citygisoo Montréal Building-Level Geospatial Dataset

This dataset contains the building-level geospatial output generated for the Montréal Island use case presented in the related CityGISOO manuscript. The dataset was generated by the jug_gis_cities service of the Sabu software framework using the citygisoo Python package. The Montréal preprocessing workflow implemented in jug_gis_cities integrates complementary geospatial and property-related datasets and uses reusable citygisoo operations to produce building-level features for downstream urban modelling and building carbon assessment. The dataset is provided as a GeoPackage (GPKG). Source datasets The workflow used the following source datasets: Usages prédominants, Ministère des Affaires municipales et de l’Habitation (MAMH), 2026 Rôle d’évaluation foncière, MAMH, 2025 Automatically Extracted Buildings, Natural Resources Canada (NRCan), 2023 High Resolution Digital Elevation Model (HRDEM) – DSM, Natural Resources Canada (NRCan), 2022 High Resolution Digital Elevation Model (HRDEM) – DTM, Natural Resources Canada (NRCan), 2022 Forward Sortation Areas, DMTI Spatial, 2025 The final dataset combines building geometry and attributes derived through the preprocessing workflow. Licensing note The DMTI Spatial Forward Sortation Areas dataset was used during preprocessing to organize the workflow geographically. Because the DMTI source is subject to separate redistribution restrictions, the FSA attribute has been removed from this publicly distributed dataset. The remaining distributed information is derived from source datasets that permit redistribution subject to their respective licence and attribution requirements. Users should consult the original data providers and applicable licences when reusing the dataset. Related manuscript Adli, A., and Eicker, U.CityGISOO: A Python-Based Workflow Abstraction for Geospatial Data Cleaning Automation.