Global and regional level of use of buildings and roads prepared by AI for OSM mapping
Benjamin Herfort, Milan Fila & Radim Štampach
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.
Milan Fila, M.Sc.; Department of Geography, Faculty of Science, Masaryk University, Brno, Czechia; Radim Štampach, Ph.D.; Department of Geography, Faculty of Science, Masaryk University, Brno, Czechia; Benjamin Herfort, Ph.D.; Heidelberg Institute for Geoinformation Technology, Heidelberg, Germany;