de: tabelle sachdaten vbz bus hackzurich tram verspatung offentlicher-verkehr punktlichkeit

de:
Diese Daten ermöglichen einen sehr genauen Vergleich zwischen den geplanten (SOLL) und den effektiv erfolgten (IST) Fahrzeiten jedes Fahrzeugs der Verkehrsbetriebe Zürich (VBZ). Die Haltestellenankünfte und -abfahrten jedes Fahrzeugs auf seiner Linie wird sekundengenau gemessen.

Wir publizieren jede Woche einen neuen Datensatz  zu den geplanten (SOLL) und effektiven (IST) Fahrzeiten, da das Datenvolumen sonst schnell zu gross wird. Ein Datensatz einer Woche umfasst rund 250 MB. Die Dateinamen zeigen den Zeitraum der Fahrzeitenvergleiche an: «Fahrzeiten_SOLL_IST_***VON-DATUM***_***BIS-DATUM***.csv».

Die beiden Tabellen ***Haltepunkt.csv*** und ***Haltestelle.csv*** sind Matchingtabellen.

Hier finden Sie die Daten des Jahres 2019. Die wöchentlich nachgeführten Fahrzeiten der vergangenen Jahre (seit 2015) finden sie in den Datasets «[**Fahrzeiten *[JAHR]* der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)**](https://data.stadt-zuerich.ch/dataset?q=%22SOLL-IST-Vergleich%22&sort=title_string+desc)».

name: Verkehrsbetriebe Zürich, Departement der Industriellen Betriebe

stadt-zurich

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

de: Fahrzeiten 2019 der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)


maintainer: OGD-Koordinationsstelle Kanton Thurgau

state: active

type: dataset

de: csv

media_type: text/csv

de: Lotteriefonds Kanton Thurgau: Zugesprochene Beiträge (csv)

format: CSV

mimetype: text/csv

license: CC BY 4.0

de: json

media_type: application/json

de: Lotteriefonds Kanton Thurgau: Zugesprochene Beiträge (json)

format: JSON

mimetype: application/json

de: Der Datensatz enthält die zugesprochenen Projektbeiträge aus dem Lotteriefonds des Kantons Thurgau. Zuständig für die Bearbeitung der Gesuche an den Lotteriefonds ist das Kulturamt Kanton Thurgau. Unterstützt werden kulturelle, wissenschaftliche und gemeinnützige Projekte, die einen Bezug haben zum Kanton und von überregionaler Bedeutung sind.Die gesetzlichen Grundlagen und die formalen, inhaltlichen und kulturpolitischen Kriterien für die Beurteilung von Projekten sind online unter www.kulturamt.tg.ch einzusehen.

culture

fr: Culture, médias, société de l'information, sport

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

it: Cultura, media, società dell'informazione, sport

kanton-thurgau

fr: Canton de Thurgovie

de: Kanton Thurgau

en: Canton of Thurgau

it: Cantone di Turgovia

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

political_level: canton

type: organization

approval_status: approved

key: guid

key: uri

value: TG-Kt DCAT Harvester


maintainer: Statistisches Amt des Kantons Zürich, Data Shop

label: Team "Data" des Kantons Zürich

de: Anfragestatistik des Data Shop im Statistischen Amt des Kantons Zürich ab 2015

de: Anfragestatistik des Data Shop im Statistischen Amt des Kantons Zürich - kontrollierte Vokabulare

de: Die Abteilung «Data» des Statistischen Amts ist die Anlaufstelle für alle Fragen zu statistischen Informationen. Das Team bewirtschaftet das statistische Grundangebot des Kanton Zürich und bietet Nutzenden kostenlose Auskunft und Beratung zu Anfragen per Telefon oder E-Mail. Seit 2015 werden Anfragen mit Metadaten erfasst und in einer Anfragenstatistik archiviert.

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.

kanton-zuerich

capacity: public

value: ZH-Kt Statistisches Amt - DCAT Harvester


maintainer: Open Data Zürich

de: stzh krematorium vektordaten punktdaten geodaten geoportal

media_type: dxf

format: DXF

de: Web Map Service

media_type: WMS

format: WMS

de: Web Map Tile Service

media_type: text/xml

format: XML

mimetype: text/xml

media_type: CSV

media_type: gpkg

format: GPKG

media_type: SHP

format: SHP

de: Web Feature Service

media_type: WFS

format: WFS

de: Krematorium.json (GeoJSON-Services)

media_type: JSON

de:
Standorte Krematorium

**Zweck**: Lokalisierung der Krematorien

geodaten

display_name: geodaten

geoportal

display_name: geoportal

krematorium

display_name: krematorium

punktdaten

display_name: punktdaten

stzh

display_name: stzh

vektordaten

display_name: vektordaten

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

population

fr: Population

de: Bevölkerung

en: Population

it: Popolazione

name: Bestattungs- und Friedhofamt, Bevölkerungsamt, Präsidialdepartement

stadt-zurich

fr: Ville de Zurich

de: Stadt Zürich

en: City of Zurich

it: Cità di Zurigo

fr: Vous trouverez ici les données de la ville de Zürich. En parallèle, Open Data Zürich a son propre portail Open Data où vous pouvez trouver également des manuels et des documents sur le traitement des données. À de rares exceptions près, toutes les données publiées par Open Data Zürich sont sous une licence «Creative Commons Zero».

en: Here you find all publicly available data published by Open Data Zürich. In addition, the city of Zurich runs its own Open Data Portal, where you find manuals and documentation about the handling of datasets. With only a few exceptions, all datasets from Open Data Zürich are licensed under «Creative Commons Zero».

it:
Open Data Zürich propone qui dati pubblici della città di Zurigo, pronti alla libera utilizzazione.
La città di Zurigo dispone parallelamente di un proprio portale Open Data, sul quale sono disponibili anche istruzioni e documentazioni per contestualizzare i datasets.
A parte poche eccezioni tutte le datasets della città di Zurigo hanno una licenza «Creative Commons Zero».

political_level: commune

value: ZH - DCAT Harvester

de: Krematorium


maintainer: Fachstelle für OGD Basel-Stadt

de: csv

de: Wahl eines Mitglieds des Gerichts für fürsorgerische Unterbringungen (csv)

license: CC BY 3.0 CH

de: json

de: Wahl eines Mitglieds des Gerichts für fürsorgerische Unterbringungen (json)

de: Dieser Datensatz zeigt die Resultate des 1. Wahlgangs der Wahl eines Mitglieds des Gerichts für fürsorgerische Unterbringung vom 9. Mai 2021.

legislation

fr: Législation

de: Gesetzgebung

en: Legislation

it: Legislazione

politics

fr: Politique

de: Politik

en: Politics

it: Politica

kanton-basel-stadt

fr: Canton de Bâle-Ville

de: Kanton Basel-Stadt

en: Canton of Basel-City

it: Cantone di Basilea-Città

de: Der Kanton Basel-Stadt veröffentlicht nach und nach Open Government-Datensätze von kantonalen Ämtern und Dienststellen. Die kantonale Fachstelle für Open Government Data ist als Koordinationsorgan zuständig für die Unterstützung der datenpublizierenden Verwaltungsstellen.

value: BS Kanton Stadt - DCAT Harvester


maintainer: Fachstelle Open Government Data des Kantons Zürich

label: Fachausschuss für offene Behördendaten: Standards

label: Repository: Formale Leitlinien zur Datenpublikation des Kantons Zürich

de: Leitlinien des Kantons Zürich für einfach nutzbare Behördendaten (Version 1.0)

media_type: text/html

de: Version 1.0 in Kraft seit dem 16. Dezember 2021.

format: HTML

mimetype: text/html

de: Handlungsleitende Normen, um offene Behördendaten ('Open Government Data', OGD) bereitzustellen, die einfach nutzbar sind. Der Fachausschuss Open Government Data des Kantons Zürich verwaltet die Normen gemäss der Maxime, den Bedürfnissen der Nutzenden zweckmässig und wirtschaftlich zu entsprechen. Die Fach- und Koordinationsstelle Open Government Data nimmt Feedback (Hinweise, Wünsche und Fragen) zu den Leitlinien entgegen. Entweder als 'Issue' im Repository (verlinkt unter 'Weitere Informationen') oder via E-Mail (verlinkt unter 'Kontakt'). Im Austausch mit den Nutzenden klärt sie deren Bedürfnisse, berät mit den Datenverwaltenden ('Data Custodians') mögliche Lösungen und schlägt diese vierteljährlich dem Fachausschuss zur Inkraftsetzung vor.

national-economy

de: Volkswirtschaft

fachstelle-ogd-kanton-zuerich

de: Fach- und Koordinationsstelle Open Government Data Kanton Zürich

de: Die Fach- und Koordinationsstelle Open Government Data (OGD) ist das kantonale Kompetenzzentrum für offene Behördendaten im Statistischen Amt. Wir unterstützen die Organisationseinheiten und Organe des Kantons bei der Bereitstellung ihrer nicht schützenswerten Daten als Open Data.

value: ZH-Kt Fachstelle OGD - DCAT Harvester


de: punktlichkeit tabelle verspatung hackzurich vbz offentlicher-verkehr sachdaten tram bus

de:
Diese Daten ermöglichen einen sehr genauen Vergleich zwischen den geplanten (SOLL) und den effektiv erfolgten (IST) Fahrzeiten jedes Fahrzeugs der Verkehrsbetriebe Zürich (VBZ). Die Haltestellenankünfte und -abfahrten jedes Fahrzeugs auf seiner Linie wird sekundengenau gemessen.

Wir publizieren jede Woche einen neuen Datensatz  zu den geplanten (SOLL) und effektiven (IST) Fahrzeiten, da das Datenvolumen sonst schnell zu gross wird. Ein Datensatz einer Woche umfasst rund 250 MB. Die Dateinamen zeigen den Zeitraum der Fahrzeitenvergleiche an: «Fahrzeiten_SOLL_IST_***VON-DATUM***_***BIS-DATUM***.csv».

Die beiden Tabellen ***Haltepunkt.csv*** und ***Haltestelle.csv*** sind Matchingtabellen.

Hier finden Sie die Daten des Jahres **2022**. Die wöchentlich nachgeführten Fahrzeiten der vergangenen Jahre (seit 2015) finden sie in den Datasets «[**Fahrzeiten *[JAHR]* der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)**](https://data.stadt-zuerich.ch/dataset?q=%22SOLL-IST-Vergleich%22&sort=title_string+desc)».

stadt-zurich

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

de: Fahrzeiten 2022 der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)


maintainer: Geoinformationdienst

title_for_slug: Kennzahlen öffentliche Ladeinfrastruktur Elektromobilität

de: kennzahlen-ladeinfrastruktur-schweiz mobilitat e-mobilitat elektromobilitat energie geoinformation erneuerbare-energie bfe gis geodaten statistiken

fr: Chiffres-clés concernant l’infrastructure de recharge pour la mobilité électrique

en: Key figures about the charging infrastructure for electrical vehicles

it: Indicatori dell'infrastruttura di ricarica per veicoli elettrici

author: Geoinformationdienst

label: Documentation

fr: Frictionless datapackage

de: Frictionless datapackage

fr: Frictionless metadata datapackage. See https://frictionlessdata.io/

fr:
La mobilité électrique est une technologie essentielle pour assurer une mobilité plus durable. Elle contribue à l’atteinte des objectifs énergétiques et de politique climatique dans la mesure où les moteurs électriques sont efficaces sur le plan énergétique et où le recours à l’électricité permet d’utiliser une énergie renouvelable. La disponibilité de bornes de recharge publiques constitue un facteur de réussite déterminant pour la diffusion des voitures électriques. À cet effet, l’application https://je-recharge-mon-auto.ch indique en temps réel les bornes de recharge disponibles pour les véhicules électriques.

En Suisse, l’infrastructure de recharge pour les véhicules électriques ne cesse de s’étoffer. Pour documenter cette évolution, les données en temps réel disponibles sur https://je-recharge-mon-auto.ch sont régulièrement analysées et des chiffres-clés concernant l’infrastructure de recharge sont calculés. Ces derniers sont collectés quotidiennement et publiés chaque mois. La collecte a commencé en novembre 2020 et se poursuit actuellement. Les chiffres-clés sont collectés aussi bien à l’échelle nationale que cantonale. Une documentation détaillée est mise à disposition pour une meilleure compréhension des données.

Visualisation des chiffres clés : http://www.je-recharge-mon-auto.ch/statistiques

en:
Electric mobility is a key technology for more sustainable mobility and is one way of achieving ambitious energy and climate policy goals. Electric engines are efficient, and using electricity means that renewable energies can also be used. The availability of public charging stations is a critical factor in the success of the increasingly widespread use of electric cars, which is why https://www.recharge-my-car.ch displays charging station availability for electric vehicles in real time.

The charging infrastructure for electric vehicles in Switzerland is constantly being developed. We use real-time data from https://www.recharge-my-car.ch to regularly evaluate the ever-increasing number of charging stations, charging points, and types of plug in Switzerland. Since November 2020, this data has been and will continue to be collected on a daily basis for the whole of Switzerland and for the individual cantons, and then averaged each month. This gives an overview of how the charging infrastructure is expanding. Detailed documentation is available for a better understanding of the data.

Visualization of the key figures: http://www.recharge-my-car.ch/keydata

de:
Die Elektromobilität ist eine Schlüsseltechnologie für eine nachhaltigere Mobilität und trägt zur Erreichung ambitionierter energie- und klimapolitischer Ziele bei, da Elektroantriebe effizient sind und der Einsatz von Strom die Nutzung erneuerbarer Energien erlaubt. Ein wichtiger Erfolgsfaktor für die Verbreitung von Elektroautos ist die Verfügbarkeit von öffentlichen Ladestationen. Deshalb zeigt https://ich-tanke-strom.ch die Verfügbarkeit von Ladestationen für Elektrofahrzeuge in Echtzeit an.

Die öffentliche Ladeinfrastruktur für Elektrofahrzeuge in der Schweiz wird stetig ausgebaut. Um diese Entwicklung zu dokumentieren, werden die Echtzeit-Daten von https://ich-tanke-strom.ch regelmässig ausgewertet und Kennzahlen zur Ladeinfrastruktur abgeleitet. Die Kennzahlen werden täglich erhoben und anschliessend pro Monat gemittelt. Die Erhebung startete im November 2020 und wird laufend weitergeführt. Die Kennzahlen werden für die ganze Schweiz sowie für die einzelnen Kantone erhoben. Für das bessere Verständnis der Daten steht eine detaillierte Dokumentation bereit.

Visualisierung der Kennzahlen: http://www.ich-tanke-strom.ch/kennzahlen

it:
La mobilità elettrica è una tecnologia chiave per una mobilità più sostenibile e contribuisce al raggiungimento di ambiziosi obiettivi di politica energetica e climatica: infatti, i veicoli a propulsione elettrica sono efficienti e l'impiego dell'elettricità permette l'utilizzo di energie rinnovabili. Un importante fattore di successo per la diffusione delle auto elettriche è la disponibilità di stazioni di ricarica pubbliche. Per questo motivo, la piattaforma https://pieno-di-elettricita.ch mostra in tempo reale la disponibilità delle stazioni di ricarica per veicoli elettrici.

L'infrastruttura di ricarica per veicoli elettrici in Svizzera viene costantemente ampliata. Per documentare questo sviluppo, i dati in tempo reale di https://pieno-di-elettricita.ch vengono valutati regolarmente e da essi vengono ricavati gli indicatori dell'infrastruttura di ricarica. Tali indicatori sono rilevati quotidianamente per l'intera Svizzera e per i singoli Cantoni, e se ne calcola la media mensile. Il rilevamento ha avuto inizio nel novembre 2020 ed è ancora in corso. Per una migliore comprensione dei dati, è disponibile una documentazione dettagliata.

Visualizzazione degli indici: http://www.pieno-di-elettricita.ch/indici

energy

fr: Energie

de: Energie

en: Energy

it: Energia

industry

fr: Industrie, services

de: Industrie, Dienstleistungen

en: Industry and services

it: Industria, servizi

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).

political_level: confederation


maintainer: EnviDat Support

en: snow metamorphism 18o advection stable-water-isotope

en: Read-me

media_type: text/plain

en: A short description of the data contained in the zipped-file. Recommended for reading before downloading the dataset.

format: TXT

mimetype: text/plain

en: Data files and read-me

media_type: application/zip

en: raw data and micro-CT data available from contacts

format: ZIP

mimetype: application/zip

en:
Stable water isotopes (δ18O) obtained from snow and ice samples of polar regions are used to reconstruct past climate variability, but heat and mass transport processes can affect the isotopic composition. Here we present an experimental study on the effect on the snow isotopic composition by airflow through a snow pack in controlled laboratory conditions. The influence of isothermal and controlled temperature gradient conditions on the δ18O content in the snow and interstitial water vapor is elucidated. The observed disequilibrium between snow and vapor isotopes led to exchange of isotopes between snow and vapor under non-equilibrium processes, significantly changing the δ18O content of the snow. The type of metamorphism of the snow had a significant influence on this process.
Ebner, P. P., Steen-Larsen, H. C., Stenni, B., Schneebeli, M., and Steinfeld, A.: Experimental observation of transient δ18O interaction between snow and advective airflow under various temperature gradient conditions, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-16, accepted, 2017.

advection

display_name: advection

metamorphism

display_name: metamorphism

snow

display_name: snow

stable-water-isotope

display_name: stable-water-isotope

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

political_level: other

value: Envidat Harvester

en: Experiments on stable water isotopes,  snow metamorphism, and advection


intratrait

maintainer: Christian Rixen

title_for_slug: intratrait

en: elevation-range elevation-gradient cold-adapted-plants neighbour-interactions climate-change plant-traits

media_type: R

format: SERVICE

en: Plant trait data along elevation gradients on mountains

en:
This data set was used to test whether species specialized to high elevations or with narrow elevational ranges show more conservative (i.e. less variable) trait responses across their elevational distribution, or in response to neighbours, than species from lower elevations or with wider elevational ranges. We did so by studying intraspecific trait variation of 66 species along 40 elevational gradients in four countries (Switzerland, Australia, New Zealand, China) in both hemispheres. As an indication of potential neighbour interactions that could drive trait variation, we also analysed plant species’ height ratio, its height relative to its nearest neighbour.
The following traits and parameters were measured and are available in this data set:
As an indication of plant stature, we measured vegetative and generative height, where vegetative height was distance from soil to highest vegetative leaf and generative height was distance to the highest point on the reproductive shoot. As a measure of reproductive investment, we noted the presence of flowers on the randomly chosen individuals (see below). As a measure of individual and genet basal area, we measured individual plant and patch diameters, in two dimensions (along the largest diameter and perpendicular to it). In clonal plant species, plant diameter was equivalent to an individual rosette, whereas patch diameter referred to the whole genet and could represent the size of a tuft, tussock or cushion. For genera with more singular growth forms (e.g., some Gentiana species) plant and patch diameter were the same. The two diameter measurements were made at right angles, allowing estimates of patch and plant areas to be calculated as an ellipse (i.e., area = 0.5 a 0.5 b Π). All traits were measured on ten randomly selected individuals per site. Flower count data was considered in a binary fashion on a per individual basis (because for some species individuals only produce one flower when flowering) so that the presence or absence of flower(s) was a nominal value between 0 and 10 for each species at each site. We then collected at least three leaves (up to 30 for small and light leaves) from each of the first three individuals selected from each species for determination of leaf dry matter content (LDMC) and specific leaf area (SLA). For calculations of LDMC and SLA, fresh leaves were scanned on a flatbed scanner to determine leaf area. Leaves were then weighed on a balance to a precision of +/- 0.001g, prior to being air dried and reweighed with a balance to a precision of +/- 0.0001g. LDMC was calculated by dividing dry leaf mass by fresh leaf mass. SLA was calculated by dividing leaf area by dry leaf mass. Additionally, within an area of 10 cm diameter around the target individual, we determined the tallest neighbouring species and measured its vegetative and generative height, and estimated the percent cover of the target species, other vegetation, rock, and bare soil.
For more details see Rixen et al. 2022, Journal of Ecology.

climate-change

display_name: climate-change

cold-adapted-plants

display_name: cold-adapted-plants

elevation-gradient

display_name: elevation-gradient

elevation-range

display_name: elevation-range

neighbour-interactions

display_name: neighbour-interactions

plant-traits

display_name: plant-traits

en: intratrait


dma-mediathek

maintainer: Digitale Medien der Armee DMA, Kundendienst Medienagentur

title_for_slug: dma-mediathek

fr: mediatheque ddps groupes-thematiques video photo 360 militaire

de: vbs video 360 mediathek foto militar themes

en: video 360 photograph media-library military theme-world ddps

it: video ddps foto 360 ambiti-tematici militare mediateca

fr: MNA - Médiathèque historique

en: AFDM - Historic Media Library

de: DMA - Historische Mediathek

it: MDE - Mediateca storica

media_type: html

fr: Photos et films historiques.

de: Historische Momentaufnahmen in Fotos und in Filmen.

en: Historical snapshots and video footage.

it: Istantanee storiche in forma di foto e filmati.

mimetype: html

fr: MNA - Médiathèque

de: DMA - Mediathek

en: AFDM - Media library

it: MDE - Mediateca

fr: Compétences en photos et en vidéos.

de: Kompetenz in Fotos und Videos.

en: Expertise for photographs and videos.

it: Competenza sotto forma di foto e video.

fr: MNA - Métadonnées

en: AFDM - Metadata

de: DMA - Metadaten

it: MDE - Metadati

fr: Les métadonnées montrent les clients et ressources de la médiathèque.

de: Die Metadaten zeigen, welche Mandanten und Assets erfasst sind.

en: The metadata show the clients and assets of the media library.

it: I metadati mostrano i clienti e asset della mediateca.

fr: MNA - Ressources

en: AFDM - Assets

de: DMA - Assets

it: MDE - Asset

fr: Cette liste contient les ressources saisies par MNA.

de: Diese Liste enthält die von DMA erfassten Assets.

en: This list contains the assets of AFDM.

it: Questa lista contiene i asset dello MDE.

fr: Sis à Berne, le MNA est le centre de compétences pour les produits et services dans les domaines de la formation et de la communication.

en: The AFDM, located in Bern, is the competence center for products and services in the fields of education and communication.

de: Das DMA mit Standort in Bern ist das Kompetenzzentrum für Produkte und Dienstleistungen in den Bereichen der Ausbildung und der Kommunikation.

it: Il MDE, con sede a Berna, è il centro di competenza per i prodotti e le prestazioni nei settori dell'istruzione e della comunicazione.

ambiti-tematici

display_name: ambiti-tematici

ddps

display_name: ddps

foto

display_name: foto

groupes-thematiques

display_name: groupes-thematiques

media-library

display_name: media-library

mediateca

display_name: mediateca

mediathek

display_name: mediathek

mediatheque

display_name: mediatheque

militaire

display_name: militaire

militar

display_name: militar

militare

display_name: militare

military

display_name: military

culture

fr: Culture, médias, société de l'information, sport

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

it: Cultura, media, società dell'informazione, sport

name: Digitale Medien der Armee (DMA), Departement VBS

fr: Sis à Berne, le Centre des médias numériques de l’armée MNA est le centre de compétences pour les produits et services dans les domaines de la formation et de la communication.

en: The Armed Forces Digital Media Centre AFDM, located in Bern, is the competence center for products and services in the fields of education and communication.

de: Das Zentrum digitale Medien der Armee DMA mit Standort in Bern ist das Kompetenzzentrum für Produkte und Dienstleistungen in den Bereichen der Ausbildung und der Kommunikation.

it: Il Centro dei media digitali dell’esercito MDE, con sede a Berna, è il centro di competenza per i prodotti e le prestazioni nei settori dell'istruzione e della comunicazione.


maintainer: Bundesamt für Energie BFE

fr: bilan-electricite ogd51-bfe production-nette production-d-electricite statistique-electricite energie-hydraulique consommation-de-courant saldo-import energies-renouvelables consommation-nationale pompes-d-accumulation energie-atomique production-d-electricite-thermique

de: stromverbrauch thermische-stromproduktion landesverbrauch elektrizitaetsbilanz nettoerzeugung wasserkraft kernkraft ogd51-bfe elektrizitaetsstatistik importsaldo speicherpumpen stromproduktion erneuerbare-energien

it: produzione-netta produzione-d-elettricita energie-rinnovabili saldo-importazioni pompe-d-accumulo consumo-nazionale bilancio-elettricita energia-idrica statistica-elettricita produzione-d-elettricita-termica ogd51-bfe energia-atomica consumo-di-corrente

fr: Statistiques heddomadaires: production et consommation d'énergie électrique en Suisse

it: Bilancio dell'elettricità: statistica settimanale - produzione e consumo di energia elettrica in Svizzera

author: Bundesamt für Energie BFE

label: BFE - Elektrizitätsstatistik

media_type: SERVICE

mimetype: SERVICE

fr: Cette statistique, élaborée chaque mercredi, recense la production, l'importation, l'exportation et la consommation d'électricité en Suisse. Elle présente la production hydraulique (centrales au fil de l'eau/centrales à accumulation), la production des centrales nucléaires ainsi que la production thermique classique et d'autres modes de production. Elle indique aussi la consommation des installations de pompage d'accumulation. Elle est établie dans le cadre de la Statistique de l'électricité, qui fait partie de la statistique publique de la Suisse (base légale: LSF).

de: Die Wochenstatistik Elektrizitätsbilanz - Erzeugung und Abgabe elektrischer Energie in der Schweiz gibt Auskunft über Produktion, Import / Export und Verbrauch von Elektrizität in der Schweiz jeweils am Mittwoch auf wöchentlicher Basis. Bei der Produktion werden die Hydrologische Erzeugung (Lauf- und Speicherwerke), die Erzeugung der Kernkraftwerke sowie die Konv.-therm. und andere Erzeugung unterschieden. Der Verbrauch der Speicherpumpen wird ausgewiesen. Die Wochenstatistik Elektrizitätsbilanz wird im Rahmen der Elektrizitätsstatistik erhoben, welche Teil der öffentlichen Statistik der Schweiz ist (gesetzliche Grundlage: BStatG).

bilan-electricite

display_name: bilan-electricite

bilancio-elettricita

display_name: bilancio-elettricita

consommation-de-courant

display_name: consommation-de-courant

consommation-nationale

display_name: consommation-nationale

consumo-di-corrente

display_name: consumo-di-corrente

consumo-nazionale

display_name: consumo-nazionale

elektrizitaetsbilanz

display_name: elektrizitaetsbilanz

elektrizitaetsstatistik

display_name: elektrizitaetsstatistik

energia-atomica

display_name: energia-atomica

energia-idrica

display_name: energia-idrica

energie-atomique

display_name: energie-atomique

energie-hydraulique

display_name: energie-hydraulique

energie-rinnovabili

display_name: energie-rinnovabili

energies-renouvelables

display_name: energies-renouvelables

erneuerbare-energien

display_name: erneuerbare-energien

importsaldo

display_name: importsaldo

kernkraft

display_name: kernkraft

landesverbrauch

display_name: landesverbrauch

nettoerzeugung

display_name: nettoerzeugung

pompe-d-accumulo

display_name: pompe-d-accumulo

pompes-d-accumulation

display_name: pompes-d-accumulation

production-d-electricite

display_name: production-d-electricite

production-d-electricite-thermique

display_name: production-d-electricite-thermique

production-nette

display_name: production-nette

produzione-d-elettricita

display_name: produzione-d-elettricita

produzione-d-elettricita-termica

display_name: produzione-d-elettricita-termica

produzione-netta

display_name: produzione-netta

saldo-import

display_name: saldo-import

saldo-importazioni

display_name: saldo-importazioni

speicherpumpen

display_name: speicherpumpen

statistica-elettricita

display_name: statistica-elettricita

statistique-electricite

display_name: statistique-electricite

stromproduktion

display_name: stromproduktion

stromverbrauch

display_name: stromverbrauch

thermische-stromproduktion

display_name: thermische-stromproduktion

wasserkraft

display_name: wasserkraft

statistical-basis

fr: Bases statistiques

de: Statistische Grundlagen

en: Statistical basis

it: Basi statistiche

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

bundesamt-fur-energie-bfe

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).


en: hydrology discharge climate-change-impact model water-temperature

en: Data access

media_type: .zip

en:
This work presents the first extensive study of climate change impacts on rivers temperature in Switzerland. Results show that even for low emissions scenarios, water temperature increase will lead to adverse effect for both ecosystems and socioeconomic sectors (such as nuclear plant cooling) throughout the 21st century. For high emissions scenarios, the effect will be worsen. This study also shows that water warming in summer will be more important in Alpine regions than in lowlands.
This material is distributed under CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/legalcode).

climate-change-impact

display_name: climate-change-impact

discharge

display_name: discharge

hydrology

display_name: hydrology

model

display_name: model

water-temperature

display_name: water-temperature

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

en: Dataset for: Future water temperature of rivers in Switzerland under climate change investigated with physics-based models


maintainer: Joan Casanelles Abella

en: trap-nest urban-ecology osmia-cornuta zurich tartu poznan plant-pollinator-interactions antwerp hylaeus-communis paris chelostoma-florisomne cavity-nesting-bees dna-metabarcoding osmia-bicornis

en: Explanation data variables

en: Larval food composition

en: Urbanization poses threats and opportunities for the biodiversity of wild bees. A main gap relates to the food preferences of wild bees in urban ecosystems, which usually harbour large numbers of plant species, particularly at the larval stage. This data sets describes the larval food of four wild bee species (i.e. Chelostoma florisomne, Hylaeus communis, Osmica bicornis and Osmia cornuta) and three genera (i.e. Chelostoma sp., Hylaeus sp, and Osmia sp.) common in urban areas in five different European cities (i.e. Antwerp, Paris, Poznan, Tartu and Zurich). This data results from a European-level study aimed at understanding the effects of urbanization on biodiversity across different cities and citiscapes, and a Swiss project aimed at understanding the effects of urban ecosystems in wild bee feeding behaviour. Wild bees were sampled using standardized trap-nests in 80 sites (32 in Zurich and 12 in each of the remaining cities), selected following a double gradient of available habitat at local and landscape scales. Larval pollen was obtained from the bee nests and identified using DNA metabarconding. The data provides the plant composition at the species or genus level of the different bee nests of the studied species in the studied sites of the five European cities. For Hylaeus communis, this is the first study in reporting larval food composition.

antwerp

display_name: antwerp

cavity-nesting-bees

display_name: cavity-nesting-bees

chelostoma-florisomne

display_name: chelostoma-florisomne

dna-metabarcoding

display_name: dna-metabarcoding

hylaeus-communis

display_name: hylaeus-communis

osmia-bicornis

display_name: osmia-bicornis

osmia-cornuta

display_name: osmia-cornuta

paris

display_name: paris

plant-pollinator-interactions

display_name: plant-pollinator-interactions

poznan

display_name: poznan

tartu

display_name: tartu

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

zurich

display_name: zurich

en: Larval food composition of four wild bee species in five European cities


de: bus punktlichkeit tabelle verspatung hackzurich vbz sachdaten offentlicher-verkehr tram

media_type: text/csv

de:
Diese Daten ermöglichen einen sehr genauen Vergleich zwischen den geplanten (SOLL) und den effektiv erfolgten (IST) Fahrzeiten jedes Fahrzeugs der Verkehrsbetriebe Zürich (VBZ). Die Haltestellenankünfte und -abfahrten jedes Fahrzeugs auf seiner Linie wird sekundengenau gemessen.

Wir publizieren jede Woche einen neuen Datensatz  zu den geplanten (SOLL) und effektiven (IST) Fahrzeiten, da das Datenvolumen sonst schnell zu gross wird. Ein Datensatz einer Woche umfasst rund 250 MB. Die Dateinamen zeigen den Zeitraum der Fahrzeitenvergleiche an: «Fahrzeiten_SOLL_IST_***VON-DATUM***_***BIS-DATUM***.csv».

Die beiden Tabellen ***Haltepunkt.csv*** und ***Haltestelle.csv*** sind Matchingtabellen.

Hier finden Sie die Daten des Jahres 2016. Die wöchentlich nachgeführten Fahrzeiten der vergangenen Jahre (seit 2015) und die des aktuellen Jahres finden sie in den Datasets «[**Fahrzeiten *[JAHR]* der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)**](https://data.stadt-zuerich.ch/dataset?q=%22SOLL-IST-Vergleich%22&sort=title_string+desc)».

stadt-zurich

fr: Vous trouverez ici les données de la ville de Zürich. En parallèle, Open Data Zürich a son propre portail Open Data où vous pouvez trouver également des manuels et des documents sur le traitement des données. À de rares exceptions près, toutes les données publiées par Open Data Zürich sont sous une licence «Creative Commons Zero».

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

en: Here you find all publicly available data published by Open Data Zürich. In addition, the city of Zurich runs its own Open Data Portal, where you find manuals and documentation about the handling of datasets. With only a few exceptions, all datasets from Open Data Zürich are licensed under «Creative Commons Zero».

it:
Open Data Zürich propone qui dati pubblici della città di Zurigo, pronti alla libera utilizzazione.
La città di Zurigo dispone parallelamente di un proprio portale Open Data, sul quale sono disponibili anche istruzioni e documentazioni per contestualizzare i datasets.
A parte poche eccezioni tutte le datasets della città di Zurigo hanno una licenza «Creative Commons Zero».

de: Fahrzeiten 2016 der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)


maintainer: Michael Lehning

en: snow alpine3d alpine-precipitation alpine3d-simulations snow-cover snow-hydrology snow-distribution

en: ADS datasets and simulation inputs

en: The file contains the ADS datasets of snow depth and input data used for simulations.

en:
Dataset (Model input, snow distribution and validation) for the precipitation scaling paper, which should be cited along with the data set citation.

This data is useful for distributed hydrological modelling or other tasks that involve the study of snow distribution and precipitation in the high Alpine.

The format of the data is for Alpine3D (models.slf.ch) model runs but other models could be used, too.

Please cite:

_Vögeli, C., Lehning, M., Wever, N., Bavay M., 2016: Scaling Precipitation Input to Spatially Distributed Hydrological Models by Measured Snow Distribution., Front. Earth Sci. 4: 108. doi: 10.3389/feart.2016.00108._

Dataset is provided as a single zip file.
The archive contains two directories, the valuable distributed snow depth maps for the landscape Davos and the simulation input.
The archive also contains the file: "ReadMeMetadataDataSetPrecipitationScaling" which explains the data structure.

alpine-precipitation

display_name: alpine-precipitation

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-distribution

display_name: snow-distribution

snow-hydrology

display_name: snow-hydrology

en: Precipitation Scaling Data Set (Vögeli et al., Frontiers)


en: soil-water-balance relative-humidity solar-radiation growing-season-length temperature growing-degree-days precipitation

en: CHELSA-BIOCLIM+

media_type: geotiff

en: Global extented set of bioclimatic variables at different temporal (e.g. monthly, annual, long term normals) resolution in Geotiff format.

format: GeoTIFF

en: CHELSA-BIOCLIM+ Technical Documentation

media_type: PDF

en: Technical documentation document including the variable names, units, scaling, offset, and background.

format: PDF

en: A multitude of physical and biological processes on which ecosystems and human societies depend are governed by climatic conditions. Understanding how these processes are altered by climate change is central to mitigation efforts. Based on mechanistically downscaled climate data, we developed a set of climate-related variables at yet unprecedented spatiotemporal detail as a basis for environmental and ecological analyses. We created gridded data for near-surface relative humidity (hurs), cloud area fraction (clt), near-surface wind speed (sfcWind), vapour pressure deficit (vpd), surface downwelling shortwave radiation (rsds), potential evapotranspiration (pet), climate moisture index (cmi), and site water balance (swb), at a monthly temporal and 30 arcsec spatial resolution globally starting 1980 until 2018. At the same spatial resolution, we further estimated climatological normals of frost change frequency (fcf), snow cover days (scd), potential net primary productivity (npp), growing degree days (gdd), and growing season characteristics for the periods 1981-2010, 2011-2040, 2041-2070, and 2071-2100, considering three shared socioeconomic pathways (SSP126, SSP370, SSP585) and five Earth system models. Time-series variables showed high accuracy when validated against observations from meteorological stations. Climatological normals were also highly correlated to observations although some variables showed notable biases, e.g., snow cover days (scd). Together, the data sets presented here allow improving our understanding of patterns and processes that are governed by climate, including the impact of recent and future climate changes on the world’s ecosystems and associated services to societies.

growing-degree-days

display_name: growing-degree-days

growing-season-length

display_name: growing-season-length

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

soil-water-balance

display_name: soil-water-balance

solar-radiation

display_name: solar-radiation

temperature

display_name: temperature

en: CHELSA-BIOCLIM+ A novel set of global climate-related predictors at kilometre-resolution


de: hackzurich vbz bus punktlichkeit offentlicher-verkehr tram verspatung tabelle sachdaten

de:
Diese Daten ermöglichen einen sehr genauen Vergleich zwischen den geplanten (SOLL) und den effektiv erfolgten (IST) Fahrzeiten jedes Fahrzeugs der Verkehrsbetriebe Zürich (VBZ). Die Haltestellenankünfte und -abfahrten jedes Fahrzeugs auf seiner Linie wird sekundengenau gemessen.

Wir publizieren jede Woche einen neuen Datensatz  zu den geplanten (SOLL) und effektiven (IST) Fahrzeiten, da das Datenvolumen sonst schnell zu gross wird. Ein Datensatz einer Woche umfasst rund 250 MB. Die Dateinamen zeigen den Zeitraum der Fahrzeitenvergleiche an: «Fahrzeiten_SOLL_IST_***VON-DATUM***_***BIS-DATUM***.csv».

Die beiden Tabellen ***Haltepunkt.csv*** und ***Haltestelle.csv*** sind Matchingtabellen.

Hier finden Sie die Daten des Jahres 2018. Die wöchentlich nachgeführten Fahrzeiten der vergangenen Jahre (seit 2015) und die des aktuellen Jahres finden sie in den Datasets «[**Fahrzeiten *[JAHR]* der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)**](https://data.stadt-zuerich.ch/dataset?q=%22SOLL-IST-Vergleich%22&sort=title_string+desc)».

de: Fahrzeiten 2018 der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)


snow-drift-station-flowcapt

maintainer: Benjamin Walter

title_for_slug: snow-drift-station-flowcapt

en: wind-speed acoustic-mass-flux flowcapt raclets snow-blowing snowdrift

en: minimum mass flux

en: The data file contains the minimum mass flux of 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

format: XLS

en: maximum mass flux

en: The data file contains the maximum mass flux of 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: minimum wind spees

en: The data file contains the minimum wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: average wind speed

en: The data file contains the average wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: maximum wind speed

en: The data file contains the maximum wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6 s observations and 54 s stand-by. The time is given in UTC+1.

en: avergaged mass flux

en: Average mass flux of 10 min measurement interval. The Cycle duration is 1 min which includes 6 s observation and 54 s stand-by. The time is given in UTC+1.

en: The FlowCapt is an ultra-robust instrument measuring solid particle acoustic mass - flux intensities (g m‾ ² s‾ ¹) and wind speeds (m s‾ ¹). It was deployed at Gotschnagrat (LON: 46.859 LAT: 9.849). The vertical tube with a length of 1 m monitors snowdrift and snow-blowing; and is mounted at a height between 0.1 an 1.1 m above snow surface. The time within each data set is given in UTC+1.

acoustic-mass-flux

display_name: acoustic-mass-flux

flowcapt

display_name: flowcapt

raclets

display_name: raclets

snow-blowing

display_name: snow-blowing

snowdrift

display_name: snowdrift

wind-speed

display_name: wind-speed

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Snow Drift Station - Flowcapt


de: tram offentlicher-verkehr sachdaten vbz hackzurich verspatung tabelle punktlichkeit bus

de:
Diese Daten ermöglichen einen sehr genauen Vergleich zwischen den geplanten (SOLL) und den effektiv erfolgten (IST) Fahrzeiten jedes Fahrzeugs der Verkehrsbetriebe Zürich (VBZ). Die Haltestellenankünfte und -abfahrten jedes Fahrzeugs auf seiner Linie wird sekundengenau gemessen.

Wir publizieren jede Woche einen neuen Datensatz  zu den geplanten (SOLL) und effektiven (IST) Fahrzeiten, da das Datenvolumen sonst schnell zu gross wird. Ein Datensatz einer Woche umfasst rund 250 MB. Die Dateinamen zeigen den Zeitraum der Fahrzeitenvergleiche an: «Fahrzeiten_SOLL_IST_***VON-DATUM***_***BIS-DATUM***.csv».

Die beiden Tabellen ***Haltepunkt.csv*** und ***Haltestelle.csv*** sind Matchingtabellen.

Hier finden Sie die verfügbaren Daten des Jahres 2015 ab dem 11. November bis zum 31. Dezember 2015. Die wöchentlich nachgeführten Fahrzeiten der vergangenen Jahre und die des aktuellen Jahres finden sie in den Datasets «[**Fahrzeiten *[JAHR]* der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)**](https://data.stadt-zuerich.ch/dataset?q=%22SOLL-IST-Vergleich%22&sort=title_string+desc)».

bus

display_name: bus

hackzurich

display_name: hackzurich

offentlicher-verkehr

display_name: offentlicher-verkehr

punktlichkeit

display_name: punktlichkeit

sachdaten

display_name: sachdaten

tabelle

display_name: tabelle

tram

display_name: tram

vbz

display_name: vbz

verspatung

display_name: verspatung

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

stadt-zurich

fr: Ville de Zurich

de: Stadt Zürich

en: City of Zurich

en: Here you find all publicly available data published by Open Data Zürich. In addition, the city of Zurich runs its own Open Data Portal, where you find manuals and documentation about the handling of datasets. With only a few exceptions, all datasets from Open Data Zürich are licensed under «Creative Commons Zero».

de: Fahrzeiten 2015 der VBZ im SOLL-IST-Vergleich (Nachführung eingestellt)


maintainer: Avalanche Warning Service SLF

en: Avalanche fatalities per year in Switzerland since 1936/1937

en:
This dataset contains the statistics on the number of avalanche fatalities per hydrological year in Switzerland. The data set commences with the beginning of the hydrological year 1936/37 on 01/10/1936. After the completion of a hydrological year, the new data is appended to the existing dataset.

The following information is contained (by column and column title):
 - hydrological year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)

The definition for these four categories as described in the guidelines to the avalanche accident database:

**tour**:
activities include back-country ski, snowboard or snow-shoe touring

**offpiste**:
access from ski area, generally from the top of a skilift with short hiking distances

**transportation.corridors** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people travelling or recreating on open or temporarily closed
transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)

**buildings** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people inside or just outside buildings, and workers on high alpine building
sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

en: Number of avalanche fatalities per hydrological year in Switzerland since 1936-1937


maintainer: Matthias Haeni

en: long-term swiss-forest-lab meteorology climate-change wind-speed relative-humidity meteo precipitation par temperature

en: Data plot of the field station (CLF)

media_type: application/pdf

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

mimetype: application/pdf

en: Site photo of the forest station (CLB)

media_type: image/jpeg

en: Site photo of the forest station from below (viewing upwards the slope).

mimetype: image/jpeg

en: Site aerial photo (Celerina)

en: Site aerial photo from both Celerina stations. Source: Google. 2016. Site aerial photo from both Celerina stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: Data plot of the forest station (CLB)

en: Data file.

en: Site photo of the field station (CLF)

en: Site phote of the field station from the side.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Celerina in Switzerland where one station is located within a natural coniferous forest stand (CLB) with Swiss pine (_Pinus cembra_; 210-250 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CLF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Celerina is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

en: Celerina, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: Elisabeth Hafner

en: satellite validation avalanche-hazard-mapping avalanche snow

en: Satellite Avalanche Mapping Validation data and data description

media_type: ZIP

en: 14 shapefiles to be used only together with the data description also provided as a pdf.

en:
Validation points, validation area, ground truth coverage, SPOT 6 avalanche outlines, Sentinel-1 avalanche outlines, Sentinel-2 avalanche outlines, Davos avalanche mapping (DAvalMap) avalanche outlines as shapefiles and a detailed attribute description (DataDescription_EvalSatMappingMethods.pdf).

Coordinate system: CH1903+_LV95

The generation of this dataset is described in detail in:

Hafner, E. D., Techel, F., Leinss, S., and Bühler, Y.: Mapping avalanches with satellites – evaluation of performance and completeness, The Cryosphere, https://doi.org/10.5194/tc-2020-272, 2021.

avalanche

display_name: avalanche

avalanche-hazard-mapping

display_name: avalanche-hazard-mapping

satellite

display_name: satellite

snow

display_name: snow

validation

display_name: validation

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Satellite avalanche mapping validation data


maintainer: Ana Beatriz Pierri Daunt

en: socio-ecological-system sense-of-place literature-review pdfsearch green-infrastructure resilience landscape-perception ecosystem-services landscape-planning landscape-services multifunctionality planning decision-making landscape-ecology

en: 2. Frequency of additional concepts.

media_type: CSV

en: 3. Use of any early concept.

en: 5. Planning steps.

en: 6. Protocol

media_type: XLSX

en: 1. Frequency of early concepts.

en: 4. Use of any additional concept.

en:
Table of content: 1. Frequency of early concepts; 2. Frequency of additional concepts; 3. Use of any early concept; 4. Use of any additional concept, 5. Planning steps; 6. Protocol.

The present dataset is part of the published scientific paper entitled “Landscape ecological concepts in planning: review of recent developments” (Hersperger et al., 2021). The goal of this research was to review recent publications to assess the use of landscape ecological concepts in planning. Specifically, we address the following research questions: Q1. Landscape ecological concepts: What are they? How frequently are they mentioned in current research? Q2. How are landscape ecological concepts integrated in landscape planning?

We analysed all empirical and overview papers that have been published in four key academic journals in the field of landscape ecology and landscape planning in the years 2015–2019 (n = 1918). Four key journals in the field of landscape ecology were selected to conduct the analysis, respectively Landscape Ecology (LE), Landscape Online (LO), Current Landscape Ecology Reports (CLER), and Landscape and Urban Planning (LUP). The title, abstract and keywords of all papers were read in order to identify landscape ecological concepts. Then, all 1918 papers went through a keyword search to identify the use of early and additional concepts. We used the “pdfsearch” package in R programming language and searched for singular and plural forms and different variations of the concepts (see Supplementary material 1, Table A). As a result, we provided four outputs:

  1. Frequency of early concepts. This data provides the total number of times each article used each early concept (Q1). This data was used to produce the Figure 2a at the original publication.

  2. Frequency of additional concepts. This data provides the total number of times each article used each additional concept (Q1). This data was used to produce the Figure 2b at the original publication.

  3. Use of any early concept. This data provides the total number of times each article used any early concept (Q1).
This data was used to produce the Figure 3a at the original publication.

  4. Use of any additional concept. This data provides the total number of times each article used any additional concept (Q1). This data was used to produce the Figure 3b at the original publication.

To address the second question (Q2), the title, abstract and keywords of the papers included in our sample (n=1918 articles) were screened to identify papers that might show how landscape ecological concepts are integrated into planning. We selected 52 empirical papers (see Supplementary material – 4 Integration of landscape ecological concepts into planning), and we provided two outputs:

  5. Planning steps. This data provides the number of times landscape ecological concepts were addressed in each
planning steps in 52 empirical papers analysed in detail (Q2). This data was used to produce the Figure 4 at the
original publication.

  6. Protocol for assessing the integration of landscape ecological concepts into planning. To systematically collect the
data, we used this protocol which addressed the following questions: (a) which type of planning is addressed by the
paper? (b) to which planning level does the paper refer to? (c) which concepts are integrated in any of the planning
steps described above?

decision-making

display_name: decision-making

ecosystem-services

display_name: ecosystem-services

green-infrastructure

display_name: green-infrastructure

landscape-ecology

display_name: landscape-ecology

landscape-perception

display_name: landscape-perception

landscape-planning

display_name: landscape-planning

landscape-services

display_name: landscape-services

literature-review

display_name: literature-review

multifunctionality

display_name: multifunctionality

pdfsearch

display_name: pdfsearch

planning

display_name: planning

resilience

display_name: resilience

sense-of-place

display_name: sense-of-place

socio-ecological-system

display_name: socio-ecological-system

en: The usage of landscape ecological concepts in the planning literature


maintainer: Anita C. Risch

en: soil-chemistry soil soil-biology global mineralization nutrient-network worldwide grassland

en:
site.code: Site code

Continent: Continent

sampleID: Sample ID

nn.latitude: Lattitude

nn.longitude: Longitude

bioclim.T.ann: Mean annual temperature (°C)

bioclim.T.var: Temperature variability (°C)

bioclim.T.q.wet: Temperature of the wettest quarter (°C)

bioclim.T.q.dry: Temperature of the driest quarter (°C)

bioclim.T.q.warm: Temperature of the warmest quarter (°C)

bioclim.P.ann: Mean annual preciptiation (mm)

bioclim.P.q.wet: Precipitation of the wettest quarter (mm)

ch.pH: pH

ch.WSK.vol: Water holding capacity (vol%)

ch.bulkdensity.gcm3: Bulk density (g cm-3)

ch.porespace: Pore space (vol%)

ch.sand.perc: Soil texture: sand (%)

ch.silt.perc: Soil texture: silt (%)

ch.clay.perc: Soil texture: clay (%)

ch.NO3start.mgg: NO3 at the beginning of the incubation (mgkg)

ch.Ntot.perc: Total soil N (%)

ch.Ctot.perc: Total soil C (%)

ch.Corg.perc: Soil organic C (%)

ch.netNminfield.mgkgd: Realised soil net N mineralisation (mg kg-1 d-1)

ch.netNminlab.mgkgd: Potential soil ne N mineralisation (mg kg-1 d-1)

archaea.cpg.log: Ammonia oxidising archaea (archaeal amoA gene copies g-1 soil)

bacteria.cpg.log: Ammonia oxidising bacteria (bacterial amoA gene copies g-1 soil)

micr.biom: Microbial biomass (ug g-1 soil)

ch.CtoN: C to N ratio

ch.netNnitriffield.mgkgd.sqrt: Realised soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniffield.mgkgd.sqrt: Realised soil net ammonification, transformed (mg kg-1 d-1)

ch.netNnitriflab.mgkgd.sqrt: Potential soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniflab.mgkgd.sqrt: Potential soil net ammonifiation, transformed (mg kg-1 d-1)

en:
This dataset contains all data on which the following publication below is based.

Paper Citation:

Risch, A. C.; Zimmermann, S.; Ochoa-Hueso, R.; Schütz, M.; Frey, B.; Firn, J. L.; Fay, P. A.; Hagedorn, F.; Borer, E. T.; Seabloom, E. W.; et al. Soil net nitrogen mineralisation across global grasslands. Nat. Commun. 2019, 10 (1), 4981 (10 pp.). doi.org/10.1038/s41467-019-12948-2

Please cite this paper together with the citation for the datafile.

We conducted coordinated measurements of realised and potential soil net Nmin, and assessed water holding capacity, bulk density, C and N content, texture, pH, pore space, microbial biomass, and archaeal (AOA) and bacterial (AOB) ammonia oxidiser abundance using identical materials and methods across 30 grasslands on six continents. The sites covered a globally relevant range of climatic and edaphic conditions. Climate data was obtained from worldclim - Global climate data https://www.worldclim.org/

global

display_name: global

grassland

display_name: grassland

mineralization

display_name: mineralization

nutrient-network

display_name: nutrient-network

soil

display_name: soil

soil-biology

display_name: soil-biology

soil-chemistry

display_name: soil-chemistry

worldwide

display_name: worldwide


mountain-permafrost-hydrology

maintainer: Jeannette Noetzli

title_for_slug: mountain-permafrost-hydrology

en: permafrost-degradation mass-movements mountain-permafrost-hydrology monitoring-techniques ice-rich-permafrost climate-change-impacts

en: DORA Persistent URL

en: Synthesis report chapter of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN)

en: This report was prepared as one of the synthesis report chapters of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN). In earlier reports such as the CH2014-IMPACTS report (CH-Impacts 2014), the topic of mountain permafrost hydrology was not addressed. Here, we provide a baseline of the available knowledge of mountain permafrost in the Swiss Alps for future reference. We compile an overview of the current understanding of mountain permafrost in the Swiss Alps, its distribution and characteristics, observed and projected changes, and expected impacts on slope stability, infrastructure and hydrological aspects. We also briefly describe the measurement techniques and modelling approaches applied. The chapter closes with a summary of the most important open research questions. The literature cited mainly includes studies on mountain permafrost published in scientific journals and assessments of long-term observation data. We focus on permafrost hydrology interactions wherever information is available. However, systematic studies on permafrost hydrology in mountain areas are still limited.

climate-change-impacts

display_name: climate-change-impacts

ice-rich-permafrost

display_name: ice-rich-permafrost

mass-movements

display_name: mass-movements

monitoring-techniques

display_name: monitoring-techniques

mountain-permafrost-hydrology

display_name: mountain-permafrost-hydrology

permafrost-degradation

display_name: permafrost-degradation

en: Mountain Permafrost Hydrology


en: long-term meteo par precipitation climate-change wind-speed relative-humidity swiss-forest-lab meteorology temperature

en: Site photo of the forest station (BTB)

en: Site photo of the forest station from the side.

en: Data plot of the field station (BTF)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Field station data (BTF)

en: Data file.

en: Site aerial photo (Bettlachstock)

en: Site aerial photo from both Bettlachstock stations. Source: Google. 2016. Site aerial photo from both Bettlachstock stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: Data plot of the forest station (BTB)

en: Site photo of the field station (BTF)

en: Site photo of the field station from the side.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Bettlachstock in Switzerland where one station is located within a natural mixed forest stand (BTB) with European beech (_Fagus sylvatica_; 170-190 yrs), European silver fir (_Abies alba_; 190 yrs) and Norway spruce (_Picea abies_; 200 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Bettlachstock is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Bettlachstock, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: Adam Winstral

en: snow snow-depth snow-simulation jules-investigation-model jim

en: HS and SWE observations

en: Automated (HS) and manual (SWE) data used to evaluate model simulations

en: Station forcing data

en: All forcing data need to run JIM at HS and SWE stations. These are data downscaled directly from COSMO NWP data (WY14, WY15) and further enhanced by additional station observations of snow depth (HS) and air temperature (Ta) in WY17. Further information can be found in README file. Note that in WY14 and WY15, shortwave radiation was not split into direct and diffuse (not necessary for JIM) and that the default method in JIM for splitting precipitation phase was used. In WY 17, direct and diffuse were combined as input to JIM and JIM was forced with pre-processed liquid and solid precipitation phases.

en: DEM

en: 1-km resolution DEM used for downscaling gridded NWP data to stations and for distributing BDE evaluations at HS-stations to SWE-stations

en: File/data descriptor

en: These data were used to drive and evaluate Jules Investigation Model (JIM) snow simulations. The data provided are the forcing data used for the "deterministic" runs as described in Winstral et al., 2019. The bias-detecting ensemble (Winstral et al., 2019) used observed snow depths (HS) to detect biases in these deterministic simulations related to precipitation and energy inputs to JIM. Simulations that included the BDE evaluations substantially improved JIM simulations.

jim

display_name: jim

jules-investigation-model

display_name: jules-investigation-model

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-simulation

display_name: snow-simulation

en: Meteorological data used to develop and validate the bias-detecting ensemble (BDE)


en: precipitation temperature swiss-forest-lab meteo par wind-speed long-term relative-humidity climate-change meteorology

en: Forest station data (NAB)

en: Data file.

en: Site aerial photo (Nationalpark)

en: Site aerial photo from both Nationalpark stations. Source: Google. 2016. Site aerial photo from both Nationalpark stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: Site photo of the forest station (NAB)

en: Site photo of the forest station from the side.

en: Data plot of the forest station (NAB)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Data plot of the field station (NAF)

en: Field station data (NAF)

en: Site photo of the field station (NAF)

en: Site photo of the field station form the side.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Nationalpark in Switzerland where one station is located within a natural coniferous forest stand (NAB) with mountain pine (_Pinus mugo_; 210 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Nationalpark is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

en: Nationalpark, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


en: alptal runoff first-order-catchment snow subalpine meteorological-data

en: Daily runoff data from three steep torrents in the Alptal (1968-2019)

en: Runoff, water temperature and electrical conductivity have been measured since 1968 at the outlet of three torrential catchments (with an area of approximately 1 km2 each) located in the Alptal valley: Erlenbach, Lümpenenbach and Vogelbach. This data set provides daily mean values; data at 10-min resolution can be provided on request for the period 1984-2020 (contact: alptal@wsl.ch).

en: Daily meteorological and snow data (1968-2019) Alptal

en:
Air temperature, dew point temperature, relative humidity, wind speed, precipitation and global radiation have been measured (since 1981) on a meadow (Erlenhöhe) in the Erlenbach catchment. It is located at 1'220 m a.s.l. with an exposure towards west. In order to assess the spatial variability of precipiation, two additional rain gauges have been running in the Vogelbach and Lümpenenbach catchment, respectively.
For the period before 1981, meteorological variables have been extrapolated from the nearby MeteoSwiss station Einsiedeln (ca. 15 km north) to the WSL station Erlenhöhe using a linear correction factor for air temperature, wind speed and precipitation.
Snow depth has been recorded automatically since 2003.

en: Manual snow measurements Alptal (1968-2020)

en:
Snow depth, snow density and snow water equivalent have been measured since winter 1968/69 along more than 15 transects distributed across the Alptal valley representing different altitudes, aspects and land use (closed forest and open meadows). Length of the snow courses: 20 to 30 m. The measurement interval has been weekly to monthly.
More details about the locations and methods can be found in Stähli, M.; Gustafsson, D., (2006). Long-term investigations of the snow cover in a subalpine semi-forested catchment. Hydrological Processes, 20, 411-428. doi: 10.1002/hyp.6058.

en:
This data set includes 52 years of hydrometeorological measurements from small (first-order) catchments in the pre-alpine valley Alptal. Here we provide daily mean values; values in sub-daily resolution can be provided on demand.
Runoff has been measured at the outlet of three small (first-order) catchments of approximately 1 km2 area: Erlenbach (two independent runoff measurements), Vogelbach and Lümpenenbach. The catchments are similar with regard to geology (Flysch) and soil conditions (clay soils), but differ in forest coverage (20 to 60%). A detailed description of the catchments can be found at https://www.wsl.ch/alptal .
Runoff in these small catchments is typically very dynamic and can temporally carry large amounts of sediment and large wood. Thus, the accuracy of the measurements at very large flow is limited.
Meteorological variables have been measured on a meadow (Erlenhöhe) located in the Erlenbach catchment at 1220 m a.s.l. using a standard meteorological station (incl. ventilated air temperature and heated rain gauges). In addition, precipitation has also been recorded at two other locations (in the Vogelbach and Lümpenenbach catchments).
Snow measurements have been conducted weekly to monthly since 1968 at more than 15 locations (30-m transects) representing different altitudes, aspects and land uses (meadow, forest). In addition, snow depth has been recorded continuously since 2003 at Erlenhöhe, and for this location we also include a simulation of snow depth and SWE (using the numerical model COUP) that assimilates the manual weekly snow-course measurements. Details on these snow measurements can be found in Stähli, M. and Gustafsson, D. 2006. Hydrol. Proc., 20, 411-428. doi: 10.1002/hyp.6058.

Further information on the methods and sensors can be found at https://www.wsl.ch/alptal .

A first version of this data set (for the period 1968-2017) was uploaded in June 2018 at the occasion of the 50-year anniversary. This original data set was updated in February 2021 (with data from 2018 and 2019), and this data set was used for a longterm trend analysis, submitted for publication in a special issue of Hydrological Processes.

alptal

display_name: alptal

first-order-catchment

display_name: first-order-catchment

meteorological-data

display_name: meteorological-data

runoff

display_name: runoff

subalpine

display_name: subalpine

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Longterm hydrological observatory Alptal (central Switzerland)


en: snowpack winter-tourism snow snow-conservation terrestrial-laser-scanning snow-farming

en: Fluela .sno

media_type: SNO

en: Input snow profile (.sno file) used for SNOWPACK simulations of the Flüela heap

en: HS Fluela spring 2015

en:
Snow depth/ height of snow heap in spring 2015 obtained by terrrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903

en: HS Martell spring 2015

en:
Snow depth/ height of snow heap in spring 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

en: Fluela .smet

media_type: SMET

en: Meteodata used as input for SNOWAPCK simulations, orginating from Station Windtunnel and DAV.

en: Martell .smet

en: Meteodata used as input for SNOWAPCK simulations, orginating from Station Hintermartell.

en: HS Fluela autumn 2015

en:
Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903
Nodata: -9999

en: Martell .sno

en: Input snow profile (.sno file) used for SNOWPACK simulations of the Martell heap

en: HS Martell autumn 2015

en:
Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

en:
Two data sets obtained for snow farming projects (Fluela, Davos, CH and Martell, IT) in 2015.

The data set contains for each site:

* 10 cm GIS raster of snow depth calculated from terrestrial laserscanning surveys (TLS) in the end of winter season (April/May)

* 10 cm GIS raster of snow depth calculated from TLS in the end of summer season (October)

Input files for SNOWPACK model:

* .sno: snow profile at the end of winter

* .smet: meteorological data measured by weather stations in the area

For more details see Grünewald, T., Lehning, M., and Wolfsperger, F.: Snow farming: Conserving snow over the summer season, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-93, in review, 2017.

snow-conservation

display_name: snow-conservation

snow-farming

display_name: snow-farming

snowpack

display_name: snowpack

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

winter-tourism

display_name: winter-tourism

en: Snowfarming data set Davos and Martell 2015


en: roads buffer density jupyter gis geospatial

media_type: ipynb

en: Road Density Calculation (Python Notebook) online

media_type: url

en: Plots

en: Random plot locations

en: Road data from OSM for the surroundings of Menzberg, Switzerland

en:
This dataset contains the road and plot data used for the geospatial analysis example showcased in "Fostering Open Science at WSL with the EnviDat Environmental Data Portal", a contribution to the 5th Open Source Geospatial Research and Education Symposium (OGRS), 2018.
The example uses Jupyter Notebook to calculate road densities in the neighbourhood of sample plot locations with Python. Road data were extracted from OpenStreetMap, while the point data (sample plots) were generated manually.

buffer

display_name: buffer

density

display_name: density

geospatial

display_name: geospatial

gis

display_name: gis

jupyter

display_name: jupyter

roads

display_name: roads

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Dataset for OGRS 2018 publication


en: antarctica aws consistent python cryowrf

en: Scripts to preprocess (and download for some databases) atmospheric weather station data. Furthermore, a list of stations and a map can be created to have an overview.

en:
There are many sources providing atmospheric weather station data for the Antarctic continent. However, variable naming, timestamps and data types are highly variable between the different sources. The published python code intends to make processing of different AWS sources from Antarctica easier. For all datasets that are taken into account variables are renamed in a consistent way. Data from different sources can then be handled in one consistent python dictionary.

The following data sources are taken into account:

* AAD: Australian Antarctic Division (https://data.aad.gov.au/aws)
* ACECRC: Antarctic Climate and Ecosystems Cooperative Research Centre by the Australian Antarctic Division
* AMRC: Antarctic Meteorological Research Center (ftp://amrc.ssec.wisc.edu/pub/aws/q1h/)
* BAS: British Antarctic Survey (ftp://ftp.bas.ac.uk/src/ANTARCTIC_METEOROLOGICAL_DATA/AWS/; https://legacy.bas.ac.uk/met/READER/ANTARCTIC_METEOROLOGICAL_DATA/)
* CLIMANTARTIDE: Antarctic Meteo-Climatological Observatory by the italian National Programme of Antarctic Research (https://www.climantartide.it/dataaccess/index.php?lang=en)
* IMAU: Institute for Marine and Atmospheric research Utrecht (Lazzara et al., 2012), https://www.projects.science.uu.nl/iceclimate/aws/antarctica.ph
* JMA: Japan Meteorological Agency (https://www.data.jma.go.jp/antarctic/datareport/index-e.html)
* NOAA: National Oceanic and Atmospheric Administration (https://gml.noaa.gov/aftp/data/meteorology/in-situ/spo/)
* Other/AWS_PE: Princess Elisabeth (PE), KU Leuven, Prof. N. van Lipzig, personal communication
* Other/DDU_transect: Stations D-17 and D-47 (in transect between Dumont d’Urville and Dome C, Amory, 2020)
* PANGAEA: World Data Center (e.g. König-Langlo, 2012)

Important notes

* Information about data sources is available. Some downloading scripts are included in the provided code. However, users should make sure to comply with the data providers terms and conditions.
* Given changing download options of the differnent institutions the above links may not permanently work and data has to be retrieved by the user of this dataset.
* No quality control is applied in the provided preprocessing software - quality control is up to the user of the datasets. Some dataset are quality controlled by the owner.

Acknowledgements
--------------------------
We thank all the data providers for making the data publicly available or providing them upon request. Full acknowledgements can be found in Gerber et al., submitted.

References
---------------
Amory, C. (2020). “Drifting-snow statistics from multiple-year autonomous measurements in Adélie Land, East
Antarctica”. The Cryosphere, 1713–1725. doi: 10.5194/tc-14-1713-2020

Gerber, F., Sharma, V. and Lehning, M.: CRYOWRF - a validation and the effect of blowing snow on the Antarctic SMB, JGR - Atmospheres, submitted.

König-Langlo, G. (2012). “Continuous meteorological observations at Neumayer station (2011-01)”. Alfred Wegener
Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA, doi: 10.1594/PANGAEA.
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aws

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en: Preprocessing Antarctic Weather Station (AWS) data in python