OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for French Polynesia in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap data is open data, with a very permissive licence. You can download it and use it for any purpose you like, as long as you credit OpenStreetMap and its contributors. You don't have to pay anyone, or ask anyone's permission. When you download and use the data, you're granted permission to do that under the Open Database Licence (ODbL). The only conditions are that you Attribute, Share-Alike, and Keep open.

The required credit is “© OpenStreetMap contributors”. If you make a map, you should display this credit somewhere. If you provide the data to someone else, you should make sure the license accompanies the data

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for 21 Pacific Island Countries, in a GIS-friendly format. The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly and contains data for Cook Islands, Federated States of Micronesia, Fiji, Kiribati, Republic of the Marshall Islands, Nauru, Niue, Palau, Papua New Guinea, Samoa, Solomon Islands, Tonga, Tuvalu, Vanuatu, Guam, Northern Mariana Islands, French Polynesia, Wallis and Futuna, Tokelau, American Samoa as well as data on the Pacific region. The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for the Northern Mariana Islands in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for Guam in a GIS-friendly format. The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly. The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for American Samoa in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for Solomon Islands in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for Tuvalu in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for Palau in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for the Federated States of Micronesia in a GIS-friendly format. The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly. The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for Wallis and Futuna in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for the Republic of the Marshall Islands in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for Vanuatu in a GIS-friendly format.

The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly.

The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

This road network dataset was created from data extracted from OpenStreetMap (OSM) across the geographic area of Australia on 05 August 2020. Its purpose is to represent motor-vehicle traversable public roads within Australia. Note, however, as the original dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk. This road network has been topologically corrected for the purposes of network analysis for motor vehicles. For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki. Please note: The original data for this dataset has been downloaded from Geofabrik on 05 August 2020. AURIN has filtered the original data and omitted features to present the topologically correct, motor-vehicle traversable road network.

This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps). The purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin Seilaplan for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting. The vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019. Additional notes for vector data: Please note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API - https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any perimeter or area can be digitised freely using the QGIS editing toolbar. The DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are: - Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM) - Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif This methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed. Additional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range. This sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.

BETA Map of each municipality extracted from Open Street Map, updated weekly. NB: The regions are also available. #Content Each department is delivered as a ZIP archive that contains several map layers to the fomat shapefile (mapping.doc): — places.shp: names of cities or neighbourhoods — roads.shp: all routes from highway to pedestrian path — buildings.shp: built space — raillways.shp: railway tracks — waterways.shp:the hydrolic network — paragraphs.shp: a list of points of interest — natural.shp: green areas — landuse.shp: land occupancy — admin-department.shp: the department In addition, a very summary project file QGis is provided in the archive, in order to visualise the layer overlay in a free tool. Screenshot of the open map under QGis #Origin The data come from the community and free cartographic database OpenStreetMap. The division by department comes from Contours of the French departments from OpenStreetMap. Shapefiles are extracted according to the method shown by Maxime Résibois’ excellent article on PortailSIG: http://www.portailsig.org/content/recuperer-des-donnees-openstreetmap-gdalogr The sources of automatic extraction processing are available on github. They rely on tuttle, a build system for data. # License This data is derived from crowdsourcing carried out by the contributors to the OpenStreetMap project and is under ODbL license which imposes an identical sharing and the mandatory attribution statement must be “© the ODbL-licensed OpenStreetMap contributors” in accordance with http://osm.org/copyright # Modification history

内容 OpenStreetMapの道路ネットワークデータ(2019年12月時点)から日本の主要道路(motorway, trunk, primary, secondary, それぞれの_link)を抽出し,断片化したリンクを集約し軽量化したデータです.道路名や路線番号を一目で簡易に確認することを目的にしています.正確性は保証しません. ファイル構成 - shp.zip: 全データを圧縮したファイル.ページの下のFilesからダウンロードできます.以下のファイルが含まれています. - osm_*_major_roads.*: スクリプト(https://github.com/toruseo/osm-road-extractor-simplifier)により縮約した各地域の主要道路シェープファイル. - japan_road_network.qgz: 全シェープを閲覧できるQGISプロジェクトファイル. 製作者 瀬尾亨(https://toruseo.github.io/) ライセンス Open Data Commons Open Database License

As of January 1, 2016, some of the regions established in the 1960s merge to leave only 13. # Content Each department is delivered as a ZIP archive that contains several map layers at the fomat shapefile (the.doc of mapping): — places.shp: names of cities or neighborhoods — roads.shp: all paths from highway to pedestrian path — buildings.shp: built space — raillways.shp: railways — waterways.shp: the hydrolic network — points.shp: a list of points of interest — natural.shp: green areas — landuse.shp: land occupancy — admin-department.shp: the department In addition, a project file QGis is provided in the archive, in order to visualise the layer overlay in a free tool. # Origin The geofabrik site is well known for providing reference maps extracted from OpenStreetMap on the whole world, but it offers the old split, this data set is the up-to-date declination of the new regions! The data comes from the OpenStreetMap community and free cartographic database. The division by department comes from the ‘Contours of the French departments from OpenStreetMap’. Shapefiles are extracted according to the method exposed by Maxime Résibois’ excellent article on PortalSIG: http://www.portailsig.org/content/recuperer-des-donnees-openstreetmap-gdalogr The sources of automatic extraction processing are available on github. They rely on tuttle, a build system for data. # License This data comes from crowdsourcing carried out by the contributors to the OpenStreetMap project and is under ODbL license which requires an identical sharing and the mandatory attribution mention must be “© OpenStreetMap contributors under ODbL license” in accordance with http://osm.org/copyright # List of regions covered — Auvergne-Rhône-Alpes — Bourgogne-Franche-Comté — Brittany — Centre-Val de Loire — Corsica — Great East — Guadeloupe — Guyana — Up-de-France — Island of France — Martinique — Mayotte — Normandy — New-Aquitaine — Occitanie — Country of the Loire — Provence-Alpes-Côte d’Azur — The Reunion

Update NotesMar 16 2024, remove spaces in the file and folder names.Mar 31 2024, delete the underscore in the city names with a space (such as San Francisco) in the '02_TransCAD_results' folder to ensure correct data loading by TransCAD (software version: 9.0).Aug 31 2024, add the 'cityname_link_LinkFlows.csv' file in the '02_TransCAD_results' folder to match the link from input data and the link from TransCAD results (LinkFlows) with the same Link_ID.IntroductionThis is a unified and validated traffic dataset for 20 US cities. There are 3 folders for each city.01 Input datathe initial network data obtained from OpenStreetMap (OSM)the visualization of the OSM dataprocessed node / link / od data02 TransCAD results (software version: 9.0)cityname.dbd : geographical network database of the city supported by TransCAD (version 9.0)cityname_link.shp / cityname_node.shp : network data supported by GIS software, which can be imported into TransCAD manually. Then the corresponding '.dbd' file can be generated for TransCAD with a version lower than 9.0od.mtx : OD matrix supported by TransCADLinkFlows.bin / LinkFlows.csv : traffic assignment results by TransCADcityname_link_LinkFlows.csv: the input link attributes with the traffic assignment results by TransCADShortestPath.mtx / ue_travel_time.csv : the traval time (min) between OD pairs by TransCAD03 AequilibraE results (software version: 0.9.3)cityname.shp : shapefile network data of the city support by QGIS or other GIS softwareod_demand.aem : OD matrix supported by AequilibraEnetwork.csv : the network file used for traffic assignment in AequilibraEassignment_result.csv : traffic assignment results by AequilibraEPublicationXu, X., Zheng, Z., Hu, Z. et al. (2024). A unified dataset for the city-scale traffic assignment model in 20 U.S. cities. Sci Data 11, 325. https://doi.org/10.1038/s41597-024-03149-8Usage NotesIf you use this dataset in your research or any other work, please cite both the dataset and paper above.A brief introduction about how to use this dataset can be found in GitHub. More detailed illustration for compiling the traffic dataset on AequilibraE can be referred to GitHub code or Colab code.ContactIf you have any inquiries, please contact Xiaotong Xu (email: kid-a.xu@connect.polyu.hk).

Point de téléchargement sur le pays entier et carte d'extraction partielle de couches thématiques OSM, disponibles dans l'anglais d'origine ou traduites en français (par exemple, amenity=college et craft=joiner deviennent equipement=enseignement supérieur et artisanat=menuisier), et mises à jour en continu via imposm à partir des extraits et réplication minute fournis par OSM France (le décalage avec le serveur principal OSM peut être vérifié ici : http://munin.openstreetmap.fr/osm14.openstreetmap.fr/download.vm.openstreetmap.fr/osm_replication_lag_osmbin.html).

Pour télécharger les données, deux possibilités : - soit le territoire entier dans l'un des formats disponibles via le point WFS « Couches thématiques OSM EN et FR sur l'ensemble du pays » ci-dessous - soit sur une partie du territoire à dessiner soi-même ou à choisir au sein des limites administratives du pays en question, en cliquant sur le lien « Carte de visualisation et extraction complète ou partielle en EN ou FR » pour accéder à depuis un contexte MapStore sur le pays. Des vidéos de démonstration sont disponibles ici : https://llg-collabora.ethibox.fr/s/owY8DQTQpgDr8sw

Actuellement, LE FORMAT GEOPACKAGE N'EST PAS FONCTIONNEL (les couches obtenues sont presque vides de leurs attributs) : préférer le format geojson pour récupérer l’intégralité des noms des champs et le convertir en geopackage depuis QGIS.

Pour plus d'informations sur ce point de téléchargement LLg, consulter la fiche de métadonnées parent en lien au bas de cette fiche, qui mène également à des fiches enfants qui présentent chaque thématique proposée.

Point de téléchargement sur le pays entier et carte d'extraction partielle de couches thématiques OSM, disponibles dans l'anglais d'origine ou traduites en français (par exemple, amenity=college et craft=joiner deviennent equipement=enseignement supérieur et artisanat=menuisier), et mises à jour en continu via imposm à partir des extraits et réplication minute fournis par OSM France (le décalage avec le serveur principal OSM peut être vérifié ici : http://munin.openstreetmap.fr/osm14.openstreetmap.fr/download.vm.openstreetmap.fr/osm_replication_lag_osmbin.html).

Pour télécharger les données, deux possibilités : - soit le territoire entier dans l'un des formats disponibles via le point WFS « Couches thématiques OSM EN et FR sur l'ensemble du pays » ci-dessous - soit sur une partie du territoire à dessiner soi-même ou à choisir au sein des limites administratives du pays en question, en cliquant sur le lien « Carte de visualisation et extraction complète ou partielle en EN ou FR » pour accéder à depuis un contexte MapStore sur le pays. Des vidéos de démonstration sont disponibles ici : https://llg-collabora.ethibox.fr/s/owY8DQTQpgDr8sw

Actuellement, LE FORMAT GEOPACKAGE N'EST PAS FONCTIONNEL (les couches obtenues sont presque vides de leurs attributs) : préférer le format geojson pour récupérer l’intégralité des noms des champs et le convertir en geopackage depuis QGIS.

Pour plus d'informations sur ce point de téléchargement LLg, consulter la fiche de métadonnées parent en lien au bas de cette fiche, qui mène également à des fiches enfants qui présentent chaque thématique proposée.