fr: commune mariage nationalite

de: nationalitat heirat gemeinde

fr: Mariages, par nationalité des conjoints et commune, dès 1969 (json)

de: Heiraten nach Staatsangehörigkeit der Ehepartner und Gemeinde ab 1969 (json)

de: xlsx

fr: Mariages, par nationalité des conjoints et commune, dès 1969 (xlsx)

de: Heiraten nach Staatsangehörigkeit der Ehepartner und Gemeinde ab 1969 (xlsx)

fr: Mariages, par nationalité des conjoints et commune, dès 1969 (n3)

de: Heiraten nach Staatsangehörigkeit der Ehepartner und Gemeinde ab 1969 (n3)

fr: Mariages, par nationalité des conjoints et commune, dès 1969 (turtle)

de: Heiraten nach Staatsangehörigkeit der Ehepartner und Gemeinde ab 1969 (turtle)

de: jsonld

fr: Mariages, par nationalité des conjoints et commune, dès 1969 (jsonld)

de: Heiraten nach Staatsangehörigkeit der Ehepartner und Gemeinde ab 1969 (jsonld)

de: csv

fr: Mariages, par nationalité des conjoints et commune, dès 1969 (csv)

de: Heiraten nach Staatsangehörigkeit der Ehepartner und Gemeinde ab 1969 (csv)

de: jsonl

fr: Mariages, par nationalité des conjoints et commune, dès 1969 (jsonl)

de: Heiraten nach Staatsangehörigkeit der Ehepartner und Gemeinde ab 1969 (jsonl)

fr: Mariages, par nationalité des conjoints et commune, dès 1969 (rdfxml)

de: Heiraten nach Staatsangehörigkeit der Ehepartner und Gemeinde ab 1969 (rdfxml)

fr: Mariages, par nationalité des conjoints et commune, dès 1969 (parquet)

de: Heiraten nach Staatsangehörigkeit der Ehepartner und Gemeinde ab 1969 (parquet)

fr: Ce jeu de données présente les mariages, par nationalité des conjoints et commune, dès 1969.

de: Dieser Datensatz enthält Heiraten nach Nationalität der Ehepartner und Gemeinde, ab 1969.

commune

display_name: commune

gemeinde

display_name: gemeinde

heirat

display_name: heirat

mariage

display_name: mariage

nationalitat

display_name: nationalitat

nationalite

display_name: nationalite

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

de: Das Amt für Statistik und Daten ist das kantonale Kompetenzzentrum für die öffentliche Statistik. Es erhebt, analysiert und verbreitet statistische Daten über die Lage und die Entwicklung des Kantons, unterstützt die Dienststellen des Staats bei der Verwaltung ihrer Daten und koordiniert die Veröffentlichung der offenen Verwaltungsdaten.


maintainer: Centre de compétences et de coordination OGD / Kompetenz- und Koordinationszentrum für OGD

fr: indicateurs-conjoncturels nuitees hotels etablissements tourisme conjoncture-fribourgeoise

de: hotels arbeitsstatten konjunkturindikatoren tourismus freiburger-konjunkturspiegel ubernachtungen

state: active

type: dataset

media_type: application/json

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1993 (jsonl)

de: Logiernächte in Hotel- und Kurbetrieben pro Monat ab 1993 (jsonl)

format: JSON

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1993 (xlsx)

de: Logiernächte in Hotel- und Kurbetrieben pro Monat ab 1993 (xlsx)

format: XLS

de: turtle

media_type: text/turtle

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1993 (turtle)

de: Logiernächte in Hotel- und Kurbetrieben pro Monat ab 1993 (turtle)

format: RDF Turtle

media_type: text/csv

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1993 (csv)

de: Logiernächte in Hotel- und Kurbetrieben pro Monat ab 1993 (csv)

format: CSV

de: json

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1993 (json)

de: Logiernächte in Hotel- und Kurbetrieben pro Monat ab 1993 (json)

de: rdfxml

media_type: application/rdf+xml

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1993 (rdfxml)

de: Logiernächte in Hotel- und Kurbetrieben pro Monat ab 1993 (rdfxml)

format: RDF XML

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1993 (n3)

de: Logiernächte in Hotel- und Kurbetrieben pro Monat ab 1993 (n3)

de: parquet

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1993 (parquet)

de: Logiernächte in Hotel- und Kurbetrieben pro Monat ab 1993 (parquet)

format: PARQUET

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1993 (jsonld)

de: Logiernächte in Hotel- und Kurbetrieben pro Monat ab 1993 (jsonld)

format: JSON-LD

fr: Ce jeu de données présente l'aperçu mensuel des nuitées dans les hôtels et les établissements de cure dans le canton de Fribourg et dans l'ensemble de la Suisse, depuis 1993. Aucune donnée n'est disponible pour l'année 2004, la série a été interrompue à fin 2003 par l'OFS et reprise en 2005.

de: Dieser Datensatz enthält eine monatliche Übersicht über die Übernachtungen in Hotels und Kurbetrieben im Kanton Freiburg und in der gesamten Schweiz seit 1993. Für das Jahr 2004 sind keine Daten verfügbar, da die Reihe Ende 2003 vom BFS unterbrochen und 2005 fortgesetzt wurde.

arbeitsstatten

display_name: arbeitsstatten

conjoncture-fribourgeoise

display_name: conjoncture-fribourgeoise

etablissements

display_name: etablissements

freiburger-konjunkturspiegel

display_name: freiburger-konjunkturspiegel

hotels

display_name: hotels

indicateurs-conjoncturels

display_name: indicateurs-conjoncturels

konjunkturindikatoren

display_name: konjunkturindikatoren

nuitees

display_name: nuitees

tourisme

display_name: tourisme

tourismus

display_name: tourismus

ubernachtungen

display_name: ubernachtungen

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

ssd

fr: Service de la statistique et de la donnée Fribourg

de: Amt für Statistik und Daten Freiburg

en: Statistics and Data Service Fribourg

it: Servizio Statistiche e Dati Friburgo

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.

en: The Statistics and Data Service is the cantonal competence center for public statistics. It collects, analyzes, and disseminates statistical data on the situation and development of the canton, supports state services in data management, and coordinates the dissemination of administrative data in open access.

it: Il Servizio Statistiche e Dati è il centro di competenza cantonale per la statistica pubblica. Raccoglie, analizza e diffonde dati statistici sulla situazione e l'evoluzione del cantone, supporta i servizi statali nella gestione dei dati e coordina la diffusione dei dati amministrativi ad accesso aperto.

political_level: canton

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: DCAT Harvester Kt. FR


name: Centre de compétences et de coordination OGD / Kompetenz- und Koordinationszentrum für OGD

fr: carburant energie voitures

de: energie treibstoff personenwagen

de: xlsx

fr: Voitures de tourisme, par type de carburant/énergie, dès 2017 (xlsx)

de: Personenwagen nach Treibstoffart/Energie ab 2017 (xlsx)

de: csv

fr: Voitures de tourisme, par type de carburant/énergie, dès 2017 (csv)

de: Personenwagen nach Treibstoffart/Energie ab 2017 (csv)

de: jsonld

fr: Voitures de tourisme, par type de carburant/énergie, dès 2017 (jsonld)

de: Personenwagen nach Treibstoffart/Energie ab 2017 (jsonld)

fr: Voitures de tourisme, par type de carburant/énergie, dès 2017 (rdfxml)

de: Personenwagen nach Treibstoffart/Energie ab 2017 (rdfxml)

de: jsonl

fr: Voitures de tourisme, par type de carburant/énergie, dès 2017 (jsonl)

de: Personenwagen nach Treibstoffart/Energie ab 2017 (jsonl)

fr: Voitures de tourisme, par type de carburant/énergie, dès 2017 (json)

de: Personenwagen nach Treibstoffart/Energie ab 2017 (json)

fr: Voitures de tourisme, par type de carburant/énergie, dès 2017 (parquet)

de: Personenwagen nach Treibstoffart/Energie ab 2017 (parquet)

fr: Voitures de tourisme, par type de carburant/énergie, dès 2017 (turtle)

de: Personenwagen nach Treibstoffart/Energie ab 2017 (turtle)

fr: Voitures de tourisme, par type de carburant/énergie, dès 2017 (n3)

de: Personenwagen nach Treibstoffart/Energie ab 2017 (n3)

fr: Ce jeu de données présente les voitures de tourisme, par type de carburant/énergie, dès 2017.

de: Dieser Datensatz enthält die Personenwagen nach Treibstoffart/Energie ab 2017.

carburant

display_name: carburant

energie

display_name: energie

personenwagen

display_name: personenwagen

treibstoff

display_name: treibstoff

voitures

display_name: voitures

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

de: Das Amt für Statistik und Daten ist das kantonale Kompetenzzentrum für die öffentliche Statistik. Es erhebt, analysiert und verbreitet statistische Daten über die Lage und die Entwicklung des Kantons, unterstützt die Dienststellen des Staats bei der Verwaltung ihrer Daten und koordiniert die Veröffentlichung der offenen Verwaltungsdaten.


fr: emplois forme-juridique etablissements activite-economique equivalents-plein-temps

de: vollzeitaquivalente arbeitsstatten rechtsform wirtschaftssektor beschaftigte

fr: Etablissements, emplois et équivalents plein temps, selon l'activité économique et la forme juridique, dès 2011 (n3)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalente nach Wirtschaftszweig und Rechtsform ab 2011 (n3)

de: rdfxml

fr: Etablissements, emplois et équivalents plein temps, selon l'activité économique et la forme juridique, dès 2011 (rdfxml)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalente nach Wirtschaftszweig und Rechtsform ab 2011 (rdfxml)

fr: Etablissements, emplois et équivalents plein temps, selon l'activité économique et la forme juridique, dès 2011 (xlsx)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalente nach Wirtschaftszweig und Rechtsform ab 2011 (xlsx)

fr: Etablissements, emplois et équivalents plein temps, selon l'activité économique et la forme juridique, dès 2011 (jsonld)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalente nach Wirtschaftszweig und Rechtsform ab 2011 (jsonld)

de: turtle

fr: Etablissements, emplois et équivalents plein temps, selon l'activité économique et la forme juridique, dès 2011 (turtle)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalente nach Wirtschaftszweig und Rechtsform ab 2011 (turtle)

fr: Etablissements, emplois et équivalents plein temps, selon l'activité économique et la forme juridique, dès 2011 (csv)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalente nach Wirtschaftszweig und Rechtsform ab 2011 (csv)

de: parquet

fr: Etablissements, emplois et équivalents plein temps, selon l'activité économique et la forme juridique, dès 2011 (parquet)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalente nach Wirtschaftszweig und Rechtsform ab 2011 (parquet)

de: json

fr: Etablissements, emplois et équivalents plein temps, selon l'activité économique et la forme juridique, dès 2011 (json)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalente nach Wirtschaftszweig und Rechtsform ab 2011 (json)

fr: Etablissements, emplois et équivalents plein temps, selon l'activité économique et la forme juridique, dès 2011 (jsonl)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalente nach Wirtschaftszweig und Rechtsform ab 2011 (jsonl)

fr: Ce jeu de données présente les chiffres annuels du nombre d'établissements, d'emplois et d'emplois en équivalents plein temps du canton de Fribourg, selon l'activité économique et la forme juridique, depuis 2011.Les données de Clavaleyres, commune anciennement bernoise fusionnée avec Morat au 1er janvier 2022, sont incluses à celles du canton de Fribourg rétroactivement pour toute la période d'observation.

de: Dieser Datensatz enthält die jährlichen Zahlen der Anzahl Arbeitsstätten , Beschäftigten und Vollzeitäquivalente des Kantons Freiburg nach Wirtschaftszweigen und Rechtsform ab 2011.Die Daten von Clavaleyres, einer ehemals bernischen Gemeinde, die am 1. Januar 2022 mit Murten fusionierte, sind rückwirkend für den gesamten Beobachtungszeitraum in die Daten des Kantons Freiburg integriert.

activite-economique

display_name: activite-economique

beschaftigte

display_name: beschaftigte

emplois

display_name: emplois

equivalents-plein-temps

display_name: equivalents-plein-temps

forme-juridique

display_name: forme-juridique

rechtsform

display_name: rechtsform

vollzeitaquivalente

display_name: vollzeitaquivalente

wirtschaftssektor

display_name: wirtschaftssektor

econ

de: Wirtschaft und Finanzen

ssd

de: Amt für Statistik und Daten Freiburg


fr: systeme-dexploitation exploitation agriculture district commune

de: betriebssystem landwirtschaft gemeinde bezirk betrieb

author: ssd

fr: Exploitations agricoles selon le système d'exploitation, dès 1975 (json)

de: Landwirtschaftsbetriebe nach Betriebssystem ab 1975 (json)

fr: Exploitations agricoles selon le système d'exploitation, dès 1975 (rdfxml)

de: Landwirtschaftsbetriebe nach Betriebssystem ab 1975 (rdfxml)

fr: Exploitations agricoles selon le système d'exploitation, dès 1975 (turtle)

de: Landwirtschaftsbetriebe nach Betriebssystem ab 1975 (turtle)

de: xlsx

fr: Exploitations agricoles selon le système d'exploitation, dès 1975 (xlsx)

de: Landwirtschaftsbetriebe nach Betriebssystem ab 1975 (xlsx)

de: csv

fr: Exploitations agricoles selon le système d'exploitation, dès 1975 (csv)

de: Landwirtschaftsbetriebe nach Betriebssystem ab 1975 (csv)

fr: Exploitations agricoles selon le système d'exploitation, dès 1975 (parquet)

de: Landwirtschaftsbetriebe nach Betriebssystem ab 1975 (parquet)

de: jsonld

fr: Exploitations agricoles selon le système d'exploitation, dès 1975 (jsonld)

de: Landwirtschaftsbetriebe nach Betriebssystem ab 1975 (jsonld)

fr: Exploitations agricoles selon le système d'exploitation, dès 1975 (n3)

de: Landwirtschaftsbetriebe nach Betriebssystem ab 1975 (n3)

de: jsonl

fr: Exploitations agricoles selon le système d'exploitation, dès 1975 (jsonl)

de: Landwirtschaftsbetriebe nach Betriebssystem ab 1975 (jsonl)

fr:
Ce jeu de données présente le nombre d'exploitations agricoles, par systèmes d'exploitation dans le canton de Fribourg, par district et commune depuis 1975. Les données sont fournies en 3 catégories :

- Exploitations conventionnelles
- Exploitations biologiques
- Indeterminé

Une exploitation agricole est considérée biologique si une partie ou la totalité de sa surface agricole utile est certifiée BIO.Les données de Clavaleyres, commune anciennement bernoise fusionnée avec Morat au 1er janvier 2022, sont incluses à celles du canton de Fribourg et de la commune de Morat rétroactivement pour toute la période d'observation.

de:
Dieser
Datensatz zeigt die Anzahl Landwirtschaftsbetriebe nach Betriebssystem im
Kanton Freiburg, aufgeschlüsselt nach Bezirk und Gemeinde, seit 1975. Die Daten
werden in 3 Kategorien bereitgestellt:
Konventionelle
     Betriebe
Biologische
     Betriebe
Unbestimmt

Ein
landwirtschaftlicher Betrieb gilt als biologisch, wenn ein Teil oder die
gesamte landwirtschaftlich genutzte Fläche BIO-zertifiziert ist.

agriculture

display_name: agriculture

betrieb

display_name: betrieb

betriebssystem

display_name: betriebssystem

bezirk

display_name: bezirk

commune

display_name: commune

district

display_name: district

exploitation

display_name: exploitation

gemeinde

display_name: gemeinde

landwirtschaft

display_name: landwirtschaft

systeme-dexploitation

display_name: systeme-dexploitation

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

fr: Service de la statistique et de la donnée Fribourg

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.

de: Das Amt für Statistik und Daten ist das kantonale Kompetenzzentrum für die öffentliche Statistik. Es erhebt, analysiert und verbreitet statistische Daten über die Lage und die Entwicklung des Kantons, unterstützt die Dienststellen des Staats bei der Verwaltung ihrer Daten und koordiniert die Veröffentlichung der offenen Verwaltungsdaten.


fr: indicateurs-conjoncturels offices-des-poursuites poursuites district conjoncture-fribourgeoise

de: freiburger-konjunkturspiegel schuldbetreibungen bezirk betreibungsamter konjunkturindikatoren

de: parquet

fr: Poursuites, par mois, dès 1994 (parquet)

de: Betreibungen pro Monat ab 1994 (parquet)

de: rdfxml

fr: Poursuites, par mois, dès 1994 (rdfxml)

de: Betreibungen pro Monat ab 1994 (rdfxml)

de: turtle

fr: Poursuites, par mois, dès 1994 (turtle)

de: Betreibungen pro Monat ab 1994 (turtle)

de: json

fr: Poursuites, par mois, dès 1994 (json)

de: Betreibungen pro Monat ab 1994 (json)

fr: Poursuites, par mois, dès 1994 (csv)

de: Betreibungen pro Monat ab 1994 (csv)

fr: Poursuites, par mois, dès 1994 (xlsx)

de: Betreibungen pro Monat ab 1994 (xlsx)

fr: Poursuites, par mois, dès 1994 (jsonld)

de: Betreibungen pro Monat ab 1994 (jsonld)

fr: Poursuites, par mois, dès 1994 (jsonl)

de: Betreibungen pro Monat ab 1994 (jsonl)

fr: Poursuites, par mois, dès 1994 (n3)

de: Betreibungen pro Monat ab 1994 (n3)

fr: Ce jeu de données présente les chiffres mensuels des poursuites, par district du canton de Fribourg, depuis 1994.

de: Dieser Datensatz enthält die monatlichen Betreibungszahlen, nach Bezirken des Kantons Freiburg, seit 1994.

betreibungsamter

display_name: betreibungsamter

conjoncture-fribourgeoise

display_name: conjoncture-fribourgeoise

freiburger-konjunkturspiegel

display_name: freiburger-konjunkturspiegel

indicateurs-conjoncturels

display_name: indicateurs-conjoncturels

konjunkturindikatoren

display_name: konjunkturindikatoren

offices-des-poursuites

display_name: offices-des-poursuites

poursuites

display_name: poursuites

schuldbetreibungen

display_name: schuldbetreibungen

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

ssd

de: Amt für Statistik und Daten Freiburg


fr: etablissements secteurs equivalents-plein-temps activite-economique emplois commune

de: arbeitsstatten wirtschaftssektor sektoren beschaftigte gemeinde vollzeitaquivalente

fr: Etablissements, emplois et équivalents plein temps du secteur privé et du secteur public, selon l'activité économique, dès 2011 (turtle)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalenten des privaten und des öffentlichen Sektors nach Wirtschaftszweig ab 2011 (turtle)

de: xlsx

fr: Etablissements, emplois et équivalents plein temps du secteur privé et du secteur public, selon l'activité économique, dès 2011 (xlsx)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalenten des privaten und des öffentlichen Sektors nach Wirtschaftszweig ab 2011 (xlsx)

de: jsonl

fr: Etablissements, emplois et équivalents plein temps du secteur privé et du secteur public, selon l'activité économique, dès 2011 (jsonl)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalenten des privaten und des öffentlichen Sektors nach Wirtschaftszweig ab 2011 (jsonl)

de: jsonld

fr: Etablissements, emplois et équivalents plein temps du secteur privé et du secteur public, selon l'activité économique, dès 2011 (jsonld)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalenten des privaten und des öffentlichen Sektors nach Wirtschaftszweig ab 2011 (jsonld)

fr: Etablissements, emplois et équivalents plein temps du secteur privé et du secteur public, selon l'activité économique, dès 2011 (json)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalenten des privaten und des öffentlichen Sektors nach Wirtschaftszweig ab 2011 (json)

fr: Etablissements, emplois et équivalents plein temps du secteur privé et du secteur public, selon l'activité économique, dès 2011 (rdfxml)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalenten des privaten und des öffentlichen Sektors nach Wirtschaftszweig ab 2011 (rdfxml)

de: csv

fr: Etablissements, emplois et équivalents plein temps du secteur privé et du secteur public, selon l'activité économique, dès 2011 (csv)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalenten des privaten und des öffentlichen Sektors nach Wirtschaftszweig ab 2011 (csv)

fr: Etablissements, emplois et équivalents plein temps du secteur privé et du secteur public, selon l'activité économique, dès 2011 (n3)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalenten des privaten und des öffentlichen Sektors nach Wirtschaftszweig ab 2011 (n3)

fr: Etablissements, emplois et équivalents plein temps du secteur privé et du secteur public, selon l'activité économique, dès 2011 (parquet)

de: Arbeitsstätten, Beschäftigte und Beschäftigte in Vollzeitäquivalenten des privaten und des öffentlichen Sektors nach Wirtschaftszweig ab 2011 (parquet)

fr: Ce jeu de données présente les chiffres annuels du nombre d'établissements, d'emplois et d'emplois en équivalents plein temps du canton de Fribourg du secteur privé et du secteur public, selon l'activité économique et la commune, depuis 2011.Les données de Clavaleyres, commune anciennement bernoise fusionnée avec Morat au 1er janvier 2022, sont incluses à celles du canton de Fribourg et de la commune de Morat rétroactivement pour toute la période d'observation.

de: Dieser Datensatz enthält die jährlichen Zahlen der Anzahl Betriebe, Arbeitsplätze und Vollzeitäquivalente im Kanton Freiburg des privaten und öffentlichen Sektors, nach Wirtschaftszweigen und Gemeinden, seit 2011.Die Daten von Clavaleyres, einer ehemals bernischen Gemeinde, die am 1. Januar 2022 mit Murten fusionierte, sind rückwirkend für den gesamten Beobachtungszeitraum in die Daten des Kantons Freiburg bzw. der Gemeinde Murten integriert.

activite-economique

display_name: activite-economique

arbeitsstatten

display_name: arbeitsstatten

beschaftigte

display_name: beschaftigte

emplois

display_name: emplois

equivalents-plein-temps

display_name: equivalents-plein-temps

etablissements

display_name: etablissements

secteurs

display_name: secteurs

sektoren

display_name: sektoren

vollzeitaquivalente

display_name: vollzeitaquivalente

wirtschaftssektor

display_name: wirtschaftssektor

de: Das Amt für Statistik und Daten ist das kantonale Kompetenzzentrum für die öffentliche Statistik. Es erhebt, analysiert und verbreitet statistische Daten über die Lage und die Entwicklung des Kantons, unterstützt die Dienststellen des Staats bei der Verwaltung ihrer Daten und koordiniert die Veröffentlichung der offenen Verwaltungsdaten.


fr: commune population-dite-legale

de: gemeinde zivilrechtliche-bevolkerung

fr: Population dite légale par commune, dès 1980 (xlsx)

de: Zivilrechtliche Bevölkerung nach Gemeinde ab 1980 (xlsx)

de: rdfxml

fr: Population dite légale par commune, dès 1980 (rdfxml)

de: Zivilrechtliche Bevölkerung nach Gemeinde ab 1980 (rdfxml)

fr: Population dite légale par commune, dès 1980 (jsonl)

de: Zivilrechtliche Bevölkerung nach Gemeinde ab 1980 (jsonl)

fr: Population dite légale par commune, dès 1980 (jsonld)

de: Zivilrechtliche Bevölkerung nach Gemeinde ab 1980 (jsonld)

fr: Population dite légale par commune, dès 1980 (n3)

de: Zivilrechtliche Bevölkerung nach Gemeinde ab 1980 (n3)

de: json

fr: Population dite légale par commune, dès 1980 (json)

de: Zivilrechtliche Bevölkerung nach Gemeinde ab 1980 (json)

de: turtle

fr: Population dite légale par commune, dès 1980 (turtle)

de: Zivilrechtliche Bevölkerung nach Gemeinde ab 1980 (turtle)

fr: Population dite légale par commune, dès 1980 (csv)

de: Zivilrechtliche Bevölkerung nach Gemeinde ab 1980 (csv)

de: parquet

fr: Population dite légale par commune, dès 1980 (parquet)

de: Zivilrechtliche Bevölkerung nach Gemeinde ab 1980 (parquet)

fr: Ce jeu de données présente la population dite légale par commune depuis 1980.

de: Dieser Datensatz zeigt die zivilrechtliche Bevölkerung nach Gemeinde ab 1980.

commune

display_name: commune

gemeinde

display_name: gemeinde

population-dite-legale

display_name: population-dite-legale

zivilrechtliche-bevolkerung

display_name: zivilrechtliche-bevolkerung

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

ssd

fr: Service de la statistique et de la donnée Fribourg

de: Amt für Statistik und Daten Freiburg

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.


fr: logements batiments vacants constructions commune

de: wohnungen gebaude leerstehende bau gemeinde

de: jsonld

fr: Logements vacants, selon la catégorie de bâtiment et le nombre de pièces, dès 1995 (jsonld)

de: Leerstehende Wohnungen nach Gebäudekategorie und Anzahl Zimmer ab 1995 (jsonld)

fr: Logements vacants, selon la catégorie de bâtiment et le nombre de pièces, dès 1995 (json)

de: Leerstehende Wohnungen nach Gebäudekategorie und Anzahl Zimmer ab 1995 (json)

fr: Logements vacants, selon la catégorie de bâtiment et le nombre de pièces, dès 1995 (parquet)

de: Leerstehende Wohnungen nach Gebäudekategorie und Anzahl Zimmer ab 1995 (parquet)

de: csv

fr: Logements vacants, selon la catégorie de bâtiment et le nombre de pièces, dès 1995 (csv)

de: Leerstehende Wohnungen nach Gebäudekategorie und Anzahl Zimmer ab 1995 (csv)

fr: Logements vacants, selon la catégorie de bâtiment et le nombre de pièces, dès 1995 (turtle)

de: Leerstehende Wohnungen nach Gebäudekategorie und Anzahl Zimmer ab 1995 (turtle)

de: xlsx

fr: Logements vacants, selon la catégorie de bâtiment et le nombre de pièces, dès 1995 (xlsx)

de: Leerstehende Wohnungen nach Gebäudekategorie und Anzahl Zimmer ab 1995 (xlsx)

fr: Logements vacants, selon la catégorie de bâtiment et le nombre de pièces, dès 1995 (rdfxml)

de: Leerstehende Wohnungen nach Gebäudekategorie und Anzahl Zimmer ab 1995 (rdfxml)

fr: Logements vacants, selon la catégorie de bâtiment et le nombre de pièces, dès 1995 (n3)

de: Leerstehende Wohnungen nach Gebäudekategorie und Anzahl Zimmer ab 1995 (n3)

de: jsonl

fr: Logements vacants, selon la catégorie de bâtiment et le nombre de pièces, dès 1995 (jsonl)

de: Leerstehende Wohnungen nach Gebäudekategorie und Anzahl Zimmer ab 1995 (jsonl)

fr: Ce jeu de données présente les logements vacants, selon la catégorie de bâtiment et le nombre de pièces dès 1995.Remarques: Les données statistiques des communes fribourgeoises qui fusionnent sont intégrées rétroactivement à la nouvelle commune. Les données statistiques de Clavaleyres, anciennement commune bernoise, sont incluses à celles du canton de Fribourg et à la commune de Morat dès la période d’observation 2022.

de: Dieser Datensatz zeigt die leerstehenden Wohnungen nach Gebäudekategorie und Zimmerzahl ab 1995.Anmerkungen: Die statistischen Daten von fusionierenden Freiburger Gemeinden werden rückwirkend in die neue Gemeinde integriert. Die statistischen Daten von Clavaleyres, einer ehemals bernischen Gemeinde, werden ab dem Beobachtungszeitraum 2022 in die Daten des Kantons Freiburg und der Gemeinde Murten integriert.

batiments

display_name: batiments

bau

display_name: bau

constructions

display_name: constructions

gebaude

display_name: gebaude

leerstehende

display_name: leerstehende

logements

display_name: logements

vacants

display_name: vacants

wohnungen

display_name: wohnungen

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

de: Das Amt für Statistik und Daten ist das kantonale Kompetenzzentrum für die öffentliche Statistik. Es erhebt, analysiert und verbreitet statistische Daten über die Lage und die Entwicklung des Kantons, unterstützt die Dienststellen des Staats bei der Verwaltung ihrer Daten und koordiniert die Veröffentlichung der offenen Verwaltungsdaten.


fr: conjoncture-fribourgeoise registre-du-commerce faillites indicateurs-conjoncturels

de: konkurse konjunkturindikatoren freiburger-konjunkturspiegel handelsregister

de: parquet

fr: Ouvertures de faillites inscrites au Registre du commerce, par mois, dès 2019 (parquet)

de: Im Handelsregister eingetragene Konkurseröffnungen, pro Monat ab 2019 (parquet)

de: rdfxml

fr: Ouvertures de faillites inscrites au Registre du commerce, par mois, dès 2019 (rdfxml)

de: Im Handelsregister eingetragene Konkurseröffnungen, pro Monat ab 2019 (rdfxml)

de: turtle

fr: Ouvertures de faillites inscrites au Registre du commerce, par mois, dès 2019 (turtle)

de: Im Handelsregister eingetragene Konkurseröffnungen, pro Monat ab 2019 (turtle)

fr: Ouvertures de faillites inscrites au Registre du commerce, par mois, dès 2019 (csv)

de: Im Handelsregister eingetragene Konkurseröffnungen, pro Monat ab 2019 (csv)

fr: Ouvertures de faillites inscrites au Registre du commerce, par mois, dès 2019 (n3)

de: Im Handelsregister eingetragene Konkurseröffnungen, pro Monat ab 2019 (n3)

fr: Ouvertures de faillites inscrites au Registre du commerce, par mois, dès 2019 (jsonl)

de: Im Handelsregister eingetragene Konkurseröffnungen, pro Monat ab 2019 (jsonl)

fr: Ouvertures de faillites inscrites au Registre du commerce, par mois, dès 2019 (jsonld)

de: Im Handelsregister eingetragene Konkurseröffnungen, pro Monat ab 2019 (jsonld)

fr: Ouvertures de faillites inscrites au Registre du commerce, par mois, dès 2019 (xlsx)

de: Im Handelsregister eingetragene Konkurseröffnungen, pro Monat ab 2019 (xlsx)

de: json

fr: Ouvertures de faillites inscrites au Registre du commerce, par mois, dès 2019 (json)

de: Im Handelsregister eingetragene Konkurseröffnungen, pro Monat ab 2019 (json)

fr: Ce jeu de données présente les chiffres mensuels du nombre d'inscriptions des ouvertures de faillites d'entités juridiques du canton de Fribourg, depuis 2019. Ces chiffres ne comprennent pas les dissolutions et successions répudiées.

de: Dieser Datensatz enthält die monatlichen Zahlen der Eintragungen der Konkurseröffnungen von juristischen Personen im Kanton Freiburg ab 2019. Diese Zahlen beinhalten keine Auflösungen und ausgeschlagene Erbschaften.

conjoncture-fribourgeoise

display_name: conjoncture-fribourgeoise

faillites

display_name: faillites

freiburger-konjunkturspiegel

display_name: freiburger-konjunkturspiegel

handelsregister

display_name: handelsregister

indicateurs-conjoncturels

display_name: indicateurs-conjoncturels

konjunkturindikatoren

display_name: konjunkturindikatoren

konkurse

display_name: konkurse

registre-du-commerce

display_name: registre-du-commerce

ssd

de: Amt für Statistik und Daten Freiburg


fr: canton district votations

de: kanton abstimmungen bezirk

de: jsonld

fr: Votations cantonales fribourgeoises par district, dès 2015 (jsonld)

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015 (jsonld)

de: xlsx

fr: Votations cantonales fribourgeoises par district, dès 2015 (xlsx)

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015 (xlsx)

fr: Votations cantonales fribourgeoises par district, dès 2015 (turtle)

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015 (turtle)

fr: Votations cantonales fribourgeoises par district, dès 2015 (n3)

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015 (n3)

de: jsonl

fr: Votations cantonales fribourgeoises par district, dès 2015 (jsonl)

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015 (jsonl)

fr: Votations cantonales fribourgeoises par district, dès 2015 (parquet)

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015 (parquet)

fr: Votations cantonales fribourgeoises par district, dès 2015 (rdfxml)

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015 (rdfxml)

fr: Votations cantonales fribourgeoises par district, dès 2015 (json)

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015 (json)

de: csv

fr: Votations cantonales fribourgeoises par district, dès 2015 (csv)

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015 (csv)

fr: Ce jeu de données présente les résultats des votations cantonales par district dès 2015.L'état des districts est celui en vigueur au moment du vote.La somme des votes "oui" et "non" pour la votation du 9 juin 2024 concernant les urgences hospitalières publiques 24/24 ne correspond pas au nombre de bulletins valides, l'option "sans réponse" étant comptabilisée comme un vote valide.

de: Freiburger kantonale Abstimmungen nach Bezirken, ab 2015.Der Stand der Bezirke ist jener zum Zeitpunkt der Abstimmung gültige.Die Summe der „Ja“- und „Nein“-Stimmen für die Abstimmung vom 9. Juni 2024 über öffentliche 24-Stunden-Notaufnahmen in Krankenhäusern entspricht nicht der Anzahl der gültigen Stimmzettel, da die Option „keine Antwort“ als gültige Stimme gezählt wird.

abstimmungen

display_name: abstimmungen

bezirk

display_name: bezirk

canton

display_name: canton

district

display_name: district

kanton

display_name: kanton

votations

display_name: votations

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

fr: Service de la statistique et de la donnée Fribourg

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.

de: Das Amt für Statistik und Daten ist das kantonale Kompetenzzentrum für die öffentliche Statistik. Es erhebt, analysiert und verbreitet statistische Daten über die Lage und die Entwicklung des Kantons, unterstützt die Dienststellen des Staats bei der Verwaltung ihrer Daten und koordiniert die Veröffentlichung der offenen Verwaltungsdaten.


de: rdfxml

fr: Liste des communes du canton de Fribourg dès 1960 (rdfxml)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (rdfxml)

de: kml

fr: Liste des communes du canton de Fribourg dès 1960 (kml)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (kml)

format: KML

de: shp

media_type: application/zip

fr: Liste des communes du canton de Fribourg dès 1960 (shp)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (shp)

format: ZIP

fr: Liste des communes du canton de Fribourg dès 1960 (n3)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (n3)

fr: Liste des communes du canton de Fribourg dès 1960 (jsonl)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (jsonl)

media_type: text/plain

fr: Liste des communes du canton de Fribourg dès 1960 (ov2)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (ov2)

format: TXT

fr: Liste des communes du canton de Fribourg dès 1960 (jsonld)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (jsonld)

de: gpx

fr: Liste des communes du canton de Fribourg dès 1960 (gpx)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (gpx)

format: GPX

de: turtle

fr: Liste des communes du canton de Fribourg dès 1960 (turtle)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (turtle)

de: fgb

fr: Liste des communes du canton de Fribourg dès 1960 (fgb)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (fgb)

format: OCTET

fr: Liste des communes du canton de Fribourg dès 1960 (csv)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (csv)

de: json

fr: Liste des communes du canton de Fribourg dès 1960 (json)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (json)

de: parquet

fr: Liste des communes du canton de Fribourg dès 1960 (parquet)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (parquet)

de: geojson

fr: Liste des communes du canton de Fribourg dès 1960 (geojson)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (geojson)

fr: Liste des communes du canton de Fribourg dès 1960 (xlsx)

de: Liste der Gemeinden im Kanton Freiburg ab 1960 (xlsx)

fr: Ce jeu de données présente la liste des communes fribourgeoise par année dès 1960.

commune

display_name: commune

gemeinde

display_name: gemeinde

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

ssd

de: Amt für Statistik und Daten Freiburg


maintainer: Paraskevi Georgakaki

en: secondary-ice-production wrf jungfraujoch ice-water-content ice-crystal-number-concentration swiss-alps blowing-snow liquid-water-content

en: WRF outputs

en:
The .zip file contains all the NetCDF outputs produced by the mesoscale Weather Research and Forecasting (WRF) model (version: 4.0.1). Two case studies were simulated in this study, between 25-28 January 2014 (00:00 UTC) and 29 January - 1 February 2014 (00:00 UTC), respectively. The former is denoted as "NW" and the latter as "SE", owing to the prevailing wind conditions at the Jungfraujoch (JFJ) station.

The outputs come from the innermost domain of the simulations with a spatial resolution of 1 km and are extracted from the nearest to JFJ model grid point (46.55°N 7.98°E). The dimensions of each model variable is [145,100], which corresponds to time and height, respectively. The frequency of the outputs is 30 min. Note that the first 24 hours of each simulation (i.e., the first 48 outputs) were considered spin up time.

The following sets of sensitivity simulations were presented in this study:

* CNTRL_NW.nc, CNTRL_SE.nc : Sensitivity simulations performed with the default version of WRF
* DS_PHILL_NW.nc, DS_PHILL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Phillips et al. (2018)
* DS_SULL_NW.nc, DS_SULL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Sullivan et al. (2018)
* PHILL_NW.nc, PHILL_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Phillips et al. (2017)
* TAKAH_NW.nc, TAKAH_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Sullivan et al. (2018) based on Takahashi et al. (1995)
* TAKAHrim_NW.nc, TAKAHrim_SE.nc : Same set-up as before but applied only to collisions between rimed ice particles
* BIPS_Xk0_DY_NW.nc, BIPS_Xk0_DY_SE.nc : Sensitivity simulations including a source of Xk0 (either 10.0 or 100.0 L⁻¹) ice crystals with sizes of DY (either 10 or 100 μm) in the first atmospheric level of the model
* BIPS100_PHILL_NW.nc, BIPS100_PHILL_SE.nc : Sensitivity simulations where the combined effect of blowing snow and ice-ice collisional break-up is examined

format: SERVICE

en: Observational data

en:
The .zip file contains 6 .csv files including all microphysical measurements taken at the Jungfraujoch station during the two periods of interest:

* 25-28 January 2014 : northwesterly-winds (NW)
* 29 January - 1 February 2014 : southeasterly-winds (SE)

The total Ice Crystal Number Concentration (ICNC; reported in L⁻¹) is measured by the two-dimensional stereo hydrometeor spectrometer (2D-S; Lawson et al., 2006) over the size range 10-1280 μm. The total ice water content (IWC; reported in gm⁻³) is also derived by the 2D-S data using the Brown and Francis (1995) mass-diameter relationship. Finally, the quantification of the liquid water content (LWC; reported in gm⁻³) is based on the liquid droplet size distribution data derived from a DMT cloud droplet probe (CDP; Lance et al., 2010) over the size range 2-50 μm. The frequency of the measurements in the .csv files is 30 min, to match the output frequency of the model. Datetime is also reported in the files (DD/MM/YYYY h:mm) in UTC.

Acknowledgment: Collection and pre-processing of the microphysical measurements has been performed by Gary Lloyd (gary.lloyd@manchester.ac.uk). More details about the instrumentation during the CLACE2014 campaign can be found in Lloyd et al. (2015).

en:
This repository contains all WRF model outputs and observational data sets used for the paper:
Georgakaki, P., Sotiropoulou, G., Vignon, É., Billault-Roux, A.-C., Berne, A., and Nenes, A.: Secondary ice production processes in wintertime alpine mixed-phase clouds, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-760, in review, 2021.

blowing-snow

display_name: blowing-snow

ice-crystal-number-concentration

display_name: ice-crystal-number-concentration

ice-water-content

display_name: ice-water-content

jungfraujoch

display_name: jungfraujoch

liquid-water-content

display_name: liquid-water-content

secondary-ice-production

display_name: secondary-ice-production

swiss-alps

display_name: swiss-alps

wrf

display_name: wrf

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

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: Data for the publication "Secondary ice production processes in wintertime alpine mixed-phase clouds"


maintainer: EnviDat Support

en: landscape wetlands connectivity conservation amphibians occupancy-models

en: Covariate data 2

en: This file contains covariate data that changes over time for 856 ponds in 21 years (long format): whether or not a pond exists in year _t_, the age of constructed ponds in year _t_, structural connectivity of the pond in year _t_.

en: Covariate data 1

en: This file contains covariate data that does not change over time for 856 ponds: the region the pond is in, whether the pond is old or new (constructed since 1991), elevation, water surface area, fluctuations of the water table (yes, no), the percent forest cover in 100m radius around the pond, the area or large (>6m wide) roads in 1km radius around the pond.

en: Original raw data

en: This file contains the original raw monitoring data as provided by the canton of Aargau. Access is restricted and only considered upon request and in consultation with the canton of Aargau.

en: Potential population connectivity data

en: This file contains potential population connectivity data (three different metrics), calculated based on all existing and occupied ponds in each year, for each species, in long format. See Readme v2.0 for details. Required to run Model code 2.

en: Model code 2

en: This R markdown file contains all code and descriptions necessary to load and format the provided data and to fit the dynamic occupancy models described in the second associated publication, including JAGS code for the fitted models.

en: Model code

en: This R markdown file contains all code and descriptions necessary to load and format the provided data and to fit the dynamic occupancy models described in the associated publication, including JAGS code for the fitted models.

en: Model code 2, description

media_type: text/html

en: This is the output of the R markdown file Model code 2 that provides JAGS model code and describes how to format the provided data and fit the dynamic occupancy models described in the second associated publication, for a quick overview.

format: HTML

en: Observation data

en: This file contains detection/non-detection data for the 12 amphibian species between 1999 and 2019 for 3 annual visits. Detectable denotes whether or not a visit j was made to pond i in year t. ObservedID gives a unique ID for the observer collecting the data during visit j to pond i in year t.

en: Structural connectivity data

en: This file contains structural connectivity data (three different metrics), calculated based on all existing ponds in each year, in long format. See Readme v2.0 for details. Required to run Model code 2.

en: Model code, description

en: This is the output of the R markdown file that provides JAGS model code and describes how to format the provided data and fit the dynamic occupancy models described in the associated publication, for a quick overview.

en: Readme

media_type: application/pdf

en: Description of methods and datasets. Version 1.

format: PDF

en: Readme, v 2.0

en: Description of methods and datasets. Version 2.0, including new datasets fro structural and potential population connectivity.

en:
In the canton of Aargau, hundreds of new ponds have been constructed since the 1990s to benefit declining amphibian populations. This dataset consists of monitoring data for all 12 pond-breeding amphibian species in the canton of Aargau from 1999 to 2019 in 856 ponds, and environmental variables that describe the ponds and the landscape surrounding the ponds. Species observation data is detection/non-detection data from repeat visits during survey years, during which all potentially suitable ponds in an area were surveyed. Environmental variables describing the ponds are whether the pond has been newly constructed since 1991 or not, pond age (if constructed), elevation a.s.l., the water surface area, and whether the water table fluctuates or not. Environmental variables describing the surroundings of the ponds are the percent area of forest within a circular buffer of radius 100m around the pond, the area of large (width ≥6m) roads within a circular buffer of radius 1km around the pond, as well as structural and potential population connectivity, quantified by three different metrics each.
The canton of Aargau is the owner of the monitoring data; the original datafile is only disclosed upon request and in consultation with the canton of Aargau.
The edited dataset contains cleaned observation data for the 12 amphibian species, as well as compiled and edited covariate data and code to fit dynamic occupancy models.

amphibians

display_name: amphibians

connectivity

display_name: connectivity

conservation

display_name: conservation

landscape

display_name: landscape

occupancy-models

display_name: occupancy-models

wetlands

display_name: wetlands

en: Amphibian observation and pond data (Aargau, Switzerland)


maintainer: Athanasios Nenes

en: sigma-w cloud-modeling cloud-droplets raclets supersaturation wolfgangpass

en: Predicted cloud droplet numbers (kappa=0.25) Weissfluhjoch

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.25 is assumed, which is the upper limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

mimetype: text/csv

en: Predicted cloud droplet numbers (kappa=0.1) Davos Wolfgang

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.1 is assumed, which is the lower limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

en: Cloud droplet properties were predicted between February 24 and March 8 2019 for the measurement site Davos Wolfgang (1630 m a.s.l., LON: 9.853594, LAT: 46.835577). Droplet calculations are carried out with the physically based aerosol activation parameterization of Morales and Nenes (2014), employing the “characteristic velocity” approach of Morales and Nenes (2010). Aerosol size distribution observations required to predict the cloud droplet numbers and maximum in-cloud supersaturation are obtained from a Scanning Mobility Particle Size Spectrometer (SMPS) instrument deployed at Davos Wolfgang (https://www.envidat.ch/dataset/aerosol-data-davos-wolfgang). The required vertical velocity measurements are derived from the wind Doppler Lidar (https://www.envidat.ch/dataset/lidar-wind-profiler-data) deployed at the same station and are extracted from the first bin of the instrument, being 200 m above ground level. The hygroscopic properties of the particles measured at Davos Wolfgang could not be estimated, owing to a lack of concurrent CCN measurements. As a sensitivity test, droplet calculations are performed assuming two different values of the aerosol hygroscopicity parameter, 0.1 and 0.25, based on the analysis carried out for Weissfluhjoch. Additional information can be found in Section 2.3 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

cloud-droplets

display_name: cloud-droplets

cloud-modeling

display_name: cloud-modeling

raclets

display_name: raclets

sigma-w

display_name: sigma-w

supersaturation

display_name: supersaturation

wolfgangpass

display_name: wolfgangpass

educ

en: Education, culture and sport

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: Predicted cloud droplet numbers Davos Wolfgang


maintainer: Stefan Klesse

en: tree-ring temperature-reconstruction paleoclimate mxd wood-anatomy

en: This dataset contains the mean chronologies of MXD and QWA of the relict and living wood material presented in Figure 3. It also contains the JJA temperature record of the Salekhard Meteo station.

en:
This dataset contains data presented in Figure 2 in the paper "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy".

Sample ID = Sample ID
group = living or relict wood material
Bulk wood density = volumetric measured density (kg / m^3)
Mean Tree Ring Density	= Density derived via X-ray densitometry (kg / m^3)
Cellulose_to_wood ratio = Holo-cellulose-to-wood ratio
Anatomical density = Area of cell wall / (area of cell wall + lumen area)

en: Data (Quantitative Wood Anatomy, Maximum Latewood Density, Volumetric Density, holo-cellulose-to-wood-ratio) used in the manuscript "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy". Wood samples stem from Larix sibirica collected in the Yamal region, northeastern Siberia, Russia. We investigated wood properties of living trees and subfossil wood buried in riverbank sediments, dated to approximately -2760 to -2600 BCE. Our goal was to evaluate the integrity of climate proxies in sub-fossil wood and develop practical methods to detect wood degradation when reconstructing Late Holocene and Common Era climate conditions using tree-ring data.

mxd

display_name: mxd

paleoclimate

display_name: paleoclimate

temperature-reconstruction

display_name: temperature-reconstruction

tree-ring

display_name: tree-ring

wood-anatomy

display_name: wood-anatomy

en: Quantitative Wood Anatomy and Maximum Latewood Density from Yamal peninsula


en: plants ecological-indicator-values landolt switzerland ecological-maps soil-ph soil-moisture soil-mapping

en: Predictors

en: Predictors generated and used in Descombes et al. (2020)

mimetype: application/zip

en: Description

en: Description of the predictors provided in this dataset

en:
Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we derived environmental data layers by mapping ecological indicator values (EIVs) in space by using a large set of environmental predictors in Switzerland.

This dataset contains the predictors (raster layers) generated and used in the following publication (Descombes et al. 2020). Only predictors for which we have the rights to share them are provided. Other datasets and predictors can be accessed via the original data provider. Details on the predictors and sources are fully described in the publication. The predictors are provided as GeoTIFF files, at 93 m spatial resolution and Mercator projection ("+proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"). The excel file (xlsx) provides a short description of the raster layers.

Paper Citation:

Descombes, P. et al. (2020). Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes. Ecography. (accepted)

ecological-indicator-values

display_name: ecological-indicator-values

ecological-maps

display_name: ecological-maps

landolt

display_name: landolt

plants

display_name: plants

soil-mapping

display_name: soil-mapping

soil-moisture

display_name: soil-moisture

soil-ph

display_name: soil-ph

switzerland

display_name: switzerland


maintainer: Johanna T. Malle

en: evapotranspiration high-resolution snow-simulation oshd clm5 land-cover forest-productivity land-use snow

en: Point-scale CLM5 simulation output of snow depth and snow water equivalent for 9 different simulation scenarios, each performed at 36 snow station locations across Switzerland. Please have a look at table A1 in the appendix of the linked publication for coordinates of the stations. Additional information on the setup, and the differences between simulation setups can also be found in the linked publication.

en:
12 gridded CLM5 simulations over the spatial extent of Switzerland:
- 1km, 0.25deg, 0.5deg
- 3 different meteorological forcings (Clim_CRU, CLIM_CRU*, CLIM_OSHD)
- 2 different land use forcings
each with the following outputs:
- daily snow depth (file SNOW_DEPTH.nc)
- monthly summed gross primary production (file FPSN_MONTH_SUM.nc)
- monthly summed evapotranspiration (file QFLX_EVAP_TOT_MONTH_SUM.nc).
Temporal extent of all simulations: 01/01/2015 - 31/12/2020.

en: Forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution. For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR) are provided.

en:
This dataset contains Community Land Model 5 (CLM5) simulation output over the spatial extent of Switzerland at different resolutions and based on a range of input datasets. It further contains land-use surface data used for the CLM5-simulations.

**Detailed description of the CLM5 simulation setup and the various input datasets can be found in the accompanying publication: https://doi.org/10.5194/egusphere-2023-1832.**

 CLM5 simulation output

This dataset includes gridded CLM5 simulations of snow depth, gross primary productivity (GPP) and evapotranspiration at different resolutions ( 1km, 0.25° and 0.5°) and based on a range of input datasets over the spatial extent of Switzerland (see folder *gridded_CLM5_simulations*). Additionally, point-scale CLM5 simulations of snow depth and snow-water-equivalent at 36 snow-station locations (see folder *point_scale_CLM5_simulations*) are included. Latitude, longitude and elevation for these station locations can be found in table A1 of the above-mentioned publication. All simulation output spans from 01/01/2015 - 31/12/2019.

Included CLM5 simulation results are based on 3 different meteorological forcing datasets:
* Clim_CRU: standard global dataset, we used the recent state-of-the-art standrd global dataset CRU-JRA (https://catalogue.ceda.ac.uk/uuid/aed8e269513f446fb1b5d2512bb387ad)

* Clim_CRU*: ClimCRU upraded by downscaling temperature data using a temperature lapse rate of -6.5K/1000m and a high-resolution DEM

* Clim_OSHD: highest level of detail, meteorological forcing generated according to methods developed by the Operational Snow Hydrological Service (OSHD), at 1km spatial and 1hour temporal resolution</li>

 Land-use surface data

This dataset further includes forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution (see folder *surface_landuse_datasets*). For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR), which includes a higher level of detail and is based on a more up-to-date land use datase, are provided. More details on these two datasets can be found in the above-mentioned publication.

evapotranspiration

display_name: evapotranspiration

forest-productivity

display_name: forest-productivity

high-resolution

display_name: high-resolution

land-cover

display_name: land-cover

land-use

display_name: land-use

oshd

display_name: oshd

snow

display_name: snow

snow-simulation

display_name: snow-simulation

en: Multi-resolution CLM5 simulations across Switzerland


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

en: Data plot of the forest station (LAB)

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

mimetype: application/pdf

en: Site photo of the forest station (LAB)

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

mimetype: image/jpeg

en: Field station data (LAF)

en: Data file.

en: Site photo of the field station (LAF)

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

en: Data plot of the field station (LAF)

en: Forest station data (LAB)

en: Site aerial photo (Lausanne)

en: Site aerial photo from both Lausanne stations. Source: Google. 2016. Site aerial photo from both Lausanne 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 Lausanne in Switzerland where one station is located within a natural mixed forest stand (LAB) with European beech (_Fagus sylvatica_; 160-170 yrs), European silver fir (_Abies alba_; 160-170 yrs) and Norway spruce (_Picea abies_; 160-170 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, LAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lausanne 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

educ

en: Education, culture and sport

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: Lausanne, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1996 onwards


en: review biogas manure switzerland bioenergy

en: Production de biogaz à partir d’engrais de ferme en Suisse

en: L'objectif de ce livre blanc est de fournir aux décideurs, aux administrations et aux parties prenantes les résultats de recherche les plus récents afin de promouvoir l'utilisation optimale de la bioénergie issue des engrais de ferme dans la transition énergétique suisse. A cette fin, les résultats du centre de compétence suisse pour la recherche en bioénergie - SCCER BIOSWEET - sont résumés et présentés dans un contexte plus large. Si rien d'autre n'est mentionné, les résultats se réfèrent à la Suisse et, dans le cas de la matière première, aux potentiels nationaux de biomasse.

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland


mosaic-snow-on-sea-ice-data

title_for_slug: mosaic-snow-on-sea-ice-data

en: arctic-sea-ice spatial-variability drifting-and-blowing-snow surface-mass-balance snow-distribution

en: SNOWPACK setup for MOSAiC

en:
 The zip file contains both input and output data as well as the model configuration as used in the submitted manuscript "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

The zip file contains 2 main folders:
* SNOWPACK_JGR_ALPHA1
* SNOWPACK_JGR_ALPHA3

In the SNOWPACK_JGR_ALPHA1 (reference "SP_R" simulation) and SNOWPACK_JGR_ALPHA3 (comparison "SP_C" scenario) folders you find the corresponding inputs, outputs and configuration as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each SNOWPACK_JGR_ALPHA/setup/io.ini file. The input data is already linked accordingly in each io.ini file.

To reproduce the results, download and compile the source code for the adjusted SNOWPACK model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/snowpack.git under the "snowpack_mosaic" branch. After installing, you can run the provided model setup uploaded here.

en: ALPINE3D setup for MOSAiC

en:
The zip file contains a folder structure that must be kept as it is in order to run the simulation in the current configuration.
The setup contains both input and output data as well as the model configuration as used in the submitted manuscript
"Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

The zip file contains 3 main folders:
* base_setup_files
* a3d_jgr_alpha1
* a3d_jgr_alpha3

The "base_setup_files" contains all input files that are necessary to run the reference (R) simulation ("a3d_jgr_alpha1" folder) and the comparison "C" scenario ("a3d_jgr_alpha3") folder. In the a3d_jgr_alpha1 and a3d_jgr_alpha3 folders you find the corresponding outputs as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each a3d_jgr_alphax/setup/io.ini file. The input data is already linked accordingly in each io.ini file.

a3d_jgr_alpha1 also contains the detailed snow profiles for each point along the transects.

To reproduce the results, download and compile the source code for the adjusted ALPINE3D model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/alpine3d.git under the "alpine3d_mosaic" branch. After installing, you can run the provided model setup uploaded here.

en:
Data accompanying David Wagners' Dissertation.
Covers model results and various input from ALPINE3D and SNOWPACK adjusted for sea ice during MOSAiC.

arctic-sea-ice

display_name: arctic-sea-ice

drifting-and-blowing-snow

display_name: drifting-and-blowing-snow

snow-distribution

display_name: snow-distribution

spatial-variability

display_name: spatial-variability

surface-mass-balance

display_name: surface-mass-balance

en: MOSAIC Snow on Sea Ice Data


maintainer: Axel Volkwein

en: trajectory field-data natural-hazards experiment mass-movements field-test rockfall field-tests experiments

en: Jumps and impacts

en: This table contains data of more than 2200 of each jumps and impacts of the test blocks on a grassy slope. It gives there durations in combination with acting accerlartions and the rotational speed of the blocks. The data were retrieved using the block internal accelerometer and rotation sensors. The combination of these data with the measurement from the local positioning system allows the deduction of jump lengths, slope gradient etc.

en: Overview of all tests

en:
This table gives an overview on all tests performed including
- block used
- start & end position
- number of jumps
- etc.
-

en: These data contain the point clouds obtained from laser scanning the test slope and the six test blocks used for the experiments. The coordinates of the slope are given in CH-1903 format. The coordinates of the block point clouds are kept in a lokal x/y/z coordinate system.

en: Block trajectories recorded from local positioning system

en: This file contains more than 80 rockfall trajectories projected onto the terrain, i.e. the positions of the single blocks over time during the single tests that were recorded by the local positioning system with about 10Hz. It contains the detected positions as well as a smoothened path (see Volkwein et al., Geosciences, 2018). The table also contains the derived velocities and accelerations along the slope (attention: these accelerations are the once that occur during an impact).

en:
In summer 2014, 6 rock blocks between 20 and 80kg have been thrown in total 111 times down a slope at the Swiss Oberalppass close to the village Tschamut. The slope was mainly covered by grass and its lower part was flat and large enough to provide natural runouts of the single trajectories.

An extensive measurement program has been set up to measure the block trajectories: With surveyor's instruments the slope and the six used rock blocks were scanned and the start and end positions of each test were recorded. During the single events two cameras filmed the trajectories. A special sensor device located within the blocks recorded the acting accelerations and rotational speeds over time. Further, the device emitted a Wifi signal that got detected from eight receivers around the slope. Based on this signal the block position has been recorded over time.

The dataset contains all data that were gathered through above field campaign.

experiment

display_name: experiment

experiments

display_name: experiments

field-data

display_name: field-data

field-test

display_name: field-test

field-tests

display_name: field-tests

mass-movements

display_name: mass-movements

natural-hazards

display_name: natural-hazards

rockfall

display_name: rockfall

trajectory

display_name: trajectory

en: Repetitive trajectory testing in Tschamut 2014


maintainer: Stephanie Mayer

en: snow-profiles snowpack snow-instability snow-stratigraphy failure-layer rutschblock snowpack-simulation

en: ReadMe

en: ReadMe file explaining data structure and content

en: Observed snow profiles

en: Observed snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding simulated profile in the "simulated_profiles" folder. One row corresponds to one observed snow layer. The content of the columns is described in Table 2 of the ReadMe file.

en: DAV data set: Properties of observed snow profiles and simulated failure layers

en:
For each profile pair from the DAV data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. The content of the columns is explained in Table 1 of the ReadMe file. Only those profile pairs which fulfilled predefined similarity criteria (column
"similarity_obs_sim" = 1) and which belonged to the stability classes "stable" and "unstable" (column "stability_class"
= 0 or 1) were used to train the RF model. Please note that for each of the two snow profiles with RB score 7 (profile
IDs 7228 and 9526), three additional layers were included in this data set to obtain a balanced set of training data (73
unstable and 73 stable profiles).

en: Simulated snow profiles

en: Simulated snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding observed profile in the "observed_profiles" folder. One row corresponds to one simulated snow layer. The content of the columns 1-7 is described in Table 3 of the ReadMe file. The remaining columns (8-31) contain all features that were used in the development of the RF model and are described in Table 1 of the ReadMe file.

en: SWISS data set: Properties of observed snow profiles and simulated failure layers

en: For each profile pair from the SWISS data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. Please note that only those profile pairs which fulfilled the similarity criteria (column similarity_obs_sim = 1, 121 profiles) were used to validate the RF model. The content of the columns is explained in Table 1 of the ReadMe file.

en:
This data set includes information on all observed and simulated snow profiles that were used to train and validate the
random forest model described in Mayer et al. (2022). The RF model was trained to assess snow instability from simulated snow stratigraphy. The data set contains observed snow profiles from the region of Davos (DAV subset, 512 profiles) and from all over Switzerland (SWISS subset, 230 profiles). For each observed snow profile, there is a corresponding simulated profile which was obtained using meteorological input data for the numerical snow cover model SNOWPACK. The information on the observed snow profile contains a Rutschblock test result including the depth of the failure interface. As part of the study described in Mayer et al. (2022), each observed snow profile was manually compared to its simulated counterpart and the simulated layer corresponding to the Rutschblock failure layer was identified.

The data are provided in the following form: one file each per observed and simulated snow profile (2x512 files DAV, 2x230 files SWISS), two files (1 file DAV, 1 file SWISS) containing the observed information on snow instability, the allocation between observed and simulated failure layer, and all features extracted from the simulated weak layers that were used to develop the RF model.

failure-layer

display_name: failure-layer

rutschblock

display_name: rutschblock

snow-instability

display_name: snow-instability

snow-profiles

display_name: snow-profiles

snow-stratigraphy

display_name: snow-stratigraphy

snowpack

display_name: snowpack

snowpack-simulation

display_name: snowpack-simulation

educ

en: Education, culture and sport

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: Observed and simulated snow profile data


tree-ring-laser-ablation-data

maintainer: Paula Ballikaya

title_for_slug: tree-ring-laser-ablation-data

en: dendrochronology air-pollution laser-ablation dendrochemistry tree-rings

en: Laser ablation data

en:
This dataset contains the values of several chemical elements (Mg, Al, Si, S, K, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, Tl, Pb, Bi) measured in the latewood of tree rings of Mongolian oak from Harbin, China, at a 5-year resolution. Due to the lack of a suitable reference material for wood, absolute concentration was not calculated, and the ratio between the chemical element and 13C was taken as proxy for the element signal.

In Harbin, one of the largest cities and most important industrial centers in northeastern China, air quality monitoring systems were built only by the end of 2015 to meet the national requirements. Thus, dendrochemical analyses could be used as a tool to complement for the lack of air quality data over longer periods of time, allowing for the reconstruction of the temporal trend of trace metals. Our main scopes were to: (a) assess the chemical composition of Quercus mongolica Fisch. ex Ledeb. tree rings from Harbin using a recently developed system of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), (b) identify the main chemical elements which
derived from air pollution and may be used as indicators over the period 1965–2020 in Harbin, while excluding those that were controlled by physiological processes in the tree, and (c) reconstruct the history of pollution in Harbin by comparing the tree-ring chemical composition of recent decades with that of previous decades, in trees growing in the highly polluted city of Harbin and in trees growing in a control site 90 km away from major pollution sources.

Briefly, the temporal trend of some elements was influenced by physiological factors, by environmental factors such as pollution, or influenced by both. Mg, K, Zn, Cu, Ni, Pb, As, Sr and Tl showed changes in pollution levels over time.

air-pollution

display_name: air-pollution

dendrochemistry

display_name: dendrochemistry

dendrochronology

display_name: dendrochronology

laser-ablation

display_name: laser-ablation

tree-rings

display_name: tree-rings

en: Tree-ring laser ablation data


maintainer: Matthias Haeni

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

en: Forest station data (CIB)

en: Data file.

en: Data plot of the field station (CIF)

en: Site photo of the field station (CIF)

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

en: Data plot of the forest station (CIB)

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

en: Site photo of the forest station (CIB)

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

en: Site aerial photo (Chironico)

en: Site aerial photo from both Chironico stations. Source: Google. 2016. Site aerial photo from both Chironico 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 Chironico in Switzerland where one station is located within a natural coniferous forest stand (CIB) with Norway spruce (_Picea abies_; 160-180 yrs) and European silver fir (_Abies alba_; 140-160 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CIF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Chironico 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: Chironico, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 2000 onwards


maintainer: Frank Techel

en: avalanche-forecasting verification avalanche-forecast avalanche-danger-level avalanche-bulletin

en: D_QC for forecasting seasons 2020/2021 - 2022/2023.

en: Data for the 2023/2024 forecasting season. It was added on 26 Aug 2024 by F. Techel.

en: D_QC for forecasting seasons 2001/2002 until 2019/2020.

en:
The data set contains the re-analyzed (or quality-checked) regional avalanche danger levels (D_QC) for Switzerland.

D_QC relates to dry-snow avalanche conditions only. Measuring the avalanche danger level D is not possible; forecast, nowcast, and hindcast assessments of D are judgments by humans interpreting data. However, combining several pieces of information indicating the same D, it can be expected that it is more likely that D_QC represents the avalanche conditions well.

For the **forecasting seasons 2001/2002 until 2019/2020**, the approach to obtain D_QC is described in detail in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

For the **forecasting seasons 2020/2021 and later**, D_QC is derived using the following approach:
1. *Combination of forecast (D_forecast) and nowcast (D_nowcast)*: If there was only one assessment available by an observer after a day in the field for a region, and if D_forecast = D_nowcast --> D_QC = D_forecast.
2. *Combination of several nowcast assessments (D_nowcast)*: If two (or more) observers agreed (or majority opinion) in their (independent) assessments of D_nowcast after a day in the field in the same warning region. --> D_QC = D_nowcast.
3. *Hindcast analysis (D_hindcast)*: In Switzerland, avalanche forecasters re-evaluate all situations when D = 4 (high) or D = 5 (very high) were either forecast, should have been forecast, or when forecasters discussed given one of these two levels but had not given them. Generally, two forecasters assess each situation. In these cases, D_QC = D_hindcast. The hindcast analysis, only available since the forecasting season 2020/2021, replaces what was step (2) in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

All other cases - ties in case of (1) or (2), no new information from the warning region in question, or if no D_hindcast was available - are not considered quality-checked, and are, thus, not contained in the data set.

In addition to D_QC, the file contains information on the elevation and aspect, where D_QC likely prevails.
- The indicated elevation is the mean of the respective elevations in (1), (2), or (3). At danger level 1 (low), when no elevation is indicated in the Swiss forecast, a value of 1500 m is set.
- For the four cardinal aspects N, E, S, and W, a value of 1 means that there was agreement that D was reached in this aspect and a value of 0 means that there was agreement that D was not reached in this aspect. Intermediate values correspondingly mark disagreements in the assessments.

avalanche-bulletin

display_name: avalanche-bulletin

avalanche-danger-level

display_name: avalanche-danger-level

avalanche-forecast

display_name: avalanche-forecast

avalanche-forecasting

display_name: avalanche-forecasting

verification

display_name: verification

educ

en: Education, culture and sport

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: Re-analyzed regional avalanche danger levels in Switzerland


en: ppgis survey outdoor-restoration traffic-noise landscape-perception

en: RESTORE WP4_Questionnaire_French.pdf

en: Questionnaire in French

en: RESTORE WP4_Questionnaire_Italian.pdf

en: Questionnaire in Italian

en: Variable list for article 2

en: Variable list for statistical analyses for article 1

en: Description of the sample stratification process for the invitation to participate in the survey

en: Processed data for article 2

en: Processed survey data for window view for article 1

en: Study protocol of the survey

en: Coding analysis second round for article 2

en: Coding analysis third round for article 2

en: Processed survey data of restorative locations for article 1

en: Processed data for coding analysis for article 2

en: Cleaned raw data from survey for article 1

en: Coding analysis first round for article 2

en: Raw data for article 2

en: RESTORE WP4_Questionnaire_German.pdf

en: Questionnaire in German

en:
This repository contains data related to the Swiss-wide survey of the RESTORE project. This project is a collaboration between the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and the Swiss Federal Laboratories for Materials Science & Technology (EMPA). It has received funding from the Swiss National Science Foundation. The objective of the RESTORE project was to assess the effects of green spaces as facilitators and noise as impediment to recover from stress in people's daily environments across Switzerland.
We conducted a nation-wide participatory mapping survey among Swiss residents to explore:
1.	The effects of greenness and noise exposure on psychological restoration when looking out of the window at home or when visiting nearby green spaces. It adopted a landscape approach to examine the interplay between environmental factors, individual perceptions, and personal traits – Scientific article 1
2.	The multiple aspects that constraint restoration when visiting nearby green spaces – Scientific article 2
Accordingly, this repository includes data and documentation for the following 2 scientific articles:
1.	Scientific article 1. “The role of greenness and road traffic noise for psychological restoration in everyday environments. A participatory mapping approach”. Landscape and Urban Planning, 2025
2.	Scientific article 2. “Perceived constraints for psychological restoration in nearby greenspaces. An exploratory and multi-dimensional approach”. Urban Forestry and Urban Greening, 2025

landscape-perception

display_name: landscape-perception

outdoor-restoration

display_name: outdoor-restoration

ppgis

display_name: ppgis

survey

display_name: survey

traffic-noise

display_name: traffic-noise

en: Swiss-wide survey on restorative places and road traffic noise


en: ash-dieback emerald-ash-borer cross-resistance invasive-species defense-chemistry fraxinus intraspecific-variation

en: Raw data-Publication cross-resistance in ash-New Phytologist

en:
What are the research data files about: Raw data on perfomance (dry weight, development and mortality) of emerald ash borer larvae used in published bioassays. Raw data on ash dieback leasion lenghts. Raw data on untargeted and targeted specialized ash metabolites.
Which methods were used: Bioassays in greenhouses and climate chambers to collect data on emerald ash borer and ash dieback perfomance. Phytochemical analyses on ash phloem for quantifiying specialized metabolites
When and where was the data created / extracted: Summer 2020-2021

en:
 What are the research data files about: Raw data on perfomance (dry weight, development and mortality) of emerald ash borer larvae used in published bioassays. Raw data on ash dieback leasion lenghts. Raw data on untargeted and targeted specialized ash metabolites.

Which methods were used: Bioassays in greenhouses and climate chambers to collect data on emerald ash borer and ash dieback perfomance. Phytochemical analyses on ash phloem for quantifiying specialized metabolites.

When and where was the data created / extracted: Summer 2020-2021

ash-dieback

display_name: ash-dieback

cross-resistance

display_name: cross-resistance

defense-chemistry

display_name: defense-chemistry

emerald-ash-borer

display_name: emerald-ash-borer

fraxinus

display_name: fraxinus

intraspecific-variation

display_name: intraspecific-variation

invasive-species

display_name: invasive-species

educ

en: Education, culture and sport

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: Raw data-Publication cross-resistance in ash - New Phytologist


en: aerodynamic-entrainment drifting-snow large-eddy-simulation snow-saltation splash saltation-parameterizations

en: Code and input files to reproduce the simulations in Melo et al. (2024), as well as the post-processing scripts used in the analysis.

en:
This dataset includes the necessary files to reproduce the results presented in Melo et al. (2024):
- code version used in the simulations (also available at the institutional [GitLab repository](https://gitlabext.wsl.ch/atmospheric-models/les-lsm) - tag 'r2024')
- input files to run the simulations
- post-processing scripts (MATLAB and FORTRAN)
- selected raw output files
- post-processed results (MATLAB data files).
 	**Note:** Direct model outputs are not provided because of their size, but they can be shared upon request. They can be reproduced by running the code. The post-processed results allow you to reproduce all figures in Melo et al. (2024).

aerodynamic-entrainment

display_name: aerodynamic-entrainment

drifting-snow

display_name: drifting-snow

large-eddy-simulation

display_name: large-eddy-simulation

saltation-parameterizations

display_name: saltation-parameterizations

snow-saltation

display_name: snow-saltation

splash

display_name: splash

en: Understanding snow saltation parameterizations - Reproducibility


maintainer: Frank Hagedorn

en: treeline-ecosystems plant-traits soil-nutrients plant-community biomass-dynamics climate-change

en: Data on soils, tree biomass, plant nutrients, rock mineralogy, climate of treeline ecosystems in Khibiny mountains, Kola Penninsula, Russia

en: Data on soil nutrients and charcteristics, tree and understory biomass, foliage nutrients, mineralogy, soil temperature and moisture along an elevation gradient from boreal forest to mountain tundra in teh Khibiny mountains (Kola Penninsula, Russia). Samples were taken along two gradients at 7 elevation level either under tree canopy (tree) and in open areas (open).

biomass-dynamics

display_name: biomass-dynamics

climate-change

display_name: climate-change

plant-community

display_name: plant-community

plant-traits

display_name: plant-traits

soil-nutrients

display_name: soil-nutrients

treeline-ecosystems

display_name: treeline-ecosystems


maintainer: Manuel R. Popp

en: species-observations plant-species vascular-plants testing photo

en:
Zipped directory containing approximately 5'600 photographs of vascular plants from the Swiss flora, taken at 153 sampling locations. Sampling locations were assigned a TypoCH habitat type.
Folder structure:
 - Each folder represents a plant population, defined by the same species, sampling date, and location.
 - Higher-level directories organize populations observed within the same sampling plot.
Naming convention:
Each image is names img_<index>_<plant organ>.jpg whereby <index> is the number of the photograph within the folder. For each observed population, images have consecutive integers as index. <plant organ> is a single letter indicating the depicted part(s) of the plant:
b = bark
i = inflorescense
f = infructescense
s = several parts
v = vegetative parts

en:
This data set contains roughly 5600 photographs of plants and plant parts from 153 sites recorded in all major biogeographic regions of Switzerland using smartphone cameras. Image names contain a letter referring to depicted plant parts: b = bark, i = inflorescence, f = infructescense, s = several parts, v = vegetative parts.
Photos are grouped in folders by observation (individual or population), i.e., photos in the same folder are of the same species, observed at the same time and sampling plot. At a higher organisational level, these folders are grouped by sampling plot (usually 3×3 m in open areas and 10×10 m in forests). The main folder contains metadata including taxon name, sampling time and location, as well as the TypoCH habitat type encoded as integers.

photo

display_name: photo

plant-species

display_name: plant-species

species-observations

display_name: species-observations

testing

display_name: testing

vascular-plants

display_name: vascular-plants

en: Photos of vegetative and reproductive parts of 560 vascular plant species taken in all biogeographic regions of Switzerland


maintainer: Yves Bühler

en: avalanche snow hazard-indication-mapping ramms release hazard-mapping

en: Potential Release  Area  NHESS

en: This folder contains the output of the different investigated algorithms plus the reference dataset, used for training and validation.

en: RAMMS simulations NHESS

en: Simulated maximum pressures for the scenarios frequent and extreme taking the forest layer into account

en:
This dataset contains the output and reference data published in the paper "Automated snow avalanche release area delineation - validation of existing algorithms and proposition of a new object-based approach for large scale hazard indication mapping" Yves Bühler, Daniel von Rickenbach, Andreas Stoffel, Stefan Margreth, Lukas Stoffel, Marc Christen (2018) Natural Hazards And Earth System Sciences.

Abstract:
Snow avalanche hazard is threatening people and infrastructure in all alpine regions with seasonal or permanent snow cover around the globe. Coping with this hazard is a big challenge and during the past centuries, different strategies were developed. Today, in Switzerland, experienced avalanche engineers produce hazard maps with a very high reliability based on avalanche cadastre information, terrain analysis, climatological datasets and numerical modelling of the flow dynamics for selected avalanche tracks that might affect settlements. However, for regions outside the considered settlement areas such area-wide hazard maps are not available mainly because of the too high cost, in Switzerland and in most mountain regions around the world. Therefore, hazard indication maps, even though they are less reliable and less detailed, are often the only spatial planning tool available. To produce meaningful and cost-effective avalanche hazard indication maps over large regions (regional to national scale), automated release area delineation has to be combined with volume estimations and state-of-the-art numerical avalanche simulations.

In this paper we validate existing potential release area (PRA) delineation algorithms, published in peer-reviewed journals, that are based on digital terrain models and their derivatives such as slope angle, aspect, roughness and curvature. For validation, we apply avalanche cadastre data from three different ski resorts in the vicinity of Davos, Switzerland, where experienced ski-patrol staff mapped most avalanches in detail since many years. After calculating the best fit input parameters for every tested algorithm, we compare their performance based on the reference datasets. Because all tested algorithms do not provide meaningful delineation between individual potential release areas (PRA), we propose a new algorithm based on object-based image analysis (OBIA). In combination with an automatic procedure to estimate the average release depth (d0), defining the avalanche release volume, this algorithm enables the numerical simulation of thousands of avalanches over large regions applying the well-established avalanche dynamics model RAMMS. We demonstrate this for the region of Davos for two hazard scenarios, frequent (10 – 30 years return period) and extreme (100 – 300 years return period). This approach opens the door for large scale avalanche hazard indication mapping in all regions where high quality and resolution digital terrain models and snow data are available.

avalanche

display_name: avalanche

hazard-indication-mapping

display_name: hazard-indication-mapping

hazard-mapping

display_name: hazard-mapping

ramms

display_name: ramms

release

display_name: release

snow

display_name: snow

en: Automated Avalanche Release Area (PRA) Delineation Davos