Can I read highway2vec: representing OpenStreetMap microregions with respect to their road network characteristics on EtoBox?

highway2vec: representing OpenStreetMap microregions with respect to their road network characteristics by Kacper Leśniara; Piotr Szymański is a scholarly article available to read on EtoBox.

What is highway2vec: representing OpenStreetMap microregions with respect to their road network characteristics about?

Recent years brought advancements in using neural networks for representation learning of various language or visual phenomena. New methods freed data scientists from hand-crafting features for common tasks. Similarly, problems that require considering the spatial variable can benefit from pretrained map region representations instead of manually creating feature tables that one needs to prepare to solve a task. However, very few methods for map area representation exist, especially with respect to road network characteristics. In this paper, we propose a method for generating microregions' embeddings with respect to their road infrastructure characteristics. We base our representations on OpenStreetMap road networks in a selection of cities and use the H3 spatial index to allow reproducible and scalable representation learning. We obtained vector representations that detect how similar map hexagons are in the road networks they contain. Additionally, we observe that embeddings yield a latent space with meaningful arithmetic

Author

Kacper Leśniara; Piotr Szymański

Publisher

ACM

Published

2022

Language

EN