de: energiedashboard stromverbrauch

en: energy-dashboard power-consumption

it: dashboard-sullenergia consumo-elettrico

de: Stromverbrauch Prognose SDSC

de: energiedashboard.ch: Stromverbrauch Prognose SDSC

fr: Le modèle de consommation d'électricité produit une estimation de la consommation d'électricité à l'échelle nationale suisse. Le modèle est entraîné sur des données provenant des sources suivantes : consommation nationale horaire fournie par Swissgrid (aperçu de l'énergie), données météorologiques de MétéoSuisse (y compris les prévisions météorologiques), et informations calendaires telles que les jours fériés fournis par le paquet de jours fériés python et les jours fériés acquis manuellement. Le modèle appartient à la catégorie des modèles additifs généralisés (GAM) et produit une prédiction sur une base quotidienne avec un intervalle de confiance inférieur et supérieur de 2,5 et 97,5 respectivement. Source: Quelle: OFEN, SDSC.

de: Das Stromverbrauchsmodell liefert eine Schätzung des Stromverbrauchs auf nationaler Ebene in der Schweiz. Das Modell wird mit Daten aus den folgenden Quellen trainiert: stündlicher nationaler Verbrauch von Swissgrid (Energieübersicht), meteorologische Daten von MeteoSchweiz (einschliesslich Wettervorhersage) und Kalenderinformationen wie Feiertage, die vom python Holiday Package bereitgestellt werden, sowie manuell erfasste Feiertage. Das Modell gehört zur Kategorie der verallgemeinerten additiven Modelle (GAMs) und liefert eine Vorhersage auf täglicher Basis mit einem unteren und oberen Konfidenzintervall von 2,5 bzw. 97,5. Quelle: BFE, SDSC.

en: The electricity consumption model outputs an estimate of electricity consumption at the Swiss national scale. The model is trained on data from the following sources: hourly national consumption provided by Swissgrid (Energy overview), meteorological data from MeteoSwiss (including weather forecast), and calendar information such as public holidays as provided by the python holidays package and manually acquired holidays. The model belongs to the category of Generalized Additive Models (GAMs) and output is a prediction at a daily basis with a lower and upper confidence interval of 2.5 and 97.5 respectively. Source: SFOE, SDSC

it: Il modello di consumo di elettricità produce una stima del consumo di elettricità su scala nazionale svizzera. Il modello è addestrato sui dati provenienti dalle seguenti fonti: consumo nazionale orario fornito da Swissgrid (panoramica dell'energia), dati meteorologici di MeteoSvizzera (comprese le previsioni del tempo) e informazioni sul calendario, come i giorni festivi forniti dal pacchetto vacanze di python e i giorni festivi acquisiti manualmente. Il modello appartiene alla categoria dei modelli additivi generalizzati (GAM) e il risultato è una previsione su base giornaliera con un intervallo di confidenza inferiore e superiore di rispettivamente 2,5 e 97,5 . Fonti: UFE, SDSC.

consommation-delectricite

display_name: consommation-delectricite

consumo-elettrico

display_name: consumo-elettrico

dashboard-de-lenergie

display_name: dashboard-de-lenergie

dashboard-sullenergia

display_name: dashboard-sullenergia

energiedashboard

display_name: energiedashboard

energy-dashboard

display_name: energy-dashboard

power-consumption

display_name: power-consumption

fr: Office fédéral de l'énergie (OFEN)

de: Bundesamt für Energie (BFE)

en: Swiss Federal Office of Energy (SFOE)

it: Ufficio federale dell'energia (UFE)

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

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

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

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

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

value: DCAT I14Y BFE

fr: energiedashboard.ch - Prévisions de consommation d'électricité SDSC

de: energiedashboard.ch - Stromverbrauch Prognose SDSC

en: energiedashboard.ch - Power consumption forecast SDSC

it: energiedashboard.ch - Previsione del consumo di energia SDSC


de: stromverbrauch energiedashboard

state: active

type: dataset

fr: Energiedashboard - Consommation estimée modélisée

de: Energiedashboard - Modellbasiert geschätzter Verbrauch

it: Energiedashboard - Consumo stimato modellizzato

media_type: text/csv

format: CSV

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

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

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

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

dashboard-de-lenergie-suisse

display_name: dashboard-de-lenergie-suisse

dashboard-sullenergia-svizzera

display_name: dashboard-sullenergia-svizzera

energy-dashboard-switzerland

display_name: energy-dashboard-switzerland

stromverbrauch

display_name: stromverbrauch

political_level: confederation

type: organization

approval_status: approved

key: guid

key: uri

fr: energiedashboard.ch - Consommation nationale estimée modélisée

en: energiedashboard.ch - Model-based estimated national consumption

de: energiedashboard.ch -Modellbasiert geschätzter Landesverbrauch

it: energiedashboard.ch - Consumo nazionale stimato modellizzato


de: energiedashboard stromproduktion

fr:
En Suisse, il existe un grand nombre de centrales électriques qui produisent de l'énergie électrique (électricité). En ce qui concerne la production, on distingue les catégories suivantes : centrales nucléaires, centrales thermiques, centrales hydroélectriques fluviales, centrales hydroélectriques à accumulation, centrales éoliennes et centrales photovoltaïques. La production de ces centrales est entraînée par différents facteurs. Alors que les centrales à accumulation et à pompage-turbinage, par exemple, sont fortement guidées par le marché (en fonction des signaux de prix), les centrales nucléaires produisent de l'énergie en bande. En revanche, le photovoltaïque et l'éolien dépendent du soleil et du vent. Source: Swissgrid

La production en Suisse, ajoutée aux importations et aux exportations, donne la consommation nationale, y compris la consommation des centrales de pompage-turbinage.

La tendance indique l'évolution de la production totale suisse par rapport à la moyenne des 10 derniers jours.

de:
In der Schweiz gibt es eine Vielzahl an Kraftwerken, die elektrische Energie (Strom) produzieren. Bei der Produktion werden die Kategorien Kernkraftwerke, thermische Kraftwerke, Flusswasserkraft, Speicherwasserkraft, Windkraft und Photovoltaik unterschieden. Die Produktion dieser Kraftwerke ist getrieben durch unterschiedliche Faktoren. Während beispielsweise Speicher- und Pumpspeicherkraftwerke stark marktgetrieben (anhand von Preissignalen) eingesetzt werden, produzieren die Kernkraftwerke Bandenergie. Photovoltaik und Wind sind hingegen abhängig von Sonne und Wind. Quelle: Swissgird.

Die Produktion in der Schweiz zusammen mit Import und Export ergibt den Landesverbrauch inklusive des Verbrauchs der Pumpspeicher.

Der Trend gibt die Entwicklung der Schweizer Gesamtproduktion im Vergleich zum Durchschnitt der letzten 10 Tage an.

en:
In Switzerland, there are a large number of power plants that produce electrical energy (electricity). In terms of production, a distinction is made between the categories of nuclear power plants, thermal power plants, river hydropower, storage hydropower, wind power and photovoltaics. The production of these power plants is driven by different factors. For example, while storage and pumped storage power plants are strongly market-driven (based on price signals), nuclear power plants produce band energy. Photovoltaics and wind, on the other hand, are dependent on the sun and wind. Source: Swissgrid.

The production in Switzerland together with import and export results in the country's consumption including the consumption of pumped storage.

The trend indicates the development of the total Swiss production compared to the average of the last 10 days.

it:
In Svizzera, ci sono un gran numero di centrali elettriche che producono energia elettrica (elettricità). In termini di produzione, si distingue tra le categorie di centrali nucleari, centrali termiche, energia idroelettrica fluviale, energia idroelettrica di accumulo, energia eolica e fotovoltaica. La produzione di queste centrali elettriche è guidata da diversi fattori. Per esempio, mentre le centrali di accumulo e di pompaggio sono fortemente orientate al mercato (basandosi sui segnali di prezzo), le centrali nucleari producono energia di banda. Il fotovoltaico e l'eolico, invece, dipendono dal sole e dal vento. Fonte: Swissgrid.

La produzione in Svizzera, insieme all'importazione e all'esportazione, si traduce nel consumo del Paese, compreso il consumo dell'accumulo con pompaggio.

Il trend indica l'andamento della produzione totale svizzera rispetto alla media degli ultimi 10 giorni.

power-production

display_name: power-production

producion-delectricite

display_name: producion-delectricite

produzione-di-elettricita

display_name: produzione-di-elettricita

stromproduktion

display_name: stromproduktion

fr: energiedashboard.ch: Producion d'électricité Swissgrid

en: energiedashboard.ch: Electricity production Swissgrid

it: energiedashboard.ch: Produzione di elettricità Swissgrid


vde-schleifen

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: vde-schleifen

de: induktionsschleifen schleifen vde verkehrsdaten verkehrsdatenerfassung verkehrszahlung

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

it: geocat.ch link permanente

de: Web Map Services WMS

format: WMS

de: Sämtliche Induktionsschleifen im Eigentum von Tiefbau Stadt Bern, für die Verkehrsdatenerfassung des motorisierten Individualverkehrs sowie des Veloverkehrs

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

stadt-bern

capacity: public

value: Geoinformation Stadt Bern - Geocat Harvester

de: VDE-Schleifen


oberstufenschulkreise

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: oberstufenschulkreise

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: Einzugsgebiete und Schulhausstandorte der Oberstufen im Kanton Uri

spatial: Canton of Uri (UR)

fr: Amt für Volksschulen Kt. Uri

de: Amt für Volksschulen Kt. Uri

en: Amt für Volksschulen Kt. Uri

it: Amt für Volksschulen 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

value: Uri-Kt - Geocat Harvester

fr: Oberstufenschulkreise

de: Oberstufenschulkreise

en: Oberstufenschulkreise

it: Oberstufenschulkreise


regi

de: Regionen und Städte

url: https://geo.ur.ch/?layers=Strassenverkehrslärm Emissionen IST Nacht

fr: Der Strassenlärmemissionen wurden mit dem Berechnungsprogramm SLIP erstellt. Grundlagen für die Berechnungen bilden die Verkehrszahlen der Kantons- und Gemeindestrassen aus dem Jahr 2018.

fr: Amt für Umwelt Kt. Uri

de: Amt für Umwelt Kt. Uri

en: Amt für Umwelt Kt. Uri

it: Amt für Umwelt Kt. Uri


baulandangebot

title_for_slug: baulandangebot

author: Kanton Luzern, Abteilung Geoinformation

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

format: SERVICE

de: Durch Gemeinden angebotene Baulandparzellen. Die Angebote werden durch teilnehmenden Gemeinden selber verwaltet.

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

de: Baulandangebote Gemeinden


fr: geo.admin.ch: le géoportail fédéral

de: geo.admin.ch: das Geoportal des Bundes

en: geo.admin.ch: the federal geoportal

it: geo.admin.ch: il geoportale federale

de: geocat.ch Permalink

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

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

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

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

fr: Aperçu map.geo.admin.ch

de: Vorschau map.geo.admin.ch

en: Preview map.geo.admin.ch

it: Previsione map.geo.admin.ch

fr: Service WMS-IFDG, couche "Carte nationale 1:500`000 | CN500"

de: WMS-BGDI Dienst, Layer "Landeskarte 1:500`000 | LK500"

en: WMS-FSDI service, layer "National Map 1:500`000"

it: Servizio WMS-IFDG, strato "Carta nazionale 1:500`000 | CN500"

fr: Service WMTS-IFDG, couche , Layer "Carte nationale 1:500'000 | CN500"

de: WMTS-BGDI Dienst, Layer "Landeskarte 1:500'000 | LK500"

en: WMTS-FSDI service, layer "National Map 1:500'000"

it: Servizio WMTS-IFDG, strato "Carta nazionale 1:500'000 | CN500"

format: WMTS

fr: Information du produit Swiss Map Raster + Download

de: Produktinformation Swiss Map Raster + Download

en: Product info Swiss Map Raster + Download

it: Informazioni sul prodotto Swiss Map Raster + Download

fr: La carte nationale au 1:500'000 est une carte topographique synoptique de la Suisse. La carte nationale au 1:500'000 est disponible sous forme analogique (carte papier) et digitale (Swiss Map Raster, Swiss Map Vector).

de: Die Landeskarte 1:500'000 ist eine topografische Übersichtskarte der Schweiz. Die Landeskarte 1:500'000 ist in analoger (Papierkarte) und in digitaler Form (Swiss Map Raster, Swiss Map Vector) verfügbar.

en: The National Map 1:500,000 is a topographic map giving an overview of Switzerland. The National Map 1:500,000 is published in analogue format as a printed map and in digital format as the Swiss Map Raster and Swiss Map Vector.

it: La Carta nazionale 1:500'000 è una carta sinottica topografica della Svizzera. La Carta nazionale 1:500'000 è disponibile in formato analogico (cartaceo) e digitale (Swiss Map Raster, Swiss Map Vector).

spatial: Landeskarte 1:500'000

fr: Office fédéral de topographie swisstopo

de: Bundesamt für Landestopografie swisstopo

en: Federal Office of Topography swisstopo

it: Ufficio federale di topografia swisstopo

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

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

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

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

value: Swisstopo - Geocat Harvester

fr: Carte nationale 1:500'000

de: Landeskarte 1:500'000

en: National Map 1:500'000

it: Carta nazionale 1:500'000


mobilfunkanlagen

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: mobilfunkanlagen

author: Bundesamt für Kommunikation

fr: Lien vers le portail

de: Link zum Fachportal

en: Link to portal

it: Link al portale

fr: geocat.ch permalien

en: geocat.ch permalink

it: geocat.ch link permanente

fr: Service WMS-IFDG, couche "Stations de téléphonie mobile"

de: WMS-BGDI Dienst, Layer "Mobilfunkanlagen"

en: WMS-FSDI service, layer "Mobile phone base stations"

it: Servizio WMS-IFDG, strato "Impianti di telefonia mobile"

fr: Service WMTS-IFDG, couche "Stations de téléphonie mobile"

de: WMTS-BGDI Dienst, Layer "Mobilfunkanlagen"

en: WMTS-FSDI service, layer "Mobile phone base stations"

it: Servizio WMTS-IFDG, strato "Impianti di telefonia mobile"

fr: RESTful API de geo.admin.ch

de: RESTful API von geo.admin.ch

en: RESTful API from geo.admin.ch

it: RESTful API da geo.admin.ch

format: API

fr: Serveur de téléchargement de geo.admin.ch

de: Download von data.geo.admin.ch

en: Download server from geo.admin.ch

it: Server di download di geo.admin.ch

format: HTML

fr:
Représentation des emplacements des stations de téléphonie mobile.
Plus d'informations
Disponibilité des réseaux mobiles

de:
Darstellung der Standorte von Mobilfunkstationen.
Mehr Information
Verfügbarkeit von Mobilfunknetzen

en:
Visualisation of the locations of mobile phone stations.
More information
Availability of mobile networks

it:
Visualizzazione della posizione delle stazioni di telefonia mobile.
Più informazioni
Disponibilità di reti telefoniche mobili

spatial: Schweiz

fr: Office Fédéral de la Communication

de: Bundesamt für Kommunikation

en: Federal Office of Communications

it: Ufficio federale delle comunicaioni

bundesamt-fur-kommunikation-bakom

fr: Office fédéral de la communication OFCOM

de: Bundesamt für Kommunikation BAKOM

en: Federal Office of Communications OFCOM

it: Ufficio federale delle comunicazioni UFCOM

fr:
Téléphoner, s’informer par les journaux, la radio ou la télévision, échanger des courriels ou des SMS, surfer sur Internet : autant d’activités quotidiennes qui dépendent d’une infrastructure de communication performante. L’OFCOM contribue à ce que la population et l’économie disposent de services de télécommunication appropriés et compétitifs.
L’office veille à ce que les auditeurs et téléspectateurs puissent s’informer dans leur région, grâce aux diffuseurs régionaux, et au niveau national, par les programmes de la SSR. Il répartit équitablement le produit de la redevance radio et TV entre toutes les régions de Suisse. Dans le domaine postal, il permet aux journaux et périodiques de bénéficier de prix préférentiels.
L’OFCOM gère les fréquences pour que les stations de radio, les téléphones mobiles et les appareils sans fil puissent communiquer sans perturbation.
Grâce à ses activités de surveillance, il participe aussi à la protection des consommateurs : il vérifie que les dispositions légales sont respectées, par exemple en matière de publicité dans les programmes radio et TV, dans le domaine des services à valeur ajoutée proposés par téléphone sur des numéros 090x ou dans l’usage des fréquences.

en:
Every day we read the paper, pick up the phone, write and send emails and text messages, surf online, listen to the radio and watch TV. In order to be able to use all these services, there has to be a stable and powerful communications infrastructure in place. OFCOM helps to ensure that the population and businesses in all parts of the country have access to adequate and competitive tele-communications services.
OFCOM makes it possible for radio and television users at local level to access regional stations and the SRG’s programmes at national level. It also distributes the revenues from television and radio licence fees fairly among all regions in Switzerland. In the postal sector, OFCOM makes sure that newspapers and magazines benefit from reduced postage rates. It also manages and allocates frequencies for radio stations, mobile and wireless devices to ensure interference-free communication.
OFCOM’s oversight responsibilities include consumer protection. It monitors compliance with statutory provisions for radio and television advertising, value-added services which are offered with 090x numbers and for use of frequencies.

de:
Telefonieren, sich via Presse, Radio oder Fernsehen informieren, E-Mails oder SMS schreiben und empfangen, im Internet surfen – für diese alltäglichen Tätigkeiten braucht es eine leistungsfähige Kommunikationsinfrastruktur. Das BAKOM trägt dazu bei, dass die Bevölkerung und die Wirtschaft in allen Landesteilen über angemessene und kompetitive Telekommunikationsdienste verfügen. Das Amt ermöglicht, dass sich Radio-und Fernsehnutzer auf lokaler Ebene über regionale Sender und auf nationaler Ebene über die Programme der SRG informieren können. Es verteilt auch die Erträge aus den Radio-und Fernsehgebühren gerecht auf alle Regionen der Schweiz. Im Postbereich sorgt es dafür, dass Zeitungen und Zeitschriften von günstigen Versandkosten profitieren.
Weiter gewährleistet es über die Frequenzverwaltung und -zuteilung für Radio, Mobilfunk und drahtlose Geräte eine störungsfreie Kommunikation.
Mit seiner Aufsichtstätigkeit trägt das BAKOM auch zum Schutz der Konsumentinnen und Konsumenten bei: Es überwacht das Einhalten der gesetzlichen Bestimmungen, sei es bei der Radio-und Fernsehwerbung, den Mehrwertdiensten, die über 090x-Nummern angeboten werden, oder bei der Frequenznutzung.

it:
Ogni giorno parliamo al telefono, ci teniamo informati attraverso la stampa, la radio e la televisione, scriviamo e-mail o SMS e navighiamo in Internet. Per svolgere tutte queste attività occorre un’infrastruttura di comunicazione performante. L’UFCOM contribuisce affinché la popolazione e l’economia dispongano di servizi di telecomunicazione adeguati e competitivi.
L’Ufficio permette ai telespettatori e ai radioascoltatori di informarsi a livello locale, grazie alle emittenti regionali, e a livello nazionale, attraverso i programmi della SSR. Ripartisce equamente i proventi derivanti dai canoni radiotelevisivi tra le regioni della Svizzera. Nel settore postale, offre a giornali e periodici la possibilità di beneficiare di riduzioni sui prezzi di spedizione.
L’UFCOM gestisce le frequenze affinché le stazioni radiofoniche, i telefoni cellulari e gli apparecchi senza fili possano comunicare senza interferenze.
Grazie alla sua attività di vigilanza l’UFCOM contribuisce inoltre alla tutela dei consumatori, verificando il rispetto delle disposizioni legali vigenti, in ambiti quali la pubblicità nei programmi radiotelevisivi, i servizi a valore aggiunto offerti tramite i numeri telefonici 090x o l’utilizzazione delle frequenze.

value: BAKOM - Geocat Harvester

fr: Stations de téléphonie mobile

de: Mobilfunkanlagen

en: Mobile phone base stations

it: Impianti di telefonia mobile


de: bgdi-bundesgeodaten-infrastruktur bund

de: geocat.ch Permalink

protocol: WWW:DOWNLOAD:Portable Document Format (PDF)

fr: Atlas hydrologique de la Suisse

de: Hydrologischer Atlas der Schweiz

en: Hydrological Atlas of Switzerland

it: Atlante idrologico della Svizzera

format: PDF

fr: Zenodo

de: Zenodo

en: Zenodo

it: Zenodo

fr: Le terme de vulnérabilité est utilisé pour décrire la sensibilité d’un système à l’égard d’une atteinte venant de l’extérieur. Appliqué à l’eau souterraine, ce terme définit la menace que représente, pour un réservoir aquifère, la pénétration de polluants dans le sous-sol. La présente planche a pour but de représenter la sensibilité des réservoirs aquifères au point de vue des menaces possibles par des polluants, à l’échelle du territoire national.

de: Der Begriff der Vulnerabilität beschreibt die Empfindlichkeit eines Systems hinsichtlich einer externen Beeinträchtigung. Übertragen auf das Grundwasser definiert Vulnerabilität die Gefährdung eines Grundwasservorkommens durch den Eintrag von Schadstoffen in den Untergrund. In der vorliegenden Tafel wird die Empfindlichkeit der Grundwasservorkommen bezüglich möglicher Gefährdungen durch Schadstoffe in einem gesamtschweizerischen Kontext dargestellt.

en: The term «vulnerability» refers to the sensitivity of a system in relation to a harmful external influence. In the case of groundwater, vulnerability is defined as the exposure to pollution through the influx of harmful substances into the aquifer. This plate shows the vulnerability of groundwater resources to potential pollutants throughout Switzerland.

it: Il concetto di vulnerabilità è inteso a descrivere la sensibilità di un sistema nei confronti di un’aggressione esterna. Nel caso delle acque sotterranee la vulnerabilità è riferita al rischio connesso con l’introduzione d’inquinanti nel sottosuolo. La presente tavola rappresenta nel contesto nazionale l’esposizione delle falde idriche alle possibili minacce causate dagli agenti inquinanti.

fr: Office fédéral de l'environnement /Division Hydrologie

de: Bundesamt für Umwelt / Abteilung Hydrologie

en: Federal Office for the Environment / Hydrology Division

it: Ufficio federale dell'ambiente / Divisione Idrologia

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.

value: BAFU - Geocat Harvester

fr: Planche 8.7 Vulnérabilité des réservoirs aquifères

de: Tafel 8.7 Vulnerabilität der Grundwasservorkommen

en: Plate 8.7 Vulnerability of Groundwater Ressources

it: Tavola 8.7 Vulnerabilità delle riserve idriche sotterranee


schutzinventar-landschaft

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: schutzinventar-landschaft

fr: geocat.ch permalien

en: geocat.ch permalink

it: geocat.ch link permanente

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: Der Datensatz zeigt die schutzwürdigen Landschaften. Das Kantonale Schutzinventar hat gemäss kNHG Art. 17 hinweisenden Charakter. Es ist nicht abschliessend und wird laufend nachgeführt. Für die vollständige Anzeige des Schutzinventars müssen noch die beiden Layer "Schutzinventar: Kultur" und "Schutzinventar: Natur" dazugeladen werden. Link zu den Inventarlisten des Kantons Uri

fr: Amt für Raumentwicklung Kt. Uri

de: Amt für Raumentwicklung Kt. Uri

en: Amt für Raumentwicklung Kt. Uri

it: Amt für Raumentwicklung Kt. Uri

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

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

fr: Schutzinventar Landschaft

de: Schutzinventar Landschaft

en: Schutzinventar Landschaft

it: Schutzinventar Landschaft


gemeindestrassenplan-genehmigt

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: gemeindestrassenplan-genehmigt

fr: Gemeindestrassenplan gemäss dem Strassengesetz (StrG) Artikel 17. Beinhaltet die Nationalstrassen, Kantonstrassen, Gemeindestrassen, Korporationsstrassen, Privatstrassen. Noch nicht genehmigte Gemeinden sind farblich markiert und werden nach der Genehmigung freigeschalten.

fr: Gemeinden des Kt. Uri

de: Gemeinden des Kt. Uri

en: Gemeinden des Kt. Uri

it: Gemeinden des Kt. Uri

fr: Gemeindestrassenplan (genehmigt)

de: Gemeindestrassenplan (genehmigt)

en: Gemeindestrassenplan (genehmigt)

it: Gemeindestrassenplan (genehmigt)


gerichtsbezirke

title_for_slug: gerichtsbezirke

de: geocat.ch Permalink

fr: Zuständigkeitsgebiete der Gerichte im Kanton Uri

fr: Justizdirektion Kt. Uri

de: Justizdirektion Kt. Uri

en: Justizdirektion Kt. Uri

it: Justizdirektion Kt. Uri

fr: Gerichtsbezirke

de: Gerichtsbezirke

en: Gerichtsbezirke

it: Gerichtsbezirke


waldabstandslinien-ur

title_for_slug: waldabstandslinien-ur

de: waldabstand baulinie geobasisdaten

fr: Mit Waldabstandslinien wird im Nutzungsplan der Waldabstand gegenüber der festgelegten Waldgrenze, in Abweichung zum generellen Waldabstand von 20 Metern gemäss Artikel 93 Absatz 1 des Planungs- und Baugesetzes (PBG; RB 40.1111), festgelegt. Sie entsprechen einer Baulinie Wald gemäss Artikel 48 Absatz 2 PBG.

fr: Waldabstandslinien (UR)

de: Waldabstandslinien (UR)

en: Waldabstandslinien (UR)

it: Waldabstandslinien (UR)


regi

fr: Régions et villes

de: baulinie eigentumsbeschrankungoreb grundeigentum strasse

de: Datenshop

de: Produktansicht Geodatenshop

de: Der Datensatz der Baulinien Nationalstrassen enthält die Informationen über die Lage und den Genehmigungstand der Baulinien entlang den Nationalstrassen.

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.

de: Baulinien Nationalstrassen


de: Regionen und Städte

envi

fr: Environnement

de: Umwelt

de: artenschutz biodiversitat lebensraum naturschutz

fr: geocat.ch permalien

de: Landwirtschaftliche Vernetzungsprojekte zur Erhaltung und Förderung der natürlichen Artenvielfalt auf der landwirtschaftlichen Nutzfläche.

de: Ökologische Vernetzungsprojekte


maintainer: ERNEUERBARE ENERGIEN

de: Bundesamt für Energie

en: Swiss Federal Office of Energy

fr: Office fédéral de l'énergie

it: Ufficio federale dell'energia

fr: prix de marché trimestriels pour la prime flottante

de: Vierteljahrige Referenz-Marktpreis gleitende Marktprämie

media_type: application/xml

fr: Données trimestrielles  du prix de référence pour la prime de marché flottante

format: XML

fr: prix de marché mensuels pour la prime flottante

de: Monatliche Referenz-Marktpreis gleitende Marktprämie

fr: Données mensuelles du prix de référence pour la prime de marché flottante

de: Vierteljahrliche Referenz-Marktpreis gleitende Marktprämie

fr: Données mensuelle du prix de référence pour la prime de marché flottante

fr:
Les prix du marché de référence sont déterminants pour fixer la prime de marché flottante, soit
la différence entre le taux de rétribution et le prix de marché de référence. Le prix de marché de
référence pour la prime de marché flottante correspond au prix de marché de référence visé à
l’art. 15 OEneR, auquel s’ajoute un prix pour les garanties d’origine.
Le prix des garanties d'origine pour les installations photovoltaïques participant au système de
la prime de marché flottante est calculé sur la base des prix payés en moyenne par les
gestionnaires de réseau durant l'année précédente en Suisse pour des garanties d'origine
concernant des installations photovoltaïques. L'OFEN fixe le prix pour toute l'année en cours.
Le prix des garanties d’origine pour les installations hydroélectriques, pour les installations de
biomasse et pour les installations éoliennes est calculé sur la base d’un pourcentage du prix de
marché de référence visé à l’art. 15 OEneR. Le pourcentage est de:
pour les installations hydroélectriques: 5 %,
pour les installations de biomasse et éoliennes: 10 %.
Les prix s’entendent hors taxe sur la valeur ajoutée.

de:
Die Referenz-Marktpreise sind massgebend für die Festlegung der gleitenden Marktprämie
als Differenz zwischen Vergütungssatz und Referenz-Marktpreis. Der Referenz-Marktpreis für
die gleitende Marktprämie entspricht dem Referenz-Marktpreis nach Artikel 15 EnFV,
zuzüglich eines Preises für die Herkunftsnachweise.
Der Preis für die Herkunftsnachweise für Photovoltaikanlagen in der gleitenden Marktprämie
wird jeweils anhand der Preise, die in der Schweiz im Vorjahr für Herkunftsnachweise für
Photovoltaikanlagen durchschnittlich von den Netzbetreibern bezahlt wurden, berechnet. Das
BFE setzt den Preis für das ganze laufende Jahr fest.
Der Preis für die Herkunftsnachweise für Wasserkraft-, Biomasse- und Windenergieanlagen
wird anhand eines Prozentsatzes des Referenz-Marktpreises nach Artikel 15 EnFV berechnet.
Der Prozentsatz beträgt:
für Wasserkraftanlagen: 5 Prozent,
für Biomasse- und Windenergieanlagen: 10 Prozent.
Die Preise verstehen sich exklusive Mehrwertsteuer.
Publikation: jeweils in der zweiten Woche nach Quartalsende.

gleitende-marktpramie

display_name: gleitende-marktpramie

premio-di-mercato-fluttuante

display_name: premio-di-mercato-fluttuante

prezzo-di-mercato-di-riferimento

display_name: prezzo-di-mercato-di-riferimento

prime-de-marche-flottante

display_name: prime-de-marche-flottante

prix-de-reference

display_name: prix-de-reference

referenz-marktpreis

display_name: referenz-marktpreis

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

fr: Prix de marché de référence pour la prime de marché flottante selon l’art. 30aquinquies OEneR

de: Referenz-Marktpreise für die gleitende Marktprämie gemäss Art. 30aquinquies EnFV

en: Reference market price for the floating market premium

it: Prezzo di mercato di riferimento per il premio di mercato fluttuante ai sensi dell'articolo 30aquinquies OPEn

fr: Office fédéral de l'énergie (OFEN)

en: Swiss Federal Office of Energy (SFOE)

de: Bundesamt für Energie (BFE)

it: Ufficio federale dell'energia (UFE)

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

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

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

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

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


maintainer: Stefan Klesse

en: wood-anatomy paleoclimate temperature-reconstruction tree-ring mxd

en:
This dataset contains data presented in Figure 2 in the paper "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy".

Sample ID = Sample ID
group = living or relict wood material
Bulk wood density = volumetric measured density (kg / m^3)
Mean Tree Ring Density	= Density derived via X-ray densitometry (kg / m^3)
Cellulose_to_wood ratio = Holo-cellulose-to-wood ratio
Anatomical density = Area of cell wall / (area of cell wall + lumen area)

media_type: text/plain

en: This dataset contains the mean chronologies of MXD and QWA of the relict and living wood material presented in Figure 3. It also contains the JJA temperature record of the Salekhard Meteo station.

format: TXT

en: Data (Quantitative Wood Anatomy, Maximum Latewood Density, Volumetric Density, holo-cellulose-to-wood-ratio) used in the manuscript "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy". Wood samples stem from Larix sibirica collected in the Yamal region, northeastern Siberia, Russia. We investigated wood properties of living trees and subfossil wood buried in riverbank sediments, dated to approximately -2760 to -2600 BCE. Our goal was to evaluate the integrity of climate proxies in sub-fossil wood and develop practical methods to detect wood degradation when reconstructing Late Holocene and Common Era climate conditions using tree-ring data.

mxd

display_name: mxd

paleoclimate

display_name: paleoclimate

temperature-reconstruction

display_name: temperature-reconstruction

tree-ring

display_name: tree-ring

wood-anatomy

display_name: wood-anatomy

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

value: Envidat Harvester

en: Quantitative Wood Anatomy and Maximum Latewood Density from Yamal peninsula


maintainer: EnviDat Support

en: landscape-services switzerland statistical-model land-use-change urbanization modeling land-use

en: Scripts for Assessing potential landscape service trade-offs driven by urbanization in Switzerland

media_type: application/zip

en:
Scripts ordered by their main purpose within sequential folders in this ReadMe marked with

Within the folders the capital letters refer to the parallel or sequential use of the scripts; scripts here in ReadMe are marked with

 00_Function Scripts
 Functions.r
Script containing several functions for analyzing statistical models: cohen.kappa, meva.table, D2, max-Tss, plot-TSS

 Service_functions.R
Script containing functions for calculating all services and returning sums (and median for bd and rec) as well as rasters

 01_Data Preparation
 A_AS_raster_preparation.R
Preparation of the land use rasters for the years 1985, 1997, and 2009 based on the original Arealstatistik (AS/ASCH); Assigning our categories and assining new values to all "construction sites" for calibrating the models
For model projection starting point (2009) and for service calculations (all ASCH years) the "other" categories were assigned to the land use categories based on dominant neighbor, so that there were no empty cells
Creation of water & mountainous area raster that stayed stable throughout the projections
Creation of MFH raster (2009), to have as base for all new projection years, as this category never becames any other

 B_Factors_preparation.R
Preparation of the factor rasters that were used to calculate service values per cell (see Table 2): LWfactor, Transportation, Vol, Rivers, Lakes, slope, TWW, Hazard_risk

 B_Predictors_preparation.R
Preparation of the raster of the predictors used for calibrating (ASCH years) and projecting (stable) the transition models that do not depend on the land use categories: Temperature (ASCH years), solar radiation (stable), Public transportation access (stable), Elevation (stable), Workers density (ASCH years), Population change (ASCH transitions)

 B_Regions_preparation.R
Preparation of bioregions as raster to be used to mask asxxxx later to calculated services and land use area just for one region

 C_Pred_proj.R
Projecting the dynamic predictors into the future for projecting the land use transitions with the model: Linear extrapolations for workers densities and population; more detailed extrapolation of temperature (based on data for all stations that matched between the temp table we used for the calibration period and the projections from CS2M, and then making a spatial interpolation for all years based on the interpolation of temperature for all years per station)

 02_Model calibration
 A_Bioreg_pred_corr.R
Calculating correlation between the predictors for each bioregion and land use category, Output are those with too high correlation so that one predictor can be removed from transitions were both predictors occur

 A_trans_numbers_bioreg.R
Calculate transition numbers for each bioregion to decide which transitions to primarily consider

 B_Bioreg_ext_eval.R
Calculating TSS based on the external evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 85-97, evaluation data: 97-09)

 B_Bioreg_int_eval.R
Calculating TSS based on the internal evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 70%, evaluation data: 30%)

 C_Bioreg_TSS_analysis.R
Extracting TSS numbers from internal and external evaluation, calculating mean and median for each transition for each region for each evaluation method and saving as csv per region to be able to select only the transitions with high enough model performance

 D_Bioreg_Models_for_prediction.R
Calibration of the models that were then used to project land use transitions into the future; calibrated separately for each bioregion

 E_Residuals_trans_models.R
Calculation of Moran's I statistics to analyze the residuals of the land use transition models

 03_Projections
 A_Bioreg_Projections_run.R
Master script for: Extrapolaitng into the future with the regional models and then assembling for each time step to calculate new AS predictors; Several Outputs: txt file to test for NAs in Predictors, txt file with random seed number for sampling, txt file with times for calculation steps (check progress of script while running), csv sheet with projected transition frequencies, tif-rasters for every region and time step, pdf with raster plot for every region and time step

 04_Service calculation
 A_Bioreg_as_services.R
Calculate services per bioregion for years 1985, 1997, 2009

 A_Service_calculation_bioregions.R
Extracting service numbers(sums) per bioregions for all projection runs and storing them in a list of matrixes to be available for further plotting; can be run for swiss wide projections or regional ones

 05_Analysis
 A_Bioreg_ASCH_development.R
Extracting the occurrence of each category per region for all runs (first part), then for ASCH years, and then plotting them nicely; only works for regional projections

 A_Bioreg_Predictors_importanceD2.R
Calculating D2 for each transition and each considered predictor from bivariate models to get value of importance

 B_Bioreg_Pred_imp_analysis.R
Using calculated D2 to sort Predictors according to their importance for each transition

 A_Bioreg_Spatial_results_analysis.R
Plotting randomly sampled runs for ASCH and services to analyses their spatial development

 A_Bioreg_Transition_numbers_check_v1.R
Analyzing the frequency for all transitions for all regions and producing the point plots for each transition separately

 A_Bioreg_Transition_numbers_check_v2.R
Analyzing percentage and numbers of all transitions but plotting them per region and originating ASCH category

 B_Transition_Analysis.R
Further Analysis of transition numbers

 A_Service_analysis.R
Plotting of the service development for bioregions in several ways for analyzing

format: ZIP

mimetype: application/zip

en: Data for Assessing potential landscape service trade-offs driven by urbanization in Switzerland

en:
The provided folder structure follows the set up of the scripts.
Data is only provided when it has been fully produced by us, otherwise dummies are given.
For data that will be produced by one of the scripts, no dummies are given.
The folders may contain sub-folders, which would be filled if the scripts were all run

 00_Analysis_Data
Data produced throughout the process of the calibration and projection that is later needed for analysis

 01_Raw_Data
Primary data from external sources that were used to compile the rasters and numbers used during the calibration and projection of landscape transitions as well as service calculation

 02_Prepared_Data
Data that will be prepared for further use by scripts are put in here
Additionally it contains the parameter sheets for the transition predictors that we compiled

 03_Model_Data
 Model outputs
Folder were the projection models statistics will be saved
 Models
Folder into which the actual transition models will be saved
 Residuals
Folder into which data on models residuals will be saved for future use

 04_Projected_Data
The output of the projections will be saved into this folder

 05_Service_Data
Any service calculations will be saved in here

 06_Results_Analysis
Any Analysis plots and tables as well as intermediate data will be saved here in the respective sub-folder

en:
Data and scripts of publication:

Madleina Gerecke, Oskar Hagen, Janine Bolliger, Anna M. Hersperger, Felix Kienast, Bronwyn Price, Loïc Pellissier (2019) Assessing potential landscape service trade-offs driven by urbanization in Switzerland. Palgrave communications.

Contains land use projections for Switzerland and scripts and data for these projections as well as the calculation of landscape services.

Data Folder:
Contains sub-folder with the data necessary for this study (provided were no copyright issues, otherwise placeholders with descriptions), and folders where produced data may be stored

Scripts Folder:
Contains scripts organized into subfolders depending on their purpose

Note: Some abbreviations within the scripts and data are derived from German words and not English.

land-use

display_name: land-use

land-use-change

display_name: land-use-change

landscape-services

display_name: landscape-services

modeling

display_name: modeling

statistical-model

display_name: statistical-model

switzerland

display_name: switzerland

urbanization

display_name: urbanization

en: Land use projections and services for Switzerland


en: model-validation-data model-calibration-data snow-water-equivalent snow-depth snow-density

en: swe2hs calibration and validation data

en:
 Contents of this archive

 README.md

 A readme file containing a description of the other files.

 automatic_stations_validation_data.csv

 Daily data from the automatic weather stations used for validation.

 Data sources and providers are listed in the SWE2HS paper, Table 1.

 Columns:

  * date: timestamp of the format YYYY-MM-DD
  * HS_[m]: snow depth in [m]
  * SWE_[m]: snow water equivalent in [m]
  * site_id: code for the measurement site
  - HS_interpolated: boolean flag for interpolated values
  - SWE_interpolated: : boolean flag for interpolated values

 coordinates_swe2hs_paper_stations.csv

 Coordinates of all measurement sites used in the SWE2HS paper.

 Columns:

  * site_id: code for the measurement site
  * location_name: location name of the measurement site
  * lon_[wgs84]: longitude in WGS84
  * lat_[wgs84]: latitude in WGS84
  * elevation_[m]: atitude of the measurement site in [m]
  * dataset: dataset in which the station is included

 manual_station_calibration_data.csv

 Calibration data from the Swiss manual observer stations. Long station records
 trmmed to 15 random water-years.

 Columns:

  * date: timestamp of the format YYYY-MM-DD
  * HS_[m]: snow depth in [m]
  * SWE_[m]: snow water equivalent in [m]
  * SWE_from_profile_[m]: biweekly measurement from the SWE in the measurement
   pit. Corrected with the bulk density in order to match the snow depth from
   the measurement stake. Please refer to the paper for further details.
  * site_id: code for the measurement site

 manual_stations_validation_data.csv

 Validation data from the Swiss manual observer stations. Remaining water-years
 from the long sttaion record not used for the calibration data.

 Columns:

  * date: timestamp of the format YYYY-MM-DD
  * HS_[m]: snow depth in [m]
  * SWE_[m]: snow water equivalent in [m]
  * SWE_from_profile_[m]: biweekly measurement from the SWE in the measurement
   pit. Corrected with the bulk density in order to match the snow depth from
   the measurement stake. Please refer to the paper for further details.
  * site_id: code for the measurement site

 manual_stations_used_deltasnow_parameters.csv

 Site specific DeltaSNOW model parameters used for the calculation of the daily
 SWE series in 'manual_stations_calibration_data.csv' and
 'manual_stations_validation_data.csv'.

 Parameters were optimized by reducing RMSE to the biweekly snow pit SWE measurements.
 Please refer to the paper for further details.

 A python implementation of the DeltaSNOW model was used for the calculation:
 pydeltasnow (https://pypi.org/project/pydeltasnow/)

 For a detailed description of the DeltaSNOW model parameters please see the
 respective publication:

 Winkler, M., Schellander, H., & Gruber, S. (2021). Snow water equivalents
 exclusively from snow depths and their temporal changes: the Δ snow model.
 Hydrology and Earth System Sciences, 25(3), 1165-1187.

 Columns:

  * site_id: code for the measurement site
  * rho_max: Maximum density of an individual snow layer produced by the DeltaSNOW model in [kg/m3]
  * rho_null: Fresh snow density for a newly created layer [kg/m3
  * c_ov: Overburden factor due to fresh snow [-]
  * k_ov: Defines the impact of the individual layer density on the compaction due to overburden [-]
  * k: Exponent of the exponential-law compaction [m3/kg]
  * tau: Uncertainty bound [m]
  * eta_null: Effective compactive viscosity of snow for “zero-density” [Pa s]

en:
The data in this repository was used for the calibration and validation of the
SWE2HS model in the following publication:
Aschauer, J., Michel, A., Jonas, T., & Marty, C. (2023). An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0. Geoscientific Model Development Discussions, 1-19. https://doi.org/10.5194/gmd-2022-258
Contains daily snow water equivalent and snow depth timeseries from stations in the European Alps.

model-calibration-data

display_name: model-calibration-data

model-validation-data

display_name: model-validation-data

snow-density

display_name: snow-density

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent

en: SWE2HS model calibration and validation data


irkis-soil-moisture-measurements-davos

maintainer: Nander Wever

title_for_slug: irkis-soil-moisture-measurements-davos

en: meteo-station soil-moisture dischma-catchment meteorological-measurements davos

en: IRKIS soil moisture data (zip file)

en: Compressed archive (zip) containing soil moisture measurements, as well as meteorological measurements and interpolated meteorological time series.

en:
Meteorological and soil moisture measurements from soil moisture stations installed from October 2010 - October 2013 in the area surrounding Davos, in particular in the Dischma catchment.

There are in total 7 stations: 1202, 1203, 1204, 1205, 222, 333 and SLF2. For each of the stations, there is a:

* vwc_[stn].smet: containing the soil moisture measurements

* station_[stn].smet: in-situ measured meteorlogical parameters. Note, the quality of these measurements for stations 1202, 1203, 1204 and 1205 is very low, with data gaps. Use this data with care. For stations 222, 333 and SLF2, data quality is high and only the default cautiousness should be applied.

* interpolatedmeteo_[stn].smet contains per stations a dataset derived by interpolating from several stations in the Davos area to the stations location. This dataset was generated from the output of the Alpine3D model, of which simulations are presented in the Wever et al. (2017) manuscript.

At the soil moisture measurement sites, Decagon 10HS sensors were installed, at 10, 30, 50, 80 and 120 cm depth. Per depth 2 sensors were installed, labelled A and B in the datafiles. Note that at stations 1203, 1204 and 1205, sensors were only installed at 10, 30 and 50 cm depth.

The files follow the SMET format: https://models.slf.ch/docserver/meteoio/SMET_specifications.pdf and metadata for the stations can be found in the header of the smet files.

Please cite the Wever et al. (2017) reference when using this data in publications.

For a more detailed description, please refer to: Wever, N., Comola, F., Bavay, M., and Lehning, M.: Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment, Hydrol. Earth Syst. Sci., 21, 4053-4071, https://doi.org/10.5194/hess-21-4053-2017, 2017.

davos

display_name: davos

dischma-catchment

display_name: dischma-catchment

meteo-station

display_name: meteo-station

meteorological-measurements

display_name: meteorological-measurements

soil-moisture

display_name: soil-moisture

en: IRKIS Soil moisture measurements Davos


disdrometer-data-davos-wolfgang

title_for_slug: disdrometer-data-davos-wolfgang

en: disdrometer fall-velocity raclets davos precipitation

en: Disdrometer Data Davos Wolfgang

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

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

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

disdrometer

display_name: disdrometer

fall-velocity

display_name: fall-velocity

precipitation

display_name: precipitation

raclets

display_name: raclets

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.


dischmex-meteorological-measurements

maintainer: Rebecca Mott

title_for_slug: dischmex-meteorological-measurements

en: meteorological-data meteo-station meteorological-measurements dischmex dischma

en: Meteorological measurement 2015

en: Overview sensors

format: XLS

en: data

media_type: application/pdf

en: Location of the meteorological stations

mimetype: application/pdf

en: Meteorological measurement 2014

en: Meteorological measurements 2014

en: Meteorological measurements 2016

en:
Meteorological measurements recorded in the Dischma valley from 2014-2016. In 2014 and 2015 we used 11 mobile weather stations from sensorscope to record meteorological parameter in the upper Dischma valley in the closer surroundings of the Gletschboden area. The meteorological stations are eqiupped with at least air temperature/humidity, wind velocity and wind direction sensors. Some stations are additionally equipped with precipitation, shortwave radiation and snow surface temperature sensors.
Three transects were installed at different aspects and were equipped with air temperature/humidity and wind sensors. Transect 1 (stations 2-4) provides meteorological Information on an east-north-east facing slope at elevations ranging between 2100 m and 2500 m. Transect 2 (stations 5-7) provides meteorological Information on a south-west slope and transect 3 (stations 8-10) on a north-west slope. Station 1 is fully equipped with meteorological sensors (temperature/humidity, wind, IR, up and downwand shortwave radiation and precipitation).
In 2016, mobile stations from sensorscope were replaced with six permanent meteorological stations. Meteorological stations 1-3 are equipped with an air temperature/humidity sensor, two wind speed sensors, a wind direction sensor and an incoming and outgoing shortwave radiation sensor. Stations 4 and 6 are equipped with an air temperature/humidity sensor and a wind speed/direction sensor. Station 5 is a equipped with an air temperature/humidity sensor, a wind speed/direction sensor, a snow surface temperature sensor, an incoming and outgoing shortwave radiation sensor and an incoming longwave radiation sensor.

dischma

display_name: dischma

dischmex

display_name: dischmex

meteorological-data

display_name: meteorological-data

en: DISCHMEX - Meteorological measurements


backward-trajectories

maintainer: Michael Sprenger

title_for_slug: backward-trajectories

en: complex-topopgraphy atmospheric-dynamics alps lagrangian-analysis backward-trajectories cosmo raclets

en: Backward Trajectories

en: The trajectories are started from surface up to 5000 m altitude, with an equidistant vertical spacing of 200 m, and calculated 120 h backward in time. As long as the trajectories stay in the COSMO1 domain (essentially the Alpine region), as run operationally at MeteoSwiss, the COSMO analysis wind fields are used. When the trajectories leave this domain, they are extended further backward in time based on ECMWF analysis data. The following fields are traced along the trajectories: longitude, latitude, geopotential height, pressure, specific humidity, temperature and surface topography. Furthermore, it is indicated for each trajectory time instance on which model data, COSMO or ECMWF, the trajectory time is based. Finally, the trajectories are started every hour in the specified time period, and positions and fields are available every 10 min. Each day is saved as a separate file. The last 8 digits of the file names indicate the starting date of the trajectories.

en: Backward trajectories were calculated from two positions: Davos Wolfgang (LON: 9.85361, LAT: 46.83551) and Weissfluhjoch (LON: 9.80646 LAT: 46.83304) for the time period February 2 until March 27 2019 using COSMO or ECMWF, respectively.

alps

display_name: alps

atmospheric-dynamics

display_name: atmospheric-dynamics

backward-trajectories

display_name: backward-trajectories

complex-topopgraphy

display_name: complex-topopgraphy

cosmo

display_name: cosmo

lagrangian-analysis

display_name: lagrangian-analysis

en: Backward  Trajectories


en: radar illgraben pulse-doppler analysis debris-flow 3d-lidar

en: LiDAR and PD radar data as well as camera videos of the 30 June 2022 debris flow at the Illgraben (Switzerland).

analysis

display_name: analysis

debris-flow

display_name: debris-flow

illgraben

display_name: illgraben

pulse-doppler

display_name: pulse-doppler

radar

display_name: radar

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Dataset for "Sorting and Surging 3D LiDAR and Pulse-Doppler Radar Analysis of a Natural Debris Flow"


maintainer: Valentina Vitali

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

en: Read me file.docx

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

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

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

dendrochronology

display_name: dendrochronology

isotopes

display_name: isotopes

pfynwald

display_name: pfynwald

pinus-sylvestris

display_name: pinus-sylvestris

scots-pine

display_name: scots-pine

tree-ring-cellulose

display_name: tree-ring-cellulose

tree-rings

display_name: tree-rings

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: Pfynwald 2019 - Dendrochronological and tree-ring isotope dataset


maintainer: Mountain Hydrology and Mass Movements

en: earthquake-fatalities debris-flow-fatalities rockfall-fatalities windstorm-fatalities lightning-fatalities flood-fatalities natural-hazard-fatalities landslide-fatalities ice-avalanche-fatalities

en: Natural hazard fatalities per year in Swizterland since 1946.

mimetype: text/csv

en:
This dataset contains the number of fatalities due to flood, debris flow, landslide, rockfall, windstorm, lightning, ice avalanche, earthquake and other processes like roof avalanche or lacustrine tsunami for each year since 1946.
The following information is contained (by column and column title):

* year
* total number of hazard fatalities
* number of fatalities by flood (German: Hochwasser, Überschwemmung). Flood includes people drowned in flooded or inundated areas or carried away in streams under high-water conditions.
* number of fatalities by debris flow (German: Murgang).
* number of fatalities by landslide (German: Erdrutsch). Landslide includes people killed by landslides and hillslope debris flows (German: Hangmure).
* number of fatalities by rockfall (German: Steinschlag, Fels- und Bergsturz).
* number of fatalities by windstorm (German: Sturm). Windstorm includes people killed by falling objects or trees during very strong wind conditions and people who drowned in lakes because their boat capsized during such conditions.
* number of fatalities by lightning (German: Blitz).
* number of fatalities by ice avalanche (German: Eislawine).
* number of fatalities by earthquake (German: Erdbeben).
* number of fatalities by other processes like roof avalanche, lacustrine tsunami (German: andere Prozesse wie Dachlawine, Tsunami im See).

The data was collected based on newspaper research. For more information please refer to

_Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747-2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016._

The data collection is financed by the FOEN (with exception of the collection of the avalanche fatalities). The data contains the official statistics of the FOEN on fatalities due to flood, debris flow, landslide, rock fall and avalanche.

Restrictions: The data set is not complete. Only fatalities in or around settlements and on open transportation routes are included. More precisely, fatalities were not collected, when persons exposed themselves to a great danger on purpose. Or fatalities during leisure activities which are connected to a higher risk were not included (this includes e.g. canoeing or river surfing during flood, canyoning, mountaineering, climbing, walking or driving on a closed road).

Fatalities by avalanches are collected at the WSL Institute for Snow and Avalanche Research SLF. You can download the avalanche fatalities per hydrological year [here](https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936) and per calendar year [here](https://www.envidat.ch/dataset/avalanche-fatalities-per-calendar-year-since-1936). For a direct comparison with the fatalities presented here, please download the data set with the calendar years and do not consider fatalities in the backcountry (tour) or in terrain close to ski areas (offpiste).

debris-flow-fatalities

display_name: debris-flow-fatalities

earthquake-fatalities

display_name: earthquake-fatalities

flood-fatalities

display_name: flood-fatalities

ice-avalanche-fatalities

display_name: ice-avalanche-fatalities

landslide-fatalities

display_name: landslide-fatalities

lightning-fatalities

display_name: lightning-fatalities

natural-hazard-fatalities

display_name: natural-hazard-fatalities

rockfall-fatalities

display_name: rockfall-fatalities

windstorm-fatalities

display_name: windstorm-fatalities

en: Number of natural hazard fatalities per year in Switzerland since 1946


urban-birds-point-counts-data

title_for_slug: urban-birds-point-counts-data

en: biodiversity environmental-gradients spatially-distributed-sampling birds urban periurban

en:
The study area included the cities of Basel, Lugano and Zurich. The sampling design reflected four main city districts related to four categories of tree cover (Figure 1): 1) industrial/commercial areas, 0-20% tree cover; 2) residential areas, 20-40% tree cover; 3) urban parks and cemeteries, 40-60% tree cover; 4) peri-urban forests (natural/semi-natural forests), 60-100% tree cover. The tree cover gradient was evaluated across a square grid with a square side length of 100 m. For each square, we evaluated the area covered by urban trees using the Urban Atlas Street Tree Layer 2018 (European Union’s Copernicus Land Monitoring Service information, 2021).
In each city, we established eight transects of 1.2 km, two for each tree cover category. Transects crossed contiguous grid squares belonging to the same tree cover categories as much as possible. We performed aural-visual point counts of birds every 200 m along each transect (six points per transect) during the breeding season (April-June 2024) (Bibby et al., 2000). The transects were walked at the time of highest activity of birds, which is from thirty minutes after sunrise until 4 hours later. Each transect was walked twice, 20-60 days apart, to account for imperfect detection of birds and sample completeness (Balestrieri et al., 2017; Kéry et al., 2005).

biodiversity

display_name: biodiversity

birds

display_name: birds

environmental-gradients

display_name: environmental-gradients

periurban

display_name: periurban

spatially-distributed-sampling

display_name: spatially-distributed-sampling

urban

display_name: urban

en: Urban birds point counts data


maintainer: Benjamin Reuter

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

en: 1999-2017 Avalanche problem types from SNOWPACK

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

en: 1999-2017 Avalanche problem types from Crocus

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

en: 2015-2016 Avalanche problem types from SNOWPACK

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

en: 2015-2016 Avalanche problem types from Crocus

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

en: 2015-2016 Seismic avalanche acitivity catalogue

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

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

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

avalanche-danger

display_name: avalanche-danger

avalanche-problem-type

display_name: avalanche-problem-type

crocus

display_name: crocus

snow

display_name: snow

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability

snowpack

display_name: snowpack

weissfluhjoch

display_name: weissfluhjoch

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


en: research-data-management gridded-data core time-series geodata video-encoding raster sentinel-2

en: View publication in the Digital Object Repository at WSL (DORA)

media_type: text/html

en: Disclaimer: provided for the Geomatics peer review in 2021 and left as additional information for the dataset. Software dependencies and libraries, as well as cloud storage paths, may change over time (after 2021).

en: CORE Dataset (80 GB)

en:
Acknowledgements: The CORE format was proudly inspired by the Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) format, by considering how to leverage the ability of clients issuing HTTP GET range requests for a time-series of remote sensing and aerial imagery (instead of just one image).

License: The Cloud Optimized Raster Encoding (CORE) specifications are released to the public domain under a Creative Commons 1.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

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

Summary:
The Cloud Optimized Raster Encoding (CORE) format is being developed for the efficient storage and management of gridded data by applying video encoding algorithms. It is mainly designed for the exchange and preservation of large time series data in environmental data repositories, while in the same time enabling more efficient workflows on the cloud. It can be applied to any large number of similar (in pixel size and image dimensions) raster data layers. CORE is not designed to replace COG but to work together with COG for a collection of many layers (e.g. by offering a fast preview of layers when switching between layers of a time series).

WARNING: Currently only applicable to RGB/Byte imagery. The final CORE specifications may probably be very different from what is written herein or CORE may not ever become productive due to a myriad of reasons (see also 'Major issues to be solved').

With this early public sharing of the format we explicitly support the Open Science agenda, which implies "shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process" (quote from: European Commission, Directorate General for Research and Innovation, 2016. Open innovation, open science, open to the world).

CORE Specifications:

1) a MP4 or WebM video digital multimedia container format (or any future video container playable as HTML video in major browsers)

2) a free to use or open video compression codec such as H.264, VP9, or AV1 (or any future video codec that is open sourced or free to use for end users)

Note: H.264 is currently recommended because of the wide usage with support in all major browsers, fast encoding due to acceleration in hardware (which is currently not the case for AV1 or VP9) and the fact that MPEG LA has allowed the free use for streaming video that is free to the end users. However, please note that H.264 is restricted by patents and its use in proprietary or commercial software requires the payment of royalties to [MPEG LA](https://www.mpegla.com/programs/avc-h-264/). However, when AV1 matures and accelerated hardware encoding becomes available, AV1 is expected to offer 30% to 50% smaller file size in comparison with H.264, while retaining the [same quality](https://trac.ffmpeg.org/wiki/Encode/AV1).

3) the encoding frame rate should be of one frame per second (fps) with each layer segmented in internal tiles, similar to COG, ordered by the main use case when accessing the data: either layer contiguous or tile contiguous;

Note: The internal tile arrangement should support an easy navigation inside the CORE video format, depending on the use case.

4) a CORE file is optimised for streaming with the moov atom at the beginning of the file (e.g. with -movflags faststart) and optional additional optimisations depending on the codec used (e.g. -tune fastdecode -tune zerolatency for H.264)

5) metadata tags inside the moov atom for describing and using geographic image data (that are preferably compatible with the [OGC GeoTIFF standard](https://www.ogc.org/standards/geotiff) or any future standard accepted by the geospatial community) as well as list of original file names corresponding to each CORE layer

6) it needs to encode similar source rasters (such as time series of rasters with the same extent and resolution, or different tiles of the same product; each input raster should be having the same image and pixel size)

7) it provides a mechanism for addressing and requesting overviews (lower resolution data) for a fast display in web browser depending on the map scale (currently external overviews)

Major issues to be solved:

- Internal overviews (similar to COG), by chaining lower resolution videos in the same MP4 container for fast access to overviews first); Currently, overviews are kept as separate files, as external overviews.

- Metadata encoding (how to best encode spatial extent, layer names, and so on, for each of the layer inside the series, which may have a different geographical extent, etc...; Known issues: adding too many tags with FFmpeg which are not part of the standard MP4 moov atom; metadata tags have a limited string length.

- Applicability beyond RGB/Byte datasets; defining a standard way of converting cell values from Int16/UInt16/UInt32/Int32/Float32/Float64/ data types into multi-band Byte values (and reconstructing them back to the original data type within acceptable thresholds)

Example

Notice: The provided CORE (.mp4) examples contain modified Copernicus Sentinel data [2018-2021].

For generating the CORE examples provided, 50 original Sentinel 2 (S-2) TCI data images from an area located inside Switzerland were downloaded from www.copernicus.eu, and then transformed into CORE format using ffmpeg with H.264 encoding using the [x264 library](https://www.videolan.org/developers/x264.html).

DISCLAIMER: Basic scripts are provided for the Geomatics peer review (in 2021) and kept as additional information for the dataset. Nevertheless, please note that software dependencies and libraries, as well as cloud storage paths, may quickly become deprecated over time (after 2021). For compatibility, stable dependencies and libraries released around 2020 should be used.

core

display_name: core

geodata

display_name: geodata

gridded-data

display_name: gridded-data

raster

display_name: raster

research-data-management

display_name: research-data-management

time-series

display_name: time-series

video-encoding

display_name: video-encoding

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.


maintainer: Matthias Haeni

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

en: Field station data (ISF)

en: Data file.

en: Site photo of the forest station (ISB)

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

mimetype: image/jpeg

en: Site aerial photo (Isone)

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

en: Data plot of the forest station (ISB)

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

en: Data plot of the field station (ISF)

en: Forest station data (ISB)

en: Site photo of the field station (ISF)

en: Site photo of the field station from the side.

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 Isone in Switzerland where one station is located within a natural broad-leaved forest stand (ISB) with European beech (_Fagus sylvatica_; 70-100 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, ISF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Isone 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: Isone, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


en: snow-depth uas swe remote-sensing snow

en: HS map Brämabül, 14. April 2015

media_type: image/tiff

en:
10 cm resolution
15 cm accuracy

format: TIFF

mimetype: image/tiff

en: .tfw file

en: coordinates for the .tif raster

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

A detailed description is given here:

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

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

remote-sensing

display_name: remote-sensing

snow

display_name: snow

snow-depth

display_name: snow-depth

swe

display_name: swe

uas

display_name: uas

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: UAS based snow depth maps Brämabüel, Davos, CH


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

en: README

mimetype: text/plain

en: WFJ_ICE_LAYERS dataset

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

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


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

en: Site photo of the forest station (BTB)

en: Site photo of the forest station from the side.

en: Site aerial photo (Bettlachstock)

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

en: Data plot of the field station (BTF)

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

en: Site photo of the field station (BTF)

en: Site photo of the field station from the side.

en: Data plot of the forest station (BTB)

en: Data file.

en: Field station data (BTF)

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 Bettlachstock in Switzerland where one station is located within a natural mixed forest stand (BTB) with European beech (_Fagus sylvatica_; 170-190 yrs), European silver fir (_Abies alba_; 190 yrs) and Norway spruce (_Picea abies_; 200 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Bettlachstock 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

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


maintainer: Lyu

en: fagales species-range-map species-occurrence pinales species-richness species-distribution-model

en: Occurrence maps for species of Fagales and Pinales with few records

en: Point_buffer.zip includes 267 occurrence maps of species that do not have enough occurrence data for polygon mapping.

en: Species range maps of species in Fagales and Pinales (with enough occurrences)

en: species_map.zip includes species 1690 range maps generated based on the integrated method described in Lyu et al., (2022). File names with (polygon) indicate that this map is only generated by polygon mapping, as there are not enough occurrences for SDMs.

en:
This database contains 1957 distribution maps of species from Fagales and Pinales constructed based on a method integrating polygon mapping and SDMs (Lyu et al., 2022).
To construct the maps, we first collected occurrence data from 48 different sources. According to the number of occurrences after data cleaning, three kinds of maps are constructed: (1) For species with more than 20 occurrences, we performed SDM and polygon mapping described in Lyu et al. (2022) and select the integration of the two layers as the distribution range; (2) For species with more than 4 but less than 20 occurrences, we only use polygon mapping to draw the distribution range; (3) For species with less than 4 occurrences, a 20-km buffer was generated around the occurrences as the distribution range. The maps were manually checked and evaluated (see Note S3 and Table S9 in Lyu et al., 2022 for details).

fagales

display_name: fagales

pinales

display_name: pinales

species-distribution-model

display_name: species-distribution-model

species-occurrence

display_name: species-occurrence

species-range-map

display_name: species-range-map

species-richness

display_name: species-richness

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Species distribution maps of Fagales and Pinales (GDPlants)


en: review switzerland bioenergy manure biogas

en: Production de biogaz à partir d’engrais de ferme en Suisse

en: L'objectif de ce livre blanc est de fournir aux décideurs, aux administrations et aux parties prenantes les résultats de recherche les plus récents afin de promouvoir l'utilisation optimale de la bioénergie issue des engrais de ferme dans la transition énergétique suisse. A cette fin, les résultats du centre de compétence suisse pour la recherche en bioénergie - SCCER BIOSWEET - sont résumés et présentés dans un contexte plus large. Si rien d'autre n'est mentionné, les résultats se réfèrent à la Suisse et, dans le cas de la matière première, aux potentiels nationaux de biomasse.

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland

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


maintainer: Frank Techel

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

en: Rutschblock data (Switzerland)

en: ECT data (Norway, Switzerland)

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

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

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

avalanche-danger

display_name: avalanche-danger

avalanche-observations

display_name: avalanche-observations

extended-column-test

display_name: extended-column-test

norway

display_name: norway

rutschblock-test

display_name: rutschblock-test

en: Stability tests, avalanche observations, Switzerland, Norway


maintainer: Yohann Chauvier

en: hard-limit gbif taxonomy landsca filtering large-scale ecoregions r-package range-maps conservation accepted-name species-observations occurrence-records synonyms species-distribution flags

en: wsl.gbif R package version 0.1 (deprecated)

en: Test version, not to be used.

en: gbif.range R package version 0.2 (deprecated)

en: gbif.range R package version 1.1 (current)

en: GitHub URL

en: Although species range may be obtained using expert maps or modeling methods, expert data is often species-limited and statistical models need more technical expertise as well as many species observations. When unavailable, such information may be extracted from the Global Biodiversity Information facility (GBIF), the largest public data repository inventorying georeferenced species observations worldwide. However, retrieving GBIF records at large scale may be tedious if users are unaware of specific tools and functions that need to be employed. Here we present *gbif.range*, an R library that contains automated methods to generate species range maps from scratch using in-house ecoregions shapefiles and an easy-to-use GBIF download wrapper. Finally, this library also offers a set of additional very useful parameters and functions for large GBIF datasets (generate doi, extract GBIF taxonomy, records filtering...). [gbif.range R project](https://github.com/8Ginette8/gbif.range)

accepted-name

display_name: accepted-name

conservation

display_name: conservation

ecoregions

display_name: ecoregions

filtering

display_name: filtering

flags

display_name: flags

gbif

display_name: gbif

hard-limit

display_name: hard-limit

landsca

display_name: landsca

large-scale

display_name: large-scale

occurrence-records

display_name: occurrence-records

r-package

display_name: r-package

range-maps

display_name: range-maps

species-distribution

display_name: species-distribution

species-observations

display_name: species-observations

synonyms

display_name: synonyms

taxonomy

display_name: taxonomy

en: gbif.range - An R package to generate species range maps based on ecoregions and a user-friendly GBIF wrapper