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@proceedings{58667,
author = {Fila, Milan and Štampach, Radim and Herfort, Benjamin and Herfort, Benjamin},
keywords = {OpenStreetMap; ohsome; artificial intelligence; humanitarian mapping; Volunteered geographic information},
language = {eng},
title = {Global and regional level of use of buildings and roads prepared by AI for OSM mapping},
url = {https://zenodo.org/records/10443308},
year = {2023}
}
TY - CONF
ID - 58667
AU - Fila, Milan - Štampach, Radim - Herfort, Benjamin - Herfort, Benjamin
PY - 2023
TI - Global and regional level of use of buildings and roads prepared by AI for OSM mapping
KW - OpenStreetMap
KW - ohsome
KW - artificial intelligence
KW - humanitarian mapping
KW - Volunteered geographic information
UR - https://zenodo.org/records/10443308
N2 - Despite the hard work of volunteers, OpenStreetMap is still poorly mapped in many parts of the world. Using AI-assisted tools was seen as one possibility to fill data gaps. We search the actual level of AI-assisted mapping, show the overall global level and highlight differences between countries and regions and their temporal evolution. In 2021-2023, a minimum of 5.6% of buildings and 0.8% of principal roads newly created in OSM came from AI-assisted mapping workflow.
ER -
FILA, Milan, Radim ŠTAMPACH a Benjamin HERFORT. \textit{Global and regional level of use of buildings and roads prepared by AI for OSM mapping}. 2023.
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