envi

fr: Environnement

it: Ambiente

de: Link zum Fachportal

de: geocat.ch Permalink

en: geocat.ch permalink

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

fr: Service WMS-IFDG, couche "Etages de végétation 2085 moins sec"

de: WMS-BGDI Dienst, Layer "Höhenstufen 2085 mässig trocken"

en: WMS-FSDI service, layer "Altitudinal zones 2085 less dry"

it: Servizio WMS-IFDG, strato "Fasce altitudinali 2085 meno secco"

fr: Service WMTS-IFDG, couche , Layer "Etages de végétation 2085 moins sec"

de: WMTS-BGDI Dienst, Layer "Höhenstufen 2085 mässig trocken"

en: WMTS-FSDI service, layer "Altitudinal zones 2085 less dry"

it: Servizio WMTS-IFDG, strato "Fasce altitudinali 2085 meno secco"

fr: Lien vers la distribution des données

de: Link zum Datenbezug

en: Link for download

it: Link per le fonti dei dati

fr: Cette carte montre les étages de végétation forestière en Suisse pour la période 2070-2099 dans l'hypothèse d'un futur climat moins sec. Les étages de végétation suivants ne sont présents que dans les vallées méridionales: «méditerranée», «hyperinsubrique», «collinéen avec hêtre», et «montagnard inférieur/supérieur». La carte «Étages de végétation modélisés pour 1995» sert de base pour le déplacement des étages de végétation à l’avenir. Parmi les trajectoires de concentration représentatives, le trajectoire RCP 4.5 avec la combinaison de modèles SMHI-RCA_MPIESM_EUR44 a été choisi comme projection «moins sèche» (NCCS 2018). Ce modèle projète un réchauffement moyen de 1.8 °C (nord de la Suisse), resp. 2.3 °C (sud de la Suisse) et une réduction des précipitations de 4.0% (nord de la Suisse), resp. 0.5% (sud de la Suisse) pour les mois d’avril à août, qui sont considérés comme les plus pertinents pour l'adéquation climatique des arbres, par rapport à la période 1981-2010 (Remund 2020). La limite supérieure naturelle de la forêt a été modélisée par une approche analogue (Könz et al. 2021). --- Source : Zischg et al. (subm.)

de: Diese Karte bildet die Höhenstufen der Waldvegetation in der Schweiz für die Periode 2070 - 2099 unter Annahme einer weniger trockenen Klimazukunft ab. Folgende Höhenstufen kommen nur in den Südtälern vor: «mediterran», «hyperinsubrisch», «collin mit Buche», und «unter-/obermontan». Als Grundlage für die Verschiebung der Höhenstufen in die Zukunft dient die Karte «Vegetationshöhenstufen modelliert für 1995». Unter den Repräsentativen Konzentrationspfaden wurde RCP 4.5 mit der Modellkombination SMHI-RCA_MPIESM_EUR44 als «weniger trockene» Klimaprojektion gewählt (NCCS 2018). Dieses Modell schätzt im Vergleich zur Periode 1981-2010 für die Monate April bis August, die als für die Klimaeignung der Bäume am relevantesten angesehen werden, eine durchschnittliche Erwärmung um 1.8 °C (Nordschweiz), resp. 2.3 °C (Südschweiz), und eine Reduktion der Niederschläge um 4.0% (Nordschweiz) bzw. 0.5% (Südschweiz) (Remund 2020). Die natürliche obere Waldgrenze wurde mit einem analogen Vorgehen modelliert (Könz et al. 2021). --- Quelle: Zischg et al. (subm.)

en: This map shows the altitudinal vegetation belts of forest vegetation in Switzerland for the period 2070-2099 assuming a less dry future climate. The following altitudinal vegetation belts only occur in the southern valleys: «mediterranean», «hyperinsubric», «colline with beech», and «lower/upper montane». The map «Modelled altitudinal vegetation belts for 1995» serves as a basis for the shift of the altitudinal vegetation belts into the future. Among the Representative concentration pathways, RCP 4.5 with the model combination SMHI-RCA_MPIESM_EUR44 was selected as the «less dry» projection (NCCS 2018). This model projects an average warming of 1.8 °C (northern Switzerland) or 2.3 °C (southern Switzerland) and a reduction in precipitation of 4.0% (northern Switzerland) or 0.5% (southern Switzerland) for the months April-August, which are considered most relevant for the climate suitability of trees, compared to the period 1981-2010 (Remund 2020). The natural upper timberline was also modelled using an analogous procedure (Könz et al. 2021). --- Source: Zischg et al. (subm.)

it: Questa carta mostra la quota delle diverse fasce altitudinali della vegetazione forestale in Svizzera per il periodo 2070-2099 nell'ipotesi di un futuro di clima meno secco. Le seguenti fasce altitudinali sono presenti solo nelle valli meridionali: «mediterraneo», «iperinsubrica», «collinare con faggio» e «montana inferiore/superiore». La carta «Fasce altitudinali modellati per 1995» serve come base per lo spostamento delle fasce altitudinali nel futuro. Il percorso di concentrazione rappresentativo RCP 4.5 con la combinazione di modelli SMHI-RCA_MPIESM_EUR44 è stata scelta come la proiezione «meno secca» (NCCS 2018). Questo modello stima un riscaldamento medio di 1.8 °C (Svizzera settentrionale), rispettivamente di 2.3 °C (Svizzera meridionale), e una riduzione delle precipitazioni del 4.0% (Svizzera settentrionale), rispettivamente dello 0.5% (Svizzera meridionale) per i mesi aprile-agosto, che sono considerati i più rilevanti in relazione all'idoneità climatica degli alberi, rispetto al periodo 1981-2010 (Remund 2020). Il limite superiore naturale della foresta è stato modellato con un approccio analogo (Könz et al. 2021). --- Fonte: Zischg et al. (subm.)

fr: Division forêts, Office fédéral de l'environnement

en: Forest Division, Federal Office of the Environment

it: Divisione foreste, Ufficio federale dell'ambiente

fr: Office fédéral de l'environnement OFEV

en: Federal Office for the Environment FOEN

it: Ufficio federale dell'ambiente UFAM

de: Die Fachbehörde für die Umwelt. Es ist zuständig für die nachhaltige Nutzung der natürlichen Ressourcen sowie für den Schutz des Menschen vor Naturgefahren und den Schutz der Umwelt vor übermässigen Belastungen.

fr: Etages de végétation modélisés pour 2085 avec futur climat moins sec

de: Vegetationshöhenstufen modelliert für 2085 mit weniger trockener Klimazukunft

en: Altitudinal vegetation belts in Switzerland for 2085 with less dry future climate

it: Fasce altitudinali modellati per 2085 con futuro clima meno secco


tannenareale

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

de: Umwelt

en: Environment

title_for_slug: tannenareale

author: Abteilung Wald, Bundesamt für Umwelt

fr: Lien vers le portail

en: Link to portal

it: Link per il portale

fr: geocat.ch permalien

it: geocat.ch link permanente

state: active

type: dataset

fr: Map (Preview) Aperçu 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 "Aires du sapin blanc"

de: WMS-BGDI Dienst, Layer "Tannenareale"

en: WMS-FSDI service, layer "Areas of silver fir"

it: Servizio WMS-IFDG, strato "Areale dell`abete bianco"

format: WMS

fr: Service WMTS-IFDG, couche , Layer "Aires du sapin blanc"

de: WMTS-BGDI Dienst, Layer "Tannenareale"

en: WMTS-FSDI service, layer "Areas of silver fir"

it: Servizio WMTS-IFDG, strato "Areale dell'abete bianco"

format: WMTS

fr: La carte montre les aires de sapin blanc. Dans l'aire principale, le sapin contribue naturellement dans une large mesure à la structure du peuplement dans les étages de végétation de montagnard supérieur et de haute-montagnard. Dans l'aire secondaire, sa vitalité est plus faible que dans l'aire principale. Selon la région et l'écotype, il est encore impliqué à des degrés divers dans la structure du peuplement. Dans l'aire relictuelle, il se trouve tout au plus dans de petits peuplements isolés comme vestiges d'une zone du sapin autrefois plus grande.Les écorégions forestières ont été élaborées pour "Gestion durable des forêts de protection" (Frehner et al. 2005). Des informations détaillées sont disponibles sur https://www.gebirgswald.ch/de/nais-download.html

de: Die Karte zeigt die Areale der Weisstanne. Im Hauptareal ist die Tanne in der obermontanen und hochmontanen Stufe natürlicherweise in einem erheblichen Masse am Bestandesaufbau beteiligt. Im Nebenareal ist ihre Vitalität im Vergleich zum Hauptareal geringer. Je nach Region und Ökotyp ist sie hier noch unterschiedlich stark am Bestandesaufbau beteiligt. Im Reliktareal kommt sie höchstens noch in kleinen, isolierten Beständen als Relikte eines ehemals grösseren Tannenareals vor.Die Tannenareale wurden erarbeitet für "Nachhaltigkeit und Erfolgskontrolle im Schutzwald" (Frehner et al. 2005). Detaillierte Informationen stehen zur Verfügung unter https://www.gebirgswald.ch/de/nais-download.html

en: The map shows the areas of silver fir occurrence. In the main area, fir is naturally involved to a considerable extent in the stand development in the upper montane and high-montane vegetation belts. In the secondary area, its vitality is lower than in the main area. Depending on the region and ecotype, it is still involved to varying degrees in the stand build-up. In the relict area it occurs at most in small, isolated stands as relics of a formerly larger fir area.The areas of silver fir were developed for "Sustainability and success monitoring in protection forests" (Frehner et al. 2005). Detailed information is available at https://www.gebirgswald.ch/de/nais-download.html

it: La carta mostra gli areali dell'abete bianco. Nell'areale principale, l'abete bianco è naturalmente coinvolto in larga misura nello sviluppo dei popolamenti nelle fasce altitudinali montana superiore e altimontana. Nell'areale secondario, la sua vitalità è inferiore a quella dell'areale principale. A seconda della regione e dell'ecotipo, la specie è ancora coinvolta, in misura diversa, nella costruzione del popolamento. Nell'areale relitto dell'abete quest'ultimo è presente al massimo in piccole aree isolate in forma di relitti di un'areale maggiore nel passato.Le areale dell'abete bianco sono state sviluppate per "Continuità nel bosco di protezione e controllo dell'efficacia" (Frehner et al. 2005). Informazioni dettagliate si trovano su https://www.gebirgswald.ch/de/nais-download.html

spatial: Schweiz

de: Abteilung Wald, Bundesamt für Umwelt

bundesamt-fur-umwelt-bafu

de: Bundesamt für Umwelt BAFU

fr: L’autorité compétente pour les questions environnementales. Il est à ce titre chargé de gérer les ressources naturelles selon les principes du développement durable et de protéger l’homme contre les dangers naturels et l’environnement contre les pollutions.

en: The federal environmental authority. It is responsible for ensuring that natural resources are used sustainably, that the public is protected against natural hazards, and that the environment is protected from unacceptable adverse impacts.

it: Il servizio specializzato in materia ambientale, è competente per quanto riguarda l'utilizzazione sostenibile delle risorse naturali, la protezione delle persone dai pericoli naturali e dell'ambiente da un inquinamento eccessivo.

political_level: confederation

type: organization

approval_status: approved

value: BAFU - Geocat Harvester

fr: Aires du sapin blanc

de: Tannenareale

en: Areas of silver fir

it: Areale dell'abete bianco


envi

fr: Environnement

it: Ambiente

author: Info Flora GENÈVE

de: Link zum Fachportal

de: geocat.ch Permalink

en: geocat.ch permalink

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

fr: Service WMS-IFDG, couche "Chèvrefeuille du Japon"

de: WMS-BGDI Dienst, Layer "Japanisches Geissblatt"

en: WMS-FSDI service, layer "Lonicera japonica"

it: Servizio WMS-IFDG, strato "Caprifoglio giapponese"

fr: Service WMTS-IFDG, couche , Layer "Chèvrefeuille du Japon"

de: WMTS-BGDI Dienst, Layer "Japanisches Geissblatt"

en: WMTS-FSDI service, layer "Lonicera japonica"

it: Servizio WMTS-IFDG, strato "Caprifoglio giapponese"

de: Link für Datenbezug

format: HTML

fr: Le set « plantes exotiques envahissantes » contient les cartes de distribution potentielle pour 56 plantes exotiques envahissantes en Suisse et répertoriées dans la Liste Noire et la Watch-List, ou présentes dans les pays voisins et ayant le potentiel de coloniser la Suisse. Les cartes sont le résultat de modélisation de l'Université de Lausanne et prédisent leur potentiel de propagation de ces espèces en Suisse. Les modèles sont basés respectivement sur les données d’occurrence du GBIF (Global Biodiversity Information Facility) et associées aux données climatiques de Worldclim (résolution de 1km), et sur les données d’occurrence d'infoflora associées aux données climatiques du WSL (résolution de 100m). Les cartes à 100m utilisent également d’autres variables telles que l'utilisation du sol et de la géologie.

de: Das Set Invasive gebietsfremde Pflanzen enthält die Karten der potentiellen Verbreitung von 56 in der Schweiz vorkommenden invasiven gebietsfremden Arten sowie solchen aus Nachbarländern mit dem Potential sich in die Schweiz auszudehnen. Die Karten sind das Ergebnis einer Modellierung der Uni Lausanne zur Vorhersage der Verbreitung von invasiven Pflanzen, welche in der Schwarzen Liste resp. der Watchliste aufgeführt sind. Das Modell basiert auf den verfügbaren Daten von GBIF (Global Biodiversity Information Facility), verknüpft mit aktuellen Klimadaten von Worldclim (1km Auflösung) sowie den verfügbaren Daten von InfoFlora verknüpft mit Klimadaten der WSL (100 m Auflösung). Die Karten mit 100 m Auflösung beinhalten weitere Variablen wie Landnutzung und Geologie.

en: The set of invasive alien plants shows the maps of the potential areas of 56 alien plants species present in Switzerland as well as some invasive species present in neighboring countries with the potential to reach Switzerland. The maps are the result of model-based tool to anticipate the spread of invasive alien plants listed on the Swiss Black and Watch list. The model is using occurrence data from GBIF (Global Biodiversity Information Facility), current climate data from Worldclim(1 km resolution) and occurrence data from InfoFlora combined with climate data from the WSL (100 m resolution).The maps with 100 m resolution utilize additional necessary variables including landuse and geology.

it: Il set Piante esotiche invasive contiene le carte di distribuzione potenziale di 56 specie di piante invasive non indigene presenti in Svizzera nonché di quelle dei Paesi vicini che hanno il potenziale di diffondersi in Svizzera. Le carte sono il frutto di una modellizzazione operata dall'Università di Losanna per prevedere la distribuzione delle piante invasive riportate nella lista nera, rispettivamente nella lista di osservazione Il modello si basa sui dati disponibili della GBIF (Global Biodiversity Information Facility) combinati con dati climatici aggiornati di Worldclim (risoluzione 1km) nonché sui dati disponibili di InfoFlora combinati con dati climatici di WSL (risoluzione 100 m). Le carte con una risoluzione di 100 m contengono altre variabili, come lo sfruttamento del terreno e la geologia.

fr: Office fédéral de l'environnement / Division Biodiversité et paysage

de: Bundesamt für Umwelt / Abteilung Biodiversität und Landschaft

en: Federal Office for the Environment / Biodiversity and Landscape Division

it: Ufficio federale dell'ambiente / Divisione Biodiversità e paesaggio

fr: Plantes exotiques envahissantes - Carte de distribution potentiel Chèvrefeuille du Japon

de: Invasive gebietsfremde Pflanzen - Potentialkarte Japanisches Geissblatt

en: Invasive alien plants - map of the potential area Lonicera japonica

it: Piante esotiche invasive - carte di distribuzione potenziale Caprifoglio giapponese


ladepreiskarte-swiss-emobility

title_for_slug: ladepreiskarte-swiss-emobility

fr: infrastructure-de-recharge chargement frais-delectricite transparence-des-prix kwh prix-de-la-recharge mobilite-electrique voiture-electrique mobilite

de: kwh ladeinfrastruktur preistranparenz aufladen stromkosten mobilitat elektroauto elektromobilitat ladepreis

en: charging-infrastructure charge price-transparency charging-price electricity-costs mobility electric-mobility electric-car kwh

it: auto-elettrica mobilita costi-dellelettricita prezzo-di-ricarica infrastruttura-di-ricarica elettromobilita ricarica kwh trasparenza-dei-prezzi

fr: Carte interactive atlas des prix de la recharge

de: Interaktive Karte Ladepreisatlas

en: Interactive Map Charging Prize Atlas

it: Mappa interattiva atlante dei prezzi di ricarica

media_type: application/json

fr: Tous les prix de recharge des membres de Swiss eMobility, qui mettent à disposition leurs données de prix en direct, peuvent être facilement consultés sur la carte en ligne.

de: Alle Ladepreise der Swiss eMobility Mitglieder, die Ihre Preisdaten live verfügbar machen, sind auf der Online-Karte bequem abrufbar.

en: All charging prices of Swiss eMobility members who make their price data available live can be conveniently accessed on the online map.

it: Tutti i prezzi di ricarica dei membri di Swiss eMobility che rendono disponibili i loro dati sui prezzi in tempo reale possono essere comodamente richiamati sulla mappa online.

format: JSON

fr: Valeurs actuelles de l'atlas des prix de chargement

en: Current values from the charging price atlas

de: Aktuelle Werte aus dem Ladepreisatlas

it: Valori attuali dall'atlante dei prezzi di ricarica

fr: Accès à la base de données en direct de l'atlas des prix de chargement

de: Zugang zu der Live Datenbank vom Ladepreisatlas

en: Access to the live charging tariffs database

it: Accesso al database live dell'atlante dei prezzi di ricarica

fr:
Combien coûte la recharge d'un véhicule électrique chez les différents fournisseurs de bornes de recharge ? La carte des prix de recharge indique tous les prix de recharge des membres de Swiss eMobility qui mettent leurs données de prix à disposition en direct.

Exemples et instructions pour la connexion via OCPI ou CSV pour les membres de Swiss eMobility disponibles ici : https://docs.google.com/spreadsheets/d/1P8ZnCo_Y9RHN0T9ZFx35WIlyBx3Tt3Iy6AFdupmFK-E/edit?usp=sharing

Malgré un contrôle minutieux, des erreurs ne peuvent pas être totalement exclues. Par conséquent, aucune valeur juridique n'est assumée.

de:
Wie viel kostet das Aufladen des Elektrofahrzeugs bei den verschiedenen Anbietern von Ladestellen? Die Ladepreiskarte zeigt alle Ladepreise der Mitglieder von Swiss eMobility, die ihre Preisdaten live verfügbar machen.

Beispiele und Anleitung zur Anbindung via OCPI oder CSV für Swiss eMobility Mitglieder hier verfügbar: https://docs.google.com/spreadsheets/d/1P8ZnCo_Y9RHN0T9ZFx35WIlyBx3Tt3Iy6AFdupmFK-E/edit?usp=sharing

Trotz sorgfältiger Prüfung können Fehler nicht vollständig ausgeschlossen werden, daher keine rechtliche Verbindlichkeit.

en:
How much does it cost to charge an electric vehicle at the various charging point providers? The charging price map shows all the charging prices of Swiss eMobility members who make their price data available in real time.

Examples and instructions for connection via OCPI or CSV for Swiss eMobility members are available here: https://docs.google.com/spreadsheets/d/1P8ZnCo_Y9RHN0T9ZFx35WIlyBx3Tt3Iy6AFdupmFK-E/edit?usp=sharing

Despite careful review, errors cannot be entirely excluded; therefore, no legal validity is assumed.

it:
Quanto costa ricaricare il veicolo elettrico presso i vari fornitori di punti di ricarica? La mappa dei prezzi di ricarica mostra tutti i prezzi di ricarica dei membri di Swiss eMobility che rendono disponibili i loro dati sui prezzi in tempo reale.

Esempi e istruzioni per la connessione tramite OCPI o CSV per i membri di Swiss eMobility sono disponibili qui: https://docs.google.com/spreadsheets/d/1P8ZnCo_Y9RHN0T9ZFx35WIlyBx3Tt3Iy6AFdupmFK-E/edit?usp=sharing

Nonostante un'attenta verifica, non si possono escludere del tutto errori, pertanto non si assume alcun valore legale.

aufladen

display_name: aufladen

auto-elettrica

display_name: auto-elettrica

charge

display_name: charge

chargement

display_name: chargement

charging-infrastructure

display_name: charging-infrastructure

charging-price

display_name: charging-price

costi-dellelettricita

display_name: costi-dellelettricita

electric-car

display_name: electric-car

electric-mobility

display_name: electric-mobility

electricity-costs

display_name: electricity-costs

elektroauto

display_name: elektroauto

elektromobilitat

display_name: elektromobilitat

elettromobilita

display_name: elettromobilita

frais-delectricite

display_name: frais-delectricite

infrastructure-de-recharge

display_name: infrastructure-de-recharge

infrastruttura-di-ricarica

display_name: infrastruttura-di-ricarica

kwh

display_name: kwh

ladeinfrastruktur

display_name: ladeinfrastruktur

ladepreis

display_name: ladepreis

mobilita

display_name: mobilita

mobilitat

display_name: mobilitat

mobilite

display_name: mobilite

mobilite-electrique

display_name: mobilite-electrique

mobility

display_name: mobility

preistranparenz

display_name: preistranparenz

prezzo-di-ricarica

display_name: prezzo-di-ricarica

price-transparency

display_name: price-transparency

prix-de-la-recharge

display_name: prix-de-la-recharge

ricarica

display_name: ricarica

stromkosten

display_name: stromkosten

transparence-des-prix

display_name: transparence-des-prix

trasparenza-dei-prezzi

display_name: trasparenza-dei-prezzi

voiture-electrique

display_name: voiture-electrique

spatial: CH

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

swiss-emobility

fr: L'association Swiss eMobility a été fondée en 2012. Swiss eMobility soutient la création des bases politiques et institutionnelles pour le développement de l'électromobilité en Suisse. Elle défend les intérêts de ses membres en lien avec l'électromobilité. Elle traite des questions économiques, juridiques, techniques, structurelles, écologiques et sociales liées à l'électromobilité, émet des recommandations et prend des mesures à l'intention des autorités et des parlements. Swiss eMobility est en principe ouverte à toutes les personnes, entreprises et institutions intéressées par le développement du marché de l'électromobilité en Suisse. Vous trouverez plus d'informations sur [notre site internet](www.swiss-emobility.ch"Swiss eMobility")

en: The Swiss eMobility association was founded in 2012. Swiss eMobility supports the creation of political and institutional foundations for the development of electromobility in Switzerland. It advocates for the interests of its members in relation to electromobility. It addresses economic, legal, technical, structural, ecological, and social issues of electromobility, provides recommendations, and takes measures directed at authorities and parliaments. Swiss eMobility is generally open to all interested individuals, companies, and institutions committed to developing the electromobility market in Switzerland. For more information, please visit [our website](www.swiss-emobility.ch"Swiss eMobility").

de: Der Verband Swiss eMobility wurde 2012 gegründet. Swiss eMobility unterstützt die Schaffung der politischen und institutionellen Grundlagen für die Entwicklung der Elektromobilität in der Schweiz. Er tritt ein für die Wahrung der Interessen seiner Mitglieder im Zusammenhang mit der Elektromobilität. Er befasst sich mit wirtschaftlichen, rechtlichen, technischen, strukturellen, ökologischen und sozialen Fragen der Elektromobilität, gibt Empfehlungen ab und trifft Massnahmen zuhanden von Behörden und Parlamenten. Swiss eMobility steht grundsätzlich allen interessierten Einzelpersonen, Unternehmen und Institutionen offen, die sich für die Marktentwicklung der Elektromobilität in der Schweiz einsetzen. Weitere Informationen finden Sie auf [unserer Webseite](www.swiss-emobility.ch"Swiss eMobility").

it: L'associazione Swiss eMobility è stata fondata nel 2012. Swiss eMobility sostiene la creazione delle basi politiche e istituzionali per lo sviluppo della mobilità elettrica in Svizzera. Difende gli interessi dei suoi membri in relazione alla mobilità elettrica. Si occupa di questioni economiche, legali, tecniche, strutturali, ecologiche e sociali relative alla mobilità elettrica, fornisce raccomandazioni e adotta misure destinate alle autorità e ai parlamenti. Swiss eMobility è fondamentalmente aperta a tutte le persone, aziende e istituzioni interessate allo sviluppo del mercato della mobilità elettrica in Svizzera. Ulteriori informazioni sono disponibili su [il nostro sito web](www.swiss-emobility.ch"Swiss eMobility").

fr: Atlas des tarifs de recharge Swiss eMobility

it: Atlante dei prezzi di ricarica Swiss eMobility


elektro-leitungen

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

de: Umwelt

en: Environment

title_for_slug: elektro-leitungen

author: Elektrizitätswerke

fr: geocat.ch permalien

de: 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

format: WFS

fr: Elektro Trasse, Bauwerke und Trassepunkte.

spatial: Canton of Uri (UR)

fr: Elektrizitätswerke

de: Elektrizitätswerke

en: Elektrizitätswerke

it: Elektrizitätswerke

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.

political_level: canton

kanton-uri

capacity: public

value: Uri-Kt - Geocat Harvester

fr: Elektro Leitungen

de: Elektro Leitungen

en: Elektro Leitungen

it: Elektro Leitungen


wasser-leitungen-offentlich

envi

fr: Environnement

it: Ambiente

title_for_slug: wasser-leitungen-offentlich

en: geocat.ch permalink

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: Gemeinden des Kt. Uri

de: Gemeinden des Kt. Uri

en: Gemeinden des Kt. Uri

it: Gemeinden des Kt. Uri

fr: Wasser Leitungen öffentlich

de: Wasser Leitungen öffentlich

en: Wasser Leitungen öffentlich

it: Wasser Leitungen öffentlich


gemeindliche-nutzungsplanung-ur

title_for_slug: gemeindliche-nutzungsplanung-ur

de: nutzungsplanung zonenplan geobasisdaten

fr: Die Nutzungsplanung ordnet die räumlichen Sachverhalte in genereller Weise: die Nutzung des Bodens, die Erschliessung, den Schutz usw., indem er eigentümerverbindlich und parzellenscharf Art und Mass der Nutzung festlegt (Art. 14 RPG).

fr: Amt für Raumentwicklung Kt. Uri

de: Amt für Raumentwicklung Kt. Uri

en: Amt für Raumentwicklung Kt. Uri

it: Amt für Raumentwicklung Kt. Uri

fr: Gemeindliche Nutzungsplanung (UR)

de: Gemeindliche Nutzungsplanung (UR)

en: Gemeindliche Nutzungsplanung (UR)

it: Gemeindliche Nutzungsplanung (UR)


fledermaus-inventar

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

title_for_slug: fledermaus-inventar

fr: Dieses Inventar dient dazu, einen Überblick über dachstockbewohnende Fledermäuse in ausgewählten öffentlichen Gebäuden des Kantons zu bekommen. Einige Fledermausarten nutzen ungestörte Dachstöcke. Es sind dies vor allem seltene Arten wie das Grosse Mausohr, das Braune und das Alpenlangohr sowie die Kleine Hufeisennase. Letztere ist im Kanton Uri jedoch nicht nachgewiesen. Durch die Angaben können besonders wertvolle Quartiere und Wochenstuben geschützt und der Schutz der Fledermäuse kann bei Sanierungsmassnahmen der Gebäude beachtet werden.

fr: Fledermaus Inventar

de: Fledermaus Inventar

en: Fledermaus Inventar

it: Fledermaus Inventar


kantonsstrassenverzeichnis

regi

fr: Régions et villes

tran

fr: Transports

de: Verkehr

it: Trasporti

title_for_slug: kantonsstrassenverzeichnis

de: verkehrsnetz strasse strassenachse kantonsstrasse

de: Kantonsstrassenverzeichnis

media_type: application/zip

format: ZIP

de: WMS-Dienst Kanton Glarus

de: Folgende Layer stehen zur Verfügung: ch.gl.transportation.kantonsstrassen,ch.gl.transportation.kantonsstrassen_abschnitte

de: WFS-Dienst Kanton Glarus

de: Verzeichnis der Kantonsstrassen inkl. Abschnitte (topologisches Netz). Erfasst werden die Haupt- und Nebenstrassen im Eigentum des Kantons beziehungsweise in Zuständigkeit des Kantons für den Strassenunterhalt.

spatial: Kanton Glarus (GL)

de: Hauptabteilung Tiefbau (DBU)

en: Office of Geoinformation, Canton of Glarus

de: Fachstelle Geoinformation des Kantons Glarus. Zuständig für die kantonale Geodaten-Infrastruktur inklusive Geoportal und Datenbereitstellung.

value: Glarus-kt - Geocat Harvester


wasserrechte

regi

de: Regionen und Städte

envi

de: Umwelt

title_for_slug: wasserrechte

de: konzession wasserrecht entnahme ruckgabe kanal wasserrechtskanal stauwehr stauwehrreglement wasserrechtskonzession eheliche-konzession wasserrechtsbezirk wasserrechtsnummer

author: Kanton Zürich

fr: geocat.ch permalien

de: geocat.ch Permalink

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

fr: Öffentliche Oberflächengewässer, Gewässerraum und Wasserrechte

fr: Die konzessionierten Wasserrechte wurden ab 1997 mit den öffentlichen Oberflächengewässern im GIS erfasst und werden seit 1998 als eigener Datensatz in Abstimmung zu den öffentlichen Oberflächengewässern vom AWEL, Abt. Wasserbau nachgeführt. Seit Januar 2022 werden aktive und gelöschte Wasserrechte in getrennten Datensätzen zu Verfügung gestellt. Die Daten sind auf dem SDE Server vom GIS-ZH abgelegt unter: GISZHPUB.WASSERRECHTE_F für die Wasserrechtsweiher (Flächendaten) GISZHPUB.WASSERRECHTE_GELOESCHT_F für die gelöschten Wasserrechtsweiher (Flächendaten) GISZHPUB.WASSERRECHTE_L für die Wasserrechtskanäle und Leitungen (Liniendaten) GISZHPUB.WASSERRECHTE_GELOESCHT_L für die gelöschten Wasserrechtskanäle und Leitungen (Liniendaten) GISZHPUB.WASSERRECHTE_P für die Entnahme- und Rückgabeorte (Punktdaten) GISZHPUB.WASSERRECHTE_GELOESCHT_P für die gelöschten Entnahme- und Rückgabeorte (Punktdaten)

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.

value: ZH - Geocat Harvester

fr: Wasserrechte

de: Wasserrechte

en: Wasserrechte

it: Wasserrechte


grundwasserschutzareale-projektiert-ur

regi

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

en: Environment

title_for_slug: grundwasserschutzareale-projektiert-ur

de: grundwasserschutzareal geobasisdaten

it: geocat.ch link permanente

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: Grundwasserschutzareale sind speziell ausgeschiedene Gebiete, in welchen der Schutz des unterirdischen Gewässers im Hinblick auf eine künftige Grundwasserbewirtschaftung (Nutzung oder Anreicherung) vorsorglich sichergestellt werden soll. In diesen Arealen dürfen keine Bauten und Anlagen erstellt werden, welche die künftige Bewirtschaftung beeinträchtigen können.

fr: Amt für Umwelt Kt. Uri

de: Amt für Umwelt Kt. Uri

en: Amt für Umwelt Kt. Uri

it: Amt für Umwelt 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.


bodenverbesserungsgenossenschaften

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

title_for_slug: bodenverbesserungsgenossenschaften

fr: telepherique geodonnees-de-base

de: seilbahn geobasisdaten

en: cableway official-geodata

it: teleferica geodati-di-base

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: Der Datensatz umfasst die öffentlich-rechtlichen Bodenverbesserungsgenossenschaften gemäss RB 9.36161. Es wird zwischen Wegbau-, Meliorations-, Wasserversorgungs- und Seilbahngenossenschaften unterschieden. Als Dokument je Genossenschaft ist nur der Übersichtsplan öffentlich zugänglich. Der Datensatz befindet sich zurzeit im Aufbau und es sind bis jetzt die Wegbaugenossenschaften digitalisiert. Die weiteren Genossenschaftstypen werden aufgeschaltet, sobald die Daten digital erhoben sind.

fr: Amt für Landwirtschaft Kt. Uri

de: Amt für Landwirtschaft Kt. Uri

en: Amt für Landwirtschaft Kt. Uri

it: Amt für Landwirtschaft Kt. Uri

fr: Bodenverbesserungsgenossenschaften

de: Bodenverbesserungsgenossenschaften

en: Bodenverbesserungsgenossenschaften

it: Bodenverbesserungsgenossenschaften


naturschutzgebiete-kantonal

title_for_slug: naturschutzgebiete-kantonal

de: Naturschutzgebiete

de: Kantonale Naturschutzgebiete, durch den Kantonsrat im Richtplan bezeichnet. Die zugehörigen Schutzpläne sind vom Regierungsrat erlassen.

naturschutz

display_name: naturschutz

name: Amt für Raum und Verkehr 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: Naturschutzgebiete kantonal


kommunale-bebauungsplane

regi

fr: Régions et villes

de: Regionen und Städte

envi

de: Umwelt

it: Ambiente

title_for_slug: kommunale-bebauungsplane

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

author: Kanton Luzern, Abteilung Geoinformation

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

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

de: Kanton Luzern, Abteilung Geoinformation

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

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

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

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

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

value: LU-Kt - Geocat Harvester

de: Kommunale Bebauungspläne


maintainer: EnviDat Support

en: enet snow-height snow-temperatures weissfluhjoch snow-water-equivalent imis

en: DATA ACCESS

en:
Station WFJ2: merged IMIS + ENET datasets. Provides parameters height of snow, snow surface temperatures and snow temps at 0, 1, 1.5 m above ground surface. Supporting meteo data are also contained in this dataset.

fields      = timestamp TA RH TSG TSS HS VW DW VW_MAX OSWR PSUM VW_DRIFT DW_DRIFT TS1 TS2 TS3 HTS1 HTS2 HTS3

en: This dataset provides HS, TSS and TS50, TS100, TS150 at the station WFJ2 situated on the Weisfluhjoch research site (2536 m asl). It has been created from merging ENET and IMIS datsets to form a continuous timeseries from 1992- present. ENET is at 1 h resolution whereas IMIS is 30 min. This is a level 2 dataset as defined [here](http://models.slf.ch/p/dataset-processing/).

enet

display_name: enet

imis

display_name: imis

snow-height

display_name: snow-height

snow-temperatures

display_name: snow-temperatures

snow-water-equivalent

display_name: snow-water-equivalent

weissfluhjoch

display_name: weissfluhjoch

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: WFJ2: Snow measurements from the Weissfluhjoch research site, Davos


en: sentinel-2 time-series remote-sensing switzerland tree-species

media_type: text/csv

en: Tree species profiles for 2020, Red-Edge-2 band

format: CSV

en: Tree species profiles for 2020, CCI index

en: Tree species profiles for 2019, Red-Edge-1 band

en: Tree species profiles for 2020, Red band

en: Tree species profiles for 2019, Green band

en: Tree species profiles for 2019, SWIR-2 band

en: Tree species profiles for 2019, Red-Edge-2 band

en: Tree species profiles for 2020, Blue band

en: Tree species profiles for 2020, SWIR-2 band

en: Tree species profiles for 2019, Red-Edge-3 band

en: Tree species profiles for 2019, CCI index

en: Tree species profiles for 2019, NDVI index

en: Tree species profiles for 2020, SWIR-1 band

en: Tree species profiles for 2019, NIR band

en: Tree species profiles for 2020, Red-Edge-1 band

en: Tree species profiles for 2020, NIR band

en: Tree species profiles for 2020, NDVI index

en: Tree species profiles for 2019, Red band

en: Tree species profiles for 2020, NDMI index

en: Tree species profiles for 2020, Red-Edge-3 band

en: Tree species profiles for 2019, Blue band

en: Tree species profiles for 2020, Green band

en: Tree species profiles for 2020, EVI index

en: Tree species profiles for 2019, EVI index

en: Tree species profiles for 2019, CIre Index

en: Tree species profiles for 2020, CIre index

en: Tree species profiles for 2019, SWIR-1 band

en: Tree species profiles for 2019, NDMI/NDWI index

en:
 Tree species profiles from Sentinel-2 time series
We obtained tree species-specific Sentinel-2 time series for the years 2019 and 2020. The Sentinel-2 time series originated from [here](https://www.envidat.ch/#/metadata/sentinel-2-time-series-of-switzerland), and the tree species information was derived from pure plots of the Swiss National Forest Inventory, spread all over Switzerland.
In addition to the 10 and 20 m bands from Sentinel-2 (Blue, Green, Red, Red-Edge-1, Red-Edge-2, Red-Edge-3, NIR, SWIR-1, SWIR-2), we calculated indices (CCI, CIre, EVI, NDMI/NDWI, NDVI).
In total, tree species profiles of 763 pixels for 2020 and 562 pixels for 2019 are available for seven tree species (*Abies alba*, *Castanea sativa*, *Fagus sylvatica*, *Fraxinus excelsior*, *Larix* spp., *Picea abies*, *Pinus sylvestris*).

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

time-series

display_name: time-series

tree-species

display_name: tree-species


maintainer: Achille Capelli

en: gnss gps lwc snow liquid-water-content snow-water-equivalent swe

en: Snow and meteo data from automatic sensors for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

mimetype: text/csv

en: Snow and meteo data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: Snow profiles data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Daily data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Snow and meteo data from automatic sensors from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: GNSS derived SWE, LWC and HS from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-20

en: Daily data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Daily data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Manual profiles

en: Data of the traditional manual profiles for the locations Weissfluhjoch, Klosters and Küblis. For the location of Küblis there are no traditional manual profile data. We provided the data as both PDF and .CAAML format (See https://niviz.org/ or http://caaml.org/Schemas/V5.0/Profiles/SnowProfileIACS/CAAMLv5_SnowProfileIACS.pdf). Moreover, we added LWC and density profiles when available (all locations).

en: Daily observer data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: Snow and meteo data from automatic sensors for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Daily observer data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: GNSS derived data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Profile data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Webcam images

en: Webcam images showing some typical differences in the snow conditions at the four sites (Küblis, Klosters, Laret and Weissfluhjoch) for two time periods (14-18.3.2019 and 27.1-11.2.2020). Both time periods included a precipitation event with partial rain-on–snow occurring at the lower locations.

en: Daily data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: GNSS derived SWE, LWC and HS from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-20

en: GNSS derived SWE, HS, and LWC for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Snow profiles data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: Snow profiles data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: Daily observer data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: This database contains GNSS derived snow water equivalent (SWE), liquid water content (LWC), and snow height (HS) and reference data collected during the two winter 2018-2020 at 4 sites Weissfluhjoch (2540 m asl, 46°49’47’’ N, 9°48’34’’E), Laret (1515 m asl, . 46°50’2’’N, 9°52’17’’E), Klosters (1200 m asl, 46°51’49’’N, 9°53’17’’E), and Küblis (815 m asl, 46°54’48’’N, 9°46’54’’E).

gnss

display_name: gnss

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

lwc

display_name: lwc

snow

display_name: snow

envidat

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

en: Snow water equivalent measurements with low-cost GNSS receivers along a steep elevation gradient in the East-ern Swiss Alps


maintainer: James W. Kirchner

en: ecohydrology groundwater diurnal-cycle evapotranspiration diel-cycle sap-flow snowmelt streamflow

en: MODIS NDSI script

media_type: text/plain

en: Google Earth Engine script for computing MODIS normalized difference snow index (NDSI) values and averaging them over subcatchment areas.

format: TXT

mimetype: text/plain

en: Subcatchment polygons

en: Subcatchment polygons for use in the Google Earth Engine scripts.

en: Metadata

media_type: application/pdf

en: Column descriptions for both data files, and map coordinates for all measurement locations.

format: PDF

mimetype: application/pdf

en: MODIS EVI2 script

en: Google Earth Engine script for computing MODIS two-band enhanced vegetation index (EVI2) values and averaging them over subcatchments.

en: Daily time series

en: Daily hydrometeorological and ecohydrological time series

en: 30-minute time series

en: 30-minute hydrometeorological and ecohydrological time series.

en:
Hydrometerological and ecohydrological time series from Sagehen Creek and Independence Creek, Sierra Nevada, USA, illustrating hydrological responses to daily cycles in snowmelt and evapotranspiration forcing.

Data include 30-minute time series of

- weather variables,

- sap flow fluxes,

- groundwater levels (in two riparian transects of shallow groundwater wells),

- and stream stages (at 12 sites spanning a 500-meter elevation gradient),

and daily time series of

- temperature, precipitation, and snow water equivalent at three nearby snow telemetry stations

- diel cycle index values for groundwater levels and stream stages,

- and MODIS normalized difference snow index (NDSI) and enhanced vegetation index (EVI2) values averaged over selected subcatchments.

Google Earth Engine scripts for extracting the MODIS data are also provided.

diel-cycle

display_name: diel-cycle

diurnal-cycle

display_name: diurnal-cycle

ecohydrology

display_name: ecohydrology

evapotranspiration

display_name: evapotranspiration

groundwater

display_name: groundwater

sap-flow

display_name: sap-flow

snowmelt

display_name: snowmelt

streamflow

display_name: streamflow

educ

en: Education, culture and sport

en: EnviDat: the Environmental Data Portal

en: Daily cycles in solar flux, snowmelt, transpiration, groundwater, and streamflow at Sagehen and Independence Creeks, Sierra Nevada, USA


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

en: Data Compilation

en: Compressed TXT files

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

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

boundary-layer-winds

display_name: boundary-layer-winds

saltation

display_name: saltation

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

vertical-wind-motion

display_name: vertical-wind-motion

envidat

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

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


maintainer: Leo Gallus Bont

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

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

open-source

display_name: open-source

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: colonisation habitat-heterogeneity forest-management sloss saproxylic-beetles conservation biodiversity habitat-availability dead-wood

en: Community matrix (saproxylic beetles)

en: Abundances of saproxylic beetle species for each branch bundle

format: XLS

en: Community matrix (all beetles)

en: Abundances of all beetle species for each branch bundle

en: Variable description

en: Detailed description of the forest and environmental variables

en: Forest and environmental variables

en: Data on the branch bundle, forest and environmental variables

en:
The data was generated during a landscape experiment performed on 69 plots in Sihlwald forest between 2016 and 2019. Branch bundles of different sizes consisting of beech branches were exposed in the forest for one year to be colonized by saproxylic beetles and later reared for one year in emergence traps. All beetles emerging from the branches were collected. Overall 244 branch bundles are included and we found 66 beetles species (23511 individuals) of which 43 were classified as saproxylic (20873 individuals).
 Species data (2 tables)
Two community matrices (including abundance): one for saproxylic beetles and one for all beetles. Beetles were classfied as saproxylic following an extended list of the list reported in Schmidl & Bussler (2004).
 Model data (1 table)
*Response variables*
Species richness and abundance of (saproxylic) beetles.
*Branch bundles*
Branch bundles consisted of 1, 3, 6 or 12 branches and each bundle size was installed at each of the 69 plots. The bundles consisted of standardized freshly cut beech branches (Fagus sylvatica) with a length of 80 cm and a diameter between 3 and 6 cm. Total surface and volume of each bundle is reported.
*Tree on which the bundle was installed*
Information on the tree to which the bundles were attached (tree species, dbh, distance and azimut from the plot center).
*Temperature and light availability*
Temperature (plot level) and light availability (bundle level) were calculated.
*Deadwood availability in the landscape*
Based on a map of lying dead wood, dead wood amount and isolation were calculated for concentric circles with a radius ranging from 20 to 200 m (in 10 m steps) around each branch bundle.
 Variable descriptions (1 table)

biodiversity

display_name: biodiversity

colonisation

display_name: colonisation

conservation

display_name: conservation

dead-wood

display_name: dead-wood

forest-management

display_name: forest-management

habitat-availability

display_name: habitat-availability

habitat-heterogeneity

display_name: habitat-heterogeneity

saproxylic-beetles

display_name: saproxylic-beetles

sloss

display_name: sloss

en: Beetle communities reared from beech branches and associated forest and environmental variables


en: swe snow-depth remote-sensing snow uas

en: .tfw file

en: coordinates for the .tif raster

en: HS map Brämabül, 14. April 2015

media_type: image/tiff

en:
10 cm resolution
15 cm accuracy

format: TIFF

mimetype: image/tiff

en:
This snow depth map was generated 14 January 2015, close to peak of winter accumulation, applying Unmanned Aerial System digital surface models with a spatial resolution of 10 cm. The covered area is 285'000 m2 at the top of Brämabüel, 2490 m a.s.l. covering all expositions. Coordinate system: CH1903LV03.

A detailed description is given here:

Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075-1088, 10.5194/tc-10-1075-2016, 2016.

Abstract:
Detailed information on the spatial and temporal distribution, and variability of snow depth (HS) is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Nowadays, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network is not able to capture the large spatial variability of snow depth in alpine terrain.
Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, such data acquisition is costly, if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand, is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UAS), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Such systems have the advantage that they are comparatively cost-effective and can be applied very flexibly to cover also otherwise inaccessible terrain. In this study we map snow depth at two different locations: a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and b) an exposed location (2500 m a.s.l.) on a peak in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) better than 0.07 to 0.15 m on meadows and rocks and a RMSE better than 0.30 m on sections covered by bushes or tall grass. This new measurement technology opens the door for efficient, flexible, repeatable and cost effective snow depth monitoring for various applications, investigating the worlds cryosphere.

remote-sensing

display_name: remote-sensing

snow

display_name: snow

snow-depth

display_name: snow-depth

swe

display_name: swe

uas

display_name: uas

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: UAS based snow depth maps Brämabüel, Davos, CH


en: COST European Snow Booklet (ESB)

en: Please find here the web version of the COST European Snow Booklet (ESB).

en: List of authors and list of the editorial board of the European Snow Booklet

en:
Here you can find the list of all lead authors of the different chapters of the European Snow Booklet (ESB).
In addition a list of the editorial board that reviewed the ESB is given.

en: COST European Snow Booklet (ESB) - DORA Link

media_type: text/html

en: DORA Link of the COST European Snow Booklet (ESB).

en: European Snow Booklet public metadata

en:
The core of the European Snow Booklet (ESB), the country reports of 38 European countries, are based on information and metadata on snow measurements collected through a comprehensive survey, the ESB Questionnaire, between August 2017 and March 2018. The station metadata (for example location, elevation, measurement start date) from each country was provided by one or several institutions responsible for snow observations. By answering the questionnaire the contacts agreed that the information and metadata provided could be presented in the ESB. For cases where institutions indicated that information on station locations could be made publicly available, the metadata for the variables snow depth (HS), depth of snowfall (HN) and water equivalent of the snow cover (SWE), is additionally provided here for download (METADATA.xlsx).
Please note that not all institutions gave permission to publish their station metadata. This metadata has to be requested from the non-personal institution contacts provided in the METADATA.xlsx file. In some cases, however, no institutional contact is available and thus the contact of the country representative who filled in the questionnaire is used.
For current, updated station metadata we refer to the (non-personal) institutional contacts provided in METADATA.xlsx and/or the institution webpages. Note, however, that we cannot guarantee for completeness of the dataset for all countries because operational networks are prone to changes.

en:
The European Snow Booklet (ESB) is a book of reference for snow measurements that has been produced through collaboration with many European snow practitioners and snow scientists in the framework of the European Cooperation in Science and Technology (COST) Action ES1404 “A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction (HarmoSnow)”. The ESB provides a unique collection of information about operational snow observations in the European countries and the methods used to perform basic measurements of snow on the ground: snow depth (HS), depth of snowfall (HN), water equivalent of the snow cover (SWE) and presence of snow on the ground (PSG). Information and station metadata (for example location, elevation) for these basic snow variables were collected through a comprehensive survey, the ESB questionnaire between August 2017 and March 2018. Numerous institutions of 38 European countries provided detailed information describing the status of the operational snow observations and the methods used at the time of the survey. Based on the information provided, a country report was written for each European country. Similarities and differences among the countries, that is, the choice of snow variables to be measured, the measurement principles applied, the number of stations, or the spatial and elevational station distribution are pointed out. Thus the collection of country reports demonstrates the relevance of snow measurements for each country. Thus, the intention of the ESB is to foster better knowledge transfer regarding snow measurements between the snow science and operational communities and to improve the communication of information to the general public.

For detailed information on the European countries, we refer to the ESB, which can be downloaded here (envidat.ch). Please note that the ESB is not a living document and information and station metadata are from August 2017 till March 2018, except for Latvia (metadata updated in December 2018).

depth-of-snowfall

display_name: depth-of-snowfall

harmonisation-of-snow-measurements

display_name: harmonisation-of-snow-measurements

snow-measurement-methods

display_name: snow-measurement-methods

water-equivalent-of-the-snow-cover

display_name: water-equivalent-of-the-snow-cover

en: European Snow Booklet – an Inventory of Snow Measurements in Europe


data-interactive-avalanche-segmentation

maintainer: Elisabeth D. Hafner

title_for_slug: data-interactive-avalanche-segmentation

en: avalanche interactive deep-learning segmentation snow

en:
Images and corresponding avalanche annotations used for interactive avalanche segmentation:
SLF train, vali and test
WebNew
GroundPic
UserPic
UIBK dataset: List of images used
Pictures are from SLF (mostly from the Dischma Cams) if not otherwise indicated. If used, the data needs to be properly cited!

avalanche

display_name: avalanche

deep-learning

display_name: deep-learning

interactive

display_name: interactive

segmentation

display_name: segmentation

en: Data interactive avalanche segmentation


maintainer: Frank Techel

en: avalanche-statistics avalanche-fatalities avalanche-accident-statistics avalanche-accident long-term-trends

en: Data avalanche fatalities 1969/1970 - 2014/2015

en: The data comprises avalanche fatality data from the Alpine regions in the seven countries Austria, France, Germany, Italy, Liechtenstein, Slovenia, and Switzerland.

en:
During the last 45 years, about 100 people lost their lives in avalanches in the European Alps each year. Avalanche fatalities in settlements and on transportation corridors have considerably decreased since the 1970s. In contrast, the number of avalanche fatalities during recreational activities away from avalanche-secured terrain doubled between the 1960s and 1980s and has remained relatively stable since, despite a continuing strong increase in winter backcountry recreational activities.

Data complementing Figure 2 in:
_"Avalanche fatalities in the European Alps: long-term trends and statistics"_, by Techel, F., Jarry, F., Kronthaler, G., Mitterer, S., Nairz, P., Pavšek, M., Valt, M., and Darms, G.

Data description:
please refer to section 2 (Data and Methods) in the mentioned publication

avalanche-accident

display_name: avalanche-accident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

avalanche-statistics

display_name: avalanche-statistics

long-term-trends

display_name: long-term-trends

educ

en: Education, culture and sport

en: Avalanche fatalities in the European Alps (1969/1970 - 2014/2015)


en: cosmo-wrf wrf numerical-simulation grayzone complex-terrain

en:
This dataset contains simulation data for *"Influence of Air Flow Features on Alpine Wind Energy Potential" (Kristianti et al., 2024).*
•	The WRF_dia2702 and WRF_dia1103 folders contain the namelist.wps, namelist.input, and output files from the simulation in the Diablerets region on 27/02/2021 and 11/03/2021, respectively.
•	The WRF_luk2310 and WRF_luk0912 folders contain the namelist.wps, namelist.input, and output files from the simulation in the Lukmanier region on 23/10/2020 and 09/12/2020, respectively.
•	The postprocessing file contains Python codes used to create figures in Kristianti et al. (2024).
**Notes:**
•	Topography input is provided by Gerber et al. (2021).
•	Simulations are run using the COSMO-WRF model developed by Gerber et al. (2018).
•	Visualization by Python code uses wrf-python provided by Ladwig et al. (2017).
*This dataset was produced by the EDGE consortium sponsored by the Swiss Federal Office of Energy's SWEET programme, Swiss National Science Foundation (SNSF): Grant 179130, and the Swiss National Supercomputing Centre (CSCS) projects s938, s1115 and s1242.*

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

grayzone

display_name: grayzone

numerical-simulation

display_name: numerical-simulation

wrf

display_name: wrf

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: COSMO-WRF Dataset for Swiss Alps Simulations in Gray-Zone Resolution


maintainer: Milojevic

en: extreme-values low-flow reservoir-inflow return-periods alpine-precipitation

en: R codes for Extreme Values Analysis

en: Zip file containing R codes for running extreme value analyses for high precipitation and inflow events as well as code for determining return levels of low inflow and low precipitation events

en: Daily Luzzone Reservoir Inflow 01-01-2000 to 31-12-2019

en: Daily total water inflow to Luzzone reservoir. Natural inflow (LUZ_inflow_raw) is back-calculated based on daily water level in reservoir (removing hydropower inputs and spills). Linear interpolation between daily values is used to bring all inflow values into positive space (LUZ_inflow_intrp).

en:
 Summary

* Dataset of daily inflow to Luzzone reservoir in Ticino, Switzerland

* R scripts used to generate return levels for low reservoir inflow, low precipitation, high inflow, and extreme high precipitation based on various methods from extreme value analysis

 Data
The dataset included here is the "natural" reservoir inflow for the Luzzone reservoir.
Additional analyses were conducted on daily total precipitation of 6 meteorological stations (abbreviations: TIOLI, TIOLV, COM, VRN, VLS, ZEV). These precipitation data are freely available for teaching and research from the MeteoSwiss IDAweb portal (https://www.meteoswiss.admin.ch/services-and-publications/service/weather-and-climate-products/data-portal-for-teaching-and-research.html).

 Codes
R scripts used to determine return levels of the data set are included for both extreme high events and low events. The scripts include the following methods for calculating return levels:

* GEV (Generalized Extreme Value)

* GPD and GPDd (Generalized Pareto Distribution including declustered version)

* eGPD (extended Generalized Pareto Distribution)

* MEV (Metastatistical Extreme Value)

alpine-precipitation

display_name: alpine-precipitation

extreme-values

display_name: extreme-values

low-flow

display_name: low-flow

reservoir-inflow

display_name: reservoir-inflow

return-periods

display_name: return-periods

en: Data and Code on Extreme Inflow and Lowflow Analysis for Alpine Reservoirs


en: avalanche-release-probability forecast-models machine-learning avalanche-forecast spatial-modelling

en: Avalanche forecast

en: Data contains forecasts relating to dry-snow avalanche conditions only. Forecast issued at 17.00 local time. Contains variables for the warning region (sector_id), publication date (date), danger level - sub-level combination expressed using numeric values (integer value of danger level -0.33 for sub-level minus, -0 for sub-level neutral, +0.33 for sub-level plus, altitude as indicated in the bulletin, and whether aspect (North = 0, Northeast = 45, ...) was indicated in the bulletin (no: 0, yes: 1).

en: Snowline estimates 2022/2023

en: Daily snowline estimates provided by observers for North (aspect = 0) and South (aspect = 180) slopes for the 2022/2023 season. For aspects in between North and South, values are interpolated. Contains observation date (date), coordinates (Swiss coordinates x, y), snowline elevation (snowline), and aspect.

en: Model predictions (raw data)

en: Model predictions (raw data) for three models, in nowcast and forecast mode. Not all models are available for both seasons. - These data are the basis for the interpolated predictions, which can be found in the other zip-folder

en: GPS data and human-triggered avalanches

en: Contains (1) the subset of points extracted from GPS tracks recorded during backcountry touring and uploaded to the website skitourenguru.ch and (2) the corresponding subset of human-triggered avalanches. Data (1) was provided by Skitourenguru GmbH and data (2) was collected by SLF. - Variables contained are date, Swiss coordinates (x, y), aspect (N = 0, NE = 45, ...), elevation (ele), and event (event = 1, non-event = 0).

en: Randomly sampled subset of grid points from 1 km DEM

en: Contains the randomly sampled subset of grid points from 1 km DEM. Three variables: coordinates (x, y) and elevation (elev).

en: Human-triggered avalanches 2022/2023

en: The file contains the reported human-triggered avalanches. The variables are as follows: id, release date (date), name, Swiss coordinates (x,y), elevation (ele), remark, reported avalanche size expressed using avalanche activity index (sizeAAI), aspect, event type (type), event (yes = 1, no = 0)

en: Model predictions (interpolated)

en: The zip file contains csv-files the interpolated model predictions for three models, in forecast and nowcast-mode, for the three different data sets, as described in the publication.

en: Human-triggered avalanches 2023/2024

en: Natural avalanches 2023/2024

en: Natural avalanche observation (dry avalanches). 2023/2024 forecasting season.

en: Snowline estimates 2023/2024

en: Daily snowline estimates provided by observers for North (aspect = 0) and South (aspect = 180) slopes for the 2023/2024 season. For aspects in between North and South, values are interpolated. Contains observation date (date), coordinates (Swiss coordinates x, y), snowline elevation (snowline), and aspect.

en: Natural avalanches 2022/2023

en: Natural avalanche observation (dry avalanches). 2022-2023 forecasting season.

en:
This data set was used in the analysis by Techel et al. *Forecasting avalanche danger: human-made forecasts vs. fully automated model-driven predictions*, submitted to *Natural Hazards Earth System Sciences* on 20 Aug 2024.
The repository contains data from two avalanche forecasting seasons (2022/2023, 2023/2024) in Switzerland.
**Interpolated predictions**
- The .zip file contains the interpolated predictions for the three models in nowcast- and forecast- mode. This data is needed to reproduce the figures and tables in the submitted preprint.
The other data are the **raw data** underlying the interpolations:
- Avalanche forecast by WSL Institute for Snow and Avalanche Research SLF, published at 17.00 local time, valid for the following 24 hours and relating to dry snow avalanche conditions.
- Model predictions in *nowcast*- and *forecast*-mode for three models (*danger level*, *instability*, *natural avalanche*), valid for 12.00 local time
- Subset of points extracted from GPS tracks (courtesy of Skitourenguru GmbH)
- Avalanche observations - natural avalanches and human-triggered avalanches
- Estimates of the snowline
- Randomly chosen subset of grid points used for generating reference distributions
For details regarding the data sets refer to the publication.

avalanche-forecast

display_name: avalanche-forecast

avalanche-release-probability

display_name: avalanche-release-probability

forecast-models

display_name: forecast-models

machine-learning

display_name: machine-learning

spatial-modelling

display_name: spatial-modelling

en: Evaluating the predictive performance of human avalanche forecasts and model predictions in Switzerland


climarctic-seasons

maintainer: Aline Frossard

title_for_slug: climarctic-seasons

en: microbial-functions arctic microbial-biodiversity soil greenhouse-gases

en: Climarctic seasons dataset Envidat.xlsx

en:
Samples description
•	sample number: sample list number (S1 to S126)
•	season: season during which the samples were collected
•	location: one of the two location where the samples were collected in the vicinity of Ny Alesund on Svalbard
•	slope site: sites where the samples were collected along the toposequence (upslope = top of the slope, midslope = middle of the slope, downslope = bottom of the slope)
•	soil layer: depth layer where the sample were collected (biocrust = 0-2 cm and mineral soil = 5-10 cm)
•	replicate: replicated sampled (3 replicates per site)
Environmental variables
•	pH = pH value of the soil
•	sand = proportion of sand of the soil [%]
•	silt = proportion of silt of the soil [%]
•	clay = proportion of clay of the soil [%]
•	GWC = Gravimetric Water content in the soil [%]
•	OM = Organic Matter content in the soil [g]
•	N = Total Nitrogen content in soil [mg/g]
•	C = Total Carbon content in soil [mg/g]
•	C/N = ration of C content over N content [ratio]
•	NO3 = Nitrate content in soil [mg/kg]
•	NO2 = Nitrite content in soil [mg/kg]
•	NH4 = Ammonium content in soil [mg/kg]
•	Ptot = Total Phosphorus content in soil [mg/kg]
•	Pavail = Available Phosphorus content in soil [mg/kg]
•	PO4 = Phsphate content in soil [mg/kg]
•	CO2 = CO2 fluxes from soil [mmol CO2 m-2 d-1]
•	CH4 = CH4 fluxes from soil [umol CH4 m-2 d-1]
•	N2O = N2O fluxes from soil [umol CH4 m-2 d-1]
•	GPP = Gross Primary Production [mmol CO2 m-2 d-1]
•	ER = Ecosystem respiration [mmol CO2 m-2 d-1]
•	NEE = Net Ecosystem Exchange [mmol CO2 m-2 d-1]
•	glucoOM = glucosidase enzyme activity [mmol h-1 gOM-1]
•	23 xyloOM = xylosidase enzyme activity [mmol h-1 gOM-1]
•	chitOM = N-acetyl-glucosaminidase (chitinase) enzyme activity [mmol h-1 gOM-1]
•	phosOM = phosphatase enzyme activity [mmol h-1 gOM-1]
•	leuOM = leucine-aminopeptidase enzyme activity [mmol h-1 gOM-1]
•	PPOM = Polyphenol Peroxidase enzyme activity [mmol h-1 gOM-1]
•	POOM = Polyphenol Oxidase enzyme activity [mmol h-1 gOM-1]
•	30. Bac16SOM = Bacterial 16S gene abundance [copies gOM-1]
•	31. BacamoAOM = Bacterial amoA gene abundance [copies gOM-1]
•	32. ArchamoAOM = Archaeal 16S gene abundance [copies gOM-1]
•	33. nifHOM = nifH gene abundance [copies gOM-1]
•	34. nirSOM = nirS gene abundance [copies gOM-1]
•	35. nosZOM = nosZ gene abundance [copies gOM-1]
•	36. nxrBOM = nxrB gene abundance [copies gOM-1]
•	37. mcrAOM = mcrA gene abundance [copies gOM-1]
•	38. pmoAOM = pmoA gene abundance [copies gOM-1]

en: This dataset includes measurements of potential microbial functions (potential extracellular enzyme activities and microbial functional genes abundance) and soil physico-chemical properties (pH, nutrients, texture, etc) in biocrusts and underlying mineral soils in High-Arctic tundra near Ny-Ålesund (Svalbard) during each season along a toposequence.

arctic

display_name: arctic

greenhouse-gases

display_name: greenhouse-gases

microbial-biodiversity

display_name: microbial-biodiversity

microbial-functions

display_name: microbial-functions

soil

display_name: soil

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: Climarctic seasons


en: ecology wetlands environmental---history historical-carthography switzerland environmental--policy

en: Wetlands 1850 - 2010 (shapefiles)

en:
 History of wetlands - GIS-Layers
 Location of wetlands based on signatures in topographic maps
* Basis 1850: original measuring table sheets Dufour created between the years 1834 and 1863.
* Basis 1900/ Basis 1950: The Siegfried maps were updated and published at regular intervals between 1870 and 1949. This long period of time made it possible to reconstruct wetlands for two periods based on the Siegfried Maps: the first edition (hereinafter referred to as "1900") and the last edition ("1950").
* Basis 2010: Map sheets from the National Map from 2006 to 2011 were used for the most recent time period of the reconstruction.
 Location of wetlands due to reconstructions
The reconstruction **must not** be interpreted in the sense of a surface-accurate separation, but shows without claim to location accuracy the approximate extent of the areas that would have corresponded to the mapping criteria for wetlands used in today's topographic maps around 1850, 1900 and 1950. The basics can be found in Stuber & Bürgi 2019, chapter 5.4.

mimetype: application/zip

en:
Naturally, large parts of the Swiss Plateau are characterised by wetlands
and meandering rivers. That this is no longer the case today is the result
of centuries of efforts to obtain dry land. But how did this process take
place? What were the relevant actors and what were their motivations? And
what can be said about the ecological consequences of this development?

In a research project on the history of wetlands in Switzerland since 1700,
we conducted (a) a historical analysis of the development of land use in
wetlands and the actors involved, (b) a historical-cartographic
reconstruction of wetland extent since 1850 and (c) an evaluation of
ecological effects of changes in wetlands on various organisms groups.

The series of GIS layers on wetland history stem from the second part of
the project. The area reconstruction is based on digitized and homogenized
signatures from national map series, as they have been available since
about 1850. Details about the digitalization process and the homogenization
procedures applied ("Rekonstruktionen") are included in Stuber & Bürgi
2019.

Book Citation:
 > Stuber M, Bürgi M (2019) Vom «eroberten Land» zum Renaturierungsprojekt. Geschichte der Feuchtgebiete in der Schweiz seit 1700. "Bristol Schriftenreihe", Band 59. Haupt Verlag, Bern, Stuttgart, Wien. 262 Seiten.

ecology

display_name: ecology

environmental---history

display_name: environmental---history

environmental--policy

display_name: environmental--policy

historical-carthography

display_name: historical-carthography

switzerland

display_name: switzerland

wetlands

display_name: wetlands

en: History of wetlands in Switzerland since 1850


en: rutschblock-test extended-column-test norway avalanche-danger avalanche-observations switzerland

en: avalanche occurrence data (Norway, Sitzerland) - avalanche sizes per day and warning region

en: ECT data (Norway, Switzerland)

en: avalanche occurrence data (Norway, Sitzerland) - largest avalanche size per day and warning region

en: Rutschblock data (Switzerland)

en:
Observational data used to quantitatively describe the key elements describing avalanche danger: snowpack stability, the frequency distribution of snowpack stability, and avalanche size.
The data set consists of
- Rutschblock test results (Switzerland)
- Extended Column Test results (Switzerland, Norway)
- Avalanche occurrence data (Switzerland, Norway).
The data were extracted from the respective operational databases of the national avalanche warning services in Switzerland (WSL Institute for Snow and Avalanche Research SLF Davos, Switzerland) and Norway (The Norwegian Water Resources and Energy Directorate NVE).
For further information regarding the data, please refer to the publication or contact the author.

avalanche-danger

display_name: avalanche-danger

avalanche-observations

display_name: avalanche-observations

extended-column-test

display_name: extended-column-test

norway

display_name: norway

rutschblock-test

display_name: rutschblock-test

en: Stability tests, avalanche observations, Switzerland, Norway


root-traits

maintainer: Ivano Brunner

title_for_slug: root-traits

en: drought ingrowth-cores soil-coring belowground-biomass fine-root-traits

en: Root-traits

en:
Fine-root traits of Scots pine in response to enhanced soil water availability deriving from long-term irrigation in the Pfynwald

Data_Fig.1.xlsx
Fine-root biomass of the topsoil (0-10 cm) in the dry and irrigated treatment of the Scots pine forest of the years 2003 to 2016 recorded by soil coring

Data_Tab1+2_2005.xlsx
Fine-root traits from roots of ingrowth cores from 2005 after two years of growth in the dry and irrigated treatment of the Scots pine forest

Data_Tab1+2_2016.xlsx
Fine-root traits from roots of ingrowth cores from 2016 after two years of growth, and from roots of the soil-coring sampling from 2016 in the dry and irrigated treatment of the Scots pine forest

belowground-biomass

display_name: belowground-biomass

drought

display_name: drought

fine-root-traits

display_name: fine-root-traits

ingrowth-cores

display_name: ingrowth-cores

soil-coring

display_name: soil-coring


en: snow erosion mars model sediment-transport

en: Datasets of Figure 3a

en: Datasets of Figure 4a

en: Datasets of Figure 3b

en: Datasets of Figure 4b

en: Datasets of Figure 2

en:
The files contain the datasets used to produce Figures 2, 3, and 4 of the manuscript ([doi: 10.1002/2016GL071822](http://dx.doi.org/10.1002/2016GL071822)).

 Manuscript Abstract:
Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow

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: Energy- and momentum-conserving model of splash entrainment in sand and snow saltation


disdrometer-data-davos-wolfgang

title_for_slug: disdrometer-data-davos-wolfgang

en: precipitation raclets davos disdrometer fall-velocity

en: Disdrometer Data Davos Wolfgang

en:
The zip folder contains one netCDF file per day for Davos Wolfgang from February 8 to March 19 2019 with a temporal resolution of 30 seconds (time in UTC) and includes:

- characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...)
- precipitation rate
- radar reflectivity
- visibility range
- weather codes
- instrument performance

en: The dataset contains information on precipitation amount and type for Davos Wolfgang (LON: 9.853594, LAT: 46.835577) from February 8 to March 19 2019. It includes: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

davos

display_name: davos

disdrometer

display_name: disdrometer

fall-velocity

display_name: fall-velocity

precipitation

display_name: precipitation

raclets

display_name: raclets


maintainer: Yael Frischholz

en: alpine preferential-deposition snow-transport renewable-energy photovoltaic

en: Browse simulation files

en:
This file contains the snowBedFoam simulations carried out to produce the results presented in: _article not published yet_.
 Content
 1. /simulations
Groups all simulations folders organised by parameter (azimuth, groupsize, height, interspace) and by type of experiment (single_ref, group_ref).
 2. /simulations/[parameter]/
For each parameter multiple simulations were carried out. Each simulation folder follows the same naming systematic:
`helioplant_n#_h#_ARL#_BL#_az#_windDir#`
- n: number of Helioplant units
- h: height-above-surface
- sp: regular distance between the units
- ARL: additional refinement level
- BL: boundary layer first cell height
- windDir: wind direction
- stag: staggered arangement (suffix)
Here is an example of a folder content for a specific parameter
(simulations/azimuth/):
- `helioplant_n9_h07_sp10_ARL45_BL0015_az30_windDir5`: following the naming systematic this folder corresponds to a simulation with 9 aligned Helioplant units with 0.7m of height-above-surface, an inter-unit distance of 10m an azimuth of 30° and a wind direction of 5°.
 3. /simulations/[parameter]/[helioplant_n#_h#_ARL#_BL#_az#_windDir#]
Each simulation folder contains multiple sub-folders (0/, 100/, 300/, constant/ etc.) and files that define the experiment. For each simulation, the files used in the processing [scripts] are the following:
- 0/Cx: contains the x coordinates of sampling grid cells and of the Helioplants structures.
- 0/Cy: contains the y coordinates of sampling grid cells and of the Helioplants structures.
- 300/kinematicCloud-massCheckPatterns: contains the snow mass distribution values [kg/m2] for each grid cell.

[scripts]: https://github.com/frischwood/snowbed-helio.git

en:
This dataset groups numerical simulation outputs and validation measurement data produced in the context of the following [publication]: _not published yet_
The snow transport model [snowBedFoam] was used to analyse snow deposition around a specific type of Alpine PV structures named HELIOPLANT®.
The results of a sensitivity analysis of multiple key parameters that govern the spatial organisation of these structures are provided here. Measurements of snow distribution taken from the test-site of the [Gondosolar] project, are provided too.

To reproduce the results of the aforementioned publication, follow the instructions on this [repository].
[publication]: https://
[snowBedFoam]: https://www.doi.org/10.16904/envidat.223
[Gondosolar]: https://www.gondosolar.ch
[repository]: https://github.com/frischwood/snowbed-helio.git

alpine

display_name: alpine

photovoltaic

display_name: photovoltaic

preferential-deposition

display_name: preferential-deposition

renewable-energy

display_name: renewable-energy

snow-transport

display_name: snow-transport

en: Drifting and blowing snow distribution around structures for Alpine PV applications


maintainer: Kunfeng Gao

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

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

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


maintainer: Valentina Vitali

en: scots-pine tree-rings tree-ring-cellulose pfynwald isotopes dendrochronology pinus-sylvestris

en: Isotope measurements of tree-level tissues for the vegetative season 2019.

en: Read me file.docx

en:
Data from a 17-year-long irrigation experiment (Pfynwald, Switzerland) in a naturally dry forest dominated by 100-year-old pine trees (Pinus sylvestris). This dataset includes measure tree-ring width and tree-ring isotope chronologies (stable isotope ratios of non-exchangeable hydrogen δ2H, oxygen δ18O, and carbon δ13C), for the Pfynwald experiment, including control trees, irrigation and irrigation-stop treatments until the year 2019.

This dataset contains all data on which the following publication below is based.
Please cite this paper together with the citation for the datafile.

dendrochronology

display_name: dendrochronology

isotopes

display_name: isotopes

pfynwald

display_name: pfynwald

pinus-sylvestris

display_name: pinus-sylvestris

scots-pine

display_name: scots-pine

tree-ring-cellulose

display_name: tree-ring-cellulose

tree-rings

display_name: tree-rings

educ

en: Education, culture and sport

en: Pfynwald 2019 - Dendrochronological and tree-ring isotope dataset


maintainer: Ueli Reber

en: biodiversity switzerland policy-documents policy-analysis text-corpus environmental--policy bgb

en: Replication files

en:
 Introduction

The ZIP file contains all data and code to replicate the analyses reported in the following paper.

Reber, U., Fischer, M., Ingold, K., Kienast, F., Hersperger, A. M., Grütter, R., & Benz, R. (2022). Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics. *Policy Sciences*. [https://doi.org/10.1007/s11077-022-09456-4](https://doi.org/10.1007/s11077-022-09456-4)

If you use any of the material included in this repository, please refer to the paper. If you use (parts of) the text corpus, please also refer to the sources used for its compilation listed below. The content of the texts may not be changed.

 Data folder

The data folder contains the following files.

* _corpus.parquet_: Text corpus of Swiss policy documents
* _dict_de.csv_: Biodiversity dictionary (German)
* _dict_fr.csv_: Biodiversity dictionary (French)
* _dict_it.csv_: Biodiversity dictionary (Italian)
* _topic_labels.csv_: labels/codes for policy sectors
* _topics.csv_: labels/codes for policy sectors

The corpus and the dictionary were compiled by the authors specifically for this project. The labels/codes for policy sectors are based on the [coding scheme](http://ws-old.parlament.ch/affairs/topics) of the Swiss Parliament.

 Text corpus

The text corpus consists of 439,984 Swiss policy documents in German, French, and Italian from 1999 to 2018. The corpus was compiled from the following source between 2020-10-01 and 2021-01-31.

* Transcripts and parliamentary businesses (e.g. questions, motions, parliamentary initiatives) via the [Web Services (WS)](https://www.parlament.ch/de/%C3%BCber-das-parlament/fakten-und-zahlen/open-data-web-services) provided by the Swiss Parliament
* The official compilation of federal legislation ("Amtliche Sammlung", AS) via [opendata.swiss](https://opendata.swiss/de/dataset/official-compilation-of-federal-legislation-bs-as-1947-2018) provided by the Swiss Federal Archives (SFA)
* The federal gazette ("Bundesblatt") via [fedlex.admin.ch](https://www.fedlex.admin.ch/de/fga/index)
* Decisions of federal courts via [entscheidsuche.ch (ES)](https://entscheidsuche.ch/)

The corpus is stored in a single data frame to use with R saved as [PARQUET](https://parquet.apache.org/) file (corpus.parquet). The data frame has the following structure.

* _text_id_: Unique identifier for each text (source information as prefix, e.g. "t_")
* _doc_type_: Document type (see coding scheme below)
* _branch_: Government branche (1 legislative, 2 executive, 3 judicative)
* _stage_: Stage of policy process (1 drafting, 2 introduction, 3 interpretation)
* _year_: Year of publication
* _topic_: Policy sector (coding scheme in separate file in data folder)
* _lang_: Language (de, fr, it)
* _text_: Text

The following list contains the coding scheme for the doc_type variable.

* 101: Federal gazette // Draft for public consultation ("Vernehmlassungsverfahren")
* 102: Federal gazette // Explanation of draft for parliament ("Botschaft")
* 103: Federal gazette // Strategy, action plan
* 104: Federal gazette // Federal council decree ("Bundesratsbeschluss")
* 105: Federal gazette // (Simple) Federal decree ("(Einfacher) Bundesbeschluss")
* 106: Federal gazette // General decree ("Allgemeinverfügung")
* 107: Federal gazette // Treaty ("Übereinkommen")
* 108: Federal gazette // Treaty ("Abkommen")
* 109: Federal gazette // Draft for parliament ("Entwurf")
* 110: Federal gazette // Report ("Bericht")
* 111: Federal gazette // Report of parliamentary comission ("Bericht")
* 112: Federal gazette // Report of federal council ("Bericht")
* 201: Parl. businesses // Submitted text
* 202: Parl. businesses // Reason text
* 203: Parl. businesses // Federal council response
* 204: Parl. businesses // Initial situation
* 205: Parl. businesses // Proceedings
* 301: Parl. transcripts // Speech of MP
* 302: Parl. transcripts // Speech of federal council
* 401: Federal legislation // Legal text of the official compilation (law, ordinances, etc.)
* 501: Court decisions // Federal Supreme Court
* 502: Court decisions // Federal Criminal Court
* 503: Court decisions // Federal Administrative Court

 Code folder

The code folder contains all R code for the analyses. The files are numbered chronologically.

* _1_classifier_training.R_: Training of classifiers for classification of policy sectors
* _2_classifier_application.R_: Classification of documents in corpus
* _3_dictionary_application.R_: Biodiversity indexing of documents in corpus
* _4_stm_truncation.R_: Truncation of indexed documents to keep only relevant parts
* _5_stm_translation.R_: Translation of FR and IT documents to DE
* _6_stm_model.R_: Preprocesssing and structural topic model
* _7_plots.R_: Plots and numbers as included in the paper

The code/functions folder contains custom functions used in the scripts, e.g. to support topic model interpretation.

Package versions and setup details are noted in the code files.

 Contact

Please direct any questions to Ueli Reber (ueli.reber@eawag.ch).

bgb

display_name: bgb

biodiversity

display_name: biodiversity

environmental--policy

display_name: environmental--policy

policy-analysis

display_name: policy-analysis

policy-documents

display_name: policy-documents

switzerland

display_name: switzerland

text-corpus

display_name: text-corpus

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: Replication files for "Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics"