culture

fr: Culture, médias, société de l'information, sport

it: Cultura, media, società dell'informazione, sport

fr: Energie

de: Energie

it: Energia

fr: Map (Preview) Géoportail thématique - map.energie.admin.ch

de: Map (Preview) Fachportal - map.energie.admin.ch

it: Map (Preview) Geoportale tematico - map.energie.admin.ch

de: Fachportal - map.energie.admin.ch

en: Thematic geoportal - map.energie.admin.ch

de: swisstopo REST API

fr: La biomasse est une ressource renouvelable pour l'énergie qui peut être transformée en plusieurs formes d'énergie : chaleur, électricité, biogaz ou combustibles liquides. La biomasse est principalement stockable et peut donc être utilisée pour compenser les fluctuations de la production d'énergie éolienne et solaire. Les types de biomasse ligneuse ont été étudiés à l'aide d'approches méthodique comparables : bois de forêt, bois usagé, sous-produits ligneux et bois récolté hors forêt.Dans le cadre de la mise en oeuvre de la stratégie énergétique 2050, le gouvernement suisse prévoit une augmentation massive de la part des énergies renouvelables. Le Centre de compétences suisse pour la recherche énergétique (SCCER) Biosweet (Biomass for Swiss Energy Future) cherche des solutions aux défis techniques, sociaux et politiques que pose la transition énergétique dans le domaine de la biomasse. L'institut fédéral de recherches sur la forêt, la neige et le paysage (WSL) a quantifié et localisé le potentiel d'importantes ressources de biomasse en Suisse, notamment en ce qui concerne leur disponibilité pour une exploitation durable. Les résultats sont utiles pour (i) optimiser les processus de conversion afin de tenir compte des développements technologiques et (ii) identifier les voies prometteuses d'utilisation de la biomasse et les meilleurs sites pour leur mise en œuvre. Les données (https://www.envidat.ch/dataset/swiss-biomass-potentials) et un rapport détaillé sont disponibles en ligne (https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A13277/datastream/PDF/Thees-2017-Biomassepotenziale_der_Schweiz_f%C3%BCr_die-%28published_version%29.pdf). Cette carte montre le potentiel durable (quantité maximale de biomasse produite au niveau national qui pourrait être utilisée, après déduction des contraintes écologiques, économiques, juridiques et politiques) de la biomasse ligneuse pour la bioénergie en Suisse au niveau communal en énergie primaire (quantité maximale d'énergie disponible dans une ressource sans conversion) en terajoules.

de: Biomasse ist eine erneuerbare Energiequelle, die in verschiedene Energieformen umgewandelt werden kann: Wärme, Strom, Biogas oder flüssige Treibstoffe. Biomasse ist meist speicherbar und kann daher verwendet werden, um die schwankende Energieproduktion von Wind und Sonne auszugleichen. Verholzte Arten von Biomassen wurden mit methodisch vergleichbaren Ansätzen untersucht: Waldholz, Flurholz, Restholz und Altholz.Im Rahmen der Umsetzung der Energiestrategie 2050 sieht die Schweizer Regierung eine massive Erhöhung des Anteils der erneuerbaren Energien vor. Das Schweizerische Kompetenzzentrum für Energieforschung (SCCER) Biosweet (Biomass for Swiss Energy Future) sucht nach Lösungen für die technischen, sozialen und politischen Herausforderungen des Energiewandels im Bereich Biomasse. Die Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft WSL hat das Potenzial wichtiger Biomasse-Ressourcen in der Schweiz quantifiziert und lokalisiert, insbesondere im Hinblick auf ihre nachhaltige Verfügbarkeit. Die Ergebnisse dienen als Grundlage für (i) die Optimierung von Umwandlungsprozessen unter Berücksichtigung technologischer Entwicklungen und (ii) die Identifizierung vielversprechender Biomassenutzungspfade und der besten Standorte für deren Umsetzung. Die Daten (https://www.envidat.ch/dataset/swiss-biomass-potentials) und ein detaillierter Bericht sind online verfügbar (https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A13277/datastream/PDF/Thees-2017-Biomassepotenziale_der_Schweiz_f%C3%BCr_die-%28published_version%29.pdf). Diese Karte zeigt das nachhaltige Potenzial (maximale Menge an national produzierter Biomasse, die nach Abzug ökologischer, wirtschaftlicher, rechtlicher und politischer Restriktionen genutzt werden kann) der verholzten Biomassen für die Bioenergie in der Schweiz auf Gemeindeebene in Primärenergie (maximale Menge an Energie, die in einer Ressource ohne Umwandlung verfügbar ist) in Terajoule.

en: Biomass is a renewable resource for energy which can be transformed into several forms of energy: heat, electricity, biogas or liquid fuels. Woody types of biomass were investigated using methodically comparable approaches: forest wood, wood from landscape maintenance, waste wood and industrial wood residues. Within the implementation of the energy strategy 2050 the Swiss government foresees a massive increase in the share of renewable energy. The Swiss Competence Center for Energy Research (SCCER) Biosweet (Biomass for Swiss Energy Future) seeks solutions to the technical, social and political challenges posed by the Energy Transition with regard to biomass. The Swiss Federal Institute for Forest, Snow and Landscape Research WSL quantified and localised the potential of important biomass resources in Switzerland, particularly with regard to their sustainable availability. The results are useful as a basis for identifying promising biomass-use pathways and the best sites for their implementation. Data (https://www.envidat.ch/dataset/swiss-biomass-potentials) and a detailed report are available online (https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A13277/datastream/PDF/Thees-2017-Biomassepotenziale_der_Schweiz_f%C3%BCr_die-%28published_version%29.pdf). This map shows the sustainable potential of woody biomass for bioenergy (maximum amount of nationally produced woody biomass that could be used, after deducting any ecological, economic, legal and political constraints) in Switzerland at the municipality level in primary energy (maximum amount of energy available in a resource without conversion) in terajoules.

it: La biomassa è una risorsa rinnovabile che può essere trasformata in diverse forme di energia: calore, elettricità, biogas o combustibili liquidi. I seguenti tipi di biomassa legnosa sono stati esaminati usando approcci metodici paragonabili: boschi, legna, scarti verdi agricoli, legname di scarto, rifiuti legnosi provenienti dall'industria.Nel quadro dell'attuazione della strategia energetica 2050, il Governo svizzero prevede un forte aumento della quota delle energie rinnovabili. Lo Swiss Competence Center for Energy Research (SCCER) Biosweet (Biomass for Swiss Energy Future) si occupa di trovare soluzioni per le sfide tecniche, sociali e politiche poste dalla svolta energetica in relazione alla biomassa. L'Istituto federale di ricerca per la foresta, la neve e il paesaggio WSL ha quantificato e localizzato il potenziale delle importanti risorse di biomassa in Svizzera, con particolare attenzione alla relativa disponibilità sostenibile. I risultati costituiscono una base per l'identificazione di soluzioni promettenti per l'uso della biomassa e dei migliori siti per la relativa implementazione. I dati (https://www.envidat.ch/dataset/swiss-biomass-potentials) e un rapporto dettagliato sono disponibili su Internet ( https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A13277/datastream/PDF/Thees-2017-Biomassepotenziale_der_Schweiz_f%C3%BCr_die-%28published_version%29.pdf). La cartina mostra il potenziale sostenibile della biomassa legnosa per la produzione di bioenergia in Svizzera (quantità massima di biomassa legnosa prodotta a livello nazionale che potrebbe essere utilizzata, tenuto contro delle restrizioni a livello ambientale, giuridico e politico) a livello dei Comuni. Il potenziale di energia primaria (quantità massima di energia disponibile in una risorsa senza conversione) è espresso in teraajoule.

bundesamt-fur-energie-bfe

de: Bundesamt für Energie BFE

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).

fr: Potentiel durable des ressources de biomasse ligneuse pour la production de bioénergie en Suisse à l'échelle municipale

de: Nachhaltiges Potenzial der verholzten Biomassenressourcen für Bioenergie in der Schweiz auf Gemeindeebene

en: Sustainable potential of woody biomass resources for bioenergy in Switzerland at the municipality level

it: Il potenziale sostenibile delle risorse di biomassa legnosa per la produzione di bioenergia in Svizzera a livello dei Comuni


culture

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

energy

en: Energy

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

de: energie sachplan strom bgdi-bundesgeodaten-infrastruktur stromnetz

label: geocat.ch permalink

state: active

spatial: Schweiz

type: dataset

fr: Map (Preview)

de: Map (Preview)

en: Map (Preview)

it: Map (Preview)

fr: Géoportail thématique - map.geo.admin.ch

de: Fachportal - map.geo.admin.ch

en: Thematic geoportal - map.geo.admin.ch

it: Geoportale tematico - map.geo.admin.ch

format: SERVICE

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: Consultations des cantons et des communes sur le plan sectoriel des lignes de transport d'électricité, avec information et participation de la population, conformément à l’art. 19 OAT, en cours ou terminées.

de: Laufende oder vergangene Anhörungen der Kantone und Gemeinden sowie Information und Mitwirkung der Bevölkerung nach Art. 19 RPV des Sachplans Übertragungsleitungen.

en: Current or past consultations of the cantons and communes as well as information and participation of the population in accordance with Art. 19 RPV of the Electricity Transmission Lines sectoral plan.

it: Audizioni dei Cantoni e dei Comuni in corso o concluse nonché informazione e partecipazione della popolazione conformemente all’articolo 19 OPT in relazione al piano settoriale degli elettrodotti.

fr: Office fédéral de l'énergie OFEN

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

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

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

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

political_level: confederation

type: organization

approval_status: approved

value: BFE - Geocat Harvester

fr: Plan sectoriel des lignes de transport d'électricité (PSE) - consultations

de: Sachplan Übertragungsleitungen (SÜL) - Anhörungen

en: Electricity Transmission Lines sectoral plan - consultations

it: Piano settoriale degli elettrodotti (PSE) - consultazioni


sachplan-geologische-tiefenlager

title_for_slug: sachplan-geologische-tiefenlager

protocol: WWW:DOWNLOAD:Geopackage (ogc)

de: Geopackage

media_type: Geopackage (ogc)

format: GPKG

de: Interlis

media_type: INTERLIS

format: INTERLIS

en: Map (Preview) Thematic geoportal - map.energie.admin.ch

fr: Géoportail thématique - map.energie.admin.ch

it: Geoportale tematico - map.energie.admin.ch

fr: Web Map Services WMS

de: Web Map Services WMS

en: Web Map Services WMS

it: Web Map Services WMS

format: WMS

fr: Si la majeure partie des déchets radioactifs en Suisse résulte de l'exploitation des cinq centrales nucléaires, une certaine quantité provient des activités de la médecine, de l'industrie et de la recherche. Ces déchets doivent être conservés très longtemps à l'abri des hommes et de l‘environnement. Selon l'état actuel des connaissances, le stockage dans des formations rocheuses souterraines constitue la solution la plus sûre.La loi sur l'énergie nucléaire prescrit donc le stockage des déchets radioactifs dans des dépôts en couches géologiques profondes. La recherche de sites d'implantation potentiels pour ces dépôts se déroule en trois étapes, dans le cadre du plan sectoriel «Dépôts en couches géologiques profondes». Le Conseil fédéral optera à l'issue de la troisième étape soit pour deux sites, l'un pour les déchets faiblement et moyennement radioactifs (DFMR) et l'autre pour les déchets hautement radioactifs (DHR), soit pour un seul site pour les déchets de toutes les catégories (autorisation générale). Les géodonnées répertorient les domaines d'implantation géologique pour les DFMR et les DHR ainsi que les emplacements pour les installations de surface, conformément au niveau de coordination actuel de la procédure de sélection.

de: Die radioaktiven Abfälle der Schweiz stammen grösstenteils aus den fünf Kernkraftwerken, aber auch aus Medizin, Industrie und Forschung. Sie müssen für sehr lange Zeit sicher von Mensch und Umwelt ferngehalten werden. Dazu ist die Einlagerung in unterirdische Gesteinsschichten nach heutigem Kenntnisstand die sicherste Lösung.Das Kernenergiegesetz schreibt deshalb die geologische Tiefenlagerung der radioaktiven Abfälle vor. Die Standortsuche für geologische Tiefenlager erfolgt im Rahmen des "Sachplan geologische Tiefenlager (SGT)". Die Standortsuche erfolgt in drei Etappen. Am Ende der dritten Etappe wird der Bundesrat über einen Standort für schwach- und mittelradioaktive Abfälle SMA sowie einen Standort für hochradioaktive Abfälle HAA oder für einen Standort für alle Abfallkategorien entscheiden (Rahmenbewilligung). Die Geodaten enthalten die geologischen Standortgebiete für SMA bzw. HAA und die Standortareale für eine Oberflächenanlage entsprechend dem aktuellen Koordinationsstand der Festlegung.

en: Most of the radioactive waste in Switzerland comes from the country's five nuclear power plants, though a certain amount is also produced in the healthcare sector, in industry and from research. Radioactive waste has to be stored safely and away from people and the environment for an extremely long time. According to the current state of knowledge, storage in rock layers deep under the ground is the safest solution.In view of this, the Federal Nuclear Energy Act calls for the construction of deep geological repositories for the storage of radioactive waste. The search for suitable sites is being carried out within the framework of the “deep geological repository” sectoral plan in three stages. At the end of stage three the Federal Council is to decide on a site for the storage of low and intermediate level radioactive waste, plus a separate site for high-level radioactive waste, or a single site suitable for all waste categories (general licence). The geodata contain the proposed geological sites for low and intermediate level, respectively high-level radioactive waste, together with the sites for housing the installations on the surface in accordance with the current status of coordination of the concept.

it: Le scorie radioattive svizzere derivano in massima parte dalle cinque centrali nucleari, ma anche dalla medicina, dall'industria e dalla ricerca. Devono essere conservate per un periodo molto lungo in un luogo sicuro senza contatti con l'ambiente e le persone. Allo stato attuale delle conoscenze, la soluzione più sicura è rappresentata dallo stoccaggio in strati rocciosi sotterranei. La legge federale sull'energia nucleare prescrive quindi lo stoccaggio delle scorie radioattive in un deposito in strati geologici profondi. La procedura di selezione dei siti di questi depositi è disciplinata nel "Piano settoriale dei depositi in strati geologici profondi" e si svolge in tre tappe. Al termine della terza tappa, il Consiglio federale deciderà in merito al rilascio dell'autorizzazione di massima per due siti, uno per le scorie debolmente e mediamente radioattive (SDM) e uno per quelle altamente radioattive (SAA), oppure per un sito unico per tutte le categorie di scorie. I geodati contengono le aree geologiche di ubicazione per i depositi SDM e SAA e i siti per gli impianti di superficie conformemente all'attuale stato di coordinamento dei dati acquisiti.

fr: Plan sectoriel des dépôts en couches géologiques profondes

de: Sachplan geologische Tiefenlager

en: Sectoral Plan Deep Geological Repositories


maintainer: EnviDat Support

en: natural-climate-variability cryosphere climate-change-impact rain-on-snow snow-water-equivalent uncertainty

en: climate realizations

en: The dataset contains for three variables (snow water equivalent, surface water input and liquid precipitation) 50 realizations of current and future climate periods for two time horizons (mid end end of century), two emission senarions (RCP 4.5 and 8.5) and 10 climate model chains (all EUR11 chains within CH2018). To quantify natural climate variability for projections of snow conditions and resulting rain-on-snow (ROS) flood events, a weather generator was applied to simulate inherently consistent climate variables for multiple realizations of current and future climates at 100 m spatial and hourly temporal resolution over a 12 x 12 km high-altitude study area in the Swiss Alps. The output of the weather generator was used as input for subsequent simulations with an energy balance snow model. The data was extracted in 2021 from original model output.

climate-change-impact

display_name: climate-change-impact

cryosphere

display_name: cryosphere

natural-climate-variability

display_name: natural-climate-variability

rain-on-snow

display_name: rain-on-snow

snow-water-equivalent

display_name: snow-water-equivalent

uncertainty

display_name: uncertainty

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

key: guid

key: uri

value: Envidat Harvester

en: Multiple realizations of daily snow water equivalent, surface water input and liquid precipitation projections for mid- and late-century


biogasanlagen

culture

fr: Culture, médias, société de l'information, sport

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

it: Cultura, media, società dell'informazione, sport

energy

fr: Energie

de: Energie

en: Energy

it: Energia

geography

en: Geography

territory

en: Territory and environment

title_for_slug: biogasanlagen

fr: Map (Preview) Géoportail thématique - map.energie.admin.ch

de: Map (Preview) Fachportal - map.energie.admin.ch

it: Map (Preview) Geoportale tematico - map.energie.admin.ch

de: Fachportal - map.energie.admin.ch

en: Thematic geoportal - map.energie.admin.ch

protocol: WWW:DOWNLOAD:Text (.csv), comma separated

de: Csv

media_type: Text (.csv), comma separated

format: CSV

de: swisstopo REST API

fr: Les installations de biogaz transforment la matière organique en gaz par un processus de fermentation. Le mélange gazeux obtenu est composé principalement de méthane riche en énergie (CH4) et de dioxyde de carbone (CO2). Electricité, chaleur et carburant peuvent être obtenus à partir du biogaz.La Suisse dispose de plus d'une centaine d'installations de biogaz. Le biogaz produit dans notre pays provient exclusivement de déchets et de résidus issus des ménages, de l'industrie alimentaire ou encore de l'agriculture. Cette énergie est donc durable en plus d'être renouvelable et neutre en CO2. Le biogaz peut être utilisé directement dans une centrale de cogénération pour produire de l'électricité et de la chaleur. Il peut également être purifié en biométhane avant d'être injecté dans le réseau de gaz naturel. Ce biométhane peut alors à nouveau servir à produire de l'électricité, de la chaleur ou du carburant. Les géodonnées des installations de biogaz renseignent sur l'état actuel de ce type d'installations de production d'énergie en Suisse. Pour le moment, les données se fondent uniquement sur la liste des récipiendaires de la RPC. L'objectif, à terme, est de pouvoir représenter l'ensemble des installations de biogaz en activité en Suisse, que celles-ci produisent de l'électricité et de la chaleur sur site ou qu'elles injectent du biométhane dans le réseau de gaz naturel. Les informations servent à informer le grand public et ne constituent pas des informations officielles ni des déclarations de nature contraignante.

de: In Biogasanlagen wird aus organischem Material mittels Vergärung Gas erzeugt. Das dabei entstehende Gasgemisch besteht zum überwiegenden Teil aus energiereichem Methan (CH4) und aus Kohlendioxid (CO2). Biogas kann zur Erzeugung von Strom und Wärme sowie als Treibstoff genutzt werden. Die Schweiz zählt mehr als 100 Biogasanlagen. Bei der inländischen Biogasproduktion werden ausschliesslich Abfälle und Speisereste aus Haushalten, der Nahrungsmittelindustrie und der Landwirtschaft verwertet. Biogas ist damit nicht nur ein erneuerbarer und CO2-neutraler, sondern auch ein nachhaltiger Energieträger. Mit Biogas kann direkt in einem Blockheizkraftwerk (BHKW) Strom und Wärme erzeugt werden. Es kann aber auch zu Biomethan aufbereitet und anschliessend ins Erdgasnetz eingespeist werden. Es steht dann wiederum für die Strom- und Wärmeproduktion oder als Treibstoff zur Verfügung. Die Geodaten über Biogasanlagen geben Auskunft über den derzeitigen Stand solcher Energieerzeugungsanlagen in der Schweiz. Derzeit beruhen die Daten nur auf der Liste der KEV-Bezüger. Das langfristige Ziel besteht darin, alle in der Schweiz in Betrieb stehenden Biogasanlagen erfassen zu können – ob sie nun Elektrizität oder Wärme vor Ort produzieren oder ob sie Biomethan ins Erdgasnetz einspeisen. Die Daten sind zur Information der breiten Öffentlichkeit bestimmt und stellen keine amtlichen oder verbindlichen Angaben dar.

en: Biogas plants convert organic matter into gas through a fermentation process. The resulting gas mixture is composed mainly of energy-rich methane (CH4) and carbon dioxide (CO2). Electricity, heat and fuel can be obtained from biogas.Switzerland has more than 100 biogas plants. The biogas produced in our country comes exclusively from waste and residues from households, the food industry or agriculture. This energy is therefore sustainable, renewable and CO2 neutral. Biogas can be used directly in a cogeneration plant to produce electricity and heat. It can also be purified into biomethane before being injected into the natural gas network. Biomethane can in turn be used to produce electricity, heat or fuel. The geodata of biogas plants provide information on the current status of biogas plants in Switzerland. Currently, the data is based solely on the list of recipients of feed-in remuneration at cost. The ultimate aim is to be able to show all biogas installations operating in Switzerland, whether they produce electricity and heat on site or feed biogas into the natural gas grid.This information is intended for the general public and is unofficial and non-binding.

it: Gli impianti di produzione di biogas trasformano la materia organica in gas attraverso un processo di fermentazione. La miscela di gas ottenuta è composta principalmente da metano ricco di energia (CH4) e da diossido di carbonio (CO2). Dal biogas è possibile ottenere elettricità, calore e carburante.In Svizzera esiste più di un centinaio di impianti di produzione di biogas. Il biogas prodotto nel nostro Paese proviene esclusivamente da rifiuti e residui derivanti dalle economie domestiche, dall'industria alimentare o dall'agricoltura. Questo tipo di energia è quindi sostenibile, rinnovabile e neutro dal punto di vista delle emissioni di CO2. Il biogas può essere utilizzato direttamente in una centrale di cogenerazione per produrre elettricità e calore, ma può anche essere purificato e reso biometano prima di essere immesso nella rete di gas naturale. In tal modo il biometano può nuovamente essere utilizzato per la produzione di elettricità, calore o carburante. I geodati degli impianti di produzione di biogas forniscono informazioni sullo stato attuale di questo tipo di installazioni per la produzione di energia in Svizzera. Attualmente i dati si basano esclusivamente sull'elenco dei beneficiari della rimunerazione per l'immissione in rete di energia elettrica (RIC). L'obiettivo, a termine, è rappresentare la totalità degli impianti di produzione di biogas in funzione in Svizzera, sia quelli che producono elettricità e calore in loco sia quelli che immettono biometano nella rete di gas naturale. Le informazioni servono ad informare il grande pubblico, ma non costituiscono informazioni ufficiali e nemmeno dichiarazioni di natura vincolante.

bundesamt-fur-energie-bfe

de: Bundesamt für Energie BFE

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).

fr: Installations de biogaz

de: Biogasanlagen

en: Biogas plants

it: Impianti di produzione di biogas


geography

fr: Géographie

de: Geographie

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

it: Territorio e ambiente

en: Map (Preview) Thematic geoportal - map.energie.admin.ch

en: Web Map Services WMS

de: Geopackage

de: Interlis

fr: L'Office fédéral de l'énergie (OFEN) encourage le développement et l'expérimentation de nouvelles technologies, solutions et approches dans les domaines de l'utilisation économe et efficace de l'énergie, du transfert et du stockage d'énergie et de l'utilisation des énergies renouvelables. Le programme P+D se situe à l'interface entre la recherche et le marché et vise à relever le degré de maturité des nouvelles technologies, afin que celles-ci soient commercialisables à terme.Cette base de données contient les projets pilotes et de démonstration actuels soutenus par l'Office fédéral de l'énergie.

de: Das Bundesamt für Energie BFE fördert mit dem Pilot- und Demonstrationsprogramm (P+D-Programm) die Entwicklung und Erprobung von neuen Technologien, Lösungen und Ansätzen im Bereich der sparsamen und effizienten Energienutzung, der Energieübertragung und -speicherung sowie der Nutzung erneuerbarer Energien. Das P+D-Programm positioniert sich an der Schnittstelle zwischen Forschung und Markt und hat das Ziel, den Reifegrad von neuen Technologien zu erhöhen, um sie letztendlich zur Marktreife zu bringen. Dieser Datenbestand enthält aktuelle Pilot- und Demonstrationsprojekte, welche vom Bundesamt für Energie unterstützt werden.

en: With its Pilot and Demonstration programme the Swiss Federal Office of Energy (SFOE) promotes the development and testing of new technologies, solutions and concepts relating to the economical and ecological use of energy, the transmission and storage of energy and the use of renewable forms of energy. The Pilot and Demonstration programme acts as an interface between research and the market. Its main aim is to help increase the status of development of new technologies so that they can ultimately be brought onto the market.This dataset contains current pilot and demonstration projects supported by the Swiss Federal Office of Energy.

it: Con il Programma pilota e di dimostrazione (Programma P+D), l'UFE promuove lo sviluppo e la sperimentazione di nuove tecnologie, soluzioni e approcci nei settori dell'uso parsimonioso ed efficiente dell'energia, del suo trasporto e stoccaggio nonché dello sfruttamento delle fonti rinnovabili. Il programma P+D si posiziona all'interfaccia tra la ricerca e il mercato e mira ad aumentare il livello di maturità delle nuove tecnologie per portarle infine alla maturità di mercato.Questa banca dati contiene gli attuali progetti pilota e dimostrativi sostenuti dall'Ufficio federale dell'energia.

bundesamt-fur-energie-bfe

en: Swiss Federal Office of Energy SFOE

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).

fr: Projets pilotes et de démonstration actuels de l'Office fédéral de l'énergie

de: Aktuelle Pilot- und Demonstrationsprojekte des Bundesamts für Energie

en: Current pilot and demonstration projects of the Swiss Federal Office of Energy

it: Progetti pilota e dimostrativi in corso dell'Ufficio federale dell'energia


windenergieanlagen

title_for_slug: windenergieanlagen

de: Web Map Services WMS

fr: Les installations éoliennes utilisent l’énergie cinétique des masses d’air qui se déplacent pour faire tourner des hélices. L’énergie mécanique ainsi générée est ensuite transformée en énergie électrique grâce à un générateur. D’une puissance de 28 kW, la première centrale éolienne suisse a été mise en service en 1986 près de la ferme Soolhof (Langenbruck). En 2013, notre pays compte 34 installations éoliennes, qui produisent ensemble quelque 85 gigawattheures (GWh) d’électricité. Situé au Mont Crosin, sur les hauts de Saint-Imier dans le Jura bernois, le plus grand parc éolien de Suisse abrite seize éoliennes, qui totalisent une puissance de 23,6 MW. D’autres grandes installations ont été construites dans la vallée du Rhône (VS), à Entlebuch (LU) et sur le Gütsch au-dessus d’Andermatt (UR). En Suisse, l’énergie éolienne dispose d’un large potentiel. La production annuelle pourrait en effet atteindre quelque 600 GWh à l’horizon 2020 et dépasser 4000 GWh d’ici à 2050. Les sites appropriés se trouvent sur les crêtes du Jura, mais également dans les Alpes et les Préalpes, ainsi qu’à l’ouest du Plateau. Les géodonnées techniques «installations éoliennes» renseignent sur l’état actuel des installations éoliennes en Suisse. L’ensemble des informations se fondent sur les données fournies par les exploitants des installations. Les indications servent à informer le grand public et ne constituent pas des informations officielles ni des déclarations de nature contraignante.

de: Windenergieanlagen nutzen die kinetische Energie der anströmenden Luft zur Rotation der Flügel. Die auf diese Weise erzeugte mechanische Energie wird von einem Generator in elektrische Energie umgewandelt.Die erste Windenergieanlage der Schweiz wurde 1986 beim Soolhof (Langenbruck, BL) mit einer Leistung von 28 kW in Betrieb genommen. 2013 gibt es insgesamt 34 Windenergieanlagen, die rund 85 Gigawattstunden (GWh) Windstrom produzieren. Der grösste Windpark befindet sich auf dem Mont Crosin im Berner Jura bei St. Imier: Hier stehen 16 Windturbinen mit einer Gesamtleistung von 23,6 MW. Weitere Grossanlagen stehen u.a. im Rhonetal (VS), bei Entlebuch (LU) und auf dem Gütsch ob Andermatt (UR). In der Schweiz kann sich die Windenergie noch stark entwickeln. So sollen Windenergieanlagen bis zum Jahr 2020 rund 600 GWh und bis 2050 etwa 4‘000 GWh Strom pro Jahr produzieren. Geeignete Standorte befinden sich auf den Jurahöhen, aber auch in den Alpen und Voralpen und im westlichen Mittelland. Die Geofachdaten «Windenergieanlagen» dokumentieren den aktuellen Bestand der Windenergieanlagen der Schweiz. Sämtliche Informationen basieren auf den Auskünften der Anlagenbetreibenden. Die Angaben dienen als Informationsmaterial für die Öffentlichkeit und stellen keine amtliche Auskunft oder rechtsverbindliche Aussage dar.

en: Wind energy plants utilise the kinetic energy of airflow to rotate turbine blades. The mechanical energy that is produced in this way is then converted by a generator into electricity.The first wind energy facility in Switzerland was put into operation in 1986 near Soolhof Farm (Langenbruck, canton of Baselland) and had an output of 28 kilowatts. In 2013, a total of 34 wind power plants produced around 85 gigawatt hours (GWh) of electricity. The largest wind park is on Mont Crosin in the Bernese Jura near St Imier: this facility comprises 16 wind turbines with a total output of 23.6 megawatts. Other large facilities are in operation in Rhonetal (canton of Valais), near Entlebuch (canton of Lucerne) and on the Gütsch (above Andermatt, canton of Uri). There is still a great deal of potential for wind energy in Switzerland. The goal is to increase the annual production of electricity from wind energy plants to around 600 GWh by 2020 and 4,000 GWh by 2050. Suitable locations for wind parks exist in the Jura range, as well as in the Alps and the western region of the central plateau. The “Wind energy plants” geodata document the current situation regarding wind energy facilities in Switzerland. All data are based on information provided by the power plant operators and are intended to function as information material for the general public. They do not take the form of official information and are not legally binding.

it: Gli impianti a energia eolica sfruttano l'energia cinetica delle correnti d'aria per mantenere in rotazione le pale dei generatori, le quali trasformano questa energia meccanica in energia elettrica.Il primo impianto svizzero a energia eolica è stato messo in funzione nel 1986 a Soolhof (Langenbruck) e aveva una potenza di 28 kW. Nel 2013, in Svizzera si contavano 34 impianti eolici con una produzione complessiva di ca. 85 gigawattora (GWh) di energia elettrica all'anno. Il parco di generatori più grande si trova sul Mont Croisin, nel Giura bernese presso St. Imier, dove sono in esercizio 16 turbine eoliche, con una potenza complessiva di 23,6 MW. Si trovano altri grossi impianti nella valle del Rodano (VS), nei pressi di Entlebuch (LU) e sul Gütsch, sopra Andermatt (UR). In Svizzera l'energia eolica presenta tuttora un elevato potenziale di crescita: entro il 2020 gli impianti dovrebbero produrre ca. 600 GWh di energia elettrica all'anno ed entro il 2050 addirittura 4 000 GWh. I siti più adeguati per questo tipo di impianti si trovano sulle alture del Giura, lungo la catena alpina, nelle Prealpi e nell'Altopiano occidentale. I geodati relativi agli impianti eolici documentano l’attuale parco impianti eolici in Svizzera, basandosi unicamente sulle informazioni rilasciate dai gestori degli impianti. I dati sono da intendere come materiale informativo destinato all’opinione pubblica; sotto il profilo giuridico non hanno carattere vincolante e non sono da considerarsi informazioni ufficiali.

fr: Office fédéral de l'énergie OFEN

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.

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).

fr: Installations éoliennes

de: Windenergieanlagen

en: Wind energy plants

it: Impianti eolici


en: stable-water-isotopes precipitation stream-water spatially-distributed-sampling geochemical-solutes

format: XLS

en: The dataset contains daily measurements of volumes, isotopes and solutes of stream water as well as precipitation measured several locations; meteorological variables are added. Date: 18.07.2019

en:
This dataset contain measurements of solute and stable water isotopes in stream water and precipitation in the Alp catchment and two of its tributaries (between 2015 -2018) . The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l. The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (precipitation rates, discharge) at daily intervals from several sampling locations.
An updated version of the isotope dataset is available here: https://www.doi.org/10.16904/envidat.242

geochemical-solutes

display_name: geochemical-solutes

precipitation

display_name: precipitation

spatially-distributed-sampling

display_name: spatially-distributed-sampling

stable-water-isotopes

display_name: stable-water-isotopes

stream-water

display_name: stream-water

education

de: Bildung, Wissenschaft

en: Education and science

envidat

de: EnviDat: das Umwelt-Datenportal

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.

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.

en: Daily data of solute and stable water isotopes in stream water and precipitation in the Alp catchment, Central Switzerland


maintainer: Joan Casanelles Abella

en: hylaeus-communis tartu trap-nest urban-ecology dna-metabarcoding poznan chelostoma-florisomne zurich osmia-cornuta cavity-nesting-bees antwerp paris osmia-bicornis plant-pollinator-interactions

en: Larval food composition

media_type: CSV

en: Explanation data variables

en: Urbanization poses threats and opportunities for the biodiversity of wild bees. A main gap relates to the food preferences of wild bees in urban ecosystems, which usually harbour large numbers of plant species, particularly at the larval stage. This data sets describes the larval food of four wild bee species (i.e. Chelostoma florisomne, Hylaeus communis, Osmica bicornis and Osmia cornuta) and three genera (i.e. Chelostoma sp., Hylaeus sp, and Osmia sp.) common in urban areas in five different European cities (i.e. Antwerp, Paris, Poznan, Tartu and Zurich). This data results from a European-level study aimed at understanding the effects of urbanization on biodiversity across different cities and citiscapes, and a Swiss project aimed at understanding the effects of urban ecosystems in wild bee feeding behaviour. Wild bees were sampled using standardized trap-nests in 80 sites (32 in Zurich and 12 in each of the remaining cities), selected following a double gradient of available habitat at local and landscape scales. Larval pollen was obtained from the bee nests and identified using DNA metabarconding. The data provides the plant composition at the species or genus level of the different bee nests of the studied species in the studied sites of the five European cities. For Hylaeus communis, this is the first study in reporting larval food composition.

antwerp

display_name: antwerp

cavity-nesting-bees

display_name: cavity-nesting-bees

chelostoma-florisomne

display_name: chelostoma-florisomne

dna-metabarcoding

display_name: dna-metabarcoding

hylaeus-communis

display_name: hylaeus-communis

osmia-bicornis

display_name: osmia-bicornis

osmia-cornuta

display_name: osmia-cornuta

paris

display_name: paris

plant-pollinator-interactions

display_name: plant-pollinator-interactions

poznan

display_name: poznan

tartu

display_name: tartu

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

zurich

display_name: zurich

en: Larval food composition of four wild bee species in five European cities


soil-respiration-exclosure-experiment

title_for_slug: soil-respiration-exclosure-experiment

en: subalpine grassland ungulates soil-respiration grazing

en: Soil respiration Switzerland

en:
ID: Fence number

Year	:Year of sampling

mean.CO2: soil respiration measured with PP-systems SRC-1 soil respriation chamber attached to a EGM-4 infrared gas analyser; units CO2 g m-2 h-1

Grassland: Grasslands where fences were errected. Note that on large grasslands (STAB, GRIM, MING) 2 pairs of fences were errected (2 in short, 2 in tall-grass vegetation), on small grasslands (DADA, MARG, BOTS) only one pair of fences was errected (1 short-grass; one-tallgrass vegetation)

Fence: Fence number; un-even numbers on short-grass vegetation (1,3,5,7,9,11,13,15,17), even numbers on tall-grass vegetation (2,4,6,8,10,12,14,16,18)

Vegetation:	1 = shortgrass vegetation, 2 = tall-grass vegetation (9 replicate fences on each vegetation type)

Treatment	: 1 = all herbivores grazing, 2 = large ungulates (red deer, chamois) excluded

en:
Location of data collection
The Swiss National Park (SNP) is located in the southeastern part of Switzerland, and covers an area of 170 km2, 50 km2 of which is forested, 33 km2 is occupied by alpine and 3 km2 by subalpine grasslands. Elevations range from 1350 to 3170 m a.s.l., and mean annual precipitation and temperature are 871 mm and 0.6°C measured at the Park’s weather station in Buffalora (1980 m a.s.l.) between 1960 and 2009 (MeteoSchweiz 2011). Founded in 1914, the SNP received minimal human disturbance for almost 100 years (no hunting, fishing, or camping, visitors are not allowed to leave the trails). Large (> 1 ha) homogeneous patches of short- and tall-grass vegetation characterize the subalpine grasslands. The average vegetation height of short-grass vegetation is 2 to 5 cm. Red fescue (Festuca rubra L.), quaking grass (Briza media L.) and common bent grass (Agrostis tenuis Sipthrob) are the predominating plant species in this vegetation type. Tussocks of evergreen sedge (Carex sempervirens Vill.) and mat grass (Nardus stricta L.) are predominant in the tall-grass vegetation, which averages 20 cm in vegetation height (Schütz and others 2006). Short-grass vegetation developed in areas where cattle and sheep rested (high nutrient input) during agricultural land-use (from 14th century until 1914); tall-grass vegetation developed in areas where cattle and sheep used to graze, but did not rest (Schütz and others 2003, 2006). Herbivores were shown to consume > 60% of the biomass in short-grass compared to < 20% in tall-grass vegetation (Schütz and others 2006). The herbivore community present in the SNP can be divided into four groups based on body size/weight: large [red deer (Cervus elaphus L.) and chamois (Rupricapra rupricapra L.); 30 - 150 kg], medium [marmot (Marmota marmota L.) and snow hare (Lepus timidus L.); 3 – 6 kg], and small vertebrate herbivores (small rodents: e.g. Clethrionomys spp., Microtus spp., Apodemus spp.; 30 – 100 g) as well as invertebrates (e.g. grasshoppers, caterpillars, cicadas, < 5 g).

Experimental design
We selected 18 subalpine grassland sites (9 short-grass, 9 tall-grass vegetation). The sites were spread across the entire park on dolomite parent material at altitudes of 1975 to 2300 meters. At each site we established an exclosure network (fences) in spring 2009 (early June), immediately after snowmelt. Each exclosure network consisted of a total of five 2 × 3 m sized plots that progressively excluded the different herbivores listed above (further labeled according to the herbivore guilds that had access to the respective plots “All”, “Marmot/Mice/Invertebrates”, “Mice/Invertebrates”, “Invertebrates”, “None”). The “All” treatment was thus accessible to all herbivores, was not fenced and was located at least 5 m away from a 2.1 m tall and 7 × 9 m main fence that enclosed the other four treatments. This fence was constructed of 10 × 10 cm wooden posts and electrical equestrian tape (AGRARO ECO, Landi, Bern, Switzerland; 20 mm width) mounted at 0.7 m, 0.95 m, 1.2 m, 1.5 m and 2.1 m above the ground that were connected to a solar charged battery (AGRARO Sunpower S250, Landi, Bern, Switzerland). We also mounted non-electrically charged equestrian tape at 0.5 m to help exclude deer and chamois, yet allow marmots and hares to enter safely. Within each main fenced area we randomly established four 2 × 3 m plots: (1) The “Marmot/Mice/Invertebrates” plot remained unfenced, thus, with the exception of red deer and chamois, all herbivores were able to access the plot, (2) The “Mice/Invertebrates” plot consisted of a 90 cm high electric sheep fence (AGRARO Weidezaunnetz ECO, Landi, Bern, Switzerland; mesh size 10 × 10 cm) connected to the solar panel and excluded all medium sized mammals (marmots, hares), but provided access for small mammals and invertebrates, (3) The “Invertebrates” plot provided access for invertebrates only and was surrounded by 1 m high metal mesh (Hortima AG, Hausen, Schweiz; mesh size 2 × 2 cm), (4) The “None” plot was surrounded by a 1 m tall mosquito net (Sala Ferramenta AG, Biasca, Switzerland; mesh size 1.5 × 2 mm) to exclude all herbivores. This plot was covered with a roof constructed of a wooden frame lined with mosquito mesh that was mounted on the wooden corner posts. We also treated this plot with a biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) when needed to remove insects that might have entered during data collection or that hatched from the soil.

!!! The here published data set only contains data for “All”, and “Marmot/Mice/Invertebrates” (= ungulates excluded) plots !!!

Data collection
In-situ soil CO2 emissions were measured with a PP-Systems SRC-1 soil respiration chamber (closed circuit) attached to a PP-Systems EGM-4 infrared gas analyzer (PP-Systems, Amesbury, MA, USA) on two randomly selected locations on one subplot within each of the 90 plots. For each measurement the soil chamber (15 cm high; 10 cm diameter) was placed on a permanently installed PVC collar (10 cm diameter) driven five centimeters into the soil at the beginning of the study (June 2009). The measurements were conducted between 0900 and 1700 hours every two weeks from early to early September 2009, 2010, 2011 and 2013. Freshly germinated plants growing within the PVC collars were removed prior to each measurement to avoid measuring plant respiration/photosynthesis. The two measurements collected per plot every two weeks were averaged.

Please acknowledge the funding of the study: funded by the Swiss National Science Foundation, SNF grant-no 31003A_122009/1 to Anita C. Risch, Martin Schütz and Flurin Filli

grassland

display_name: grassland

grazing

display_name: grazing

soil-respiration

display_name: soil-respiration

subalpine

display_name: subalpine

ungulates

display_name: ungulates

en: Soil respiration - exclosure experiment


en: community-energy renewable-energy switzerland energy-cooperatives cooperatives

en: Questionnaire with variable names

media_type: PDF

en: Modified questionnaire with variable names for each item. Should be used together with the data files (.csv or .sav) to reconstruct the data and variable structures.

format: PDF

mimetype: application/pdf

en: Raw data (.csv)

en: Raw data in csv. format. For comprehension of the data and variable structure, please consult the codebook and the modified questionnaire with variable names.

mimetype: text/csv

en: Codebook

en: Description of variable attributes and valid n

en: Raw date (SPSS)

media_type: SAV

en: Raw data in sav. format (SPSS). For comprehension of the data and variable structure, please consult the modified questionnaire with variable names.

en:
 Topic of Survey
The data at hand on energy cooperatives in Switzerland were collected in 2016 as part of the project "Collective financing of renewable energy projects in Switzerland and Germany" of the National Research Programme 71 "Managing Energy Consumption". The cooperatives were surveyed on their organizational structure, their activities in electricity and heat generation, their finances, the political context and their assessments of the future.

 Survey Method
The survey was targeted at all energy cooperatives in Switzerland (this is the basic population). The Swiss Commercial Register was searched for cooperatives and specific keywords in order to determine this basic population and collect addresses. This search in May 2016 resulted in a total of 304 energy cooperatives, to which a questionnaire was sent in July 2016. A pre-test with 8 persons had been carried out before the questionnaire was sent out. The questionnaire was provided in German and French. It was sent by mail and an attached letter referred to a link for the digital version if preferred. The online version was designed with the software "Sawtooth". After three weeks, a first, and after six weeks a second reminder letter was sent to those cooperatives that had not yet completed the questionnaire. The returned hardcopy questionnaires were manually entered into the database and then combined with the electronic data from the online survey. In the course of the survey, the total population was reduced from 304 to 289: in 4 cases the survey was not deliverable, 4 cooperatives had dissolved, 6 were not actually energy cooperatives, 1 case had recently changed its legal form. With a response rate of 47%, the final data set comprises 136 responses (from 77 digital and 59 hardcopy questionnaires). However, not all 136 of the returned questionnaires were filled out completely. We checked for answers that seemed contradictory or incomprehensible. If an error could be clearly identified and the correct answer derived, the answer was adjusted, otherwise the answer was replaced by "missing data".

 Anonymization
Participating cooperatives have been assured that their information will be kept confidential and will only be made public anonymously. For this reason, the data have been anonymized in in order to prevent any identification of individual cooperatives.

 How to Use the Data
* The data are available in CSV and SPSS (sav.) format.
* A codebook and a modified version of the used questionnaire are provided to illustrate the data and variable structure. In the questionnaire, the variable names are assigned to the corresponding questions. In the codebook, further information on these variables (valid n, answer categories) can be found. This information (of the codebook) is already integrated in the SPSS file.

 Current Embargo on Data
These data are currently under embargo and will only be released when the project is completed (not before 2020).

#Additional Information
* The used questionnaire is provided in German and French.
* Descriptive results of the survey were published in a WSL report: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:18943

community-energy

display_name: community-energy

cooperatives

display_name: cooperatives

energy-cooperatives

display_name: energy-cooperatives

renewable-energy

display_name: renewable-energy

switzerland

display_name: switzerland

en: Energy Cooperatives in Switzerland: Survey Results // Energiegenossenschaften in der Schweiz: Befragungsergebnisse


maintainer: Jana von Freyberg

en: stable-water-isotopes review plant-water-uptake root-zone uncertainties endmember-mixing-models ecohydrology

en: Data set of MEE-20-04-264 (CSV)

en: Data set of MEE-20-04-264

media_type: application/pdf

en: The following two tables contain information about the data sources of the values reported in Table 1 and 2 in the paper “Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources” published in the journal ‘Methods in Ecology and Evolution’.

en: The following two tables contain information about the data sources of the values reported in Table 1 and 2 in the paper “Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources” published in the journal 'Methods in Ecology and Evolution'.

ecohydrology

display_name: ecohydrology

endmember-mixing-models

display_name: endmember-mixing-models

plant-water-uptake

display_name: plant-water-uptake

review

display_name: review

root-zone

display_name: root-zone

stable-water-isotopes

display_name: stable-water-isotopes

uncertainties

display_name: uncertainties

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Data set of: Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources


en: longwave-radiation outgoing shortwave-radiation incoming davos

en: Metadata

en: DATA ACCESS

media_type: SMET

en: Processing doc

en: Parameter file

media_type: text/plain

format: TXT

mimetype: text/plain

en:
Incoming and outgoing shortwave and longwave 2 min radiation measurements in Davos Dorf, CH.

 References
1. Marty, C., Philipona, R., Frohlich, C., Ohmura, A.. Altitude dependence of surface radiation fluxes and cloud forcing in the alps: results from the alpine surface radiation budget network. 2002. Theoretical and Applied Climatology. Volume 72. Issue 3-4. 137-155. http://dx.doi.org/10.1007/s007040200019. 10.1007/s007040200019.
2. Christoph Marty. Surface Radiation, Cloud Forcing and Greenhouse Effect in the Alps. 2000. Institute fuer Klimaforschung ETH. Zuercher Klima-Schriften. Volume 79. http://e-collection.library.ethz.ch/eserv/eth:23491/eth-23491-01.pdf.

davos

display_name: davos

incoming

display_name: incoming

longwave-radiation

display_name: longwave-radiation

outgoing

display_name: outgoing

shortwave-radiation

display_name: shortwave-radiation

en: ASRB_DAV: Shortwave and longwave radiation measurements (2 min) in Davos Dorf


maintainer: Leo Gallus Bont

en: qgis accessible-forest forest geoprocessing seilaplan openstreetmap

en: DEM (for the area of the sample forest range)

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Juypter Notebook for Data Preparation

media_type: ipynb

en: Juypter Notebook for Data Preparation (online)

en: Railways vector data (close to the sample forest range)

media_type: application/zip

format: ZIP

mimetype: application/zip

en: Forest vector data (for sample forest range)

en: Preview

media_type: image/png

format: PNG

mimetype: image/png

en: Digitised sample perimeter

en: Power lines vector data (close to the area of the sample forest range)

en:
This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps).
The purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin [Seilaplan]( https://doi.org/10.16904/envidat.software.1) for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting.
The vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019.

Additional notes for vector data:
Please note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API - https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any perimeter or area can be digitised freely using the QGIS editing toolbar.

The DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are:

- Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM)
- Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif

This methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed.

Additional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range.

This sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.

accessible-forest

display_name: accessible-forest

forest

display_name: forest

geoprocessing

display_name: geoprocessing

openstreetmap

display_name: openstreetmap

qgis

display_name: qgis

seilaplan

display_name: seilaplan

en: Sample Geodata and Software for Demonstrating Geospatial Preprocessing for Forest Accessibility and Wood Harvesting at FOSS4G2019


en: snowmelt-rate snowpack-outflow stable-water-isotopes snowmelt-lysimeter solutes

en: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution. 10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

en:
This data contain volumes, solutes and isotopes of snowpack outflow measured by a snowmelt lysimeter system at three locations in the southern Alp catchment, situated Central Switzerland. The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.
The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (snowpack outflow volumes) at daily intervals from several sampling locations. Additionally, the data measured by the snowmelt lysimeter system are provided in 10-minute resolution.

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Daily data of the volumes, solutes and isotopes in snowpack outflow measured at three locations in the southern Alp catchment


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

en: Data plot of the forest station (LEB)

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

en: Site photo of the forest station (LEB)

media_type: image/jpeg

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

mimetype: image/jpeg

en: Forest station data (LEB)

media_type: text/csv

en: Data file.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for one meteorological station in Lens in Switzerland which is located within a natural coniferous forest with Scots pine (_Pinus sylvestris_; 150-170 yrs)) as dominant tree species. The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lens 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: Lens, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


en: consistent aws antarctica cryowrf python

media_type: .zip

en: Scripts to preprocess (and download for some databases) atmospheric weather station data. Furthermore, a list of stations and a map can be created to have an overview.

en:
There are many sources providing atmospheric weather station data for the Antarctic continent. However, variable naming, timestamps and data types are highly variable between the different sources. The published python code intends to make processing of different AWS sources from Antarctica easier. For all datasets that are taken into account variables are renamed in a consistent way. Data from different sources can then be handled in one consistent python dictionary.

The following data sources are taken into account:

* AAD: Australian Antarctic Division (https://data.aad.gov.au/aws)
* ACECRC: Antarctic Climate and Ecosystems Cooperative Research Centre by the Australian Antarctic Division
* AMRC: Antarctic Meteorological Research Center (ftp://amrc.ssec.wisc.edu/pub/aws/q1h/)
* BAS: British Antarctic Survey (ftp://ftp.bas.ac.uk/src/ANTARCTIC_METEOROLOGICAL_DATA/AWS/; https://legacy.bas.ac.uk/met/READER/ANTARCTIC_METEOROLOGICAL_DATA/)
* CLIMANTARTIDE: Antarctic Meteo-Climatological Observatory by the italian National Programme of Antarctic Research (https://www.climantartide.it/dataaccess/index.php?lang=en)
* IMAU: Institute for Marine and Atmospheric research Utrecht (Lazzara et al., 2012), https://www.projects.science.uu.nl/iceclimate/aws/antarctica.ph
* JMA: Japan Meteorological Agency (https://www.data.jma.go.jp/antarctic/datareport/index-e.html)
* NOAA: National Oceanic and Atmospheric Administration (https://gml.noaa.gov/aftp/data/meteorology/in-situ/spo/)
* Other/AWS_PE: Princess Elisabeth (PE), KU Leuven, Prof. N. van Lipzig, personal communication
* Other/DDU_transect: Stations D-17 and D-47 (in transect between Dumont d’Urville and Dome C, Amory, 2020)
* PANGAEA: World Data Center (e.g. König-Langlo, 2012)

Important notes

* Information about data sources is available. Some downloading scripts are included in the provided code. However, users should make sure to comply with the data providers terms and conditions.
* Given changing download options of the differnent institutions the above links may not permanently work and data has to be retrieved by the user of this dataset.
* No quality control is applied in the provided preprocessing software - quality control is up to the user of the datasets. Some dataset are quality controlled by the owner.

Acknowledgements
--------------------------
We thank all the data providers for making the data publicly available or providing them upon request. Full acknowledgements can be found in Gerber et al., submitted.

References
---------------
Amory, C. (2020). “Drifting-snow statistics from multiple-year autonomous measurements in Adélie Land, East
Antarctica”. The Cryosphere, 1713–1725. doi: 10.5194/tc-14-1713-2020

Gerber, F., Sharma, V. and Lehning, M.: CRYOWRF - a validation and the effect of blowing snow on the Antarctic SMB, JGR - Atmospheres, submitted.

König-Langlo, G. (2012). “Continuous meteorological observations at Neumayer station (2011-01)”. Alfred Wegener
Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA, doi: 10.1594/PANGAEA.
775173

antarctica

display_name: antarctica

aws

display_name: aws

consistent

display_name: consistent

cryowrf

display_name: cryowrf

python

display_name: python

en: Preprocessing Antarctic Weather Station (AWS) data in python


maintainer: Thorsten Bartels-Rausch

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

en: Matlab Script to view and plot data

media_type: .m

en: Ozone data

media_type: dat

en: Trend of ozone mixing ratio ( _O3mixingRatio_ppb_ with time ( _time_s_ ) as measured downstream of the snow sample during the experiments. Time "0" denotes the time when data acquisition with ozone analyser was started. And, ozone (_nOzone_molec_per_s_ ) loss for each experiment with duration of ozone exposure ( _duration_s_ ) of ozone exposure, as derived from the ozone trends shown above. Time "0" denotes the time when the carrier gas with ozone was passed via the snow sample.

en: Data Figure 1

en: Data of published Figure

en: Readme file

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

en: Matlab Data

media_type: mat

en: All data as Matlab mat file

en: Acetone data

en:
intensity of the acetone-water-cluster and water-cluster (as derived by a chemical ionisation mass spectrometer) with time in the carrier gas downstream of packed bed flow tube holding the snow sample or the by-pass, respectively. Time "0" denotes the time when the mass spectrometer data acquisition was started. When the carrier
gas with acetone was passed via the packed bed flow tube, that is switched from by-pass to pass the snow, acetone concentration in the carrier gas rapidly dropped due to surface adsorption and slowly recovered as the adsorption sites saturate. From this, the surface area can be obtained.

en: data list

en: Lists file names, snow sample properties, and flow settings for each data-set.

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

alpine

display_name: alpine

arctic

display_name: arctic

brine

display_name: brine

chemistry

display_name: chemistry

heterogeneous

display_name: heterogeneous

interface

display_name: interface

laboratory-study

display_name: laboratory-study

metamorphism

display_name: metamorphism

ozone

display_name: ozone

reaction

display_name: reaction

snow

display_name: snow

solution

display_name: solution

education

en: Education and science

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


maintainer: Henning Löwe

en: grain-shape fast-sintering angle-of-repose granular-snow discrete-element-modelling

en: Angle of repose and 3D CT images

en:
5 Snow types were examined and glass beads as a cohesion-less reference, named as follows:

RG: rounded grains (sieved with 0.7 - 1.4 mm)

FC: faceted grains (1.4 - 2 mm)

FCS: small faceted grains (0.7 - 1.4 mm)

IB: ice beads (4 mm)

IBS: small ice beads (2 - 2.2 mm)

GB: glass beads(2 mm)

en:
Angle of repose experiments were performed with different snow types at temperatures between -2 and -40°C. They were used to examine granular snow dynamics on the grain-scale with focus on the role of grain shape and cohesion. The angle of repose was observed by sieving snow onto a round, freestanding base until a stationary heap was formed.

This dataset consists of 1) the images of the experimental heaps that were taken to determine the angle of repose, 2) one binary 3D micro computed tomography image of each snow type. The CT images were taken with the SLF micro-CT40 to characterize snow properties and grain shape.

The experiments with natural snow types (rounded and faceted grains) and spherical model snow allowed for an examination of the differences in granular properties between natural grain shapes and spherical particles in view of Discrete Element Modelling. With the chosen temperatures, the effect of sintering could be observed that increases the angle of repose with increasing temperature.

angle-of-repose

display_name: angle-of-repose

discrete-element-modelling

display_name: discrete-element-modelling

fast-sintering

display_name: fast-sintering

grain-shape

display_name: grain-shape

granular-snow

display_name: granular-snow

envidat

en: EnviDat: the Environmental Data Portal

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

en: Angle of repose experiments with natural and spherical snow


en: satellite hazard-mapping avalanche natural-hazard snow

en: SPOT6 Avalanche outlines 24 January 2018

media_type: SHP

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

format: SHP

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

The generation of the data is described in:

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

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

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

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

Koordinate System: CH1903+ LV95 LN02

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite


maintainer: EnviDat

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

en: MeteoIO (future reference implementation)

media_type: text/html

format: HTML

mimetype: text/html

en: NEAD syntax v0.1 (EBNF)

en: PyNEAD (future reference implementation)

en: NEAD on GitHub

media_type: HTML

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

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

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

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

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

csv

display_name: csv

metadata-convention

display_name: metadata-convention

meteorological-data-format

display_name: meteorological-data-format

nead

display_name: nead

research-data-management

display_name: research-data-management

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


maintainer: Matthias Haeni

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

en: Data plot of the field station (ISF)

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

en: Forest station data (ISB)

en: Data file.

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: Site photo of the field station (ISF)

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

en: Field station data (ISF)

en: Site photo of the forest station (ISB)

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

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

education

en: Education and science

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


snow-drift-station-snow-and-air-data

maintainer: Benjamin Walter

title_for_slug: snow-drift-station-snow-and-air-data

en: snow raclets snow-depth snow-height snow-temperature temperature

en: Snow Surface Temperature

en: The snow surface temperature (°C) was measured with a Campbell SI-111 at 0.7 m above ground. The time is given in UTC+1.

en: Snow Depth

en: The snow depth (cm) was measured with a Lufft SHM-31 which was mounted at 1.7 m above ground. The time is given in UTC+1.

en: Relative Humidity

en: The relative humidity (%) was measured with a Campbell CS-215 at a height of 2.2 m above ground. The time is given in UTC+1.

en: Air Temperature

en: The air temperature (°C) was measured with a Campbell CS-215 which was mounted at a height of 2.2 m above ground. The time is given in UTC+1.

en: Snow and air data was monitored at Gotschnagrat (LON: 46.859 LAT: 9.849) by an infrarot radiometer (Campbell SI-111) for snow temperature (°C), a snow height sensor (Lufft SHM-31) for snow height change (cm) and a temperature and humidity sensor (Campbell CS-215) for air temperature (°C) and relative humidity (%). No filter was applied to the sensors and the smapling frequency was 1 Hz.

raclets

display_name: raclets

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-height

display_name: snow-height

snow-temperature

display_name: snow-temperature

envidat

en: EnviDat: the Environmental Data Portal

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

en: Snow Drift Station - Snow and Air Data


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

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

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

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


maintainer: Mountain Hydrology and Mass Movements

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

media_type: CSV

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

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

education

en: Education and science

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


en: biogeography forest-management soil-impacts biodiversity pairwise-stand-comparisons

en: references

media_type: XLS

en: Bibliography of all references cited in data_wohlgemuth_etal_Neobiota_2022.

en: headers

media_type: ascii, tab separated, also as excel table

en: Description of headers for data_wohlgemuth_etal_Neobiota_2022

en: Baseline data

en: Compiled data on the impacts of seven important NNTs (Acacia dealbata, Ailanthus altissima, Eucalyptus globulus, Prunus serotina, Pseudotsuga menziesii, Quercus rubra, Robinia pseudoacacia) on physical and chemical soil and biodiversity in Europe, and summarise commonalities and differences. A total of 107 publications considered, studies referred to biodiversity attributes and soil properties: 2804 lines and 30 rows.

biodiversity

display_name: biodiversity

biogeography

display_name: biogeography

forest-management

display_name: forest-management

pairwise-stand-comparisons

display_name: pairwise-stand-comparisons

soil-impacts

display_name: soil-impacts

en: Impact of non-native tree species in Europe on soil properties and biodiversity: a review


en: model sediment-transport erosion snow mars

media_type: text/plain

en: Datasets of Figure 2

en: Datasets of Figure 4b

en: Datasets of Figure 3a

en: Datasets of Figure 3b

en: Datasets of Figure 4a

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

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

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow

envidat

en: EnviDat: the Environmental Data Portal

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

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