Austria transport data

Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: railway - Part of the country exports on HDX by HOT

Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: aeroway, building, emergency - Part of the country exports on HDX by HOT

Sea ports, harbours and ferry terminals. Useful for maritime logistics, supply-chain analysis, and coastal access planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: industrial=port, harbour, port, amenity=ferry_terminal, building=ferry_terminal - Part of the country exports on HDX by HOT

Road network across the area tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: highway - Part of the country exports on HDX by HOT

Der Datensatz beinhaltet freigegebene Mountainbikerouten, überregionale Radwanderrouten, Radwege und freigegebene Singletrail-Strecken in Tirol. Link zu den Metadaten (Update: 20.10.2026 05:11Uhr)

Der Datensatz beinhalten das gesamte Straßen- und Wegenetz von Tirol auf Grundlage der Graphenintegrations-Plattform (GIP). Link zu den Metadaten (Update: 16.10.2026 12:00Uhr)

Im Meldewege über die Gemeinden werden alle Seilhindernisse erfasst, die für den Rettungsdienst mit Helikoptern aber auch für den Flugsport generell eine Gefahr darstellen können. Link zu den Metadaten (Update: 16.10.2026 12:01Uhr)

Standorte der öffentlichen Behindertenparkplätze in den Tiroler Gemeinden Link zu den Metadaten (Update: 16.10.2026 12:02Uhr)

This dataset provides detailed information on road surfaces from OpenStreetMap (OSM), distinguishing between **paved** and **unpaved** roads across the region. Surface classification is derived using a hybrid deep learning approach. For methodological details, see: http://arxiv.org/abs/2410.19874 Recently, we also published a new country-level dataset based on PlanetScope satellite imagery with near-complete coverage of all arterial roads. It is available on HDX under the name Austria **Planet** Road Surface. The corresponding paper is available at: https://arxiv.org/abs/2512.04092 Road Surface Statistics Approximately 0.5122 million km of roads are mapped in OSM in this region. Based on AI-derived estimates: - Paved roads: 0.11 million km (21.4685%) - Unpaved roads: 0.0709 million km (13.8363%) About 0.3314 million km (64.6952%) of road surface information is missing in OSM. To reduce this gap, the Mapillary-derived road surface dataset provides an additional 0.0012 million km (0.3629%) of the missing surface information. Intended Use This dataset supports transportation planning, infrastructure analysis, climate emissions assessment, and GIS applications. AI Features - **pred_class**: Model-predicted surface class ("paved" or "unpaved") - **pred_label**: Binary label (0 = paved, 1 = unpaved) - **osm_surface_class**: Surface classification derived from OSM tags - **combined_surface_osm_priority**: Combined classification prioritizing OSM - **combined_surface_DL_priority**: Combined classification prioritizing DL prediction - **n_of_predictions_used**: Number of predictions used for estimation - **predicted_length**: Predicted length based on DL estimation (meters) - **DL_mean_timestamp**: Mean timestamp of predictions used OSM Attributes - **name** - **name:en** - **name:* (local language)** - **highway** - **surface** - **smoothness** - **width** - **lanes** - **oneway** - **bridge** - **layer** - **source** Urban Classification Attributes - **continent** - **country_iso_a2** - **urban** (0 = rural, 1 = urban) - **urban_area** - **osm_id** - **osm_type** Data Sources The dataset originates from OpenStreetMap (OSM) and is augmented with deep learning predictions based on Mapillary street-level imagery, combined with the GHSU Global Human Settlement Urban Layer 2019 and AFRICAPOLIS 2020 urban layer. More HeiGIT datasets: https://data.humdata.org/organization/heidelberg-institute-for-geoinformation-technology More information: https://heigit.org/ Contact: communications@heigit.org

Groundwater fields describe areas with large contiguous groundwater deposits. Reported for INSPIRE. Important fields and data types of the attribute table (those that contain content information): ANLAGENNAM (String) = name of the groundwater field in the water information system VOrarlberg TYPE OF INSTALLATION (string) TYPCODE (string) INSTALLATION SUB (string) SUBTYPCODE (string) WORKING (string) STRATEGY (String) Postcode (number) COMMUNITY (string) WISONLINE (URL) = URL to the WIS extract (only available in the country portal!) WIS _ID (String)= unique identification of the plant in the Vorarlberg water information system Data source: groundwater fields.shp Data up-to-dateness: Up-to-date, updated if necessary