fr: entreprises commune emplois

de: gemeinde unternehmen beschaftigte

fr: Création de nouvelles entreprises et de nouveaux emplois, dès 2013 (turtle)

de: Unternehmensgründungen und neugeschaffene Arbeitsstellen nach Gemeinde ab 2013 (turtle)

fr: Création de nouvelles entreprises et de nouveaux emplois, dès 2013 (xlsx)

de: Unternehmensgründungen und neugeschaffene Arbeitsstellen nach Gemeinde ab 2013 (xlsx)

fr: Création de nouvelles entreprises et de nouveaux emplois, dès 2013 (json)

de: Unternehmensgründungen und neugeschaffene Arbeitsstellen nach Gemeinde ab 2013 (json)

fr: Création de nouvelles entreprises et de nouveaux emplois, dès 2013 (jsonld)

de: Unternehmensgründungen und neugeschaffene Arbeitsstellen nach Gemeinde ab 2013 (jsonld)

de: parquet

fr: Création de nouvelles entreprises et de nouveaux emplois, dès 2013 (parquet)

de: Unternehmensgründungen und neugeschaffene Arbeitsstellen nach Gemeinde ab 2013 (parquet)

de: csv

fr: Création de nouvelles entreprises et de nouveaux emplois, dès 2013 (csv)

de: Unternehmensgründungen und neugeschaffene Arbeitsstellen nach Gemeinde ab 2013 (csv)

fr: Création de nouvelles entreprises et de nouveaux emplois, dès 2013 (rdfxml)

de: Unternehmensgründungen und neugeschaffene Arbeitsstellen nach Gemeinde ab 2013 (rdfxml)

fr: Création de nouvelles entreprises et de nouveaux emplois, dès 2013 (n3)

de: Unternehmensgründungen und neugeschaffene Arbeitsstellen nach Gemeinde ab 2013 (n3)

fr: Création de nouvelles entreprises et de nouveaux emplois, dès 2013 (jsonl)

de: Unternehmensgründungen und neugeschaffene Arbeitsstellen nach Gemeinde ab 2013 (jsonl)

fr: Ce jeu de données présente les chiffres annuels des créations de nouvelles entreprises et de nouveaux emplois du canton de Fribourg selon la commune, depuis 2013. Ne font partie du relevé que les entreprises véritablement nouvelles - créées «ex nihilo» - et exerçant une activité économique marchande. Les entreprises issues d’une fusion, d’une dissolution ou d’une scission d’entreprises préexistantes ne sont pas considérées. Le secteur primaire est exclu des données.Les valeurs "GDPr" dans le jeu de données sont incluses pour être conforme à la nouvelle loi sur la protection des données (nLPD, effective depuis le 1er septembre 2023).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 Neugründungen von Unternehmen und Arbeitsplätzen im Kanton Freiburg nach Gemeinde, seit 2013. Zur Erhebung gehören nur wirklich neue - „ex nihilo“ gegründete - Unternehmen, die eine marktwirtschaftliche Tätigkeit ausüben. Unternehmen, die aus einer Fusion, Auflösung oder Spaltung bereits bestehender Unternehmen hervorgegangen sind, werden nicht berücksichtigt. Der Primärsektor ist aus den Daten ausgeschlossen.Die "GDPr"-Werte im Datensatz sind enthalten, um dem neuen Datenschutzgesetz (nLPD, wirksam seit dem 1. September 2023) zu entsprechen.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.

commune

display_name: commune

entreprises

display_name: entreprises

gemeinde

display_name: gemeinde

unternehmen

display_name: unternehmen

de: ssd

ssd

de: Amt für Statistik und Daten Freiburg


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

fr: age primes assurance-maladie sante

de: pramien krankenversicherung gesundheit alter

state: active

type: dataset

de: jsonl

media_type: application/json

fr: Primes moyennes dans l'assurance obligatoire des soins (AOS), dès 1996 (jsonl)

de: Mittlere Prämien in der obligatorischen Krankenpflegeversicherung (OKP), ab 1996 (jsonl)

format: JSON

fr: Primes moyennes dans l'assurance obligatoire des soins (AOS), dès 1996 (parquet)

de: Mittlere Prämien in der obligatorischen Krankenpflegeversicherung (OKP), ab 1996 (parquet)

format: PARQUET

de: xlsx

fr: Primes moyennes dans l'assurance obligatoire des soins (AOS), dès 1996 (xlsx)

de: Mittlere Prämien in der obligatorischen Krankenpflegeversicherung (OKP), ab 1996 (xlsx)

format: XLS

de: turtle

media_type: text/turtle

fr: Primes moyennes dans l'assurance obligatoire des soins (AOS), dès 1996 (turtle)

de: Mittlere Prämien in der obligatorischen Krankenpflegeversicherung (OKP), ab 1996 (turtle)

format: RDF Turtle

de: json

fr: Primes moyennes dans l'assurance obligatoire des soins (AOS), dès 1996 (json)

de: Mittlere Prämien in der obligatorischen Krankenpflegeversicherung (OKP), ab 1996 (json)

fr: Primes moyennes dans l'assurance obligatoire des soins (AOS), dès 1996 (n3)

de: Mittlere Prämien in der obligatorischen Krankenpflegeversicherung (OKP), ab 1996 (n3)

de: rdfxml

media_type: application/rdf+xml

fr: Primes moyennes dans l'assurance obligatoire des soins (AOS), dès 1996 (rdfxml)

de: Mittlere Prämien in der obligatorischen Krankenpflegeversicherung (OKP), ab 1996 (rdfxml)

format: RDF XML

media_type: text/csv

fr: Primes moyennes dans l'assurance obligatoire des soins (AOS), dès 1996 (csv)

de: Mittlere Prämien in der obligatorischen Krankenpflegeversicherung (OKP), ab 1996 (csv)

format: CSV

de: jsonld

fr: Primes moyennes dans l'assurance obligatoire des soins (AOS), dès 1996 (jsonld)

de: Mittlere Prämien in der obligatorischen Krankenpflegeversicherung (OKP), ab 1996 (jsonld)

format: JSON-LD

fr: Ce jeu de données présente la prime moyenne en francs par personne assurée dans l'assurance obligatoire des soins (AOS) dans le canton de Fribourg et dans l'ensemble de la Suisse, selon l'année et le groupe d'âge, depuis 1996.

de: Dieser Datensatz zeigt die mittlere Prämie pro versicherter Person in der obligatorischen Krankenpflegeversicherung (OKP) im Kanton Freiburg und in der gesamten Schweiz, nach Jahr und Altersgruppe, seit 1996.

age

display_name: age

alter

display_name: alter

assurance-maladie

display_name: assurance-maladie

gesundheit

display_name: gesundheit

krankenversicherung

display_name: krankenversicherung

pramien

display_name: pramien

primes

display_name: primes

sante

display_name: sante

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

fr: Service de la statistique et de la donnée Fribourg

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.

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.

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


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

fr: suffrage force-des-partis politique

de: politik parteistarke stimmen

author: ssd

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (turtle)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (turtle)

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (jsonld)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (jsonld)

de: jsonl

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (jsonl)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (jsonl)

de: geojson

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (geojson)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (geojson)

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (json)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (json)

de: csv

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (csv)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (csv)

de: parquet

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (parquet)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (parquet)

de: fgb

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (fgb)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (fgb)

format: OCTET

de: shp

media_type: application/zip

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (shp)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (shp)

format: ZIP

de: kml

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (kml)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (kml)

format: KML

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (xlsx)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (xlsx)

media_type: text/plain

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (ov2)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (ov2)

format: TXT

de: gpx

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (gpx)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (gpx)

format: GPX

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (rdfxml)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (rdfxml)

fr: Elections au Conseil national (suffrages des partis et force des partis depuis 1971: districts et communes) (n3)

de: Nationalratswahlen (Parteistimmen und Parteistärke seit 1971: Bezirke und Gemeinden) (n3)

fr: Ce jeu de données présente le suffrage des partis et la force des partis par commune (à l'état du 31.12.2023), depuis 1971. Aucune donnée n'est disponible pour les fribourgeois de l'étranger entre 1971 et 2011.

de: Dieser Datensatz zeigt die Parteistimmen und die Parteistärke nach Gemeinde (Stand 31.12.2023), seit 1971. Für die Freiburger im Ausland sind zwischen 1971 und 2011 keine Daten verfügbar.

force-des-partis

display_name: force-des-partis

parteistarke

display_name: parteistarke

politik

display_name: politik

politique

display_name: politique

stimmen

display_name: stimmen

suffrage

display_name: suffrage

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico


fr: situation-beneficiaire conjoncture-fribourgeoise situation-des-affaires prix-dachat exportations indicateurs-conjoncturels position-concurrentielle prix-de-vente capacite-technique

de: ausfuhren konjunkturindikatoren technische-kapazitaten wettbewerbsposition geschaftslage freiburger-konjunkturspiegel ertragslage verkaufspreise einkaufspreise

de: jsonl

fr: Indicateurs trimestriels pour l'ensemble de l'industrie, dès 1988 (jsonl)

de: Vierteljährliche Indikatoren für die Industrie insgesamt ab 1988 (jsonl)

de: xlsx

fr: Indicateurs trimestriels pour l'ensemble de l'industrie, dès 1988 (xlsx)

de: Vierteljährliche Indikatoren für die Industrie insgesamt ab 1988 (xlsx)

fr: Indicateurs trimestriels pour l'ensemble de l'industrie, dès 1988 (parquet)

de: Vierteljährliche Indikatoren für die Industrie insgesamt ab 1988 (parquet)

de: turtle

fr: Indicateurs trimestriels pour l'ensemble de l'industrie, dès 1988 (turtle)

de: Vierteljährliche Indikatoren für die Industrie insgesamt ab 1988 (turtle)

de: jsonld

fr: Indicateurs trimestriels pour l'ensemble de l'industrie, dès 1988 (jsonld)

de: Vierteljährliche Indikatoren für die Industrie insgesamt ab 1988 (jsonld)

de: json

fr: Indicateurs trimestriels pour l'ensemble de l'industrie, dès 1988 (json)

de: Vierteljährliche Indikatoren für die Industrie insgesamt ab 1988 (json)

fr: Indicateurs trimestriels pour l'ensemble de l'industrie, dès 1988 (n3)

de: Vierteljährliche Indikatoren für die Industrie insgesamt ab 1988 (n3)

de: csv

fr: Indicateurs trimestriels pour l'ensemble de l'industrie, dès 1988 (csv)

de: Vierteljährliche Indikatoren für die Industrie insgesamt ab 1988 (csv)

de: rdfxml

fr: Indicateurs trimestriels pour l'ensemble de l'industrie, dès 1988 (rdfxml)

de: Vierteljährliche Indikatoren für die Industrie insgesamt ab 1988 (rdfxml)

fr: Ce jeu de données présente les réponses au questionnaire trimestriel de l'enquête conjoncturelle du KOF dans l'industrie manufacturière, du canton de Fribourg et de la Suisse, depuis 1988.

de: Dieser Datensatz enthält die Antworten auf den vierteljährlichen Fragebogen der KOF-Konjunkturumfrage in der verarbeitenden Industrie, im Kanton Freiburg und in der Schweiz, seit 1988.

ausfuhren

display_name: ausfuhren

capacite-technique

display_name: capacite-technique

conjoncture-fribourgeoise

display_name: conjoncture-fribourgeoise

einkaufspreise

display_name: einkaufspreise

ertragslage

display_name: ertragslage

exportations

display_name: exportations

freiburger-konjunkturspiegel

display_name: freiburger-konjunkturspiegel

geschaftslage

display_name: geschaftslage

indicateurs-conjoncturels

display_name: indicateurs-conjoncturels

konjunkturindikatoren

display_name: konjunkturindikatoren

position-concurrentielle

display_name: position-concurrentielle

prix-dachat

display_name: prix-dachat

prix-de-vente

display_name: prix-de-vente

situation-beneficiaire

display_name: situation-beneficiaire

situation-des-affaires

display_name: situation-des-affaires

technische-kapazitaten

display_name: technische-kapazitaten

verkaufspreise

display_name: verkaufspreise

wettbewerbsposition

display_name: wettbewerbsposition

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

de: ssd

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.

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: vacants batiments logements commune constructions

de: gemeinde leerstehende gebaude wohnungen bau

fr: Logements vacants selon la mise à disposition sur le marché et le nombre de pièces, dès 1995 (jsonld)

de: Leerstehende Wohnungen nach Art der Transaktion und Anzahl Zimmer ab 1995 (jsonld)

fr: Logements vacants selon la mise à disposition sur le marché et le nombre de pièces, dès 1995 (json)

de: Leerstehende Wohnungen nach Art der Transaktion und Anzahl Zimmer ab 1995 (json)

fr: Logements vacants selon la mise à disposition sur le marché et le nombre de pièces, dès 1995 (turtle)

de: Leerstehende Wohnungen nach Art der Transaktion und Anzahl Zimmer ab 1995 (turtle)

de: parquet

fr: Logements vacants selon la mise à disposition sur le marché et le nombre de pièces, dès 1995 (parquet)

de: Leerstehende Wohnungen nach Art der Transaktion und Anzahl Zimmer ab 1995 (parquet)

fr: Logements vacants selon la mise à disposition sur le marché et le nombre de pièces, dès 1995 (rdfxml)

de: Leerstehende Wohnungen nach Art der Transaktion und Anzahl Zimmer ab 1995 (rdfxml)

de: jsonl

fr: Logements vacants selon la mise à disposition sur le marché et le nombre de pièces, dès 1995 (jsonl)

de: Leerstehende Wohnungen nach Art der Transaktion und Anzahl Zimmer ab 1995 (jsonl)

fr: Logements vacants selon la mise à disposition sur le marché et le nombre de pièces, dès 1995 (n3)

de: Leerstehende Wohnungen nach Art der Transaktion und Anzahl Zimmer ab 1995 (n3)

de: xlsx

fr: Logements vacants selon la mise à disposition sur le marché et le nombre de pièces, dès 1995 (xlsx)

de: Leerstehende Wohnungen nach Art der Transaktion und Anzahl Zimmer ab 1995 (xlsx)

fr: Logements vacants selon la mise à disposition sur le marché et le nombre de pièces, dès 1995 (csv)

de: Leerstehende Wohnungen nach Art der Transaktion und Anzahl Zimmer ab 1995 (csv)

fr: Ce jeu de données présente les logements vacants, selon le type de transaction 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 enthält leer stehende Wohnungen nach Transaktionsart und Zimmeranzahl 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

commune

display_name: commune

constructions

display_name: constructions

gebaude

display_name: gebaude

gemeinde

display_name: gemeinde

leerstehende

display_name: leerstehende

logements

display_name: logements

vacants

display_name: vacants

wohnungen

display_name: wohnungen


fr: Population dite légale par groupe d'âge et par commune, dès 2010 (parquet)

de: Zivilrechtliche Bevölkerung nach Altersgruppe und Gemeinde ab 2010 (parquet)

de: json

fr: Population dite légale par groupe d'âge et par commune, dès 2010 (json)

de: Zivilrechtliche Bevölkerung nach Altersgruppe und Gemeinde ab 2010 (json)

de: turtle

fr: Population dite légale par groupe d'âge et par commune, dès 2010 (turtle)

de: Zivilrechtliche Bevölkerung nach Altersgruppe und Gemeinde ab 2010 (turtle)

de: csv

fr: Population dite légale par groupe d'âge et par commune, dès 2010 (csv)

de: Zivilrechtliche Bevölkerung nach Altersgruppe und Gemeinde ab 2010 (csv)

de: jsonld

fr: Population dite légale par groupe d'âge et par commune, dès 2010 (jsonld)

de: Zivilrechtliche Bevölkerung nach Altersgruppe und Gemeinde ab 2010 (jsonld)

fr: Population dite légale par groupe d'âge et par commune, dès 2010 (n3)

de: Zivilrechtliche Bevölkerung nach Altersgruppe und Gemeinde ab 2010 (n3)

fr: Population dite légale par groupe d'âge et par commune, dès 2010 (xlsx)

de: Zivilrechtliche Bevölkerung nach Altersgruppe und Gemeinde ab 2010 (xlsx)

de: rdfxml

fr: Population dite légale par groupe d'âge et par commune, dès 2010 (rdfxml)

de: Zivilrechtliche Bevölkerung nach Altersgruppe und Gemeinde ab 2010 (rdfxml)

fr: Population dite légale par groupe d'âge et par commune, dès 2010 (jsonl)

de: Zivilrechtliche Bevölkerung nach Altersgruppe und Gemeinde ab 2010 (jsonl)

fr: Ce jeu de données présente la population dite légale par groupe d'âge et par commune depuis 2010.

de: Dieser Datensatz zeigt die sogenannte gesetzliche Bevölkerung nach Altersgruppen und Gemeinden seit 2010.

altersgruppen

display_name: altersgruppen

groupe-dage

display_name: groupe-dage

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

de: ssd


windmessungen-cote-du-glaney

title_for_slug: windmessungen-cote-du-glaney

fr: energie mesures vent eolienne

de: messungen wind energie windenergie

fr: Mesures de vents - Côte du Glâney (json)

de: Windmessungen - Côte du Glâney (json)

fr: Mesures de vents - Côte du Glâney (rdfxml)

de: Windmessungen - Côte du Glâney (rdfxml)

fr: Mesures de vents - Côte du Glâney (n3)

de: Windmessungen - Côte du Glâney (n3)

fr: Mesures de vents - Côte du Glâney (turtle)

de: Windmessungen - Côte du Glâney (turtle)

de: parquet

fr: Mesures de vents - Côte du Glâney (parquet)

de: Windmessungen - Côte du Glâney (parquet)

de: jsonl

fr: Mesures de vents - Côte du Glâney (jsonl)

de: Windmessungen - Côte du Glâney (jsonl)

fr: Mesures de vents - Côte du Glâney (jsonld)

de: Windmessungen - Côte du Glâney (jsonld)

de: xlsx

fr: Mesures de vents - Côte du Glâney (xlsx)

de: Windmessungen - Côte du Glâney (xlsx)

fr: Mesures de vents - Côte du Glâney (csv)

de: Windmessungen - Côte du Glâney (csv)

fr:
Ce jeu de données fournit des mesures de vent enregistrées toutes les 10 minutes pour le périmètre « Côte du Glâney », situé dans le canton de Fribourg. Collectées dans le cadre du mandat du Grand Conseil pour la planification éolienne cantonale, ces données comprennent la vitesse et la direction du vent, la température, l'humidité relative à différentes hauteurs, ainsi que le potentiel de production éolienne (productible éolien). Ces informations sont essentielles pour la planification énergétique et sont mises à disposition en libre accès sur la plateforme Open Government Data du canton de Fribourg dans un souci de transparence et d'accès à l'information pour tous. Le périmètre « Côte du Glâney » se situe dans le district de la Glâne à environ 800 mètres d’altitude, à l’ouest et sud-ouest de la commune de Romont.L'heure
UTC (temps universel coordonné) sert de référence mondiale et ne change pas
avec les saisons. Pour obtenir l'heure locale, ajoutez 1 heure en hiver (UTC+1)
et 2 heures en été (UTC+2).Pour plus d'informations : [https://www.fr.ch/fribourg-vents/cote-du-glaney-avec-espace-didactique](https://www.fr.ch/fribourg-vents/cote-du-glaney-avec-espace-didactique)

de:
Dieses Datenset liefert Windmessungen, die alle 10 Minuten für das Gebiet „Côte du Glâney“ im Kanton Freiburg aufgezeichnet wurden. Erfasst im Rahmen des Auftrags des Grossen Rates zur kantonalen Windenergieplanung, enthalten diese Daten die Windgeschwindigkeit und -richtung, die Temperatur, die relative Luftfeuchtigkeit in verschiedenen Höhen sowie das Potenzial der Windenergieproduktion (Windenergieertrag). Diese Informationen sind wesentlich für die Energieplanung und werden im Sinne von Transparenz und offenem Zugang für alle auf der Open-Government-Data-Plattform des Kantons Freiburg frei zur Verfügung gestellt. Das Gebiet „Côte du Glâney“ befindet sich im Bezirk Glâne auf rund 800 Metern Höhe, westlich und südwestlich der Gemeinde Romont.
Die UTC-Zeit (koordinierte Weltzeit) dient als globale Referenz und ändert sich nicht mit den Jahreszeiten. Um die lokale Zeit zu erhalten, addiert man 1 Stunde im Winter (UTC+1) und 2 Stunden im Sommer (UTC+2).
Weitere Informationen: [https://www.fr.ch/de/freiburg-wind/cote-du-glaney-mit-didaktischem-bereich](https://www.fr.ch/de/freiburg-wind/cote-du-glaney-mit-didaktischem-bereich)

energie

display_name: energie

eolienne

display_name: eolienne

messungen

display_name: messungen

mesures

display_name: mesures

vent

display_name: vent

wind

display_name: wind

windenergie

display_name: windenergie

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

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.

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: Mesures de vents - Côte du Glâney

de: Windmessungen - Côte du Glâney


temperaturindikatoren

title_for_slug: temperaturindikatoren

fr: jours-tropicaux jours-dhiver degres-jours jours-de-gel jours-estivaux jours-de-chauffage

de: frosttage sommertage eistage hitzetage heizgradtage heiztage

de: turtle

fr: Indicateurs de température journalière, dès 1959 (turtle)

de: Tägliche Temperaturindikatoren (turtle)

de: jsonld

fr: Indicateurs de température journalière, dès 1959 (jsonld)

de: Tägliche Temperaturindikatoren (jsonld)

fr: Indicateurs de température journalière, dès 1959 (jsonl)

de: Tägliche Temperaturindikatoren (jsonl)

fr: Indicateurs de température journalière, dès 1959 (parquet)

fr: Indicateurs de température journalière, dès 1959 (n3)

de: Tägliche Temperaturindikatoren (n3)

fr: Indicateurs de température journalière, dès 1959 (xlsx)

de: Tägliche Temperaturindikatoren (xlsx)

de: csv

fr: Indicateurs de température journalière, dès 1959 (csv)

de: Tägliche Temperaturindikatoren (csv)

de: json

fr: Indicateurs de température journalière, dès 1959 (json)

de: Tägliche Temperaturindikatoren (json)

de: rdfxml

fr: Indicateurs de température journalière, dès 1959 (rdfxml)

de: Tägliche Temperaturindikatoren (rdfxml)

fr: Ce jeu de données présente le nombre de jours d'hiver, nombre de jours de gel, nombre de jours estivaux, nombre de jours tropicaux, nombre de jour de chauffage, nombre de degrés jours ainsi que ceux des normes 1961-1990 et 1991-2020, pour les stations de Fribourg/Grangeneuve, Payerne, Plaffeien et Le Moléson, dès 1965 (dès 1959 concernant le nombre de jours de chauffage et le nombre de degrés-jours).h: données homogénéisées 10000000 : valeurs numériques manquantes

de: Dieser Datensatz enthält die Anzahl Eistage, Anzahl Frosttage, Anzahl Sommertage, Anzahl Hitzetage, Anzahl Heiztage, Anzahl Heizgradtage sowie die Normen 1961-1990 und 1991-2020 für die Stationen Freiburg/Grangeneuve, Payerne, Plaffeien und Le Moléson ab 1965 (ab 1959 für die Anzahl Heiztage und die Anzahl Heizgradtage).h: homogenisierte Daten10000000: fehlende numerische Werte

degres-jours

display_name: degres-jours

eistage

display_name: eistage

frosttage

display_name: frosttage

heizgradtage

display_name: heizgradtage

heiztage

display_name: heiztage

hitzetage

display_name: hitzetage

jours-de-chauffage

display_name: jours-de-chauffage

jours-de-gel

display_name: jours-de-gel

jours-dhiver

display_name: jours-dhiver

jours-estivaux

display_name: jours-estivaux

jours-tropicaux

display_name: jours-tropicaux

sommertage

display_name: sommertage

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

de: ssd


fr: pluie precipitations quantite-de-pluie

de: regen regenmenge niederschlage

fr: Quantité de précipitations, dès 1959 (jsonld)

de: Niederschlagsmenge ab 1959 (jsonld)

fr: Quantité de précipitations, dès 1959 (turtle)

de: Niederschlagsmenge ab 1959 (turtle)

fr: Quantité de précipitations, dès 1959 (rdfxml)

de: Niederschlagsmenge ab 1959 (rdfxml)

de: jsonl

fr: Quantité de précipitations, dès 1959 (jsonl)

de: Niederschlagsmenge ab 1959 (jsonl)

de: xlsx

fr: Quantité de précipitations, dès 1959 (xlsx)

de: Niederschlagsmenge ab 1959 (xlsx)

fr: Quantité de précipitations, dès 1959 (csv)

de: Niederschlagsmenge ab 1959 (csv)

fr: Quantité de précipitations, dès 1959 (n3)

de: Niederschlagsmenge ab 1959 (n3)

de: parquet

fr: Quantité de précipitations, dès 1959 (parquet)

de: Niederschlagsmenge ab 1959 (parquet)

fr: Quantité de précipitations, dès 1959 (json)

de: Niederschlagsmenge ab 1959 (json)

fr: Ce jeu de données présente les chiffres mensuels de la quantité de précipitations en mm, normes des précipitations 1961-1990, 1991-2020, écarts aux normes 1961-1990, 1991-2020, pour les stations de Fribourg/Grangeneuve (dès 1959), Payerne (dès 1964), Plaffeien (dès 1972) et Le Moléson (dès 1982).h: données homogénéisées10000000 : valeurs numériques manquantes

de: Dieser Datensatz enthält die monatlichen Zahlen der Niederschlagsmenge in mm, Niederschlagsnormen 1961-1990, 1991-2020, Abweichungen von den Normen 1961-1990, 1991-2020 für die Stationen Freiburg/Grangeneuve (ab 1959), Payerne (ab 1964), Plaffeien (ab 1972) und Le Moléson (ab 1982).h: homogenisierte Daten;10000000: fehlende numerische Werte

niederschlage

display_name: niederschlage

pluie

display_name: pluie

precipitations

display_name: precipitations

quantite-de-pluie

display_name: quantite-de-pluie

regen

display_name: regen

regenmenge

display_name: regenmenge

ssd

de: Amt für Statistik und Daten Freiburg

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: Quantité de précipitations, dès 1959

de: Niederschlagsmenge ab 1959


fr: enseignement public degre ecole commune

de: offentlich gemeinde schule unterricht stufe

de: rdfxml

fr: Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010 (rdfxml)

de: Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010 (rdfxml)

de: json

fr: Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010 (json)

de: Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010 (json)

de: csv

fr: Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010 (csv)

de: Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010 (csv)

de: jsonld

fr: Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010 (jsonld)

de: Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010 (jsonld)

fr: Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010 (n3)

de: Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010 (n3)

fr: Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010 (xlsx)

de: Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010 (xlsx)

fr: Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010 (jsonl)

de: Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010 (jsonl)

de: turtle

fr: Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010 (turtle)

de: Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010 (turtle)

fr: Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010 (parquet)

de: Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010 (parquet)

fr: Ce jeu de données présente les classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010.

de: Dieser Datensatz enthält Klassen der öffentlichen Schulen nach Schulstufe im Oktober ab 2010

commune

display_name: commune

degre

display_name: degre

ecole

display_name: ecole

enseignement

display_name: enseignement

gemeinde

display_name: gemeinde

offentlich

display_name: offentlich

public

display_name: public

schule

display_name: schule

stufe

display_name: stufe

unterricht

display_name: unterricht

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

de: ssd

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.


fr: voitures habitants

de: personenwagen einwohner

de: xlsx

fr: Voitures de tourisme pour 1000 habitants, dès 2009 (xlsx)

de: Personenwagen pro 1000 Einwohner ab 2009 (xlsx)

de: jsonl

fr: Voitures de tourisme pour 1000 habitants, dès 2009 (jsonl)

de: Personenwagen pro 1000 Einwohner ab 2009 (jsonl)

fr: Voitures de tourisme pour 1000 habitants, dès 2009 (csv)

de: Personenwagen pro 1000 Einwohner ab 2009 (csv)

de: rdfxml

fr: Voitures de tourisme pour 1000 habitants, dès 2009 (rdfxml)

de: Personenwagen pro 1000 Einwohner ab 2009 (rdfxml)

fr: Voitures de tourisme pour 1000 habitants, dès 2009 (n3)

de: Personenwagen pro 1000 Einwohner ab 2009 (n3)

fr: Voitures de tourisme pour 1000 habitants, dès 2009 (json)

de: Personenwagen pro 1000 Einwohner ab 2009 (json)

fr: Voitures de tourisme pour 1000 habitants, dès 2009 (turtle)

de: Personenwagen pro 1000 Einwohner ab 2009 (turtle)

fr: Voitures de tourisme pour 1000 habitants, dès 2009 (jsonld)

de: Personenwagen pro 1000 Einwohner ab 2009 (jsonld)

de: parquet

fr: Voitures de tourisme pour 1000 habitants, dès 2009 (parquet)

de: Personenwagen pro 1000 Einwohner ab 2009 (parquet)

fr:
Ce jeu de données présente les voitures de tourisme pour 1000 habitants, dès 2009.Il englobe les données (1) par canton, (2) par districts
et (3) par communes. Le filtrage s’effectue à l’aide des colonnes niveau géographique.

de: Dieser Datensatz zeigt Personenwagen pro 1000 Einwohner ab 2009.Er umfasst die Daten (1) nach Kanton, (2) nach Bezirken und (3) nach Gemeinden. Die Filterung erfolgt mithilfe der Spalten Geografische Ebene.

einwohner

display_name: einwohner

habitants

display_name: habitants

personenwagen

display_name: personenwagen

voitures

display_name: voitures

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

ssd

de: Amt für Statistik und Daten Freiburg

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: sante assureurs assurance-maladie

de: xlsx

fr: Assureurs de l'assurance obligatoire des soins (AOS), dès 2011 (xlsx)

de: Versicherer in der obligatorischen Krankenpflegeversicherung (OKP), ab 2011 (xlsx)

fr: Assureurs de l'assurance obligatoire des soins (AOS), dès 2011 (rdfxml)

de: Versicherer in der obligatorischen Krankenpflegeversicherung (OKP), ab 2011 (rdfxml)

de: jsonld

fr: Assureurs de l'assurance obligatoire des soins (AOS), dès 2011 (jsonld)

de: Versicherer in der obligatorischen Krankenpflegeversicherung (OKP), ab 2011 (jsonld)

fr: Assureurs de l'assurance obligatoire des soins (AOS), dès 2011 (jsonl)

de: Versicherer in der obligatorischen Krankenpflegeversicherung (OKP), ab 2011 (jsonl)

fr: Assureurs de l'assurance obligatoire des soins (AOS), dès 2011 (parquet)

de: Versicherer in der obligatorischen Krankenpflegeversicherung (OKP), ab 2011 (parquet)

fr: Assureurs de l'assurance obligatoire des soins (AOS), dès 2011 (n3)

de: Versicherer in der obligatorischen Krankenpflegeversicherung (OKP), ab 2011 (n3)

de: json

fr: Assureurs de l'assurance obligatoire des soins (AOS), dès 2011 (json)

de: Versicherer in der obligatorischen Krankenpflegeversicherung (OKP), ab 2011 (json)

de: turtle

fr: Assureurs de l'assurance obligatoire des soins (AOS), dès 2011 (turtle)

de: Versicherer in der obligatorischen Krankenpflegeversicherung (OKP), ab 2011 (turtle)

de: csv

fr: Assureurs de l'assurance obligatoire des soins (AOS), dès 2011 (csv)

de: Versicherer in der obligatorischen Krankenpflegeversicherung (OKP), ab 2011 (csv)

fr: Ce jeu de données comprend le nombre d'assureurs de l'assurance obligatoire des soins (AOS), en exercice dans le canton de Fribourg et dans l'ensemble de la Suisse

de: Dieser Datensatz umfasst die Anzahl der Krankenversicherer, die in Kanton Freiburg und in der gesamten Schweiz in der obligatorischen Krankenpflegeversicherung (OKP) tätig sind

assurance-maladie

display_name: assurance-maladie

assureurs

display_name: assureurs

gesundheit

display_name: gesundheit

krankenversicherung

display_name: krankenversicherung

sante

display_name: sante

versicherer

display_name: versicherer

heal

fr: Santé

de: Gesundheit

de: ssd


maintainer: Mountain Hydrology and Mass Movements

en: rockfall-fatalities natural-hazard-fatalities ice-avalanche-fatalities lightning-fatalities debris-flow-fatalities landslide-fatalities earthquake-fatalities flood-fatalities windstorm-fatalities

en: Natural hazard fatalities per year in Switzerland since 1946

en:
This dataset contains the number of fatalities due to flood, debris flow, landslide, rockfall, windstorm, lightning, ice avalanche, earthquake and other processes like roof avalanche or lacustrine tsunami for each year since 1946.
The following information is contained (by column and column title):

* year
* total number of hazard fatalities
* number of fatalities by flood (German: Hochwasser, Überschwemmung). Flood includes people drowned in flooded or inundated areas or carried away in streams under high-water conditions.
* number of fatalities by debris flow (German: Murgang).
* number of fatalities by landslide (German: Erdrutsch). Landslide includes people killed by landslides and hillslope debris flows (German: Hangmure).
* number of fatalities by rockfall (German: Steinschlag, Fels- und Bergsturz).
* number of fatalities by windstorm (German: Sturm). Windstorm includes people killed by falling objects or trees during very strong wind conditions and people who drowned in lakes because their boat capsized during such conditions.
* number of fatalities by lightning (German: Blitz).
* number of fatalities by ice avalanche (German: Eislawine).
* number of fatalities by earthquake (German: Erdbeben).
* number of fatalities by other processes like roof avalanche, lacustrine tsunami (German: andere Prozesse wie Dachlawine, Tsunami im See).

The data was collected based on newspaper research. For more information please refer to

_Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747-2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016._

The data collection is financed by the FOEN (with exception of the collection of the avalanche fatalities). The data contains the official statistics of the FOEN on fatalities due to flood, debris flow, landslide, rock fall and avalanche.

Restrictions: The data set is not complete. Only fatalities in or around settlements and on open transportation routes are included. More precisely, fatalities were not collected, when persons exposed themselves to a great danger on purpose. Or fatalities during leisure activities which are connected to a higher risk were not included (this includes e.g. canoeing or river surfing during flood, canyoning, mountaineering, climbing, walking or driving on a closed road).

Fatalities by avalanches are collected at the WSL Institute for Snow and Avalanche Research SLF. You can download the avalanche fatalities per hydrological year [here](https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936) and per calendar year [here](https://www.envidat.ch/dataset/avalanche-fatalities-per-calendar-year-since-1936). For a direct comparison with the fatalities presented here, please download the data set with the calendar years and do not consider fatalities in the backcountry (tour) or in terrain close to ski areas (offpiste).

debris-flow-fatalities

display_name: debris-flow-fatalities

earthquake-fatalities

display_name: earthquake-fatalities

flood-fatalities

display_name: flood-fatalities

ice-avalanche-fatalities

display_name: ice-avalanche-fatalities

landslide-fatalities

display_name: landslide-fatalities

lightning-fatalities

display_name: lightning-fatalities

natural-hazard-fatalities

display_name: natural-hazard-fatalities

rockfall-fatalities

display_name: rockfall-fatalities

windstorm-fatalities

display_name: windstorm-fatalities

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und 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: Number of natural hazard fatalities per year in Switzerland since 1946


chelsacanaryclim-climatologies

title_for_slug: chelsacanaryclim-climatologies

en: canaries precipitation air-temperature climate climatologies

en: CHELSACanaryClim-climatologies: Daily Mean Near-Surface Air Temperature

en:
Daily Mean Near-Surface Air Temperature
Files are provided as Cloud-Optimized GeoTIFFs (COGs) with standardized metadata.
Each COG encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

format: SERVICE

en: CHELSACanaryClim-climatologies: Daily Maximum Near-Surface Air Temperature

en:
Daily Maximum Near-Surface Air Temperature
Files are provided as Cloud-Optimized GeoTIFFs (COGs) with standardized metadata.
Each COG encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

en: CHELSACanaryClim-climatologies: Daily Minimum Near-Surface Air Temperature

en:
Daily Minimum Near-Surface Air Temperature
Files are provided as Cloud-Optimized GeoTIFFs (COGs) with standardized metadata.
Each COG encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

en:
Precipitation
Files are provided as Cloud-Optimized GeoTIFFs (COGs) with standardized metadata.
Each COG encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

en:
CHELSACanaryClim is a high-resolution, terrain-informed downscaling model developed specifically for the Canary Islands. It builds on the CHELSA v1.2 framework and integrates extensive local meteorological station data to refine temperature and precipitation estimates. The model incorporates high-resolution elevation data (down to 5 m), planetary boundary layer height, and ERA-Interim reanalysis inputs to simulate fine-scale climatic variation in mountainous island terrain.

CHELSACanaryClim-climatologies is a very-high resolution climate dataset generated with the CHELSACanaryClim downscaling model. It consists of monthly climatologies of air-temperatures and precipitation.

air-temperature

display_name: air-temperature

canaries

display_name: canaries

climate

display_name: climate

climatologies

display_name: climatologies

precipitation

display_name: precipitation

en: CHELSACanaryClim-climatologies


maintainer: EnviDat Support

en: force time-series switzerland sentinel-2 raster-processing remote-sensing

media_type: image/tiff

format: TIFF

en: Parameter file that defined all the parameters for processing the Sentinel-2 time series

en:
We processed Sentinel-2 image time series from 2017 to 2023 for Switzerland with the Software FORCE (Frantz 2019) on the basis of [Sentinel-2 images](https://envidat.ch/#/metadata/sentinel-2-imagery-of-switzerland). The respective parameter files can be found here: [Github](https://github.com/TLKoch/Sentinel-2_CH). All the image time series consist of several TB and therefore access will be granted upon request.
The available bands (in spatial reference system EPSG 3035) are the following:
Red, Green, Blue, NIR, Red-Edge-1, Red-Edge-2, Red-Edge-3, SWIR-1, SWIR-2
The available indices (in spatial reference system EPSG 3035) are the following:
CCI, CIRE, NDWI/NDMI, NDVI, EVI

 Processing
On the basis of processed Sentinel-2 images for the 14 Sentinel-2 tiles covering Switzerland (T31TGN, T32TLT, T32TMT, T32UMU, T32TNT, T32TPT, T31TGM, T32TLS, T32TMS, T32TNS, T32TPS, T32TLR, T32TMR, T32TNR), we processed the image time series further with FORCE v. 3.7.8-12.
We generated interpolated Sentinel-2 time series with a 5-day interval, corresponding to the theoretical revisit time of the Sentinel-2 satellites. It's important to note that the 5-day time series consist of interpolated and smoothed composites, not the original images. We used the radial basis convolutional filtering (RBF) available in the FORCE time series analysis (TSA) submodule (Schwieder et al. 2016). The RBF is similar to a spatial moving window average approach over time (Schwieder et al. 2016). We applied kernel width values of 10, 20, 30, and 50 days. We spectrally adjusted all the images to match Sentinel-2A, and we removed curve outliers and pixels that failed the quality checks for clouds and their shadows, snow, saturation, and limited illumination. The processed image time series are available in tiles of 30 by 30 km.

 Example images
Uploaded is an example of the index EVI for one of the generated 30 by 30 km tiles located around the city of Zürich. The values are multiplied by 10.000. The time series spans the month of July from 2018.

force

display_name: force

raster-processing

display_name: raster-processing

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

time-series

display_name: time-series

educ

en: Education, culture and sport

en: Sentinel-2 time series of Switzerland


en: insects biodiversity birds plant-insect-interaction urban-ecology insect-herbivores urban-biodiversity larvae

en:
We established our study sites in the cities of Basel, Lugano and Zurich. We characterised urban tree cover of each city using a rectangular grid with squares of 100x100 m. Within each square, we measured the area covered by urban trees using the European Union's Copernicus Land Monitoring Service information, Urban Atlas Street Tree Layer 2018 [https://doi.org/10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c](https://doi.org/10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c).

Then we assigned each square to three categories of urban tree cover that roughly represented the main types of urban uses:

1) low cover, industrial/commercial areas, 0-20% tree cover;
2) intermediate cover, residential areas, 20-40% tree cover;
3) high cover, urban parks and cemeteries, 40-60% tree cover.

We measured bird predation rate on the non-native insect larvae of the horse chestnut leaf miner (HCLM) Cameraria ohridella, an invasive moth that lays eggs and completes its larval and pupal development stages within the leaves of the horse chestnut Aesculus hippocastanus. The larvae feed on leaf fluids and tissue while creating mines within the leaf, which ultimately results in early leaf browning and loss of photosynthetic activity. We collected roughly ten twigs from each tree, including five twigs from the inner and five from the outer crown. Each twig carried 2-4 leaves, for a total of 3408 leaflets. Leaves were stored for ~10 weeks in a refrigerated room at 4 degrees C. We checked all HCLM mines using a stereo microscope and distinguished among open and close mines.
Open mines were further divided based on the opening hole, whether it was a small round exit hole of the larva or the parasitoid, or an irregularly shaped, large bird predation hole.

biodiversity

display_name: biodiversity

birds

display_name: birds

insect-herbivores

display_name: insect-herbivores

insects

display_name: insects

larvae

display_name: larvae

plant-insect-interaction

display_name: plant-insect-interaction

urban-biodiversity

display_name: urban-biodiversity

urban-ecology

display_name: urban-ecology

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: Urban bird predation on horse chestnut leaf miner Cameraria ohridella in three Swiss cities


dischmex-meteorological-measurements

maintainer: Rebecca Mott

title_for_slug: dischmex-meteorological-measurements

en: meteorological-data dischmex meteo-station dischma meteorological-measurements

en: Meteorological measurement 2014

en: data

mimetype: application/zip

en: Meteorological measurements 2014

media_type: application/pdf

en: Location of the meteorological stations

format: PDF

mimetype: application/pdf

en: Meteorological measurements 2016

en: Meteorological measurement 2015

en: Overview sensors

en:
Meteorological measurements recorded in the Dischma valley from 2014-2016. In 2014 and 2015 we used 11 mobile weather stations from sensorscope to record meteorological parameter in the upper Dischma valley in the closer surroundings of the Gletschboden area. The meteorological stations are eqiupped with at least air temperature/humidity, wind velocity and wind direction sensors. Some stations are additionally equipped with precipitation, shortwave radiation and snow surface temperature sensors.
Three transects were installed at different aspects and were equipped with air temperature/humidity and wind sensors. Transect 1 (stations 2-4) provides meteorological Information on an east-north-east facing slope at elevations ranging between 2100 m and 2500 m. Transect 2 (stations 5-7) provides meteorological Information on a south-west slope and transect 3 (stations 8-10) on a north-west slope. Station 1 is fully equipped with meteorological sensors (temperature/humidity, wind, IR, up and downwand shortwave radiation and precipitation).
In 2016, mobile stations from sensorscope were replaced with six permanent meteorological stations. Meteorological stations 1-3 are equipped with an air temperature/humidity sensor, two wind speed sensors, a wind direction sensor and an incoming and outgoing shortwave radiation sensor. Stations 4 and 6 are equipped with an air temperature/humidity sensor and a wind speed/direction sensor. Station 5 is a equipped with an air temperature/humidity sensor, a wind speed/direction sensor, a snow surface temperature sensor, an incoming and outgoing shortwave radiation sensor and an incoming longwave radiation sensor.

dischma

display_name: dischma

dischmex

display_name: dischmex

meteo-station

display_name: meteo-station

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

en: DISCHMEX - Meteorological measurements


maintainer: Michael Lehning

en: stable-water-isotopes paleoclimate sublimation snow latent-heat natural-tracer post-depositional-processes weissfluhjoch

en: Weather

en: Meteorological data, snow height measurement, and SNOWPACK simulations covering the different field campaigns.

en: Stable water isotopes in snow

en: Stable water isotopes in snow measurements

en:
Details on the data collected during the different field campaigns and available in this dataset.
Information on the sampling procedure of the snow isotopes samples.

en: Details about the different folders

en: Stable water isotopes in vapor

en:
Stable water isotopes in vapor measurements. Processed (calibrated) and raw data for February - June 2017. Raw data for January and February 2020.
For the time in between July 2017 and April 2020, raw vapor isotopic measurements are available, but no calibrations were performed during that time. For data delivery, please contact one of the authors.
This folder also contains the post-processing scripts for stable water isotopes in vapor measurements.

en:
Notice: Changes to the dataset are still possible. Please do not use this dataset until the final publication with a DOI. Contact the authors if you have questions about this.

This dataset contains measurements of stable water isotopes in snow and vapor on the Weissfluhjoch from different field campaigns (Winter 2017 (Trachsel, 2019), January 2020, December 2020, and March 2021 (Sadowski et al., 2022).
Snow profiles and surface samples are available at different frequencies for each campaign. Please see "Data_description.pdf" for details.

Scripts and SNOWPACK simulations used in (Trachsel, 2019) and (Sadowski et al., 2022) are also provided.

latent-heat

display_name: latent-heat

natural-tracer

display_name: natural-tracer

paleoclimate

display_name: paleoclimate

post-depositional-processes

display_name: post-depositional-processes

snow

display_name: snow

stable-water-isotopes

display_name: stable-water-isotopes

sublimation

display_name: sublimation

weissfluhjoch

display_name: weissfluhjoch

educ

en: Education, culture and sport

en: Stable Water Isotopes in snow and vapor on the Weissfluhjoch


historical-vegetation-height-model-nfi

maintainer: Mauro Marty

title_for_slug: historical-vegetation-height-model-nfi

en: historical nfi forest dsm photogrammetry vhm

en: 1985-1991 Vegetation Height Model

format: GeoTIFF

en: 1990-1998 Vegetation Height Model

en: 1998-2006 Vegetation Height Model

en: Description of available data

en: 1979-1985 Vegetation Height Model

en:
The main datasets available are 4 nationwide **Digital Surface Models (DSMs)** and corresponding **Vegetation Height Models (VHMs)** with a spatial resolution of 1 m.
The Vegetation Height Models are calculated by subtraction of a Digital Terrain Model (swissAlti3d version 2017, swisstopo) from the generated DSMs. DSMs were derived by image matching of **scanned historical images** (panchromatic 8-bit) acquired with a RC10 frame camera, in the context of the swisswide image acquisition campaigns of swisstopo.
Nationwide products could be generated for the **four epochs**
 1979-1985 / 1985-1991 / 1990-1998 / 1998-2006.
Additional information about successful image matching vs. interpolation of pixels and about the year of image acquisition are available in the corresponding files (**matched_area_xxxx_xxxx_binay.tif** and **meta_acquisition_year_xxxx_xxxx.json**, respectively).
To separate vegetation from non-vegetation areas a mask derived from a combination of information of the Topographic landscape model - TLM (swisstopo) and a NDVI layer was used and is supplied as **"TLM_mask.tif"**
Due to the occurrence of unrealistic vegetation height values caused by the failure of the image matching process (mainly overexposed images and clouds or very steep rocky terrain), pixel values > 60 m were set to NoData and < 0 m to 0.
All datasets are available in the Reference System **LV95 (EPSG: 2056) LN02 (EPSG: 5728)** and share the common **extent definition** (xmin ymin xmax ymax): 2480000 1070000 2840000 1300000

dsm

display_name: dsm

forest

display_name: forest

historical

display_name: historical

nfi

display_name: nfi

photogrammetry

display_name: photogrammetry

vhm

display_name: vhm

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: Historical Vegetation Height Model NFI


en: microct intercomparison specific-surface-area snow icecube

en: Statistics of samples

en: artificial_snow_data set

en: The file contains all micro-CT and IC measurements of the artificial snow data set. The data set was originally produced to investigate the influence of black carbon on SSA measurements.

en: SMP measurement files for snow types A, B, C and D.

en: IceCube and MicroCT data

en: The file contains all micro-CT and IC measurements for snow types A, B, C, D and E used in our study. All samples were processed (and stored) in a cold laboratory at -15°C.

en: TARTES simulations

en: Jupyter notebook with TARTES simulations.

en: Grain survey of snow particles

en: The file contains all measurements of the artificial particles for snow types A, B, C, D and E, including the artificial particle mass in the Petri dish.

en: The file contains all data for the plot in figure 1 of the co-located density and SSA measurement at Summit, Greenland in May 2015, conducted by Schneebeli, Proksch, Schmid.

en: Influence of black carbon on the measurement of the specific surface of snow with the near infrared method - Philipp Baumann

en: These experiments investigate different possible errors by measuring the specific surface area (SSA) of snow with the near infrared method. The influence of black carbon on this measurement was disproved, the theory was therefore validated. It shows that sunlight has no influence on the measurement with the IceCube. Wind drift snow as thin layer on the sample can increase the measured value of the specific surface by a few percent. This could be part of the error, observed in former measurements at SLF. As reference for the measured SSA values with the near infrared method, computer tomography was used to verify the SSA values.

en: The specific surface area (SSA) of different snow types were measured with the IceCube instrument and the Scanco Medical microCT 40. In addition, the snow particles created during the preparation of IceCube samples were counted. The difference in SSA between these instruments is explained by the formation of the surface particles. A numerical simulation using TARTES simulation support the observations.

icecube

display_name: icecube

intercomparison

display_name: intercomparison

microct

display_name: microct

specific-surface-area

display_name: specific-surface-area


en: red-list range-size europe conservation-priority endemic bryophytes rarity

en: This dataset provides data on the occurrence of 672 European bryophyte species in European countries or territories. All species which are considered threatened or near threatened according to the European Red List (Hodgetts et al. 2019) are included (553 species). Further, all species evaluated in the European Red List assessed as LC, DD, NE and EX, which at the same time are either endemic, near endemic or globally rare, are included (119 species). Therefore, the list contains not only all European bryophyte species that are threatened or near threatened, but also all species endemic or near endemic to Europe as well as all globally rare species occurring in Europe. For each of the 553 threatened or near threatened species, we provide a conservation a priority score which was calculated based the Red List status and the proportion of the European population of the global population or the global rarity of the species. For details on the prioritisation approach see Bisang et al. (2025).

bryophytes

display_name: bryophytes

conservation-priority

display_name: conservation-priority

endemic

display_name: endemic

europe

display_name: europe

range-size

display_name: range-size

rarity

display_name: rarity

red-list

display_name: red-list

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: Priority ranking for the conservation of all European bryophyte species - dataset


en: reservoirs climate-change water-demand water-supply water-scarcity

en: Water demand version 2 (corrected version)

en: Shapefile of 307 catchments in Switzerland

en: Shapefile of 307 catchments for which estimates of water supply, demand, and reservoir volumes are provided. The OBJECTID entry corresponds to the catchment ID which is used as a reference in the other datasets provided.

en: Water demand (deprecated)

en:
Warning: please use the corrected version 2, since this file contains errors for certain categories such as Livestock, Industry or Houshold.

Water demand estimates for the 307 medium-sized catchments for different categories for current and future conditions. One text file is provided per demand category. One column corresponds to one catchment (IDs compare to shapefile), The data are provided at monthly resolution in mm/d and can be converted to volumes by using the catchment area. E.g.
Q[mm/d] * catchment area [m²] /1000 = Q[m³/d]
or to obtain discharge in m³/s
Q[mm/d] * catchment area [m²]/1000/24/3600 = Q [m³/s].
Future irrigation and hydropower water demand are provided per climate model chain.

en: Water supply

en: Simulated discharge series for a reference period 1981-2010 and till the end of the century. Data are provided for 39 climate model chains and a control run based on the observed meteorology. Data are provided at daily resolution (mm/d).

en: Reservoir volumes

en: Reservoir volume for the 307 medium-sized catchments for different storage categories: natural lakes, artificial reservoirs, reservoirs for artificial snow production, drinking water reservoirs, and usable volumes of natural lakes. Unit: Mio m³. One column per catchment (see shapefile).

en:
The dataset Hydro-CH2018 reservoirs provides estimates of current and future water supply, water demand, and storage volumes for 307 medium-sized catchments in Switzerland.
Water supply for current (1981-2010) and future (2070-2099) climate conditions was simulated using the hydrological model PREVAH. For modeling current water supply, observed meteorological time series were used as input, while simulated meteorological time series derived from 39 model chains of the CH2018 initiative were used as an input for simulating future climate conditions.

Water demand was estimated for six categories:

- 1) Drinking water (households and tourism),
- 2) industry (second and third sector),
- 3) artificial snow production,
- 4) agriculture (irrigation and livestock feeding),
- 5) ecology (residual flows), and
- 6) hydropower.

Future estimates consider changes in demand related to population growth and changes in the hydrological conditions.
Storage volumes are provided for natural lakes (storage capacities and usable volumes), artificial reservoirs, reservoirs for artificial snow production, and drinking reservoirs.

A detailed description of the simulation and estimation procedures can be found in

*  Brunner, M.I., Björnsen Gurung, A., Zappa, M., Zekollari, H., Farinotti, D., Stähli, M., 2019. Present and future water scarcity in Switzerland: Potential for alleviation through reservoirs and lakes. Sci. Total Environ. 666, 1033–1047. https://doi.org/10.1016/j.scitotenv.2019.02.169.

This dataset contains the following information:

1.	Shapefile with the 307 medium-sized Swiss catchments.
2.   Textfiles with the water supply simulations for the control run and the 39 climate model chains (one file per chain) at daily resolution for the 307 catchments.
3.	Textfiles with the current and future demand estimates per category at monthly resolution for the 307 catchments.
4.	Textfiles with the storage volumes per category and catchment.

climate-change

display_name: climate-change

reservoirs

display_name: reservoirs

water-demand

display_name: water-demand

water-scarcity

display_name: water-scarcity

water-supply

display_name: water-supply

en: Hydro-CH2018 reservoirs


maintainer: Irene Cordero

en: soil land-use drought pesticide soil-nutrients heatwave soil-biodiversity

en: All soil data

en: Soil physicochemical characteristics

en:
Soil chemical and biological properties of soils affected by 10 different perturbations related with global change, applied individually or in combination. Greenhouse experiment. Perturbations applied to intact soil cores (15 cm diameter, 15 cm deep) collected in an extensively managed grassland on the WSL grounds in June 2023.
This dataset contains all data on which the publication below was based:
"Fioratti Junod M, Gombeer S, Holmes J, Zimmerman S, Rillig M, Risch AC and Cordero I. Soil functionality declines under multiple superimposed global change perturbations. XXXX "
Please, cite this publication together with the citation of the datafile.
Database includes:
Pot_ID: pot or soil core identifier.
Batch: numeric, 1 or 2.
Enzyme_plate: numeric, from 1 to 6.
Number_of_perturbations: numeric, from 0 to 10.
N_addition: binary. Yes = 1, No = 0.
P_addition: binary. Yes = 1, No = 0.
Defoliation: binary. Yes = 1, No = 0.
Trampling: binary. Yes = 1, No = 0.
Insecticide: binary. Yes = 1, No = 0.
Fungicide: binary. Yes = 1, No = 0.
Herbicide: binary. Yes = 1, No = 0.
Antibiotic: binary. Yes = 1, No = 0.
Drought: binary. Yes = 1, No = 0.
Heat_wave: binary. Yes = 1, No = 0.
Treatment: character. Description of the treatment, 15 levels.
SWC: soil water content. Numeric, unitless.
Green_biomass: green plant biomass. Numeric, g.
Brown_biomass: brown or dead plant biomass. Numeric, g.
Biomass_cut: plant biomass cut during defoliation treatments. Numeric, g.
CO2_flux_light: net CO2 flux under ambient light. Numeric, mg CO2 m-2 h-1.
CO2_flux_dark: ecosystem respiration. Numeric, mg CO2 m-2 h-1.
S: organic matter stabilisation factor (tea bag index). Numeric, unitless.
k: organic matter decomposition rate (tea bag index). Numeric, unitless.
DOC: dissolved organic carbon, mg Kg-1 dry soil.
IC: inorganic carbon, mg Kg-1 dry soil.
Ammonium_KCl: plant available ammonium, mg Kg-1 dry soil.
Nitrate_KCl: plant available nitrate, mg Kg-1 dry soil.
Phosphate: phosphate, mg Kg-1 dry soil.
MBC: microbial biomass carbon, mg Kg-1 dry soil.
MBN: microbial biomass nitrogen, mg Kg-1 dry soil.
PHO: phosphatase activity, nmol h-1 g-1 dry soil.
BG: β-glucosidase, nmol h-1 g-1 dry soil.
XYL: xylosidase, nmol h-1 g-1 dry soil.
CBH: cellobiohydrolase, nmol h-1 g-1 dry soil.
NAG: N-acetylglucosaminidase, nmol h-1 g-1 dry soil.
LAP: leucine aminopeptidase, nmol h-1 g-1 dry soil.
POX: phenoloxidase, nmol h-1 g-1 dry soil.
PER: peroxidase, nmol h-1 g-1 dry soil.
pH: soil pH, unitless
Water_stable_aggregates: water stable aggregates, %
Surface_infiltration_time: water surface infiltration time, s.

drought

display_name: drought

heatwave

display_name: heatwave

land-use

display_name: land-use

pesticide

display_name: pesticide

soil

display_name: soil

soil-biodiversity

display_name: soil-biodiversity

soil-nutrients

display_name: soil-nutrients

en: Escalating effects of multiple perturbations on soil functionality


maintainer: Joan Casanelles Abella

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

en: Information on the study sites

en: For each site, IDs, city, coordinates, structure where trapnest was attahced and height of the trapnest is provided

en: Explanation data variables

en: Larval food composition

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

antwerp

display_name: antwerp

cavity-nesting-bees

display_name: cavity-nesting-bees

chelostoma-florisomne

display_name: chelostoma-florisomne

dna-metabarcoding

display_name: dna-metabarcoding

hylaeus-communis

display_name: hylaeus-communis

osmia-bicornis

display_name: osmia-bicornis

osmia-cornuta

display_name: osmia-cornuta

paris

display_name: paris

plant-pollinator-interactions

display_name: plant-pollinator-interactions

poznan

display_name: poznan

tartu

display_name: tartu

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

zurich

display_name: zurich

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


en: community-assembly beta-diversity water-filled-tree-holes spatial-factors metacommunity functional-diversity environmental-factors taxonomic-diversity

en: This dataset contains values of taxonomic and functional β-diversity for each study site, along with their respective components: species richness difference vs. turnover (taxonomic), and functional richness difference vs. functional turnover (functional). Used to generate Fig. 1.

en: This dataset includes physical and environmental characteristics of water-filled tree holes (WTHs), such as water depth, height, opening size, hole origin and orientation, circumference at breast height, WTH type, and water volume. It also contains physico-chemical parameters, nutrient concentrations (ammonium, nitrogen, phosphate, sulfate, chloride), CDOM, Chlorophyll-A, turbidity, and dry organic matter (FPOM, CPOM, total).

en: This dataset provides the geographic coordinates (latitude and longitude) of each sampled water-filled tree hole (WTH) for the French forest plot.

en: This dataset contains trait information used to characterize the macroinvertebrates in our study, for the French forest plot. The dataset includes seven trait groups: aquatic developmental stage, maximum body size, locomotion, dispersal mode, respiration mode, feeding group, and cohort production interval. These trait groups are further divided into 32 distinct categories.

en: This dataset contains trait information used to characterize the macroinvertebrates in our study, for the Indian forest plot. The dataset includes seven trait groups: aquatic developmental stage, maximum body size, locomotion, dispersal mode, respiration mode, feeding group, and cohort production interval. These trait groups are further divided into 32 distinct categories.

en: This dataset provides the geographic coordinates (latitude and longitude) of each sampled water-filled tree hole (WTH) for the Indian forest plot.

en: Code to do the analysis and figures of the paper.

en: This dataset contains trait information used to characterize the macroinvertebrates in our study, for the Brazilian forest plot. The dataset includes seven trait groups: aquatic developmental stage, maximum body size, locomotion, dispersal mode, respiration mode, feeding group, and cohort production interval. These trait groups are further divided into 32 distinct categories.

en: This dataset describes the animal community composition sampled from 35 water-filled tree holes (WTHs) per site. It includes abundance and taxonomic identification (to morphospecies level) of aquatic macroinvertebrates and Chordata.

en: This dataset includes results from variation partitioning analysis used to assess the relative contributions of environmental and spatial factors to taxonomic and functional β-diversity and their components across biogeographic regions. It contains site-level values for pure and shared effects of predictors. Used to generate Fig_2.

en: This dataset provides the geographic coordinates (latitude and longitude) of each sampled water-filled tree hole (WTH) for the Brazilian forest plot.

en: This Excel file contains metadata that provides detailed information about all other files included here. It describes the ten accompanying datasets, outlining the type of data each contains, the variables used, their descriptions, and the units of measurement (where applicable).

en: These datasets and code support research on the community assemblage of aquatic macroinvertebrates in ephemeral microhabitats, specifically water-filled tree holes (WTH), in three biogeographically and climatically distinct old-growth forests: Temperate-Mediterranean (France), Neotropical (Brazil) and Palaeotropical (India). By integrating standardised biological sampling, detailed environmental measurements and spatial analysis, the dataset allows for an in-depth examination of how local habitat conditions and spatial configuration influence taxonomic and functional beta-diversity patterns. The data capture the variation in species composition and ecological traits in 35 WTH per forest site and are particularly important for understanding how environmental filtering and spatial processes shape beta-diversity in natural forest ecosystems.

beta-diversity

display_name: beta-diversity

community-assembly

display_name: community-assembly

environmental-factors

display_name: environmental-factors

functional-diversity

display_name: functional-diversity

metacommunity

display_name: metacommunity

spatial-factors

display_name: spatial-factors

taxonomic-diversity

display_name: taxonomic-diversity

water-filled-tree-holes

display_name: water-filled-tree-holes

en: Spatial factors shape taxonomic and functional beta-diversity in water-filled tree holes in different biogeographical regions


radiosondes

maintainer: Jörg Wieder

title_for_slug: radiosondes

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

en: Radiosond Template Files

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

en: Radiosond Sounding Files

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

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

holoballoon

display_name: holoballoon

pressure

display_name: pressure

raclets

display_name: raclets

radiosonde

display_name: radiosonde

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

wind

display_name: wind

wind-direction

display_name: wind-direction

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: Radiosondes


en: avalanche-danger danger-level avalanche-forecasting avalanche snow snow-instability

en: Read-me file

en: This read-me file contains the descriptions of the variables.

en: Field observations of snow instabilities

en:
This data set includes 589 snow profile observations including a rutschblock test, observations of signs of instability and an assessment of the local avalanche danger level, mainly recorded in the region of Davos (eastern Swiss Alps) during the winter seasons 2001-2002 to 2018-2019.

These data were analyzed and results published by Schweizer et al. (2021). They characterized the avalanche danger levels based on signs of instability (whumpfs, shooting cracks, recent avalanches), snow stability class and new snow height.

The data are provided in a csv file (589 records); the variables are described in the corresponding read-me file.

These data are the basis of the following publication: Schweizer, J., Mitterer, C., Reuter, B., and Techel, F.: Avalanche danger level characteristics from field observations of snow instability, Cryosphere, 15, 3293-3315, https://doi.org/10.5194/tc-15-3293-2021, 2021.

 Acknowlegements
Many of the data were recorded by SLF observers and staff members, among those Roland Meister, Stephan Harvey, Lukas Dürr, Marcia Phillips, Christine Pielmeier and Thomas Stucki. Their contribution is gratefully acknowledged.

avalanche

display_name: avalanche

avalanche-danger

display_name: avalanche-danger

avalanche-forecasting

display_name: avalanche-forecasting

danger-level

display_name: danger-level

snow

display_name: snow

snow-instability

display_name: snow-instability


maintainer: Ana Beatriz Pierri Daunt

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

en: 3. Use of any early concept.

en: 6. Protocol

en: 1. Frequency of early concepts.

en: 2. Frequency of additional concepts.

en: 4. Use of any additional concept.

en: 5. Planning steps.

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

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

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

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

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

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

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

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

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

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

decision-making

display_name: decision-making

ecosystem-services

display_name: ecosystem-services

green-infrastructure

display_name: green-infrastructure

landscape-ecology

display_name: landscape-ecology

landscape-perception

display_name: landscape-perception

landscape-planning

display_name: landscape-planning

landscape-services

display_name: landscape-services

literature-review

display_name: literature-review

multifunctionality

display_name: multifunctionality

pdfsearch

display_name: pdfsearch

planning

display_name: planning

resilience

display_name: resilience

sense-of-place

display_name: sense-of-place

socio-ecological-system

display_name: socio-ecological-system

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


en: alpine3d preferential-deposition tls lidar lee-side-flow-field

en: Dataset

en:
The data presented here corresponds to the publication "A Close-Ridge Small-Scale Atmospheric Flow Field and its Influence on Snow Accumulation" (Gerber et al., 2017), which investigates an eddy-like structure in the vicinity of the Sattelhorn in the Dischma valley (Davos Switzerland) and its influence on snow accumulation. The dataset contains:

* Alpine3D: Alpine3D snow depth grids (25 m resolution) for two simulations with and without snow redistribution.
* ARPS: 10 ARPS simulations (25 m horizontal resolution) with different model setups (wind direction, wind speed, stability).
* LiDAR: Processed LiDAR PPI (D2_PPI_1h) and RHI (D2_cross_1h) across the valley with a hourly resolution for the period 27 October 2015 01:00 - 29 October 2015c 21:00 (spatial resolution: 25 m).
* meteostations-dischma: Meteorological station data of two meteorological stations in the Dischma valley with 10 minute resolution for the period 28 October 2015 - 30 October 2015.
* TLS: Snow depth change data (m) between 28 October 2015 and 30 October 2015 based on terrestrial laser scans.

For more details about the simulation and observation data, see Gerber et al., 2017.

Publication: Gerber et al., 2017: A Close-Ridge Small-Scale Atmospheric Flow Field and its Influence on Snow Accumulation, submitted to JGR - Atmospheres.

lee-side-flow-field

display_name: lee-side-flow-field

lidar

display_name: lidar

preferential-deposition

display_name: preferential-deposition

tls

display_name: tls

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: DISCHMEX - Observations and simulations of the close-ridge small-scale atmospheric flow field and snow accumulation at Sattelhorn, Dischma valley, Davos, Switzerland.


maintainer: Avalanche Warning Service SLF

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

mimetype: text/csv

en:
Attention: this data is not updated after 2022 anymore.
This dataset contains the statistics on the number of avalanche fatalities per hydrological year in Switzerland. The data set commences with the beginning of the hydrological year 1936/37 on 01/10/1936. After the completion of a hydrological year, the new data is appended to the existing dataset.
The following information is contained (by column and column title):
 - hydrological year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)
The definition for these four categories as described in the guidelines to the avalanche accident database:
**tour**:
activities include back-country ski, snowboard or snow-shoe touring
**offpiste**:
access from ski area, generally from the top of a skilift with short hiking distances
**transportation.corridors** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people travelling or recreating on open or temporarily closed
transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)
**buildings** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people inside or just outside buildings, and workers on high alpine building
sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

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

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


en: uav photogrammetry dsm drone-data wingtra

en: Data Access

en:
- DSM 10cm resolution
- Orthomosaic 3cm resolution
- Agisoft Metashape Processing Report
- original RGB images

All generated products are also available as a cloud optimized geotiff.

en: We conducted four drone flights in Davos Wolfgang Arelen, in 2020/21 and 2022 to obtain data for the generation of DSMs and orthomosaics at a high resolution. The data was processed with the Agisoft Metashape Professional Software.

drone-data

display_name: drone-data

dsm

display_name: dsm

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

en: Photogrammetric Drone Data Wolfgang Arelen


radar-wind-profiler-davos-wolfgang

maintainer: Maxim Hervo

title_for_slug: radar-wind-profiler-davos-wolfgang

en: raclets radar wolfgangpass wind-direction wind-speed

en: Radar Wind Profiler Data

en: A Vaisala Lap3000 was installed at Davos Wolfgang to record wind profiles. The time format is number of days fom January 0, 0000 in UTC with a 10 minute resolution.

en: The RADAR wind profiler from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 2171 m above sea level to 11079 m, with a temporal resolution of 10 minutes.

raclets

display_name: raclets

radar

display_name: radar

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

wolfgangpass

display_name: wolfgangpass

en: RADAR Wind profiler Davos Wolfgang


rorcc

maintainer: Tobias Wechsler

title_for_slug: rorcc

en: environmental-flow hydropower design-discharge run-of-river-power-plants climate-change

en: RoRCC

en:
The dataset “RoRCC” consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
-	metadata on the RoR power plants under consideration
-	annual and seasonal production scenarios differentiated into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)
-	annual and seasonal production loss due to environmental flow requirements
-	annual and seasonal the technical increase potential (via design discharge optimisation)
-	annual and seasonal changes in the hydrological cycle for the three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)

en:
The dataset "RoRCC" consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
1) metadata on the RoR power plants under consideration, 2) annual and seasonal production potential scenarios under into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099), 3) annual and seasonal streamflow scenarios, 4) annual and seasonal production loss due to environmental flow requirements, 5) annual and seasonal the technical increase potential (via design discharge optimisation) and 6) annual and seasonal changes in the hydrological cycle.

climate-change

display_name: climate-change

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants

educ

en: Education, culture and sport


maintainer: Matthias Haeni

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

en: Site photo of the forest station (VSB)

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

mimetype: image/jpeg

en: Site aerial photo (Visp)

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

en: Data plot of the forest station (VSB)

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

en: Site photo of the field station (VSF)

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

en: Data plot of the field station (VSF)

en: Forest station data (VSB)

en: Data file.

en: Field station data (VSF)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Visp in Switzerland where one station is located within a natural mixed forest stand (VSB) with Scots pine (_Pinus sylvestris_; 40-80 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, VSF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Visp is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

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