Der Datensatz enthält das Straßennetz Hamburgs, das aufgrund der INSPIRE-Datenspezifikation zum Anhang I - Thema Verkehrsnetze (Transport Networks) aus der Straßeninformationsbank (HH-SIB) ausgewählt wurde.Quelle: Open Data Portal HamburgVerarbeitungsprozesse: GML Datei wurde in ArcGIS Pro importiert, nach WebMercator WGS84 projiziert und als Feature Service in ArcGIS Online veröffentlicht.

This GIS dataset depicts the surficial geology of the Hamburg Area (NTS 84E/SW) (GIS data, line features). The data were created in geodatabase format and output for public distribution in shapefile format. These data comprise the line features of Alberta Geological Survey Map 565, Surficial Geology of the Hamburg Area (NTS 84E/SW).

Abgeleitetes, flächendeckendes digitales Geländemodell mit einer Rasterweite von 1 Meter. Für die Fläche der Freien und Hansestadt Hamburg (ohne das Gebiet des hamburgischen Wattenmeeres) wurde in 2010 eine Laserscanvermessungen (Airborne Laserscanning) durchgeführt.Quelle: Transparenzportal HamburgVerarbeitungsprozesse: ASCII Dateien wurden in ArGIS Pro verarbeitet, nach WGS84 projiziert, als Tile Paket in ArcGIS Online veröffentlicht und daraus ein Elevation Layer generiert.

This GIS dataset depicts the surficial geology of the Hamburg Area (NTS 84E/SW) (discontinuous permafrost features). The data were created in geodatabase format and output for public distribution in shapefile format. These data comprise the permafrost polygon features of Alberta Geological Survey Map 565, Surficial Geology of the Hamburg Area (NTS 84E/SW).

This GIS dataset depicts the surficial geology of the Hamburg Area (NTS 84E/SW) (GIS data, line features). The data were created in geodatabase format and output for public distribution in shapefile format. These data comprise the line features of Alberta Geological Survey Map 565, Surficial Geology of the Hamburg Area (NTS 84E/SW).

Ortsteile Hamburg aus der ALKIS Verwaltungsgrenzen.Quelle: Open Data Portal HamburgVerarbeitungsprozesse: GML Datei wurde in ArcGIS Pro importiert, nach WebMercator WGS84 projiziert und als Feature Service in ArcGIS Online veröffentlicht.

This GIS dataset depicts the surficial geology of the Hamburg Area (NTS 84E/SW) (GIS data, polygon features). The data were created in geodatabase format and output for public distribution in shapefile format. These data comprise the polygon features of Alberta Geological Survey Map 565, Surficial Geology of the Hamburg Area (NTS 84E/SW).

This GIS dataset depicts the surficial geology of the Hamburg Area (NTS 84E/SW) (discontinuous permafrost features). The data were created in geodatabase format and output for public distribution in shapefile format. These data comprise the permafrost polygon features of Alberta Geological Survey Map 565, Surficial Geology of the Hamburg Area (NTS 84E/SW).

Im Amtlichen Liegenschaftskatasterinformationssystem (ALKIS®) werden alle Daten des Liegenschaftskatasters zusammengeführt und integriert gepflegt. Damit sind Daten der ehemaligen Liegenschaftskarte, des ehemaligen Liegenschaftsbuches und des Grenznachweises in ALKIS enthalten. Daneben gibt es entsprechend dem Datenmodell länderspezifische zusätzliche Daten. Dieser Datensatz enthält die ALKIS Gebäude.Quelle: Open Data Portal HamburgVerarbeitungsprozesse: GML Datei wurde in ArcGIS Pro importiert, nach WebMercator projiziert und als Feature Service in ArcGIS Online veröffentlicht.

Data and maps on habitats of plants and animals with special attention to the legally protected biotopes. The basis for the data collection of the biotopes/habitats of Hamburg are the "Mapping Instructions and Biotope Type Keys for Biotope Mapping Hamburg" and the "Biotope Assessment for Biotope Mapping Hamburg". Both can be found as download files in PDF format at https://www.hamburg.de/biotopkartierung. On this page, the biotope mapping is also briefly explained. Despite plausibility checks, no guarantee can be given for the completeness or accuracy of the data. The actual state of a biotope in nature is always decisive for the implementation of the statutory biotope protection. WMS card services: The datasets underlying these data are derived from a modelling that leads to a comprehensive mapping as an overlay-free layer. For this purpose, the data of the overall database of the biotope register Hamburg were used, which completely reproduce the vintages 2010 to 12/2019. This may lead to deviations in the size data compared to those in the survey form. The size information in the survey forms is decisive. For the WMS card service, there is a GML file corresponding to the WMS card service. Download area: In addition, a GML file with an extended attribute table and all vintages is provided (zip, in the download area, see link above), which contains the geographical data of the biotopes as well as their essential descriptive data with the exception of the plant species lists for the individual biotopes. The GML files can be integrated into geographic information systems (GIS). The instructions for this can be found in the download area of the transparency portal for the biotope register Hamburg (Link: List of hits on the Transparency Portal Hamburg). All information on a biotope can be found in the corresponding survey sheet, which is also provided as a zip file in the download area of the transparency portal. The sheets are assigned to the biotopes via the DK5, biotope no. and the mapping date (e.g. 6620_317_080716.pdf).

Urban areas have a manifold and far-reaching impact on our environment, and the three-dimensional structure is a key aspect for characterizing the urban environment.

This dataset features a map of building height predictions for entire Germany on a 10m grid based on Sentinel-1A/B and Sentinel-2A/B time series. We utilized machine learning regression to extrapolate building height reference information to the entire country. The reference data were obtained from several freely and openly available 3D Building Models originating from official data sources (building footprint: cadaster, building height: airborne laser scanning), and represent the average building height within a radius of 50m relative to each pixel. Building height was only estimated for built-up areas (European Settlement Mask), and building height predictions <2m were set to 0m.

Temporal extent The acquisition dates of the different data sources vary to some degree: - Independent variables: Sentinel-2 data are from 2018; Sentinel-1 data are from 2017. - Dependent variables: the 3D building models are from 2012-2020 depending on data provider. - Settlement mask: the ESM is based on a mosaic of imagery from 2014-2016. Considering that net change of building stock is positive in Germany, the building height map is representative for ca. 2015.

Data format The data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (.tif). Metadata are located within the Tiff, partly in the FORCE domain. There is a mosaic in GDAL Virtual format (.vrt), which can readily be opened in most Geographic Information Systems. Building height values are in meters, scaled by 10, i.e. a pixel value of 69 = 6.9m.

Further information For further information, please see the publication or contact David Frantz (david.frantz@geo.hu-berlin.de). A web-visualization of this dataset is available here.

Publication Frantz, D., Schug, F., Okujeni, A., Navacchi, C., Wagner, W., van der Linden, S., & Hostert, P. (2021). National-scale mapping of building height using Sentinel-1 and Sentinel-2 time series. Remote Sensing of Environment, 252, 112128. DOI: https://doi.org/10.1016/j.rse.2020.112128

Acknowledgements The dataset was generated by FORCE v. 3.1 (paper, code), which is freely available software under the terms of the GNU General Public License v. >= 3. Sentinel imagery were obtained from the European Space Agency and the European Commission. The European Settlement Mask was obtained from the European Commission. 3D building models were obtained from Berlin Partner für Wirtschaft und Technologie GmbH, Freie und Hansestadt Hamburg / Landesbetrieb Geoinformation und Vermessung, Landeshauptstadt Potsdam, Bezirksregierung Köln / Geobasis NRW, and Kompetenzzentrum Geodateninfrastruktur Thüringen. This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC.

Funding This dataset was produced with funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).

LSA-ProzessdatenDer Datensatz umfasst momentan die LSA-Prozessdaten für rund die Hälfte aller am Verkehrsrechnernetz angeschlossenen Knoten in Hamburg und enthält aktuelle Signalausprägungen in Echtzeit. Zusätzlich werden Daten zu Detektoren wie Fahrrad-, Fußgänger- und Kfz- Anforderungen sowie Busmeldungen übertragen.Folgende Punkte sollten bei der Nutzung der Daten berücksichtigt werden:Durch Wartungsarbeiten kann es vereinzelt zu kurzen Ausfällen bei der Signalübertragung für mehrere Straßenzüge kommen.In wenigen Fällen gib es außerdem fehlerhafte Zeitstempel aus den LSA-Steuergeräten (phenomenonTime), die für unplausible Werte bei der Latenz verantwortlich sind.Für ein besseres Verständnis der Daten, ist im Bereich Verweise und Downloads ein Benutzerhandbuch (Usage Guide) verlinkt.Weitere Informationen zum Echtzeitdienst:Der OGC SensorThings API konforme Echtzeitdatendienst enthält Datenströme und Positionen von Fahrspurbeziehungen an Kreuzungen mit Lichtsignalanlagen für Fahrradfahrer, Fußgänger sowie Kraftfahrzeuge im Hamburger Stadtgebiet. Wenn an der Lichtsignalanlage bereitgestellt, werden folgende Datenströme als JSON-Objekte ausgeliefert: Primärsignale, Sekundärsignale, Hilfssignale, Akustiksignale, KFZ-Signalanforderungen, Fahrradfahrersignalanforderungen, Fußgängersignalanforderungen, Akustiksignalanforderung, ÖPNV-Voranmeldung, ÖPNV-Anmeldung, ÖPNV-Abmeldung, Signalprogramm und Wellensekunde. In der OGC SensorThings API sind die Informationen zu den Fahrspurbeziehungen in der Entität Thing hinterlegt. Für die oben aufgelisteten Datenströme, die an einem konkreten Thing verfügbar sind, wird ein Eintrag in der Entität Datastreams erstellt, der das entsprechende Thing referenziert.Alle Zeitangaben sind in der koordinierten Weltzeit (UTC) angegeben.In der Entität Datastreams gibt es im JSON-Objekt unter dem "key" "properties" weitere "key-value-Paare". In Anlehnung an die Service- und Layerstruktur im GIS haben wir Service und Layer als zusätzliche "key-value-Paare" unter dem JSON-Objekt properties eingeführt.Hier ein Beispiel:{ "properties": { "serviceName": "HH_STA_traffic_lights", "layerName": "primay_signal", "key":"value" }}Alle möglichen values für “layerName”: * primay_signal (Primärsignal), * secondäary_signal (Sekundärsignal), * auxiliary_signal (Hilfssignal), * acoustic_signal (Akustiksignal), * detector_car (KFZ-Signalanforderung), * detector_cyclist (Fahrradfahrersignalanforderung), * detector_pedestrian (Fußgängersignalanforderung), * detector_acoustic_traffic_request (Akustiksignalanforderung), * bus_pre-request_point (ÖPNV-Voranmeldung), * bus_request_point (ÖPNV-Anmeldung), * bus_checkout (ÖPNV-Abmeldung), * signal_program (Nummer des Signalprogramms), * cycle_second (Wellensekunde)Mit Hilfe dieser "key-value-Paare" können dann Filter für die REST-Anfrage definiert werden, bspw.https://tld.iot.hamburg.de/v1.1/Datastreams?$filter=properties/serviceName eq 'HH_STA_traffic_lights' and properties/layerName eq 'primary_signal'Die Echtzeitdaten kann man auch über einen MQTT-Broker erhalten. Die dafür notwendigen IDs können über eine REST-Anfrage bezogen werden und dann für das Abonnement auf einen Datastream verwendet werden:MQTT-Broker: tld.iot.hamburg.deTopic: v1.1/Datastreams({id})/ObservationsFerner können über folgenden Link die MAP-Dateien (xml und kml) sowie die OCIT-C-Dateien (Versorgungsdatei im Format xml) aller bereits veröffentlichter Knoten abgerufen werden:https://daten-hamburg.de/tlf_public/

The tree register includes the area-wide representation of the trees on public road plots as a basis for tree inspections for traffic safety and planning. Essential data fields: location, genus/species, year of planting, vitality (if necessary CIR flight), biological parameters, signs of damage. An integrated GIS component provides fast graphic visualization of the tree locations and background maps. The factual data is available in an SQL database. They are recorded as part of ongoing surveys and updates. Update within the framework of tree inspections for road safety.

The street tree cadastre includes the area-wide representation of the trees on public street plots as a basis for tree inspections for road safety and planning. Important data fields are: location, genus/species, year of planting, crown circumference, stem diameter, biological parameters and signs of damage. An integrated GIS component provides fast graphic visualization of the tree locations and background maps. The factual data is available in a SQL Server database. It is recorded as part of ongoing surveys and updates. The updates are also made as part of the prescribed tree inspections for road safety. The - online street tree cadastre - includes the area-wide representation of trees on public street plots with essential root attributes as well as the data of the Hamburg Port Authority, which are stored in a separate database. The following data fields are assigned to each tree: location, genus/species, year of planting, crown diameter and trunk circumference. This data, recorded as part of regular tree inspections, is updated annually for the Internet as of January 1st. They are available as a WMS and WFS service and in GML format for download.

Notes on data quality: The data is transmitted in real time to the Urban Data Platform of the FHH. This means that they are available to all users and interested parties in a timely manner. Due to the real-time component, however, various framework conditions must be observed: The data is not fully quality-assured. Unusual deviations from the expected data and data gaps are automatically detected by the system, but cannot be corrected in real time. Gaps, which occur e.g. due to a demolition of the data transmission, can still be delivered afterwards. Under certain circumstances and in the case of longer outages, changes in the historical data can therefore still take place after a few days. The data are therefore updated daily for the following periods: The day before: 5-min intervals, 15-min intervals and 60-min intervals Six days ago: 5-min intervals, 15-min intervals, 60-min intervals and daily intervals 28 days ago: 5-min intervals, 60-min intervals, daily intervals Weekly values are updated weekly for the previous week and the week before four weeks. The data published here are not officially verified data of the FHH. As with any traffic count, whether automated or manual, there are certain tolerances in measurement accuracy. The system used here requires accuracies for the counting fields of +/- 10% for the recording of cycle traffic on sidewalks, cycle paths and cycle lanes and +/-20% for the recording of cycle traffic in mixed traffic with motor vehicles. Since counting points are formed from a combination of different counting fields, the deviation can be up to +/-20%. More information about the real-time service: The real-time data service contains the active locations of the counting fields and counting points via which the current bicycle volume at the location is determined by means of infrared detectors. The data is provided in JSON format via the SensorThings API (STA). For each counting field and point in the SensorThings API (STA), there is an object in the entity "Thing". For each temporal (respective time interval) and spatial resolution level (count fields/count points), an object stands in the entity "Datastreams". The real-time data on the number of bicycles per time interval and unit of space is published in the STA in the entity "Observations". The temporal and spatial resolution levels can be found in the data set description. All times are given in Coordinated Universal Time (UTC). In the Datastreams entity, there are additional key-value pairs under the "key" "properties" in the JSON object. Following the service and layer structure in GIS, we have introduced service and layer as additional "key-value pairs" under the JSON property. Here is an example: { "properties":{ "serviceName": "HH_STA_HamburgerRadzaehlnetz", "layerName": "Number_Fahrraeder_Zaehlfeld_5-Min", "key":"value"} } Available layers in the layerName are: * Number of bicycles_Zaehlfeld_5-Min * Number of bicycles_point of destination_15-min * Number of bicycles_point of destination_1 hour * Number of bicycles_point of destination_1 day * Number_riding bikes_point_1-week With the help of these "key-value pairs", filters can then be defined for the REST request, e.g. https://iot.hamburg.de/v1.0/Datastreams?$filter=properties/serviceName eq 'HH_STA_HamburgerRadzaehlnetz' and properties/layerName eq 'Number_Fahrraeder_Zaehlfeld_5-Min' The real-time data can also be obtained through an MQTT broker. The necessary IDs can be obtained via a REST request and then used for the subscription to a data stream: MQTT broker: iot.hamburg.de Topic: v1.0/Datastream({id})/Observations

The data set contains the position of all StadtRAD stations in the Hamburg city area and the number of bicycles and load pedals currently available for rental.

More information about the real-time service:

The real-time data service contains the position of all StadtRAD stations in the Hamburg city area and the number of bicycles and load pedals currently available for rental in JSON format provided in the SensorThings API (STA). In the SensorThings API (STA), the entity "Thing" stands for one StadtRad station at a time. For the number of available wheels and the load pedals, there is one entity "Datastream" for each "Thing". The number of available wheels (real-time data) is obtained via the entity "Observations".

All times are given in Coordinated Universal Time (UTC).

In the Datastreams entity, there are additional key-value pairs under the "key" "properties" in the JSON object. Following the service and layer structure in GIS, we have introduced service and layer as additional "key-value pairs" under the JSON property.

{ "properties":{ "serviceName": "HH_STA_StadtRad", "layerName": "E-carrier", "key":"value"} }

Available layers in the layerName are: * E-load bicycle * Bicycles

With the help of these "key-value pairs", filters can then be defined for the REST request, e.g. https://iot.hamburg.de/v1.0/Datastreams?$filter=properties/serviceName eq 'HH_STA_StadtRad' and properties/layerName eq 'E-Lastenraeder'

The real-time data can also be obtained through an MQTT broker. The necessary IDs can be obtained via a REST request and then used for the subscription to a data stream:

MQTT broker: iot.hamburg.de Topic: v1.0/Datastream({id})/Observations

This is a georeferenced data collection (database) with the released geoscientific drilling and profile data from the geological strata directories. The basis of the data encryption is the "Symbol Key Geology (SEP1 of 1991)" of the State Geological Services of Germany. If approved for publication, the data will be displayed in the Hamburg Drill Data Portal. For free machine processing in accordance with the Hamburg Transparency Act, data in the format gml is provided in a rar archive. This contains the master data of all drillings. Due to their size, the shift data are divided into 7 files according to the districts of Hamburg and do not contain the data of private drilling for which no release for publication is available for data protection reasons. The download files are updated as required. For a better understanding of the data, a file with field descriptions and key lists is also provided. The data will also be provided by the WFS services ¿WFS BoreholeML 3.0 Header¿ and ¿WFS BoreholeML 3.0¿ for the drill point map Germany, subject to release for publication. The data are not available in the original SEP1 but in the more undifferentiated BoreholeML3 format. These two services provide complex GML schemas that cannot be easily processed by standard GIS clients such as ArcMap or QGis.

The street tree cadastre includes the area-wide representation of trees on public street plots as a basis for tree inspections for traffic safety and planning. Important data fields are: location, genus/species, year of planting, crown circumference, stem diameter, biological parameters and signs of damage. An integrated GIS component provides fast graphic visualization of the tree locations and background maps. The factual data is available in a SQL Server database. It is recorded as part of ongoing surveys and updates. The updates are also made as part of the prescribed tree inspections for road safety. The - online street tree register - includes the area-wide representation of the trees on public street plots with essential root attributes as well as the data of the Hamburg Port Authority, which are stored in a separate database. The following data fields are assigned to each tree: location, genus/species, year of planting, crown diameter and trunk circumference. This data, recorded as part of regular tree inspections, is updated annually for the Internet as of January 1st. They are available as a WMS and WFS service and in GML format for download.

The road tree cadastre includes the comprehensive representation of the trees on public street corridors as the basis of tree controls for traffic safety and planning. Key data fields are: Location, genus/species, plant year, crown circumference, stem diameter, biological parameters and damage characteristics. The fast graphical visualisation of tree locations and background maps provides an integrated GIS component. The material data is available in an SQL Server database. It is recorded as part of continuous surveying and updates. These updates are also carried out within the framework of the prescribed tree controls for road safety.

The online street tree cadastre includes the comprehensive representation of the trees on public street corridors with essential root attributes as well as the data of the Hamburg Port Authority, which are stored in its own database. The following data fields are assigned to each tree: Location, genus/species, plant year, crown diameter and trunk circumference. This data collected as part of regular tree inspections is updated annually for the Internet as of 1 January. They are available as a WMS & WFS service as well as in the format GML for download.

The land use plan presents the type of land use resulting from the intended urban development according to the foreseeable needs of the City of Hamburg (Baugesetzbuch § 5). It is binding on authorities and public authorities, but does not yet establish any building claims. As a preparatory land-use plan with a scale of 1:20,000, it outlines the planning. It thus leaves room for the development plans to be developed from it. A large number of plans and other usage regulations according to other legal regulations are components of the land use plan, for the sake of clarity they are summarized in a separate supplement "Notifications, markings and notes". New planning goals of the city of Hamburg such as the "HafenCity" as well as small-scale changes require constant updates of the land use plan. In addition to the land use plan, the landscape program is an ecological and open space planning contribution to urban development planning, with an emphasis on the landscape qualities. Land Use Plan Hamburg as amended by the re-announcement of October 1997 Including the 1. - 181. Amendment and 1. - 15th corrigendum - as of January 2024, including the adjustments due to the contour alignment of construction/open spaces September 2014 and updated memorandum takeovers as of September 2022. Notes: If change overviews are provided in the portals, they show the planning status - see below "Subordinate objects - Change overview". Geo-information systems (GIS) - data, internet, intranet: The Land Use Plan Hamburg is available: - In various Internet and Intranet portals, for the public: http://www.hamburg.de/bebauungsplaene-online (including the Hamburg Landscape Programme, development plans); See also here under "References". - In editable and non-editable data formats for a limited group of users. For further processing, the data is made publicly available as a WFS download service and as a WMS display service.