Abstract
Transportation infrastructure is crucial in determining accessibility and mobility metrics, which help us to optimize transportation systems. However, current representations of the local environment are less standardized, making it hard to extract relevant data. To address this, we propose a framework that enables geographic and categorical homogenization of environmental data and recombination with additional sociodemographic data. Ensuring semantic consistency, our framework leverages the styling rules of OSM Carto representation to extract land use and transportation infrastructure data worldwide. We evaluated the framework's performance in Munich, Germany, by refining WorldPops' distribution via OSM building data from our framework to synthetically derive a more accurate population distribution for Munich's districts. Our benchmark against official administrative ground truth shows a significant improvement compared to the baseline distributions.
| Original language | English |
|---|---|
| Title of host publication | 2024 IEEE 27th International Conference on Intelligent Transportation Systems, ITSC 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3872-3879 |
| Number of pages | 8 |
| ISBN (Electronic) | 9798331505929 |
| DOIs | |
| State | Published - 2024 |
| Event | 27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024 - Edmonton, Canada Duration: 24 Sep 2024 → 27 Sep 2024 |
Publication series
| Name | IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC |
|---|---|
| ISSN (Print) | 2153-0009 |
| ISSN (Electronic) | 2153-0017 |
Conference
| Conference | 27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024 |
|---|---|
| Country/Territory | Canada |
| City | Edmonton |
| Period | 24/09/24 → 27/09/24 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 11 Sustainable Cities and Communities
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