Sample data for analysis of demographic potential of the 15-minute city in northern and southern France

This upload contains two Geopackage files of raw data used for urban analysis in the outskirts of Lille and Nice, France. The data include building footprints (layer "building"), roads (layer "road"), and administrative boundaries (layer "adm_boundaries")extracted from version 3.3 of the French dataset BD TOPO®3 (IGN, 2023) for the municipalities of Santes, Hallennes-lez-Haubourdin,Haubourdin, and Emmerin in northern France (Geopackage "DPC_59.gpkg") and Drap, Cantaron and La Trinité in southern France (Geopackage "DPC_06.gpkg"). Metadata for these layers is available here: https://geoservices.ign.fr/sites/default/files/2023-01/DC_BDTOPO_3-3.pdf Additionally, this upload contains the results of the following algorithms available in GitHub (https://github.com/perezjoan/emc2-WP2?tab=readme-ov-file) 1. The identification of main streets using the QGIS plugin Morpheo (layers "road_morpheo" and "buffer_morpheo") https://plugins.qgis.org/plugins/morpheo/ 2. The identification of main streets in local contexts – connectivity locally weighted (layer "road_LocRelCon") 3. Basic morphometry of buildings (layer "building_morpho") 4. Evaluation of the number of dwellings within inhabited buildings (layer "building_dwellings") 5. Projecting population potential accessible from main streets (layer "road_pop_results") Project website: http://emc2-dut.org/ Publications using this sample data: Perez, J. and Fusco, G., 2024. Potential of the 15-Minute Peripheral City: Identifying Main Streets and Population Within Walking Distance. In: O. Gervasi, B. Murgante, C. Garau, D. Taniar, A.M.A.C. Rocha and M.N. Faginas Lago, eds. Computational Science and Its Applications – ICCSA 2024 Workshops. ICCSA 2024. Lecture Notes in Computer Science, vol 14817. Cham: Springer, pp.50-60. https://doi.org/10.1007/978-3-031-65238-7_4. This resource was produced within the emc2 project, which is funded by ANR (France, grant ANR-23-DUTP-0003), FFG (Austria, grant FO999905461), MUR (Italy, grant 2024/0017648) and Vinnova (Sweden, grant 2023-02581) under the Driving Urban Transition Partnership, which has been co-funded by the European Commission.