en: vdv-736 siri-sx data incident-management transport-operator transport-company incident disruption line train bus passenger business-organisation ojp gtfs-sa

de: vdv-736 siri-sx daten ereignismanagement transportunternehmen verkehrsunternehmen ereignis storung fahrt linie bus zug passagier geschaftsorganisation ojp gtfs-sa

fr: vdv-736 siri-sx donnees management-des-evenements operateur-de-transport entreprise-de-transport evenement perturbation voyage ligne train autobus passager organisation-commerciale ojp gtfs-sa

it: vdv-736 siri-sx dati gestione-degli-eventi operatore-di-trasporto azienda-di-trasporto evento interruzione viaggio linea treno autobus passaggero organizzazione-aziendale ojp gtfs-sa

de: Cookbook (Documentation)

en: Cookbook (Documentation)

fr: Cookbook (Documentation)

it: Cookbook (Documentation)

de: Cookbook Geschäftsorganisationen mit Ereignisdaten für Infrastrukturobjekte

de: Cookbook

en: Cookbook

fr: Cookbook

it: Cookbook

en: Business organisations with event data

fr: Organisations commerciales avec données d’événements

it: Organizzazioni aziendali con dati di eventi

tran

en: Transport

it: Trasporti

de:
Die Liste umfasst alle Geschäftsorganisationen, für die Ereignisdaten zur Verfügung stehen.

Letztes Update: 17.02.2026

en:
The list contains all business organisations for which situation exchange data is available.

Last Update: 17.02.2026

fr:
La liste contient toutes les organisations commerciales pour lesquelles des données d'événements sont disponibles.

Dernière mise à jour : 17.02.2026

it:
L'elenco contiene tutte le organizzazioni aziendali per le quali sono disponibili dati sugli eventi.

Ultimo aggiornamento: 17.02.2026

identifier: GO SIRI-SX

autobus

display_name: autobus

azienda-di-trasporto

display_name: azienda-di-trasporto

bus

display_name: bus

business-organisation

display_name: business-organisation

data

display_name: data

daten

display_name: daten

dati

display_name: dati

disruption

display_name: disruption

donnees

display_name: donnees

entreprise-de-transport

display_name: entreprise-de-transport

ereignis

display_name: ereignis

ereignismanagement

display_name: ereignismanagement

evento

display_name: evento

geschaftsorganisation

display_name: geschaftsorganisation

gtfs-sa

display_name: gtfs-sa

interruzione

display_name: interruzione

ojp

display_name: ojp

operateur-de-transport

display_name: operateur-de-transport

operatore-di-trasporto

display_name: operatore-di-trasporto

organisation-commerciale

display_name: organisation-commerciale

organizzazione-aziendale

display_name: organizzazione-aziendale


$oid: OBSOLETE

en: behig vdv-736 siri-sx data event incident disruption business-organisation ojp gtfs-sa

de: behig vdv-736 siri-sx daten ereignisdaten transportunternehmen verkehrsunternehmen ereignis storung geschaftsorganisation ojp gtfs-sa

fr: behig vdv-736 siri-sx donnees evenement perturbation organitsation-commerciale ojp gtfs-sa

it: behig vdv-736 siri-sx donnees eventi organizzazione-aziendale ojp gtfs-sa

oevch

approval_status: approved

fr: Le Secrétariat des tâches du système d’information à la clientèle (SKI) publie pour le compte de l’OFT les données de l’ensemble des transports publics de Suisse.

en: Working on behalf of the Swiss Federal Office of Transport (FOT), the Customer Information System Tasks (SKI) business office publishes data on all public transport in Switzerland

de: Die Geschäftsstelle Systemaufgaben Kundeninformation (SKI) veröffentlicht im Auftrag des BAV die Daten des gesamten öffentlichen Verkehrs der Schweiz

it: Il servizio commerciale Attività di sistema Informazione alla clientela (SKI) pubblica, per conto dell’UFT, i dati di tutto il trasporto pubblico in Svizzera.

de: Geschäftsstelle Systemaufgaben Kundeninformation (SBB AG)

en: Business office of Customer Information System Tasks (SBB CFF FFS)

fr: Secrétariat des tâches du système d’information à la clientèle (CFF SA)

it: Servizio commerciale Attività di sistema Informazione alla clientela (FFS SA)

political_level: other

state: active

type: organization

schweizerische-bundesbahnen-sbb

capacity: public

de: Ereignismanagementsystem – EMS SKI

en: Event Management System - EMS SKI

fr: Système de gestion des événements – EMS SKI

it: Gestione degli avvenimenti: EMS SKI

en: Cookbook Geschäftsorganisationen mit Ereignisdaten für Infrastrukturobjekte

de: (Beta) Geschäftsorganisationen mit Ereignisdaten für Infrastrukturobjekte

en: (Beta) Business organisations with event data for infrastructure objects

fr: (Beta) Organisations commerciales avec données d’événements pour les objets d’infrastructure

it: (Beta) Organizzazioni aziendali con dati di eventi per oggetti infrastrutturali

type: dataset

key: guid

key: uri

value: Opentransportdata - DCAT Harvester

tran

de: Verkehr

fr: Transports

de:
Die Liste enthält alle Infrastrukturobjekte, für welche Geschäftsorganisationen Ereignisdaten zur Verfügung stellen.

Letztes Update: 10.01.2025

en:
The list contains all infrastructure objects for which business organisations provide event data.

Last Update: 10.01.2025

fr:
La liste contient tous les objets d'infrastructure pour lesquels les organisations commerciales mettent à disposition des données d'événement.

Dernière mise à jour: 10.01.2025

it:
L'elenco contiene tutti gli oggetti dell'infrastruttura per i quali le organizzazioni aziendali forniscono dati sugli eventi.

Ultimo aggiornamento: 10.01.2025

format: CSV

identifier: GO SIRI-SX Infra

media_type: text/csv

behig

display_name: behig

business-organisation

display_name: business-organisation

data

display_name: data

ereignisdaten

display_name: ereignisdaten

evenement

display_name: evenement

event

display_name: event

eventi

display_name: eventi

incident

display_name: incident

organitsation-commerciale

display_name: organitsation-commerciale

perturbation

display_name: perturbation

siri-sx

display_name: siri-sx

storung

display_name: storung

transportunternehmen

display_name: transportunternehmen

verkehrsunternehmen

display_name: verkehrsunternehmen


de:
Echtzeitdaten des öV Schweiz im SIRI-Format.

Für den Zugriff muss ein API-Key verwendet werden, siehe: https://opentransportdata.swiss/de/howto-access-apis

en:
Real-time data for public transport in Switzerland in SIRI format.

An API key must be used for access, see: https://opentransportdata.swiss/en/howto-access-apis

fr:
Données en temps réel des TP suisses au format SIRI.

Pour l'accès, une clé API doit être utilisée, voir : https://opentransportdata.swiss/fr/howto-access-apis

it:
Dati in tempo reale per il trasporto pubblico in Svizzera in formato SIRI.

Per l'accesso è necessario utilizzare una chiave API, vedi: https://opentransportdata.swiss/it/howto-access-apis

en: siri-et api delays forecast real-time-traffic

de: siri-et api verspatung prognose echtzeitverkehr

fr: siri-et api prognostic retard trafic-en-temps-reel

it: siri-et api previsione ritardotraffico-in-tempo-reale

de: Profil CH

en: Profil CH

fr: Profil CH

it: Profil CH

de: Howto: Access our APIs with API Keys

en: Howto: Access our APIs with API Keys

fr: Howto: Access our APIs with API Keys

it: Howto: Access our APIs with API Keys

spatial: Schweiz

de: SIRI Estimated Timetable

en: SIRI Estimated Timetable

fr: SIRI Estimated Timetable

it: SIRI Estimated Timetable

de: SIRI-ET

en: SIRI-ET

fr: SIRI-ET

it: SIRI-ET

format: XML

identifier: siri-et-api

media_type: application/xml

api

display_name: api

delays

display_name: delays

echtzeitverkehr

display_name: echtzeitverkehr

forecast

display_name: forecast

previsione

display_name: previsione

prognose

display_name: prognose

prognostic

display_name: prognostic

real-time-traffic

display_name: real-time-traffic

retard

display_name: retard

ritardotraffico-in-tempo-reale

display_name: ritardotraffico-in-tempo-reale

siri-et

display_name: siri-et

trafic-en-temps-reel

display_name: trafic-en-temps-reel

verspatung

display_name: verspatung


de:
Der tagesaktuelle Betriebsfahrplan als SIRI.

Für den Zugriff muss ein API-Key verwendet werden, siehe: https://opentransportdata.swiss/de/howto-access-apis

en:
The daily updated operating timetable as SIRI.

An API key must be used for access, see: https://opentransportdata.swiss/en/howto-access-apis

fr:
L'horaire d'exploitation actualisé quotidiennement sous forme de SIRI.

Pour l'accès, une clé API doit être utilisée, voir : https://opentransportdata.swiss/fr/howto-access-apis

it:
L'orario di servizio aggiornato quotidianamente come SIRI.

Per l'accesso è necessario utilizzare una chiave API, vedi: https://opentransportdata.swiss/it/howto-access-apis

en: siri-pt day-timetable

de: siri-pt tagesfahrplan

fr: siri-pt horaire-journalier

it: siri-pt orario-giornaliero

de: Cookbook (Documentation)

en: Cookbook (Documentation)

fr: Cookbook (Documentation)

it: Cookbook (Documentation)

de: SIRI Planned Timetable

en: SIRI Planned Timetable

fr: SIRI Planned Timetable

it: SIRI Planned Timetable

de: SIRI-PT

en: SIRI-PT

fr: SIRI-PT

it: SIRI-PT

identifier: siri-pt-api

day-timetable

display_name: day-timetable

horaire-journalier

display_name: horaire-journalier

orario-giornaliero

display_name: orario-giornaliero

siri-pt

display_name: siri-pt

tagesfahrplan

display_name: tagesfahrplan


geschaftsorganisationen

de:
#2026-06-30-DECOMMISSIONED

**WICHTIG: Dieser Datensatz wird per 30. Juni 2026 eingestellt, bitte verwenden Sie die neue Version dieses Datensatzes auf**
https://data.opentransportdata.swiss/dataset/business-organisation-v2

Die Geschäftsorganisationen stellen eine organisatorische Strukturierung der Transportunternehmen nach abrechnungstechnischen und kundeninformativen Merkmalen dar.

Die Geschäftsorganisationen werden über ihre Swiss Business Organisation ID (SBOID) identifiziert. Der Datensatz enthält zudem die Swiss Administration ID (SAID), welche Teil der SBOID ist, und für definierte Anwendungsfälle (z.B. Swiss Journey ID) genutzt werden kann.

Der Datensatz enthält die folgenden Ausprägungen:

- "actual-date": Datensätze, die am aktuellen Tag (heute) gelten.

- "full": alle Datensätze für sämtliche Gültigkeits-Zeiten (vergangene und zukünftige).

- "future-timetable": Datensätze, die im kommenden Fahrplanjahr gültig sein werden - Achtung: Dieser Datensatz wird im Laufe von 2026 ausser Betrieb genommen.

- "timetable-years": Datensätze, die im aktuellen und im kommenden Fahrplanjahr gültig sind.

en:
#2026-06-30-DECOMMISSIONED

**IMPORTANT: This dataset will be discontinued on Juni 30, 2026. Please use the new version of this data set available on**
https://data.opentransportdata.swiss/dataset/business-organisation-v2

The business organisations represent an organisational structuring of the transport companies according to billing and customer information characteristics.

The business organisations are identified by their Swiss Business Organisation ID (SBOID). The data set also contains the Swiss Administration ID (SAID), which is part of the SBOID and can be used for defined use cases (e.g. Swiss Journey ID).

The data sets contains the following characteristics:

- ‘actual-date’: records that apply on the current day (today).

- ‘full’: all records for all validity periods (past and future).

- ‘future-timetable’: Data sets that will be valid for the coming timetable year – Please note: This data set will be taken out of service in the course of 2026.

- ‘timetable-years’: data sets that apply to the current and upcoming timetable year.

fr:
#2026-06-30-DECOMMISSIONED

**IMPORTANT: Ce jeu de données sera supprimé le 30 juin 2026. Veuillez utiliser la nouvelle version du jeu de données disponible sur**
https://data.opentransportdata.swiss/dataset/business-organisation-v2

Les organisations commerciales représentent une structuration organisationnelle des entreprises de transport selon des caractéristiques de facturation et d'information des clients.

Les organisations commerciales sont identifiées par leur Swiss Business Organisation ID (SBOID). L'ensemble de données contient en outre le Swiss Administration ID (SAID), qui fait partie du SBOID et peut être utilisé pour des cas d'application définis (p. ex. Swiss Journey ID).

Ce jeu de données contient les caractéristiques suivantes:

- «actual-date»: enregistrements valables à la date actuelle (aujourd’hui).

- «full»: tous les blocs de données pour toutes les périodes de validité (passées et futures).

- «future-timetable»: Bloc de données valables pour la prochaine année d’horaire – Attention: Ce bloc de données sera mis hors service dans le courant de l’année 2026.

- «timetable-years»: Blocs de données valables pour l’année d’horaire en cours et l’année d’horaire à venir.

it:
#2026-06-30-DECOMMISSIONED

**IMPORTANTE: questo set di dati verrà dismesso il 30 giugno 2026. Si prega di utilizzare la nuova versione di questo set di dati disponibile su**
https://data.opentransportdata.swiss/dataset/business-organisation-v2

Le organizzazioni commerciali rappresentano una struttura organizzativa delle aziende di trasporto in base alle caratteristiche di fatturazione e di informazione dei clienti.

Le organizzazioni commerciali sono identificate dal loro Swiss Business Organisation ID (SBOID). Il set di dati contiene anche lo Swiss Administration ID (SAID), che fa parte dello SBOID e può essere utilizzato per casi d'uso definiti (ad esempio, lo Swiss Journey ID).

Il record contiene le seguenti versioni:

- «actual-date»: record validi alla data corrente (oggi).

- «full»: tutti i record di dati per tutti i periodi di validità (passati e futuri).

- «future-timetable»: Record di dati che saranno validi nell’anno di orario successivo – Attenzione: Questo record di dati verrà messo fuori servizio nel corso del 2026.

- «timetable-years»: Record di dati validi nell’anno di orario in corso e in quello successivo.

en: proprietary data business-register swiss-business-organisation-id swiss-administration-id transport-operator transport-company business-organisation on-demand-bus train bus mobility-service-provider

de: proprietar embag daten geschaftsregister swiss-business-organisation-id swiss-administration-id transportunternehmen verkehrsunternehmen geschaftsorganisation on-demand-bus zug bus mobilitatsdienstleister

it: proprietario lmeca registro-delle-imprese id-organizzazione-aziendale-svizzera id-amministrazione-svizzera operatore-di-trasporto azienda-di-trasporto organizzazione-aziendale autobus-a-richiesta treno autobus fornitore-di-servizi-di-mobilita

oevch

fr: Le Secrétariat des tâches du système d’information à la clientèle (SKI) publie pour le compte de l’OFT les données de l’ensemble des transports publics de Suisse.

en: Working on behalf of the Swiss Federal Office of Transport (FOT), the Customer Information System Tasks (SKI) business office publishes data on all public transport in Switzerland

de: Die Geschäftsstelle Systemaufgaben Kundeninformation (SKI) veröffentlicht im Auftrag des BAV die Daten des gesamten öffentlichen Verkehrs der Schweiz

de: atlas (SKI Business Plattform)

en: atlas (SKI Business Platform)

fr: atlas (plateforme SKI Business)

it: atlas (piattaforma commerciale SKI)

de: Cookbook

en: Cookbook

fr: Cookbook

it: Cookbook

de: Cookbook - Geschäftsorganisationen mit Echtzeitdaten

de: Cookbook - Geschäftsorganisationen mit SIRI-SX

de: Geschäftsorganisationen

en: Business organisations

fr: Organisations commerciales

it: Organizzazioni aziendali

title_for_slug: geschaftsorganisationen

tran

en: Transport

it: Trasporti

format: ZIP

media_type: application/zip

autobus

display_name: autobus

autobus-a-richiesta

display_name: autobus-a-richiesta

azienda-di-trasporto

display_name: azienda-di-trasporto

bus

display_name: bus

bus-a-la-demande

display_name: bus-a-la-demande

business-organisation

display_name: business-organisation

business-register

display_name: business-register

data

display_name: data

daten

display_name: daten

donnees

display_name: donnees

embag

display_name: embag

entreprise-de-transport

display_name: entreprise-de-transport

fornitore-di-servizi-di-mobilita

display_name: fornitore-di-servizi-di-mobilita

geschaftsorganisation

display_name: geschaftsorganisation

geschaftsregister

display_name: geschaftsregister

id-amministrazione-svizzera

display_name: id-amministrazione-svizzera

id-de-la-administration-suisse

display_name: id-de-la-administration-suisse

id-organizzazione-aziendale-svizzera

display_name: id-organizzazione-aziendale-svizzera

lmeca

display_name: lmeca

lmeta

display_name: lmeta

mobilitatsdienstleister

display_name: mobilitatsdienstleister

mobility-service-provider

display_name: mobility-service-provider

on-demand-bus

display_name: on-demand-bus

operateur-de-transport

display_name: operateur-de-transport

operatore-di-trasporto

display_name: operatore-di-trasporto

organisation-commerciale

display_name: organisation-commerciale

organizzazione-aziendale

display_name: organizzazione-aziendale


geschaftsorganisationen-mit-echtzeit

de:
Die Liste enthält alle Geschäftsorganisationen, für die Echtzeitdaten zur Verfügung stehen oder in Zukunft stehen werden.

ACHTUNG:
Der Datensatz wurde per 01.06.2026 um eine zusätzliche Spalte erweitert. Diese neue Spalte "siriVDV" wird zwischen den Spalten «source» und «etAUS» eingefügt. Sie gibt an, ob die entsprechende Geschäftsorganisation die Daten im Format SIRI oder VDV einliefert.

en:
The list contains all business organisations for which realtime data is available or will be in the future.

PLEASE NOTE:
An additional column was be added to the data set as of 1 June 2026. This new ‘siriVDV’ column is inserted between the columns ‘source’ and ‘etAUS’. It indicates whether the business organisation in question delivers data in the SIRI or VDV format.

fr:
La liste contient toutes les organisations commerciales pour lesquelles des données en temps réel sont disponibles ou qui le seront à l’avenir.

ATTENTION:
Le jeu de données a été complété par une colonne supplémentaire au 1er juin 2026. Cette nouvelle colonne «siriVDV» sera insérée entre les colonnes «source» et «etAUS». Elle indique si l’organisation commerciale concernée livre les données au format SIRI ou VDV.

it:
L'elenco contiene tutte le organizzazioni aziendali per le quali sono disponibili dati in tempo reale o lo sarà in futuro.

ATTENZIONE:
Dal 1° giugno 2026, il record di dati è stato ampliato con un’ulteriore colonna. Questa nuova colonna «siriVDV» viene inserita tra le precedenti colonne «source» e «etAUS». Indica se la rispettiva organizzazione aziendale fornisce o meno i dati nel formato SIRI o VDV.

en: proprietary data business-register swiss-business-organisation-id swiss-administration-id transport-operator transport-company business-organisation real-time on-demand-bus train bus mobility-service-provider

de: proprietar embag daten geschaftsregister swiss-business-organisation-id swiss-administration-id transportunternehmen verkehrsunternehmen geschaftsorganisation echtzeit on-demand-bus zug bus mobilitatsdienstleister

it: proprietario lmeca dati registro-delle-imprese id-organizzazione-aziendale-svizzera id-amministrazione-svizzera operatore-di-trasporto azienda-di-trasporto organizzazione-aziendale tempo-reale autobus-a-richiesta treno autobus fornitore-di-servizi-di-mobilita

oevch

it: Il servizio commerciale Attività di sistema Informazione alla clientela (SKI) pubblica, per conto dell’UFT, i dati di tutto il trasporto pubblico in Svizzera.

de: Geschäftsstelle Systemaufgaben Kundeninformation (SBB AG)

en: Business office of Customer Information System Tasks (SBB CFF FFS)

fr: Secrétariat des tâches du système d’information à la clientèle (CFF SA)

it: Servizio commerciale Attività di sistema Informazione alla clientela (FFS SA)

de: Ereignismanagementsystem – EMS SKI

en: Event Management System - EMS SKI

fr: Système de gestion des événements – EMS SKI

it: Gestione degli avvenimenti: EMS SKI

en: Cookbook - Geschäftsorganisationen mit Echtzeitdaten

en: Business organisations with realtime data

fr: Organisations commerciales avec données en temps réel

it: Organizzazioni aziendali con dati in tempo reale

title_for_slug: geschaftsorganisationen-mit-echtzeit

tran

de: Verkehr

fr: Transports

de:
Die Liste umfasst alle Geschäftsorganisationen, für die Echtzeitdaten zur Verfügung stehen oder in Zukunft stehen werden.

Letztes Update: 2026-07-03

en:
The list includes all business organisations for which real-time data is available or will be in the future.

Last Update: 2026-07-03

fr:
La liste comprend toutes les organisations commerciales pour lesquelles des données en temps réel sont disponibles ou qui le seront à l’avenir.

Dernière mise à jour : 2026-07-03

it:
L’elenco comprende tutte le organizzazioni aziendali per le quali sono disponibili dati in tempo reale o lo sarà in futuro.

Ultimo aggiornamento: 2026-07-03

it: Organizzazioni con dati in tempo reale

identifier: GO Realtime

autobus

display_name: autobus

autobus-a-richiesta

display_name: autobus-a-richiesta

azienda-di-trasporto

display_name: azienda-di-trasporto

bus

display_name: bus

bus-a-la-demande

display_name: bus-a-la-demande

business-organisation

display_name: business-organisation

business-register

display_name: business-register

data

display_name: data

daten

display_name: daten

dati

display_name: dati

donnees

display_name: donnees

echtzeit

display_name: echtzeit

embag

display_name: embag

prestataire-de-mobilite

display_name: prestataire-de-mobilite

proprietaire

display_name: proprietaire

proprietar

display_name: proprietar


name: Gesundheitsdirektion des Kantons Zürich, Kantonales Labor

de: Konzentrationsbereiche zur Trinkwasserqualität für verschiedene Analyten aus den im Auftrag der Wasserversorgungen durchgeführten Selbstkontrolluntersuchungen sowie amtlichen Untersuchungen in den Gemeinden des Kantons Zürich – im regulären Trinkwassernetz (ohne Notversorgung, Laufbrunnen und Ressourcen). Die Daten-Ressource 'Netzproben' enthält u. a. das Datum der Probenahme, die spezifische Bezeichnung des Analyten (z. B. Chlorothalonil "R471811"), die Bezeichnung der Verteilzone(n) der Gemeinde sowie den Konzentrationsbereich (dem der Messwert zugeordnet wurde). Die Daten-Ressource 'Bewertungskategorien' enthält die Kategorien der Konzentrationsbereiche pro Analyt sowie den Zeitraum, zu dem sie für die Qualitätsbewertung Gültigkeit haben. Die Messwerte aus den ergänzenden Selbstkontrolluntersuchungen durchgeführt durch externe Dienstleistungslaboratorien im Auftrag der Wasserversorgungen sind im Datensatz 'Qualität des Trinkwassers im Kanton Zürich ab 2020 (Selbstkontrolle der Wasserversorgungen)' enthalten (siehe Verwandte Datensätze).

de: trinkwasser pestizide wasserversorgung lebensmittel wasser schwellenwert pflanzenschutzmittel gesundheit verunreinigung gemeinden

gesundheitsdirektion-kanton-zuerich

de: Die Gesundheitsdirektion setzt sich ein für eine hochstehende, sichere und wirtschaftlich tragbare Gesundheitsversorgung, für qualitativ einwandfreie medizinische Dienstleistungen, Heilmittel, Lebensmittel und Gebrauchsgegenstände, für finanziell tragbare Krankenversicherungsprämien. Das Veterinärwesen zählt ebenfalls zu ihrem Aufgabenbereich.

de: Gesundheitsdirektion Kanton Zürich

political_level: canton

de: Trinkwasser

en: Trinkwasser

fr: Trinkwasser

it: Trinkwasser

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

de: Trinkwasserqualität der Wohngemeinden (Schweizerischer Verein des Gas- und Wasserfaches SVGW)

de: Trinkwasserqualität im Kanton Zürich nach Gemeinden und Verteilzonen

value: ZH-Kt Gesundheitsdirektion - DCAT Harvester

heal

de: Gesundheit

en: Health

fr: Santé

it: Salute

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

fr: Agriculture, pêche, sylviculture et alimentation

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

de: Kategorien von Konzentrationsbereichen pro Analyt zur Qualitätsbewertung. Variablen: 'analyt' = spezifische Bezeichnung des Indikators (z. B. Chlorothalonil "R471811"); 'kategorie' = Konzentrationsbereich von Messwerten; 'kategorie_sortierung' = Sortierung nach aufsteigender Konzentration; 'farbcode' = hexadezimaler Farbcode, der die Einfärbung der Kategorie in der Visualisierung des Kantonalen Labors bestimmt (siehe 'Trinkwasser' unter "Weitere Informationen"); 'start_datum' = Beginn der Gültigkeit des Konzentrationsbereichs; 'end_datum' = Ende der Gültigkeit des Konzentrationsbereichs; 'bemerkung' = Hinweise zum Grund der Änderung des Konzentrationsbereichs.

de: Netzproben der Trinkwasserqualität

gemeinden

display_name: gemeinden

gesundheit

display_name: gesundheit

lebensmittel

display_name: lebensmittel

pestizide

display_name: pestizide

pflanzenschutzmittel

display_name: pflanzenschutzmittel

schwellenwert

display_name: schwellenwert

trinkwasser

display_name: trinkwasser

verunreinigung

display_name: verunreinigung

wasser

display_name: wasser

wasserversorgung

display_name: wasserversorgung


de: Dieser Datensatz enthält die Web Analytics des Datenkatalogs des Kantons Zürich (www.zh.ch/daten). Die Daten zeigen, welche Datensätze (dataset) und Ressourcen (distribution) (siehe Definition in DCAP-AP CH, unten verlinkt) wie oft aufgerufen und besucht wurden. Die Aufrufe und Besuche von externen Webseiten, welche den Datenkatalog eingebunden haben, werden mitgezählt. Aus technischen Gründen werden nicht alle Zugriffe registriert (bei Verwendung von Werbeblockern z.B 'Ad-Blocker'). Wir beziehen die Daten von mehreren Matomo APIs. Datensätze und Ressourcen mit 0 Aufrufen/Besuchenden sind nicht ausgewiesen. Aufrufe über Metadatenkatalog wie opendata.swiss sind nicht ausgewiesen.

statistisches-amt-kanton-zuerich

de: Das Amt für Statistik und Daten umfasst das Kompetenzzentrum Daten des Kantons Zürich, organisiert, koordiniert und steuert die politische Teilhabe inkl. der Wahlen und Abstimmungen im Kanton und beobachtet die Entwicklung des Kantons mit statistischen Methoden. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Information und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.

de: Amt für Statistik und Daten Kanton Zürich

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

value: ZH-Kt Statistisches Amt - DCAT Harvester

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

fr: Gouvernement et secteur public

it: Governo e settore pubblico

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

it: Economia e finanze

de: Zeigt die Anzahl Klicks und Besuchende pro Datensatz und Tag.  'Datensatz' entspricht 'dataset' nach DCAP-AP CH.

de: Web Analytics auf Ebene Datensatz

de: Zeigt die Anzahl Klicks auf die 'Herunterladen' oder 'Konvertiere zu Excel' Schaltflächen und die Anzahl Besuchenden welche mindestens einen Klick auf die 'Herunterladen' oder 'Konvertiere zu Excel' Schaltfläche pro Ressource und Tag gemacht haben. 'Ressource' entspricht 'distribution' nach DCAP-AP CH. Zusätzlich wird die Anzahl Downloads (wie oft die Ressource aufgerufen wurde) ausgewiesen. In der Regel sollte die Anzahl Downloads immer höher oder gleich als die Anzahl Klicks auf die Schaltflächen im Datenkatalog sein. Da aber im Zeitraum von September 2023 bis heute aus nicht bekannten Gründen, nicht alle Zugriffe detektiert werden, sind die Zahlen zu den Downloads in diesem Zeitraum nicht abschliessend. Die Anzahl Downloads von Ressourcen, welche nicht auf unserem Webserver gespeichert sind, werden nicht gezählt und ist der Grund warum es bei den Anzahl Downloads zu leeren Werten kommen kann.

de: Web Analytics zu den Zugriffen auf Ebene Ressource

format: OCTET

de: Zeigt die Anzahl Klicks und Besuchende der Informationsseite der Ressourcen (Klick auf "Details anzeigen") pro Ressource und Tag. 'Ressource' entspricht 'distribution' nach DCAP-AP CH.

de: Web Analytics 'Details anzeigen' zu Ressourcen

de: Zeigt die Anzahl Klicks und Besuchende pro verwandten Datensatz und Tag. 'Datensatz' entspricht 'dataset' nach DCAP-AP CH. Die Merkmale 'datensatz_id' und 'datensatz_titel' zeigen, von welchem Datensatz aus der Klick auf den verwandten Datensatz erfolgte.

de: Web Analytics auf Ebene verwandter Datensatz

statistik

display_name: statistik


pflanzensorten-in-der-schweiz

de:
Der Datensatz enthält Informationen zu in der Schweiz zugelassenen oder durch Sortenschutz (PVR) geschützten Pflanzensorten, die im nationalen Sortenkatalog (NLI) aufgeführt sind. Erfasst werden Sortenmerkmale, der Zulassungsstatus und die Schutzdauer. Die Daten dienen der Transparenz sowie der Unterstützung von Landwirtschaft, Züchtung und Verwaltung. Die Inhalte werden laufend aktualisiert.

Sortenschutz gehört wie Patente und Marken zur Familie des Geistigen Eigentums. Das Sortenschutzrecht regelt den gewerblichen Schutz neuer Pflanzenzüchtungen. Die Person, welche den Sortenschutztitel innehat, hat das Recht, ihre Sorte vor unerwünschter gewerbsmässiger Nutzung zu schützen. Dauer Sortenschutz 25 - 30 Jahre.

Im Sortenkatalog werden landwirtschaftlich genutzte Pflanzenarten erfasst. Man spricht von einer Zulassung, die durch eine Verordnung (Sortenverordnung) über Kataloge und Listen geregelt wird. Agroscope sowie Branchenverbände erstellen empfohlene Sortenlisten.

Die hier veröffentlichten Sorten im Sortenschutz sowie im nationalen Sortenkatalog sind derzeit unvollständig. Die Liste wird jedoch laufend aktualisiert mit neu validierten Daten.

it:
Il set di dati contiene informazioni sulle varietà vegetali ammesse in Svizzera o protette dalla protezione delle varietà vegetali (PVR) e iscritte nel Catalogo nazionale delle varietà (NLI). Sono registrati i caratteri varietali, lo stato di ammissione e la durata della protezione. I dati servono a garantire la trasparenza e a sostenere l'agricoltura, la selezione e l'amministrazione. I contenuti sono aggiornati costantemente.
La protezione delle varietà vegetali appartiene alla stessa famiglia dei brevetti e dei marchi, il diritto di proprietà intellettuale. Il diritto di protezione delle varietà vegetali regola la protezione commerciale delle nuove varietà. La persona che detiene il titolo di protezione ha il diritto di proteggere la propria varietà da un uso commerciale indesiderato. Durata della protezione delle varietà vegetali: 25-30 anni.

L'elenco nazionale (NLI) comprende le specie vegetali utilizzate in agricoltura. Esse necessitano di un'autorizzazione, che è regolata da un'ordinanza (Ordinanza sulle varietà) tramite cataloghi ed elenchi. Agroscope e le associazioni professionali stabiliscono elenchi raccomandati di varietà.

Le varietà qui pubblicate sono attualmente incomplete. Tuttavia, l'elenco viene costantemente aggiornato con i dati appena convalidati.

fr:
Le jeu de données contient des informations sur les variétés végétales admises en Suisse ou protégées par le droit de protection des obtentions végétales (PVR) qui figurent dans le catalogue national des variétés (NLI). Il recense les caractéristiques des variétés, leur statut d'admission et la durée de la protection. Les données servent à garantir la transparence et à soutenir l'agriculture, la sélection et l'administration. Le contenu est actualisé en permanence.

La protection des variétés végétales fait partie de la famille de la propriété intellectuelle, tout comme les brevets et les marques. Le droit de la protection des variétés végétales régit la protection commerciale des nouvelles obtentions végétales. La personne qui détient le titre de protection de la variété a le droit de la protéger contre une utilisation commerciale indésirable. Durée de la protection des variétés : 25 à 30 ans.

Les espèces végétales utilisées en agriculture sont répertoriées dans le catalogue des variétés. On parle d'homologation. Celle-ci est régie par une ordonnance (ordonnance sur les variétés), via des catalogues et des listes. Agroscope ainsi que les associations professionnelles établissent des listes de variétés recommandées.

Les variétés dans le registre et répertoriées dans le catalogue national publiées ici sont actuellement incomplètes. La liste est toutefois mise à jour en permanence avec les données nouvellement validées.

en:
The dataset contains information on plant varieties registered in Switzerland or protected by plant variety rights (PVR) that are listed in the national catalogue of varieties (NLI). It includes variety characteristics, registration status and the duration of protection. The data serves to promote transparency and support agriculture, breeding and administration. The content is updated on an ongoing basis.
Plant variety protection belongs to the same family than patents and trademarks, the intellectual property right. The plant variety protection right regulates the commercial protection of new varieties. The person who holds the protection title has the right to protect their variety from undesired commercial use. Duration of plant variety protection: 25–30 years.

The national listing (NLI) includes plant species used for agriculture. They need an authorization, which is regulated by an ordinance (Plant Variety Ordinance) via catalogues and lists. Agroscope and professional associations establish recommended lists of varieties.

The varieties published here in the plant variety protection and in the national catalogue of varieties are currently incomplete. However, the list is continuously updated with newly validated data.

bundesamt-fur-landwirtschaft-blw

de: Das Bundesamt für Landwirtschaft (BLW) ist das Kompetenzzentrum des Bundes für den Agrarsektor. Es setzt sich für eine multifunktionale Landwirtschaft ein.

en: The Federal Office for Agriculture (FOAG) is the Confederation's competence center for all core issues relating to the agricultural sector. The FOAG promotes multifunctional agriculture.

fr: L’Office fédéral de l’agriculture (OFAG) est le centre de compétence de la Confédération pour les questions relevant du secteur agricole. Il œuvre pour une agriculture multifonctionnelle.

it: L’Ufficio federale dell’agricoltura (UFAG) è il centro di competenza della Confederazione per le questioni inerenti al settore agricolo. Esso si impegna per un'agricoltura multifunzionale.

en: Federal Office for Agriculture FOAG

de: Bundesamt für Landwirtschaft BLW

fr: Office fédéral de l'agriculture OFAG

it: Ufficio federale dell'agricoltura UFAG

political_level: confederation

de: Bundesamt für Landwirtschaft (BLW)

fr: Office fédéral de l'agriculture (OFAG)

en: Federal Office for Agriculture (FOAG)

it: Ufficio federale dell'agricoltura (UFAG)

de: Pflanzensorten in der Schweiz

en: Plant varieties in Switzerland

it: Varietà vegetali in Svizzera

fr: Variétés végétales en Suisse

title_for_slug: pflanzensorten-in-der-schweiz

value: I14Y DCAT BLW

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

de: Diese JSON-Datei bietet detaillierte, strukturierte Daten zu Pflanzensorten, die sowohl die botanische Klassifikation als auch rechtliche Aspekte wie den Sortenschutz und nationale Listen umfassen. Sie enthält Datensätze für jede Sorte, Informationen zu Arten, Handels- und Markennamen, Statusverläufe sowie relevante Kontakte zu Züchtern und Eigentümern. Abgeleitet aus UPOV- und nationalen Agrarquellen unterstützt diese Verteilung sowohl die wissenschaftliche Klassifikation als auch den Schutz des geistigen Eigentums in der Pflanzenzüchtung.

fr: Ce fichier JSON fournit des données détaillées et structurées sur les variétés de plantes, englobant à la fois la classification botanique et les aspects juridiques tels que les droits des obtenteurs et les listes nationales. Il inclut des enregistrements pour chaque variété, des informations sur les espèces, les noms commerciaux et de marque, les historiques de statut ainsi que les contacts pertinents des obtenteurs et propriétaires. Issu de sources agricoles nationales et de l'UPOV, cette distribution soutient à la fois la classification scientifique et la protection de la propriété intellectuelle en sélection végétale.

en: This JSON file provides detailed, structured data on plant varieties, encompassing both the botanical classification and legal aspects such as plant breeders' rights and national listings. It includes records for each variety, species information, trade and brand names, status histories, and relevant contacts for breeders and owners. Derived from UPOV and national agricultural sources, this distribution supports both scientific classification and the protection of intellectual property in plant breeding.

it: Questo file JSON fornisce dati dettagliati e strutturati sulle varietà vegetali, comprendendo sia la classificazione botanica che gli aspetti legali, come i diritti dei costitutori e le liste nazionali. Include registri per ogni varietà, informazioni sulle specie, nomi commerciali e di marca, storici di stato e contatti pertinenti per costitutori e proprietari. Derivata da fonti agricole nazionali e dall'UPOV, questa distribuzione supporta sia la classificazione scientifica che la protezione della proprietà intellettuale nel miglioramento genetico vegetale.

format: JSON

media_type: application/json

pflanzen

display_name: pflanzen

piante

display_name: piante

plantes

display_name: plantes

plants

display_name: plants


en: Premium reductions by Year, Age group, Sex and Unit

de: Prämienverbilligungen nach Jahr, Altersgruppe, Geschlecht und Einheit bei Jahr, Altersgruppe, Geschlecht und Einheit

amt-fuer-statistik-fl

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Amt für Statistik

en: Office of Statistics

de: Prämienverbilligungen nach Altersgruppe und Geschlecht seit 2001

en: Premium reductions by age group and sex since 2001

value: DCAT Harvester Amt für Statistik FL

soci

de: Bevölkerung und Gesellschaft

en: Population and society

fr: Population et société

it: Popolazione e società

en: Data structure in German

de: Datenstruktur auf Deutsch

de: Datenwürfel auf Englisch

en: Data cube in English

format: HTML

media_type: text/html

en: Data structure in English

de: Datenstruktur auf Englisch

de: Datenwürfel auf Deutsch

en: Data cube in German

social-benefits

display_name: social-benefits

sozialleistungen

display_name: sozialleistungen


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.

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

envidat

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.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

de: EnviDat

value: Envidat Harvester

envi

de: Umwelt

en: Environment

en:
Resource Title: Field observations of snow instabilities
    Size: 107300 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/321f2050-93be-4772-b5d8-562f46658256/resource/5927f50c-3a33-4ceb-91bf-d583efd14cfe/download/snow_instability_field_data.csv
    Description: 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.

en:
Resource Title: Read-me file
    Size: 133885 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/321f2050-93be-4772-b5d8-562f46658256/resource/b3aeef4d-1b54-467c-88b4-4d2da8076885/download/read-me.pdf
    Description: This read-me file contains the descriptions of the variables.

format: PDF

media_type: application/pdf

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


en:
The dataset includes spatially aggregated canopy temperature measurements (°C) of one to two tree crowns obtained using infrared (IR) point sensors.
The dataset was quality screened using a multi-step outlier detection procedure based on Median Absolute Deviation (MAD) statistics within a defined analysis period (= 1 year).
**Three complementary quality-control checks were applied**:
1\. Global MAD screening – detects observations that strongly deviate from the overall distribution of each individual sensor time series.
2\. Local spike detection – identifies short-term anomalous spikes within each sensor time series using rolling median and rolling MAD statistics.
3\. Cross-sensor consistency screening – compares measurements across all sensors recorded at the same timestamp to identify extreme deviations relative to the network-wide median behaviour.
Each observation received individual QC flags for all three checks, followed by a combined final quality flag. Observations passing all criteria were labelled as `good`, while flagged observations were labelled as `outlier` if considered suspect, or as `bad` if associated with known sensor drifts. Observations labelled as `outlier` may still represent physically plausible values, while observations labelled as `bad` should not be considered for further analysis. All observations were retained in the exported dataset for traceability.

en: heat-stress cooling vpdrought transpiration pfynwald ir-sensor pinus-sylvestris irrigation

en: Pfynwald VPDrought experiment canopy temperature parameter

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_1min_2024.zip
    Size: 51370310 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/966309dc-3bf5-4bbc-9964-6af79bf294fd/download/pfynwald_vpdrought_canopy_temperature_1min_2024.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_10min_2025.zip
    Size: 5833672 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/66747b91-d345-4e98-97c7-9d7b3ce92266/download/pfynwald_vpdrought_canopy_temperature_10min_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_10min_2024.zip
    Size: 5872908 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/212221fb-14a0-4157-97e9-1670e221959d/download/pfynwald_vpdrought_canopy_temperature_10min_2024.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_1min_2025.zip
    Size: 50905903 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/3ed284f7-5ca4-4b25-9441-00722b92e58d/download/pfynwald_vpdrought_canopy_temperature_1min_2025.zip
    Description:

cooling

display_name: cooling

heat-stress

display_name: heat-stress

ir-sensor

display_name: ir-sensor

irrigation

display_name: irrigation

pfynwald

display_name: pfynwald

pinus-sylvestris

display_name: pinus-sylvestris

transpiration

display_name: transpiration

vpdrought

display_name: vpdrought


en:
Atmospheric drought (high vapor pressure deficit, VPD) and soil drought frequently co-occur, yet plants respond to these stressors through partially distinct physiological pathways, potentially altering source (photosynthesis) and sink (growth and respiration) activities. Despite significant advances in understanding drought impacts on photosynthesis and plant hydraulics, the independent and interactive effects of soil vs. atmospheric drought on whole-tree carbon balance, including non-structural carbohydrate (NSC) dynamics, allocation priorities, and growth, remain insufficiently understood.
This project aims to disentangle the effects of soil and atmospheric droughts on tree sink and source dynamics in European forests, by studying leaf-to-whole-tree ecophysiological processes that drive growth, carbon sequestration and tree mortality. Research will primarily be conducted in Pfynwald (Valais, Switzerland), as part of the VPDrought experiment, where mature Scots pines (Pinus sylvestris) are exposed to increased soil drought and reduced VPD.
Our study addresses the research question: how do soil and atmospheric droughts differentially affect tree carbon uptake and allocation to growth? We hypothesize that atmospheric drought primarily limits carbon assimilation via stomatal closure, leading to reduced growth and respiration (sink activity), whereas soil drought suppresses both carbon uptake (source activity) and sink strength (growth and respiration), leading to stronger shifts in carbon allocation and early reductions in sink demand. Soil drought restricts carbon transport to belowground sinks, while atmospheric drought promotes NSC accumulation in source tissues due to stomatal closure and reduced sink demand.
**Methods:**
Four campaigns (~4 days each) will be conducted at VPDrought during the summer of 2026-2028, covering four experimental treatments: 1) soil drought + ambient air, 2) soil drought + reduced VPD, 3) irrigation + ambient air, 4) irrigation + reduced VPD. Each treatment will include 6-9 replicates.
During the campaigns, gas exchange measurements will be performed, including net photosynthesis, stomatal conductance, temperature responses of photosynthesis and respiration, and A/Ci curves, using three LI-COR systems (LI-6800). Twig water potential (pre-dawn and midday) will be measured with a Scholander pressure chamber (PMS, model 1505D). Twig, needles, and root samples will be collected across treatments for non-structural carbohydrate (NSC) analyses. Stem respiration measurements will be taken using a custom-made chamber and analyzed with the LI-COR (LI-8100A). In addition, stem radial growth (measured with dendrometers) and leaf area development (using Lidar measurements) will be utilized as proxies for sink activity and carbon allocation to structural growth.  Measurements will be repeated across all years, with additional assessments in 2027 and 2028, including resin flow and phloem transport efficiency using a 13C pulse labeling approach.

en: vpd gas-exchange pinus-sylvestris carbon-dynamics soil-drought

en: Carbon balance under dual droughts: Disentangling the effects of soil and atmospheric moisture on tree sink and source dynamics in European forests.

format: TXT

carbon-dynamics

display_name: carbon-dynamics

gas-exchange

display_name: gas-exchange

soil-drought

display_name: soil-drought

vpd

display_name: vpd


en:
The dataset refers to samples collected across 6 farms in the Bega Valley region of Australia. The farms are located in the grassy woodland ecoregion and are extensively managed with sheep and cattle grazing. Livestock shares the landscape with native mammalian and invertebrate herbivores. On each farm, two nested fenced exclosure systems were established. These included an open area, a fence excluding livestock but allowing access to native mammals and invertebrates and a fence excluding all mammals but allowing access to invertebrates. In each farm, one of these systems was located in a zone dominated by the native Kangaroo grass, and another in a zone co-dominated by the Invasive African lovegrass. The sample and treatment numbering, as well as a summary of the aggregated indicators is provided in the file Indicator_summary.
Leaf swab s(phyllosphere) samples were taken and DNA was extracted and amplified for 16s and ITS markers. The resulting metabarcoding derived tables are presented (Bacteria_swabs and Fungi_swabs respectively), as are the inferred functional profiles for bacteria at the pathway level (PICRUSt2_pathways), as derived by the PICRUSt2 pipeline.
Two 20 by 100 cm strips had their vegetation removed and their living and litter biomass quantified by dry weight (Biomass). Sensors measuring temperature 10 cm above the soil surface were installed in each plot and their output is presented in Climate. Invertebrates were collected with both pitfall traps and sweepnets and the counts for both sampling techniques can be found in Invertebrates. Damage scores across different categories were collected on 5 leaves of the two species in each plot and the average scores can be found in Leaf_damage.

en: herbivore-exclusion grassland invertebrates phyllosphere biological-invasions

en: Herbivory disrupts invasion_associated phyllosphere and arthropod community shifts in grasslands

en:
Resource Title: PICRUSt2.csv
    Size: 469821 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/665f8907-396a-4b1e-b564-fa100a2b5968/download/picrust2.csv
    Description: Predicted pathway profiles of sampled phyllosphere bacterial communities

en:
Resource Title: Climate.csv
    Size: 5096079 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/787a3947-a316-4ac5-aeda-ffacfd832bed/download/climate.csv
    Description: Sensor collected soil surface temperatures

en:
Resource Title: Fungi_swabs.csv
    Size: 1059062 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/02fb3082-a33e-4af4-8ea1-d4c4953eec4e/download/fungi_swabs.csv
    Description: OTU table of fungal phyllosphere communities

en:
Resource Title: Bacteria_swabs.csv
    Size: 1153434 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/f97a1423-4749-45fa-a07e-93697dd72676/download/bacteria_swabs.csv
    Description: OTU table of bacterial phyllosphere communities

en:
Resource Title: Leaf_damage.csv
    Size: 2007 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/5c2f7e5f-cc22-4ac6-aa16-f3ef13d27ea7/download/leaf_damage.csv
    Description: Aggregated leaf damage scores for African lovegrass and Kangaroo grass

en:
Resource Title: Biomass.csv
    Size: 3031 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/ac6aecef-5a8d-4539-b231-3403691fc3f9/download/biomass.csv
    Description: Dry biomass weight of collected plant material

en:
Resource Title: Indicator_summary.csv
    Size: 19067 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/d68e884c-0153-4d0f-95c6-eb5702972cce/download/indicator_summary.csv
    Description: Sample metadata and aggregate indicators

en:
Resource Title: Invertebrates.csv
    Size: 18842 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/493ae610-9929-4499-8dfb-fdb7c8feafed/download/invertebrates.csv
    Description: Counts of invertebrates collected with pitfall traps and sweepnets

biological-invasions

display_name: biological-invasions

grassland

display_name: grassland

herbivore-exclusion

display_name: herbivore-exclusion

invertebrates

display_name: invertebrates

phyllosphere

display_name: phyllosphere


en:
Dataset content
Continuous soil measurements (10-min resolution) from the Pfynwald long-term irrigation experiment, covering five treatments: **control, irrigation, irrigation+VPD, roof, roof+VPD**.
Measurements were taken at multiple plots and at three depths (-0.1, -0.8, -1.2 m below soil surface).
Sensors include TEROS-21 (matric potential), TEROS-12 (volumetric water content), TEROS-21 (soil temperature), and TEROS-12 (electrical conductivity).
 Processing steps
**1. Raw retrieval** from the LWF database (`ada.v_messvar`, project `Pfynwald irrigation`), 10-min cadence.
**2. Range filtering** to remove physically implausible values:
   - SWP: drop values ≥ 0 kPa or ≤ −8000 kPa
   - VWC: drop values ≤ 0 or - 0.8 m³/m³
   - TEM: drop values - 40 °C or - −20 °C
**3. Duplicate aggregation** within the same 10-min timestamp by mean (median for SWP).
**4. Temperature correction (SWP_TC)**: matric potential is temperature-corrected using the TEROS-21 manufacturer equation referenced to T_ref = 20 °C:
   - Convert SWP (kPa) to head h = |SWP|·10.197, then pF = log10(h)
   - ΔpF = (919.890694·ΔT − 6.945352·ΔT²)·exp(−150.754657 / (pF + 9.153084))
   - SWP_TC = −10^(pF + ΔpF) / 10.197
**5. No gap filling applied.** Missing values remain absent from the delivered CSV.
 Methods
- Database query and aggregation: R, `data.table`, `rLWFpg`
- Temperature correction: in-house implementation of TEROS-21 manufacturer formula
- See repository / script reference below
 Limitations
- Values flagged out of range during step 2 are absent (not interpolated)
- Winter periods may include frozen-soil readings — these pass the range filter as physical sensor outputs but should be interpreted with caution by downstream users
- SWP_TC rows carry the messvar_id of the underlying SWP sensor; the corresponding TEM sensor used for correction is paired via site/plot/depth/datetime but not encoded in the messvar_id
- Sensor calibration uses manufacturer defaults; site-specific calibration was not performed
- Roofs were installed in spring 2024. Readings under "roof" / "roof_vpd" treatments before that reflect ambient conditions, not the experimental treatment.
- In 2025, three additional TEROS-21 sensors were added per roofed treatment at 10 cm depth to obtain a balanced sample relative to roof position (under panels, at panel edges, and in inter-panel gaps).
  This expansion means roofed treatments have six positions at 10 cm from 2025 onward, compared to three before.

en: soil-temperature pfynwald teros-12 irrigation-manipulation teros-21 vpdrought pinus-sylvestris electrical-conductivity irrigation drought-experiment soil-moisture water-potential

envidat

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

en: EnviDat: the Environmental Data Portal

en: Pfynwald VPDrought experiment soil parameters

envi

en: Environment

en:
Resource Title: pfynwald_vpdrought_soil_10Minutes_2025.zip
    Size: 66201780 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/12bc2274-e48f-4ff1-8961-b86699aaa450/resource/edaa3e3a-1045-4d2f-952f-e23689c20bb9/download/pfynwald_vpdrought_soil_10minutes_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_soil_10Minutes_2024.zip
    Size: 59025329 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/12bc2274-e48f-4ff1-8961-b86699aaa450/resource/3606ad5b-f308-4bfc-8aa4-db5b017ee47a/download/pfynwald_vpdrought_soil_10minutes_2024.zip
    Description:

drought-experiment

display_name: drought-experiment

electrical-conductivity

display_name: electrical-conductivity

irrigation-manipulation

display_name: irrigation-manipulation

soil-moisture

display_name: soil-moisture

soil-temperature

display_name: soil-temperature

water-potential

display_name: water-potential


en:
Description
This dataset contains continuous sap-flow measurements and derived whole-tree transpiration estimates for 45 Pinus sylvestris trees at the Pfynwald experimental platform in southwestern Switzerland during 2024–2025. Trees were distributed across five treatment combinations established within the VPDrought experiment: Control, Irrigation, Irrigation + VPD reduction, Roof, and Roof + VPD reduction. Sap flux density was measured every 10 min using heat-ratio sap-flow sensors (IX-SF30, Implexx, Melbourne, Australia) installed at breast height on the north-facing side of each tree.
Raw temperature signals were converted to sap flux density following the heat ratio method (Marshall 1958; Burgess et al. 2001; Forster 2019). Thermal diffusivity and related wood properties were parameterized using increment cores collected near the site and tree-specific allometric relationships. Probe misalignment was corrected by estimating a zero-flow offset from nighttime measurements during well-watered, low-VPD conditions in February 2024 and subtracting this offset from the full time series.
Sap flux density measurements at 0.5 and 1.5 cm sapwood depth were combined to total sap flow for the depth where the sensors were installed. Whole-tree transpiration can be calculated by integrating sap flux density across concentric sapwood depth of 2 cm.
The dataset includes processed sap flux density values together with metadata on treatment, tree identity, sensor depth, and quality-control corrections. Limitations include possible residual uncertainty due to sensor drift, assumptions in the sapwood depth, and the replacement of two trees that died during summer 2024 and lost parts of their crown in 2025.
 Additional Information
Data processing was performed in an R environment following the heat ratio method workflow described by Forster (2019). Raw heat-pulse measurements were converted to sap flux density and subsequently corrected for thermal diffusivity, and probe misalignment. Outliers and implausible values were identified and removed using the R package datacleanr (Hurley et al. 2022). Sensor needle misalignment was corrected by defining a zero-flow offset during periods of low atmospheric demand and assumed zero sap flow (i.e. rainy periods), and subtracting this offset from the time series. The processing script used to derive the dataset is available from the authors upon request.
Relevant literature:
- Burgess S.S.O., Adams M.A., Turner N.C., Beverly C.R., Ong C.K., Khan A.A.H. & Bleby T.M. (2001) An improved heat pulse method to measure low and reverse rates of sap flow in woody plants†. Tree Physiology 21, 589–598.
- Forster M.A. (2019) The Dual Method Approach (DMA) Resolves Measurement Range Limitations of Heat Pulse Velocity Sap Flow Sensors. Forests 10.
- Hurley A.G., Peters R.L., Pappas C., Steger D.N. & Heinrich I. (2022) Addressing the need for interactive, efficient, and reproducible data processing in ecology with the datacleanr R package. PLOS ONE 17, e0268426-.
- Marshall D.C. (1958) Measurement of Sap Flow in Conifers by Heat Transport. 1. Plant Physiology 33, 385–396.

en: continuous-monitoring xylem-flux rhone-valley irrigation drought-experiment pfynwald reduction transpiration sap-flow forest-ecophysiology rain-exclusion tree-transpiration vpd vpdrought pinus-sylvestris

en: Pfynwald VPDrought  experiment sap flow parameter

en:
Resource Title: pfynwald_vpdrought_sapflow_10Minutes_2024.zip
    Size: 53546175 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9e439e5-827a-40a7-956c-1a05699e6adc/resource/6a0cd3b8-8e29-4b85-9296-86196808fd32/download/pfynwald_vpdrought_sapflow_10minutes_2024.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_sapflow_10Minutes_2025.zip
    Size: 53424631 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9e439e5-827a-40a7-956c-1a05699e6adc/resource/455662d6-f0b7-4ea8-8cb6-d31eb714952e/download/pfynwald_vpdrought_sapflow_10minutes_2025.zip
    Description:

continuous-monitoring

display_name: continuous-monitoring

forest-ecophysiology

display_name: forest-ecophysiology

irrigation

display_name: irrigation

pfynwald

display_name: pfynwald

pinus-sylvestris

display_name: pinus-sylvestris

rain-exclusion

display_name: rain-exclusion

reduction

display_name: reduction

rhone-valley

display_name: rhone-valley

sap-flow

display_name: sap-flow

transpiration

display_name: transpiration

tree-transpiration

display_name: tree-transpiration

xylem-flux

display_name: xylem-flux


en:
Project description:
Forest soils are among the largest terrestrial carbon pools. How soil carbon (C) responds to changing water availability is still poorly understood, particularly in already water-limited systems. This project investigates the composition and persistence of soil organic matter (SOM) and associated microbial communities in a dry inner-Alpine Scots pine forest exposed to long-term changes in precipitation and atmospheric demand. Earlier work showed that 19 years of irrigation redistributed bulk soil C from the organic layer into the mineral soil. Although total soil C stocks remained unchanged, a higher incorporation into mineral soils may increase long-term C storage (Guidi et al., 2022; Minich et al., 2026). We now ask, how persistent this redistributed C is, in which soil C fraction (particulate or mineral-associated) it resides, and which microbial communities are associated with it.
The work is based at Pfynwald, where a long-term irrigation experiment (since 2003) and the recently installed [VPDrought platform](https://vpdrought.wsl.ch/de/) together span three precipitation regimes (≈300, 600, and 1200 mm per year) crossed with manipulation of atmospheric vapour-pressure deficit. This setup allows us to disentangle the effects of soil and atmospheric drought, which typically co-vary in nature but may shape soil carbon dynamics through distinct pathways. SOM is separated by physical fractionation into particulate (POM) and mineral-associated (MAOM) fractions, characterized through elemental and isotopic analyses (C, N, δ¹³C, δ¹⁵N, ¹⁴C) and fraction-specific microbial community profiling. At the bulk soil level, we measure nutrient pools and extracellular enzyme activities, continue year-round soil respiration, and complement them by CH4 fluxes. Together, these data will reveal how soil carbon stocks and microbial processing respond to changing precipitation in a water-limited pine forest.

en: pfynwald microbial-communities drought radiocarbon som

en: Soil organic matter dynamics under altered precipitation in a dry Scots pine forest

drought

display_name: drought

microbial-communities

display_name: microbial-communities

radiocarbon

display_name: radiocarbon

som

display_name: som


historical-vegetation-height-model-nfi

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

en: photogrammetry dsm nfi historical forest vhm

en: Historical Vegetation Height Model NFI

title_for_slug: historical-vegetation-height-model-nfi

en:
Resource Title: 1990-1998 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1990-1998_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: readme.txt
    Size: 2045 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d16d27e5-b239-4909-b914-1b0b5337dab3/resource/f6cabeaa-bf7c-4141-bea9-af99d3224487/download/readme.txt
    Description: Description of available data

media_type: text/plain

en:
Resource Title: 1985-1991 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1985-1991_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1998-2006 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1998-2006_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1979-1985 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1979-1985_vegetation_height_model_nfi%2F
    Description:

dsm

display_name: dsm

forest

display_name: forest

historical

display_name: historical

nfi

display_name: nfi

photogrammetry

display_name: photogrammetry

vhm

display_name: vhm


vegetation-height-model-lidar-nfi

en:
Countrywide **vegetation height models (VHM)** were generated for Switzerland based on
LiDAR data acquired in the framework of the **swissSURFACE3D** campaign (swisstopo).
To derive vegetation height, the classified point cloud got normalized by calculating height above ground for all points not belonging to the class ground (2). Vegetation point (class 3,4,5) got then rasterized to a grid size of 0.5 m using an interpolation distance of one grid cell. Raster cells not belonging to a vegetation class got set to 0 m above ground.
These VHM's are produced in the framework of the Swiss National forest Inventory (NFI).
Each year about 1/6 of switzerland surface is updated using swissSURFACE3D data in leaf-off state.

en: point-cloud forest vegetation-classification vegetation vegetation-height nfi three-dimensional

envidat

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

en: EnviDat: the Environmental Data Portal

en: Vegetation Height Model LiDAR NFI

title_for_slug: vegetation-height-model-lidar-nfi

envi

en: Environment

en:
Resource Title: 2024 Vegetation Height Model LiDAR NFI
    Size: 149786984448 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2024%2F
    Description: Vegetation Height Model of Switzerland for the year 2024 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

en:
Resource Title: 2025 Vegetation Height Model LiDAR NFI (current)
    Size: 160202280141 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2025%2F
    Description: Vegetation Height Model of Switzerland for the year 2025 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

point-cloud

display_name: point-cloud

three-dimensional

display_name: three-dimensional

vegetation

display_name: vegetation

vegetation-classification

display_name: vegetation-classification

vegetation-height

display_name: vegetation-height


en:
The data show locations of the most recent outdoor activity (referred to as restorative location, RL) of Swiss residents, and descriptive characteristics of these places. The data was collected via an online participatory mapping survey targeting residents of urban, peri-urban, and rural areas across Switzerland. Respondents were selected using a stratified random sampling method, considering the greenness and noise exposure of their home locations, and demographic factors such as age, gender, and language region.
The survey was conducted using Maptionnaire software (https://maptionnaire.com). Participants were asked to map the location of their most recent outdoor activity (referred to as restorative location, RL) and provide additional information on their experience in these places. The responses were integrated with the quantitative spatial information (biophysical landscape characteristics, referred to as metrics) on the visited locations, obtained from spatial and remote sensing data.

en: restorative-environments sensory-perception traffic-noise quiet-areas gis-analysis soundscape

en: Restorative locations from participatory mapping by Swiss residents

gis-analysis

display_name: gis-analysis

quiet-areas

display_name: quiet-areas

restorative-environments

display_name: restorative-environments

sensory-perception

display_name: sensory-perception

soundscape

display_name: soundscape

traffic-noise

display_name: traffic-noise


en:
This study examines the siting scenarios for renewable energy infrastructure (REI) in Switzerland, incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed.
MARXAN was run for 2 versions: a) without ground-mounted open space PV infrastructure (excl. OS) and b) with ground-mounted open space PV infrastructure (incl. OS). In each version optimization was done using ecological costs (ECUess) or social costs (ECUsoc) in a regular grid of 4x4km (planning unit).
File:
PU_data.shp: compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.
Headers are described below:
X01 = Planning_units (PUs)
X02 = incl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)
geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).
For MARXAN optimizations (for meaning of standard files in MARXAN see https://scholar.google.ch/scholar_url?url=https://courses.washington.edu/cfr590/software/Marxan1810/marxan_manual_1_8_2.pdf&hl=de&sa=X&ei=NAWHZI6JJ8PFmAGMo47oDQ&scisig=AGlGAw-DBrsV4kUzkR6GkN1jtG66&oi=scholarr), pu_data.shp was used to generate MARXAN files input.dat, pu.dat, puvfeat.dat, spec.dat.
Coordinate Reference System: CH1903 / LV03. EPSG: 21781.

en: spatial-planning photovoltaic social-acceptance marxan optimization wind-power landscape energy ecosystem-services

en: Optimizing renewable energy siting in the Swiss landscape

ecosystem-services

display_name: ecosystem-services

energy

display_name: energy

landscape

display_name: landscape

marxan

display_name: marxan

optimization

display_name: optimization

photovoltaic

display_name: photovoltaic

social-acceptance

display_name: social-acceptance

spatial-planning

display_name: spatial-planning

wind-power

display_name: wind-power


en: Site description of the Seehornwald Davos (CH-DAV) research site. The material provided offers information on the biomass and growth of trees in CH-DAV, including supporting materials such as maps, geolocations and analyses. CH-DAV is part of networks such as ICOS, LWF, TreeNet, ICPForests and is dedicated to forest monitoring and research.

en: forest-ecosystems forest-characteristics icp-forests forest-canopy climate-change climate-growth biomass atmospheric-conditions ilter dbh automated-monitoring forest-area flux carbon-storage stem-growth forest-dynamics carbon-cycle metadata dendrometer eddy-covariance twd forest-monitoring davos open-data forest-biomass forest-function water-relations subalpine carbon-dioxide ecosystem-functioning sap-flow ecophysiology co2 forest icos treenet tree-stem lwf carbon-sequestration seehornwald picea-abies eddy-covariance-measurements

en: Site description Davos Seehornwald CH-DAV

en:
Resource Title: CH-DAV_Site_2024_V2.zip
    Size: 27267396 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4d332ffa-d5f5-413c-ba1c-5f73ceebbed6/resource/41e3d87c-7907-4a01-bf5e-36a0d4457c40/download/ch-dav_site_2024_v2.zip
    Description: Collection of files with information about the research site Seehornwald Davos CH-DAV

en:
Resource Title: Readme
    Size: 2476 bytes
    Format: application/rtf
    URL: https://www.envidat.ch/dataset/4d332ffa-d5f5-413c-ba1c-5f73ceebbed6/resource/7f13f634-76b5-4d56-aa5a-61140240f616/download/readme.rtf
    Description:

format: rtf

en:
Resource Title: CH-DAV_Site_2024.zip
    Size: 34214528 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4d332ffa-d5f5-413c-ba1c-5f73ceebbed6/resource/73875879-bec0-4e15-a805-e6cd9d4fe596/download/ch-dav_site_2024.zip
    Description: Collection of files with information about the research site Seehornwald Davos CH-DAV

atmospheric-conditions

display_name: atmospheric-conditions

automated-monitoring

display_name: automated-monitoring

biomass

display_name: biomass

carbon-cycle

display_name: carbon-cycle

carbon-dioxide

display_name: carbon-dioxide

carbon-sequestration

display_name: carbon-sequestration

carbon-storage

display_name: carbon-storage

climate-change

display_name: climate-change

climate-growth

display_name: climate-growth

davos

display_name: davos

dbh

display_name: dbh

dendrometer

display_name: dendrometer

ecophysiology

display_name: ecophysiology

ecosystem-functioning

display_name: ecosystem-functioning

eddy-covariance

display_name: eddy-covariance

eddy-covariance-measurements

display_name: eddy-covariance-measurements

flux

display_name: flux

forest

display_name: forest

forest-area

display_name: forest-area

forest-biomass

display_name: forest-biomass

forest-canopy

display_name: forest-canopy

forest-characteristics

display_name: forest-characteristics

forest-dynamics

display_name: forest-dynamics

forest-ecosystems

display_name: forest-ecosystems

forest-function

display_name: forest-function

forest-monitoring

display_name: forest-monitoring

icos

display_name: icos

icp-forests

display_name: icp-forests

ilter

display_name: ilter

lwf

display_name: lwf

metadata

display_name: metadata

open-data

display_name: open-data

picea-abies

display_name: picea-abies


alan-spongy-moth-laboratory-experiment

en:
Data and Code for ALAN Spongy Moth lab experiment
In this repository you will find all the raw datasets used for the data analysis performed in our paper about the impacts of artificial light at night (ALAN) on the development of Spongy Moth caterpillars. The files are attached as a csv file.
Also attached is all the R-code later used for the statistical analysis and for generating the graphics displayed in the paper. This files are attached as an R.file.

en: spongy-moth alan light-pollution insect-development lab-experiment

envidat

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

en: EnviDat: the Environmental Data Portal

en: ALAN Spongy Moth Laboratory Experiment

title_for_slug: alan-spongy-moth-laboratory-experiment

en:
Resource Title: CoxHazard_KaplanMeier_Mort_Pup.R
    Size: 3933 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/0a205353-8812-4f39-af3f-8d67d2d1495c/download/coxhazard_kaplanmeier_mort_pup.r
    Description: R code for the Cox hazard analysis and producing the Kaplan Meier survival curves for both Mortality and Pupation.

en:
Resource Title: SM_R_long_NvK.csv
    Size: 567035 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/401242a6-4430-4725-8c41-263a4f769041/download/sm_r_long_nvk.csv
    Description: Raw data modified and used for the Bodymass Analysis

en:
Resource Title: Pupation_analysis.R
    Size: 7606 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/f5ad6fb7-b540-4742-8b77-e5fa86855b1d/download/pupation_analysis.r
    Description: R code for the pupation analysis and producing the graphics.

en:
Resource Title: SM_R_NvK.csv
    Size: 56547 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/c93124fd-448c-403b-bc42-70f4b6722636/download/sm_r_nvk.csv
    Description: Raw data used for the Pupation and Cox Hazard/Kaplan Meier Analysis.

en:
Resource Title: BodyMass_analysis.R
    Size: 4254 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/0ff15832-2eb3-4420-9afd-869e36ce92ef/download/bodymass_analysis.r
    Description: R code for the bodymass analysis and producing the graphics.

alan

display_name: alan

insect-development

display_name: insect-development

lab-experiment

display_name: lab-experiment

light-pollution

display_name: light-pollution

spongy-moth

display_name: spongy-moth


forest-canopy-layer

en: This dataset provides a LiDAR-based classification of the forest canopy layer for selected Swiss cantons. Combining an area-based and tree-centred approach, forest areas are categorised into four canopy layering classes that differentiate between single-layered and multi-layered canopies.

en: mountain-forest forest-structure lidar forest-management nfi forest-canopy

en: Forest Canopy Layer

title_for_slug: forest-canopy-layer

envi

en: Environment

en:
Resource Title: ForestCanopyLayer.tif
    Size: 558505541 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/90bcde13-c71d-4618-a198-362ebccd0516/download/forestcanopylayer.tif
    Description: Forest Canopy Layer (class 1: single-layered; class 2: probably single-layered; class 3: probably multi-layered; class 4: multi-layered).

format: TIFF

media_type: image/tiff

en:
Resource Title: ForestCanopyLayer.qml
    Size: 8139 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/378dbed2-33a3-4398-8a41-5c341d27557d/download/forestcanopylayer.qml
    Description: QGIS QML file with stored layer style definitions for the ForestCanopyLayer.tif.

en:
Resource Title: IFA_Data.csv
    Size: 3837 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/a15b3bdb-c45e-4a8a-b526-8d43b265862c/download/ifa_data.csv
    Description: Validation data from the Independent Forester Assessment (IFA). x- /y-coordinate (CH1903+ LV03) and layer (1: single-layered; 2: multi-layered; -999: NA).

forest-canopy

display_name: forest-canopy

forest-management

display_name: forest-management

forest-structure

display_name: forest-structure

lidar

display_name: lidar

mountain-forest

display_name: mountain-forest

nfi

display_name: nfi


en:
This dataset contains the input data generated for the pseudo-global warming (PGW) experiments used in the study of the March 2022 Antarctic heatwave with the CRYOWRF model. It includes:
- PGW delta fields derived from CMIP6 simulations, used to perturb ERA5 reanalysis data for past and  future storyline experiments.
- Model configuration files required to reproduce the CRYOWRF simulations.
These resources allow researchers to reproduce the experimental setup and generate model outputs consistent with the results presented in the study.

en: era5 event-attribution climate-change extreme-events cmip6 antarctica heatwave atmospheric-rivers

en: Storylines of the March 2022 heatwave event at Concordia - East Antarctica

en:
Resource Title: CRYOWRF_ANT_20220315_ConfigFiles.tar
    Size: 912259096 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/79b7c457-e689-49bd-8330-29b0508d2b2c/resource/7f77d116-cd3b-4eec-a6d6-061b0d7b43f6/download/cryowrf_ant_20220315_configfiles.tar
    Description: Model configuration files required to reproduce the CRYOWRF simulations over Antarctica.

en:
Resource Title: PGW_deltas.tar
    Size: 3701853962 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/79b7c457-e689-49bd-8330-29b0508d2b2c/resource/9936c23c-dc86-4eaa-8a6f-5a49cffb338c/download/pgw_deltas.tar
    Description: PGW delta fields derived from CMIP6 simulations, used to perturb ERA5 reanalysis data for future storyline experiments.

antarctica

display_name: antarctica

atmospheric-rivers

display_name: atmospheric-rivers

climate-change

display_name: climate-change

event-attribution

display_name: event-attribution

extreme-events

display_name: extreme-events

heatwave

display_name: heatwave


en:
Regional disturbance predisposition maps for windthrow, bark beetle and snow breakage. The maps are created using spatially explicit data of classified forest structure and site factor parameters. The classified input parameters were weighted according to their effect on windthrow, bark beetle and snow breakage predisposition using an expert-based model. The predisposition raster maps (10 x 10 m) represent the sum of expert-weighted effects on the predisposition and are provided as raw values (sum of the effects on predisposition) and as classified layers.
Classified predisposition maps are encoded as follows:
1: low predisposition (-50% quantile based on raw predisposition values)
2: increased predisposition (50–75% quantile)
3: high predisposition (-75–95% quantile)
4: extreme predisposition (-95% quantile)
Also included are the derived forest structure maps for development stage, dominant stand height, number of stems and canopy cover used for the predisposition mapping, as well as the R scripts and example data to re-create these parameters. Forest structure parameters are based on a data set of individual trees detected using a high-resolution vegetation height model. Further included are ArcPy scripts and example data to re-create the predisposition maps. Running the ArcPy scripts requires a valid ArcGis license including the extensions "SpatialAnalyst", "ImageAnalyst" and "3D".
The example data provided here is assembled from different sources; please check the related publication Bührle et al. (in review) for data sources and further information about the processing, the expert-based model, the forest structure derivation and the predisposition mapping.
Also consider reviewing the related datasets and publications Bast et al. (2025) for more information about canopy layering derivation and individual tree detection (ITD).

en: predisposition canopy-cover bark-beetle development-stage windthrow snow-breakage forest-structure tree-detection stand-height als stem-number predisposition-mapping itd

envidat

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

en: EnviDat: the Environmental Data Portal

en: Regional bark beetle windthrow and snow breakage disturbance predisposition maps

en:
Resource Title: 04_forest_structure_maps.zip
    Size: 34068234 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/cd162993-bc30-46c1-816b-0722c3d83a50/download/04_forest_structure_map.zip
    Description: Maps of development stage, number of stems, dominant stand height and canopy coverage based on single trees detected from a vegetation height model.

en:
Resource Title: 01_predispostion_maps.zip
    Size: 19881001 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/59df8818-2e56-4794-9152-3652c20fe6fc/download/01_predispostion_maps.zip
    Description: Classified and raw value predisposition maps for bark beetle, windthrow and snow breakage

en:
Resource Title: 03_rcode_forest_structure.zip
    Size: 103693681 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/42199442-7c55-48ed-a3a7-04aaf9967da0/download/03_rcode_forest_structure.zip
    Description: R-codes and demo data to derive the forest structure parameters: development stage, number of stems, dominant stand height, and canopy coverage based on single trees detected from a vegetation height model. These parameters are necessary input parameters for predisposition mapping.

en:
Resource Title: 02_python_scripts_predisposition_mapping.zip
    Size: 438323 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/e165fc12-ca86-423f-807a-d7cf1c8535a5/download/02_python_scripts_predisposition_mapping.zip
    Description: ArcPy-Python scripts and demo data to create the bark beetle, windthrow and snow breakage predisposition maps.

als

display_name: als

bark-beetle

display_name: bark-beetle

canopy-cover

display_name: canopy-cover

development-stage

display_name: development-stage

itd

display_name: itd

predisposition

display_name: predisposition

predisposition-mapping

display_name: predisposition-mapping

snow-breakage

display_name: snow-breakage

stand-height

display_name: stand-height

stem-number

display_name: stem-number

tree-detection

display_name: tree-detection

windthrow

display_name: windthrow


en:
This dataset contains gridded snow depth projections for Switzerland at 1km X 1km resolution. This study was supported by Speed2Zero. The dataset contains the following structure:
- data/data_reference/hs_reference_1991_2020.nc
- data/data_projection_flat/hs_projection_flat.nc
- data/data_projection_aspect/hs_projection_aspect.nc
The data is based on climatological SPASS dataset (Marty et al., 2015) using the reference period 1991-2020. For this reference data, median snow depth evolution, as well as 5th and 95th percentile were computed for each grid point and can be found in this dataset (data/data_reference/*). Future snow depth evolutions for the flat field (data/data_projection_flat/*) were projected for the temperature scenarios +1°C, +2°C, +3°C and +4°C (deviation from 1991-2020 annual mean temperature in Switzerland) following the literature-based approach of Richter and Marty, 2026. Furthermore, this dataset contains gridded projections for north- and south-facing ascpects with a slope anle of 15° (data/data_projection_aspect/*). Detailed can be found in the related publication Richter et al., in preparation.
The files in this data set have a similar structure. Each file is a NetCDF-file containing snow depths (median, 5th, 95th percentile) for each day of the year, coordinate, temperature scenario (data_projection_flat and data_projection_aspect) and aspect (data_projection_aspect).
References:
Marty, C., Michel, A., Jonas, T., Steijn, C., Muelchi, R., and Kotlarski, S.: SPASS – new gridded climatological snow datasets for Switzerland: potential and limitations, The Cryosphere, 19, 4391–4407, https://doi.org/10.5194/tc-19-4391-2025, 2025.
Richter, B. and Marty, C.: Technical note: Literature based approach to estimate future snow, Hydrol. Earth Syst. Sci., 30, 659–670, https://doi.org/10.5194/hess-30-659-2026, 2026.
Richter et al., Gridded snow depth projections, in prepration.

en: climate-change future gridded-data snow scenario swiss-alps switzerland snow-depth climate-projections

en: Gridded projections of snow depth for Switzerland

envi

en: Environment

climate-projections

display_name: climate-projections

future

display_name: future

gridded-data

display_name: gridded-data

scenario

display_name: scenario

snow

display_name: snow

snow-depth

display_name: snow-depth

swiss-alps

display_name: swiss-alps

switzerland

display_name: switzerland


individual-detected-trees

en: This dataset provides individual detected trees for selected Swiss Cantons (Appenzell Outer-Rhodes - AR, Grisons - GR, Nidwald - NW, Obwald - OW and St. Gall - SG), including the derived diameter at breast height and the derived NFI development stage. Data show the Individual detected trees (ITD) with the x- and y-positions of each detected tree based on a spike-free vegetation height model based on nationwide LiDAR data. The shapefile contains the following attributes: tree height [m] (Height), estimated diameter at breast height [cm] (BHD), and the NFI development stage (Ent; 1: young growth/thicket (- 12 cm); 2: pole timber (12-30 cm); 3: young timber (31-40 cm); 4: medium timber (41-50 cm); 5: old timber (- 50 cm).

en: itd forest-management nfi development-stage mountain-forest forest-structure

en: Individual Detected Trees

title_for_slug: individual-detected-trees

development-stage

display_name: development-stage

forest-management

display_name: forest-management

forest-structure

display_name: forest-structure

mountain-forest

display_name: mountain-forest

nfi

display_name: nfi


iwet-insect-weight-estimation-tool

en:
Because of some corrections, a new version of the whole Dataset will be published soon.
We present a novel tool called IWET (Insect Weight Estimation Tool) for estimating morphometrics of arthropod samples using image analysis. IWET is a Java application built around ImageJ libraries and is designed to estimate length, width, area and body mass of individual arthropods from images of specimens sorted into pre-defined taxonomic groups. Using allometric relationships from Sohlströhm et al. (2018), we developed specific regression models to calculate both the individual body mass and the total biomass of arthropod taxonomic groups. IWET provides several advantages: it is non-destructive, cost-effective, and capable of processing large numbers of samples, making it particularly well-suited for biodiversity monitoring projects investigating changes in abundance and biomass, as well as for automating measurements such as specimen length, width and area.

en: arthropods body-size image-analysis automatic-detection allometric temperate biomass

en: IWET – Insect Weight Estimation Tool

title_for_slug: iwet-insect-weight-estimation-tool

en:
Resource Title: IWET_EnviDat.zip
    Size: 10255073 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/3d7e7b44-af7f-4824-84b8-fc2abd1f04b3/resource/7f5681bf-cf49-47b0-a8cc-a1e8dde61354/download/iwet_envidat.zip
    Description: IWET-Software with prorpriety and model files (inkl. materials)

en:
Resource Title: R-Script_and_suppl.zip
    Size: 2243953 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/3d7e7b44-af7f-4824-84b8-fc2abd1f04b3/resource/6ca41ee8-bda9-4e65-b859-1dd9c0184c50/download/r-script_and_suppl.zip
    Description: R Script for Regression models

allometric

display_name: allometric

arthropods

display_name: arthropods

automatic-detection

display_name: automatic-detection

biomass

display_name: biomass

body-size

display_name: body-size

image-analysis

display_name: image-analysis

temperate

display_name: temperate


en:
This dataset contains all necessary data to reproduce the validation simulations performed in the linked manuscript.
The validation data includes:
- 2 cm DEM of the study site Weissfluhjoch. For the 3 cm DEM of the study site Chant Sura, see [this dataset](https://www.doi.org/10.16904/envidat.174).
- roughness index rasters for both study sites
- rock point clouds of EOTA and Real Equant shapes
- release points used in the validation simulations of both study sites
- a sample XML input file for the rockfall simulator

en: validation numerical-simulation surface-roughness natural-hazards rockfall

envidat

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

en: EnviDat: the Environmental Data Portal

en: Validation Data for Rockfall Simulations with Geometric Roughness Model

en:
Resource Title: Release Points
    Size: 4649 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/636d34b5-5031-4bb6-aa28-b3d1cb11b80e/download/release.zip
    Description: Release points used in the validation simulations of both study sites. Use the *.txt files as input for the simulator.

en:
Resource Title: DEM Weissfluhjoch
    Size: 1005521469 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/9598c524-85b4-4dad-981c-59a126314973/download/dem_weissfluhjoch_2cm.tif
    Description: Digital Elevation Model (DEM) of validation test site Weissfluhjoch with a grid resolution of 2 cm. The DEM for test site Chant Sura can be found in the linked dataset.

en:
Resource Title: Roughness Index Rasters
    Size: 36884 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/2c863503-c73d-4b97-a660-d2998b717093/download/roughness.zip
    Description: Roughness index rasters used for the validation simulations. They have a resolution of 3 m.

en:
Resource Title: Rock Pointclouds
    Size: 3779 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/c99baa33-50ba-480a-8e4b-82450130900b/download/rocks.zip
    Description: Rock point clouds of EOTA and Real Equant shapes

en:
Resource Title: Sample Simulation
    Size: 126372 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/230c5218-e7a2-4e4f-8633-0c00695cff71/download/sample_sim.zip
    Description: This dataset contains a small sample simulation to showcase the recommended folder/file structure to run rockfall simulations. The input parameters for the simulation can be changed in the XML file, which is then also used as input for the rockfall simulator.

natural-hazards

display_name: natural-hazards

numerical-simulation

display_name: numerical-simulation

rockfall

display_name: rockfall

surface-roughness

display_name: surface-roughness

validation

display_name: validation