@inproceedings{2335c75da98444498f17e68b17b7ec76,
title = "Building-Level Comparison of Microsoft and Google Open Building Footprints Datasets",
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.",
keywords = "Building footprints, Data comparison, Open data",
author = "Gonzales, {Jack Joseph}",
note = "Publisher Copyright: {\textcopyright} Jack Joseph Gonzales.; 12th International Conference on Geographic Information Science, GIScience 2023 ; Conference date: 12-09-2023 Through 15-09-2023",
year = "2023",
month = sep,
doi = "10.4230/LIPIcs.GIScience.2023.35",
language = "English",
series = "Leibniz International Proceedings in Informatics, LIPIcs",
publisher = "Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing",
editor = "Roger Beecham and Long, {Jed A.} and Dianna Smith and Qunshan Zhao and Sarah Wise",
booktitle = "12th International Conference on Geographic Information Science, GIScience 2023",
}