regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

author: Bundesamt für Umwelt / Abteilung Wasser

fr: Lien vers le portail

de: Link zum Fachportal

en: Link to portal

it: Link per il portale

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

it: geocat.ch link permanente

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

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

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

de: Vorschau map.geo.admin.ch

fr: Service WMTS-IFDG, couche , Layer "Ombre: Carte de distribution"

de: WMTS-BGDI Dienst, Layer "Äschen: Verbreitungsgebiet"

en: WMTS-FSDI service, layer "Grayling: distribution area"

it: Servizio WMTS-IFDG, strato "Temoli: aree di diffusione"

fr: Service WMS-IFDG, couche "Ombre: Carte de distribution"

de: WMS-BGDI Dienst, Layer "Äschen: Verbreitungsgebiet"

en: WMS-FSDI service, layer "Grayling: distribution area"

it: Servizio WMS-IFDG, strato "Temoli: aree di diffusione"

de: STAC Browser

fr: Serveur de téléchargement de geo.admin.ch

de: Download Server von geo.admin.ch

en: Download server from geo.admin.ch

it: Server di download di geo.admin.ch

fr: Les données sur les populations d’ombres d’importance nationale comprennent quatre sous-produits (distribution, zones principales, frayères, habitats larvaires). La couche « carte de distribution » con-tient les tronçons colonisés par 20 populations d’importance nationale. Les données de base sont tirées de l’Atlas de distribution des poissons et cyclostomes de Suisse (Pedroli et al. 1991) ou ont été fournies par les services de pêche cantonaux.

de: Der Datensatz zu den Äschenpopulationen von nationaler Bedeutung umfasst vier Teilprodukte (Verbreitungsgebiet, Kernzonen, Laichplätze, Larvenhabitate). Der Layer Verbreitungsgebiet enthält die Gewässerabschnitte 20 wichtiger Äschenpopulationen von nationaler Bedeutung. Die Grundlagendaten stammen aus dem Verbreitungsatlas der Fische und Rundmäuler der Schweiz (Pedroli et al. 1991), aus kantonalen Fangstatistiken sowie von Auskünften kantonaler Fischereiverwaltungen.

en: The data on grayling populations of national im-portance includes four subproducts; the distribution area layer includes the sections of watercourses with 20 major grayling populations of national importance. The core data come from the atlas of fish and cyclostome distribution in Switzerland (Pedroli et al. 1991), cantonal catch statistics and information from the cantonal management of fisheries.

it: I dati relativi alle popolazioni di temoli di importanza nazionale comprendono quattro prodotti parziali; l’ambito aree di diffusione contempla i tratti di corsi d’acqua in cui vivono 20 importanti popolazioni di temoli di importanza nazionale. I dati di base provengono dall’Atlante di diffusione dei pesci e dei ciclostomi della Svizzera (Pedroli et al. 1991), da statistiche cantonali delle catture e da informazioni fornite dai servizi cantonali della pesca.

fr: Office fédéral de l'environnement

de: Bundesamt für Umwelt / Abteilung Wasser

en: Federal Office for the Environment

it: Ufficio federale dell'ambiente

bundesamt-fur-umwelt-bafu

fr: Office fédéral de l'environnement OFEV

de: Bundesamt für Umwelt BAFU

en: Federal Office for the Environment FOEN

it: Ufficio federale dell'ambiente UFAM

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.

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.

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.

fr: Populations d’ombres d’importance nationale: carte de distribution

de: Äschenpopulationen von nationaler Bedeutung: Verbreitungsgebiet

en: Grayling population of national importance: distribution area

it: Popolazioni di temoli di importanza nazionale: aree di diffusione


state: active

type: dataset

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

fr: Aperçu map.geo.admin.ch

en: Preview map.geo.admin.ch

it: Previsione map.geo.admin.ch

format: SERVICE

fr: Service WMTS-IFDG, couche , Layer "Ombre: zones principales"

de: WMTS-BGDI Dienst, Layer "Äschen: Kernzonen"

en: WMTS-FSDI service, layer "Graylings: core areas"

it: Servizio WMTS-IFDG, strato "Temoli: zone centrali"

format: WMTS

fr: Service WMS-IFDG, couche "Ombre: zones principales"

de: WMS-BGDI Dienst, Layer "Äschen: Kernzonen"

en: WMS-FSDI service, layer "Graylings: core areas"

it: Servizio WMS-IFDG, strato "Temoli: zone centrali"

format: WMS

fr: Lien vers la distribution des données

de: Link zum Datenbezug

en: Link for download

it: Link per le fonti dei dati

format: HTML

fr: Les données sur les populations d’ombres d’importance nationale comprennent quatre sous-produits (distribution, zones principales, frayères, habitats larvaires). La couche « zones principales » contient les tronçons qui sont essentiels pour ces populations en raison de paramètres biolo-giques ou écomorphologiques. Les données de base sont tirées de l’Atlas de distribution des poissons et cyclostomes de Suisse (Pedroli et al. 1991) ou ont été fournies par les services de pêche cantonaux.

de: Der Datensatz zu den Äschenpopulationen von nationaler Bedeutung umfasst vier Teilprodukte (Verbreitungsgebiet, Kernzonen, Laichplätze, Larvenhabitate). Der Layer Kernzonen enthält die Strecken mit besonderer Bedeutung für Äschenpopulationen basierend auf fischereibiologischen und/oder ökomorphologischen Besonderheiten. Die Grundlagendaten stammen aus dem Verbreitungsatlas der Fische und Rundmäuler der Schweiz (Pedroli et al. 1991), aus kantonalen Fangstatistiken sowie von Auskünften kantonaler Fischereiverwaltungen.

en: The data on grayling populations of national importance includes three subproducts; the core zones layer includes the areas of particular importance for grayling populations, based on biological and/or ecomorphological characteristics at fisheries. The core data come from the atlas of fish and cyclostome distribution in Switzerland (Pedroli et al. 1991), cantonal catch statistics and information from the cantonal management of fisheries.

it: I dati relativi alle popolazioni di temoli di importanza nazionale comprendono quattro prodotti parziali; l’ambito zone centrali contempla i tratti particolarmente importanti per le popolazioni di temoli, sulla base di peculiarità legate alla biologia delle specie ittiche e/o ecomorfologiche. I dati di base provengono dall’Atlante di diffusione dei pesci e dei ciclostomi della Svizzera (Pedroli et al. 1991), da statistiche cantonali delle catture e da informazioni fornite dai servizi cantonali della pesca.

spatial: Schweiz

political_level: confederation

type: organization

approval_status: approved

value: BAFU - Geocat Harvester

fr: Populations d’ombres d’importance nationale: zones principales

de: Äschenpopulationen von nationaler Bedeutung: Kernzonen

en: Grayling population of national importance: core areas

it: Popolazioni di temoli di importanza nazionale: zone centrali


regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

fr: Lien vers le portail

de: Link zum Fachportal

en: Link to portal

it: Link per il portale

de: geocat.ch Permalink

fr: Service WMTS-IFDG, couche , Layer "Ombre: frayères"

de: WMTS-BGDI Dienst, Layer "Äschen: Laichplätze"

en: WMTS-FSDI service, layer "Graylings: spawning grounds"

it: Servizio WMTS-IFDG, strato "Temoli: siti di riproduzione"

fr: Service WMS-IFDG, couche "Ombre: frayères"

de: WMS-BGDI Dienst, Layer "Äschen: Laichplätze"

en: WMS-FSDI service, layer "Graylings: spawning grounds"

it: Servizio WMS-IFDG, strato "Temoli: siti di riproduzione"

de: Link für Datenbezug

fr: Les données sur les populations d’ombres d’importance nationale comprennent quatre sous-produits (distribution, zones principales, frayères, habitats larvaires). La couche « frayères » contient les tronçons où les ombres se reproduisent naturellement. Les données de base sont tirées de l’Atlas de distribution des poissons et cyclostomes de Suisse (Pedroli et al. 1991) ou ont été fournies par les services de pêche cantonaux.

de: Der Datensatz zu den Äschenpopulationen von nationaler Bedeutung umfasst vier Teilprodukte (Verbreitungsgebiete, Kernzonen, Laichplätze, Larvenhabitate). Der Layer Laichplätze enthält die Strecken in denen natürliche Reproduktion stattfindet. Die Grundlagendaten stammen aus dem Verbreitungsatlas der Fische und Rundmäuler der Schweiz (Pedroli et al. 1991), aus kantonalen Fangstatistiken sowie von Auskünften kantonaler Fischereiverwaltungen.

en: The data on grayling populations of national importance includes four sub-products; the spawning grounds layer includes the areas in which natural reproduction occurs. The core data come from the atlas of fish and cyclostome distribution in Switzerland (Pedroli et al. 1991), cantonal catch statistics and information from the cantonal management of fisheries.

it: I dati relativi alle popolazioni di temoli di importanza nazionale comprendono quattro prodotti parziali; l’ambito siti di riproduzione dei pesci comprende i tratti in cui avviene la riproduzione naturale. I dati di base provengono dall’Atlante di diffusione dei pesci e dei ciclostomi della Svizzera (Pedroli et al. 1991), da statistiche cantonali delle catture e da informazioni fornite dai servizi cantonali della pesca.

fr: Populations d’ombres d’importance nationale: frayères

de: Äschenpopulationen von nationaler Bedeutung: Laichplätze

en: Grayling population of national importance: spawning grounds

it: Popolazioni di temoli di importanza nazionale: siti di riproduzione dei pesci


fr: geocat.ch permalien

en: geocat.ch permalink

it: geocat.ch link permanente

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

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

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

de: Vorschau map.geo.admin.ch

fr: Service WMTS-IFDG, couche , Layer "Ombre: habitats larvaires"

de: WMTS-BGDI Dienst, Layer "Äschen: Larvenhabitate"

en: WMTS-FSDI service, layer "Graylings: larva habitats"

it: Servizio WMTS-IFDG, strato "Temoli: habitat delle larve"

fr: Service WMS-IFDG, couche "Ombre: habitats larvaires"

de: WMS-BGDI Dienst, Layer "Äschen: Larvenhabitate"

en: WMS-FSDI service, layer "Graylings: larva habitats"

it: Servizio WMS-IFDG, strato "Temoli: habitat delle larve"

de: STAC Browser

fr: Serveur de téléchargement de geo.admin.ch

de: Download Server von geo.admin.ch

en: Download server from geo.admin.ch

it: Server di download di geo.admin.ch

fr: Les données sur les populations d’ombres d’importance nationale sont formées de quatre sous-produits (distribution, zones principales, frayères, habitats larvaires). La couche « habitats larvaires » contient les tronçons où ont été observés des in-dividus au stade larvaire. Les données de base sont tirées de l’Atlas de distribution des poissons et cyclostomes de Suisse (Pedroli et al. 1991) ou ont été fournies par les services de pêche canto-naux.

de: Der Datensatz zu den Äschenpopulationen von nationaler Bedeutung umfasst vier Teilprodukte (Verbreitungsgebiet, Kernzonen, Laichplätze, Larvenhabitate). Der Layer Larvenhabitate enthält die Strecken, in denen Larven beobachtet wurden. die Grundlagendaten stammen aus dem Verbreitungsatlas der Fische und Rundmäuler der Schweiz (Pedroli et al. 1991), aus kantonalen Fangstatistiken sowie von Auskünften kantonaler Fischereiverwaltungen.

en: The data on grayling populations of national importance includes four subproducts; the larva habitats layer includes the areas in which larva were monitored. The core data come from the atlas of fish and cyclostome distribution in Switzerland (Pedroli et al. 1991), cantonal catch statistics and information from cantonal management of fisheries.

it: I dati relativi alle popolazioni di temoli di importanza nazionale comprendono quattro prodotti parziali; l’ambito habitat delle larve contempla i tratti in cui è stata osservata la presenza di larve. I dati di base provengono dall’Atlante di diffusione dei pesci e dei ciclostomi della Svizzera (Pedroli et al. 1991), da statistiche cantonali delle catture e da informazioni fornite dai servizi cantonali della pesca.

fr: Office fédéral de l'environnement

de: Bundesamt für Umwelt / Abteilung Wasser

en: Federal Office for the Environment

it: Ufficio federale dell'ambiente

bundesamt-fur-umwelt-bafu

fr: Office fédéral de l'environnement OFEV

de: Bundesamt für Umwelt BAFU

fr: Populations d’ombres d’importance nationale: habitats larvaires

de: Äschenpopulationen von nationaler Bedeutung: Larvenhabitate

en: Grayling population of national importance: larva habitats

it: Popolazioni di temoli di importanza nazionale: habitat delle larve


schneeschuhwandern

regi

de: Regionen und Städte

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: schneeschuhwandern

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

fr: Aperçu map.geo.admin.ch

en: Preview map.geo.admin.ch

it: Previsione map.geo.admin.ch

fr: Lien vers les données à télécharger

fr: -- nom technique de la couche --

fr: Service WMS-IFDG, couche "layername"

de: WMS-BGDI Dienst, Layer "ch.astra.schneeschuhwandern"

en: WMS-FSDI service, layer "layername"

it: Servizio WMS-IFDG, strato "layername"

fr: Le jeu de données « Randonnée à raquettes » comprend la sélection des meilleurs itinéraires de SuisseMobile (lignes épaisses) et les itinéraires balisés cantonaux. Cette sélection est coordonnée avec Suisse Rando, les cantons et la Principauté du Liechtenstein.

de: Der Datensatz «Schneeschuhwandern» umfasst die Best-of-Auswahl von SchweizMobil (dicken Linien) und die übrigen signalisierten Routen aus den Kantonen. Diese Auswahl wird mit Schweizer Wanderwege, den Kantonen und dem Fürstentum Liechtenstein koordiniert.

spatial: Schweiz (mit grenznahem Ausland)

fr: Suisse Rando - Hiver

de: Schweizer Wanderwege - Winter

it: Sentieri Svizzeri – hiverno

bundesamt-fur-strassen-astra

fr: Office fédéral des routes OFROU

de: Bundesamt für Strassen ASTRA

en: Federal Roads Office FEDRO

it: Ufficio federale delle strade USTRA

fr: L'Office fédéral des routes (OFROU) est l'autorité suisse compétente pour l'infrastructure routière et le trafic individuel. Chapeauté par le Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC), il oeuvre en faveur d'une mobilité routière durable et sûre. Son objectif principal est de garantir le bon fonctionnement du réseau des routes nationales et principales.

de: Das Bundesamt für Strassen (ASTRA) ist die Schweizer Fachbehörde für die Strasseninfrastruktur und den individuellen Strassenverkehr. Im Verantwortungsbereich des eidgenössischen Departements für Umwelt, Verkehr, Energie und Kommunikation (UVEK) wirkt es für eine nachhaltige und sichere Mobilität auf der Strasse. Im Mittelpunkt steht die Sicherstellung der Funktionsfähigkeit des Nationalstrassen und Hauptstrassennetzes.

en: The Federal Roads Office (FEDRO) is Switzerland's federal authority responsible for road infrastructure and private road transport. It belongs to the Federal Department of the Environment, Transport, Energy and Communications (DETEC), and focuses on securing sustainable and safe mobility on the country's roads. Its principal objective is to secure the functionality of Switzerland's motorway and main road networks.

it: L'Ufficio federale delle strade (USTRA) è l'autorità svizzera competente in materia di infrastruttura stradale e traffico stradale privato. Parte integrante del Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC), l'Ufficio è impegnato nella realizzazione di una mobilità sostenibile e sicura sulla strada. Il suo obiettivo principale è di garantire la funzionalità della rete delle strade nazionali e principali.

value: ASTRA - Geocat Harvester

fr: Randonnée à raquettes

de: Schneeschuhwandern


konzessionen-erdsonden

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

regi

fr: Régions et villes

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: konzessionen-erdsonden

fr: geocat.ch permalien

de: geocat.ch Permalink

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: Hier sind die vom Kanton Uri verliehenen Konzessionen zur Wärmenutzung mittels Erdsonden als Punkte aufgeschaltet. Die Wärme aus Erdsonden wird in den meisten Fällen zu Heizzwecken (mit Wärmepumpen) genutzt. Es gibt aber auch andere Anwendungen wie zum Beispiel zur Kühlung (Klimatisierung, Prozesskühlung). Ergänzende Informationen für die Wärmenutzung aus Boden und Untergrund liefert das Wärmenutzungskonzept Kanton Uri 2017 (auf www.ur.ch) sowie die folgenden Layer auf www.geo.ur.ch: Konzessionen Grundwasserwärmepumpen, Zulässigkeit Erdsonden, Zulässigkeit Grundwasserwärmepumpen, Grundwasserleiter und Isohypsen.

spatial: Canton of Uri (UR)

fr: Direktionssekretariat BD Kt. Uri

de: Direktionssekretariat BD Kt. Uri

en: Direktionssekretariat BD Kt. Uri

it: Direktionssekretariat BD 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.

political_level: canton

kanton-uri

capacity: public

value: Uri-Kt - Geocat Harvester

fr: Konzessionen Erdsonden

de: Konzessionen Erdsonden

en: Konzessionen Erdsonden

it: Konzessionen Erdsonden


konzessionen-grundwasserwarmepumpen

regi

de: Regionen und Städte

title_for_slug: konzessionen-grundwasserwarmepumpen

en: geocat.ch permalink

it: geocat.ch link permanente

fr: Hier sind die vom Kanton Uri verliehenen Konzessionen zur Wärmenutzung mittels Grundwasserwärmepumpen als Punkte aufgeschaltet. Die Wärme aus Grundwasserwärmepumpen wird in den meisten Fällen zu Heizzwecken (mit Wärmepumpen) genutzt. Es gibt aber auch andere Anwendungen wie zum Beispiel zur Kühlung (Klimatisierung, Prozesskühlung). Ergänzende Informationen für die Wärmenutzung aus Boden und Untergrund liefert das Wärmenutzungskonzept Kanton Uri 2017 (auf www.ur.ch) sowie die folgenden Layer auf www.geo.ur.ch: Konzessionen Erdsonden, Zulässigkeit Grundwasserwärmepumpen, Zulässigkeit Erdsonden, Grundwasserleiter und Isohypsen.

fr: Amt für Energie Kt. Uri

de: Amt für Energie Kt. Uri

en: Amt für Energie Kt. Uri

it: Amt für Energie Kt. Uri

fr: Konzessionen Grundwasserwärmepumpen

de: Konzessionen Grundwasserwärmepumpen

en: Konzessionen Grundwasserwärmepumpen

it: Konzessionen Grundwasserwärmepumpen


swisscom-leitungen

title_for_slug: swisscom-leitungen

author: Swisscom

fr: Swisscom Leitungen, Bauwerke und Schächte

fr: Swisscom

de: Swisscom

en: Swisscom

it: Swisscom

fr: Swisscom Leitungen

de: Swisscom Leitungen

en: Swisscom Leitungen

it: Swisscom Leitungen


de: naturgefahr naturrisiko naturrisikoanalyse gebiete-mit-naturbedingten-risiken bgdi-bundesgeodaten-infrastruktur

fr: Lien vers le portail

de: Link zum Fachportal

en: Link to portal

it: Link per il portale

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

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

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

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

fr: Aperçu map.geo.admin.ch

de: Vorschau map.geo.admin.ch

en: Preview map.geo.admin.ch

it: Previsione map.geo.admin.ch

fr: Service WMS-IFDG, couche "Inondation Aquaprotect 100"

de: WMS-BGDI Dienst, Layer "Überschwemmung Aquaprotect 100"

en: WMS-FSDI service, layer "Areas of flooding Aquaprotect 100"

it: Servizio WMS-IFDG, strato "Aree inondabili Aquaprotect 100"

fr: Service WMTS-IFDG, couche , Layer "Inondation Aquaprotect 100"

de: WMTS-BGDI Dienst, Layer "Überschwemmung Aquaprotect 100"

en: WMTS-FSDI service, layer "Areas of flooding Aquaprotect 100"

it: Servizio WMTS-IFDG, strato "Aree inondabili Aquaprotect 100"

fr: Lien vers la distribution des données

de: Link zum Datenbezug

en: Link for download

it: Link per le fonti dei dati

fr: Les zones inondables Aquaprotect représentent une vue d’ensemble sommaire, à échelle nationale, des zones potentiellement inondables lors de rares voire de très rares débits de crue. Cette vue d’ensemble est réalisée à partir de méthodes simples. Elle donne une vision globale des dangers et risques. À cause de cela elle ne remplace pas les cartes des dangers (http://www.bafu.admin.ch/cartes-dangers). Elle ne prend pas en compte les mesures de protection existantes contre les crues, elle permet seulement une estimation grossière d’un risque éventuel de crue lors de l'absence de cartes des dangers. Les zones inondables mises en évidence dans Aquaprotect existent pour les débits de crue avec des périodes de retour de 50, 100, 250 et 500 ans. Le débit de crue avec une période de retour de 100 ans, considéré comme une longue période, peut se produire en moyenne une fois tous les 100 ans. Même si une zone définie n’est pas signalée comme inondable par les cartes Aquaprotect, le risque de crue ne peut pas être tenu pour inexistant. Du fait de leur représentation simplifiée, les surfaces indiquées donnent un aperçu approximatif. Si l'échelle choisie est inférieure à 1:50 000, alors les zones inondables sont représentées par des hachures. En effet, des représentations trop précises conduiraient à des déductions erronées.

de: Die Überschwemmungsgebiete in Aquaprotect sind eine mit einfachen Methoden erarbeitete grobe gesamtschweizerische Übersicht der potenziell überschwemmten Gebiete bei seltenen und sehr seltenen Hochwasserabflüssen. Sie liefern eine grobe Übersicht der Gefahren und Risiken und ersetzen deshalb nicht die detaillierten Gefahrenkarten (http://www.bafu.admin.ch/gefahrenkarten). Sie berücksichtigen beispielsweise vorhandene Hochwasserschutzmassnahmen nicht und erlauben deshalb bei noch fehlenden Gefahrenkarten lediglich eine grobe Einschätzung einer möglichen Hochwassergefährdung. Die Überschwemmungsgebiete in Aquaprotect liegen für Hochwasserabflüsse mit den Wiederkehrperioden von 50, 100, 250 und 500 Jahren vor. Der Hochwasserabfluss mit beispielsweise einer Wiederkehrperiode von 100 Jahren ist jene Abflussmenge, die - über einen sehr langen Zeitraum betrachtet - im Durchschnitt ein Mal innerhalb von 100 Jahren erreicht wird. Aus der Tatsache, dass ein bestimmtes Gebiet in den Überschwemmungsgebieten von Aquaprotect nicht enthalten ist, kann nicht geschlossen werden, dass hier keine Hochwassergefahr besteht. Aufgrund der vereinfachten Betrachtung geben die ausgewiesenen Flächen eine grobe Übersicht. Bei detaillierteren Massstäben als 1:50'000 sind die Überschwemmungsgebiete nur noch mittels Schraffuren dargestellt. Dadurch soll vermieden werden, dass aus ungeeignet genauer Darstellung Fehlinterpretationen für betroffene bzw. nicht betroffene Gebiete erfolgen.

en: The areas of flooding included in “Aquaprotect” take the form of a rough overview (prepared with the aid of basic methods) of areas of Switzerland that are susceptible to damage caused by occasional and very infrequent flooding. This is intended as a rough overview of the risks and hazards, and therefore does not replace the detailed risk maps (<http://www.bafu.admin.ch/gefahrenkarten>). For example, it does not take existing flood protection measures into account, and in the event of not yet available risk maps it merely permits an approximate assessment of potential flood damage.The areas of flooding included in “Aquaprotect” concern floods in recurrence periods of 50, 100, 250 and 500 years. For example, a flood with a recurrence period of 100 years refers to a level of flooding which, viewed over a very lengthy timeframe, is reached on average once every 100 years. The fact that a given area is not included in “Aquaprotect” does not mean that there is no risk of flooding in that area. Due to the simplified method that is applied, only a rough overview is provided. At more detailed scales than 1:50,000, areas susceptible to flooding are only depicted with the aid of shading. The aim here is to avoid misinterpretation due to insufficiently accurate depiction.

it: Le aree inondabili in Aquaprotect sono una pano-ramica sommaria elaborata con strumenti semplici delle aree potenzialmente inondate in Svizzera in caso di portate di piena rare o molto rare. Forniscono una panoramica sommaria sui pericoli e sui rischi e non sostituiscono quindi le carte dei pericoli dettagliate. Questi dati non tengono ad esempio conto delle misure di protezione contro le piene e laddove mancano le carte dei pericoli consentono quindi solo una valutazione sommaria di una possibile minaccia contro le piene.Le aree inondabili in Aquaprotect sono disponibili per portate di piena con frequenze di 50, 100, 250 e 500 anni. La portata di piena con, ad esempio, una frequenza di 100 anni è un volume di portata che, considerato su un lasso di tempo molto lungo, viene raggiunto in media una volta ogni cento anni. Il fatto che una determinata area non è inclusa nelle aree inondabili di Aquaprotect non consente di escludere che in tale area non sussista un pericolo di piena. In base alla visualizzazione semplificata, le superfici considerate forniscono solo una panoramica sommaria. Con scale più dettagliate di 1:50 000, le aree inondabili sono rappresentate solo con tratteggi. In tal modo si vogliono evitare interpretazioni errate per le aree interessate o non interessate.

fr: Division Prévention des dangers, Office fédéral de l'environnement

de: Bundesamt für Umwelt / Abteilung Gefahrenprävention

en: Hazard Prevention Division, Federal Office for the Environment

it: Divisione Prevenzione dei pericoli, Ufficio federale dell'ambiente

bundesamt-fur-umwelt-bafu

fr: Office fédéral de l'environnement OFEV

de: Bundesamt für Umwelt BAFU

en: Federal Office for the Environment FOEN

it: Ufficio federale dell'ambiente UFAM

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.

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.

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.

fr: Zones inondables Aquaprotect: période de retour de 100 ans

de: Überschwemmungsgebiete Aquaprotect: Wiederkehrperiode 100 Jahre

en: Aquaprotect” areas of flooding: 100-year recurrence period

it: Aree inondabili in Aquaprotect: Frequenza 100 anni


verfahren-solaranlagen

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: verfahren-solaranlagen

author: Abteilung Energie

fr: geocat.ch permalien

de: geocat.ch Permalink

de: AGIS Direktdownload

de: Der Datensatz zeigt Perimeter für unterschiedliches Verfahren für den Bau von Solaranlagen im Solarkataster auf. Gebäude, die sich im Schutzperimeter aufhalten, sind bewilligungspflichtig und bestehen aus denkmalgeschützten Gebäuden, Altstadt-, Dorf- und Kernzone, ISOS mit Ziel A, Ortsbildschutz sowie Gebäude mit Substanz- und Volumenschutz. Der Prüfperimeter enthält alle Gebäude, die möglicherweise bewilligungspflichtig sind. Dieser besteht aus den Gebieten Wohnzone mit Vorschriften, angrenzende Parzellen an ein denkmalgeschütztes Gebäude sowie einen Radius von 50m um ein denkmalgeschütztes Gebäude. Im Meldeperimeter sind Gebäude enthalten, die nur einer Meldepflicht unterliegen. Wichtig: Alle 3 Perimeter beziehen sich nur auf die Bauzone und keine Gebiete ausserhalb.

de: Abteilung Energie

de: AGIS Service Center Kanton Aargau

de: Das AGIS Service Center unterstützt als kantonale Koordinationsstelle die Bereitstellung von Geoinformationen und Metadaten der kantonalen Verwaltung. Die zuständigen kantonalen Fachstellen stellen die öffentlichen Geodaten des Kantons Aargau mittels der Infrastruktur des AGIS Service Center in der Informatik Aargau als Webservices und zum Download bereit.

value: Aargau-Kt - Geocat Harvester

de: Verfahren Solaranlagen


akustische-ubergangssignale

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

title_for_slug: akustische-ubergangssignale

author: Tiefbauamt Stadt Bern

en: geocat.ch permalink

it: geocat.ch link permanente

fr: Map (Preview)

de: Map (Preview) Stadtplan

en: Map (Preview)

it: Map (Preview)

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

de: Web Map Services WMS

de: WFS Akustische_Uebergangssignale

de: Web Feature Services WFS

de: Akustische Signale für Menschen mit Sehbehinderungen bei Zebrastreifen.

spatial: Stadt Bern

de: Tiefbau Stadt Bern

geoinformation-der-stadt-bern

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

de: Geoinformation Stadt Bern

en: The Land Surveying Office of the City of Bern

it: L'ufficio del catasto nella Città di Berna

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

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

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

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

political_level: commune

value: Geoinformation Stadt Bern - Geocat Harvester

de: Akustische Übergangssignale


airflow

ener

de: Energie

regi

de: Regionen und Städte

envi

de: Umwelt

title_for_slug: airflow

de: geocat.ch Permalink

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: test airflow

de: test airflow

en: test airflow

it: test airflow

fr: Lisag AG

de: Lisag AG

en: Lisag AG

it: Lisag AG

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

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

fr: airflow

de: airflow

en: airflow

it: airflow


de: fliessgewasser gewasserschutz landwirtschaft landwirtschaftliche-nutzung nutzungsplanung raumplanung zonenplan

author: Kanton Luzern, Abteilung Geoinformation

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: Der Gewässerraum ist extensiv zu gestalten und zu bewirtschaften (GSchG, Art. 36a Abs. 3). In der Landwirtschaft sind folgende Gewässerraumflächen von den Bewirtschaftungseinschränkungen ausgenommen: Flächen über eingedolten Gewässerabschnitten, Randstreifen entlang Verkehrsachen und äussere Korridore bei Gewässeräumen von grossen Fliessgewässern. Der Datensatz umfasst diese Festlegungen.

spatial: Kanton Luzern

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


technische-gefahren-storfallverordnung

regi

de: Regionen und Städte

title_for_slug: technische-gefahren-storfallverordnung

de: emission gebaude-und-anlagen risiken schadenereignis strasse strassenverkehr umweltschutz verkehr

de: Zeigt Lage der Störfallbetriebe und Konsultationsbereiche, in denen raumplanerische Vorhaben koordiniert werden müssen.


maintainer: Felix Kienast

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

media_type: application/zip

en:
This is the compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.
Column description:
X01 = Planning_units (PUs)
X02 = incl.OS. number of times pu was selected in MARXAN when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)
geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).

format: ZIP

en:
This study examines the siting scenarios for renewable energy infrastructure (REI) in Switzerland, incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed.
MARXAN was run for 2 versions: a) without ground-mounted open space PV infrastructure (excl. OS) and b) with ground-mounted open space PV infrastructure (incl. OS). In each version optimization was done using ecological costs (ECUess) or social costs (ECUsoc) in a regular grid of 4x4km (planning unit).

File:
PU_data.shp: compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.

Headers are described below:
X01 = Planning_units (PUs)

X02 = incl.OS. number of times pu was selected in MARXAN when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)

geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).

For MARXAN optimizations (for meaning of standard files in MARXAN see https://scholar.google.ch/scholar_url?url=https://courses.washington.edu/cfr590/software/Marxan1810/marxan_manual_1_8_2.pdf&hl=de&sa=X&ei=NAWHZI6JJ8PFmAGMo47oDQ&scisig=AGlGAw-DBrsV4kUzkR6GkN1jtG66&oi=scholarr), pu_data.shp was used to generate MARXAN files input.dat, pu.dat, puvfeat.dat, spec.dat.
Coordinate Reference System: CH1903 / LV03. EPSG: 21781.

ecosystem-services

display_name: ecosystem-services

energy

display_name: energy

landscape

display_name: landscape

marxan

display_name: marxan

optimization

display_name: optimization

photovoltaic

display_name: photovoltaic

social-acceptance

display_name: social-acceptance

spatial-planning

display_name: spatial-planning

wind-power

display_name: wind-power

educ

de: Bildung, Kultur und Sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

key: guid

key: uri

value: Envidat Harvester

en: Optimizing renewable energy siting in the Swiss landscape


data-set-on-snow-instability

maintainer: EnviDat Support

title_for_slug: data-set-on-snow-instability

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

en: Read-me file on snow instability data

media_type: application/pdf

format: PDF

mimetype: application/pdf

en: data set on snow instability

media_type: text/csv

format: CSV

mimetype: text/csv

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

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

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

avalanche-forcasting

display_name: avalanche-forcasting

crack-propagation

display_name: crack-propagation

failure-initiation

display_name: failure-initiation

propgatoin-saw-test

display_name: propgatoin-saw-test

rutschblock

display_name: rutschblock

slab

display_name: slab

slab-tensile-support

display_name: slab-tensile-support

snow-avalanche

display_name: snow-avalanche

snow-stability-evaluation

display_name: snow-stability-evaluation

weak-layer

display_name: weak-layer

educ

en: Education, culture and sport

en: Data set on snow instability


dataset-on-new-snow-water-equivalent

title_for_slug: dataset-on-new-snow-water-equivalent

en: new-snow snowfall snow-modelling precipitation data-assimilation

en: The .zip file contains all data as described in this repository and associated publication. The .zip file contains a readme file describing its content in detail.

en:
This dataset includes quality-controlled measurements of new snow depth (HN), new snow water equivalent (HNW), snow depth (HS), and snow water equivalent (SWE) from 41 stations located in Switzerland for the period from 2016-09-01 to 2022-08-31.
These data are the basis of the following publication: Magnusson J., Cluzet B., Quéno L., Mott R., Oberrauch M., Mazzotti G., Marty C., Jonas T., 2025, Evaluating methods to estimate the water equivalent of new snow from daily snow depth recordings, Cold Regions Science and Technology, https://doi.org/10.1016/j.coldregions.2025.104435.
Abstract
The water equivalent of new snow (HNW) plays a crucial role in various fields, including hydrological modeling, avalanche forecasting, and assessing snow loads on structures. However, in contrast to snow depth (HS), obtaining HNW measurements is challenging as well as time-consuming and is hence rarely measured. Therefore, we assess the reliability of two semi-empirical methods, HS2SWE and ΔSNOW, for estimating HNW. These methods are designed to simulate continuous water equivalent of the snowpack (SWE) from daily HS only, with changes in SWE yielding daily HNW estimates. We compare both parametric methods against HNW predictions from a physics-based snow model (FSM2oshd) that integrates daily HS recordings using data assimilation. Our findings reveal that all methods exhibit similar performance, with relative biases of less than ~3 % in replicating SWE observations commonly used for model evaluations. However, the ΔSNOW model tends to underestimate daily HNW by ~17 %, whereas HS2SWE and FSM2oshd combined with a particle filter data assimilation scheme provide nearly unbiased estimates, with relative biases below ~5 %. In contrast to the parsimonious parametric methods, we show that the physics-based approach can yield information about unobserved variables, such as total solid precipitation amounts, that may differ from HNW due to concurrent melt. Overall, our results underscore the potential of utilizing commonly available daily HS data in conjunction with appropriate modeling techniques to provide valuable insights into snow accumulation processes. Our study demonstrates that daily SWE observations or supplementary measurements like HNW are important for validating the day-to-day accuracy of simulations and should ideally already be incorporated during the calibration and development of models.
Acknowlegements
These data were recorded by SLF observers and staff members. Their contribution is gratefully acknowledged.

data-assimilation

display_name: data-assimilation

new-snow

display_name: new-snow

precipitation

display_name: precipitation

snow-modelling

display_name: snow-modelling

snowfall

display_name: snowfall

en: Dataset on new snow water equivalent


en: lake-level-regulation perialpine-lakes hydrologic-and-hydrodynamic-modelling climate-change switzerland

en: Lake characteristics

en: Lake characteristics: stage-area relation for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun, stage-discharge relations for the unregulated Lake Walen and semi-regulated Lake Brienz and, lake level management rules for the two regulated lakes Zurich and Thun.

format: XLS

en: Lake outflow scenarios CH2018

en: Lake outflow scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en: Lake water level scenarios CH2018

en: Lake water level scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en:
The dataset "Lake_climate_change_scenarios_CH2018" provides simulation-based climate change impact scenarios for perialpine lakes in Switzerland. These transient future scenarios were produced by combining the hydrologic model PREVAH with the hydrodynamic model MIKE11 to simulate daily lake water level (Lake_water_level_scenarios_CH2018.xls) and outflow scenarios (Lake_outflow_scenarios_CH2018.xls) from 1981 to 2099, using the Swiss Climate Change Scenarios CH2018. The future scenarios contain a total of 39 model members for three Representative Concentration Pathways, RCP2.6 (concerted mitigation efforts), RCP4.5 (limited climate mitigation) and RCP8.5 (no climate mitigation measures). These scenarios result from the study titled "Lower summer lake levels in regulated perialpine lakes, caused by climate change," authored by Wechsler et al. in 2023.

The dataset emphasizes four specific Swiss lakes, each subject to different degrees of lake level management: an unregulated lake (Lake Walen), a semi-regulated lake (Lake Brienz), and two regulated lakes (Lake Zurich and Lake Thun).

In addition, the file (Lake_characteristics.xlsx) includes data used in the modeling process, encompassing the stage-area relation for the four lakes, stage-discharge relations for the unregulated and semi-regulated lakes, and lake level management rules for the two regulated lakes.

climate-change

display_name: climate-change

hydrologic-and-hydrodynamic-modelling

display_name: hydrologic-and-hydrodynamic-modelling

lake-level-regulation

display_name: lake-level-regulation

perialpine-lakes

display_name: perialpine-lakes

switzerland

display_name: switzerland

en: Lake climate change scenarios CH2018


en: ramms climada risk climate-change avalanche snow-avalanche

en: By using hazard scenarios based on CH2018 climate projections and the RAMMS avalanche model, we generated large-scale hazard indication maps for future avalanche hazards. By employing the open-source probabilistic risk assessment platform CLIMADA, along with building data and vulnerability functions, we estimated risks for the present time and two future time frames: mid-century (2060) and the end of the century (2085). An uncertainty and sensitivity analysis complemented the study to account for potential fluctuations in model assumptions. The data contains the hazard information and data used for the Climada risk analysis.

avalanche

display_name: avalanche

climada

display_name: climada

ramms

display_name: ramms

risk

display_name: risk

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: Assessing the impacts of climate change on snow avalanche-induced risk in alpine regions


en: ice-layers water-front weissfluhjoch snowmicropen snow-temperature snow-stratigraphy

en: README

media_type: text/plain

format: TXT

mimetype: text/plain

en: WFJ_ICE_LAYERS dataset

mimetype: application/zip

en: The WFJ_ICE_LAYERS dataset contains multi-instrument snowpack measurements at high temporal resolution, which enable to monitor the formation of deep ice layers due to preferential water flow, at the Weissfluhjoch research site, Davos, Switzerland. It covers the winter 2016/2017, with a focus on the early melting season. This dataset includes traditional snowpack profiles (weekly resolution, 15/11/2016-29/05/2017), SnowMicroPen penetration resistance profiles (daily resolution, 01/02/2017-19/04/2017), snow temperatures measured at different heights in the snowpack (half-hourly resolution, 01/03/2017-15/04/2017) and the water front height derived from an upward-looking ground penetrating radar (3-hour resolution, 04/03/2017-08/04/2017). The measurements are complemented by initialization files for SNOWPACK model simulations with the ice reservoir parameterization at Weissfluhjoch for the winter 2016/2017.

ice-layers

display_name: ice-layers

snow-stratigraphy

display_name: snow-stratigraphy

snow-temperature

display_name: snow-temperature

snowmicropen

display_name: snowmicropen

water-front

display_name: water-front

weissfluhjoch

display_name: weissfluhjoch

educ

en: Education, culture and sport

en: WFJ_ICE_LAYERS: Multi-instrument data for monitoring deep ice layer formation in an alpine snowpack


maintainer: Joan Casanelles Abella

en: paris zurich floral-resources antwerp poznan angiospermae urban plants floral-inventories tartu

en: Trait values for the sampled plants

en: List of plant species sampled in the five cities (Antwerp, Paris, Poznan, Tartu and Zurich) during the different sampling perionds (four for Zurich, three for the other cities) with their frequency (oc1-oc16) within a 100 m radius

en: Floral units, mean number of flowers per floral unit and floral abundance of the different plants counted in quadrats in the study sites in Zurich during the four sampling periods

en: Data of a survey of flowering plants in 80 sites in five European cities and urban agglomerations (Antwerp, Belgium; greater Paris, France; Poznan, Poland; Tartu, Estonia; and Zurich, Switzerland) sampled between April and July 2018.

angiospermae

display_name: angiospermae

antwerp

display_name: antwerp

floral-inventories

display_name: floral-inventories

floral-resources

display_name: floral-resources

paris

display_name: paris

plants

display_name: plants

poznan

display_name: poznan

tartu

display_name: tartu

urban

display_name: urban

zurich

display_name: zurich

en: Flowering Plants (Angiospermae) in Urban Green Areas in five European Cities


en: clouds ice-nucleation aerosol backward-trajectories raclets

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

aerosol

display_name: aerosol

backward-trajectories

display_name: backward-trajectories

clouds

display_name: clouds

ice-nucleation

display_name: ice-nucleation

raclets

display_name: raclets

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


maintainer: Michael Lehning

en: alpine3d snow alpine-precipitation alpine3d-simulations snow-distribution snow-hydrology snow-cover

en: ADS datasets and simulation inputs

en: The file contains the ADS datasets of snow depth and input data used for simulations.

en:
Dataset (Model input, snow distribution and validation) for the precipitation scaling paper, which should be cited along with the data set citation.

This data is useful for distributed hydrological modelling or other tasks that involve the study of snow distribution and precipitation in the high Alpine.

The format of the data is for Alpine3D (models.slf.ch) model runs but other models could be used, too.

Please cite:

_Vögeli, C., Lehning, M., Wever, N., Bavay M., 2016: Scaling Precipitation Input to Spatially Distributed Hydrological Models by Measured Snow Distribution., Front. Earth Sci. 4: 108. doi: 10.3389/feart.2016.00108._

Dataset is provided as a single zip file.
The archive contains two directories, the valuable distributed snow depth maps for the landscape Davos and the simulation input.
The archive also contains the file: "ReadMeMetadataDataSetPrecipitationScaling" which explains the data structure.

alpine-precipitation

display_name: alpine-precipitation

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-distribution

display_name: snow-distribution

snow-hydrology

display_name: snow-hydrology

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: Precipitation Scaling Data Set (Vögeli et al., Frontiers)


weather-station-davos-wolfgang

maintainer: Jörg Wieder

title_for_slug: weather-station-davos-wolfgang

en: raclets pressure temperature weather relative-humidity

en: Weather Station Davos Wolfgang

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

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

pressure

display_name: pressure

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

weather

display_name: weather

educ

en: Education, culture and sport


maintainer: Alexis Shakas

en: irrigation drought ert pinus-sylvestris drone-data

en: This zip file contains all raw and processed data for the electrical resistivity and drone campaigns that took place in Pfynwald, 2022

en: This .csv file contains the soil water potential data for all treatments (irrigation, irrigation-stop and control) and for the whole year of 2022. The data is given as a mean value and with an upper and lower uncertainty bound, given from the manufacturer. The depth of the sensor is given in cm, and the measured values are in units of kPa.

en:
This collection of datasets consists of various measurements taken during the year 2022 in Pfynwald. It combines 2 electrical resistivity transects which were monitored in May and July, before and after the irrigation season. The transects transverse all treatments (irrigation, control, irrigation stop). Each transect was repeated twice during the day for a period of 3 days to a week.
In addition there are raw and post-processed drone images (and resulting PRI maps), which were used to compare the below ground responses (from resistivity) to the above ground (crown) stress.
Here, the raw data is stored and a link to a git project is provided where python code is stored to reproduce all the results the published manuscript: "Does optimality partitioning theory fail for belowground traits? Insights from geophysical imaging of a drought-release experiment in a dry Scots Pine forest", New Phytologist, Shakas et al., 2024. The in-depth explanations from each processing step are found in the code (git project).

drone-data

display_name: drone-data

drought

display_name: drought

ert

display_name: ert

irrigation

display_name: irrigation

pinus-sylvestris

display_name: pinus-sylvestris

en: Pfynwald Geoelectric Experiment 2022


en:
Attention: this data is not updated after 2022 anymore.
This dataset contains the statistics on the number of avalanche fatalities per **calendar year** in Switzerland. The data collection commences with the beginning of the year 1937. After the completion of a hydrological year, which is the standard way avalanche fatalities are summarized in Switzerland and ends on the 30th of September, the new data is appended to the existing dataset.
If you require annual statistics per hydrological year, please download the data from here: [https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936]
The following information is contained (by column and column title):
 - year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste, away from open and secured ski runs)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)
The definitions for these four categories, as described in the guidelines to the avalanche accident database are:
tour:
activities include back-country ski, snowboard or snow-shoe touring
offpiste:
access from ski area, generally from the top of a skilift with short hiking distances
transportation.corridors (Techel et al., 2016):
people travelling or recreating on open or temporarily closed transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)
buildings (Techel et al., 2016):
people inside or just outside buildings, and workers on high alpine building sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

en: Number of avalanche fatalities per calendar year in Switzerland since 1937


maintainer: Achille Capelli

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

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

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: 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: 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 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 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: 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 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 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: 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: 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: 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: 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

snow-water-equivalent

display_name: snow-water-equivalent

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


maintainer: Tessa Hegetschweiler

en: adolescents teenagers childhood forest recreational-activities

en: Dataset survey at schools

en: The dataset of the questionnaire survey at schools in excel format.

en: Dataset comments

en: The codebook to the dataset

en: Survey at schools 2017

en: The dataset of the questionnaire survey at schools in SPSS-format.

en: Questionnaire school survey

en: The questionnaire used in the survey at 8 schools aimed at teenagers in German.

en: The data results from a questionnaire survey conducted at 8 schools in the cantons Zurich, Aargau and St. Gallen. Respondents aged 13-22 years. The aim of the survey was to gain insight into teenagers' relationship to the forest, reasons for visiting or not visiting the forest and activities in the forest.

adolescents

display_name: adolescents

childhood

display_name: childhood

forest

display_name: forest

recreational-activities

display_name: recreational-activities

teenagers

display_name: teenagers

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: Factors influencing teenagers' forest visit frequency


soil-property-maps-for-the-swiss-forest

title_for_slug: soil-property-maps-for-the-swiss-forest

en: switzerland soil-ph forest soil-depth soil soc soil-properties dsm soil-texture

en:
We used 2071 forest soil profiles to model a wide range of soil properties for the forested area of Switzerland. The spatial prediction is based on the principle of «digital soil mapping». This involves linking soil profiles with soil forming factors using statistical or machine learning methods.

A quantile regression forest (QRF) approach was applied to predict the following soil properties at six depth ranges: clay, gravel, sand, fine earth density, SOC. The depth ranges correspond to the standard depths of the [GlobalSoilMap.Net](https://www.isric.org/) specification: 0–5, 5–15, 15–30, 30–60, 60–100 and 100–200 cm. In addition, the total soil depth down to a non-root-permeable layer or solid rock soil thick was predicted. To quantify the uncertainty for each predicted pixel, the upper and lower limit of the 90% prediction interval derived from QRF was calculated. More details on the methods and results are described in Baltensweiler et al. 2021 and Baltensweiler et al 2022.

The soil property maps, and the uncertainty maps are provided as a GeoTIFF files at 25 m resolution. The excel file (xlsx) provides a short description of the raster layers.

**The soil and the uncertainty maps can be viewed in a simple web-GIS application available at:**
[www.wsl.ch/soilmaps](https://www.wsl.ch/soilmaps).

dsm

display_name: dsm

soc

display_name: soc

soil

display_name: soil

soil-depth

display_name: soil-depth

soil-ph

display_name: soil-ph

soil-properties

display_name: soil-properties

soil-texture

display_name: soil-texture

switzerland

display_name: switzerland

en: Soil property maps for the Swiss forest


maintainer: Frank Techel

en: alps observations avalanches snow shapefile

en: Selected wet snow avalanche activity data Davos, Switzerland (2011-2014)

en: Zip archive with shapefiles for the selected wet snow avalanche polygons, including metadata.

en:
Polygons of wet snow avalanches in the Davos area, as documented by the Swiss avalanche warning service. The georeferenced outlines of the avalanches contain both the release as well as the deposit area, but without separating between both.

The dataset is a subset of the total record of 1615 avalanches classified as wet snow avalanches from October 2011 - September 2014, containing those 255 avalanches exceeding 0.0125 km^2. Every polygon comes with meta data, including the date of occurrence.

This dataset is the underlying dataset to:
Wever, N., Vera Valero, C. and Techel, F. (2018) _Coupled snow cover and avalanche dynamics simulations to evaluate wet snow avalanche activity_. Submitted to J. Geophys. Res., in review.

alps

display_name: alps

avalanches

display_name: avalanches

observations

display_name: observations

shapefile

display_name: shapefile


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

en: Questionnaires management intensity anonymised

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

en: Not used: raw questionnaires

en: Data of the study

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

en: Raw data nests

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

en: Script for the analyses v1.0

en: Cleaned script to reproduce the analyses

format: OCTET

en: Not used: data of the study

en: Script for the analyses v2.0

en: Read me file

en: Not used: readme

en: Thesaurus

en: Variable names and their description.

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

bees

display_name: bees

cavity-nesting

display_name: cavity-nesting

food-webs

display_name: food-webs

host-enemy-interactions

display_name: host-enemy-interactions

hymenoptera

display_name: hymenoptera

management-intensity

display_name: management-intensity

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wasps

display_name: wasps

zurich

display_name: zurich

en: Data on interaction diversity in urban gardens


maintainer: James W. Kirchner

en: plynlimon streamflow tracer stable-water-isotopes catchment chloride precipitation deuterium

en: Data Set Documentation

en: This file contains a documentation of the data sets, including references to other helpful documentations.

en: 7-hourly stable water istopes

en: Data set of 7-hourly stable water isotope data measured at Carreg Wen (precipitation) and Upper Hafren (streamflow).

en: Weekly stable water isotopes

en: Data set of weekly stable water isotope data collected at Carreg Wen (precipitation) and Lower Hafren and Tanllwyth (streamflow).

en: The data base contains timeseries of stable water isotopes in precipitation and streamflow at Plynlimon, Wales, UK. One data set contains weekly stable water isotope data from the Lower Hafren and Tanllwyth catchments, and the other data set contains 7-hourly stable water isotope data from Upper Hafren. Both data sets also include chloride concentrations in precipitation and streamflow.

catchment

display_name: catchment

chloride

display_name: chloride

deuterium

display_name: deuterium

plynlimon

display_name: plynlimon

precipitation

display_name: precipitation

stable-water-isotopes

display_name: stable-water-isotopes

streamflow

display_name: streamflow

tracer

display_name: tracer

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: Stable water isotopes in precipitation and streamflow at Plynlimon, Wales, UK


en: bryophytes garten flechten moose lichens bryolich diversitat

en: Im Rahmen des Bryolich-Projekts “Moose und Flechten in Gärten” wurden möglichst vollständige Artenlisten von Moosen und Flechten in 26 bzw. 7 Gärten um Wohnhäuser erstellt. In 5 dieser Gärten wurden beide Artengruppen erfasst. Zusätzlich wurden Informationen über unterschiedliche Lebensräume innerhalb der Gärten (z.B. Fläche mit Gehölzen, Fläche von Blumenbeeten) und weitere Garten-Charakteristika (z.B. Fläche des Gartens, Alter des Gartens, Einsatz von Dünger) erfasst. Details zum Projekt und den erfassten Daten können im zugehörigen Artikel (Bergamini et al. 2024) und auf der Webseite von Bryolich gefunden werden (https://www.bryolich.ch/mfig/mfig_de.html).

bryolich

display_name: bryolich

bryophytes

display_name: bryophytes

diversitat

display_name: diversitat

flechten

display_name: flechten

garten

display_name: garten

lichens

display_name: lichens

moose

display_name: moose

en: Daten Bryolich-Projekt Moose und Flechten in Gärten


en: soil measurements soil-classification glide-snow-avalanche lwc soil-texture matric-potential alpine

en: Detailed information of each file in the dataset

en: Complete list of the van Genuchten parameter values for each soil and method

en: Daily averaged values used for the direct fitting

en: Coordinates of each soil location, location of the snow profiles, and location of the snow liquid water content measurements

en: Texture data of the soil locations

en: Hydrus files used for the inverse fitting

en: The dataset contains measured values of soil liquid water content, matric potential, and soil texture of 40 soil samples in Davos, Switzerland. The measurements were used for determining van Genuchten parameter values through fitting of water retention curves, pedotransfer functions, and inverse fitting with Hydrus-1D.

alpine

display_name: alpine

glide-snow-avalanche

display_name: glide-snow-avalanche

lwc

display_name: lwc

matric-potential

display_name: matric-potential

measurements

display_name: measurements

soil

display_name: soil

soil-classification

display_name: soil-classification

soil-texture

display_name: soil-texture

en: Soil measurements of Seewer Berg and Davos


maintainer: Francesco Comola

en: sand cohesion saltation wind sediment snow

en: Output of the model simulations

en: Model results on granular splash and saltation process of sand and snow particles

en:
The wind-driven saltation of sand and snow shapes dunes and ripples, generates dust emission, and erodes the surface of the Antarctic ice sheet. Here, we use a model based on the discrete element method to simulate grain-flow interactions and study the effect of particle cohesion on saltation dynamics.

The data contains the model output of granular splash simulations and saltation simulations. Granular splash, the main particle entrainment process in saltation, occurs upon impact of saltating particles with the granular bed. We performed Monte Carlo simulations of granular splash for loose sand grains and for cohesive ice grains. The analysis indicate that different values of cohesion have significant effects not on the number of splashed grains, on the ejection velocity, and the rebound velocity.

In our saltation simulations, we trigger particle movement with a single splash event at the inlet section section and let the system evolve until steady state. Our results show that saltation over cohesive surfaces is difficult to initiate but easy to sustain at low wind speed. The occurrence of transport thus depends on the history of the wind speed, a phenomenon known as hysteresis. We also show that saltation over cohesive surfaces presents higher mass fluxes but requires longer distances to saturate, which increases the size of the smallest stable surface ripples. Our model results have implications for large-scale aeolian processes on Earth and Titan, where sand grains are thought to be very cohesive.

cohesion

display_name: cohesion

saltation

display_name: saltation

sand

display_name: sand

sediment

display_name: sediment

snow

display_name: snow

wind

display_name: wind

en: Saltation of cohesive granular materials


en: sankt-annafirn drone glacier uav orthoimage orthophoto dem gletscher griesgletscher dsm alps findelengletscher

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 21th of July 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 26th of September 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 22th of September 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 30th of August 2016.

en: This .pdf contains an orthoimage for each dataset as well as a Table which displays the number of flights made, image acquired, number of GCP set and the total area covered.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 15th of July 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 09th of April 2015.

en: Bulk Data Access

en: Link to the S3 bucket where all the data resources can be downloaded in bulk

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 19th of April 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 2nd of July 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 28th of September 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 13th of September 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 15th of August 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 15th of September 2015.

en: This folder contains all UAV flights paths that we created for the Sankt Annafirn, the Findelengletscher and Griesgletscher. They have been created with the software eMotion2, that was developped for the eBee platform from Sensefly.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 3rd of August 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 15th of April 2015.

en:
 UAV-derived DSMs and orthoimages

Unmanned Aerial Vehicle (UAV) surveys were conducted between 2015 and 2016 on the Sankt Annafirn, Findelen- and Griesgletscher, situated in the Swiss Alps. Three surveys at the Sankt Annafirn allowed for a full glacier coverage, four surveys at Griesgletscher allowed an almost full glacier coverage and seven surveys at Findelengletscher allowed for a partial coverage of the glacier tongue (see individual datasets for exact extent). For each survey, a high resolution orthoimage and a Digital Surface Model (DSM) was created.

 UAV surveys:

Prior flight, Ground Control Points (GCPs) were deployed on the glacier surface and measured with a differential GPS (Trimble R7 or Leica GPS 1200). They allowed precise georeferencing of the UAV-derived datasets. UAV flight plans were planned with the software *eMotion 2* and a SenseFly eBee was used as surveying platform. The images were then processed with the software Agisoft Photoscan Pro 1.1.6 .

The location and dates of each survey can be found in the table together with the number of flights performed (Nflights), the number of acquired images (Nimages), the number of GCPs set (NGCPs) and the surveyed area.

A folder for each dataset is available (see folder name in table), which contains:

- An orthoimage *glacier_date_photoscan_oi_CH1903+_LV95_0.1m.tif*

- A Digital Surface Model *glacier_date_photoscan_dsm_CH1903+_LV95_0.1m.tif*

- The Agisoft Photoscan automatic processing report  *glacier_date_photoscan_report.pdf*

where:

- *glacier* is the name of the surveyed glacier

- *date* is the date of the UAV image acquisition

- *photoscan* is the name of the photogrammetric software

- *oi* or *dsm* the type of dataset

- *CH1903+_LV95* is the coordinate system and datum of the dataset

- *0.1m* is the resolution of the dataset in meter

- *.tif* is the extention of the dataset

Details about the UAV surveys, the image processing and the accuracy of the UAV-derived products can be found in this publication below.

Paper Citation:
 > _Gindraux et al. 2017. Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’Imagery on Glaciers, Remote Sensing, 9, 186, 1-15, [doi: 10.3390/rs9020186](https://doi.org/10.3390/rs9020186)._

The folder UAV_flight_paths.zip contains all UAV flights performed on the Sankt Annafirn, Findelengletscher and Griesgletscher. The flights were planned with the software eMotion2 and have the .afp extention.

alps

display_name: alps

dem

display_name: dem

drone

display_name: drone

dsm

display_name: dsm

findelengletscher

display_name: findelengletscher

glacier

display_name: glacier

gletscher

display_name: gletscher

griesgletscher

display_name: griesgletscher

orthoimage

display_name: orthoimage

orthophoto

display_name: orthophoto

sankt-annafirn

display_name: sankt-annafirn

uav

display_name: uav

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: UAV-derived Digital Surface Models and orthoimages for three alpine glaciers


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

en: Field station data (SCF)

en: Data file.

en: Site photo of the forest station (SCB)

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

en: Site photo of the field station (SCF)

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

en: Data plot of the forest station (SCB)

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

en: Further details on the data repository

en: Meta data documentation.

en: Data plot of the field station (SCF)

en: Site aerial photo (Schänis)

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

en: Forest station data (SCB)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Schänis in Switzerland where one station is located within a natural mixed forest stand (SCB) with European beech (_Fagus sylvatica_; 130-150 yrs), European silver fir (_Abies alba_; 130-150 yrs) and European ash (_Fraxinus excelsior_; 130-150 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, SCF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Schänis is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

en: Schänis, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1998 onwards


maintainer: Daniel Scherrer

en: land-use species-migration r-package species-interaction bioclimatic-variables forest forest-dynamics gui forest-model spatial-modelling treemig

en: Description input data

en: Details where the input data come from and how they have been processed

en: Tutorial for using the TreeMig framework; updated

en: TreeMig Simulation Environment and Input Data

en:
The zip file consists of a R-script to provide the framework, an example simulation environment and a set of input data.
- The R-script installAndRunTreeMigWrapperAndGUI.R installs the R-package, links to the input data and starts the graphical user interface.
- The gridded input datasets in TMInputData are specifically tailored to Switzerland and have the same coordinate reference system and a congruent 200m spatial resolution. They consist of climate, topographic, land use and soil data. For details see TMInputDataDetails.pdf.
- TMEnvironment is an example simulation environment, i.e. a set of hierarchically structured folders. For the first example simulation of the tutorial it contains the
  - the TreeMig executables for MacOS, Linux and Windows
  - simulation control files that define the setup and input files of the simulation (in folder C)
  - species parameters (in folder P)
  - bioclimatic data (in folder E)
  - folder R for results
  - folder Plots for plots of the simulation results.
  - This environment can be also used for the subsequent simulations of the tutorial.
- Some additional R-scripts demonstrate more complex applications described in the tutorial, e.g. coupling to another model.

en: TreeMig Tutorial

en:
Starter kit for the TreeMig framework that allows for an easy application of the forest landscape model TreeMig for simulating forest dynamics in space under changing environmental and land use conditions.
The starter kit consists of a set of climate, land-use, topography and soil property input data for Switzerland, a script for installing the framework and running the GUI of the framework with the link to the input data, a tutorial covering a range of simulation examples for Switzerland and a transect through Europe, and an associated example simulation environment containing the model executables and other model inputs.

bioclimatic-variables

display_name: bioclimatic-variables

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-model

display_name: forest-model

gui

display_name: gui

land-use

display_name: land-use

r-package

display_name: r-package

spatial-modelling

display_name: spatial-modelling

species-interaction

display_name: species-interaction

species-migration

display_name: species-migration

treemig

display_name: treemig

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: Starter Kit for the TreeMig framework v1 for easy simulation of spatio-temporal forest dynamics


en: antarctica mass-flux snowmicropen drifting-snow meteorological-data terrestrial-laser-scanning

en: Dataset

en: Links to the dataset

en: README

en: Describes the dataset in detail

en:
This dataset contains the data acquired during the expedition to Princess Elisabeth Antarctica Station in December 2016 and January 2017. The dataset consits of meterorological data, drifting snow mass flux data, SnowMicroPen data and Terrestrial Laser Scanning data.

Please refer to the README for more information about the data.

This dataset is the basis of the following publication:

Sommer, C. G., Wever, N., Fierz, C., and Lehning, M.: Wind-packing of snow in Antarctica, The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-36, in review, 2018.

antarctica

display_name: antarctica

drifting-snow

display_name: drifting-snow

mass-flux

display_name: mass-flux

meteorological-data

display_name: meteorological-data

snowmicropen

display_name: snowmicropen

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

en: Expedition to Princess Elisabeth Antarctica Station, 2016/2017


en: land-use climate-change bioclimatic-variables forest forest-dynamics example-applications treemig spatial-modelling species-migration r-package forest-management

en: Where the environmental and land use input data come from and how they were processed

en: R-script to install the TreeMig framework and start the graphical user interface

en: A condensed instruction for running the presented simulations.

en:
1) Simulation environment TMEnvironmentExampleApplications for the simulation of the case study applications. It contains a) simulation settings (folder C), b) species parameters (folder P), c) folders S, R and P for the state files and results and plots to be produced, and the binaries of the TreeMig model.
2) Input data for Switzerland in TMInputData (Climate, soil, land cover, DEM)
3) Several R scripts (folder Scripts) to run and plot the simulations directly from R without having to use the graphical user interface.
For learning how to use TreeMig we recommend the starter kit https://www.doi.org/10.16904/envidat.533.

en:
The TreeMig framework allows for an easy application of the forest landscape model TreeMig for simulating forest dynamics in space under changing environmental and land use conditions.
Here, case study examples in Switzerland are given that simulate the dynamics and spatial spread of competing tree species in a region in Switzerland, the invasion of a hypothetical invasive tree species, and the control of this species via a management model coupled to TreeMig. The datasets consist of the installation- and GUI starting-script, example environmental input data for Switzerland, the simulation environment, and further R-scripts for running the simulations and plotting the simulation results directly from R and for coupling TreeMig to the forest management model.

bioclimatic-variables

display_name: bioclimatic-variables

climate-change

display_name: climate-change

example-applications

display_name: example-applications

forest-management

display_name: forest-management

en: Case study applications demonstrating the use and potential of the TreeMig framework v1


en: large-eddy-simulations meteorological-data mass-flux turbulence blowing-snow antarctica eddy-covariance-measurements drifting-snow micro-rain-radar

en: Source code of the large-eddy simulations coupled with a Lagrangian stochastic model (LES-LSM), available on GitLab.

en: Simulation data for a situation with negligible snow transport

en: Results from two LES-LSM simulations called NoDrift_1 and NoDrift_2, which reproduce the conditions observed at the S17 site on 12th January 2019, 05:40 to 05:50 UTC.

en: Measurement data from Micro Rain Radar (MRR)

en: Remote sensing data of blowing snow from a Micro Rain Radar (MRR).

en: Readme

en: Meta data

en: Simulation data for a situation with significant snow transport

en: Data from two LES-LSM simulations called Drift_1 and Drift_2, which reproduce the conditions observed at the S17 site on 11th January 2019, 00:40 to 00:50 UTC.

en: Measurement data from micro-meteorological station

en: Automatic in-situ measurements of micro-meteorology and snow transport

en: Measurement data from snow particle counter at MRR site

en: Near-surface observations of drifting snow from a Snow Particle Counter (SPC) installed at the location of the Micro Rain Radar.

en:
This dataset contains measurement and simulation data. The measurements characterize the standard meteorology, turbulence, and snow transport at the S17 site near Syowa Station in East Antarctica during an expedition in austral summer 2018/2019. Large-eddy simulations with sublimating particles provide additional insight into the latent and sensible heat exchange between snow and air in two example situations observed at the S17 site.

A part of the measurement data was recorded by an automatic measurement station from 10th January 2019 to 26th January 2019. This measurement station was equipped with standard meteorological sensors, a three-dimensional ultrasonic anemometer, an open-path infrared gas analyzer, a snow particle counter, an infrared radiometer for measurements of the surface temperature, and a sonic ranging sensor measuring changes in snow surface elevation.

At a horizontal distance of approximately 500 m, a Micro Rain Radar (MRR) was installed in a tilted configuration with an elevation angle of 7° for remote sensing of blowing snow between 25th December 2018 and 24th January 2019. In addition, near-surface in-situ measurements of snow transport were performed at the location of the MRR by deploying a snow particle counter from 27th December 2018 to 24th January 2019.

The simulations cover a 18 x 18 x 6 m³ domain and reproduce the steady-state conditions during a 10-min interval with significant snow transport and another 10-min interval with negligible snow transport. We provide the model source code and the post-processed simulation data, i.e., horizontally averaged quantities as a function of height and time.

blowing-snow

display_name: blowing-snow

eddy-covariance-measurements

display_name: eddy-covariance-measurements

large-eddy-simulations

display_name: large-eddy-simulations

micro-rain-radar

display_name: micro-rain-radar

turbulence

display_name: turbulence

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Meteorology and snow transport at S17 near Syowa, Antarctica, in austral summer 2018/2019