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

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Details:

  • Journal Title:
    Data in Brief
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    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.
  • Keywords:
  • Source:
    Data in Brief, 43, 108369
  • DOI:
  • ISSN:
    2352-3409
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  • Rights Information:
    CC BY
  • Compliance:
    Submitted
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