Czech Republic GIS data
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Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Czech Republic Postcodes2 Boundaries provides a 2023 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2023 boundaries are provided by Michael Bauer Research GmbH. They are sourced from Czech Statistical Office. These were published in May 2024. Other administrative boundaries for this country are also available: Country Postcodes1 Kraj Okresy Orp Postcodes3 Postcodes5 Obce BSU
Retirement Notice: This item is in mature support as of June 2024 and will retire in December 2027. Czech Republic Oblasti Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2022 boundaries are provided by Michael Bauer Research GmbH. They are sourced from Czech Statistical Office. These were published in May 2023. A new layer will be published in 12-18 months. Other administrative boundaries for this country are also available:Country Postcodes1 Kraj Postcodes2 Okresy Orp Postcodes3 Postcodes5 Obce BSU
Freizeit und Tourismus für das Gebiet des Landkreises ChamDieser Datensatz ist ein Toplayer (thematische Sammlung) und enthält verschiedene Sublayer (Themen) mit Geodaten zu touristischen Routen und Points of Interest (POI) im Landkreis Cham bzw. im Naturpark Oberer Bayerischer Wald. Verfügbar sind verschiedene Daten-Formate und -Dienste, wie Shape, GeoJSON, CSV, KML oder ArcGIS REST-Web-Service. Der Landkreis Cham übernimmt keinerlei Haftung für eventuelle Mängel an Inhalt und Richtigkeit der angebotenen Daten. Aus den Inhalten können Rechtsansprüche weder begründet noch abgeleitet werden.
Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Czech Republic Obce Boundaries provides a 2023 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2023 boundaries are provided by Michael Bauer Research GmbH. They are sourced from Czech Statistical Office. These were published in May 2024. Other administrative boundaries for this country are also available: Country Postcodes1 Kraj Postcodes2 Okresy Orp Postcodes3 Postcodes5 BSU
Retirement Notice: This item is in mature support as of June 2024 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Czech Republic Postcodes3 Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2022 boundaries are provided by Michael Bauer Research GmbH. They are sourced from Czech Statistical Office. These were published in May 2023. Other administrative boundaries for this country are also available:Country Postcodes1 Oblasti Kraj Postcodes2 Okresy Orp Postcodes5 Obce BSU
Retirement Notice: This item is in mature support as of June 2024 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Czech Republic Okresy Boundaries provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2022 boundaries are provided by Michael Bauer Research GmbH. They are sourced from Czech Statistical Office. These were published in May 2023. Other administrative boundaries for this country are also available:Country Postcodes1 Oblasti Kraj Postcodes2 Orp Postcodes3 Postcodes5 Obce BSU
This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes: - macroregion (admin-1 including region) - region (admin-2 including state, province, department, governorate) - macrocounty (admin-3 including arrondissement) - county (admin-4 including prefecture, sub-prefecture, regency, canton, commune) - localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb) The dataset also contains human settlement points and polygons for: - localities (city, town, and village) - neighbourhoods (borough, macrohood, neighbourhood, microhood) The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names. Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.
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 Czechia **Planet** Road Surface. The corresponding paper is available at: https://arxiv.org/abs/2512.04092 Road Surface Statistics Approximately 0.3757 million km of roads are mapped in OSM in this region. Based on AI-derived estimates: - Paved roads: 0.0812 million km (21.6018%) - Unpaved roads: 0.0347 million km (9.2479%) About 0.2598 million km (69.1503%) of road surface information is missing in OSM. To reduce this gap, the Mapillary-derived road surface dataset provides an additional 0.001 million km (0.3722%) 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
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This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long
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