de: wohnen bautatigkeit tabelle neubau gwz quartier zeitreihe grundangebot-bau sachdaten bauwesen sasa stistische-zone gebaude abbruch

de: Der Datensatz enthält die Anzahl fertiggestellter und abgebrochener Wohnungen nach Eigentumsart und statistischer Zone seit 2009.

abbruch

display_name: abbruch

bautatigkeit

display_name: bautatigkeit

bauwesen

display_name: bauwesen

gebaude

display_name: gebaude

grundangebot-bau

display_name: grundangebot-bau

gwz

display_name: gwz

neubau

display_name: neubau

quartier

display_name: quartier

sasa

display_name: sasa

stistische-zone

display_name: stistische-zone

tabelle

display_name: tabelle

wohnen

display_name: wohnen

construction

de: Bau- und Wohnungswesen

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: Fertiggestellte und abgebrochene Wohnungen nach Eigentumsart und statistischer Zone seit 2009


de: geoportal lod2 geodaten 3d dachstrukturen vektordaten stzh polygondaten 3d-stadtmodell

state: active

type: dataset

media_type: dxf

format: DXF

de: Web Feature Service

media_type: WFS

format: WFS

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: gdb

format: GDB

media_type: gpkg

format: GPKG

de:
Das 3D-Modell der Aussenhülle und Dachstrukturen basiert auf den Gebäudegrundrissen der AV, deren Höhe unter dem Terrain liegt. Zusätzlich sind die Dachstrukturen photogrammetrisch bestimmt worden. Luftbild 2013.

**Zweck**: Ein 3D-Stadtmodell liefert die Grundlagen für folgende, wichtige Einsatzgebiete:
- Lärmkataster
- Sichtbarkeitsanalysen
- Schattenberechnungen
- Visualisierungen grosser Bau- und Infrastrukturprojekte
- Stadtplanung
- Städtebauliche Betrachtungen
- Fahrsimulatoren
- Einsatzunterstützung Blaulichtorganisationen
- Standortmarketing
- Tourismus
- Solarenergiepotentialberechnungen
- ...

dachstrukturen

display_name: dachstrukturen

geodaten

display_name: geodaten

geoportal

display_name: geoportal

polygondaten

display_name: polygondaten

stzh

display_name: stzh

vektordaten

display_name: vektordaten

fr: Construction, logement

en: Construction and housing

it: Costruzione e abitazione

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

name: GIS-Zentrum, Geomatik + Vermessung, Tiefbau- und Entsorgungsdepartement

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

type: organization

approval_status: approved

key: guid

key: uri

value: ZH - DCAT Harvester

de: 3D-Dachmodell LoD2 Jahresstand 2013 (3D)


fernwarme-primarenergiemix

title_for_slug: fernwarme-primarenergiemix

de: fernwarme energie primarenergie

media_type: text/csv

format: CSV

mimetype: text/csv

de: Anteil der Primärenergien Kehricht, Holz, Wärmepumpe, Erdgas und Heizöl in MWh pro Jahr

energie

display_name: energie

fernwarme

display_name: fernwarme

primarenergie

display_name: primarenergie

energy

fr: Energie

de: Energie

en: Energy

it: Energia

name: Fernwärme, Entsorgung + Recycling Zürich, Tiefbau- und Entsorgungsdepartement

de: Fernwärme: Primärenergiemix


maintainer: Open Data Zürich

de: hochzeit sasa tabelle nationalitaet sachdaten zeitreihe

de: Diese Daten beschreiben die Anzahl Eheschliessungen nach der Nationalität der Eheschliessenden seit 1993.

hochzeit

display_name: hochzeit

nationalitaet

display_name: nationalitaet

sachdaten

display_name: sachdaten

zeitreihe

display_name: zeitreihe

population

fr: Population

de: Bevölkerung

en: Population

it: Popolazione

de: Eheschliessung nach Nationalität der Eheschliessenden, seit 1993


spitalnotaufnahme

title_for_slug: spitalnotaufnahme

de: spital geoportal punktdaten geodaten gesundheit stzh vektordaten

media_type: SHP

format: SHP

media_type: CSV

media_type: JSON

format: JSON

de:
Standorte der Spitalnotaufnahme in der Stadt Zürich

**Zweck**: Auffinden und Darstellen der Daten im Kontaktparagraphen der städtischen Internetseiten sowie im Stadtplan.

gesundheit

display_name: gesundheit

punktdaten

display_name: punktdaten

spital

display_name: spital

health

fr: Santé

de: Gesundheit

en: Health

it: Sanità

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: Spitalnotaufnahme


de: entsorgung sachdaten tabellen abfall entsorgungskalender kalender

de: Sammeltage CargoTram nach PLZ

abfall

display_name: abfall

entsorgung

display_name: entsorgung

entsorgungskalender

display_name: entsorgungskalender

kalender

display_name: kalender

tabellen

display_name: tabellen

administration

fr: Administration

de: Verwaltung

en: Administration

it: Amministrazione

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

name: Entsorgung + Recycling Zürich, Tiefbau- und Entsorgungsdepartement

de: Entsorgungskalender CargoTram


de: sachdaten kalender entsorgungskalender tabellen entsorgung abfall

de: Sammeltage der Papierentsorgung nach PLZ

stadt-zurich

de: Stadt Zürich

de: Entsorgungskalender Papier


veloverleih

title_for_slug: veloverleih

de: punktdaten geoportal velo stzh geodaten vektordaten

de: Veloverleih.json (GeoJSON-Services)

de: Web Map Tile Service

de: Web Feature Service

de: Web Map Service

de:
Veloverleihstandorte

**Zweck**: Visualisierung der Standorte in einer interaktiven Karte im Internet.

geodaten

display_name: geodaten

geoportal

display_name: geoportal

stzh

display_name: stzh

velo

display_name: velo

geography

de: Geographie

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

name: AOZ / DIR / KOM, AOZ, Asyl Organisation Zürich

de: Veloverleih


iwb-fernwarme-versorgungsgebiet

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

energy

de: Energie

title_for_slug: iwb-fernwarme-versorgungsgebiet

fr: reseau-electrique courant energie

de: stromnetz strom energie

en: power-grid current energy

it: rete-elettrica corrente energia

label: geocat.ch permalink

spatial: Kanton Basel-Stadt (BS)

de: Geodaten-Shop

de: Öffentlich zugänglicher Geodaten-Downloaddienst des Kantons Basel-Stadt

format: SERVICE

de: WMS BS

de: Die derzeit im WMS BS verfügbaren Datenebenen entsprechen, bis auf wenige Ausnahmen, den Geodaten, welche auch in MapBS dargestellt sind. Der WMS BS ist kostenlos nutzbar und bietet Zugriff auf öffentliche sowie beschränkt öffentliche Geodaten, wobei gegebenenfalls Benutzername und Passwort benötigt werden (Zugangsdaten von MapBS).

de: WFS BS

de: Die derzeit im WFS BS verfügbaren Datenebenen entsprechen, bis auf wenige Ausnahmen, den Geodaten, welche auch in MapBS dargestellt sind. Der WFS BS ist kostenlos nutzbar und bietet Zugriff auf öffentliche sowie beschränkt öffentliche Geodaten, wobei gegebenenfalls Benutzername und Passwort benötigt werden (Zugangsdaten von MapBS).

de: Die Karte zeigt die Gebiete, die durch die IWB mit leitungsgebundener Wärme versorgt werden. Sie entsprechen den vom Regierungsrat gestützt auf den Energierichtplan zugewiesenen Gebieten gemäss IWB-Gesetz §1, 2bis.

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.

political_level: canton

value: BS - Geocat Harvester

de: IWB Fernwärme-Versorgungsgebiet


elektro-leitungen

territory

de: Raum und Umwelt

title_for_slug: elektro-leitungen

label: Web GIS Client des Kanton Uri. Die Daten können direkt via dem Portal in den unterschiedlichsten Datenformaten heruntergeladen werden.

spatial: Canton of Uri (UR)

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: Elektro Trasse, Bauwerke und Trassepunkte.

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

kanton-uri

capacity: public

value: Uri-Kt - Geocat Harvester

fr: Elektro Leitungen

de: Elektro Leitungen

en: Elektro Leitungen

it: Elektro Leitungen


wasser-leitungen-offentlich

culture

de: Kultur, Medien, Informationsgesellschaft, Sport

energy

de: Energie

geography

de: Geographie

title_for_slug: wasser-leitungen-offentlich

fr: In diesem Datensatz werden Leitungen für die Wasserversorgung verwaltet. Im Kanton Uri sind nicht alle Wasserversorgungen digital erfasst. Die Gemeindeverwaltungen oder Wasserversorgungen bestimmen zur Zeit die Verfügbarkeit des öffentlichen oder geschützten Zugangs.

fr: Wasser Leitungen öffentlich

de: Wasser Leitungen öffentlich

en: Wasser Leitungen öffentlich

it: Wasser Leitungen öffentlich


name: Statistisches Amt des Kantons Zürich, Data Shop

de: kantonzuerich fluechtlinge aufenthalt

label: Status S im Kanton Zürich: Von Schutzsuchenden zu Arbeitskräften?

label: Ukraine-Hilfe

label: Vorbereiteter Code in R oder Python für jedes Dataset mit csv-Datei(en)

label: Ukraine: Bundesrat aktiviert Schutzstatus S für Menschen aus der Ukraine (admin.ch)

de: Bestandesdaten der ausländischen Wohnbevölkerung im Kanton Zürich mit Aufenthaltsstatus 'Schutzbedürftige'

de: Aus Datenschutzgründen werden Zellenwerte, in deren Berechnung Merkmale mit weniger als drei Fällen eingehen, als '-' angegeben.

de: Die Daten werden monatlich aktualisiert (jeweils ungefähr am 15. Tag des Folgemonats). Die Quelldaten stammen aus dem Zentralen Migrationsinformationssystem ZEMIS des Staatssekretariats für Migration SEM.

aufenthalt

display_name: aufenthalt

fluechtlinge

display_name: fluechtlinge

kantonzuerich

display_name: kantonzuerich

population

de: Bevölkerung

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.

value: ZH-Kt Statistisches Amt - DCAT Harvester

de: Ausländische Wohnbevölkerung mit Schutzstatus S im Kanton Zürich, 10-Jahres-Altersklassen und Geschlecht


fernwarme-leitungen

geography

fr: Géographie

territory

de: Raum und Umwelt

title_for_slug: fernwarme-leitungen

de: WMS-Dienst des Kanton Uri

fr: Fernwärme Trasse und Leitungspunkt.

de: Fernwärme Trasse und Leitungspunkt.

en: Fernwärme Trasse und Leitungspunkt.

it: Fernwärme Trasse und Leitungspunkt.

fr: Fernwärme Leitungen

de: Fernwärme Leitungen

en: Fernwärme Leitungen

it: Fernwärme Leitungen


name: Fachstelle Open Government Data des Kantons Zürich

label: Datenkatalog

label: DCAT-AP CH – The Swiss Application Profile for Data Portals and Catalogues

de: API-Endpoint für Datensätze im Metadatenkatalog des Kantons Zürich

media_type: application/json

de: Enthält alle aktuell im Metadatenkatalog des Kantons Zürich enthaltenen Datensätze mit ihren Metadaten: (1) häufig nachgefragte Excel-Tabellen, (2) Indikatoren aus dem Gemeindeporträt, (3) Publikationen des Statistischen Amts sowie (4) offene Behördendaten des Kantons Zürich (ausgenommen offene Geodaten).

mimetype: application/json

de: Enthält alle aktuell im Metadatenkatalog des Kantons Zürich enthaltenen Datensätze mit ihren Metadaten. Folgt dem Metadaten-Standard 'DCAT-AP CH v1' (eCH-0200).

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

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: Web Service des Metadatenkatalogs des Kantons Zürich


fr: cantonal votation

de: abstimmung kantonal

it: cantonale votazione

label: Descripziun dal format

label: Descrizione del formato

label: Description du format

label: Formatbeschreibung

identifier: json

identifier: csv

rm: Resultats finals da la votaziun chantunala "Teilrevision des Sozialhilfegesetzes vom 4. November 2021 betreffend «Anreize stärken – Arbeitsintegration fördern»", 15 da matg 2022, Kanton Basel-Landschaft, ordinà tenor vischnancas.

fr: Résultats finaux du vote cantonal "Teilrevision des Sozialhilfegesetzes vom 4. November 2021 betreffend «Anreize stärken – Arbeitsintegration fördern»", 15 mai 2022, Kanton Basel-Landschaft, répartis par municipalités.

de: Schlussresultate der kantonalen Abstimmung "Teilrevision des Sozialhilfegesetzes vom 4. November 2021 betreffend «Anreize stärken – Arbeitsintegration fördern»", 15. Mai 2022, Kanton Basel-Landschaft, aufgeschlüsselt nach Gemeinden.

it: Risultati finali della votazione cantonale "Teilrevision des Sozialhilfegesetzes vom 4. November 2021 betreffend «Anreize stärken – Arbeitsintegration fördern»", 15 maggio 2022, Kanton Basel-Landschaft, suddivisi per municipalit.

abstimmung

display_name: abstimmung

cantonal

display_name: cantonal

cantonale

display_name: cantonale

kantonal

display_name: kantonal

plaun-chantunal

display_name: plaun-chantunal

votation

display_name: votation

votazione

display_name: votazione

votaziun

display_name: votaziun

politics

fr: Politique

de: Politik

en: Politics

it: Politica

kanton-basel-landschaft

fr: Canton de Bâle-Campagne

de: Kanton Basel-Landschaft

en: Canton of Basel-Country

it: Cantone di Basilea-Campagna

en:
The Canton of Basel-Country publishes open datasets of cantonal offices and agencies.
Further information at https://ogd.bl.ch/

de:
Der Kanton Basel-Landschaft veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.
Weitere Informationen unter https://ogd.bl.ch/

value: BL - Abstimmungen


geography

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: baulinie eigentumsbeschrankungoreb fliessgewasser nutzungsplanung oberflachengewasser raumplanung strasse

spatial: Kanton Luzern

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: Baulinien, die in einem grundeigentümerverbindlichen, öffentlich-rechtlichen Planwerk festgelegt wurden.

name: Dienststelle für Verkehr und Infrastruktur (vif)

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

fr: La géoinformation du canton de Lucerne est responsable de la collecte, du traitement et de la gestion des données à référence spatiale. Elle dirige, coordonne et surveille les travaux de la géoinformation et de la mensuration officielle.

en: Geoinformation of the Canton of Lucerne is responsible for the collection, processing and management of spatial data. It manages, coordinates and monitors the work of geoinformation and of the cadastral surveying.

de: Die Geoinformation des Kantons Luzern ist für die Erhebung, Verarbeitung und Verwaltung von raumbezogenen Daten zuständig. Sie leitet, koordiniert und überwacht die Arbeiten der Geoinformation und der amtlichen Vermessung.

it: La Geoinformation del Cantone di Lucerna è responsabile della raccolta, dell'elaborazione e della gestione dei dati territoriali. Gestisce, coordina e monitora il lavoro della geoinformazione e della misurazione ufficiale.

value: LU-Kt - Geocat Harvester

de: Baulinien nach Strassen- und Baulinienplänen


maintainer: Staatsarchiv des Kantons Zürich

de: Erlasse der Zürcher Gesetzessammlung ab 1803

media_type: application/zip

format: ZIP

mimetype: application/zip

de: Sämtliche Erlasse der Zürcher Gesetzessammlung von 1803 bis 1998. Umgesetzt als XML Dateien nach Vorgaben der TEI. Die Daten stehen unter einer Creative Commons CC-BY-SA 4.0 Lizenz zur Verfügung.

regierungsrat

display_name: regierungsrat

agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

en: Agriculture, forestry

it: Agricoltura, selvicoltura

construction

fr: Construction, logement

de: Bau- und Wohnungswesen

en: Construction and housing

it: Costruzione e abitazione

crime

fr: Criminalité, droit pénal

de: Kriminalität, Strafrecht

en: Crime, criminal justice

it: Criminalità, diritto penale

culture

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

de: Kultur, Medien, Informationsgesellschaft, Sport

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

national-economy

de: Volkswirtschaft

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

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

social-security

fr: Protection sociale

de: Soziale Sicherheit

en: Social security

it: Sicurezza sociale

staatsarchiv-kanton-zuerich

de: Staatsarchiv Kanton Zürich

de: Das Staatsarchiv ist das Archiv des Kantons Zürich und seiner Rechtsvorgänger. Es bewertet, übernimmt, erschliesst und konserviert Unterlagen aus über tausend Jahren Zürcher Geschichte. Durch die Aufbewahrung dieser Unterlagen macht es staatliches Handeln nachvollziehbar und ermöglicht historische Forschung. Das Staatsarchiv gewährt allen Interessierten Einsicht in diejenigen Bestände, die keinen Beschränkungen mehr unterliegen. Der grösste Teil der Findmittel zu den Archivbeständen kann online abgefragt werden.

value: ZH-Kt Staatsarchiv - DCAT Harvester


maintainer: Gemeindeamt des Kantons Zürich

de: gemeindefinanzen gemeinden

de: Bilanzwert der langfristigen Schulden [Fr./Einw.]

de: Bilanzwert der langfristigen Schulden pro Kopf pro konsolidierte Gemeinde.

gemeindefinanzen

display_name: gemeindefinanzen

gemeinden

display_name: gemeinden

national-economy

fr: Economie nationale

it: Economia

gemeindeamt-kanton-zuerich

de: Gemeindeamt Kanton Zürich

de: Das Gemeindeamt des Kantons Zürich hilft den Gemeinden, sich in Übereinstimmung mit dem kantonalen Recht zu organisieren. Mit dem Finanzausgleich stellt das Amt sicher, dass alle Gemeinden ihre Grundaufgaben erfüllen können. Daneben obliegen dem Gemeindeamt die kantonalen Aufgaben des Zivilstands-, Einbürgerungs- und Einwohnerwesens. Schliesslich ist das Gemeindeamt Aufsichtsstelle 2. Instanz (nach den Bezirksräten) hinsichtlich Organisation, Haushaltführung, Rechnungslegung sowie Aufsichtsbehörde über die Kindes- und Erwachsenenschutzbehörden.

value: ZH-Kt Gemeindeamt - DCAT Harvester


maintainer: Bundesamt für Energie BFE

title_for_slug: Schweizerische Elektrizitätsstatistik: Schweizerische Elektrizitätsbilanz - Monatswerte

fr: ogd35-bfe electricite production importation exportation consommation

de: ogd35-bfe elektrizitat produktion import export verbrauch

en: ogd35-bfe electricity production import export

it: ogd35-bfe elettricita produzione importazione esportazione consumo

fr: Statistique suisse de l'électricité: bilan mensuel suisse de l'électricité

it: Statistica svizzera dell'elettricità: bilancio svizzero dell'elettricità - valori mensili

author: Bundesamt für Energie BFE

fr: Cette statistique recense sur une base mensuelle la production, l'importation, l'exportation et la consommation d'électricité en Suisse. Elle présente la production des centrales hydrauliques, des centrales nucléaires, des centrales thermiques classiques et renouvelables. Elle indique la consommation des installations de pompage d'accumulation et les pertes en ligne. 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 Schweizerische Elektrizitätsbilanz - Monatswerte gibt Auskunft über Produktion, Import / Export und Verbrauch von Elektrizität in der Schweiz auf monatlicher Basis. Bei der Produktion werden Wasserkraftwerke, Kernkraftwerke, konventionell-thermische und erneuerbare Kraftwerke unterschieden. Der Verbrauch der Speicherpumpen und die Leitungsverluste werden ausgewiesen. Die monatliche Elektrizitätsbilanz wird im Rahmen der Elektrizitätsstatistik erstellt, welche Teil der öffentlichen Statistik der Schweiz ist (gesetzliche Grundlage: BStatG).

statistical-basis

fr: Bases statistiques

de: Statistische Grundlagen

en: Statistical basis

it: Basi statistiche

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: Marcia Phillips

en: borehole ritigraben permafrost permos meteo-station

en: DATA ACCESS

media_type: SMET

en: Meterological station at the [Ritigraben permafrost borehole](http://www.envidat.ch/dataset/rit1) (RIT_0102) in canton Valais, Switzerland. The station is located at 2690 m asl on a flat site.

borehole

display_name: borehole

meteo-station

display_name: meteo-station

permafrost

display_name: permafrost

permos

display_name: permos

ritigraben

display_name: ritigraben

education

de: Bildung, Wissenschaft

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: RIT2: Meteorological station at Ritigraben borehole site


en: metabarcoding monitoring edna spore-dispersal air-sampling

en: Data files and analysis scripts (Version 1)

en: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of fungi". Please refer to README.pdf inside the archive for more information.

en:
Resources associated with the manuscript *A case study on the application of spore sampling for the monitoring of fungi* (Schlegel et al. 2023, submitted).
Airborne environmental DNA (eDNA) monitoring of fungi was evaluated on a species-rich grassland site. Extensive fruiting body surveys yielded 29 waxcap and clavarioid species, 19 of which were also detectable in air eDNA. The analysis indicates that spores of locally occurring fruiting bodies were detected, in addition to a large diversity of common fungal species, while rare and threatened species were underrepresented in the air.
The contents of the dataset (ZIP archive):
* All analysis scripts in [R-Markdown](https://rmarkdown.rstudio.com) format, including the rendered PDF output with figures and tables (*analysis* directory)
* eDNA sample metadata (*amplicon_meta*) and results of the amplicon clustering (*amplicon_data*) and the source code of the pipeline (*amplicon_pipeline*)
* positions of all fruiting body groups found in the surveys (3838 GPS points) (*surveys*)
* positions of the spore traps, taxonomy of studied grassland fungi and red-list species, and many more resources
Please refer to `README.pdf` inside the archive for a complete description of the file structure and information on how to reproduce the analyses.

air-sampling

display_name: air-sampling

edna

display_name: edna

metabarcoding

display_name: metabarcoding

monitoring

display_name: monitoring

spore-dispersal

display_name: spore-dispersal

en: Supporting information for case study on the application of spore sampling for the monitoring of fungi


maintainer: Varun Sharma

en: mesoscale-modelling blowing-snow alps snow-atmosphere-interaction antarctica

media_type: ZIP

en:
REPRODUCIBILITY_POSTPROCESSING.zip contains data and scripts used to produce all figures from for the associated manuscript submitted for peer review ( see section on Citations below )

The folders stand for the three case studies presented in the manuscript. Two case studies (case Ia and case Ib) are on simulations in Antarctica and one case study
case II is for simulations in the Alps.

The associated data in the form of netcdf files or text files were produced using CRYOWRF v1.0

Apart from reproducibility, the intention of sharing these scripts is also to make it easy for new users to adopt CRYOWRF and be efficient, in particular in processing snowpack outputs.

The scripts were tested on multiple machines (different OSes) with the attached YAML file (wrf_analysis.yml) to setup the conda environment. All scripts were run using spyder as the IDE.

en: REPRODUCIBILITY_SIMULATION.zip contains all the extraneous files required to perform the simulations in associated manuscript (see Citations 3 in README.txt). The purpose of sharing these files apart from purposes of reproducibility is to also serve as templates for users to learn the workflow of CRYOWRF and perform simulations for their own purposes.

en:
This repository contains data required for reproducibility of the results to be published in the associated manuscript.

Apart from reproducibility, the attached datasets also serve as templates for new users to adopt CRYOWRF in their research.

The datasets consist of two folders organized in zip format:

1. REPRODUCIBILITY_SIMULATION:
  Consists of namelists for WPS, WRF and SNOWPACK to reproduce simulations published in the manuscript
  Additional files include datasets (from IMAU-FDM / RACMO, see "credits" below ) as well as helper python scripts to
  produce *.sno files
  which are used as initial conditions for SNOWPACK in CRYOWRF.

2. REPRODUCIBILITY_POSTPROCESSING:
   Includes outputs of CRYOWRF and python scripts used to prepare figures in the manuscript.

Each of the folders have their own readme files for more details.

 Code
citation: Varun Sharma. (2021, July 2). vsharma-next/CRYOWRF: CRYOWRF v1.0 (Version v1.0). Zenodo. http://doi.org/10.5281/zenodo.5060165

location: https://gitlabext.wsl.ch/atmospheric-models/CRYOWRF   (stable releases / institutional repo)
        https://github.com/vsharma-next/CRYOWRF            (dev branches / developer repo)

 Publication
**Introducing CRYOWRF v1.0: Multiscale atmospheric flow simulations with advanced snow cover modelling.**
Varun Sharma, Fraziska Gerber and Michael Lehning, Submitted to Geoscientific Model Development

 Acknowledgements
We thank Peter Kuipers Munneke (P.KuipersMunneke@uu.nl) for preparing and sharing outputs of IMAU-FDM and RACMO used for initial conditions for case Ia. The relevant citations for the methods through which these datasets were generated are:

* Kuipers Munneke, P., S. R. M. Ligtenberg, B. P. Y. Noël, I. M. Howat, J. E. Box, E. Mosley-Thompson, J. R. McConnell, K. Steffen, J. T. Harper, S. B. Das and M. R. van den Broeke. 2015. Elevation change of the Greenland ice sheet due to surface mass balance and firn processes, 1960-2014. The Cryosphere, 9, 2009-2025. doi:10.5194/tc-9-2009-2015

 * Ligtenberg, S. R. M., P. Kuipers Munneke, B. P. Y. Noël, and M. R. van den Broeke. 2018. Brief communication: Improved simulation of the present-day Greenland firn layer (1960-2016). The Cryosphere, 12, doi:10.5194/tc-12-1643-2018

alps

display_name: alps

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

mesoscale-modelling

display_name: mesoscale-modelling

snow-atmosphere-interaction

display_name: snow-atmosphere-interaction

education

en: Education and science

en: Reproducibility Dataset for CRYOWRF v1.0


culture

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

energy

de: Energie

en: Energy

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

spatial: Schweiz

protocol: WWW:DOWNLOAD:Geopackage (ogc)

de: Geopackage

media_type: Geopackage (ogc)

de: Interlis

media_type: INTERLIS

format: INTERLIS

de: WFS

de: WMS

protocol: WWW:DOWNLOAD:ESRI Shapefile

de: Shapefile

media_type: ESRI Shapefile

fr: Service WMS-IFDG, couche "Installations électriques"

de: WMS-BGDI Dienst, Layer "Elektrische Anlagen"

en: WMS-FSDI service, layer "Electrical installations"

it: Servizio WMS-IFDG, strato "Impianti elettrici"

fr: Map (Preview) Géoportail thématique - map.energie.admin.ch

de: Map (Preview) Fachportal - map.energie.admin.ch

en: Map (Preview) Thematic geoportal - map.energie.admin.ch

it: Map (Preview) Geoportale tematico - map.energie.admin.ch

de: Fachportal - map.energie.admin.ch

de: swisstopo REST API

format: API

fr: Le réseau électrique établit la liaison entre producteurs et consommateurs d’énergie électrique. Il permet de transporter l’électricité, de la transformer (augmenter ou diminuer la tension) et de la distribuer. Le maillon que le réseau électrique constitue entre la production et la consommation est d’une importance majeure pour garantir la sécurité de l’approvisionnement en électricité. On entend par «installation électrique» tous les composants d’un réseau d’électricité servant à transporter le courant électrique, par exemple les lignes, les sous-stations et les stations de transformation. Le jeu de géodonnées de base «Installations électriques d’une tension nominale supérieure à 36 kV» comprend une vue d’ensemble géographique des installations électriques du réseau suisse à haute et à très haute tension.

de: Das Stromnetz ist die Verbindung zwischen Produzenten und Verbrauchern von elektrischer Energie. Via Netz wird der Strom transportiert, transformiert (von höherer zu tieferer Spannung und umgekehrt) und verteilt. Als Bindeglied zwischen Produktion und Verbrauch ist das Stromnetz von zentraler Bedeutung für die Gewährleistung der Stromversorgungssicherheit. Unter elektrischen Anlagen versteht man alle Komponenten eines Elektrizitätsnetzes, die der Übertragung von elektrischem Strom dienen wie beispielsweise Leitungen, Unterwerke und Transformatorenstationen. Der Geobasisdatensatz «Elektrische Anlagen mit einer Nennspannung von über 36 kV» beinhaltet eine geografische Gesamtsicht der elektrischen Anlagen des Höchst- und Hochspannungsnetzes der Schweiz.

en: The electricity grid is the point of connection between producers and consumers of electrical energy. Via the grid, electricity is transported, transformed (from a higher to lower voltage and vice versa) and distributed. As the link between production and consumption, the electricity grid is a key element in ensuring the security of electricity supply. The term electrical installations refers to all components of an electricity network that serve to transmit electrical current, such as lines, substations and transformer stations. The geodatabase dataset 'Electrical installations with a nominal voltage exceeding 36kV' contains a geographical overview of the electrical installations of the extra-high and high-voltage grid in Switzerland.

it: La rete elettrica è il risultato del collegamento tra produttori e consumatori di energia elettrica. La rete permette di trasportare, trasformare (da una tensione più alta a una tensione più bassa e viceversa) e distribuire l'energia elettrica. In quanto anello di congiunzione tra produzione e consumo, la rete elettrica è di fondamentale importanza per la sicurezza dell'approvvigionamento elettrico. Sono impianti elettrici tutti i componenti di una rete elettrica necessari ai fini del trasporto di energia elettrica, come ad esempio linee, sottostazioni e stazioni di trasformazione. Il set di geodati di base «Impianti elettrici con una tensione nominale superiore a 36 kV» contiene un quadro geografico generale degli impianti elettrici delle reti ad altissima e ad alta tensione della Svizzera.

name: Werksbetreiber und Bundesamt für Energie

bundesamt-fur-energie-bfe

en: Swiss Federal Office of Energy SFOE

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).

value: BFE - Geocat Harvester


en: remote-sensing avalanche-mapping avalanche-size-estimation avalanche reliability

en: AvalancheReliabilityData

media_type: application/x-zip-compressed

en: The .zip contains all data used to conduct the reliability study as well as the results, a detailed description of the included files is contained in the included pdf. All geospatial data is provided in the Swiss Coordinate System: CH1903+ / LV95 (EPSG 2056). For any use of the data the proper citation provided is obligatory!

mimetype: application/x-zip-compressed

en:
This dataset contains the data used and collected to investigate the reliability of avalanche size estimates and avalanche outlines (see related publications). Namely this is

 Avalanche size estimates

* the 10 pictures depicting avalanches
* the survey results from the 170 participants

 Avalanche outlines mapped from oblique photographs
* the pictures of the six avalanches
* the avalanche outlines mapped by the 10 participants
* the reference mapped from the georeferenced photographs

 Avalanche outlines from remotely-sensed imagery
* the orthophotos in the four different resolutions (2m, 1m, 50cm, 25cm)
* the area of interest (AoI) delimiting the research area
* the avalanche mappings in each resolution for all five participants
* the shade masks used to separate illuminated and shaded areas

The acquisition of the orthophotos has been partially supported by the Swiss National Science Foundation (SNF; Grant N°200021_172800).

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

avalanche-size-estimation

display_name: avalanche-size-estimation

reliability

display_name: reliability

remote-sensing

display_name: remote-sensing

education

fr: Education, science

de: Bildung, Wissenschaft

it: Formazione e scienza

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: Data reliability study: avalanche size estimates and outlines


bryophytes-of-europe-traits-bet-dataset

title_for_slug: bryophytes-of-europe-traits-bet-dataset

en: life-history-traits red-list mosses bioclimatic-variables indicator-values liverworts hornworts iucn

media_type: PDF

en: PDF including the (trait) explanations.

format: PDF

media_type: TXT

en: Text file including the BET dataset.

format: TXT

media_type: XLSX

en: Excel file including the BET dataset and (trait) explanations.

format: XLS

en: The Bryophytes of Europe Traits (BET) dataset includes values for 65 biological and ecological traits and 25 bioclimatic variables for all 1816 bryophytes included in the European Red List (Hodgetts et al. 2019). The traits are compiled from several regional trait datasets and manually complemented using Floras, species-specific literature and expert knowledge. The bioclimatic variables are calculated using the European range of each species. Details regarding the trait compilation and extraction of bioclimatic variables can be found in the corresponding data paper (Van Zuijlen et al. 2023).

bioclimatic-variables

display_name: bioclimatic-variables

hornworts

display_name: hornworts

indicator-values

display_name: indicator-values

iucn

display_name: iucn

life-history-traits

display_name: life-history-traits

liverworts

display_name: liverworts

mosses

display_name: mosses

red-list

display_name: red-list

education

en: Education and science

de: EnviDat: das Umwelt-Datenportal


maintainer: Adam Winstral

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

en: HS and SWE observations

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

en: DEM

media_type: text/plain

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

mimetype: text/plain

en: File/data descriptor

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: 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

envidat

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.

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


maintainer: Elisabeth Hafner

en: avalanche hazard-mapping snow satellite natural-hazard

en: SPOT6 Avalanche Outlines 16 January 2019

en: Shapefile of the manually mapped avalanche outlines. Please only use this data together with the example key document provided with this dataset and within the limitations of the dataset described in the publications.

en:
Outlines of 6'041 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 16 January 2019. The dataset was acquired following a period with very high avalanche danger. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping16012019.pdf)

The generation of the data is described in:

Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.

The data was comprehensivly validated in a subset area in

Hafner, E.D.; Techel, F.; Leinss, S.; Bühler, Y., 2021: Mapping avalanches with satellites - evaluation of performance and completeness. Cryosphere, 15, 2: 983-1004. doi: 10.5194/tc-15-983-2021

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

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: SPOT6 Avalanche outlines 16 January 2019


maintainer: Yohann Chauvier

en: random-stratified-sampling cluster background-data independent-dataset point-process-model survey-effort target-group covariate-correction environmental-stratification plant-species

en: Non-copyright data, scripts, diversity outputs

en:
Aim: While species distribution models (SDMs) are standard tools to predict species distributions, they can suffer from observation and sampling biases, particularly presence-only SDMs that often rely on species observations from non-standardized sampling efforts. To address this issue, sampling background points with a target-group strategy is commonly used, although more robust strategies and refinements could be implemented. Here, we exploited a dataset of plant species from the European Alps to propose and demonstrate efficient ways to correct for observer and sampling bias in presence-only models.

Innovation: Recent methods correct for observer bias by using covariates related to accessibility in model calibrations (classic bias covariate correction, Classic-BCC). However, depending on how species are sampled, accessibility covariates may not sufficiently capture observer bias. Here, we introduced BCCs more directly related to sampling effort, as well as a novel corrective method based on stratified resampling of the observational dataset before model calibration (environmental bias correction, EBC). We compared, individually and jointly, the effect of EBC and different BCC strategies, when modelling the distributions of 1’900 plant species. We evaluated model performance with spatial block split-sampling and independent test data, and assessed the accuracy of plant diversity predictions across the European Alps.

Main conclusions: Implementing EBC with BCC showed best results for every evaluation method. Particularly, adding the observation density of a target group as bias covariate (Target-BCC) displayed most realistic modelled species distributions, with a clear positive correlation (r≃0.5) found between predicted and expert-based species richness. Although EBC must be carefully implemented in a species-specific manner, such limitations may be addressed via automated diagnostics included in a provided R function. Implementing EBC and bias covariate correction together may allow future studies to address efficiently observer bias in presence-only models, and overcome the standard need of an independent test dataset for model evaluation.

background-data

display_name: background-data

cluster

display_name: cluster

covariate-correction

display_name: covariate-correction

environmental-stratification

display_name: environmental-stratification

independent-dataset

display_name: independent-dataset

plant-species

display_name: plant-species

point-process-model

display_name: point-process-model

random-stratified-sampling

display_name: random-stratified-sampling

survey-effort

display_name: survey-effort

target-group

display_name: target-group

education

en: Education and science

en: Novel methods to correct for observer and sampling bias in presence-only species distribution models


en: extreme-values return-periods low-flow alpine-precipitation reservoir-inflow

en: R codes for Extreme Values Analysis

media_type: zip-compresses folder of R scripts

en: Zip file containing R codes for running extreme value analyses for high precipitation and inflow events as well as code for determining return levels of low inflow and low precipitation events

en: Daily Luzzone Reservoir Inflow 01-01-2000 to 31-12-2019

media_type: .csv

en: Daily total water inflow to Luzzone reservoir. Natural inflow (LUZ_inflow_raw) is back-calculated based on daily water level in reservoir (removing hydropower inputs and spills). Linear interpolation between daily values is used to bring all inflow values into positive space (LUZ_inflow_intrp).

en:
 Summary

* Dataset of daily inflow to Luzzone reservoir in Ticino, Switzerland

* R scripts used to generate return levels for low reservoir inflow, low precipitation, high inflow, and extreme high precipitation based on various methods from extreme value analysis

 Data
The dataset included here is the "natural" reservoir inflow for the Luzzone reservoir.
Additional analyses were conducted on daily total precipitation of 6 meteorological stations (abbreviations: TIOLI, TIOLV, COM, VRN, VLS, ZEV). These precipitation data are freely available for teaching and research from the MeteoSwiss IDAweb portal (https://www.meteoswiss.admin.ch/services-and-publications/service/weather-and-climate-products/data-portal-for-teaching-and-research.html).

 Codes
R scripts used to determine return levels of the data set are included for both extreme high events and low events. The scripts include the following methods for calculating return levels:

* GEV (Generalized Extreme Value)

* GPD and GPDd (Generalized Pareto Distribution including declustered version)

* eGPD (extended Generalized Pareto Distribution)

* MEV (Metastatistical Extreme Value)

alpine-precipitation

display_name: alpine-precipitation

extreme-values

display_name: extreme-values

low-flow

display_name: low-flow

reservoir-inflow

display_name: reservoir-inflow

return-periods

display_name: return-periods

en: Data and Code on Extreme Inflow and Lowflow Analysis for Alpine Reservoirs


en: model-residuals hypervolume habitat-heterogeneity hengduan-mountains phytodiversity

en: Eurasia plant family richness map

en: This is the plant family level richness map at the Eurasia scale calculated from https://www.nature.com/articles/s41597-021-00997-6

en: Hengduan plant family richness map

en: This is the family level plant richness map in the Hengduan mountain scale at 1km resoution

en: Eurasia SR and heteorgeneity

media_type: text/csv

en: This table is used for the Eurasia scale analyses, including both family level species richness map and different heterogeneity predictors

en: Plant range map at Hengduan scale

en: This is the plant range map at the Hengduan mountain scale based on species distribution model, elevation, and county level distribution information

en: HDM heterogeneity scales

en: The Heterogeneity matrics in the Hengduan mountain scale

en: This research data is used to re includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions. This research data includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions.

habitat-heterogeneity

display_name: habitat-heterogeneity

hengduan-mountains

display_name: hengduan-mountains

hypervolume

display_name: hypervolume

model-residuals

display_name: model-residuals

phytodiversity

display_name: phytodiversity

en: Phytodiversity is associated with habitat heterogeneity from Eurasia to Hengduan


high-resolution-climate-data-for-europe

maintainer: EnviDat Support

title_for_slug: high-resolution-climate-data-for-europe

en: minimum-temperature daily-climate precipitation air-temperature maximum-temperature cordex eur11 europe

en: CHELSA EUR11 Technical Documentation

en: As the CHELSA project is continuously expanded, certain new parameters, time scales etc. are not included anymore in the original publication (Karger et al. 2017). We are therefore provide this document as a guideline of the current climatic parameters available and will expand it as new parameters or time periods will become available. Please refer to the version history for changes made in the document.

en: Data Access

media_type: NetCDF

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present downscaled climate data for the CORDEX EUR11 domain at a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperature lapse rates. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height. The resulting data consist of a daily temperature and precipitation timeseries.

The data is distributed under a: Creative Commons: Attribution 4.0 International (CC BY 4.0) license.

air-temperature

display_name: air-temperature

cordex

display_name: cordex

daily-climate

display_name: daily-climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation

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: High resolution climate data for Europe


maintainer: Jana von Freyberg

en: snowmelt-rate stable-water-isotopes solutes snowmelt-lysimeter snowpack-outflow

en: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution. 10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

en:
This data contain volumes, solutes and isotopes of snowpack outflow measured by a snowmelt lysimeter system at three locations in the southern Alp catchment, situated Central Switzerland. The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.
The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (snowpack outflow volumes) at daily intervals from several sampling locations. Additionally, the data measured by the snowmelt lysimeter system are provided in 10-minute resolution.

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes

stable-water-isotopes

display_name: stable-water-isotopes

en: Daily data of the volumes, solutes and isotopes in snowpack outflow measured at three locations in the southern Alp catchment


en: snow turbulence dust particles hill atmosphere deposition

en: preferential deposition patterns of all simulations performed

en: The data consist of matlab files. Each files contains a 2D array with the values of deposition at the surface nodes. Each array has Nx x Ny values. Please refer to the original paper for additional information on the spatial resolution and grid size.

en:
Preferential deposition of snow and dust over complex terrain is responsible for a wide range of environmental processes, and accounts for a significant source of uncertainty in surface mass balances of cold and arid regions. Despite the growing body of literature on the subject, previous studies reported contradictory results on the location and magnitude of deposition maxima and minima. This study aims at unraveling the governing processes of preferential deposition in neutrally stable atmosphere and to reconcile seemingly inconsistent results of previous works. For this purpose, a comprehensive modeling approach is developed, based on large eddy simulations of the turbulent airflow, Lagrangian stochastic model of particle trajectories, and immersed-boundary method to represent the underlying topography. The model performance is tested against wind tunnel measurements of dust deposition around isolated and sequential hills. A scale analysis is then performed to investigate the dependence of snowfall deposition on the particle Froude and Stokes numbers, which fully account for the governing processes of inertia, flow advection, and gravity. Additional simulations are performed, to test whether the often used assumption of inertialess particles yields accurate deposition patterns. We finally show that our scale analysis provides qualitatively similar results for hills with different aspect ratios.

This dataset contains the results of the LES-LSM model. Each Matlab file contains a 2D array of deposition values (in kg/m2) in each surface node (ix, iy) of the Cartesian grid. The file names are consistent with the simulation numbers listed in the original paper. For additional information, please refer to "Preferential deposition of snow and dust over hills: governing processes and relevant scales" by F. Comola, M. G. Giometto, S. T. Salesky, M. B. Parlange, and M. Lehning, Journal of Geophysical Research: Atmospheres, 2019.

atmosphere

display_name: atmosphere

deposition

display_name: deposition

dust

display_name: dust

hill

display_name: hill

particles

display_name: particles

snow

display_name: snow

turbulence

display_name: turbulence


radiosondes

maintainer: Jörg Wieder

title_for_slug: radiosondes

en: radiosonde holoballoon temperature raclets relative-humidity pressure wind-direction wind

en: Radiosond Template Files

en:
The "template" files contain standard parameters, i.e. ambient pressure (mbar and Pa), temperature (°C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), as well as additional information, e.g. time (UTC and local time), dew point (°C), mixing ration (g/kg), density (kg m³), altitude (m MSL), height above ground (ft and m AGL), and geographic coordinates (longitude, latitude). If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

en: Radiosond Sounding Files

en:
The "soundings" radiosond data contains information on ambient pressure (mbar), temperature (C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), and are ordered with respect to the height above ground (m AGL) with a step size of 20 m. The first line of each file idicates the geographic location and the start time (in UTC) of the ascent. If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

en: Radiosondes (Windsond, Sparv Embedded AB) were started in Davos Wolfgang (LON: 9.853594, LAT: 46.835577) to report height profiles of pressure, relative humidity and temperature at specific days. In addition to regular launches of radiosondes, sondes were attached to [HoloBalloon](https://www.envidat.ch/group/clouds-in-situ-raclets) to report the ambient conditions of the in-situ measurements. Further profiles of meteorological measures were recorded at [HoloGondel](https://www.envidat.ch/group/clouds-in-situ-raclets) which was installed at the gondola moving between Gotschnaboden and Gotschnagrat at 2285 m a.s.l.

holoballoon

display_name: holoballoon

pressure

display_name: pressure

raclets

display_name: raclets

radiosonde

display_name: radiosonde

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

wind

display_name: wind

wind-direction

display_name: wind-direction

en: Radiosondes


media_type: CSV

en:
Attention: this data is not updated after 2022 anymore.
This dataset contains the statistics on the number of avalanche fatalities per **calendar year** in Switzerland. The data collection commences with the beginning of the year 1937. After the completion of a hydrological year, which is the standard way avalanche fatalities are summarized in Switzerland and ends on the 30th of September, the new data is appended to the existing dataset.
If you require annual statistics per hydrological year, please download the data from here: [https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936]
The following information is contained (by column and column title):
 - year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste, away from open and secured ski runs)
 - 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 definitions for these four categories, as described in the guidelines to the avalanche accident database are:
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):
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):
people inside or just outside buildings, and workers on high alpine building sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

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

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: Number of avalanche fatalities per calendar year in Switzerland since 1937


maintainer: Leo Gallus Bont

en: seilaplan forest qgis geoprocessing openstreetmap accessible-forest

en: Juypter Notebook for Data Preparation

media_type: ipynb

en: Power lines vector data (close to the area of the sample forest range)

en: Railways vector data (close to the sample forest range)

en: Digitised sample perimeter

en: DEM (for the area of the sample forest range)

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Forest vector data (for sample forest range)

en: Juypter Notebook for Data Preparation (online)

en: Preview

media_type: image/png

format: PNG

mimetype: image/png

en:
This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps).
The purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin [Seilaplan]( https://doi.org/10.16904/envidat.software.1) for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting.
The vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019.

Additional notes for vector data:
Please note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API - https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any perimeter or area can be digitised freely using the QGIS editing toolbar.

The DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are:

- Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM)
- Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif

This methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed.

Additional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range.

This sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.

accessible-forest

display_name: accessible-forest

forest

display_name: forest

geoprocessing

display_name: geoprocessing

openstreetmap

display_name: openstreetmap

qgis

display_name: qgis

seilaplan

display_name: seilaplan

en: Sample Geodata and Software for Demonstrating Geospatial Preprocessing for Forest Accessibility and Wood Harvesting at FOSS4G2019


photogrammetric-drone-data-schurlialp

title_for_slug: photogrammetric-drone-data-schurlialp

en: photogrammetry orthophoto wingtra uav drone-data dsm

en: Data Access

media_type: TIF

en:
- 10 cm DSM
- 10 cm HS
- 3 cm orthophoto
- original RGB images
- Agisoft Metashape Processing Report

All of the products are also available as a cloud optimized geotiff.

en: The data was collected on 16.04.2021 and on 28.05.2021 with a Wingtra Gen II and a Sony RX1 II RGB sensor to obtain snow depth and distribution data. Following the data collection, the data was processed with Agisoft Metashape. A 10cm DSM, a 10cm snow depth raster, a 3mm orthophoto and the original drone images are available for download.

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

en: Photogrammetric Drone Data Schürlialp


maintainer: Henning Löwe

en: granular-snow angle-of-repose fast-sintering grain-shape discrete-element-modelling

en: Angle of repose and 3D CT images

en:
5 Snow types were examined and glass beads as a cohesion-less reference, named as follows:

RG: rounded grains (sieved with 0.7 - 1.4 mm)

FC: faceted grains (1.4 - 2 mm)

FCS: small faceted grains (0.7 - 1.4 mm)

IB: ice beads (4 mm)

IBS: small ice beads (2 - 2.2 mm)

GB: glass beads(2 mm)

en:
Angle of repose experiments were performed with different snow types at temperatures between -2 and -40°C. They were used to examine granular snow dynamics on the grain-scale with focus on the role of grain shape and cohesion. The angle of repose was observed by sieving snow onto a round, freestanding base until a stationary heap was formed.

This dataset consists of 1) the images of the experimental heaps that were taken to determine the angle of repose, 2) one binary 3D micro computed tomography image of each snow type. The CT images were taken with the SLF micro-CT40 to characterize snow properties and grain shape.

The experiments with natural snow types (rounded and faceted grains) and spherical model snow allowed for an examination of the differences in granular properties between natural grain shapes and spherical particles in view of Discrete Element Modelling. With the chosen temperatures, the effect of sintering could be observed that increases the angle of repose with increasing temperature.

angle-of-repose

display_name: angle-of-repose

discrete-element-modelling

display_name: discrete-element-modelling

fast-sintering

display_name: fast-sintering

grain-shape

display_name: grain-shape

granular-snow

display_name: granular-snow

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: Angle of repose experiments with natural and spherical snow


en: 3d-ct-images discrete-element-modelling snow-mechanics unconfined-compression-experiments spherical-model-snow microstructure

media_type: HTTPS

en: Data Structure (Python Notebook - view online)

en: Data Structure (Python Notebook)

en:
For the investigation of microstructural and mechanical properties of snow unconfined compression experiments and 3D computed tomography (CT) imaging were performed on sintered rounded grain snow and spherical model snow. The spherical model snow was generated to create geometrically simplified, well-defined microstructures for calibration of numerical models, such as discrete element models (DEM) in which the microstructure is represented by spherical particles.
In the experiments, microstructural variation was created by varying the sintering time (contact size) and the density of the ice sphere samples (number of contacts). The 3D CT images allow for a complete reconstruction of the entire experimental sample (cylindrical sample dimension: diameter = 33.6 mm; height = 14 mm).

microstructure

display_name: microstructure

snow-mechanics

display_name: snow-mechanics

spherical-model-snow

display_name: spherical-model-snow

unconfined-compression-experiments

display_name: unconfined-compression-experiments

en: Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples


maintainer: Matthias Haeni

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

en: Site photo of the field station (CLF)

media_type: image/jpeg

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

mimetype: image/jpeg

en: Data plot of the forest station (CLB)

en: Data file.

media_type: application/pdf

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

mimetype: application/pdf

en: Data plot of the field station (CLF)

en: Site photo of the forest station (CLB)

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

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: 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: Frank Techel

en: norway avalanche-observations avalanche-danger rutschblock-test extended-column-test switzerland

en: avalanche occurrence data (Norway, Sitzerland) - largest avalanche size per day and warning region

en: ECT data (Norway, Switzerland)

en: Rutschblock data (Switzerland)

en: avalanche occurrence data (Norway, Sitzerland) - avalanche sizes per day and warning region

en:
Observational data used to quantitatively describe the key elements describing avalanche danger: snowpack stability, the frequency distribution of snowpack stability, and avalanche size.
The data set consists of
- Rutschblock test results (Switzerland)
- Extended Column Test results (Switzerland, Norway)
- Avalanche occurrence data (Switzerland, Norway).
The data were extracted from the respective operational databases of the national avalanche warning services in Switzerland (WSL Institute for Snow and Avalanche Research SLF Davos, Switzerland) and Norway (The Norwegian Water Resources and Energy Directorate NVE).
For further information regarding the data, please refer to the publication or contact the author.

avalanche-danger

display_name: avalanche-danger

avalanche-observations

display_name: avalanche-observations

extended-column-test

display_name: extended-column-test

norway

display_name: norway

rutschblock-test

display_name: rutschblock-test

switzerland

display_name: switzerland

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: Stability tests, avalanche observations, Switzerland, Norway


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

en: Forest station data (VSB)

en: Data file.

en: Data plot of the forest station (VSB)

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

en: Site photo of the forest station (VSB)

en: Field station data (VSF)

en: Site aerial photo (Visp)

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

en: Data plot of the field station (VSF)

en: Site photo of the field station (VSF)

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 Visp in Switzerland where one station is located within a natural mixed forest stand (VSB) with Scots pine (_Pinus sylvestris_; 40-80 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, VSF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Visp is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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


swiss-fluxnet-site-lageren

title_for_slug: swiss-fluxnet-site-lageren

en: swiss-forest-lab greenhouse-gas flux forest swiss-fluxnet meteorological-measurements eddy-covariance

en: Site description

media_type: .pdf

en: Fluxnet2015 dataset

en: The flux and meteo data of the Swiss FluxNet site Lägeren are also part of the Fluxnet2015 dataset.

en: Data access

en: The flux and meteo data of the Swiss FluxNet site Lägeren are openly available from the European Fluxes Database Cluster.

en:
The Swiss FluxNet Site Lägeren is a managed mixed deciduous mountain forest located on the steep Lägeren mountain (NW of Zurich, Swiss Plateau). The forest is highly diverse, dominated by beech, but also including ash, maple, spruce and fir trees. Eddy covariance flux measurements were started in April 2004. The site was part of the international CarboEurope IP network and the National Air Pollution Monitoring Network (NABEL). In addition to Swiss FluxNet, the site is part of the Long-term Forest Ecosystem Research (LWF) of WSL and the biological drought and growth indicator network (TreeNet) of WSL.

Measurements

- Ecosystem flux measurements of CO2, H2O vapour are performed with the eddy-covariance method. This method is based on measurements of trace gas mixing ratios, using infrared gas analyzers (for CO2, H2O vapor), combined with wind speed and wind direction measurements, using 3D sonic anemometers. To resolve the short-term turbulent fluctuations in the atmosphere, very fast measurements are needed: we measure at 10-20 Hz, i.e., 10-20 times per second. To assess the energy budget of each ecosystem, also radiation sensors and soil climate profiles are installed at the site.
- Sub-canopy eddy fluxes (CO2, H2O), soil respiration campaigns
- Continuous CO2 profile measurements.
- Auxiliary micrometeorology and soil climate measurements.

Data availability

All data are available from the European Fluxes Database Cluster, but are also part of Fluxnet2015 dataset.

Data policy

ICOS data license:
[https://www.icos-cp.eu/data-services/about-data-portal/data-license](https://www.icos-cp.eu/data-services/about-data-portal/data-license)

Detailed site info:
[https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae//](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae/)

eddy-covariance

display_name: eddy-covariance

flux

display_name: flux

forest

display_name: forest

greenhouse-gas

display_name: greenhouse-gas

meteorological-measurements

display_name: meteorological-measurements

swiss-fluxnet

display_name: swiss-fluxnet

education

en: Education and science

en: EnviDat: the Environmental Data Portal

en: Swiss FluxNet Site Lägeren


mountain-permafrost-hydrology

maintainer: Jeannette Noetzli

title_for_slug: mountain-permafrost-hydrology

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

en: DORA Persistent URL

media_type: PDF

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

envidat

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: Mountain Permafrost Hydrology