infilling, and densification, and to quantitatively assess how these components have interacted during the 20th century and beyond. The regional relative growth curves (shown below) peak at different points in time, reflecting region-specific settlement patterns. Future work will examine such development patterns at local scales.

Measuring the past to predict the future

Future work will focus on the development of spatially explicit urban (and rural) growth models, informed by the spatio-temporal settlement dynamics measured through the HISDAC-US data, integrated with other spatial data sources such as road network data or historical maps ( Moreover, these datasets and the underlying ZTRAX database enable us to assess how the U.S. built environment and the building stock interact with natural hazards (flooding, fire risk) and social vulnerability, to better understand the dynamics of socio-environmental processes over the long term. The animation below illustrates how urban change (e.g., land conversion from not built-up to built-up land) can be measured over long time periods:

Animating urban sprawl: highlighted in white are areas that changed from undeveloped to developed within 30-year time periods. Watch this on YouTube:

Web links and references


Connor D., Clement K., Cunningham A., Gutmann M. and Leyk S. 2020: How Entrenched is the Spatial Structure of Neighborhood Inequality? Evidence from the Integration of Census and Housing data for Denver from 1940 to 2016. Annals of the American Association of Geographers 110(4): 1022-1039,

Leyk, S., Uhl, J. H., Connor, D. S., Braswell, A. E., Mietkiewicz, N., Balch, J. K., & Gutmann, M. (2020). Two centuries of settlement and urban development in the United States. Science Advances, 6(23), eaba2937,

Leyk, S., & Uhl, J. H. (2018). HISDAC-US, historical settlement data compilation for the conterminous United States over 200 years. Scientific Data, 5, 180175.

Mietkiewicz N., Balch J., Schoennagel T., Leyk S., St. Denis L.A., Bradley B.A. 2020: In the Line of Fire: Consequences of Human-Ignited Wildfires to Homes in the U.S. (1992-2015), Fire 3(3), 50, 

Uhl, J. H., Connor, D. S., Leyk, S., & Braswell, A. E.,  (2021). A century of decoupling size and structure of urban spaces in the United States. Communications Earth and Environment, 2, 20.

Uhl, J. H., Leyk, S., McShane, C. M., Braswell, A. E., Connor, D. S., & Balk, D. (2020). Fine-grained, spatio-temporal datasets measuring 200 years of land development in the United States. Earth System Science Data, 13, 119–153.

Data visualization and animation:

HISDAC-US Youtube channel:

Uhl, Johannes H.: Animating 200 years of urban spatial development in 35 U.S. cities. Uhl, Johannes H.. 2020.

Bar chart race: built-up area per MSA, 1910-2010:

Bar chart race: built-up intensity per MSA, 1910-2010:

Bar chart race: number of built-up patches per MSA, 1910-2010:

Data access & source data:

HISDAC-US data repository in Harvard Dataverse:

Urban spatial metrics for U.S. Metropolitan statistical areas (1910-2010):

Zillow's Assessor and Real Estate Database (ZTRAX):

Publicity & News:

Business Insider (2020): “A stunning new video shows how cities exploded onto the US map over the last 200 years” (

Financial Times (2020): "Mapping how railroads built America" (

Colorado Arts and Sciences Magazine (2018): "CU Boulder geographers studying plot-level land-use changes over 200 years (

Colorado Arts and Sciences Magazine (2020): "New CU Boulder research provides unprecedented opportunity to study history and evolution of human land-use and development in the United States" (

ASU Now: Access, Excellence, Impact (2020): "New ASU research empowers efforts to plan smarter, more resilient cities (

Johannes Uhl

Post-doctoral Research Associate, University of Colorado Boulder

1 Comment

Go to the profile of Ronnie Hawkins
Ronnie Hawkins about 1 month ago

And how much longer do you believe this kind of growth can continue? I'd like to see an assessment, not based on projecting past and present trends forward, but by taking into account the extent to which we've already overdrawn global biological systems as well as surrounding local ecologies.