risikokarte-naturgefahren

title_for_slug: risikokarte-naturgefahren

de: risikokarte naturrisiken gefahrenkarte hochwasserrisiko

fr: Risikokarte Naturgefahren mit den Teilen Hochwasser und Massenbewegungen (mit Hangmuren, permanente und spontane Rutschungen und Steinschlag).

fr: Die Risikokarte Naturgefahren ist eine Weiterentwicklung der Gefahrenkarte. Denn die Gefahrenkarte alleine zeigt nur die Gefährdung auf - nicht aber Schäden, welche die Folge sein können. In der Risikokarte werden neben den gefährdeten Flächen auch die betroffenen Werte (Personen, Sachwerte, Versorgung, Kultur und Umwelt) betrachtet. Entsprechend zeigt das Modell den Handlungsbedarf für die Vermeidung oder Verminderung von Schäden auf. Damit liegt eine wichtige Information für die risikobasierte Planung und Priorisierung von Schutzmassnahmen vor. Das Risiko wurde in 100 m Rasterauflösung modelliert und ermöglicht damit nur einen groben Überblick auf hoher Flugebene. Die Daten dienen primär Behörden und der Gebäudeversicherung Kanton Zürich (GVZ) zur Priorisierung von Schutzmassnahmen. Zur kritischen Interpretation der Modellresultate bedarf es fachlicher Kenntnisse und lokales Wissen. Die Risikokarte ist ein dynamisches Instrument und müsste nach dem Abschluss von Revisionen der Gefahrenkarte jeweils angepasst werden. Da der Aufwand für die Aktualisierung der Risikokarte gross ist, erfolgt dies trotzdem nur unregelmässig. Weitere Informationen zur Modellierung und der Verwendung finden sich im Abstract und technischen Bericht (siehe Datengrundlage - Dokumentation (PDF)) sowie auf unserer Homepage (siehe Datengrundlage - Dokumentation (HTML)).

fr: Risikokarte Naturgefahren

de: Risikokarte Naturgefahren

en: Risikokarte Naturgefahren

it: Risikokarte Naturgefahren


offentliche-oberflachengewasser

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: offentliche-oberflachengewasser

de: oberflachengewasser oberirdische-gewasser fliessgewasser stehgewasser flusse bache seen weiher offentlich gewassernetz

author: Kanton Zürich

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

it: geocat.ch link permanente

state: active

type: dataset

fr: WMS Naturgefahren: Synoptische Gefahrenkarte

format: WMS

fr: WMS Naturgefahren: Wassertiefen Hochwasser

fr: WMS Naturgefahren: Intensitäten Hochwasser

fr: WMS Naturgefahren: Intensitäten Massenbewegungen

fr: Öffentliche Oberflächengewässer, Gewässerraum, Wasserrechte

fr: WFS für Open-Government-Data des Kantons Zürich (OGD ZH WFS)

format: WFS

fr: Öffentliche Oberflächengewässer, Gewässerraum und Wasserrechte

fr: Die öffentlichen Oberflächengewässer des Kantons Zürich werden gemäss § 1a HWSchV vom AWEL mittels Verfügung festgestellt und in einem Plan sowie in einem Verzeichnis geführt. Seit 1995 werden die öffentlichen Gewässer auch im GIS erfasst und laufend nachgeführt. Durch stetige Verbesserung der Nachführungsprozesse entsprechen die GIS-Daten heute jeweils dem aktuellen, rechtskräftigen Bestand der öffentlichen oberirdischen Gewässer. Die Erfassung der Geometrien und -attribute erfolgt nach dem 'Linear Referencing'-Konzept von ESRI. Das Konzept besteht aus zwei Ebenen: der metrierten Basisgeometrien des Gewässernetzes (Routen) und mehrerer Eventtabellen (Ereignisse) zur Speicherung von Attributen entlang der Basisgeometrien mittels Meterständen (Von-Bis Angaben bei Linien). Der Nullpunkt ist jeweils bei der Mündung bzw. beim Seeauslauf. Die Basisgeometrie ist getrennt in Fliessgewässer (WB_FLIESSGEWAESSER_L_M) und Stehgewässer (WB_SEEUFERLINIEN_L_M) . Bei den Stehgewässern steht auch ein Flächendatensatz zur Verfügung (WB_STEHGEWAESSER_F). Die Daten werden wöchentlich übers Wochenende aktualisiert. HINWEIS: Die bisherige kommunale Gewässernummer (Gemeindegewässernummer) wurde per Mitte Januar 2022 durch eine neue kantonale Gewässernummer abgelöst und in den GIS-Datensätzen sowie im GIS-Browser entfernt. In offiziellen Dokumenten bitte per sofort nur noch die kantonale Gewässernummer verwenden. Kommunale Gemeinde-GIS müssen gegebenenfalls angepasst werden. Wir empfehlen die kantonalen Daten in externen Systemen als WFS oder WMS einzubinden. Damit sind die Daten immer gleich aktuell wie beim Kanton. Unter 45.8 steht eine Umrechnungstabelle der kommunalen Fliessgewässernummer sowie der Routennummer in die neue kantonale Fliessgewässernummer zur Verfügung.

spatial: Kanton Zürich

fr: Kanton Zürich

de: Kanton Zürich

en: Kanton Zürich

it: Kanton Zürich

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

fr:
Le département de géomatique est le centre de compétence du system d'information géographique du canton de Zurich.
Nous coordinons l'aquisition des géodonnées d'intérêt commun sur le territoire cantonal et les mettons à disposition des
secteurs public et privé et des particuliers.

en:
The department of geoinformation is the geospatial competency center of the Canton of Zurich.
We coordinate the acquisition of geodata within the cantonal territory and provide public, private, and government sectors with data of outstanding quality.

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

it: La divisione della geoinformazione è il centro d'eccellenza del Cantone di Zurigo per dati georeferenziati. Mettiamo a disposizione dati geografici e informazioni di alta qualità per l'economia, la società e la pubblica amministrazione su tutto il cantone.

political_level: canton

kanton-zuerich

capacity: public

type: organization

approval_status: approved

value: ZH - Geocat Harvester

fr: Öffentliche Oberflächengewässer

de: Öffentliche Oberflächengewässer

en: Öffentliche Oberflächengewässer

it: Öffentliche Oberflächengewässer


de: Oberflächenmodell DOM 2013

media_type: application/xml

format: XML

de: Das Oberflächenmodell wurde mittels Airborne-Laser-Scanning (ALS) gemessen und zu einem Relief (Hillshade) verarbeitet. Es zeigt die Oberfläche des Terrains mit allen dauerhaften künstlichen und natürlichen  Erhebungen wie Wald, Einzelbäumen und Gebäuden.

name: Amt für Grundbuch und Geoinformation des Kantons Zug

kanton-zug

fr: Canton de Zoug

de: Kanton Zug

en: Canton of Zug

it: Cantone di Zugo

de:
Hier veröffentlicht das Team von Open Data Zug von der kantonalen Fachstelle für Daten und Statistik schrittweise offene Behördendaten der kantonalen Verwaltung.

Weitere Informationen unter https://zg.ch/opendata

key: guid

key: uri

value: ZG-Kt - (Geocat) Harvester

de: Oberflächenmodell 2013


moorlandschaften

title_for_slug: moorlandschaften

de: Moorlandschaften WMS

de: Moorlandschaften

de: Im Kanton Zug liegen vier Moorlandschaften (Rothenthurm, Zugerberg, Unterägeri und Maschwander Allmend) von nationaler Bedeutung. Im Rahmen der Inventarisierung gemäss den Vorschriften des Bundes wird für jede Moorlandschaft ein Plan erstellt, welcher ein integrierender Bestandteil eines zugehörigen Berichtes ist. Die Pläne im Massstab 1:5'000 zeigen die diesem Massstab entsprechende Detailierung der Abgrenzung der einzelnen Moorlandschaften, die darin enthaltenen kantonalen und kommunalen Naturschutzgebiete, Moorflächen sowei Natur- und Kulturobjekte von besonderer Bedeutung.

landschaft

display_name: landschaft


swissbedrock

title_for_slug: swissbedrock

fr: Téléchargement

de: Download

en: Download

it: Download

fr: swissBEDROCK est un jeu de données complet qui fournit des informations détaillées sur la surface du substratum rocheux de la Suisse. En plus du modèle d’altitude du toit du rocher (BEM), il comprend des informations sur l’épaisseur des terrains meubles (TMUD), des détails sur l’incertitude, les auteurs ainsi que les modifications par rapport aux versions précédentes. Le jeu de données est structuré sous forme de raster multibande (taille de cellule raster de 10 x 10 mètres) avec 11 bandes d’information par cellule. Il prend en charge la gestion des versions pour la transparence et la traçabilité et est maintenu grâce à des mises à jour automatisées dans des zones définies, utilisant de nouvelles informations issues de forages et de levés cartographiques ou des remplacements complets avec des contributions de tiers. L’ensemble complet des données swissBEDROCK peut être téléchargé ici ou visualisé et interrogé cellule par cellule sur viewer.swissgeol.ch. Un fichier de notes de version est fourni, décrivant l’origine et les caractéristiques des différentes composantes du modèle. Des informations supplémentaires sur l’aperçu méthodologique et le flux de travail se trouvent dans la description du modèle. Les modèles 3D représentent des simplifications des paramètres géologiques réels. L'utilisateur reconnaît que les auteurs ont fait tous les efforts raisonnables pour vérifier les informations contenues dans le modèle géologique 3D présenté. Il n'y a aucune garantie que les données soient correctes à un point donné du sous-sol. En aucun cas, l'éditeur ne sera responsable des pertes ou dommages de nature matérielle ou immatérielle résultant de l'accès à l'information publiée, de son utilisation ou de sa non-utilisation, d'une mauvaise utilisation ou de défauts techniques.

de: swissBEDROCK ist ein umfassender Datensatz, der detaillierte Informationen über die Felsoberfläche der Schweiz bereitstellt. Zusätzlich zum Höhenmodell der Felsoberfläche (BEM) enthält es Informationen über die Mächtigkeit des Lockergesteins (TMUD), Angaben zu Unsicherheiten, Autoren sowie Änderungen gegenüber früheren Versionen. Der Datensatz ist als Multiband-Rasterdatensatz (Rasterzellengröße 10 x 10 Meter) mit 11 Informationsbändern pro Zelle strukturiert. Er unterstützt Versionierung für Transparenz und Rückverfolgbarkeit und wird durch automatisierte Aktualisierungen innerhalb definierter Gebiete gepflegt, unter Verwendung neuer Bohrloch- und Kartierungsinformationen oder durch Ersetzungen mit Beiträgen Dritter. Der vollständige swissBEDROCK-Datensatz kann hier heruntergeladen oder auf viewer.swissgeol.ch zellweise angezeigt und abgefragt werden. Eine Datei mit den Versionshinweisen wird bereitgestellt, die Herkunft und Eigenschaften der verschiedenen Modellkomponenten beschreibt. Weitere Informationen zur methodischen Übersicht und zum Arbeitsablauf sind in der Modellbeschreibung zu finden. 3D-Modelle stellen Vereinfachungen der realen Geologie dar. Der Nutzer anerkennt, dass die Autoren alle zumutbaren Aufwände unternommen haben, um die Informationen im geologischen 3D-Modell zu verifizieren. Es gibt keine Garantie, dass die angegebenen Daten an einem bestimmten Punkt im Untergrund korrekt sind. Der Herausgeber ist unter keinen Umständen für jegliche Verluste oder Schäden materieller oder immaterieller Art haftbar, welche aus dem Zugriff auf, die Nutzung oder Nichtnutzung der veröffentlichen Informationen, durch Missbrauch oder technische Störungen entstehen.

en: swissBEDROCK is a comprehensive dataset that provides detailed information on Switzerland’s bedrock surface. In addition to the bedrock elevation model (BEM), it includes information on the thickness of unconsolidated deposits (TMUD), details on uncertainty, authors and changes compared to previous versions. The dataset is structured as a multi-band raster dataset (10 x 10 meter raster cell size) with 11 information bands per cell. It supports versioning for transparency and traceability and is maintained through automated updates within defined areas using new borehole and mapping information or replacements with third-party contributions. The full swissBEDROCK dataset can be downloaded here or viewed and queried on viewer.swissgeol.ch on a per-cell basis. A release notes file is provided detailing the origin and characteristics of the various model components. More information on the methodological overview and workflow can be found in the model description. 3D models represent a simplification of the real geological settings. The user acknowledges that the authors have taken every reasonable effort to ensure that information contained in the presented 3D geological model is as accurate as possible. There is no guarantee that the given data related to a definite point in the subsurface is accurate. Under no circumstances will the publisher be liable for any loss or damage of a material or immaterial nature arising from access to, use or non-use of published information, or from misuse or technical breakdown.

it: swissBEDROCK è un set di dati che fornisce informazioni di dettaglio sulla superficie del substrato roccioso della Svizzera. Oltre al modello altimetrico del substrato roccioso (BEM), include informazioni sullo spessore dei depositi non consolidati (TMUD), inormazioni sul grado di incertezza, autori e le modifiche effettuate rispetto alle versioni precedenti. Il set di dati è strutturato come un set di dati raster a più bande (dimensione della cella raster 10 x 10 metri) con 11 bande informative per cella. Per garantire trasparenza e tracciabilità, il set di dati supporta il traccimanto delle versioni e viene aggiornato automaticamente in aree predefinite, utilizzando nuove informazioni provenienti da sondaggi, mappature o contributi di fonti esterne. Il set di dati completo swissBEDROCK può essere scaricato qui o visualizzato e consultato su viewer.swissgeol.ch cella per cella. È disponibile un file con le note di rilascio della versione che descrive in dettaglio l'origine e le caratteristiche dei vari componenti del modello. Maggiori informazioni sulla metodologia e sul flusso di lavoro sono disponibili nella descrizione del modello. I modelli 3D rappresentano semplificazioni dei parametri geologici reali. L'utente riconosce che gli autori hanno applicato tutti gli sforzi ragionevoli per verificare le informazioni contenute nel modello geologico 3D presentato. Non c'è alcuna garanzia che i dati siano corretti in qualsiasi punto del sottosuolo. In nessun caso l'editore sarà responsabile per qualsiasi perdita o danno di natura materiale o immateriale derivante dall'accesso, uso o non uso, abuso o difetti tecnici delle informazioni pubblicate.

spatial: Schweiz

fr: Office fédéral de topographie swisstopo

de: Bundesamt für Landestopografie swisstopo

en: Federal Office of Topography swisstopo

it: Ufficio federale di topografia swisstopo

fr: Le centre de compétence de la Confédération suisse pour les informations géographiques, c'est-à-dire pour la description, la représentation et l’archivage de données à référence spatiale.

de: Das Kompetenzzentrum der Schweizerischen Eidgenossenschaft für Geoinformation, d.h. für die Beschreibung, Darstellung und Archivierung von raumbezogenen Geodaten.

en: The centre of competence for the Swiss Confederation responsible for geographical reference data, for instance the description, representation and archiving of geographic spatial data.

it: Il centro d’eccellenza della Confederazione Elvetica per geoinformazione, cioè per la descrizione, rappresentazione e archiviazione dei dati georeferenziati (geodati).

political_level: confederation

value: Swisstopo - Geocat Harvester

fr: swissBEDROCK

de: swissBEDROCK

en: swissBEDROCK

it: swissBEDROCK


industrieminerale-vorkommen

regi

fr: Régions et villes

de: Regionen und Städte

envi

fr: Environnement

de: Umwelt

title_for_slug: industrieminerale-vorkommen

de: geotechnik mineralstoffindustrie mineralienabbau mineralische-bodenschatze geologie bgdi-bundesgeodaten-infrastruktur

author: Bundesamt für Landestopografie swisstopo

fr: Système d'informations des matières premières

de: Rohstoffinformationssystem

en: Resources Information System

it: Sistema d'informazione sulle materie prime

fr: geocat.ch permalien

de: geocat.ch Permalink

fr: Map (Preview) Aperçu map.geo.admin.ch

de: Map (Preview) Vorschau map.geo.admin.ch

en: Map (Preview)  map.geo.admin.ch

it: Map (Preview) Previsione map.geo.admin.ch

fr: Aperçu map.geo.admin.ch

de: Vorschau map.geo.admin.ch

en: Preview map.geo.admin.ch

it: Previsione map.geo.admin.ch

format: SERVICE

fr: Service WMS-IFDG, couche "Minéraux industriels: gisements"

de: WMS-BGDI Dienst, Layer "Industrieminerale: Vorkommen"

en: WMS-FSDI service, layer "Industrial minerals: deposits"

it: Servizio WMS-IFDG, strato "Minerali industriali: giacimenti"

format: HTML

fr: RESTful API de geo.admin.ch

de: RESTful API von geo.admin.ch

en: RESTful API from geo.admin.ch

it: RESTful API da geo.admin.ch

format: API

fr: Ce jeu de données montre les sites où des minéraux industriels ont été identifiés ou extraits dans le passé en Suisse. Grâce à leurs propriétés chimiques et/ou physiques spécifiques, les minéraux industriels sont utilisés dans divers procédés de production industrielle. Le gypse et le sel sont des minéraux industriels courants qui sont aujourd'hui extraits et transformés en Suisse. Compte tenu de leur importance, ils sont représentés séparément sur le géoportail (voir les jeux de données du Gypse et du Sel). Un certain nombre de minéraux industriels sont actuellement classés comme matières premières critiques (CRM) dans l’Union Européenne et certains sont considérés comme absolument essentiels pour la transition énergétique. Plusieurs sites répertoriés dans ce jeu de données indiquent une minéralisation susceptible de contenir une ou plusieurs matières premières critiques. La concentration et le volume de ces minéralisations sont généralement inconnus ou insignifiants. Dans l'état actuel des connaissances, une exploitation rentable de ces gisements ne semble pas réalisable. À l'exception du gypse et du sel, aucun minéral industriel n'est actuellement exploité commercialement. Pour un aperçu plus détaillé de la situation géologique concernant les matières premières critiques en Suisse, les utilisateurs sont invités à consulter le rapport Critical Raw Materials in Switzerland – A Review. Dans le cas où il est envisagé de développer un site d'extraction, il est indispensable de procéder à une étude géologique détaillée sur place. Ce jeu de données est régulièrement mis à jour et ne prétend pas être exhaustif.

de: Dieser Datensatz zeigt die Standorte, an denen in der Vergangenheit Industrieminerale in der Schweiz identifiziert oder abgebaut wurden. Industrieminerale werden aufgrund ihrer spezifischen chemischen und/oder physikalischen Eigenschaften in verschiedenen industriellen Produktionsprozessen eingesetzt. Gips und Salz sind gängige Industrieminerale, die heute in der Schweiz abgebaut und verarbeitet werden. Aufgrund ihrer Bedeutung werden sie im Geoportal separat dargestellt (siehe Datensätze Gips und Salz). Einige Industrieminerale werden derzeit in der Europäischen Union als kritische Rohstoffe (CRM) eingestuft, und manche gelten als absolut notwendig für die Energiewende. Mehrere Standorte in diesem Datensatz weisen auf eine Mineralisierung hin, die einen oder mehrere kritische Rohstoffe enthalten könnte. Die Konzentration und die Volumina dieser Mineralisierungen sind im Wesentlichen nicht bekannt oder unbedeutend. Nach heutiger Sachlage scheint eine wirtschaftliche Gewinnung dieser Vorkommen nicht realisierbar. Aktuell werden ausser Gips und Salz keine weiteren Industrieminerale kommerziell gewonnen. Für einen detaillierteren Überblick über die geologische Situation bezüglich kritischer Rohstoffe in der Schweiz wird auf den Bericht Critical Raw Materials in Switzerland – A Review verwiesen. Für eine Standortentwicklung eines Rohstoffabbaus ist eine detaillierte geologische Untersuchung der Vorkommen vor Ort unumgänglich. Dieser Datensatz wird periodisch aktualisiert und stellt keinen Anspruch auf Vollständigkeit.

en: This dataset shows the sites where industrial minerals have been located or mined in the past in Switzerland. Thanks to their specific chemical and/or physical properties, industrial minerals are used in various industrial manufacturing processes. Gypsum and salt are common industrial minerals mined and processed in Switzerland today. Because of their importance, they are presented separately in the Geoportal map viewer (see the Gypsum and Salt datasets). Some industrial minerals are currently classified as Critical Raw Materials (CRMs) in the European Union and some are considered absolutely essential for the energy transition. Several sites listed in this dataset indicate a mineralization that may contain one or more critical raw materials. The concentration and volume of these mineralizations are essentially unknown or insignificant. Based on current knowledge, a commercial exploitation of these occurrences does not appear feasible. Gypsum and salt aside, no industrial minerals are currently being mined commercially. Users are invited to consult the report Critical Raw Materials in Switzerland – A Review for a more detailed geological overview of the situation regarding CRMs. In case it is desired to develop a mining site, it is essential to conduct a detailed geological investigation on the location of interest. This dataset is periodically updated and does not claim to be exhaustive.

it: Questo set di dati mostra le località in cui dei minerali industriali sono stati identificati o estratti in passato in Svizzera. Grazie alle loro proprietà chimiche e/o fisiche specifiche, i minerali industriali sono utilizzati in vari processi di produzione industriale. Il gesso e il sale sono minerali industriali comuni estratti e lavorati oggi in Svizzera. Vista la loro importanza, questi sono rappresentati separatamente sul Geoportale (si vedano i dataset Gesso e Sale). Alcuni minerali industriali sono attualmente classificati come materie prime critiche (CRM) nell’Unione Europea (e talvolta in altri paesi) e altri sono considerati assolutamente essenziali per la transizione energetica. Diversi siti riportati in questo dataset indicano una mineralizzazione che potrebbe contenere una o più materie prime critiche. La concentrazione e il volume di queste mineralizzazioni sono generalmente sconosciuti o insignificanti. Allo stato attuale delle conoscenze, uno sfruttamento redditizio di questi giacimenti non sembra realizzabile. Ad eccezione del gesso e del sale, nessun minerale industriale è attualmente sfruttato commercialmente. Per una panoramica più dettagliata della situazione geologica relativa alle materie prime critiche in Svizzera, si invitano gli utenti a consultare il rapporto Critical Raw Materials in Switzerland – A Review. Nel caso si auspichi allo sviluppo di un sito di estrazione, è essenziale condurre un'indagine geologica dettagliata in loco. Questo set di dati è periodicamente aggiornamento e non pretende di essere completo.

fr: Autres minéraux industriels

de: Weitere Industrieminerale

en: Other industrial minerals

it: Altri minerali industriali


title_for_slug: Statistik der obligatorischen Krankenversicherung (OKP)

fr: assurance-de-base aos ofsp caisse-maladie assurance-maladie

de: krankenversicherung krankenkassen grundversicherung bag okp

de: BAG-OFSP-UFSP-FOPH

fr: XLSX 2023: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2023: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2023: Statistics on compulsory health insurance

it: XLSX 2023: Statistica dell'assicurazione malattie obbligatoria

format: ZIP

fr: XLSX 2022: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2022: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2022: Statistics on compulsory health insurance

it: XLSX 2022: Statistica dell'assicurazione malattie obbligatoria

fr: XLSX 2021: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2021: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2021: Statistics on compulsory health insurance

it: XLSX 2021: Statistica dell'assicurazione malattie obbligatoria

fr: XLSX 2020: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2020: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2020: Statistics on compulsory health insurance

it: XLSX 2020: Statistica dell'assicurazione malattie obbligatoria

fr: XLSX 2019: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2019: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2019: Statistics on compulsory health insurance

it: XLSX 2019: Statistica dell'assicurazione malattie obbligatoria

fr: XLSX 2018: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2018: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2018: Statistics on compulsory health insurance

it: XLSX 2018: Statistica dell'assicurazione malattie obbligatoria

fr: XLSX 2017: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2017: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2017: Statistics on compulsory health insurance

it: XLSX 2017: Statistica dell'assicurazione malattie obbligatoria

fr: XLSX 2016: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2016: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2016: Statistics on compulsory health insurance

it: XLSX 2016: Statistica dell'assicurazione malattie obbligatoria

fr: XLSX 2015: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2015: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2015: Statistics on compulsory health insurance

it: XLSX 2015: Statistica dell'assicurazione malattie obbligatoria

fr: XLSX 2014: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLSX 2014: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLSX 2014: Statistics on compulsory health insurance

it: XLSX 2014: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2013: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2013: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2013: Statistics on compulsory health insurance

it: XLS 2013: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2012: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2012: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2012: Statistics on compulsory health insurance

it: XLS 2012: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2011: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2011: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2011: Statistics on compulsory health insurance

it: XLS 2011: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2010: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2010: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2010: Statistics on compulsory health insurance

it: XLS 2010: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2009: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2009: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2009: Statistics on compulsory health insurance

it: XLS 2009: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2008: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2008: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2008: Statistics on compulsory health insurance

it: XLS 2008: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2007: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2007: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2007: Statistics on compulsory health insurance

it: XLS 2007: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2006: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2006: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2006: Statistics on compulsory health insurance

it: XLS 2006: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2005: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2005: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2005: Statistics on compulsory health insurance

it: XLS 2005: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2004: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2004: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2004: Statistics on compulsory health insurance

it: XLS 2004: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2003: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2003: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2003: Statistics on compulsory health insurance

it: XLS 2003: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2002: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2002: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2002: Statistics on compulsory health insurance

it: XLS 2002: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2001: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2001: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2001: Statistics on compulsory health insurance

it: XLS 2001: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 2000: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 2000: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 2000: Statistics on compulsory health insurance

it: XLS 2000: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 1999: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 1999: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 1999: Statistics on compulsory health insurance

it: XLS 1999: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 1998: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 1998: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 1998: Statistics on compulsory health insurance

it: XLS 1998: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 1997: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 1997: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 1997: Statistics on compulsory health insurance

it: XLS 1997: Statistica dell'assicurazione malattie obbligatoria

fr: XLS 1996: Statistique de l'assurance-maladie obligatoire (AOS)

de: XLS 1996: Statistik der obligatorischen Krankenversicherung (OKP)

en: XLS 1996: Statistics on compulsory health insurance

it: XLS 1996: Statistica dell'assicurazione malattie obbligatoria

fr: PDF 2022: FR Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 2022: FR Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 2022: FR Publications for Statistics on compulsory health insurance

it: PDF 2022: FR Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: PDF 2022: DE Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 2022: DE Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 2022: DE Publications for Statistics on compulsory health insurance

it: PDF 2022: DE Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: PDF 2021: DE Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 2021: DE Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 2021: DE Publications for Statistics on compulsory health insurance

it: PDF 2021: DE Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: PDF 2021: FR Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 2021: FR Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 2021: FR Publications for Statistics on compulsory health insurance

it: PDF 2021: FR Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: PDF 2020: DE Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 2020: DE Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 2020: DE Publications for Statistics on compulsory health insurance

it: PDF 2020: DE Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: PDF 2020: FR Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 2020: FR Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 2020: FR Publications for Statistics on compulsory health insurance

it: PDF 2020: FR Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: PDF 2019: DE Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 2019: DE Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 2019: DE Publications for Statistics on compulsory health insurance

it: PDF 2019: DE Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: PDF 2019: FR Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 2019: FR Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 2019: FR Publications for Statistics on compulsory health insurance

it: PDF 2019: FR Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: PDF 1996-2018: DE Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 1996-2018: DE Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 1996-2018: DE Publications for Statistics on compulsory health insurance

it: PDF 1996-2018: DE Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: PDF 1996-2018: FR Publications pour la Statistique de l'assurance-maladie obligatoire (AOS)

de: PDF 1996-2018: FR Publikationen zur Statistik der obligatorischen Krankenversicherung (OKP)

en: PDF 1996-2018: FR Publications for Statistics on compulsory health insurance

it: PDF 1996-2018: FR Pubblicazioni Statistica dell'assicurazione malattie obbligatoria

fr: La Statistique de l’assurance-maladie obligatoire est éditée par l’Office fédéral de la santé publique (OFSP), autorité de surveillance de l'assurance-maladie en Suisse. Elle donne un large aperçu chiffré des assureurs-maladie reconnus par la Confédération. L’assurance obligatoire des soins (AOS), régie par la loi fédérale du 18 mars 1994 sur l’assurance-maladie (LAMal), constitue l’élément central de cette publication.

en: This section provides information regarding publications on compulsory health insurance.

de: Die Statistik der obligatorischen Krankenversicherung wird vom Bundesamt für Gesundheit (BAG), Aufsichtsbehörde über die soziale Krankenversicherung in der Schweiz, herausgegeben. Sie gibt einen umfassenden, zahlenmässigen Überblick über die vom Bund anerkannten Krankenversicherer. Im Mittelpunkt der Publikation steht dabei die durch das Bundesgesetz vom 18. März 1994 über die Krankenversicherung (KVG) geregelte obligatorische Krankenpflegeversicherung (OKP).

it: Questa rubrica permette di consultare i dati relativi alle pubblicazioni sul tema dell'assicurazione malattie obbligatoria.

aos

display_name: aos

assicurazione-malattie

display_name: assicurazione-malattie

assurance-de-base

display_name: assurance-de-base

assurance-maladie

display_name: assurance-maladie

bag

display_name: bag

basic-health-insurance

display_name: basic-health-insurance

caisse-maladie

display_name: caisse-maladie

casse-malati

display_name: casse-malati

foph

display_name: foph

grundversicherung

display_name: grundversicherung

fr: Statistique de l'assurance-maladie obligatoire (AOS)

de: Statistik der obligatorischen Krankenversicherung (OKP)

en: Statistics on compulsory health insurance

it: Statistica dell'assicurazione malattie obbligatoria

bundesamt-fur-gesundheit-bag

fr: Office fédéral de la santé publique OFSP

it: Ufficio federale della sanità pubblica UFSP

fr: L'Office fédéral de la santé publique (OFSP) fait partie du Département fédéral de l'intérieur. De concert avec les cantons, il assume la responsabilité des domaines touchant à la santé publique ainsi que la mise en œuvre de la politique sanitaire. Autorité à vocation nationale, il représente les intérêts sanitaires de la Suisse dans les organisations internationales et auprès d'autres Etats.

de: Das Bundesamt für Gesundheit (BAG) ist Teil des Eidgenössischen Departements des Innern. Es ist - zusammen mit den Kantonen - verantwortlich für die Gesundheit der Schweizer Bevölkerung und für die Entwicklung der nationalen Gesundheitspolitik. Zudem vertritt das BAG als nationale Behörde die Schweiz in Gesundheitsbelangen in internationalen Organisationen und gegenüber anderen Staaten.

en: The Federal Office of Public Health (FOPH) is part of the Federal Department of Home Affairs. Along with the cantons it is responsible for public health in Switzerland and for developing national health policy. As the national health authority, the FOPH also represents Switzerland's interests in the field of health in international organisations and with respect to other countries.

it: L'Ufficio federale della sanità pubblica (UFSP) è incorporato nel Dipartimento federale dell'interno. Unitamente ai Cantoni, è responsabile della salute della popolazione svizzera e dello sviluppo della politica nazionale in materia di salute. In qualità di autorità nazionale rappresenta inoltre gli interessi della Svizzera in materia di sanità in seno a organizzazioni internazionali e nei rapporti con altri Stati.


wasser-leitungen-darstellung-eigentum

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: wasser-leitungen-darstellung-eigentum

url: https://geo.ur.ch/?layers=Wasser Leitungen Darstellung Eigentum

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

it: geocat.ch link permanente

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: Dieser Datensatz hat den gleichen Inhalt wie der Datensatz "Wasser Leitung öffentlich". Die Wasserleitungen sind gemäss dem Attribut "Eigentum" verschiedenfarbig dargestellt.

spatial: Canton of Uri (UR)

fr: Gemeinden des Kt. Uri

de: Gemeinden des Kt. Uri

en: Gemeinden des Kt. Uri

it: Gemeinden des Kt. Uri

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

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

value: Uri-Kt - Geocat Harvester

fr: Wasser Leitungen Darstellung Eigentum

de: Wasser Leitungen Darstellung Eigentum

en: Wasser Leitungen Darstellung Eigentum

it: Wasser Leitungen Darstellung Eigentum


wasser-leitungen-offentlich

title_for_slug: wasser-leitungen-offentlich

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

fr: Wasser Leitungen öffentlich

de: Wasser Leitungen öffentlich

en: Wasser Leitungen öffentlich

it: Wasser Leitungen öffentlich


elektro-leitungen

title_for_slug: elektro-leitungen

fr: Elektro Trasse, Bauwerke und Trassepunkte.

fr: Elektrizitätswerke

de: Elektrizitätswerke

en: Elektrizitätswerke

it: Elektrizitätswerke

fr: Elektro Leitungen

de: Elektro Leitungen

en: Elektro Leitungen

it: Elektro Leitungen


abfallanlagen-und-sammelstellen

title_for_slug: abfallanlagen-und-sammelstellen

de: abfall-sammelstelle abfallanlage

author: Geoinformation Stadt Bern

fr: Map (Preview)

de: Map (Preview) Stadtplan

en: Map (Preview)

it: Map (Preview)

de: Link zum Thema im Internet-Stadtplan der Stadt Bern

de: Abfallsammelstellen

de: Web Map Services WMS

de: WFS Abfallsammelstellen

de: Web Feature Services WFS

de: Standorte der Entsorgungshöfe und öffentlichen Sammelstellen in der Stadt Bern. Informationen, welche Abfallarten abgegeben werden können. Die Standorte von privaten Unterflursammelstellen für Kehricht und Papier/Karton werden nicht abgebildet.

spatial: Stadt Bern

de: Geoinformation Stadt Bern

geoinformation-der-stadt-bern

fr: L’Office du cadastre de la ville de Berne

en: The Land Surveying Office of the City of Bern

it: L'ufficio del catasto nella Città di Berna

fr: L’Office du cadastre (Geoinformation Stadt Bern) est l’organisme compétent pour la collecte, l’accès et la diffusion d’informations géographiques dans la ville de Berne.

de: Geoinformation Stadt Bern (ehemals Vermessungsamt) ist die Kompetenzstelle für die Beschaffung, den Zugang und die Verbreitung von Geoinformationen in der Stadt Bern.

en: The Surveying Office (Geoinformation Stadt Bern) is the centre of competence in the City of Bern for the procurement of, access to and dissemination of geographic information.

it: L'ufficio del catasto (Geoinformation Stadt Bern) è il centro di competenza per il reperimento, l'accesso e la diffusione di geoinformazioni nella Città di Berna.

political_level: commune

value: Geoinformation Stadt Bern - Geocat Harvester

de: Abfallanlagen und Sammelstellen


okoinfomobil

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

ener

fr: Énergie

de: Energie

regi

de: Regionen und Städte

envi

de: Umwelt

title_for_slug: okoinfomobil

de: oekomobil okomobil

de: geocat.ch Permalink

de: OekoInfoMobil

de: WFS OekoInfoMobil

de: Haltestellen, an welchen das ÖkoInfoMobil einmal die Woche für 20 Minuten hält und kleine Abfallmengen entgegennimmt. Der Fahrplan ist fix und die Haltezeiten für die jeweiligen Standorte sind angegeben. Die Mitarbeitenden im Mobil beraten kompetent zu Entsorgungsfragen.

de: ÖkoInfoMobil


licht-markt-schweiz

maintainer: Bundesamt für Energie BFE

title_for_slug: Licht-Markt Schweiz

de: ogd25-bfe leuchtmittel lampen leuchten beleuchtung licht markt verkauf erhebung statistik

author: Bundesamt für Energie BFE

fr: Marché suisse de l’éclairage - ampoules et luminaires

de: Licht-Markt Schweiz - Leuchtmittel und Leuchten

format: CSV

fr: Marché suisse de l’éclairage - capteurs

de: Licht-Markt Schweiz - Sensoren

fr:
L'Association suisse pour l'éclairage (SLG) a été chargée par l'Office fédéral de l'énergie (OFEN) de collecter chaque année, entre 2014 et 2022, les chiffres de vente de lampes et de luminaires en Suisse afin d'observer la diffusion de la technologie LED. Cette analyse s'est basée à chaque fois sur environ 140 à 170 retours d'informations de la part des fabricants et des distributeurs du secteur de l'éclairage en Suisse.
Les statistiques du marché suisse de l'éclairage distinguent les sources lumineuses et les luminaires par technologie et par type. Pour les années 2020 à 2023, les chiffres de vente des capteurs d'éclairage ont également été recensés. Cette statistique complémentaire du marché suisse des capteurs d'éclairage différencie les différents types de détection et de montage. Elle se base sur les réponses de tous les membres de sensNORM, ce qui permet de saisir les chiffres de vente de tous les fabricants de capteurs renommés. En outre, les chiffres des précédentes analyses du marché de l'éclairage ont été utilisés pour une classification différenciée des résultats de la saisie.

de:
Die Schweizer Licht Gesellschaft (SLG) hat im Auftrag des Bundesamts für Energie (BFE) zwischen 2014 und 2022 jährlich die Absatzzahlen von Lampen und Leuchten in der Schweiz erhoben, um die Verbreitung der LED-Technologie zu beobachten. Die Basis für diese Analyse bildeten jeweils rund 140 bis 170 Rückmeldungen von Herstellern und dem Handel aus der Beleuchtungsbranche in der Schweiz.
Die Statistik Licht-Markt Schweiz unterscheidet die Leuchtmittel und Leuchten nach Technologie und Typ. Für die Jahre 2020 bis 2023 wurden zusätzlich die Verkaufszahlen von Beleuchtungs-Sensoren erfasst. Diese ergänzende Statistik Beleuchtungssensoren-Markt Schweiz differenziert nach verschiedenen Erfassungs- und Montagearten. Sie basiert auf Rückmeldungen aller sensNORM-Mitglieder, womit die Verkaufszahlen sämtlicher namhafter Sensorhersteller erfasst werden. Zusätzlich wurden für eine differenzierte Einordnung der Erfassungsergebnisse die Zahlen der vergangenen Licht-Marktanalysen verwendet.

fr: Marché suisse de l’éclairage

de: Licht-Markt Schweiz

it: Mercato svizzero dell'illuminazione

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

de: Bundesamt für Energie BFE

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

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

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

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

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


kreisel-ur

regi

fr: Régions et villes

it: Regioni e città

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: kreisel-ur

url: https://geo.ur.ch/?layers=Kreisel UR

fr: geocat.ch permalien

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

fr: Realisierte und geplante Kreisel im Kanton Uri gemäss den Informationen vom Amt für Tiefbau.

fr: Amt für Tiefbau Kt. Uri

de: Amt für Tiefbau Kt. Uri

en: Amt für Tiefbau Kt. Uri

it: Amt für Tiefbau Kt. Uri

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

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

fr: Kreisel UR

de: Kreisel UR

en: Kreisel UR

it: Kreisel UR


maintainer: Kunfeng Gao

en: aerosol-cloud-interactions biological-particles aerosol-source-apportionment inp-parameterization ice-nucleation

media_type: application/zip

en: This dataset includes all processed and raw data in the paper titled "Biological and dust aerosol as sources of ice nucleating particles in the Eastern Mediterranean: source apportionment, atmospheric processing and parameterization"

en:
This repository contains all observational data sets during CALISHTO campaign used for the paper:
Gao, K., Vogel, F., Foskinis, R., Vratolis, S., Gini, M. I., Granakis, K., Billault-Roux, A.-C., Georgakaki, P., Zografou, O., Fetfatzis, P., Berne, A., Papagiannis, A., Eleftheridadis, K., Möhler, O., and Nenes, A.: Biological and dust aerosol as sources of ice nucleating particles in the Eastern Mediterranean: source apportionment, atmospheric processing and parameterization, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-511, 2024.

aerosol-cloud-interactions

display_name: aerosol-cloud-interactions

aerosol-source-apportionment

display_name: aerosol-source-apportionment

biological-particles

display_name: biological-particles

ice-nucleation

display_name: ice-nucleation

inp-parameterization

display_name: inp-parameterization

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

value: Envidat Harvester

en: CALISHTO campaign dataset for the publication Biological and Dust Aerosols as Sources of Ice-nucleating Particles in the Eastern Mediterranean


maintainer: EnviDat Support

en: zurich food-webs bees management-intensity urban-ecology hymenoptera urbanization wasps cavity-nesting urban-ecosystems trap-nest host-enemy-interactions

en: Not used: raw questionnaires

media_type: text/csv

en: Script for the analyses v2.0

en: Cleaned script to reproduce the analyses

format: OCTET

en: Read me file

media_type: text/plain

format: TXT

en: Data of the study

en: The csv. file contains the response variable "interaction diversity" (idiv), and the values of the predictors used in the paper. The "id" column indicates the garden ID, each row in the dataset correspond to a garden and each column to the response (idiv), an explanatory variable or a descriptor (name, Lat, Long). See the thesaurus and the readme file for extended information on the variables.

en: Questionnaires management intensity anonymised

en: Results from the management intensity questionnaires anonymised. IDs are randomized and don't match those in the study data csv

en: Not used: readme

en: Script for the analyses v1.0

en: Raw data nests

en: Host-enemy interaction data, used to compute the interaction diversity metrics

en: Thesaurus

en: Variable names and their description.

format: XLS

en: Not used: data of the study

en:
The data supports the paper "Local and landscape factors shape alpha and beta trophic interaction diversity in urban gardens". It provides:
(1) the host-natural enemy interaction networks and network metrics between cavity-nesting bees and wasps and their natural enemies,
 (2) the explanatory variables reflecting urban intensity, temperature, habitat amount and management intensity.
(3) the questionnaires for assessing management intensity.
(4) a thesaurus for the variable names.
(5) a readme file.
(6) the R script used for the analyses.
The data is part of the BetterGardens project. It was sampled in 85 allotment and home gardens in the ctiy of Zurich in 2015 using standardized trapnests.

bees

display_name: bees

cavity-nesting

display_name: cavity-nesting

food-webs

display_name: food-webs

host-enemy-interactions

display_name: host-enemy-interactions

hymenoptera

display_name: hymenoptera

management-intensity

display_name: management-intensity

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wasps

display_name: wasps

zurich

display_name: zurich

en: Data on interaction diversity in urban gardens


maintainer: Athanasios Nenes

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

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

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

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

mimetype: text/csv

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

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

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

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

cloud-droplets

display_name: cloud-droplets

cloud-modeling

display_name: cloud-modeling

raclets

display_name: raclets

sigma-w

display_name: sigma-w

supersaturation

display_name: supersaturation

wolfgangpass

display_name: wolfgangpass

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Predicted cloud droplet numbers Davos Wolfgang


en: forests fagus-sylvatica leaf-senescence growth-reaction-to-drought-stress drought-2018 european-summer-drought

en: Drought and Beech: 1000 beeches data set

en: The data set comprises data from the Drought and Beech 1000 beeches project. The actual data file with monitoring data of 963 beech trees in northern Switzerland over four years (Drought_and_Beech_1000beeches_Data_v1.0.csv), a metadata file with column descriptions (Drought_and_Beech_1000beeches_Legend_v1.0.csv), and a file defining the different survey periods (Drought_and_Beech_1000beeches_Survey_periods_v1.0.csv).

en: This study investigated multi-year drought impacts on beech forests through a unique large-scale monitoring of 963 individual beech trees, which showed either premature leaf discoloration during the drought in summer 2018 or no visible damage. We conducted the study in two highly drought-affected regions in northern Switzerland and one less drought-affected region located further south. We quantified the development of crown dieback and tree mortality as well as secondary drought damage, i.e. the presence of bleeding cankers and bark beetle infestations, in these trees for three consecutive years. We also determined the impact of several potential climate- and stand-related (predisposing) factors on mortality and drought legacy processes.

european-summer-drought

display_name: european-summer-drought

fagus-sylvatica

display_name: fagus-sylvatica

forests

display_name: forests

growth-reaction-to-drought-stress

display_name: growth-reaction-to-drought-stress

leaf-senescence

display_name: leaf-senescence

en: Data on multi-year drought impacts on European beech in northern Switzerland


maintainer: Ionut Iosifescu Enescu

en: research-data-management jupyter-notebooks reproducibility open-data hpc open-source open-science

en: Open Science Support @ WSL (Poster)

media_type: application/pdf

format: PDF

mimetype: application/pdf

en:
This poster was originally created for the swissuniversities Open Science Action Plan: Kick-Off Forum, and showed to the audience on 17.10.2019. It illustrates how the environmental data portal EnviDat provides the tools for fostering Open Science and Reproducibility of scientific research at WSL.

Supporting open science is a highly relevant user requirement for EnviDat and for implementing FAIR (Findability, Accessibility, Interoperability and Reusability) principles at dataset level.
EnviDat encourages WSL scientists to complement data publication with a complete description of research methods and the inclusion of the open source software, code or scripts used for processing the dataset or for obtaining the published results. By openly publishing open software (e.g. as Jupyter notebooks) alongside research data sets, researchers can contribute to mitigate reproducibility issues.

EnviDat also promotes and supports, where possible and practical, the publication of software as Jupyter notebooks. Jupyter notebooks provide a solution for improved documentation and interactive execution of open code in a wide range of programming languages (Python, R, Octave/Matlab, Java or Scala). These programming languages are widely used in environmental research at WSL and well supported by the Jupyter-compatible kernels. We have sucessfully interfaced EnviDat-hosted notebooks with the WSL High-Performance Computing (HPC) Linux Cluster through a JupyterHub/JuypterLab beta installation on the HPC cluster implemented in close collaboration with the WSL IT-Services.
For existing software that cannot be easily migrated to Jupyter Notebooks, the Open Science and Reproducibility is assisted by containerisation. We have proven that several Singularity containers can successfully run on WSL's HPC cluster.

Finally, the researchers can upload the data/results complemented by code (e.g. as Jupyter Notebooks, or Singularity containers) and any additional documentation in EnviDat. Consequently, they will receive a DOI for the entire dataset, which they can reference in their science paper in order to publish a more reproducible research.

_License_: This poster is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse this poster in any way you want, for any purposes and without restrictions.

hpc

display_name: hpc

jupyter-notebooks

display_name: jupyter-notebooks

open-data

display_name: open-data

open-science

display_name: open-science

open-source

display_name: open-source

reproducibility

display_name: reproducibility

research-data-management

display_name: research-data-management

en: Open Science Support at the Swiss Federal Research Institute WSL. The EnviDat Concept


en: smouldering zenodo lightning-location-system database holdover forest-fire

en: This database contains open, harmonized, and ready-to-use global data on holdover time. Holdover time is defined as the time between lightning-induced fire ignition and fire detection. The first version of the database is composed of three data files (censored data, non-censored data, ancillary data) and three metadata files (description of database variables, list of references, reproducible examples). These data were collected through a literature review of LIW studies and some datasets were assembled by authors of the original studies, covering more than 150,000 LIW from 13 countries in five continents and a time span of a century from 1921 to 2020. Censored data are the core of the database and consist of frequency data reporting the number or relative frequency of LIW per interval of holdover time. Ancillary data provide additional information on the methods and contexts in which the data were generated in the original studies. Potential contributors to the database are encouraged to contact the corresponding author in the readme file.

database

display_name: database

forest-fire

display_name: forest-fire

holdover

display_name: holdover

lightning-location-system

display_name: lightning-location-system

smouldering

display_name: smouldering

zenodo

display_name: zenodo

en: Database on holdover time of lightning-ignited wildfires


maintainer: Leo Gallus Bont

en: geoinformation-software swiss-geodata open-source seilaplan swisstopo qgis-plugin digital-elevation-model digital-planning cable-yarding

en: View video on youtube!

en: Herunterladen des DHM von swisstopo Website

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. As an alternative to using the ‘Swiss Geo Downloader’ plugin, the DTM can be obtained directly from Swisstopo. In this tutorial we explain step by step how to download the necessary DTM from the Swisstopo Website, and how to use it in QGIS for the digital planning of a cable line using the plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to the elevation model on the swisstopo website: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.html#technische_details

Link to the rope map website: https://seilaplan.wsl.ch

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

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Als Alternative zum Swiss Geo Downloader erklären wir in diesem Tutorial Schritt für Schritt, wie man das nötige Höhenmodell von der Swisstopo Webseite herunterladen und in QGIS zur Seillinienplanung verwenden kann.

Link zum Höhenmodell auf der swisstopo Webseite: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.html#technische_details

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

geoinformation-software

display_name: geoinformation-software

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

swisstopo

display_name: swisstopo

en: Seilaplan Tutorial: DTM download from swisstopo website


en: meteodat-gmbh wagital snow-water-equivalent snow gcos

en:
Total water reserves of the snow cover [mio m3] for Wägital catchment, Switzerland, for reference date April 1. Data is separated in 2 elevation zones 900m-1500m asl and 1500m-2300m asl. Time period 1943-2025, status 2025-04-30.

Funded currently or in the past by:

- Federal Office of Meteorology and Climatology MeteoSwiss in the context of GCOS Switzerland
- Meteodat GmbH
- Institute of Geography, University of Zurich
- WSL Institute for Snow and Avalanche Research SLF
- Institute of Geography, ETH Zurich (IAC ETH Zurich)
- AG Kraftwerk Wägital (AXPO and EWZ)

See also https://www.meteodat.ch/waegital.html

gcos

display_name: gcos

meteodat-gmbh

display_name: meteodat-gmbh

snow

display_name: snow

snow-water-equivalent

display_name: snow-water-equivalent

wagital

display_name: wagital

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Snow water equivalent for reference date April 1 for Wägital catchment, starting 1943


en: restoration field-data urban-landscape forest traffic-noise

en: 11_P4_S1_Instructions for individual mindful walking.pdf

en: This document contains the booklet with instructions for mindful walking, which participants in the mindfulness condition were encouraged to take with them and use during their individual walks over the 10 days following on-site participation.

en: This file contains the informed consent document that participants signed to participate in the study.

en: 09_P2_Fotos Noise ROS paper.zip

en: This folder included the example pictures of the conditions included in paper 2 ("Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial“).

en: This file includes the information sheet provided to participants before they consented to take part in the study.

en: 06_Studyprotocol_GPS tracks of the walking routes.zip

en: This folder contains the GPS tracks of the walking routes in the test sites.

en: 03a_Studyprotocol_Data on evaluation of acoustic impression of the test settings_Studyprotocol.sav

en: This data file includes information for an additional post hoc classification of the sound environment of the test sites. This evaluation was conducted in the afternoons of the same week in 2023 at two locations within each test site by a civil servant who was not familiar with the study's research questions.

en: 03b_Studyprotocol_Script_Analysis stationary noise evaluation.sps.sps

en: This SPSS syntax file contains a script for analyzing data related to the stationary evaluation of the acoustic impressions at the test sites, which is numbered 03a in this repository.

en: This SPSS data file includes the data used for analysis in paper 2 (Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial) and paper 3 ("The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world: A randomized controlled trial").

en: This document includes the questionnaire for Papers 2 and 3, administered at the second measurement time point (after the walk).

en: This document includes the questionnaire for Papers 2 and 3, administered at the third measurement time point (10 days after participation on site).

en: 13_P4_Data mindful walking.sav

en: This file contains data for the manuscript "Effects of a mindful walking intervention in urban forests for healthy adults".

en: 07_Studyprotocol_Test site pictures.zip

en: This folder includes two pictures of each test site. The locations for the two pictures on each route were chosen to be as characteristic as possible in terms of the visual and acoustical impressions of the walk.

en: 12_P4_S2_Description of mindful walking intervention on site.pdf

en: This file includes the guided mindful walking instructions provided to participants in the mindfulness condition during the on-site walks.

en: 01_Studyprotocol_Locations of the starting points of the walking routes in the test settings.pdf

en: This document includes GPS coordinates of the starting points of the walking routes in the test sites.

en: 02_Studyprotocol_Data on Laeq from noise recordings of walking routes_Studyprotocol.sav

en: This data file contains information on the LAeq levels recorded along the final walking routes between September 2021 and March 2022, prior to the commencement of data collection.

en: This document includes the questionnaire for Papers 2 and 3, administered at the first measurement time point (before the walk began).

en:
This repository contains data related to the field experiments of the RESTORE project. This project is a collaboration between the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and the Swiss Federal Laboratories for Materials Science & Technology (EMPA). It has received funding from the Swiss National Science Foundation. The overall objective of the RESTORE project was to assess the effects of green spaces as facilitators and noise as impediment to recover from stress in people's daily environments across Switzerland.
We conducted a randomized, controlled field study to compare the psychophysiological benefits of exposure to forests and urban built environments with different levels of road traffic noise in healthy adults during 30-minute walks in Zürich, Switzerland to explore:
1) The psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure
2) The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world
3) The effects of a mindful walking intervention in urban forests for healthy adults
Accordingly, this repository includes data and documentation for the 3 scientific articles:
Scientific article 1. “Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: study protocol of a randomized controlled trial", BMC Psychology, 2024. https://doi.org/10.1186/s40359-024-01720-x
Scientific article 2. "Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial“. Journal of Environmental Psychology, 2025.
Scientific article 3. “The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world: A randomized controlled trial". To be submitted to PLOS One, 2025.
Scientific article 4: "Effects of a mindful walking intervention in urban forests for healthy adults". To be submitted to Current Psychology, 2025.

field-data

display_name: field-data

forest

display_name: forest

restoration

display_name: restoration

traffic-noise

display_name: traffic-noise

urban-landscape

display_name: urban-landscape


maintainer: Matthias Haeni

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

en: Site photo of the field station (OTF)

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

mimetype: image/jpeg

en: Site aerial photo (Othmarsingen)

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

en: Data plot of the field station (OTF)

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

en: Field station data (OTF)

en: Data file.

en: Site photo of the forest station (OTB)

en: Site photo of the forest station from above (viewing downwards the slope).

en: Forest station data (OTB)

en: Data plot of the forest station (OTB)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Othmarsingen in Switzerland where one station is located within a natural deciduous forest stand (OTB) with European beech (_Fagus sylvatica_; 120-140 yrs) and lime trees (_Tilia sp._; 120-140 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, OTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Othmarsingen is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

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


maintainer: Yaquan Chang

en: relief climate-history endemism tectonic-faults plant-biodiversity

en:
This dataset includes geomorphic predictors and plant biodiversity patterns in the Hengduan Mountains, published in the Geological Society of London special volume: Asian Geodynamics, Climate and Biodiversity (https://doi.org/10.1144/SP549-2024-17).
The geomorphic predictors include catchment-restricted relief and chi maps, while the climate predictors comprise site water balance, growing degree days, and climate change velocity from the Last Glacial Maximum (LGM) to the present.
The plant biodiversity patterns are represented by a plant richness map for 13,321 species in the Hengduan Mountains. Species-level plant range maps are available in the dataset, previously published under DOI: 10.16904/envidat.424.

climate-history

display_name: climate-history

endemism

display_name: endemism

plant-biodiversity

display_name: plant-biodiversity

relief

display_name: relief

tectonic-faults

display_name: tectonic-faults

en: Tectonic and climatic controls on plant biodiversity in the Hengduan Mountains China


maintainer: Benjamin Reuter

en: snow-instability avalanche-problem-type snow crocus snowpack weissfluhjoch avalanche avalanche-activity avalanche-danger snow-cover-modeling

en: 2015-2016 Seismic avalanche acitivity catalogue

en:
Avalanches were indentified in seismic data recorded by two seismic arrays, one deployed at Wannengrat (2,500 m) and another one deployed in the Dischma valley (2,000 m).
The data cover the period from 01.01.2016 - 30.04.2016 and are presented in Figure 7 in Reuter et al. (2021).

en: 2015-2016 Avalanche problem types from SNOWPACK

en:
Avalanche problem types were derived from a snow cover simulation with the model SNOWAPCK for the winter season 2015-2016 at the Weissfluhjoch study plot, Davos, CH.
The data cover the period 01.01.2016-30.04.2016. The binary indicator (0,1) tells whether an avalanche problem type was identified in the snow cover simulation (1) or not (0).
The data are presented in Figure 7 in Reuter et al. (2021).

en: 2015-2016 Avalanche problem types from Crocus

en:
Avalanche problem types were derived from a snow cover simulation with the model Crocus for the winter season 2015-2016 at the Weissfluhjoch study plot, Davos, CH.
The data cover the period 01.01.2016-30.04.2016. The binary indicator (0,1) tells whether an avalanche problem type was identified in the snow cover simulation (1) or not (0).
The data are presented in Figure 7 in Reuter et al. (2021).

en: 1999-2017 Avalanche problem types from Crocus

en:
Avalanche problem types were derived from snow cover simulations with the model Crocus at the Weissfluhjoch study plot, Davos, CH.
The data cover the winter seasons between 1999-2017 and include the simulated annual frequencies of new snow, wind slab, persistent weak layer, aging-persistent weak layer and wet snow problem types.
The data are presented in Figure 8 in Reuter et al. (2021).

en: 1999-2017 Avalanche problem types from SNOWPACK

en:
Avalanche problem types were derived from snow cover simulations with the model SNOWPACK at the Weissfluhjoch study plot, Davos, CH.
The data cover the winter seasons between 1999-2017 and include the simulated annual frequencies of new snow, wind slab, persistent weak layer, aging-persistent weak layer and wet snow problem types.
The data are shown in Figure 8 in Reuter et al. (2021).

en:
Avalanche problem types were derived from snow cover simulations with the models Crocus and SNOWPACK at the Weissfluhjoch study plot, Davos, CH. The data include annual frequencies of avalanche problem types for the seasons 1999-2017 and daily presence of avalanche problem types for the period 01.01.2016 - 30.04.2016.
Avalanche activity was derived from two seismic sensor arrays deployed no further than 15 km from Weissfluhjoch, Davos, CH. The data cover the period 01.01.2016 - 30.04.2016.

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

avalanche-danger

display_name: avalanche-danger

avalanche-problem-type

display_name: avalanche-problem-type

crocus

display_name: crocus

snow

display_name: snow

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability

snowpack

display_name: snowpack

weissfluhjoch

display_name: weissfluhjoch

en: Simulated avalanche problem types and seismic avalanche activity around Weissfluhjoch


en: treeline stillberg long-term-experiment afforestation mountain-forest

en: Site photo

en: This site photo is outdated and has been replaced with an updated version (see description).

en: Dataset V1

en: This dataset is outdated and has been replaced with an updated version (see description).

format: GDB

en: Documentation

en: This data documentation is outdated and has been replaced with an updated version (see description).

mimetype: application/msword

en:
 Important
This EnviDat entry is outdated. The most recent, usable version of the data can be found under the new EnviDat entry "Long-term afforestation experiment at the Alpine treeline site Stillberg, Switzerland." The entry can be found under this link <https://www.envidat.ch/dataset/afforestation-stillberg> and with this DOI 10.16904/envidat.397.

afforestation

display_name: afforestation

long-term-experiment

display_name: long-term-experiment

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline

display_name: treeline

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Long-term treeline research dataset at Stillberg, Davos


maintainer: Michael Nobis

en: invasive-species automatic-detection computer-vision artificial-intelligence biological-invasions plants

en: Detected occurrences of Senecio inaequidens along highways on the Swiss Plateau. The number of image tiles in which the species was recognized is shown (Fig. 25 in the report). Image coordinates of the middle and side strips can be displayed separately in the interactive map.

en: Detected occurrences of Ailanthus altissima along highways on the Swiss Plateau. The number of image tiles in which the species was recognized is shown (Fig. 23 in the report). Image coordinates of the middle and side strips can be displayed separately in the interactive map.

en: Detected occurrences of Senecio inaequidens along highways on the Swiss Plateau. To reduce false-positives, only images in which the species was recognized in at least three of 16 image tiles are considered as occurrences (Fig. 40 in the report). Image coordinates of the middle and side strips can be displayed separately in the interactive map.

en: Detected occurrences of Ailanthus altissima along highways on the Swiss Plateau. To reduce false-positives, only images in which the species was recognized in at least three of 16 image tiles are considered as occurrences (Fig. 38 in the report). Image coordinates of the middle and side strips can be displayed separately in the interactive map.

en:
Transport infrastructure such as **highways** are important corridors for the spread of invasive species. In this project, an automated detection and mapping of **two invasive alien plant species** was developed and applied along highways in the **Swiss Central Plateau**, based on **artificial intelligence (AI, Deep Learning)**. The two target species are **tree of heaven *(Ailanthus altissima)*** and **narrow-leaved ragwort *(Senecio inaequidens)***.
The data is part of the project report and shows the mapping results in **interactive maps**. Technically speaking, these are **self-contained HTML files** that can be displayed with standard web browsers. To reduce the file size, the downloads are provided in zip format.
**Report**: [https://www.mobilityplatform.ch/de/research-data-shop/product/1690](https://www.mobilityplatform.ch/de/research-data-shop/product/1690)
**Project**: [https://www.wsl.ch/en/projects/automated-detection-of-invasive-alien-plants-along-highways/](https://www.wsl.ch/en/projects/automated-detection-of-invasive-alien-plants-along-highways/)

artificial-intelligence

display_name: artificial-intelligence

automatic-detection

display_name: automatic-detection

biological-invasions

display_name: biological-invasions

computer-vision

display_name: computer-vision

invasive-species

display_name: invasive-species

plants

display_name: plants

en: Automated detection of invasive alien plants along highways


maintainer: Daniela Brito Melo

en: saltation large-eddy-simulations snow-cohesion mixed-grain-transport drifting-snow

en: LES-LSM code

en: Source code used to perform the analysis presented at the research article "Modeling snow saltation: the effect of grain size and interparticle cohesion". The source code is also available at the WSL/SLF GitLab Repository (https://gitlabext.wsl.ch/atmospheric-models/les-lsm).

en: Data in Figures

en: Simulation results presented in Figures 1 to 11 of the research article "Modeling snow saltattion: the effect of grain size and interparticle cohesion" in csv format.

en:
This dataset includes the parallel application and the main results supporting the research article "Modeling snow saltation: the effect of grain size and interparticle cohesion" published at the Journal of Geophysical Research: Atmospheres.
The code is a flow solver based on the Large Eddy Simulation (LES) technique coupled with a Lagrangian Stochastic Model (LSM). The interaction of snow particles with the bed is modeled with statistical and physically-based models for aerodynamic entrainment, rebound and splash, following the works of Groot Zwaaftink et al. (2014), Comola and Lehning (2017) and Sharma et al. (2018). This algorithm was also used by Sigmund et al. (2021) to model snow sublimation.

drifting-snow

display_name: drifting-snow

large-eddy-simulations

display_name: large-eddy-simulations

mixed-grain-transport

display_name: mixed-grain-transport

saltation

display_name: saltation

snow-cohesion

display_name: snow-cohesion


en: minion switzerland edna ins16s insect drone

en: Data access

en: Please use cyberduck to download

en:
Traditional methods of biodiversity monitoring are often logistically challenging, time-consuming, require experienced experts on species identification and sometimes include destruction of the targeted specimens. Here, we investigated a non-invasive approach of combining the use of drones and environmental DNA (eDNA) to monitor insect biodiversity on vegetation.
We aimed to assess the efficiency of this novel method in capturing insect diversity and comparing insect composition across different vegetation types (grassland, shrub, and forest) in Switzerland. A commercial, off-the-shelf drone was equipped with a specialised probe that autonomously swabbed vegetation and collected eDNA. Then, samples were processed using rapid third-generation Oxford Nanopore sequencing. The obtained data were analysed for insect diversity, comparing taxonomic richness, evenness and community composition across the three habitat types using statistical techniques. Sequencing of the samples yielded 76 hexapods taxa, revealing an insect community with notable differences in taxonomic richness but not in evenness across grassland, shrub, and forest habitats.
Our study demonstrates the potential of drone-based sampling integrated with eDNA and nanopore sequencing for biodiversity monitoring, offering a non-destructive method for detecting insect occurrence on plant surfaces. Integrating robotics and eDNA technology provides a promising solution for fast, large-scale, non-invasive biodiversity monitoring, potentially improving conservation efforts and ecosystem management.

drone

display_name: drone

edna

display_name: edna

insect

display_name: insect

minion

display_name: minion

switzerland

display_name: switzerland

educ

en: Education, culture and sport

en: Robot-aided measurement of insect diversity on vegetation using environmental DNA


en: avalanche natural-hazard hazard-mapping snow satellite

en: SPOT6 Avalanche outlines 24 January 2018

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

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.


maintainer: Christoph Marty

en: CH2014 REPORT

en:
CH2014-Impacts: Toward Quantitative Scenarios of Climate Change Impacts in Switzerland

The CH2014-Impacts report presents the results of a concerted effort of 15 Swiss research institutions to describe impacts of climate change in Switzerland quantitatively. This dataset contributes to the Crosphere/Snowcover section.

en: Dataset

en: Datasets are grouped under experiment "Aare" and "Graubunden".Data is also made available in netCDF format. A range of tools are available to [read netCDF](http://www.unidata.ucar.edu/software/netcdf/software.html).

en: Graubunden input

en: Grid input data for the 'Graubunden' CH2014 simulation.

mimetype: application/x-tar

en: Aare input

en: Grid input data for the 'Aare' CH2014 simulation.

en:
 Overview

The CH2014-Impacts initiative is a concerted national effort to describe impacts of climate change in Switzerland quantitatively, drawing on the scientific resources available in Switzerland today. The initiative links the recently developed Swiss Climate Change Scenarios CH2011 with an evolving base of quantitative impact models. The use of a common climate data set across disciplines and research groups sets a high standard of consistency and comparability of results. Impact studies explore the wide range of climatic changes in temperature and precipitation projected in CH2011 for the 21st century, which vary with the assumed global level of greenhouse gases, the time horizon, the underlying climate model, and the geographical region within Switzerland. The differences among climate projections are considered using three greenhouse gas scenarios, three future time periods in the 21st century, and three climate uncertainty levels (Figure 1). Impacts are shown with respect to the reference period 1980-2009 of CH2011, and add to any impacts that have already emerged as a result of earlier climate change.

 Experimental Setup

Future snow cover changes are simulated with the physics-based model Alpine3D (Lehning et al., 2006). It is applied to two regions: The canton of Graubünden and the Aare catchment. These domains are modeled with a Digital Elevation Model (DEM) with a resolution of 200 m × 200 m. This defines the simulation grid that has to be filled with land cover data and downscaled meteorological input data for each cell for the time period of interest at hourly resolution. The reference data set consists of automatic weather station data. All meteorological input parameters are spatially interpolated to the simulation grid. The reference period comprises only thirteen years (1999–2012), because the number of available high elevation weather stations for earlier times is not sufficient to achieve unbiased distribution of the observations with elevation. The model uses projected temperature and precipitation changes for all greenhouse gas scenarios (A1B, A2, and RCP3PD) and CH2011 time periods (2035, 2060, and 2085).

 Data

Snow cover changes are projected to be relatively small in the near term (2035) (Figure 5.1 top), in particular at higher elevations above 2000 m asl. As shown by Bavay et al. (2013) the spread in projected snow cover for this period is greater between different climate model chains (Chapter 3) than between the reference period and the model chain exhibiting the most moderate change. In the 2085 period much larger changes with the potential to fundamentally transform the snow dominated alpine area become apparent (Figure 5.1 bottom). These changes include a shortening of the snow season by 5–9 weeks for the A1B scenario. This is roughly equivalent to an elevation shift of 400–800 m. The slight increase of winter precipitation and therefore snow fall projected in the CH2011 scenarios (with high associated uncertainty) can no longer compensate for the effect of increasing winter temperatures even at high elevations. In terms of Snow Water Equivalents (SWE), the projected reduction is up to two thirds toward the end of the century (2085). A continuous snow cover will be restricted to a shorter time period and/or to regions at increasingly high elevation. In Bern, for example, the number of days per year with at least 5 cm snow depth will decrease by 90% from now 20 days to only 2 days on average.

climate-change

display_name: climate-change

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent

en: Alpine3D simulations of future climate scenarios CH2014


maintainer: Thorsten Bartels-Rausch

en: metamorphism alpine arctic antarctica solution brine snow interface ozone reaction laboratory-study chemistry heterogeneous

en: Readme file

en: This file shows data, code, and plots.

en: Matlab Data

en: All data as Matlab mat file

en: Matlab Script to view and plot data

en: Earth’s snow cover is very dynamic on diurnal time scales. The changes to the snow structure during this metamorphism have wide ranging impacts such as on avalanche formation and on the capacity of surface snow to exchange trace gases with the atmosphere. Here, we investigate the influence of dry metamorphism, which involves fluxes of water vapor, on the chemical reactivity of bromide in the snow. For this, the heterogeneous reactive loss of ozone at a concentration of 5-6E12 molecules cm-3 is investigated in artificial, shock-frozen snow samples doped with 6.2 uM sodium bromide and with varying metamorphism history. The oxidation of bromide in snow is one reaction initiating polar bromine releases and ozone depletions.

alpine

display_name: alpine

antarctica

display_name: antarctica

arctic

display_name: arctic

brine

display_name: brine

chemistry

display_name: chemistry

heterogeneous

display_name: heterogeneous

interface

display_name: interface

laboratory-study

display_name: laboratory-study

metamorphism

display_name: metamorphism

ozone

display_name: ozone

reaction

display_name: reaction

solution

display_name: solution

educ

en: Education, culture and sport

en: Data set on bromide oxidation by ozone in snow during metamorphism from laboratory study