OpenUAS: Embeddings of Cities in Japan with Anchor Data for Cross-city Analysis of Area Usage Patterns
<|reference_start|>OpenUAS: Embeddings of Cities in Japan with Anchor Data for Cross-city Analysis of Area Usage Patterns: We publicly release OpenUAS, a dataset of area embeddings based on urban usage patterns, including embeddings for over 1.3 million 50-meter square meshes covering a total area of 3,300 square kilometers. This dataset is valuable for analyzing area functions in fields such as market analysis, urban planning, transportation infrastructure, and infection prediction. It captures the characteristics of each area in the city, such as office districts and residential areas, by employing an area embedding technique that utilizes location information typically obtained by GPS. Numerous area embedding techniques have been proposed, and while the public release of such embedding datasets is technically feasible, it has not been realized. One of the obstacles has been the integration of data from different cities and periods into a unified space without sharing raw location data. We address this issue by developing an anchoring method that establishes anchors within a shared embedding space. We publicly release this anchor dataset along with area embedding datasets from several periods in eight major Japanese cities. This dataset allows users to analyze urban usage patterns in Japanese cities and embed their urban dataset into the same embedding space using the anchoring method. Our key contributions include the development of the anchoring method, releasing area embedding datasets for Japanese cities, and providing tools for effective data utilization.<|reference_end|>
@article{tamura2024openuas:,
    title={OpenUAS: Embeddings of Cities in Japan with Anchor Data for Cross-city
  Analysis of Area Usage Patterns},
    author={Naoki Tamura, Kazuyuki Shoji, Shin Katayama, Kenta Urano, Takuro
  Yonezawa, Nobuo Kawaguchi},
    journal={arXiv preprint arXiv:2407.19872},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.19872},
    primaryClass={cs.LG}
}