maintainer: Bundesamt für Energie BFE

de: ogd103-bfe versorgungssicherheit landesverbrauch-strom endverbrauch-strom

fr: energiedashboard.ch: Consommation en électricité Swissgrid

en: energiedashboard.ch: Electricity consumption Swissgrid

it: energiedashboard.ch: Consumo di elettricità Swissgrid

label: swissgrid

label: ENTSO-E

fr: Consommation estimée modélisée

de: Modellbasiert geschätzter Verbrauch

en: Model-based estimated consumption

it: Consumo stimato modellizzato

fr: Les données actuelles ne sont pas disponibles, c'est pourquoi un modèle doit être utilisé pour estimer la consommation sur la base du passé.

en: Real-time data is not available, so a model must be used to estimate consumption based on the past.

de: Zeitnahe Daten sind nicht verfügbar, weshalb mit einem Modell der Verbrauch auf Basis der Vergangenheit geschätzt werden muss.

it: I dati in tempo reale non sono disponibili, quindi è necessario utilizzare un modello per stimare il consumo in base al passato.

fr: Consommation nationale et finale

de: Landesverbrauch und Endverbrauch

en: Nation and final consumtion

it: Consumo nazionale e finale

fr:
La consommation nationale, y compris la consommation des pompes de stockage, est un indicateur important en ce qui concerne l'approvisionnement en électricité. L'évolution est d'abord présentée sur la base des données communiquées à Swissgrid par les gestionnaires de réseau de distribution. Ces données peuvent être incomplètes ou erronées et sont corrigées ultérieurement.

La consommation finale indique la quantité d'électricité consommée par les ménages, le commerce, l'agriculture, les services, l'industrie et les transports. C'est le paramètre le plus important pour les efforts d'économie des Suisses. L'évolution est d'abord présentée sur la base des données communiquées à Swissgrid par les gestionnaires de réseau de distribution. Ces données peuvent être incomplètes ou erronées et sont corrigées.

en:
National consumption, including the consumption of storage pumps, is an important indicator in relation to the electricity supply. The trend is initially presented on the basis of data reported to Swissgrid by distribution grid operators. This data may be incomplete or incorrect and is subsequently corrected.

Final consumption indicates how much electricity is consumed by households, commerce, agriculture, services, industry and transport. It is the decisive factor when it comes to the Swiss' efforts to save energy. The trend is initially presented on the basis of data reported to Swissgrid by distribution grid operators. These data may be incomplete or incorrect and are corrected.

de:
Der Landesverbrauch inklusive des Verbrauchs der Speicherpumpen ist ein wichtiger Indikator in Bezug auf die Stromversorgung. Der Verlauf wird zunächst auf Basis von durch Verteilnetzbetreiber an Swissgrid gemeldeten Daten dargestellt. Diese Daten können unvollständig oder fehlerhaft sein und werden nachkorrigiert.

Der Endverbrauch gibt an, wieviel Strom durch Haushalte, Gewerbe, Landwirtschaft, Dienstleistungen, Industrie und Verkehr verbraucht wird. Wenn es um Sparbemühungen der Schweizer geht ist er die massgebliche Grösse. Der Verlauf wird zunächst auf Basis von durch Verteilnetzbetreiber an Swissgrid gemeldeten Daten dargestellt. Diese Daten können unvollständig oder fehlerhaft sein und werden nachkorrigiert.

it:
Il consumo nazionale, compreso il consumo delle pompe di accumulo, è un indicatore importante in relazione alla fornitura di elettricità. Il trend viene inizialmente presentato sulla base dei dati riferiti a Swissgrid dai gestori delle reti di distribuzione. Questi dati possono essere incompleti o errati e vengono successivamente corretti.

Il consumo finale indica la quantità di elettricità consumata dalle famiglie, dal commercio, dall'agricoltura, dai servizi, dall'industria e dai trasporti. È il fattore decisivo quando si tratta degli sforzi degli svizzeri per risparmiare energia. Il trend viene inizialmente presentato sulla base dei dati riferiti a Swissgrid dai gestori delle reti di distribuzione. Questi dati possono essere incompleti o errati e vengono corretti.

fr:
La consommation nationale de la Suisse, y compris la consommation des pompes d'accumulation des centrales de pompage-turbinage, est un indicateur important en ce qui concerne l'approvisionnement en électricité. Il est important de différencier les chiffres de la consommation. La consommation nationale comprend la consommation totale des ménages, de l'artisanat, de l'agriculture, des services, de l'industrie et des transports (ce que l'on appelle la consommation finale), plus les pertes de transport et de distribution (pertes de réseau). La consommation actuellement affichée comprend, outre la consommation nationale, la consommation d'électricité pour le fonctionnement des pompes de stockage.

La tendance indique l'évolution de la consommation nationale, y compris la consommation des pompes de stockage, par rapport à la consommation moyenne des 10 derniers jours. La valeur prévisionnelle indique la consommation nationale, y compris la consommation des pompes de stockage, estimée sur la base d'un modèle dans 5 jours.

Consommation nationale, y compris la consommation des pompes de stockage, sur les dernières semaines

La consommation d'électricité dépend également de l'utilisation des pompes de stockage. Plus les chiffres sont éloignés dans le temps, plus ils sont robustes. Les données proviennent des gestionnaires de réseau de distribution, qui les communiquent chaque mois à Swissgrid. Ces données peuvent être incomplètes ou erronées et sont corrigées ultérieurement. Ces données de Swissgrid remontent au mieux à 1 mois. Les données de consommation mesurées en temps réel ne sont pas disponibles. Pour déterminer la consommation nationale actuelle, y compris la consommation des pompes de stockage, des modèles sont utilisés. Ces modèles ne tiennent pas compte de l'évolution des températures en Suisse, mais des changements de comportement de la population, par exemple des réactions aux appels à l'économie d'énergie. De tels changements de comportement ne peuvent être détectés que par des données de consommation mesurées.

Consommation finale actuelle sur les dernières semaines

La consommation finale est l'énergie électrique consommée par l'économie, les transports et les ménages privés. Les éventuels efforts d'économie d'électricité peuvent certes être interprétés à partir de ce graphique, mais doivent être considérés comme purement indicatifs en raison de la disponibilité des données. Le graphique se base avant tout sur les données communiquées par le passé à Swissgrid par les gestionnaires de réseau de distribution et corrigées ultérieurement. En raison des incertitudes concernant les données relatives à la consommation finale, l'OFEN a spécialement fait développer un modèle de consommation finale à l'aide des méthodes de science des données les plus récentes, telles que l'apprentissage automatique.

Graphique d'expert comparant les sources de données relatives à la consommation nationale, y compris la consommation des pompes de stockage.

Les analyses montrent qu'il existe différentes différences entre les principales sources de données relatives à la consommation. Ces différences sont illustrées afin de permettre une évaluation des informations qui ont circulé jusqu'à présent. Ces différences s'expliquent par différentes raisons, telles que des approches méthodologiques et des délimitations différentes. Mais les différences sont également dues à des corrections et à des informations complémentaires fournies par le secteur.  Pour la comparaison sur une base mensuelle, les statistiques de l'OFEN sont utilisées comme base et critère de mesure.

Disclaimer Données

Les données relatives à la consommation ne sont pas satisfaisantes. Différentes sources existent, avec des approches méthodologiques différentes. La source la plus fiable est la statistique de l'OFEN, qui ne fournit cependant que des valeurs sur une base mensuelle et qui est actuellement publiée avec un retard d'environ 2 mois.  Il existe également des données de Swissgrid, basées sur les déclarations des gestionnaires de réseau de distribution. Ces données basées sur des valeurs mesurées sont entachées d'incertitudes, car les gestionnaires de réseau de distribution font régulièrement des déclarations erronées, des déclarations complémentaires et des corrections, parfois jusqu'à 6 mois après la publication. Pour que des valeurs actuelles puissent être indiquées, il faut travailler avec des modèles. Ceux-ci tiennent compte des données du passé et notamment des statistiques de l'OFEN. Pour une estimation actuelle de la consommation finale, l'OFEN a fait développer un modèle de science des données utilisant l'apprentissage automatique moderne. Ce modèle prévoit la consommation finale, mais ne peut reproduire que partiellement les changements de comportement importants au sein de la population. L'OFEN travaille actuellement sur de meilleures approches avec le secteur de l'électricité.

en:
The national consumption of Switzerland, including the consumption of the storage pumps of the pumped storage power plants, is an important indicator with regard to the electricity supply. When it comes to consumption, it is essential to differentiate between various figures. National consumption includes the total consumption of households, commerce, agriculture, services, industry and transport (the so-called final consumption) plus transmission and distribution losses (grid losses). In addition to the national consumption, the currently reported consumption also includes the electricity consumption for the operation of the storage pumps.

The trend shows the development of the national consumption including the consumption of the storage pumps compared to the average consumption of the last 10 days. The forecast value indicates the model-based estimated country consumption including the consumption of the storage pumps in 5 days.

Country consumption including consumption of storage pumps over the last few weeks

The electricity consumption also depends on the use of the storage pumps. The further back the figures go, the more reliable they are. The data comes from distribution grid operators, who report the data to Swissgrid on a monthly basis. This data can be incomplete or incorrect and is subsequently corrected. At best, this data from Swissgrid goes back 1 month. Timely measured consumption data are not available. Models are used to determine the current national consumption, including the consumption of the storage pumps. These models do not take into account the temperature development in Switzerland, but they do not take into account changes in the behaviour of the population, for example the reaction to calls to save energy. Such behavioural changes can only be recorded using measured consumption data.

Current final consumption over the last few weeks

The final consumption is the electrical energy consumed by the economy, transport and private households. Any efforts to save electricity can be interpreted from this graph, but must be considered purely indicative due to the data situation. The graph is based primarily on the data reported to Swissgrid in the past by distribution grid operators and subsequently corrected. Due to the uncertainties in the data on final consumption, the SFOE has had a model of final consumption specially developed using the latest data science methods such as machine learning.

Expert graph comparing data sources on national consumption including consumption of storage pumps.

Analyses show that there are various differences between the most important data sources on consumption. These differences are illustrated to enable an assessment of the information that has been circulating so far. The differences have various reasons, such as different methodological approaches and delimitations. However, differences also occur due to corrections and follow-up reports from the industry.  For comparison on a monthly basis, the SFOE statistics are used as a basis and yardstick.

Disclaimer Data

The data situation on consumption is not satisfactory. Different sources exist that follow different methodological approaches. Of these, the most reliable source is the SFOE statistics, which, however, only offer values on a monthly basis and are currently published with a delay of about 2 months.  In addition, there is data from Swissgrid, which is based on reports from the distribution grid operators. These data are based on measured values and are subject to uncertainties, as there are always false reports, subsequent reports and corrections by the distribution grid operators, sometimes up to 6 months after publication. In order to be able to provide current values, models must be used. These take into account past data and, in particular, SFOE statistics. For a current estimate of end consumption, the SFOE has had a data science model developed using modern machine learning. This model forecasts final consumption, but is only able to partially reproduce major changes in the population's behaviour. The SFOE is currently working on better approaches with the electricity industry.

de:
Der Landesverbrauch der Schweiz inklusive des Verbrauchs der Speicherumpen der Pumpspeicherkraftwerke ist ein wichtiger Indikator in Bezug auf die Stromversorgung. Beim Verbrauch gilt es unbedingt zwischen verschiedenen Zahlen zu differenzieren. Der Landesverbrauch enthält den gesamten Verbrauch von Haushalten, Gewerbe, Landwirtschaft, Dienstleistungen, Industrie und Verkehr (der sogenannte Endverbrauch) zuzüglich Übertragungs- und Verteilverluste (Netzverluste). Im aktuell ausgewiesenen Verbrauch ist neben dem Landesverbrauch auch der Stromverbrauch für den Betrieb der Speicherpumpen enthalten.

Der Trend zeigt die Entwicklung des Landesverbrauches inklusive des Verbrauches der Speicherpumpen im Vergleich zum durchschnittlichen Verbrauch der letzten 10 Tage an. Der prognostizierte Wert gibt den modellbasiert geschätzten Landesverbrauch inklusive des Verbrauches der Speicherpumpen in 5 Tagen an.

Landesverbrauch inklusive Verbrauch Speicherpumpen über die letzten Wochen

Der Stromverbrauch hängt auch vom Einsatz der Speicherpumpen ab. Je weiter die Zahlen zurückliegen, desto belastbarer sind sie. Die Daten stammen von Verteilnetzbetreibern, die die Daten monatlich an Swissgrid melden. Diese Daten können unvollständig oder fehlerhaft sein und werden nachkorrigiert. Diese Daten der Swissgrid reichen bestenfalls 1 Monat zurück. Zeitnahe gemessenen Verbrauchsdaten sind nicht verfügbar. Um den aktuellen Landesverbrauch inklusive des Verbrauchs der Speicherpumpen zu ermitteln, werden Modelle herangezogen. Diese Modelle berücksichtigen die Temperaturentwicklung in der Schweiz nicht aber Verhaltensänderungen der Bevölkerung, also beispielsweise Reaktion auf Aufrufe zum Energiesparen. Solche Verhaltensänderungen können nur über gemessene Verbrauchsdaten erfasst werden.

Aktueller Endverbrauch über die letzten Wochen

Der Endverbrauch ist die durch Wirtschaft, Verkehr und Privathaushalte verbrauchte elektrische Energie. Allfällige Anstrengungen zu Stromeinsparungen können aus dieser Grafik zwar interpretiert werden, müssen aber aufgrund der Datenlage als rein indikativ gelten. Die Grafik basiert vor allem auf den in der Vergangenheit durch Verteilnetzbetreiber an Swissgrid gemeldete und nachkorrigierte Daten. Aufgrund der Unsicherheiten in der Datenlage zum Endverbrauch hat das BFE eigens ein Modell des Endverbrauchs mit neuesten Data Science Methoden wie dem maschinellen Lernen entwickeln lassen.

Expertengrafik zum Vergleich der Datenquellen zum Landesverbrauch inklusive Verbrauch der Speicherpumpen.

Analysen zeigen, dass es verschiedene Unterschiede zwischen den wichtigsten Datenquellen zum Thema Verbrauch gibt. Diese Unterschiede werden veranschaulicht, damit eine Einschätzung der bisher kursierenden Information möglich wird. Die Unterschiede haben verschiedene Gründe, wie etwa unterschiedliche methodologische Ansätze und Abgrenzungen. Unterschiede kommen aber auch durch Korrekturen und Nachmeldungen aus der Branche zustande.  Zum Vergleich auf Monatsbasis wird die BFE Statistik als Grundlage und Messlatte herangezogen.

Disclaimer Daten

Die Datenlage zum Verbrauch ist nicht zufriedenstellend. Es existieren unterschiedliche Quellen, die unterschiedliche methodologische Ansätze verfolgen. Davon ist die belastbarste Quelle die BFE Statistik, welche jedoch nur Werte auf Monatsbasis bietet und derzeit mit Verzug von etwa 2 Monaten erscheint.  Daneben gibt es Daten der Swissgrid, die auf Meldungen der Verteilnetzbetreiber basieren. Diese Daten basieren auf Messwerten sind mit Unsicherheiten behaftet, da es immer wieder zu Fehlmeldungen, Nachmeldungen und Korrekturen seitens der Verteilnetzbetreiber kommt, teilweise bis zu 6 Monate nach der Veröffentlichung. Damit aktuelle Werte angegeben werden können muss mit Modellen gearbeitet werden. Diese berücksichtigen Daten der Vergangenheit und insbesondere der BFE Statistik. Für eine aktuelle Schätzung des Endverbrauchs hat das BFE ein Data Science Modell unter Nutzung modernen Maschinenlernens entwickeln lassen. Es prognostiziert den Endverbrauch, vermag aber grosse Verhaltensänderungen in der Bevölkerung nur ansatzweise nachzubilden. Das BFE arbeitet derzeit an besseren Ansätzen mit der Strombranche.

it:
Il consumo nazionale della Svizzera, compreso il consumo delle pompe di accumulo delle centrali elettriche con sistema di pompaggio, è un indicatore importante per quanto riguarda l'approvvigionamento elettrico. Quando si parla di consumi, è fondamentale distinguere tra varie cifre. Il consumo nazionale comprende il consumo totale delle famiglie, del commercio, dell'agricoltura, dei servizi, dell'industria e dei trasporti (il cosiddetto consumo finale) più le perdite di trasmissione e distribuzione (perdite di rete). Oltre al consumo nazionale, il consumo attualmente riportato include anche il consumo di elettricità per il funzionamento delle pompe di accumulo.

Il trend mostra l'andamento del consumo nazionale, incluso il consumo delle pompe di accumulo, rispetto al consumo medio degli ultimi 10 giorni. Il valore di previsione indica il consumo stimato del Paese basato sul modello, incluso il consumo delle pompe di accumulo in 5 giorni.

Consumo del Paese incluso il consumo delle pompe di accumulo nelle ultime settimane

Il consumo di elettricità dipende anche dall'uso delle pompe di accumulo. Più le cifre vanno indietro, più sono affidabili. I dati provengono dagli operatori delle reti di distribuzione, che li riportano a Swissgrid su base mensile. Questi dati possono essere incompleti o errati e vengono successivamente corretti. Questi dati di Swissgrid risalgono al massimo a 1 mese fa. Non sono disponibili dati di consumo misurati tempestivamente. I modelli vengono utilizzati per determinare il consumo nazionale attuale, compreso il consumo delle pompe di accumulo. Questi modelli non tengono conto dell'andamento della temperatura in Svizzera, ma non tengono conto dei cambiamenti nel comportamento della popolazione, ad esempio la reazione alle richieste di risparmio energetico. Tali cambiamenti comportamentali possono essere registrati solo utilizzando dati di consumo misurati.

Consumo finale attuale nelle ultime settimane

Il consumo finale è l'energia elettrica consumata dall'economia, dai trasporti e dalle famiglie. Qualsiasi sforzo per risparmiare energia elettrica può essere interpretato da questo grafico, ma deve essere considerato puramente indicativo a causa della situazione dei dati. Il grafico si basa principalmente sui dati riferiti a Swissgrid in passato dai gestori delle reti di distribuzione e successivamente corretti. A causa delle incertezze dei dati sul consumo finale, l'UFE ha fatto sviluppare appositamente un modello di consumo finale utilizzando i più recenti metodi di scienza dei dati come il machine learning.

Grafico di esperti che confronta le fonti di dati sul consumo nazionale, compreso il consumo di pompe di accumulo.

Le analisi mostrano che esistono varie differenze tra le fonti di dati più importanti sul consumo. Queste differenze sono illustrate per consentire una valutazione delle informazioni che sono circolate finora. Le differenze hanno varie ragioni, come approcci metodologici e delimitazioni diverse. Tuttavia, le differenze si verificano anche a causa delle correzioni e dei rapporti di follow-up del settore.  Per il confronto su base mensile, si utilizzano le statistiche dell'UFE come base e metro di paragone.

Dati disclaimer

La situazione dei dati sul consumo non è soddisfacente. Esistono diverse fonti che seguono approcci metodologici differenti. Di queste, la fonte più affidabile è la statistica dell'UFE, che però offre solo valori su base mensile e attualmente viene pubblicata con un ritardo di circa 2 mesi.  Inoltre, ci sono i dati di Swissgrid, che si basano sui rapporti degli operatori della rete di distribuzione. Questi dati si basano su valori misurati e sono soggetti a incertezze, poiché ci sono sempre segnalazioni false, segnalazioni successive e correzioni da parte degli operatori della rete di distribuzione, a volte fino a 6 mesi dopo la pubblicazione. Per poter fornire i valori attuali, è necessario utilizzare dei modelli. Questi tengono conto dei dati passati e, in particolare, delle statistiche dell'OFE. Per una stima attuale del consumo finale, l'UFE ha fatto sviluppare un modello di scienza dei dati utilizzando il moderno apprendimento automatico. Questo modello prevede il consumo finale, ma è in grado di riprodurre solo parzialmente i principali cambiamenti nel comportamento della popolazione. L'UFE sta attualmente lavorando per migliorare gli approcci con l'industria elettrica.

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

energy

fr: Energie

de: Energie

en: Energy

it: Energia

politics

fr: Politique

de: Politik

en: Politics

it: Politica

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

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

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


maintainer: Open Data Zürich

state: active

type: dataset

media_type: text/csv

format: CSV

mimetype: text/csv

media_type: application/pdf

format: PDF

mimetype: application/pdf

de: Die täglich aktualisierten **Zähldaten** werden vom Tiefbauamt der Stadt Zürich in eigener Regie erhoben. Die Zählstellen sind über das Stadtgebiet verteilt. Die Standorte sind auch über das [Geodatenportal](https://www.stadt-zuerich.ch/geodaten/download/Standorte_der_automatischen_Fuss__und_Velozaehlungen) erhältlich und können über das Attribut FK_ZAEHLER in Beziehung gesetzt werden. Die Erfassung des **Veloverkehrs** erfolgt mittels im Strassenbelag eingelassenen **Induktionsschlaufen**. Der **Fussverkehr** wird durch **passive Infrarotstrahlung** gezählt.

dtoer

display_name: dtoer

fussgaengerzaehlung

display_name: fussgaengerzaehlung

fussverkehr

display_name: fussverkehr

langsamverkehr

display_name: langsamverkehr

messwerte

display_name: messwerte

planung

display_name: planung

punktdaten

display_name: punktdaten

sachdaten

display_name: sachdaten

standort

display_name: standort

veloverkehr

display_name: veloverkehr

velozaehlung

display_name: velozaehlung

zaehlung

display_name: zaehlung

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

name: Tiefbauamt, Abteilung Verkehr + Stadtraum, Tiefbau- und Entsorgungsdepartement

stadt-zurich

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

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

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

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

de: Daten der automatischen Fussgänger- und Velozählung - Viertelstundenwerte


staatsquote-des-kantons-zurich

title_for_slug: staatsquote-des-kantons-zurich

name: Finanzverwaltung des Kantons Zürich, Steuerung Finanzhaushalt

label: Regierungsratsbeschluss Nr. 373/2022

label: Geschäftsbericht & Rechnung (Teil III: Finanzbericht)

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

de: Staatsquote des Kantons Zürich ab 2008

de: Variabeln: 'gesamtausgaben' und 'bruttoinlandprodukt' in Tausend CHF.

de: Die Staatsquote entspricht den «konsolidierten Gesamtausgaben» in Prozent des kantonalen Bruttoinlandprodukts (BIP). Die «konsolidierten Gesamtausgaben» umfassen die Ausgaben (Aufwand ohne Abschreibungen, Einlagen in Bestandeskonti von Fonds im Eigen- und Fremdkapital, durchlaufende Beiträge und interne Verrechnungen) plus Bruttoinvestitionen. Die konsolidierten Gesamtausgaben werden durch die Eidgenössischen Finanzverwaltung (EFV) berechnet. Das BIP des Kantons Zürich wird vom Bundesamt für Statistik (BFS) berechnet. Beide Wirtschaftsindikatoren werden mit einer zeitlichen Verzögerung von zwei Jahren veröffentlicht. Vorliegend wird die Staatsquote des Kantons ohne Gemeinden ausgewiesen. Für die interkantonale Vergleichbarkeit müsste die Staatsquote des Kantons und seiner Gemeinden betrachtet werden, aufgrund der je nach Kanton unterschiedlichen Aufgabenteilungen zwischen Kanton und Gemeinden.

finanzkennzahlen

display_name: finanzkennzahlen

oeffentlichefinanzen

display_name: oeffentlichefinanzen

staatsfinanzen

display_name: staatsfinanzen

finanzverwaltung-kanton-zuerich

de: Finanzverwaltung Kanton Zürich

de: Der Kanton Zürich hat, nach dem Bund, den zweitgrössten öffentlichen Haushalt der Schweiz. Die Finanzverwaltung ist verantwortlich für die Planung, Führung und Überwachung dieses Finanzhaushalts. Sie erstellt das Budget und den Jahresabschluss der kantonalen Verwaltung und publiziert den Geschäftsbericht. Zudem übernimmt sie das operative Rechnungswesen und sichert mit der Tresorie die Zahlungsbereitschaft des Kantons. Die Finanzverwaltung bildet die finanzielle Schnittstelle zum Bund und den anderen Kantonen, beispielsweise für den nationalen Finanzausgleich.

political_level: canton

kanton-zuerich

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: ZH-Kt Finanzverwaltung - DCAT Harvester

de: Staatsquote des Kantons Zürich


energiedashboard-ch-energiepreise

maintainer: Digital Innovation Office

title_for_slug: energiedashboard.ch: Energiepreise

de: ogd106-bfe strom gas mineralol treibstoffe

fr: energiedashboard.ch: Prix de l'énergie

de: energiedashboard.ch: Energiepreise

en: energiedashboard.ch: Energy prices

label: European Power Exchange

label: European Energy Exchange - Gas

label: European Energy Exchange - Strom

fr: Indice des prix du Diesel: Consommation finale (indice national des prix à la consommation)

de: Dieselpreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index Diesel final consumption (national consumer price index)

it: Indice dei prezzi del Diesel per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix finaux du diesel selon l'indice des prix à la consommation en Suisse

en: Development of end consumer prices for diesel according to the national consumer price index in Switzerland

de: Entwicklung der Endverbraucherpreise Diesel gemäss Landesindex der Konsumentenpreise in der Schweiz

it: Andamento dei prezzi al consumo finale del diesel in base all'indice nazionale dei prezzi al consumo in Svizzera

fr: Prix du gaz TTF "premier mois" (indexé)

de: Gaspreis TTF «Frontmonat» (indexiert)

en: Gas price TTF "front month" (indexed)

it: Prezzo del gas TTF "mese anteriore" (indicizzato)

fr: Évolution des prix du gaz sur le point d'échange TTF pour le mois suivant, c'est-à-dire les prix du gaz à l'achat pour la livraison du mois suivant. Les prix sont indexés sur le prix moyen 2019-2020

en: Development of gas prices on the TTF trading point for the following month, i.e. the gas prices in the purchase for delivery in the coming month. The prices are indexed to the average price 2019-2020

de: Entwicklung der Gaspreise auf dem TTF Handelspunkt für den Folgemonat, also die Gaspreise im Einkauf für die Lieferung im kommenden Monat. Die Preise sind indexiert auf den Durchschnittspreis 2019-2020.

it: Sviluppo dei prezzi del gas sul punto di negoziazione TTF per il mese successivo, ossia i prezzi del gas nell'acquisto per la consegna nel mese successivo. I prezzi sono indicizzati al prezzo medio del 2019-2020

fr: Indice des prix de la consommation finale de gaz (indice national des prix à la consommation)

de: Gaspreisindex Endverbraucher (Landesindex Konsumentenpreise)

en: Price index gas final consumption (national consumer price index)

it: Indice dei prezzi del gas per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix du gaz à la consommation finale indexés selon l'indice des prix à la consommation en Suisse. La base est le prix en décembre 2020 (=100)

en: Development of end consumer prices for gas indexed according to the national consumer price index in Switzerland. The basis is the prices in December 2020 (=100)

de: Entwicklung der Endverbraucherpreise Gas indexiert gemäss Landesindex der Konsumentenpreise in der Schweiz. Basis sind die Preise im Dezember 2020 (=100)

it: Andamento dei prezzi al consumo finali del gas indicizzati secondo l'indice nazionale dei prezzi al consumo in Svizzera. La base è costituita dai prezzi del dicembre 2020 (=100)

fr: Prix de l'électricité sur le marché spot "Day Ahead" Base Suisse

de: Strompreis Spotmarkt «Day Ahead» Base

en: Electricity Price Spot Market "Day Ahead" Base Switzerland

it: Prezzo dell'elettricità Mercato spot "Day ahead" Base Svizzera

fr: Évolution des prix de détail de l'électricité indexés selon l'indice des prix à la consommation en Suisse. La base est le prix en décembre 2020 (=100)

en: Development of electricity end-user prices indexed according to the national consumer price index in Switzerland. The basis is the prices in December 2020 (=100)

de: Entwicklung der Strompreise auf den Spotmärkten für «day ahead» Preise, also die Strompreise im Einkauf für den Konsum morgen.

it: Andamento dei prezzi dell'elettricità per gli utenti finali, indicizzati secondo l'indice nazionale dei prezzi al consumo in Svizzera. La base è costituita dai prezzi del dicembre 2020 (=100)

fr: Indice des prix du mazout Consommation finale (indice national des prix à la consommation)

de: Heizölpreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index for final heating oil consumption (national consumer price index)

it: Indice dei prezzi per il consumo finale di gasolio da riscaldamento (indice nazionale dei prezzi al consumo)

fr: Évolution des prix du mazout à la consommation finale indexés selon l'indice des prix à la consommation en Suisse. La base est le prix en décembre 2020 (=100)

en: Development of end consumer prices for heating oil indexed according to the national consumer price index in Switzerland. The basis is the prices in December 2020 (=100)

de: Entwicklung der Endverbraucherpreise Heizöl indexiert gemäss Landesindex der Konsumentenpreise in der Schweiz. Basis sind die Preise im Dezember 2020 (=100)

it: Andamento dei prezzi finali al consumo per il gasolio da riscaldamento, indicizzati secondo l'indice nazionale dei prezzi al consumo in Svizzera. La base è costituita dai prezzi del dicembre 2020 (=100)

fr: Indice des prix de l'essence Consommation finale (indice national des prix à la consommation)

de: Benzinpreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index petrol final consumption (national consumer price index)

it: Indice dei prezzi della benzina per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix de détail de l'essence indexés selon l'indice des prix à la consommation en Suisse. La base est le prix en décembre 2020 (=100)

en: Development of end consumer prices for petrol indexed according to the national consumer price index in Switzerland. The basis is the prices in December 2020 (=100)

de: Entwicklung der Endverbraucherpreise Benzin indexiert gemäss Landesindex der Konsumentenpreise in der Schweiz. Basis sind die Preise im Dezember 2020 (=100)

it: Andamento dei prezzi al consumo finali della benzina indicizzati secondo l'indice nazionale dei prezzi al consumo in Svizzera. La base è costituita dai prezzi del dicembre 2020 (=100)

fr: Indice des prix de l'électricité Consommation finale (indice national des prix à la consommation)

de: Strompreisindex Endverbraucher (Landesindex Konsumentenpreise)

en: Price index electricity final consumption (national consumer price index)

it: Indice dei prezzi dei consumi finali di elettricità (indice nazionale dei prezzi al consumo)

de: Entwicklung der Endverbraucherpreise Strom indexiert gemäss Landesindex der Konsumentenpreise in der Schweiz. Basis sind die Preise im Dezember 2020 (=100)

fr: Indice des prix du bois de chauffage: Consommation finale (indice national des prix à la consommation)

de: Brennholzpreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index firewood final consumption (national consumer price index)

it: Indice dei prezzi della legna da ardere per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix finaux du bois de chauffage selon l'indice des prix à la consommation en Suisse

en: Development of end consumer prices for firewood according to the national consumer price index in Switzerland

de: Entwicklung der Endverbraucherpreise Brennholz gemäss Landesindex der Konsumentenpreise in der Schweiz

it: Andamento dei prezzi al consumo finale della legna da ardere in base all'indice nazionale dei prezzi al consumo in Svizzera

fr: Indice des prix du chauffage à distance: Consommation finale (indice national des prix à la consommation)

de: Fernwärmepreis Endverbraucher (Landesindex Konsumentenpreise)

en: Price index district heating final consumption (national consumer price index)

it: Indice dei prezzi del teleriscaldamento per il consumo finale (indice nazionale dei prezzi al consumo)

fr: Évolution des prix finaux du chauffage à distance selon l'indice des prix à la consommation en Suisse

en: Development of end consumer prices for district heating according to the national consumer price index in Switzerland

de: Entwicklung der Endverbraucherpreise fernwärme gemäss Landesindex der Konsumentenpreise in der Schweiz

it: Andamento dei prezzi al consumo finale del teleriscaldamento in base all'indice nazionale dei prezzi al consumo in Svizzera

fr:
Les prix de l'énergie sur les marchés sont un indicateur important de la situation actuelle du marché et de l'approvisionnement en Europe et en Suisse. L'offre (production) y est combinée à la demande (consommation) et donne en fin de compte un prix pour un produit énergétique donné. Il existe des marchés pour différents produits. Les marchés spot donnent des signaux à court terme du marché : le marché "day ahead" indique le prix de gros pour le lendemain. Les prix du produit "Base" indiquent la moyenne arithmétique des prix pour une livraison dans les 24 heures suivantes. Le marché intrajournalier consiste à acheter et à vendre de l'énergie qui sera livrée le jour même.

Ce recueil de données fournit des informations sur différentes sources d'énergie. Il s'agit de l'électricité, du gaz, du mazout, du diesel et de l'essence. Différentes données sont utilisées à cet effet. Pour l'électricité et le gaz, ce sont les données des bourses qui sont utilisées. Contrairement aux prix de l'électricité, les données sur les prix du gaz sont référencées sur une année de base, car des questions de licence doivent encore être réglées. D'autres données sur les prix sont obtenues auprès de l'Office fédéral de la statistique.

Les prix de l'électricité et du gaz ne constituent toutefois pas directement le prix de détail que les clients privés et professionnels paient à leur entreprise locale de distribution d'énergie. Ces prix de détail dépendent entre autres de la stratégie d'approvisionnement (achat à long terme ou achat à court terme sur le marché) de l'entreprise locale d'approvisionnement en énergie. Dans le cas de l'électricité, le prix de détail dépend également de la part d'électricité produite dans les centrales électriques de l'entreprise, de la qualité de l'électricité (renouvelable ou non), des coûts de réseau et des taxes.

En ce qui concerne les prix de détail, l'indice des prix à la consommation (IPC) est déterminant. Il mesure l'évolution des prix (renchérissement) des biens et services importants pour les ménages privés (panier-type). Il indique de combien les biens de consommation ont augmenté par rapport au mois précédent, à l'année précédente ou à toute autre date antérieure. L'indice est basé sur le mois de décembre 2020. L'évolution des prix est mesurée à l'aide du panier de biens et services, qui comprend également les principales sources d'énergie - donc aussi l'électricité. La méthode de calcul est gérée par l'Office fédéral de la statistique.

en:
Energy prices on the markets are an important indicator of the current market and supply situation in Europe and Switzerland. Supply (production) is combined here with demand (consumption) and ultimately results in a price for a specific energy product. There are markets for different products. The spot markets give short-term signals from the market: the "Day Ahead" market indicates the wholesale price for the following day. The "Base" product prices indicate the arithmetic mean of the prices for a delivery in the following 24 hours. In intraday trading, energy is bought and sold for delivery on the same day.

This data collection provides information on various energy sources. These include electricity (power), gas, heating oil, diesel and petrol. Different data are used for this purpose. For electricity and gas, data from the stock exchanges are used. In contrast to electricity prices, the data on gas prices are referenced to a base year, as licensing issues still need to be clarified. Other price data is obtained from the Federal Statistical Office.

However, the prices for electricity and gas do not directly result in the end consumer price that private and commercial customers pay to their local energy supply company. These end-customer prices depend, among other things, on the procurement strategy (long-term purchases or short-term purchases on the market) of the local energy supply company. In the case of electricity, the end-user price also depends on the share of electricity produced in the utility's own power plants, the quality of the electricity (renewable or not), the grid costs and levies.

The national consumer price index (CPI) is decisive for end customer prices. It measures the price development (inflation) of goods and services that are important for private households (basket of goods). It shows by how much consumer goods have become more expensive compared to the previous month, the previous year or any other earlier point in time. The index is based on December 2020. The price development is measured on the basis of the basket of goods, which also includes the most important energy sources - i.e. also electricity. The calculation methodology is managed by the Federal Statistical Office.

de:
Die Energiepreise an den Märkten sind ein wichtiger Indikator für die aktuelle Markt- und Versorgungssituation in Europa und der Schweiz. Angebot (Produktion) wird hier mit der Nachfrage (Verbrauch) zusammengeführt und ergibt letztlich einen Preis für ein bestimmtes Energieprodukt. Es gibt Märkte für unterschiedliche Produkte. Die Spotmärkte geben kurzfristige Signale des Marktes wieder: Der «Day Ahead»-Markt gibt den Grosshandelspreis für den Folgetag an. Die Preise des Produktes «Base» geben das arithmetische Mittel der Preise für eine Lieferung in den folgenden 24 Stunden an. Beim Intraday-Handel wird Energie gekauft und verkauft, die noch am gleichen Tag geliefert wird.

Diese Datensammlung stellt Informationen zu verschiedenen Energieträgern bereit. Diese umfassen Elektrizität (Strom), Gas, Heizöl, Diesel und Benzin. Dabei werden unterschiedliche Daten herangezogen. Für Strom und Gas werden Daten der Börsen herangezogen. Die Daten zu den Gaspreisen sind im Gegensatz zu den Strompreise referenziert auf ein Basisjahr, da noch Lizenzfragen zu klären sind. Weitere Preisdaten werden vom Bundesamt für Statistik bezogen.

Die Preise für Strom und Gas ergeben allerdings nicht direkt den Endverbraucherpreis, den die Privat- und Gewerbekunden ihrem lokalen Energieversorgungsunternehmen bezahlen. Diese Endkundenpreise hängen unter anderem von der Beschaffungsstrategie (langfristig eingekauft oder kurzfristig am Markt besorgt) des lokalen Energieversorgungsunternehmen ab. Beim Strom hängt der Endverbrauchpreis auch vom Anteil an in eigenen Kraftwerken produzierten Strom, von der Qualität des Stromes (erneuerbar oder nicht), von den Netzkosten und Abgaben ab.

Hinsichtlich der Endkundenpreise ist der Landesindex der Konsumentenpreise (LIK) massgebend. Er misst die Preisentwicklung (Teuerung) der für die privaten Haushalte bedeutsamen Waren und Dienstleistungen (Warenkorb). Er zeigt, um wie viel die Konsumgüter gegenüber dem Vormonat, dem Vorjahr oder jedem anderen früheren Zeitpunkt teurer geworden sind. Der Index ist auf den Dezember 2020 bezogen. Die Preisentwicklung wird anhand des Warenkorbs gemessen, der auch die wichtigsten Energieträger - also auch Strom - enthält. Die Berechnungsmethodik wird durch das Bundesamt für Statistik verwaltet.

it:
I prezzi dell'energia sui mercati sono un importante indicatore dell'attuale situazione del mercato e dell'offerta in Europa e in Svizzera. L'offerta (produzione) si combina con la domanda (consumo) e alla fine si ottiene il prezzo di uno specifico prodotto energetico. Esistono mercati per prodotti diversi. I mercati spot forniscono segnali a breve termine dal mercato: il mercato "Day Ahead" indica il prezzo all'ingrosso per il giorno successivo. I prezzi dei prodotti "Base" indicano la media aritmetica dei prezzi per una consegna nelle 24 ore successive. Nel trading intraday, l'energia viene acquistata e venduta per la consegna nello stesso giorno.

Questa raccolta dati fornisce informazioni su varie fonti energetiche. Questi includono l'elettricità (corrente), il gas, il gasolio per riscaldamento, il diesel e la benzina. A tal fine vengono utilizzati diversi dati. Per l'elettricità e il gas si utilizzano i dati delle borse valori. A differenza dei prezzi dell'elettricità, i dati sui prezzi del gas sono riferiti a un anno base, poiché le questioni relative alle licenze devono ancora essere chiarite. Altri dati sui prezzi sono stati ottenuti dall'Ufficio federale di statistica.

Tuttavia, i prezzi dell'elettricità e del gas non si traducono direttamente nel prezzo al consumo finale che i clienti privati e commerciali pagano alla loro società di fornitura energetica locale. Questi prezzi per i clienti finali dipendono, tra l'altro, dalla strategia di approvvigionamento (acquisti a lungo termine o acquisti a breve termine sul mercato) dell'azienda fornitrice di energia locale. Nel caso dell'elettricità, il prezzo per l'utente finale dipende anche dalla quota di elettricità prodotta nelle centrali elettriche dell'azienda, dalla qualità dell'elettricità (rinnovabile o meno), dai costi di rete e dai prelievi.

L'indice nazionale dei prezzi al consumo (CPI) è determinante per i prezzi al cliente finale. Misura l'andamento dei prezzi (inflazione) di beni e servizi importanti per le famiglie (paniere di beni). Indica di quanto i beni di consumo sono diventati più costosi rispetto al mese precedente, all'anno precedente o a qualsiasi altro momento precedente. L'indice si basa su dicembre 2020. L'andamento dei prezzi è misurato sulla base di un paniere di beni che comprende anche le fonti energetiche più importanti, cioè anche l'elettricità. La metodologia di calcolo è gestita dall'Ufficio federale di statistica.

trade

fr: Commerce

de: Handel

en: Trade

it: Commercio

prices

fr: Prix

de: Preise

en: Prices

it: Prezzi

bundesamt-fur-energie-bfe

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

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

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

political_level: confederation


agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

en: Agriculture, forestry

it: Agricoltura, selvicoltura

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

de: baulinie eigentumsbeschrankungoreb nutzungsplanung wald zonenplan

label: geocat.ch permalink

spatial: Kanton Luzern

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

format: SERVICE

de: Zeigt die statischen Waldgrenzen aufgrund einer formellen Waldfeststellung durch die Dienststelle Landwirtschaft und Wald (lawa).

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

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

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

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

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

value: LU-Kt - Geocat Harvester

de: Statische Waldgrenzen


zonenplane

title_for_slug: zonenplane

de: baulinie eigentumsbeschrankungoreb grundeigentum nutzungsplanung raumplanung zonenplan

de: Zonenpläne regeln die zulässigen Nutzungen im Gebiet einer Gemeinde.

de: Zonenpläne


zonenplane-gewasserraum

title_for_slug: zonenplane-gewasserraum

de: fliessgewasser gewasserschutz nutzungsplanung oberflachengewasser raumplanung zonenplan

spatial: Schweiz

de: Gewässerraum aus den Zonenplan-Überlagerungen, unterschieden nach Freihaltezone und Grünzone.

de: Zonenpläne: Gewässerraum


maintainer: Tamara Bobst

de: schweizerinnen auslanderinnen

de: json

media_type: application/json

de: Mittlere Wohnbevölkerung nach Nationalität, Gemeinde und Jahr (seit 1980) (json)

format: JSON

mimetype: application/json

license: CC BY 3.0 CH

de: csv

de: Mittlere Wohnbevölkerung nach Nationalität, Gemeinde und Jahr (seit 1980) (csv)

de: Kantonale BevölkerungsstatistikDie mittlere Wohnbevölkerung entspricht dem gewichteten Durchschnitt der Quartalsbestände aus der kantonalen Bevölkerungsstatistik. Sie hat damit einen anderen zeitlichen Bezug als der in der kantonalen Bevölkerungsstatistik übliche Jahresendbestand. Die mittlere Wohnbevölkerung dient als Grundlage, wenn das Mittel der im Kanton niedergelassenen Personen über das gesamte Jahr interessiert und wird beispielsweise für die Berechnung des Baselbieter Finanzausgleichs verwendet. Die Berechnungsformel lautet von unten nach oben gerechnet wie folgt: ((1 x 4. Quartal Vorjahr) + (2 x 1. Quartal Jahr) + (2 x 2. Quartal Jahr) + (2 x 3. Quartal Jahr) + (1 x 4. Quartal Jahr)) / 8.

auslanderinnen

display_name: auslanderinnen

schweizerinnen

display_name: schweizerinnen

population

fr: Population

de: Bevölkerung

en: Population

it: Popolazione

kanton-basel-landschaft

fr: Canton de Bâle-Campagne

de: Kanton Basel-Landschaft

en: Canton of Basel-Country

it: Cantone di Basilea-Campagna

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

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

value: BL - DCAT


gestaltungsplane-perimeter

geography

de: Geographie

territory

de: Raum und Umwelt

title_for_slug: gestaltungsplane-perimeter

de: eigentumsbeschrankungoreb nutzungsplanung raumplanung sondernutzungsplanung

de: Datenshop

de: Produktansicht Geodatenshop

de: Perimeter der Gestaltungspläne

de: Geoinformation Kanton Luzern

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

de: Gestaltungspläne: Perimeter


kommunale-bebauungsplane

title_for_slug: kommunale-bebauungsplane

de: baulinie eigentumsbeschrankungoreb gebaude-und-anlagen nutzungsplanung raumplanung sondernutzungsplanung wirtschaftliche-aktivitaten

de: Objekte und Perimeter der kommunalen Bebauungspläne (Naturobjekte, Baulinien, Abgrenzungen, Baubereiche, Strassen, öffentlicher Raum, usw.)

de: Kommunale Bebauungspläne


waldflachen

agriculture

de: Land- und Forstwirtschaft

title_for_slug: waldflachen

de: forstwirtschaft nutzungsplanung vegetation wald

de: Wald nach Waldrecht, dieser umfasst unter anderem auch Waldstrassen, Gewässer und Gebäude innerhalb des Waldes.

name: Dienststelle Landwirtschaft und Wald (lawa)

de: Waldflächen


maintainer: EnviDat Support

en: shortwave-radiation longwave-radiation snow-height meteo-station gemstock

en: DATA ACCESS

media_type: SMET

en:
Meteo data at Gemsstock [Level 2 dataset](http://models.slf.ch/p/dataset-processing/).

fields      = timestamp TSS HS VW DW VW_MAX OSWR ISWR ILWR RECORD AUX_VOLTAGE LOGGER_VOLTAGE LW_SENSOR_TEMP VENTILATION_FLAG OLWR

en: Meteorological station at Gemstock (3021 m asl) in Canton Uri. The station includes in/out LW/SW and a snow height sensor.

gemstock

display_name: gemstock

longwave-radiation

display_name: longwave-radiation

meteo-station

display_name: meteo-station

shortwave-radiation

display_name: shortwave-radiation

snow-height

display_name: snow-height

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

value: Envidat Harvester

en: GEM2: Meteorological and snow station at Gemsstock (3021 m asl), Canton Uri, Switzerland


energiebilanz-der-schweiz

title_for_slug: Energiebilanz der Schweiz

de: bruttoenergieverbrauch ogd115-bfe sektoren inlandproduktion energiebilanz endenergieverbrauch

fr: Bilan énergétique de la Suisse

de: Energiebilanz der Schweiz

en: Switzerland energy balance

it: Bilancio energetico della Svizzera

media_type: CSV

de: Beispiel SPARQL Query auf LINDAS für den Energiebilanz der Schweiz

format: SPARQL

fr: Le bilan énergétique de la Suisse renseigne sur la production nationale, l'importation / l'exportation, le stockage, la transformation, la consommation propre, les pertes de transport et de réseau et la consommation des différentes sources d'énergie en Suisse sur une base annuelle. La production d'électricité et de chaleur à distance ainsi que l'input des agents énergétiques qui y est lié sont présentés par technologie de production. La consommation finale d'énergie de bois, de charbon, de déchets et de déchets industriels, de produits pétroliers, de gaz, d'autres énergies renouvelables (carburants biogènes, biogaz, soleil, chaleur ambiante), d'électricité et de chauffage à distance est présentée pour les secteurs des ménages, de l'industrie, des services, des transports et de la différence statistique, y compris l'agriculture.

en: Switzerland's energy balance provides information on domestic production, import / export, storage, conversion, own consumption, transport and grid losses and consumption of the various energy carriers in Switzerland on an annual basis. The production of electricity and district heating and the associated energy carrier input are presented by generation technology. The final energy consumption of wood, coal, waste and industrial waste, petroleum products, gas, other renewable energies (biogenic fuels, biogas, solar, environmental heat), electricity and district heating is shown for the sectors households, industry, services, transport and statistical difference incl. agriculture.

de: Die Energiebilanz der Schweiz gibt Auskunft über Inlandproduktion, Import / Export, Lagerhaltung, Umwandlung, Eigenverbrauch, Transport- und Netzverluste und Verbrauch der verschiedenen Energieträger in der Schweiz auf jährlicher Basis. Die Produktion von Elektrizität und Fernwärme und der damit verbundene Energieträgerinput werden nach Erzeugungstechnologien dargestellt. Der Endenergieverbrauch von Holz, Kohle, Müll und Industrieabfällen, Erdölprodukten, Gas, Übrige erneuerbare Energien (Biogene Treibstoffe, Biogas, Sonne, Umweltwärme), Elektrizität und Fernwärme wird für die Sektoren Haushalte, Industrie, Dienstleistungen, Verkehr und Statistische Differenz inkl. Landwirtschaft ausgewiesen.

it: Il bilancio energetico della Svizzera fornisce informazioni sulla produzione nazionale, l'importazione/esportazione, lo stoccaggio, la conversione, il consumo proprio, il trasporto e le perdite di rete e il consumo dei vari vettori energetici in Svizzera su base annua. La produzione di elettricità e di teleriscaldamento e il relativo apporto di vettori energetici sono presentati per tecnologia di generazione. Il consumo finale di energia di legno, carbone, rifiuti e scarti industriali, prodotti petroliferi, gas, altre energie rinnovabili (combustibili biogenici, biogas, solare, calore ambientale), elettricità e teleriscaldamento è mostrato per i settori famiglie, industria, servizi, trasporti e differenza statistica, inclusa l'agricoltura.

bruttoenergieverbrauch

display_name: bruttoenergieverbrauch

endenergieverbrauch

display_name: endenergieverbrauch

energiebilanz

display_name: energiebilanz

inlandproduktion

display_name: inlandproduktion

sektoren

display_name: sektoren

energy

fr: Energie

de: Energie

en: Energy

it: Energia

territory

de: Raum und Umwelt

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

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

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

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


en: qgis-plugin cable-yarding geoinformation-system raster-processing swiss-geodata seilaplan digital-planning geodata-processing open-source digital-elevation-model

en: View video on youtube!

en: DHM-Kacheln zusammenfügen

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. In this tutorial video, we show how to merge multiple DTM raster tiles into one file, using the QGIS tool ‘Virtual Raster’. This simplifies the digital planning of a cable line using the QGIS plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to Seilaplan website: https://seilaplan.wsl.ch

***************************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. In diesem Tutorialvideo zeigen wir, wie man mit dem QGIS-Plugin Virtuelles Raster mehrere DHM-Kacheln zu einem einzigen Rasterfile zusammenfügen und abspeichern kann. Für die Seillinienplanung mit Seilaplan muss nun nur noch eine Datei, mein neues virtuelles Raster, ausgewählt werden.

Link zur Seilaplan-Website: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geodata-processing

display_name: geodata-processing

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

raster-processing

display_name: raster-processing

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

en: Seilaplan Tutorial: Merge DTM tiles


en: satellite hazard-mapping natural-hazard avalanche snow

en: SPOT6 Avalanche outlines 24 January 2018

media_type: SHP

en: Shapefile of the manually mapped avalanche outlines. Please only use this data together with the example key document provided with this dataset.

format: SHP

mimetype: application/zip

en:
Outlines of 18'737 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 24 January 2018. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping.pdf)

The generation of the data is described in:

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

Abstract.
Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12’500 km2).

We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18’737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.

This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data is of great value to validate avalanche bulletins, complete existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.

Koordinate System: CH1903+ LV95 LN02

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


weather-station-davos-wolfgang

maintainer: Jörg Wieder

title_for_slug: weather-station-davos-wolfgang

en: temperature pressure relative-humidity weather raclets

en: Weather Station Davos Wolfgang

en: The data file contains date and time (YYYY-MM-DD hh:mm:ss) in UTC, temperature (°C), relative humidity (%), pressure (hPa) at 10 m above ground and above sea level. The data was averaged over 10 minutes.

en: The dataset contains weather parameters measured at Davos Wolfgang (LON: 9.853594, LAT: 46.835577).

pressure

display_name: pressure

raclets

display_name: raclets

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

weather

display_name: weather

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal


en: snow-cover vertical-wind-motion saltation boundary-layer-winds snow-depth

en: Data Compilation

media_type: ZIP

en: Compressed TXT files

format: ZIP

en:
The data correspond to the experiments presented and discussed in a paper regarding the interaction between turbulent wind fluctuations and snow saltation mass-fluxes (Paterna, 2016). Each of the nine data files corresponds to a different experiment presented in the paper and conducted in the winter 2014/2015 in the WSL/SLF cold wind tunnel in Davos. For each file the five columns indicate the time from the beginning of the experiment, the streamwise (u’) and the vertical (w’) wind velocity fluctuations, the streamwise (qx) and the vertical (qz) snow mass-flux components. From these time-series the scales of the snow saltation and of the turbulent flow are obtained with respect to the eddy-cycles and snow saltation cycles. From spectral analysis of the time-series a decoupling of the snow saltation from the turbulence forcing reveals two regimes of interaction: a turbulence-dependent regime occurring with weak saltation, and a turbulence-independent regime with strong saltation. Further details can be found at the link below.

Publication http://onlinelibrary.wiley.com/doi/10.1002/2016GL068171/abstract

boundary-layer-winds

display_name: boundary-layer-winds

saltation

display_name: saltation

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

vertical-wind-motion

display_name: vertical-wind-motion

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: Wind tunnel measurement data of drifting snow and turbulent wind fluctuations


de: no2 nox co stickoxide feinstaub no pm25 luftschadstoffe ozon luftqualitat pn zeitreihe echtzeit tabelle schadstoffe sachdaten stickstoffdioxid messwerte partikelanzahl o3 luft schwefeldioxid so2 stickstoffmonoxid kohlenmonoxid pm10

de:
Dieses Dataset umfasst **Tageswerte** **seit 1983 bis zum aktuellen Vortag**, aufgeteilt in Jahresdateien. Darin enthalten sind das maximale Stundenmittel und die Anzahl Überschreitungen des Stundenmittelgrenzwertes für Ozon und die Tagesmittel für Schwefeldioxid (SO2), Kohlenmonoxid (CO), Stickoxid (NOx), Stickstoffmonoxid (NO), Stickstoffdioxid (NO2), Feinstaub (PM10 und PM2.5) und Partikelanzahl (PN), sofern jeweils in genügender Qualität vorhanden.

Die Werte des vollendeten Tages für das laufende Jahr werden jeweils 30 Minuten nach Mitternacht (UTC+1) aktualisiert.

name: Messung Luftqualität, Umwelt- und Gesundheitsschutz, Gesundheits- und Umweltdepartement

stadt-zurich

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

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

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

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

de: Täglich aktualisierte Luftqualitätsmessungen, seit 1983


en: viscous-deformation snow-failure snow-mechanics acoustic-emissions sintering fiber-bundle-model snow snow-avalanche

en: fiber-bundle-model-for-snow-failure

media_type: application/zip

en: Data underlying Figures in publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted to "Geophysical Research Letters"

en:
This dataset contains modeled and experimental results for laboratory snow failure experiments and the concurrent acoustic emissions signatures for different loading rates. For modelling the snow failure we used a fiber bundle model that includes sintering and viscous deformation.

The data underlay the figures in the publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted for publication to "Geophysical Research Letters".

acoustic-emissions

display_name: acoustic-emissions

fiber-bundle-model

display_name: fiber-bundle-model

sintering

display_name: sintering

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-mechanics

display_name: snow-mechanics

viscous-deformation

display_name: viscous-deformation

en: Fiber Bundle Model for snow failure and concurrent Acoustic Emissions


maintainer: Matthias Haeni

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

en: Data plot of the forest station (ALB)

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

en: Site aerial photo (Alpthal)

media_type: image/jpeg

en: Site aerial photo from the Alpthal forest station. Source: Google. 2016. Site aerial photo from the Alpthal forest station. Retrieved November 11, 2016, from https://www.google.ch/maps

mimetype: image/jpeg

en: Forest station data (ALB)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for one meteorological station in Alpthal in Switzerland which is located within a natural coniferous forest (ALB) with Norway spruce (_Picea abies_; 180-230 yrs) as dominant tree species. The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Alpthal is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

swiss-forest-lab

display_name: swiss-forest-lab

wind-speed

display_name: wind-speed

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


maintainer: EnviDat

en: csv meteorological-data-format nead metadata-convention research-data-management

en: PyNEAD (future reference implementation)

en: MeteoIO (future reference implementation)

media_type: text/html

format: HTML

mimetype: text/html

en: NEAD syntax v0.1 (EBNF)

media_type: text/plain

format: TXT

mimetype: text/plain

en: NEAD on GitHub

media_type: HTML

en:
Acknowledgement: The NEAD format includes NetCDF metadata and is proudly inspired by both SMET and NetCDF formats. NEAD is designed as a long-term data preservation and exchange format.

The NEAD specifications were presented at the "WMO Data Conference 2020 - Earth System Data Exchange in the 21st Century" (Virtual Conference).

-----------------------

Summary:
The Non-Binary Environmental Data Archive (NEAD) format is being developed as a generic and intuitive format that combines the self-documenting features of NetCDF with human readable and writeable features of CSV. It is designed for exchange and preservation of time series data in environmental data repositories.

License: The NEAD specifications are released to the public domain under a Creative Commons CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

csv

display_name: csv

metadata-convention

display_name: metadata-convention

meteorological-data-format

display_name: meteorological-data-format

nead

display_name: nead

research-data-management

display_name: research-data-management

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Non-Binary Environmental Archive Data (NEAD) format


data-set-on-snow-instability

title_for_slug: data-set-on-snow-instability

en: failure-initiation slab crack-propagation rutschblock weak-layer snow-stability-evaluation slab-tensile-support avalanche-forcasting snow-avalanche propgatoin-saw-test

en: data set on snow instability

en: Read-me file on snow instability data

en:
These data on snow instability include three data subsets that were analyzed and the results published by Reuter and Schweizer (2018) who suggest a novel framework on how to describe snow instability by failure initiation, crack propagation and slab tensile support.

Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Reuter, B. and Schweizer, J., 2018. Describing snow instability by failure initiation, crack propagation and slab tensile support. Geophys. Res. Lett., 45, doi: 10.1029/2018GL078069.

avalanche-forcasting

display_name: avalanche-forcasting

crack-propagation

display_name: crack-propagation

failure-initiation

display_name: failure-initiation

propgatoin-saw-test

display_name: propgatoin-saw-test

rutschblock

display_name: rutschblock

slab

display_name: slab

slab-tensile-support

display_name: slab-tensile-support

snow-avalanche

display_name: snow-avalanche

snow-stability-evaluation

display_name: snow-stability-evaluation

weak-layer

display_name: weak-layer

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

en: Data set on snow instability


maintainer: Lisa Hülsmann

en: forest-inventory primeval-forests mortality-models fagus-sylvatica forest-reserves tree-mortality

en: German data

en:
READ ME for

Hülsmann L, Bugmann H, Commarmot B, Meyer P, Zimmermann S, Brang P
Data from: Does one model fit all? Patterns of beech mortality in natural forests of three European regions.
Ecological Applications http://dx.doi.org/10.5061/dryad.h4s6t

Forest inventory data of beech for the development of individual-tree mortality models from strict forests reserves in Switzerland, Germany and Ukraine.

The data package provides the files
CH_reduced: inventory data of the reduced dataset from Switzerland that was used to assess the influence of additional environmental and stand characteristics on beech mortality
CH: inventory data from strict forest reserves in Switzerland
DE: inventory data from strict forest reserves in Germany
UA: inventory data from a primeval beech forest in Ukraine

A set of three consecutive inventories was used to generate records for the calibration of mortality models based on trees that were alive in the first and second inventory and either dead or alive in the third inventory.
Diameter at breast height: dbh (mm)
Annual relative basal area increment: relBAI (), calculated based on the first and the second dbh measurement as the compound annual growth rate of the trees basal area (Bigler and Bugmann 2004)
Status of the tree: y, 0 = alive, 1 = dead
Length of the mortality period: dt (years)

Additional environmental and stand characteristics were derived for the reduced Swiss dataset.
Note the varying seasonal level of the covariates considering the entire year, the growing season from April to September (G) and the winter month January to March (W).
All climatic covariates were calculated for both the ‘growth’ (2) and the ‘mortality’ period (3). The stand covariates were derived for the second inventory of each record (2).

Mean diameter at breast height: dbh.mean.2 (mm)
Interquartile range of diameter at breast height: dbh.IQR.2 (mm)
Median diameter at breast height: dbh.median.2 (mm)
Basal area per hectare: BA.2 (m2 ha-1)
Number of trees per hectare: N.2 (ha-1)
pH-value: pH ()
Available water capacity in the soil: AWC (mm)
Mean annual precipitation sum: P.2, P.3 (mm)
Mean precipitation sum during growing season: PG.2, PG.3 (mm)
Mean annual air temperature: mT.2, mT.3 (°C)
Mean air temperature during growing season: mTG.2, mTG.3 (°C)
Mean air temperature during winter months: mTW.2, mTW.3 (°C)
Mean growing degree-days: GDD.2, GDD.3 ()
Mean number of months during growing season with water deficit: mDEFdurG.2, mDEFdurG.3 ()
Mean annual maximum water deficit: mDEFmax.2, mDEFmax.3 (mm)
Overall maximum of the annual maximum water deficit: maxDEFmax.2, maxDEFmax.3 (mm)
Mean of cumulative water deficit during growing season: mDEFcumG.2, mDEFcumG.3 (mm)
Overall maximum of cumulative water deficitduring growing season: maxDEFcumG.2, maxDEFcumG.3 (mm)
Percentage of years with at least one month water deficit: percDEF.2, percDEF.3 (%)

en: Swiss data reduced

en: Swiss data full

en: Ukrainian data

en:
The datasets comprise nearly 19’000 trees of European beech (_Fagus sylvatica_ L.) from unmanaged forests in Switzerland, Germany / Lower Saxony and Ukraine. Tree death was modelled as a function of size and growth, i.e., stem diameter (DBH) and relative basal area increment (relBAI). To explain the spatial and temporal variability in mortality patterns, we considered a large set of environmental and stand characteristics.

 Inventory data
The strict forest reserves in Switzerland and Germany had been established in the period of 1961-1975 and 1971-1974, respectively. Every reserve included up to 10 permanent plots ranging from 0.09 to 1.8 ha in size, with slightly irregular re-measurement intervals. Permanent plots with pure or mixed beech stands were selected from the reserves of both networks. Reserves with considerable wind disturbance during the monitored intervals were excluded from the analysis. In addition to data from the Swiss and German reserves, data from a 10 ha plot in the primeval beech forest Uholka in Western Ukraine including three remeasurements were used. The inventory data provide diameter measurements at breast height (dbh) for revisited trees with a diameter of more than 4, 7 and 6 cm for Switzerland, Germany and Ukraine, respectively.

 Mortality predictors
A set of three consecutive inventories was used to generate records for the calibration of mortality models based on trees that were alive in the first and second inventory and either dead or alive in the third inventory. As an explanatory variable, the annual relative basal area increment (relBAI) was calculated based on the first and the second dbh measurement as the compound annual growth rate of the trees basal area. Tree dbh in the second inventory was used in addition to relBAI to model tree status (alive or dead) of the third inventory.

To increase the generality of the mortality models, we selected environmental variables that are known to have a considerable influence on growth and mortality of beech. We emphasized the effects of water availability using a large set of drought characteristics that were calculated based on the local site water balance. We also related beech mortality to soil pH, temperature, precipitation and growing degree-days. Additionally, we considered stand characteristics that reflect the development stage, competition and structure of the forests.

 Further information
For further information, refer to Hülsmann _et al_. (2016) Does one model fit all? patterns of beech mortality in natural forests of three European regions. _Ecological Applications_.

fagus-sylvatica

display_name: fagus-sylvatica

forest-inventory

display_name: forest-inventory

forest-reserves

display_name: forest-reserves

mortality-models

display_name: mortality-models

primeval-forests

display_name: primeval-forests

tree-mortality

display_name: tree-mortality

en: Data from: Does one model fit all? patterns of beech mortality in natural forests of three European regions


en: airborne-laser-scanning snow-distribution canopy-height forest-structure snow-depth

en: Readme

en: Snow depth maps

en: Snow depth maps from two snow-on flights at each of the three field areas Davos (March 20th and 31st 2017), Engadien (March 20th and 31st, 2017) and Grand Mesa (February 8th and 16th, 2017)

en: Canopy height maps

en: Canopy height maps of each of the three field areas Davos, Engadine and Grand Mesa

en: Terrain elevation maps

en: Digital elevation model computed from snow-off flights for each of the field areas Davos, Engadine and Grand Mesa

en:
This dataset includes snow depth, canopy height and terrain elevation maps of forest stands in the Grisons (CH) and at Grand Mesa (CO,USA) derived from airborne lidar. Data were acquired i) within a pilot mission of NASA's Airborne Snow Observatory in the Swiss Alps in March 2017 and ii) during NASA’s SnowEx campaign at Grand Mesa in February 2017. Snow depth maps are available for two dates separated by approx.1 week, and include an area of ca. 0.5km2 for each of the three sites Davos, Engadine and Grand Mesa.
All data were presented and analyzed in the publication 'Revisiting Snow Cover Variability and Canopy Structure within Forest Stands: Insights from Airborne Lidar Data' (Mazzotti et al., 2019, WRR, doi: 10.1029/2019WR024898). This publication must be cited when using this dataset.

Paper Citation:
 > _Giulia Mazzotti; William Ryan Currier; Jeffrey S. Deems; Justin M. Pflug; Jessica D. Lundquist; Tobias Jonas (2019). Revisiting Snow Cover Variability and Canopy Structure Within Forest Stands: Insights From Airborne Lidar Data. Water Resources Research, 55, 6198– 6216, [doi: 10.1029/2019WR024898](https://doi.org/10.1029/2019WR024898)._

airborne-laser-scanning

display_name: airborne-laser-scanning

canopy-height

display_name: canopy-height

forest-structure

display_name: forest-structure

snow-depth

display_name: snow-depth

snow-distribution

display_name: snow-distribution

education

en: Education and science

en: ALS-based snow depth and canopy height maps from flights in 2017 (Grisons, CH and Grand Mesa, CO)


en: snow-precipitation complex-terrain orographic-precipitation precipitation-variability cosmo-wrf

en: StationData

en: Snow depth maps over Dischma valley for 26 January 2016 and 9 March 2016 and snow depth differences between the two dates.

en:
The data presented here corresponds to the publication "Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain" (Gerber et al., 2018a), which investigates the precipitation variability of snow precipitation in the central northern part of the Grisons (CH) and the publication "The importance of near-surface winter precipitation processes in complex alpine terrain" (Gerber et al., 2018b). The dataset contains:

* WRFsimulations: WRF simulation output for simulations with 4x (14x) terrain smoothing with an output timestep of 30 min/5 min and horizontal grid spacings of 1350 m, 450 m, 150 m and 50 m (currently: data available upon request).
* StationData: Meteorological station data of 18 meteorological stations in the central northern part of the Grisons with 30 minute resolution for the period 1 January 2016 till 1 May 2016.
* ADS80data: Photogrammetrically determined snow depth distribution data over the Dischma valley for the 26 January 2016 and 9 March 2016. Snow heights are corrected for buildings, vegetation (> 1m), outliers, and pixles, which are obivously snow-free on the pictures (Bühler et al., 2015). In addition the snow depth differences (snow depth on 9 March 2016 minus snow depth on 26 January 2016) are provided.

For more details about the simulation and observation data, see Gerber et al., 2018 and Gerber and Sharma (2018).

Publications:

Bühler, Y., Marty, M., Egli, L., Veitinger, J., Jonas, T., Thee, P., and Ginzler, C.: Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9, 229–243, doi:10.5194/tc-9-229-2015, 2015.

Gerber, F., Besic, N., Sharma, V., Mott, R., Daniels, M., Gabella, M., Berne, A., Germann, U., and Lehning, M.: Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain, The Cryosphere, 12, 3137–3160, doi:10.5194/tc-12-3137-2018, 2018.

Gerber, F., Mott, R. and Lehning, M.: The importance of near-surface winter precipitation processes in complex alpine terrain, Journal of Hydrometeorology, accepted, 2018.

Gerber, F., and Sharma, V.: Running COSMO-WRF on very-high resolution over complex terrain. Laboratory of Cryospheric Sciences CRYOS, École Polytechnique Fédérale de Lausanne EPFL, Lausanne, Switzerland. doi:10.16904/envidat.35, 2018.

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

orographic-precipitation

display_name: orographic-precipitation

precipitation-variability

display_name: precipitation-variability

snow-precipitation

display_name: snow-precipitation

envidat

en: EnviDat: the Environmental Data Portal

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

en: DISCHMEX - High-resolution WRF simulations in complex alpine terrain and station measurements


aerosol-data-weissfluhjoch

title_for_slug: aerosol-data-weissfluhjoch

en: linda particles inp raclets aerosol ice-nucleation

en: OPC-GT526S Dataset Weissfluhjoch

en: Particle counts were recorded in six size channels (0.3, 0.5, 0.8, 1.5, 2.5 and 5 μm) in a resolution of 20 seconds (time in UTC) by a particle counter (GT-526S, Met One Instruments, Inc.).

en: APS Dataset Weissfluhjoch

media_type: application/x-netcdf

en: The APS file contains aerosol data (total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) for aerodynamic diameters between 0.5 μm and ~20 μm as well as instrument characteristics, in a temporal resolution of 20 seconds, with time in UTC, measured at Weissfluhjoch.

mimetype: application/x-netcdf

en: OPC-N3 Dataset Weissfluhjoch

en: Particle concentrations in a size range of 0.35 μm to 40 μm were measured with an OPC-N3 (Alphasense, Inc.) in a resolution of 20 seconds (time in UTC). PM₁, PM₂,₅ and PM₁₀ were directly derived.

en: SMPS Dataset Weissfluhjoch

en: The SMPS file contains aerosol data (particle concentration, total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) in a size range between 12 and 460 nm (electrical mobility diameter) as well as instrument characteristics (sample temperature, pressure, relative humidity, mean free path and gas viscosity) in a temporal resolution of 2 minutes, with time in UTC, measured at Weissfluhjoch.

en: LINDA Dataset Weissfluhjoch

en: The LINDA file contains information on temperature (in °C) dependent frozen fractions, number of Ice Nuleating Particles (INP, per standard liter) and differential INP concentrations (per standard liter and Kelvin).

en:
Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.

Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0).

Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³).

Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³).

Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

aerosol

display_name: aerosol

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

linda

display_name: linda

particles

display_name: particles

raclets

display_name: raclets

en: Aerosol Data Weissfluhjoch


maintainer: Anita C. Risch

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

en:
site.code: Site code

Continent: Continent

sampleID: Sample ID

nn.latitude: Lattitude

nn.longitude: Longitude

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

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

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

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

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

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

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

ch.pH: pH

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

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

ch.porespace: Pore space (vol%)

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

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

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

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

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

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

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

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

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

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

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

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

ch.CtoN: C to N ratio

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

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

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

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

format: XLS

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

Paper Citation:

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

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

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

global

display_name: global

grassland

display_name: grassland

mineralization

display_name: mineralization

nutrient-network

display_name: nutrient-network

soil

display_name: soil

soil-biology

display_name: soil-biology

soil-chemistry

display_name: soil-chemistry

worldwide

display_name: worldwide

education

en: Education and science


en: ice-nucleation aerosol backward-trajectories raclets clouds

en: This dataset contains number concentrations of ice-nucleating particles active at -15 °C observed at Weissfluhjoch during February and March 2019, as well as complementary data (measured aerosol number concentrations and modelled total precipitation along air mass trajectories). This data formed the basis of our paper with the title “Towards parameterising atmospheric concentrations of ice-nucleating particles active at moderate supercooling”.

backward-trajectories

display_name: backward-trajectories

clouds

display_name: clouds

envidat

en: EnviDat: the Environmental Data Portal

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

en: Ice nucleating particle concentrations active at -15 °C at Weissfluhjoch


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

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

media_type: XLSX

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

en: Manual snow measurements Alptal (1968-2020)

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

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

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

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

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

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

alptal

display_name: alptal

first-order-catchment

display_name: first-order-catchment

meteorological-data

display_name: meteorological-data

runoff

display_name: runoff

snow

display_name: snow

subalpine

display_name: subalpine

en: Longterm hydrological observatory Alptal (central Switzerland)