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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 and Benjamin HERFORT. \textit{Global and regional level of use of buildings and roads prepared by AI for OSM mapping}. 2023.
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