An OpenStreetMap derived building classification dataset for the United States.

ABSTRACT: Building classification is crucial for population estimation, traffic planning, urban planning, and emergency response applications. Although essential, such data is often not readily available. To alleviate this problem, this work presents a comprehensive dataset by providing residential/non-residential building classification covering the entire United States. We developed a dataset of building types based on building footprints and the available OpenStreetMap information. The dataset is validated using authoritative ground truth data for select counties in the U.S., which shows a high precision for non-residential building classification and a high recall for residential buildings. In addition to the building classifications, this dataset includes detailed information on the OpenStreetM

SUBMITTER: F de Arruda H 

PROVIDER: S-EPMC11550320 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature