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Preprints
https://doi.org/10.5194/essd-2020-217
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-217
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  03 Sep 2020

03 Sep 2020

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This preprint is currently under review for the journal ESSD.

Fine-grained, spatio-temporal datasets measuring 200 years of land development in the United States

Johannes H. Uhl1,5, Stefan Leyk1,5, Caitlin M. McShane1, Anna E. Braswell2, Dylan S. Connor3, and Deborah Balk4 Johannes H. Uhl et al.
  • 1Department of Geography, University of Colorado Boulder, Boulder, CO 80309, USA
  • 2Earth Lab, Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO 80303, USA
  • 3School of Geographical Sciences & Urban Planning, Arizona State University, Tempe, AZ 85281, USA
  • 4CUNY Institute for Demographic Research & Baruch College, City University of New York, New York City, NY 10017, USA
  • 5Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO 80309, USA

Abstract. The collection, processing and analysis of remote sensing data since the early 1970s has rapidly improved our understanding of change on the Earth’s surface. While satellite-based earth observation has proven to be of vast scientific value, these data are typically confined to recent decades of observation and often lack important thematic detail. Here, we advance in this arena by constructing new spatially-explicit settlement data for the United States that extend back to the early nineteenth century, and is consistently enumerated at fine spatial and temporal granularity (i.e., 250 m spatial, and 5 a temporal resolution). We create these time series using a large, novel building stock database to extract and map retrospective, fine-grained spatial distributions of built-up properties in the conterminous United States from 1810 to 2015. From our data extraction, we analyse and publish a series of gridded geospatial datasets that enable novel retrospective historical analysis of the built environment at unprecedented spatial and temporal resolution. The datasets are available at https://dataverse.harvard.edu/dataverse/hisdacus (Uhl and Leyk, 2020a, b, c, d).

Johannes H. Uhl et al.

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Johannes H. Uhl et al.

Data sets

Historical built-up property records (BUPR) - gridded surfaces for the U.S. from 1810 to 2015 Johannes H. Uhl and Stefan Leyk https://doi.org/10.7910/DVN/YSWMDR

Historical built-up property locations (BUPL) - gridded surfaces for the U.S. from 1810 to 2015 Johannes H. Uhl and Stefan Leyk https://doi.org/10.7910/DVN/SJ213V

Historical built-up areas (BUA) - gridded surfaces for the U.S. from 1810 to 2015 Johannes H. Uhl and Stefan Leyk https://doi.org/10.7910/DVN/J6CYUJ

Uncertainty surfaces accompanying the BUPR, BUPL, and BUA gridded surface series Johannes H. Uhl and Stefan Leyk https://doi.org/10.7910/DVN/T8H5KF

Video supplement

Animating 200 years of urban spatial development in 35 U.S. cities Johannes H. Uhl https://doi.org/10.5446/48115

Johannes H. Uhl et al.

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Latest update: 21 Sep 2020
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Short summary
Fine-grained geospatial data on the spatial distribution of human settlements are scarce prior to the era of remote-sensing based earth observation. In this paper, we present datasets derived from a large, novel building stock database, enabling the spatially explicit analysis of 200 years of land development in the United States, at unprecedented spatial and temporal resolution. These datasets greatly facilitate long-term studies of socio-environmental systems in the conterminous United States.
Fine-grained geospatial data on the spatial distribution of human settlements are scarce prior...
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