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DOI: 10.4230/LIPIcs.GIScience.2023.35

Building-Level Comparison of Microsoft and Google Open Building Footprints Datasets (Short Paper)

Authors: Jack Joseph Gonzales

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract

Large-scale datasets of building footprints are a crucial source of information for a variety of efforts. In 2023, the general public benefits from open access to multiple sources of building footprints at the country scale or larger, such as those produced by Microsoft and Google. However, none of the available datasets have attained complete global coverage, and researchers and analysts may need to combine multiple sources to assemble a complete set of building footprints for their area of interest or choose between overlapping sources, requiring an understanding of the differences between different building sources. This paper presents a method to closely examine the quality of different building footprint sources by matching corresponding buildings across datasets, using building footprints in Ethiopia published by Microsoft and Google as an example set.

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Jack Joseph Gonzales. Building-Level Comparison of Microsoft and Google Open Building Footprints Datasets (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 35:1-35:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{gonzales:LIPIcs.GIScience.2023.35,
  author =	{Gonzales, Jack Joseph},
  title =	{{Building-Level Comparison of Microsoft and Google Open Building Footprints Datasets}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{35:1--35:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.35},
  URN =		{urn:nbn:de:0030-drops-189309},
  doi =		{10.4230/LIPIcs.GIScience.2023.35},
  annote =	{Keywords: Open data, Building footprints, Data comparison}
}

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Building-Level Comparison of Microsoft and Google Open Building Footprints Datasets (Short Paper)

Abstract

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