Abstract

This paper presents a method for constructing a lightweight taxonomy of geospatial features using OpenStreetMap (OSM) data. Leveraging the OSM data model, our process mines frequent tags to efficiently produce a structured hierarchy, enriching the semantic representation of geo-features. This data-driven taxonomy supports various geospatial analysis applications. Accompanying the methodology, we release the source code of our tool and demonstrate its practical application with tailored taxonomies for California (US) and Greece, underscoring our approach’s adaptability and scalability.

Date

2024

Authors

Basel Shbita, Craig A Knoblock

Conference

2024 IEEE 18th International Conference on Semantic Computing (ICSC)

Pages

208-211

Publisher

IEEE