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

<pre>This upload contains two Geopackage files of raw data used for urban analysis in the outskirts of Lille and Nice, France. <br>The data include building footprints (layer "building"), roads (layer "road"), and administrative boundaries (layer "adm_boundaries")<br>extracted from version 3.3 of the French dataset BD TOPO&reg;3 (IGN, 2023) for the municipalities of Santes, Hallennes-lez-Haubourdin,<br>Haubourdin, and Emmerin in northern France (Geopackage "DPC_59.gpkg") and Drap, Cantaron and La Trinit&eacute; in southern France <br>(Geopackage "DPC_06.gpkg").</pre> <pre>&nbsp;</pre> <pre>Metadata for these layers is available here: https://geoservices.ign.fr/sites/default/files/2023-01/DC_BDTOPO_3-3.pdf</pre> <pre>&nbsp;</pre> <pre>Additionally, this upload contains the results of the following algorithms available in GitHub (<a href="https://github.com/perezjoan/emc2-WP2?tab=readme-ov-file">https://github.com/perezjoan/emc2-WP2?tab=readme-ov-file</a>)</pre> <pre><code>&nbsp; </code></pre> <pre>1.&nbsp; The<code> </code>identification<code> </code>of<code> </code>main<code> </code>streets using the QGIS plugin Morpheo (layers "road_morpheo" and "buffer_morpheo") <br><a href="https://plugins.qgis.org/plugins/morpheo/">https://plugins.qgis.org/plugins/morpheo/</a> </pre> <pre><code>2.&nbsp; </code>The<code> </code>identification of main streets in local contexts &ndash; connectivity locally weighted<code> </code>(layer "road_LocRelCon")</pre> <pre><code>3.&nbsp; </code>Basic morphometry<code> </code>of<code> </code>buildings<code> </code>(layer "building_morpho")</pre> <pre><code>4.&nbsp; </code>Evaluation<code> </code>of<code> </code>the<code> </code>number<code> </code>of<code> </code>dwellings<code> </code>within<code> </code>inhabited<code> </code>buildings<code> </code>(layer "building_dwellings")</pre> <pre>5.&nbsp; Projecting<code> </code>population<code> </code>potential<code> </code>accessible from<code> </code>main<code> </code>streets<code> </code>(layer "road_pop_results")</pre> <pre>&nbsp;</pre> <pre>Project website: <a href="http://emc2-dut.org/">http://emc2-dut.org/</a></pre> <pre>&nbsp;</pre> <pre>Publications using this sample data: <br>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. <em>Computational Science and Its Applications &ndash; ICCSA 2024 Workshops. ICCSA 2024</em>. Lecture Notes in Computer Science, vol 14817. Cham: Springer, pp.50-60. <a href="https://doi.org/10.1007/978-3-031-65238-7_4" target="_blank" rel="noopener noreferrer">https://doi.org/10.1007/978-3-031-65238-7_4</a>.</pre> <p><strong>Acknowledgement.</strong> <a name="_Hlk162443883"></a>This work is part of the emc2 project, which received the grant ANR-23-DUTP-0003-01 from the French National Research Agency (ANR) within the DUT Partnership.</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
4

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