reisezeit-zu-zentren-mit-dem-miv

en: Transport

title_for_slug: reisezeit-zu-zentren-mit-dem-miv

de: personenverkehr individualverkehr verkehrsnetze bgdi-bundesgeodaten-infrastruktur

it: geocat.ch link permanente

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

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

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

fr: Aperçu map.geo.admin.ch

en: Preview map.geo.admin.ch

it: Previsione map.geo.admin.ch

fr: Service WMS-IFDG, couche "Temps de parcours aux centres route"

de: WMS-BGDI Dienst, Layer "Reisezeit zu Zentren Strasse"

en: WMS-FSDI service, layer "Travel time to centres by road"

it: Servizio WMS-IFDG, strato "Tempo di viaggio verso centri strada"

fr: Service WMTS-IFDG, couche , Layer "Temps de parcours aux centres route"

de: WMTS-BGDI Dienst, Layer "Reisezeit zu Zentren Strasse"

en: WMTS-FSDI service, layer "Travel time to centres by road"

it: Servizio WMTS-IFDG, strato "Tempo di viaggio verso centri strada"

fr: Serveur de téléchargement de geo.admin.ch

de: Datenzugang

en: Download server from geo.admin.ch

it: Server di download di geo.admin.ch

fr: RESTful API de geo.admin.ch

de: RESTful API von geo.admin.ch

fr: Temps de parcours vers les 6 grands centres Bâle, Berne, Genève, Lausanne, Lugano et Zurich sur le réseau routier. Le temps de parcours est déterminé à partir de chaque zone de transport jusqu'au centre le plus rapidement accessible. Source : Modèle national du trafic voyageurs (MNTP) du DETEC.

de: Reisezeit zu den 6 grossen Zentren Basel, Bern, Genf, Lausanne, Lugano und Zürich auf dem Strassennetz. Von jeder Verkehrszone aus wird die Reisezeit zum am schnellsten erreichbaren Zentrum bestimmt. Quelle: Nationales Personenverkehrsmodell (NPVM) des UVEK.

en: Travel time to the 6 major centres of Basel, Bern, Geneva, Lausanne, Lugano and Zurich on the road network. From each traffic zone, the travel time to the fastest accessible centre is determined. Source: National Passenger Traffic Model (NPVM) of DETEC.

it: Tempo di viaggio verso i 6 grandi centri di Basilea, Berna, Ginevra, Losanna, Lugano e Zurigo sulla rete stradale. Da ogni zona di traffico viene determinato il tempo di viaggio verso il centro accessibile più veloce. Fonte: Modello del traffico viaggiatori a livello nazionale (MTVN) del DATEC.

de: Bundesamt für Raumentwicklung

en: Federal Office for Spatial Development

bundesamt-fur-raumentwicklung-are

de: Bundesamt für Raumentwicklung ARE

it: Ufficio federale dello sviluppo territoriale ARE

de: Das ARE ist die Fachbehörde des Bundes für Fragen der räumlichen Entwicklung, für die Verkehrspolitik, die nachhaltige Entwicklung sowie die transnationale Zusammenarbeit in räumlichen Belangen.

fr: Temps de parcours vers 6 grands centres par la route

de: Reisezeit zu 6 grossen Zentren auf der Strasse

en: Travel time to 6 major centres by road

it: Tempo di viaggio verso 6 grandi centri su strada


regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

tran

fr: Transports

de: Verkehr

it: Trasporti

author: Bundesamt für Raumentwicklung

fr: Web-SIG ARE

de: Web-GIS ARE

it: Web-SIG ARE

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

state: active

type: dataset

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

de: Vorschau map.geo.admin.ch

format: SERVICE

fr: Service WMS-IFDG, couche "Temps de parcours aux agglos route"

de: WMS-BGDI Dienst, Layer "Reisezeit zu Agglos Strasse"

en: WMS-FSDI service, layer "Travel time to agglos by road"

it: Servizio WMS-IFDG, strato "Tempo di viaggio verso agglo strada"

format: WMS

fr: Service WMTS-IFDG, couche , Layer "Temps de parcours aux agglos route"

de: WMTS-BGDI Dienst, Layer "Reisezeit zu Agglos Strasse"

en: WMTS-FSDI service, layer "Travel time to agglos by road"

it: Servizio WMTS-IFDG, strato "Tempo di viaggio verso agglo strada"

format: WMTS

fr: Accès aux données

format: HTML

en: RESTful API from geo.admin.ch

it: RESTful API da geo.admin.ch

format: API

fr: Temps de parcours vers les agglomérations et les communes-centres hors agglomérations sur le réseau routier. Le temps de parcours a été déterminé à partir de chaque zone de transport jusqu'à l'agglomération ou la commune-centre la plus rapidement accessible. Source : Modèle national du trafic voyageurs (MNTP) du DETEC.

de: Reisezeit zu Agglomerationen und Kerngemeinden ausserhalb der Agglomerationen auf dem Strassennetz. Von jeder Verkehrszone aus wird die Reisezeit zur am schnellsten erreichbaren Agglomeration resp. Kerngemeinde bestimmt. Quelle: Nationales Personenverkehrsmodell (NPVM) des UVEK.

en: Travel time to agglomerations and core communities outside the agglomerations on the road network. From each traffic zone, the travel time to the fastest accessible agglomeration or core municipality is determined. Source: National Passenger Transport Model (NPVM) of DETEC.

it: Tempo di viaggio verso gli agglomerati e le comunità principali al di fuori degli agglomerati sulla rete stradale. Da ogni zona di traffico, viene determinato il tempo di percorrenza per raggiungere l'agglomerato o il nucleo del comune più velocemente accessibile. Fonte: Modello del traffico viaggiatori a livello nazionale (MTVN) del DATEC.

spatial: Schweiz

it: Ufficio federale dello sviluppo territoriale

bundesamt-fur-raumentwicklung-are

fr: Office fédéral du développement territorial ARE

en: Federal Office for Spatial Development ARE

fr: L'ARE est le centre de compétences de la Confédération pour les questions liées au développement territorial, à la politique des transports, au développement durable ainsi qu'à la coopération transnationale en matière de territoire.

en: The ARE is the federal government's centre of excellence for issues concerning spatial development, transport policy, sustainable development and international cooperation in spatial planning matters.

it: L'ARE è l'autorità federale responsabile per le questioni di sviluppo territoriale, politica dei trasporti, sviluppo sostenibile e collaborazione transnazionale in ambito territoriale.

political_level: confederation

type: organization

approval_status: approved

value: ARE - Geocat Harvester

fr: Temps de parcours vers les agglomérations et communes-centres par la route

de: Reisezeit zu Agglomerationen und Kerngemeinden auf der Strasse

en: Travel time to agglomerations and core communities by by road

it: Tempo di viaggio verso gli agglomerati e le comunità principali su strada


tran

en: Transport

de: personenverkehr offentlicher-verkehr verkehrsnetze bgdi-bundesgeodaten-infrastruktur

it: geocat.ch link permanente

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

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

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

fr: Aperçu map.geo.admin.ch

it: Previsione map.geo.admin.ch

fr: Service WMS-IFDG, couche "Temps de parcours aux agglos TP"

de: WMS-BGDI Dienst, Layer "Reisezeit zu Agglos ÖV"

en: WMS-FSDI service, layer "Travel time to agglos by PT"

it: Servizio WMS-IFDG, strato "Tempo di viaggio verso agglo TP"

fr: Service WMTS-IFDG, couche , Layer "Temps de parcours aux agglos TP"

de: WMTS-BGDI Dienst, Layer "Reisezeit zu Agglos ÖV"

en: WMTS-FSDI service, layer "Travel time to agglos by PT"

it: Servizio WMTS-IFDG, strato "Tempo di viaggio verso agglo TP"

de: Datenzugang

fr: Temps de parcours vers les agglomérations et les communes-centres hors agglomération en transports publics. Le temps de parcours est déterminé à partir de chaque zone de transport jusqu'à l'agglomération ou la commune-centre la plus rapidement accessible. Source : Modèle national du trafic voyageurs (MNTP) du DETEC.

de: Reisezeit zu Agglomerationen und Kerngemeinden ausserhalb der Agglomerationen mit dem öffentlichen Verkehr. Von jeder Verkehrszone aus wird die Reisezeit zur am schnellsten erreichbaren Agglomeration resp. Kerngemeinde bestimmt. Quelle: Nationales Personenverkehrsmodell (NPVM) des UVEK.

en: Travel time to agglomerations and core communities outside the agglomerations by public transport. From each traffic zone, the travel time to the fastest accessible agglomeration or core municipality is determined. Source: National Passenger Transport Model (NPVM) of DETEC.

it: Tempo di viaggio verso gli agglomerati e le comunità principali al di fuori degli agglomerati con i mezzi pubblici. Da ogni zona di traffico, viene determinato il tempo di percorrenza per raggiungere l'agglomerato o il nucleo del comune più velocemente accessibile. Fonte: Modello del traffico viaggiatori a livello nazionale (MTVN) del DATEC.

fr: Office fédéral du développement territorial

fr: Temps de parcours vers les agglomérations et communes-centres en transports publics

de: Reisezeit zu Agglomerationen und Kerngemeinden mit dem öffentlichen Verkehr

en: Travel time to agglomerations and core communities by public transport

it: Tempo di viaggio verso gli agglomerati e le comunità principali con i trasporti pubblici


elektro-leitungen

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

regi

fr: Régions et villes

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: elektro-leitungen

author: Elektrizitätswerke

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

format: WFS

fr: Elektro Trasse, Bauwerke und Trassepunkte.

spatial: Canton of Uri (UR)

fr: Elektrizitätswerke

de: Elektrizitätswerke

en: Elektrizitätswerke

it: Elektrizitätswerke

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

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

political_level: canton

kanton-uri

capacity: public

value: Uri-Kt - Geocat Harvester

fr: Elektro Leitungen

de: Elektro Leitungen

en: Elektro Leitungen

it: Elektro Leitungen


swisscom-leitungen

regi

de: Regionen und Städte

en: Regions and cities

title_for_slug: swisscom-leitungen

author: Swisscom

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

fr: Swisscom Leitungen, Bauwerke und Schächte

fr: Swisscom

de: Swisscom

en: Swisscom

it: Swisscom

fr: Swisscom Leitungen

de: Swisscom Leitungen

en: Swisscom Leitungen

it: Swisscom Leitungen


gestaltungsplane-perimeter

title_for_slug: gestaltungsplane-perimeter

de: eigentumsbeschrankungoreb nutzungsplanung raumplanung sondernutzungsplanung

author: Kanton Luzern, Abteilung Geoinformation

it: geocat.ch link permanente

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: Geltungsbereiche (Perimeter) von Gestaltungsplänen, welche eine siedlungsgerechte, architektonisch und erschliessungstechnisch gute Überbauung eines zusammenhängenden Gebietes sicherstellen.

spatial: Kanton Luzern

de: Kanton Luzern, Abteilung Geoinformation

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

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

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

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

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

value: LU-Kt - Geocat Harvester

de: Gestaltungspläne: Geltungsbereiche


envi

de: Umwelt

de: abfall altlasten betriebe boden eigentumsbeschrankungoreb risiken umweltbeobachtung umweltschutz wirtschaftliche-aktivitaten

de: Altlasten sind belastete Standorte, die wegen der Auswirkungen auf die Umwelt saniert werden müssen.

de: Kataster der belasteten Standorte (KbS)


name: Fachstelle Open Government Data des Kantons Zürich

fr: Repository: Formale Leitlinien zur Datenpublikation des Kantons Zürich

fr: Fachausschuss für offene Behördendaten: Standards

de: Leitlinien des Kantons Zürich für einfach nutzbare Behördendaten (Version 1.0)

media_type: text/html

de: Version 1.0 in Kraft seit dem 16. Dezember 2021.

de: Handlungsleitende Normen, um offene Behördendaten ('Open Government Data', OGD) bereitzustellen, die einfach nutzbar sind. Der Fachausschuss Open Government Data des Kantons Zürich verwaltet die Normen gemäss der Maxime, den Bedürfnissen der Nutzenden zweckmässig und wirtschaftlich zu entsprechen. Die Fach- und Koordinationsstelle Open Government Data nimmt Feedback (Hinweise, Wünsche und Fragen) zu den Leitlinien entgegen. Entweder als 'Issue' im Repository (verlinkt unter 'Weitere Informationen') oder via E-Mail (verlinkt unter 'Kontakt'). Im Austausch mit den Nutzenden klärt sie deren Bedürfnisse, berät mit den Datenverwaltenden ('Data Custodians') mögliche Lösungen und schlägt diese vierteljährlich dem Fachausschuss zur Inkraftsetzung vor.

fachstelle-ogd-kanton-zuerich

de: Fach- und Koordinationsstelle Open Government Data Kanton Zürich

de: Die Fach- und Koordinationsstelle Open Government Data (OGD) ist das kantonale Kompetenzzentrum für offene Behördendaten im Statistischen Amt. Wir unterstützen die Organisationseinheiten und Organe des Kantons bei der Bereitstellung ihrer nicht schützenswerten Daten als Open Data.

key: guid

key: uri

value: ZH-Kt Fachstelle OGD - DCAT Harvester


de: Datenstruktur auf Deutsch

en: Data structure in German

media_type: application/json

format: JSON

de: Datenwürfel auf Deutsch

en: Data cube in German

de: 463.005 Leistungen und Leistungen pro Unfall bei Jahr, Einheit und Versicherungszweig

accident-insurers

display_name: accident-insurers

unfallversicherer

display_name: unfallversicherer

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

political_level: other

value: DCAT Harvester Amt für Statistik FL

de: 463.005 Leistungen und Leistungen pro Unfall nach Versicherungszweig seit 2005


wasserrechte

regi

fr: Régions et villes

de: Regionen und Städte

envi

de: Umwelt

en: Environment

title_for_slug: wasserrechte

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

author: Kanton Zürich

de: geocat.ch Permalink

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

fr: Öffentliche Oberflächengewässer, Gewässerraum und Wasserrechte

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

spatial: Kanton Zürich

fr: Kanton Zürich

de: Kanton Zürich

en: Kanton Zürich

it: Kanton Zürich

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

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

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

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

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

value: ZH - Geocat Harvester

fr: Wasserrechte

de: Wasserrechte

en: Wasserrechte

it: Wasserrechte


abfallanlagen-und-sammelstellen

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

regi

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

title_for_slug: abfallanlagen-und-sammelstellen

de: abfall-sammelstelle abfallanlage

author: Geoinformation Stadt Bern

fr: geocat.ch permalien

fr: Map (Preview)

de: Map (Preview) Stadtplan

en: Map (Preview)

it: Map (Preview)

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

de: Abfallsammelstellen

de: Web Map Services WMS

de: WFS Abfallsammelstellen

de: Web Feature Services WFS

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

spatial: Stadt Bern

de: Geoinformation Stadt Bern

geoinformation-der-stadt-bern

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

en: The Land Surveying Office of the City of Bern

it: L'ufficio del catasto nella Città di Berna

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

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

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

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

political_level: commune

value: Geoinformation Stadt Bern - Geocat Harvester

de: Abfallanlagen und Sammelstellen


okoinfomobil

regi

de: Regionen und Städte

envi

de: Umwelt

it: Ambiente

title_for_slug: okoinfomobil

de: oekomobil okomobil

de: geocat.ch Permalink

en: geocat.ch permalink

de: OekoInfoMobil

de: WFS OekoInfoMobil

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

de: ÖkoInfoMobil


ener

de: Energie

author: Abteilung Energie

de: AGIS Direktdownload

de: Stromversorgungssicherheit: Netzebene 5

de: Das Modell beinhaltet alle 110 Elektrizitätsunternehmen des Kantons als Polygone. Mit der Änderung des Energiegesetzes vom 03.12.2004 wurde die Versorgungssicherheit im Stromversorgungsnetz zum Ausdruck gebracht (StromVG, SR 734.7). Die Kantone sind daher verpflichtet, Netzgebiete und deren Netzbetreiber zu nennen (Art. 5 Abs. 1 StromVG). Das Bundesmodell CH-183 verfügt über eine kantonale Erweiterung, welche im Modell AG-92 umgesetzt wird. Die kantonale Erweiterung beinhaltet Kontaktdaten über die einzelnen Elektrizitätsunternehmen (Webseite, allgemeine Telefonnummer und Email-Adresse des Unternehmens).

de: Abteilung Energie

de: AGIS Service Center Kanton Aargau

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

value: Aargau-Kt - Geocat Harvester


de: Stromversorgungssicherheit: Netzebene 7

de: Das Modell beinhaltet alle 110 Elektrizitätsunternehmen des Kantons als Polygone der Netzebene 7. Mit der Änderung des Energiegesetzes vom 03.12.2004 wurde die Versorgungssicherheit im Stromversorgungsnetz zum Ausdruck gebracht (StromVG, SR 734.7). Die Kantone sind daher verpflichtet, Netzgebiete und deren Netzbetreiber zu nennen (Art. 5 Abs. 1 StromVG). Das Bundesmodell CH-183 verfügt über eine kantonale Erweiterung, welche im Modell AG-92 umgesetzt wird. Die kantonale Erweiterung beinhaltet Kontaktdaten über die einzelnen Elektrizitätsunternehmen (Webseite, allgemeine Telefonnummer und Email-Adresse des Unternehmens).


regi

de: Regionen und Städte

de: Stromversorgungssicherheit: Netzebene 3

de: Das Modell beinhaltet alle 110 Elektrizitätsunternehmen des Kantons als Polygone auf der Netzebene 3. Mit der Änderung des Energiegesetzes vom 03.12.2004 wurde die Versorgungssicherheit im Stromversorgungsnetz zum Ausdruck gebracht (StromVG, SR 734.7). Die Kantone sind daher verpflichtet, Netzgebiete und deren Netzbetreiber zu nennen (Art. 5 Abs. 1 StromVG). Das Bundesmodell CH-183 verfügt über eine kantonale Erweiterung, welche im Modell AG-92 umgesetzt wird. Die kantonale Erweiterung beinhaltet Kontaktdaten über die einzelnen Elektrizitätsunternehmen (Webseite, allgemeine Telefonnummer und Email-Adresse des Unternehmens).


soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

educ

de: Bildung, Kultur und Sport

envi

de: Umwelt

de: geocat.ch Permalink


grundwasservorkommen

title_for_slug: grundwasservorkommen

de: geodaten gewasser grundwasser

en: geodata water-geographic groundwater

it: geocat.ch link permanente

de: Grundwasserkarte

de: ThurGIS Shop

de: Der Geobasisdatensatz beinhaltet die potenziell nutzbaren und genutzten Grundwasservorkommen. Sie sind Bestandteil der Grundwasserkarte und der Gewässerschutzkarte.

spatial: Kanton Thurgau (TG)

fr: Kanton Thurgau, Amt für Geoinformation

de: Kanton Thurgau, Amt für Geoinformation

en: Kanton Thurgau, Amt für Geoinformation

kanton-thurgau

fr: Canton de Thurgovie

de: Kanton Thurgau

en: Canton of Thurgau

it: Cantone di Turgovia

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

value: TG-Kt - Geocat Harvester

de: Grundwasservorkommen


friedhofe

regi

fr: Régions et villes

title_for_slug: friedhofe

de: bremgartenfriedhof bumplizfriedhof friedhof friedhofe schosshaldenfriedhof

author: Stadtgrün Bern

de: Map (Preview) Stadtplan

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

de: Friedhoefe

de: Web Map Services WMS

de: WFS Friedhoefe

de: Web Feature Services WFS

de: Friedhofstandorte (Punkte) und deren Perimeter (Flächen) in der Stadt Bern.

de: Stadtgrün Bern

geoinformation-der-stadt-bern

de: Geoinformation Stadt Bern

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

de: Friedhöfe


wohnbauprojekte

regi

de: Regionen und Städte

envi

de: Umwelt

title_for_slug: wohnbauprojekte

de: gemeinnutzige-wohnbautrager preisgunstiger-wohnungsbau wohnbaustrategie wohnen-in-der-stadt-bern wohnnutzung wohnpolitik wohnraum wohnstadt-bern wohnstrategie wohnungsbau

author: Stadtplanungsamt Bern

de: geocat.ch Permalink

de: Wohnbauprojekte

de: WFS Wohnbauprojekte

de: Die von der Fachstelle Wohnbauförderung erfassten Wohnbauprojekte in der Stadt Bern werden je nach Projektstand farblich unterschiedlich angezeigt.

de: Stadtplanungsamt Bern


infostande-und-kastanienkioske

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

title_for_slug: infostande-und-kastanienkioske

de: WFS Infostaende_und_Kastanienkioske

de: Standorte für bewilligte Infostände und Kastanienkioske ("Marronistände") im Stadtgebiet Bern.

de: Infostände und Kastanienkioske


parkanlagen

soci

de: Bevölkerung und Gesellschaft

educ

de: Bildung, Kultur und Sport

title_for_slug: parkanlagen

de: grunanlage grunflache park parkanlage

de: Map (Preview) Stadtplan

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

de: Parkanlagen

de: Web Map Services WMS

de: WFS Parkanlagen

de: Web Feature Services WFS

de: Standorte von Parkanlagen in der Stadt Bern.


schwarzplan

regi

de: Regionen und Städte

envi

de: Umwelt

en: Environment

title_for_slug: schwarzplan

de: av grundkarte hintergrundkarte

de: geocat.ch Permalink

de: Schwarzplan

de: WMTS Schwarzplan

de: Web Map Tile Services WMTS

de: Die Gebäudeflächen aus der Bodenbedeckung der Amtlichen Vermessung schwarz eingefärbt bilden eine einfache Grundkarte "Schwarzplan".

de: Geoinformation Stadt Bern

geoinformation-der-stadt-bern

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


ov-haltestellen

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: ov-haltestellen

de: bus poi tram ov offentlicher-verkehr

de: Map (Preview) Stadtplan

de: Haltestellen

de: WFS Haltestellen

de: Standorte Tram- und Bushaltestellen sowie Drahtseilbahnstationen in der Stadt Bern und Agglomeration.

spatial: Agglomeration Bern

de: ÖV-Haltestellen


vde-schleifen

regi

de: Regionen und Städte

title_for_slug: vde-schleifen

de: induktionsschleifen schleifen vde verkehrsdaten verkehrsdatenerfassung verkehrszahlung

de: Web Map Services WMS

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

de: Tiefbau Stadt Bern

de: VDE-Schleifen


akustische-ubergangssignale

soci

de: Bevölkerung und Gesellschaft

educ

de: Bildung, Kultur und Sport

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

title_for_slug: akustische-ubergangssignale

author: Tiefbauamt Stadt Bern

de: geocat.ch Permalink

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

de: WFS Akustische_Uebergangssignale

de: Web Feature Services WFS

de: Akustische Signale für Menschen mit Sehbehinderungen bei Zebrastreifen.

de: Akustische Übergangssignale


stadtplan-darstellung-schwarz-weiss

envi

de: Umwelt

title_for_slug: stadtplan-darstellung-schwarz-weiss

de: av grundkarte hintergrundkarte

de: Map (Preview) Stadtplan

de: WMTS Stadtplan_schwarzweiss

de: Web Map Tile Services WMTS

de: WFS Stadtplan_schwarzweiss

de: Schwarz/weisse, einfache Darstellung basierend auf den Daten der amtlichen Vermessung.

de: Geoinformation Stadt Bern

geoinformation-der-stadt-bern

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

de: Stadtplan (Darstellung schwarz/weiss)


stadtplan-darstellung-farbig

regi

de: Regionen und Städte

title_for_slug: stadtplan-darstellung-farbig

de: Web Map Services WMS

de: WMTS Stadtplan_farbig

de: WFS Stadtplan_farbig

de: Farbige, einfache Darstellung basierend auf den Daten der amtlichen Vermessung.

de: Stadtplan (Darstellung farbig)


stadtverwaltung

soci

de: Bevölkerung und Gesellschaft

educ

de: Bildung, Kultur und Sport

title_for_slug: stadtverwaltung

de: poi stadtverwaltung

de: geocat.ch Permalink

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

de: Stadtverwaltungen

de: WFS Stadtverwaltungen

de: Web Feature Services WFS

de: Standorte der Stadtverwaltung.

de: Stadtverwaltung


baulinienkataster

envi

de: Umwelt

title_for_slug: baulinienkataster

de: Map (Preview) Stadtplan

de: Baulinienkataster

de: Baulinien zeigen, wo auf einer Parzelle gebaut werden darf und welche Bereiche für öffentliche Anlagen wie Strassen, Grünstreifen, Leitungsbauten usw. frei gehalten werden müssen. Die Baulinien werden nach Art und Status unterschieden.

de: Stadtplanungsamt Bern

geoinformation-der-stadt-bern

de: Geoinformation Stadt Bern

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


signalisierte-hochstgeschwindigkeit

regi

de: Regionen und Städte

tran

de: Verkehr

title_for_slug: signalisierte-hochstgeschwindigkeit

de: Web Map Services WMS

de: Geltende Höchstgeschwindigkeit pro Strassenabschnitt. Anfangs- und Endpunkte werden von den Signalstandorten auf die Strassenachsen projiziert.

de: Tiefbau Stadt Bern

de: Signalisierte Höchstgeschwindigkeit


baumschutzzonen

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

title_for_slug: baumschutzzonen

de: baumschutz baumschutzreglement baumschutzzone schutzzone uberbauungsordnung

de: geocat.ch Permalink

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

de: Baumschutzzonen

de: Baumschutzzonen gemäss Baumschutzreglement der Stadt Bern.

de: Stadtgrün Bern


de: Datenshop

de: Produktansicht Geodatenshop

de: Ausnahmetransportrouten sind Strassen, welche auf höhere Grenzen dimensioniert werden, damit sie von bewilligungspflichtigen Ausnahmetransporten befahren werden können.

de: Kanton Luzern, Abteilung Geoinformation

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

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

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

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

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

de: Ausnahmetransportrouten


soci

de: Bevölkerung und Gesellschaft

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

regi

de: Regionen und Städte

de: eigentumsbeschrankungoreb gebaude-und-anlagen kulturdenkmal kulturguterschutz nutzungsplanung ortsbildschutz zonenplan

de: Im Bauinventar werden schützens- und erhaltenswerte Baudenkmäler erfasst. Besonders schutzwürdige Kulturobjekte werden ins kantonale Denkmalverzeichnis eingetragen und unter Schutz gestellt.

de: Kantonales Denkmalverzeichnis und Bauinventar


maintainer: Felix Kienast

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

media_type: application/zip

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

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

format: ZIP

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

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

Headers are described below:
X01 = Planning_units (PUs)

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

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

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

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

ecosystem-services

display_name: ecosystem-services

energy

display_name: energy

landscape

display_name: landscape

marxan

display_name: marxan

optimization

display_name: optimization

photovoltaic

display_name: photovoltaic

social-acceptance

display_name: social-acceptance

spatial-planning

display_name: spatial-planning

wind-power

display_name: wind-power

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.

value: Envidat Harvester

en: Optimizing renewable energy siting in the Swiss landscape


maintainer: Yohann Chauvier

en: climate soil ecological-indicator-values grain-size taxonomic-diversity phylogenetic-diversity functional-diversity

en: Data access

en:
This dataset comprises a large array of ecological data for the European Alps:

  (1) Current soil and climate predictors at various resolutions.
  (2) GBIF observations of the European Alps Flora (~4,000 species).
  (3) Species habitat suitability maps (1,109 species; based on species observations filtered at 40x40-km)
  at various resolutions used in the study to generate (4); except 'expert'...
  (4) Expert, Taxonomic, phylogenetic and functional diversity of the study region at various resolutions
  (from 100-m to 40-km --> 100-m aggregated & mean to km + non-aggregated/predicted) for CLIM,
  SOIL and CLIM-SOIL models.
  (5) Ecological and altitudinal preferences of the European Alps Flora.
  (6) Data outputs of the related published article.
  (7) All scripts used for analyses.
  (8) Additional files used for analyses.
  (9) Improved set of species habitat suitability maps (~2,600 species; based on species observations
  filtered at 1x1-km) and related taxonomic diversity at 100-m resolution (aggregated to km +
  non-aggregated/predicted) for CLIM, SOIL and CLIM-SOIL models ---> not incorporated in the study.

climate

display_name: climate

ecological-indicator-values

display_name: ecological-indicator-values

functional-diversity

display_name: functional-diversity

grain-size

display_name: grain-size

phylogenetic-diversity

display_name: phylogenetic-diversity

soil

display_name: soil

taxonomic-diversity

display_name: taxonomic-diversity

educ

it: Istruzione, cultura e sport

en: Resolution in species distribution models shapes spatial patterns of plant multifaceted diversity


mountain-permafrost-hydrology

maintainer: Jeannette Noetzli

title_for_slug: mountain-permafrost-hydrology

en: mountain-permafrost-hydrology ice-rich-permafrost climate-change-impacts mass-movements permafrost-degradation monitoring-techniques

en: Synthesis report chapter of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN)

media_type: application/pdf

format: PDF

en: This report was prepared as one of the synthesis report chapters of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN). In earlier reports such as the CH2014-IMPACTS report (CH-Impacts 2014), the topic of mountain permafrost hydrology was not addressed. Here, we provide a baseline of the available knowledge of mountain permafrost in the Swiss Alps for future reference. We compile an overview of the current understanding of mountain permafrost in the Swiss Alps, its distribution and characteristics, observed and projected changes, and expected impacts on slope stability, infrastructure and hydrological aspects. We also briefly describe the measurement techniques and modelling approaches applied. The chapter closes with a summary of the most important open research questions. The literature cited mainly includes studies on mountain permafrost published in scientific journals and assessments of long-term observation data. We focus on permafrost hydrology interactions wherever information is available. However, systematic studies on permafrost hydrology in mountain areas are still limited.

climate-change-impacts

display_name: climate-change-impacts

ice-rich-permafrost

display_name: ice-rich-permafrost

mass-movements

display_name: mass-movements

monitoring-techniques

display_name: monitoring-techniques

mountain-permafrost-hydrology

display_name: mountain-permafrost-hydrology

permafrost-degradation

display_name: permafrost-degradation

en: Mountain Permafrost Hydrology


tree-species-map-of-switzerland

maintainer: Tiziana Li Koch

title_for_slug: tree-species-map-of-switzerland

en: switzerland remote-sensing map forest tree-species

media_type: image/png

en: Image of the tree species map

format: PNG

en:
Dominant tree species map of Switzerland
We created a tree species map of Switzerland for the dominant tree species in the forested areas. The spatial resolution of the map is 10 m and the coordinate system is ETRS89-extended / LAEA Europe (EPSG 3035). The map comprises Sentinel-2 index time series from the year 2020, a digital elevation model and species reference data from the Swiss National Forest Inventory. The map is available as raster (.tif) or vector dataset (.gpkg).
**Access will be granted upon request.**
In total, the following 15 species were mapped:
*Abies alba*, *Acer pseudoplatanus*, *Alnus glutinosa*, *Alnus incana*, *Betula pendula*, *Castanea sativa*, *Fagus sylvatica*, *Fraxinus excelsior*, *Picea abies*, *Pinus cembra*, *Pinus mugo arborea*, *Pinus sylvestris*, *Quercus petraea*, *Quercus robur*, *Sorbus aucuparia*.

 Approach

 Data
- Swiss National Forest Inventory Data (stand species with > 60 % dominance in upper canopy; on at least more than 9 plots dominant)
- Sentinel-2 time series (2020, Indices: CCI, CIRE, NDMI, EVI, NDVI)
- Digital elevation model (DEM) (swissalti3d, 5 m)
- Biogeographical regions (Federal Office for the Environment FOEN)
- Forest mask 2017 (Approach: Waser et al., 2015)

 Modeling approach
We identified the most meaningful variables that led to separation of the respective groups by using random forest models with a forward feature selection (Meyer et al., 2018; Ververidis & Kotropoulos, 2005). In this approach, the final random forest model is solely built from the selected meaningful variables. By identifying meaningful variables, we can determine which variables might influence the grouping. Further, to avoid overfitting and overly optimistic results, we applied 10-fold spatial cross-validation and put all pixels from a plot in the same spatial fold.
The modeling was realized using the CAST package in R (Meyer et al., 2022), based on the well-known caret package (Kuhn, 2022). We used the ranger package in R (Wright & Ziegler, 2017) to implement the random forest models, due to its short computation time.

 Training data for modeling
- 295 Sentinel-2, DEM & Biogeographical variables
- 10525 tree species pixels

 Selected variables for final model
1. EVI of 2020.05.16
2. NDMI of 2020.03.12
3. CIRE of 2020.04.16
4. NDMI of 2020.07.05
5. CCI of 2020.05.11
6. dem
7. CCI of 2020.08.14
8. NDMI of 2020.08.24
9. CCI of 2020.12.22
10. NDMI of 2020.04.21
11. NDMI of 2020.11.17
12. NDMI of 2020.08.09
13. CIRE of 2020.03.22
14. CIRE of 2020.08.09
14. CCI of 2020.11.02
15. CIRE of 2020.06.10

 Overall Accuracy of final model
- 0.759

 Nationwide prediction
- Predicted throughout forest mask 2017 (Approach: Waser et al., 2015)
- Not applied on incomplete Sentinel-2 time series (own category in final map: incomplete_ts)
- Applied the Area of Applicability (Meyer 2022) to sort out pixels outside of the feature space; basically where the model had not the same values for pixels as in the available training data

 *Be aware that the map is only validated with the training data itself, an independent validation with other data sources remains missing*

 References
- Kuhn, M. (2022). Classification and Regression Training. 6.0-93.
- Meyer, H., Reudenbach, C., Hengl, T., Katurji, M., & Nauss, T. (2018). *Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation*. Environmental Modelling and Software, 101, 1-9. https://doi.org/10.1016/j.envsoft.2017.12.001
- Meyer, H., Milà, C., & Ludwig, M. (2022). *CAST: 'caret' Applications for Spatial-Temporal Models*. 0.7.0.
- Ververidis, D., & Kotropoulos, C. (2005). *Sequential forward feature selection with low computational cost*. 2005 13th European Signal Processing Conference.
- Waser, L., Fischer, C.,Wang, Z., & Ginzler, C. (2015). *Wall-to-Wall Forest Mapping Based on Digital Surface Models from Image-Based Point Clouds and a NFI Forest Definition*. Forests, 6, 12, 4510–4528.
- Wright, M. N., & Ziegler, A. (2017). *ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R*. Journal of Statistical Software, 77(1), 1-17. https://doi.org/doi:10.18637/jss.v077.i01

forest

display_name: forest

map

display_name: map

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

tree-species

display_name: tree-species

en: Tree species map of Switzerland


maintainer: Loïc Pellissier Pellissier

en: environmental-gradients elevation herbivores-communities functional-traits alps community-indices plant-herbivore-interactions

en: Plant traits

media_type: text/plain

en: Plant functional traits (SLA, LDMC, carbon and nitrogen content, punch strenght; averaged by species)

format: TXT

mimetype: text/plain

en: Study sites

en: Coordinates and elevation of the study sites

en: Orthoptera surveys

en: Species inventories of Orthoptera

en: Vegetion surveys

en: Species inventories of plants

en: Nematode surveys

en: Surveys of soil nematode along elevation

en: Orthoptera traits

en: Orthoptera functional traits (incisive mandibular strength averaged by species)

en: Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017.

alps

display_name: alps

community-indices

display_name: community-indices

elevation

display_name: elevation

environmental-gradients

display_name: environmental-gradients

functional-traits

display_name: functional-traits

herbivores-communities

display_name: herbivores-communities

plant-herbivore-interactions

display_name: plant-herbivore-interactions

educ

en: Education, culture and sport

en: Above- and below-ground herbivore communities along elevation


en: agri-pv speed2zero rooftop-pv alpine-pv solar-irradiance sweet-edge plane-of-array

en:
Contains seasonal and annual statistics (mean, sum) of the CH-POA300 dataset.
- "yyyy_agg_period_hourly_stat.nc": statistic <stat> for the period <agg_period> of the year <yyyy>
- "all_agg_period_stat_mean.nc": statistic <stat> for the period <agg_period> reduced on the entire dataset (all years).
\
yyyy: [2009, 2019]
agg_period: [winter, summer, annual]
stat: [mean, sum]

en: This document provides an in-depth description of the CH-POA300 dataset. It includes methodology and validation details.

en:
CH-POA300 is a set of maps of hourly solar irradiance projected onto oriented tilted surfaces, similar to monofacial solar panels, at a spatial resolution of 300m over Switzerland. Two temporal extents are available depending on the number of computed projections, i.e. azimuths and tilts combinations:
 1. Long term
 - Temporal extent: 2009-2019
 - Azimuths x Tilts: [180°] x [0°,35°,60°,90°]
 2 .Typical year
 - Temporal extent: 2016
 - Azimuths x Tilts: [0°,90°,135°,180°,225°,270°] x [0°,3°,8°, 15°, 25°, 35°, 45°, 60°, 80°, 90]
NB: Azimuth: 0°: N, 90°: E, 180°: S, 270°: W. Tilt: 0°: vertical, 90°: horizontal.
Pre-computed seasonal and annual statistics of these maps are also provided in the dataset.
Details on the method and the quality assessment can be found in the specifications (CH-POA300-v#-specs.pdf).

agri-pv

display_name: agri-pv

alpine-pv

display_name: alpine-pv

plane-of-array

display_name: plane-of-array

rooftop-pv

display_name: rooftop-pv

solar-irradiance

display_name: solar-irradiance

sweet-edge

display_name: sweet-edge

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: CH-POA300 -- Hourly Plane-of-Array Solar Irradiance at High Resolution for Switzerland


maintainer: Virginie Marques

en: switzerland vertebrates vert01 spermatophytes freshwater environmental-dna sper01 edna

en: Data access

en:
Catchment-based sampling of river eDNA integrates terrestrial and aquatic biodiversity of alpine landscapes

From 22-Jun-2020 to 26-Jun-2020, we sampled five sites comprising one low, two intermediate and two high-elevation sites per catchment (Fig. 1a). We visited two catchments per day—one in the morning and one in the afternoon—for a total of ten catchments. All samples per catchment were collected within a maximum four-hour period by three groups of samplers. The intermediate and high-elevation sites were situated along two tributaries leading into the low-elevation site of the river. We used three filters for each relative elevation class and filtered 60 L per relative elevation class. We sampled 30 L per tributary for a combined volume of 60 L at the intermediate and high-elevation sites. In total, 180 L were sampled in total per catchment. A filtration device composed of either the Athena® peristaltic pump (Proactive Environmental Products LLC; 1 L/min nominal flow) or the Subspace® underwater peristaltic pump (Subspace Pictures; 1 L/min nominal flow), combined with a VigiDNA® 0.2 µM cross-flow filtration capsule (VigiDNA, SPYGEN) was used in order to filter a large water volume. We used a finer mesh than the recommended VigiDNA® 0.45 µM cross-flow filtration capsule to maximise the capture of biological material since mountain water does not transport high quantities of sediments. For each filtration capsule, we used disposable sterile tubing. At the end of each filtration, we emptied the water inside the capsules, replaced it with 80 ml of CL1 conservation buffer (SPYGEN), and stored it at room temperature. We followed a strict contamination control protocol in both field and laboratory stages (Goldberg et al. 2016; Valentini et al. 2016). Each water sample was processed using disposable gloves and single-use filtration equipment. We used two primer sets targeting vertebrates (Vert01, forward: − TTAGATACCCCACTATGC, reverse: − TAGAACAGGCTCCTCTAG, mean marker length: 97 bp) and spermatophytes (g-h/Sper01, forward: − GGGCAATCCTGAGCCAA, reverse: CCATTGAGTCTCTGCACCTATC, mean marker length: 48 bp). Though both primers are relatively broad with low species-level resolution, we selected them as the goal was to minimise cost and effort and maximise the identification of a broad range of taxa which can represent the species assemblages of the region. Libraries were prepared with ligation using the MetaFast protocol (Fasteris).

edna

display_name: edna

environmental-dna

display_name: environmental-dna

freshwater

display_name: freshwater

spermatophytes

display_name: spermatophytes

vertebrates

display_name: vertebrates

en: Environmental DNA Freshwater Switzerland VaudCatchment Modipl 2020


maintainer: Matthias Haeni

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

en: Forest station data (BAB)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Site aerial photo (Beatenberg)

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

mimetype: image/jpeg

en: Data plot of the forest station (BAB)

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

mimetype: application/pdf

en: Field station data (BAF)

en: Data plot of the field station (BAF)

en: Site photo of the forest station (BAB)

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

en: Site photo of the field station (BAF)

en: Site photo of the field 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 Beatenberg in Switzerland where one station is located within a natural coniferous forest (BAB) with Norway spruce (_Picea abies_; 190-210 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Beatenberg 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: Beatenberg, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: EnviDat Support

en: landscape-perception outdoor-restoration traffic-noise ppgis survey

en: Coding analysis first round for article in Urban Forestry and Urban Greening [https://doi.org/10.1016/j.ufug.2025.128746](https://doi.org/10.1016/j.ufug.2025.128746)

format: XLS

en: Processed survey data of restorative locations for article in Landscape and Urban Planning [https://doi.org/10.1016/j.landurbplan.2025.105339](https://doi.org/10.1016/j.landurbplan.2025.105339)

en: Processed data for article in Urban Forestry and Urban Greening [https://doi.org/10.1016/j.ufug.2025.128746](https://doi.org/10.1016/j.ufug.2025.128746)

en: Coding analysis third round for article in Urban Forestry and Urban Greening [https://doi.org/10.1016/j.ufug.2025.128746](https://doi.org/10.1016/j.ufug.2025.128746)

en: Description of the sample stratification process for the invitation to participate in the survey

en: Cleaned raw data from survey for article in Landscape and Urban Planning [https://doi.org/10.1016/j.landurbplan.2025.105339](https://doi.org/10.1016/j.landurbplan.2025.105339)

en: RESTORE WP4_Questionnaire_German.pdf

en: Questionnaire in German

en: Raw data for article in Urban Forestry and Urban Greening [https://doi.org/10.1016/j.ufug.2025.128746](https://doi.org/10.1016/j.ufug.2025.128746)

en: RESTORE WP4_Questionnaire_French.pdf

en: Questionnaire in French

en: Coding analysis second round for article in Urban Forestry and Urban Greening [https://doi.org/10.1016/j.ufug.2025.128746](https://doi.org/10.1016/j.ufug.2025.128746)

en: Variable list for article in Urban Forestry and Urban Greening [https://doi.org/10.1016/j.ufug.2025.128746](https://doi.org/10.1016/j.ufug.2025.128746)

en: Processed data for coding analysis for article in Urban Forestry and Urban Greening [https://doi.org/10.1016/j.ufug.2025.128746](https://doi.org/10.1016/j.ufug.2025.128746)

en: RESTORE WP4_Questionnaire_Italian.pdf

en: Questionnaire in Italian

en: Study protocol of the survey

en: Processed survey data for window view for article in Landscape and Urban Planning [https://doi.org/10.1016/j.landurbplan.2025.105339](https://doi.org/10.1016/j.landurbplan.2025.105339)

en: Variable list for statistical analyses for article in Landscape and Urban Planning [https://doi.org/10.1016/j.landurbplan.2025.105339](https://doi.org/10.1016/j.landurbplan.2025.105339)

en:
This repository contains data related to the Swiss-wide survey of the RESTORE project. This project is a collaboration between the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and the Swiss Federal Laboratories for Materials Science & Technology (EMPA). It has received funding from the Swiss National Science Foundation. The objective of the RESTORE project was to assess the effects of green spaces as facilitators and noise as impediment to recover from stress in people's daily environments across Switzerland.
We conducted a nation-wide participatory mapping survey among Swiss residents to explore:
1.	The effects of greenness and noise exposure on psychological restoration when looking out of the window at home or when visiting nearby green spaces. It adopted a landscape approach to examine the interplay between environmental factors, individual perceptions, and personal traits – Scientific article 1
2.	The multiple aspects that constraint restoration when visiting nearby green spaces – Scientific article 2
Accordingly, this repository includes data and documentation for the following 2 scientific articles:
1.	Scientific article 1. “The role of greenness and road traffic noise for psychological restoration in everyday environments. A participatory mapping approach”. Landscape and Urban Planning, 2025
2.	Scientific article 2. “Perceived constraints for psychological restoration in nearby greenspaces. An exploratory and multi-dimensional approach”. Urban Forestry and Urban Greening, 2025

landscape-perception

display_name: landscape-perception

outdoor-restoration

display_name: outdoor-restoration

ppgis

display_name: ppgis

survey

display_name: survey

traffic-noise

display_name: traffic-noise

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Swiss-wide survey on restorative places and road traffic noise


maintainer: Anita C. Risch

en: non-native-plant herbivory native-plant weed-management grassland

en: Data file native and non-native plant interactions in Australian grasslands

en:
taxa tab:	list and overview of all the recorded species

* family:                 family of the plant

* genus:                genus of the plant

* species:                plant species name

* origin:                indicates whether the plant is native to Australia or not (non-native)

* common name:	        common name of the plant species

* functional group:	        functional group of the plant species: forb, graminoid, fern, tree

* functional group detailed:	gives more detail about the type of graminoid and forb: legume, forb (non-leguminous),
                        grass, sedge, rush, fern, tree

* lifeform:                annual or perennial lifeform (species which can have both of these lifeforms where
                        considered as annuals)

plot tab:	list of species found in each plot and their cover (%)

* sampling.session:        provides information about the sampling time:
                        May2020 = data that was collected in May 2020
                        Nov2020 = data that was collected in November 2020

* farm.name:	            name of the farms where the sampling took place:
                        SF = farm of the Southern group
                        NF = farm of the Northern group
                        numbers 1-3 = randomly allocated to the Southern group of farms
                        numbers 4-6 = randomly allocated to the Northern group of farms

* site.type:	                KG: Kangaroo grass dominated site
                        ALG: ALG+KG site (Kangarooo grass and African lovegrass co-dominated site)

* plot.no:                plot number: 9-12

* scientific.name:	        scientific name of the plant species found in a certain plot

* functional group:	        indicates whether the species found is a tree, forb, graminoid or fern

* functional group detailed:	indicates whether the species found is a tree, legume, forb (non-leguminous),
                        grass, sedge, rush, fern

* lifeform:                specifies the lifeform of the species: annual or perennial lifeform
                        (species which can have both of these lifeforms where considered as annuals)

en:
This dataset contains all data, on which the following publication below is based.

Paper Citation:

_Schlierenzauer, C., Risch, A.C., Schütz, M., Firn, J. 2021. Non-native Eragrostis curvula reduces plant species diversity in pastures of South-eastern Australia even when native Themeda triandra remains co-dominant. Plants 10, 596._

Please cite this paper together with the citation for the datafile.

Study area
The study was conducted in the lowland grassy woodlands of the Bega Valley Region, which is located in the south-east corner of New South Wales, Australia. Embedded between the Pacific Ocean and the Australian Alps, the lowland grassy woodlands are mostly located on granitic substrates and reach elevations of roughly 500 m above sea level. Typically, these grassy woodlands receive less precipitation (mean annual precipitation between 700-1100 mm) compared to the more elevated areas that surround them (NSW Government - Office of Environment and Heritage 2017).
The vegetation is dominated by an open tree canopy layer consisting of Eucalyptus tereticornis Sm, Angophora floribunda Sm. (Sweet) and a range of other eucalypt species. Sometimes shrub or small trees are also present, whereas grasses and forbs form the ground-cover. In areas without intensive agricultural history, this layer is dominated by perennial, tussock grasses such as Themeda triandra Forssk, Microlaena stipoides R.Br (Weeping Grass), Eragrostis leptostachya Steud. (Paddock Lovegrass) and Echinopogon ovatus P.Beauv (Forest Hedgehog Grass). The remaining inter-tussock spaces are occupied by a diversity of growth-restricted grasses and herbaceous forbs (NSW - Department of Planing, Industries and Environment 2019; NSW Government - Office of Environment and Heritage 2017).
Clearing, pasture sowing, fertilizer application and livestock grazing resulted in a dramatic decrease in the extent of these natural woodlands, with less than five percent within conservation reserves and overall, with only about 20% of their original extent in New South Wales still existing (Tozer et al. 2010). The remaining areas outside of reserves are threatened by altered fire frequencies, habitat clearing, livestock grazing and especially by non-native plant invasion, particularly Eragrostis curvula (Schrad.) Nees. For this reason, the grassy woodlands are listed as an endangered ecological community in the NSW state legislation. Additionally, they are considered as critically endangered by the Commonwealth of Australia (Threatened Species Scientific Committee (TSSC) 2013).

Experimental design and sampling
The study was conducted on six farms and in each of them two sites were chosen, representing a paired design. One of the sites at each farm is dominated by native Themeda triandra, the other one co-dominated by non-native Eragrostis curvula and Themeda triandra. All farms are within a radius of approximately 10 km from the town Candelo. Three of the farms are located North (36°40’ to 36°42’ S and 149°38’ to 149°42’ E) and three of them are located South (36°51’ to 36°49’ S and 149°38’ to 149°42’ E) of Candelo.
Non-native herbivores (mainly cattle, sheep and rabbits) and native herbivorous marsupials (mainly kangaroos, wallabies and wombats) are present in the area of these sites. On each site, data was collected within four plots (each 1 x 1 m) in May and November 2020. All plant species found within a plot were recorded and their relative abundance was estimated.

References
NSW - Department of Planing, Industries and Environment. 2019. “Lowland Grassy Woodland in the South East Corner Bioregion - Endangered Ecological Community Listing.” https://www.environment.nsw.gov.au/topics/animals-and-plants/threatened-species/nsw-threatened-species-scientific-committee/determinations/final-determinations/2004-2007/lowland-grassy-woodland-south-east-corner-bioregion-endangered-ecological-community-l (February 18, 2021).
NSW Government - Office of Environment and Heritage. 2017. “Lowland Grassy Woodland in the South East Corner Bioregion - Profile.” https://www.environment.nsw.gov.au/threatenedSpeciesApp/profile.aspx?id=20070 (January 31, 2021).
Threatened Species Scientific Committee (TSSC). 2013. Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) Conservation Advice for Lowland Grassy Woodland in the South East Corner Bioregion. http://www.environment.gov.au/biodiversity/threatened/communities/pubs/82-conservation-advice.pdf.
Tozer, Mark et al. 2010. “Native Vegetation of Southeast NSW: A Revised Classification and Map for the Coast and Eastern Tablelands.” Cunninghamia : a journal of plant ecology for eastern Australia 11(3): 359–406.

grassland

display_name: grassland

herbivory

display_name: herbivory

native-plant

display_name: native-plant

non-native-plant

display_name: non-native-plant

weed-management

display_name: weed-management

en: Native and no-native plant interactions in Australian grasslands


en: complex-terrain precipitation-variability cosmo-wrf snow-precipitation orographic-precipitation

en: Snow depth maps over Dischma valley for 26 January 2016 and 9 March 2016 and snow depth differences between the two dates.

mimetype: application/zip

en: StationData

en:
The data presented here corresponds to the publication "Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain" (Gerber et al., 2018a), which investigates the precipitation variability of snow precipitation in the central northern part of the Grisons (CH) and the publication "The importance of near-surface winter precipitation processes in complex alpine terrain" (Gerber et al., 2018b). The dataset contains:

* WRFsimulations: WRF simulation output for simulations with 4x (14x) terrain smoothing with an output timestep of 30 min/5 min and horizontal grid spacings of 1350 m, 450 m, 150 m and 50 m (currently: data available upon request).
* StationData: Meteorological station data of 18 meteorological stations in the central northern part of the Grisons with 30 minute resolution for the period 1 January 2016 till 1 May 2016.
* ADS80data: Photogrammetrically determined snow depth distribution data over the Dischma valley for the 26 January 2016 and 9 March 2016. Snow heights are corrected for buildings, vegetation (> 1m), outliers, and pixles, which are obivously snow-free on the pictures (Bühler et al., 2015). In addition the snow depth differences (snow depth on 9 March 2016 minus snow depth on 26 January 2016) are provided.

For more details about the simulation and observation data, see Gerber et al., 2018 and Gerber and Sharma (2018).

Publications:

Bühler, Y., Marty, M., Egli, L., Veitinger, J., Jonas, T., Thee, P., and Ginzler, C.: Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9, 229–243, doi:10.5194/tc-9-229-2015, 2015.

Gerber, F., Besic, N., Sharma, V., Mott, R., Daniels, M., Gabella, M., Berne, A., Germann, U., and Lehning, M.: Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain, The Cryosphere, 12, 3137–3160, doi:10.5194/tc-12-3137-2018, 2018.

Gerber, F., Mott, R. and Lehning, M.: The importance of near-surface winter precipitation processes in complex alpine terrain, Journal of Hydrometeorology, accepted, 2018.

Gerber, F., and Sharma, V.: Running COSMO-WRF on very-high resolution over complex terrain. Laboratory of Cryospheric Sciences CRYOS, École Polytechnique Fédérale de Lausanne EPFL, Lausanne, Switzerland. doi:10.16904/envidat.35, 2018.

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

orographic-precipitation

display_name: orographic-precipitation

precipitation-variability

display_name: precipitation-variability

snow-precipitation

display_name: snow-precipitation

en: DISCHMEX - High-resolution WRF simulations in complex alpine terrain and station measurements


vegetation-height-model-nfi

maintainer: Christian Ginzler

title_for_slug: vegetation-height-model-nfi

en: vegetation-height-model forest photogrammety point-cloud 3d

en: 2022 Vegetation Height Model NFI (2017-2022)

en:
Vegetation Height Model of Switzerland for the year 2022 (cloud optimized geotiff)
and Metadata file with information about acquisition date of used images for tiles of 500 x 500 m (geopackage).

en: 2012 Vegetation Height Model NFI (2007-2012)

en:
Vegetation Height Model of Switzerland for the year 2012 (cloud optimized geotiff)
and Metadata file with information about acquisition date of used images for tiles of 500 x 500 m (geopackage).

en: 2019 Vegetation Height Model NFI (2013-2019)

en:
Vegetation Height Model of Switzerland for the year 2019 (cloud optimized geotiff)
and Metadata file with information about acquisition date of used images for tiles of 500 x 500 m (geopackage).

en: 2023 Vegetation Height Model NFI (current)

en:
Vegetation Height Model of Switzerland for the year 2023 (cloud optimized geotiff)
and Metadata file with information about acquisition date of used images for tiles of 500 x 500 m (geopackage).

en: 2015 Vegetation Height Model NFI (2010-2015)

en:
Vegetation Height Model of Switzerland for the year 2015 (cloud optimized geotiff)
and Metadata file with information about acquisition date of used images for tiles of 500 x 500 m (geopackage).

en: Countrywide Stereo-Image Matching for Updating Digital Surface Models in the Framework of the Swiss National Forest Inventory

en:
Vegetation Height Model of Switzerland for the year 2021 (cloud optimized geotiff)
and Metadata file with information about acquisition date of used images for tiles of 500 x 500 m (geopackage).

en: 2016 Vegetation Height Model NFI (2011-2016)

en:
Vegetation Height Model of Switzerland for the year 2016 (cloud optimized geotiff)
and Metadata file with information about acquisition date of used images for tiles of 500 x 500 m (geopackage).

en: Thumbnail

en: 2020 Vegetation Height Model NFI (2013-2020)

en:
Vegetation Height Model of Switzerland for the year 2020 (cloud optimized geotiff)
and Metadata file with information about acquisition date of used images for tiles of 500 x 500 m (geopackage).

en:
Countrywide **vegetation height models (VHM)** were generated for Switzerland based on **stereo aerial images**, acquired by the Federal Office of Topography swisstopo.
From the ADS-80/100 sensor data, first a digital surface model (DSM) with a spatial resolution of 1 × 1 m is processed. This DSM is then normalized using the digital terrain model (DTM) swissALTI3D (swisstopo). Buildings and other artificial objects are masked out from the nomalized DSM (nDSM) using information from the topogrphic landscape model - TLM (swisstopo) to obtain the actual vegetation height model (VHM).
These VHM's are produced in the framework of the Swiss National forest Inventory (NFI). Each year about 1/6 of Switzerland's surface is updated using the leaf-on aerial images acquired by swisstopo (may - october).
Further information on the creation of the VHM NFI can be found in the paper Ginzler and Hobi (2015, https://doi.org/10.3390/rs70404343).

forest

display_name: forest

photogrammety

display_name: photogrammety

point-cloud

display_name: point-cloud

vegetation-height-model

display_name: vegetation-height-model

en: Vegetation Height Model NFI


en: urban-transformations europe land-use-transformations spatial-planning strategic-projects land-use-change large-scale-urban-development-projects strategic-spatial-planning

en: QCA data set large-scale urban development projects

en: Please refer to the sections: 3. The data set lsUDPs: 3.1 Selection of cases and data collection; 3.2 Data management and operationalization in the Metadata for further details on this resource.

en: QCA R script large-scale urban development projects Europe

en:
For the set up of this R script, we used the “QCA” (Duşa, 2019) and “SetMethods” (Oana and Schneider, 2018) R packages.

The following further resources were also used:
Dusa, A. (2019). QCA with R: A comprehensive resource. Springer: Berlin.
Schneider, C. Q., & Wagemann, C. (2012). Set-theoretic methods for the social sciences. A guide to qualitative comparative analysis. Cambridge: Cambridge University Press.
Thomann, E., Oana, I.-E., & Wittwer, S. (2018). Performing fuzzy- and crisp set QCA with R. A user-oriented beginner's guide. Retrieved from http://www.evathomann.com/links/qca-r-manual

en:
Table of Content: 1. General context of the data set "lsUDPs" ; 2. Background and aims of the study using the data set lsUDPs; 3. The data set lsUDPs: 3.1 Selection of cases and data collection; 3.2 Data management and operationalisation

1. General context of the data set "lsUDPs"
The data set "lsUDPs" has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2020. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, strategic spatial plans) into quantitative land-change modelling approaches at the urban regional level. The first stage (2016-2017) of the CONCUR project focussed on 21 urban regions in Western Europe. The urban regions were selected through a multi-stage strategy for empirical research (see Hersperger, A. M., Grădinaru, S., Oliveira, E., Pagliarin, S., & Palka, G. (2019). Understanding strategic spatial planning to effectively guide development of urban regions. Cities, 94, 96–105. https://doi.org/10.1016/j.cities.2019.05.032 ).

2. Background and aims of the study using the data set lsUDPs
As part of the CONCUR project, a specific task was to examine the relationship between strategic spatial plans and the formulation and implementation (i.e. urban land change) of large-scale urban development projects in Western Europe.
Strategic urban projects are typically large-scale, prominent urban transformations implemented locally with the aim to stimulate urban growth, for instance in the form of urban renewals of deprived neighborhoods, waterfront renewals and transport infrastructures. While strategic urban projects are referred to in the literature with multiple terms, in the CONCOR project we call them large-scale urban development projects (lsUDPs).
Previous studies acknowledged both local and supra-local (or structural) factors impacting the context-specific implementation of lsUDPs. Local governance factors, such as institutional capacity, coordination among public and private actors and political leadership, intertwine with supra-local conditions, such as state re-scaling processes and devolution of state competencies in spatial planning, de-industrialisation and increasing social inequality. Hence, in implementing lsUDPs, multi-scalar factors act in combination.
Because the formulation and implementation of lsUDPs require multi-scalar coordination among coalitions of public and private actors over an extended period of time, they are generally linked to strategic spatial plans (SSPs). Strategic spatial plans convey collective visions and horizons of action negotiated among public and private actors at the local and/or regional level to steer future urban development, and can contain legally binding dispositions, but also indicative guidelines.
The key question remains as to what extent large-scale urban development projects and strategic spatial plans can be regarded as aligned. By alignment, or “concordance”, we mean that strategic projects are formulated and implemented as part of the strategic planning process (“high concordance”), or that the strategic role of projects is reconfirmed in (subsequent) strategic plans (“moderate concordance”). Lack of concordance is found when lsUDPs have been limitedly (or not at all) acknowledged in strategic spatial plans.
We assume that certain local and supra-local factors, characterising the development of the projects, foster (but not strictly “cause”) the degree of alignment between lsUPDs and SSPs. In this study, we empirically examine how, and to what extent, the concordance between 38 European large-scale urban development projects and strategic plans (outcome: CONCOR) has been enabled by five multi-scalar factors (or conditions): (i) the role of the national state (STATE), (ii) the role of (inter)national private actors (PRIVATE), (iii) the occurrence of supra-regional external events (EVENTS), (iv) the degree of transport connectivity (TRANSP), and (v) local resistance from civil society (RESIST). We adopted a (multi-data) case-based qualitative strategy for empirical research and applied the formalised procedure of within- and cross-case comparison offered by fuzzy-set Qualitative Comparative Analysis appropriate for the goal of this study. Based on set theory, QCA formally integrates contextual sensitivity to case specificities (within-case knowledge) with systematic comparative analysis (across-case knowledge).
The research question the data set has been created to reply to is the following: which conditions, and combinations of conditions, enable the concordance between large-scale urban development projects and strategic spatial plans?
The conditions (“independent variables”) considered are. STATE: the set of large-scale urban projects characterized by a high degree of state intervention and support in their formulation and implementation, PRIVATE: the set of large-scale urban projects characterized by a high degree of involvement of (inter)national private actors in their formulation and implementation, EVENTS: the set of large-scale strategic projects whose formulation and implementation have been strongly affected by unforeseen international events and/or global trends, TRANSP: the set of large-scale strategic projects with a high degree of road and/or transit connectivity, and RESIST: set of large-scale strategic projects whose realization has been characterized by resistances that have substantially delayed or modified the project implementation.
The outcome (“dependent variable”) under analysis is CONCOR: the set of large-scale urban projects having a high degree of concordance/alignment/integration with strategic spatial plans

3. The data set lsUDPs

   3.1 Selection of cases and data collection
To generate the current data set on large-scale urban development projects in European urban regions (data set "lsUDPs"), we identified 35 large-scale urban development projects in a sample of the 21 Western urban regions considered in the CONCUR project (see supra, Hersperger et al. 2019): Amsterdam, Barcelona, Copenhagen, Hamburg, Lyon, Manchester, Milan, Stockholm, Stuttgart. The criteria we followed to identify the 35 large-scale urban development projects are: geographical location, size (large-scale), site (located either in the city core or in the larger urban region) and urban function (e.g. housing, transportation infrastructures, service and knowledge economic functions). Employing these criteria facilitated the selection of diverse large-scale urban development projects while still ensuring sufficient comparability.
In 2016, we performed 47 in-depth interviews with experts in urban and regional planning and large-scale strategic projects and infrastructure (i.e. academics and practitioners) about the formulation, implementation and development (1990s–2010s) of each project in each of the 9 selected urban regions. On average, each interviewee answered questions on 3.1 large-scale urban development projects. Three cases were subdivided into two cases because a clear differentiation between specific implementation stages was identified by the interviewees (expansion of the Barcelona airport, cases “bcn_airport80-90” and “bcn_airport00-16”; realisation of Lyon Part-Dieu, cases “lyo_partdieu70-90” and “lyo_partdieu00-16”; MediaCityUK, cases “man_salfordquays80-00” and “man_mediacityuk00-16”). Therefore, from the initial 35 cases, the final number of analysed cases in the lsUDPs dataset is 38.

    3.2 The data set lsUDPs: Data management and operationalisation
Interviews were fully transcribed and analysed through MAXQDA (version 12.3, VERBI GmbH, Berlin, Germany), and intercoder agreement was evaluated on a sample of nine interviews. We also compiled “synthetic case descriptions” (SCD) for each case (totalling more than 160 SCDs) to spot potential inconsistencies among interviewees’ accounts and to facilitate completion of the “calibration table” for each case (see below). An online expert survey distributed to the interviewees (response rate 78%) helped systematise the information collected during the interviews. We also consulted both academic and gray literature on the case studies to check for possible ambiguity and inconsistencies in the interview data, and to solve discrepancies between our assigned set membership scores and questionnaire values. Site visits were also carried out to retrieve additional information on the selected cases.
For each case (i.e. each of the 38 selected large-scale urban development projects), we operationalised each condition (i.e. STATE, PRIVATE, EVENTS, TRANSP, RESIST) and the outcome (CONCOR) in terms of sets, for subsequent application of Qualitative Comparative Analysis. This process is called “calibration”; we used a number of indicators for each condition to qualitatively assess each large-scale project across the conditions. The case-based qualitative assessment was then transformed into fuzzy-set membership values. Fuzzy-set membership values range from 0 to 1, and should be conceived as “fundamentally interpretative tools” that “operationalize theoretical concepts in a way that enhances the dialogue between ideas and evidence” (Ragin 2000:162, in “Fuzzy-set Social Science”. Chicago: University Press). We employed a four-value fuzzy-set scale (0, 0.33, 0.67, 1) to “quantify” into set membership scores the individual histories of cases retrieved from interview data. Only the condition TRANSP was calibrated as a crisp-set (0, 1).
The translation of qualitative case-based information into numerical fuzzy-set membership values was iteratively performed by populating a calibration table following standard practices recently emerged in QCA when dealing with qualitative (interview) data.

europe

display_name: europe

land-use-change

display_name: land-use-change

land-use-transformations

display_name: land-use-transformations

large-scale-urban-development-projects

display_name: large-scale-urban-development-projects

spatial-planning

display_name: spatial-planning

strategic-projects

display_name: strategic-projects

strategic-spatial-planning

display_name: strategic-spatial-planning

urban-transformations

display_name: urban-transformations

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: lsUDPS Large-scale urban development projects in European urban regions


maintainer: Yael Frischholz

en: bifaciality winter-electricity alps photovoltaic snow

en:
Title: Monitoring data set at A2 (utility-scale power-plant Muttsee), months 10.2022-09.2023
Provider: AXPO - IWB Industrielle Werke Basel
Last edition: 17.01.2024
Editor: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL
File name structure:
The power-plant is made of 23 string boxes (GAK) and inverters (WR) named after their given number. One file per device is provided in the data/ subfolder, following the same naming convention (e.g. for the string box number 1, the file name is: “A2_GAK01.csv” and for the corresponding inverter, the file name is “A2_WR01.csv”). Refer to the publication for further details on the setup of the power plant.
File format:
All files are provided in the CSV format.
Column headings:
	String boxes and inverters (GAK & WR):
	⁃	device_name (string): name of the device (same as file name)
	⁃	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC
	String boxes (GAK):
	⁃	I_ (double): input current from the substring number (W)
	⁃	I_SUM (double): output current of string box (A)
	⁃	U_DC (double): output voltage of string box (V)
	⁃	P_DC_ (double): input DC power from the substring number (W)
	⁃	P_DC (double): output DC power of string box (W)
	⁃	$S$_T#_$T$ (double): temperature from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S) of table T. Two types of temperature measurements (#) are available: 1=standard cell temperature (°C) , 2=module temperature on the rear side (°C) .
	⁃	$S$_SRAD_T (double): poa irradiation (W/m**2) from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S) of table T.
		Inverters (WR):
	⁃	I_DC (double): input DC current(A)
	⁃	U_DC(double): input DC voltage(V)
	⁃	P_DC (double): input DC power (W)
	⁃	P_AC (double): output AC power (W)
Preprocessing:
	1. Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.

	2. Missing data:
	⁃	Data holes of less or equal to 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).
	3. Wiring losses:
	⁃	To be consistent with A1, wiring losses are corrected at A2. The wiring loss between the string boxes and the inverters is removed by multiplying the value of input P_DC at the inverter level (P_DC,inv) by the mean ratio P_DC,inv / P_DC,arr.
	⁃	The computed mean wiring loss is 2.3\%. It is computed from 2023-02-01 to 2023-09-30, after the long data hole in the data sets of the string boxes.

Mean uptime:
	Raw:
	⁃	WR: 98.2%
	⁃	GAK*: 38.5%
	Processed:
	⁃	WR: 99.6%
	⁃	GAK*: 56.4%

	*The uptime at the string box level (GAK) is low because PMUs at this level shut down during steady and low signal leading to unavailable data at night. In addition, the 23 days downtime of 	January 2023 could not be interpolated nor replaced.

en:
Title: Monitoring data set at A1 (test-site of Totalp), years 2018-2022
Provider: ZHAW - EKZ
Edition: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL
Last edition: 17.01.2024
File name structure:
The test site contains 6 segments named from A to F. The six files provided in the data/ subfolder follow the same naming convention (e.g. for segment A, the file name is: “A1_A.csv”). Refer to the publication for further details on the setups of the segments.
File format:
All files are provided in the CSV format.
Column headings:
	•	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC
	•	poa_front (double): front plane-of-array irradiation (W/m**2)
	•	poa_back (double): rear plane-of-array irradiation (W/m**2)
	•	mod_temp (double): module’s temperature (°C)
	•	P_AC (double): output AC power (W)
Preprocessing:
	Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.
	Missing data:
	⁃	Data holes of less than 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).
	Wiring losses :
	⁃	As described in [1] , the test-site setup caused abnormally large wiring losses, mainly due to the distance to optimisers and to the low installed power per DC-wire.
	⁃	The wiring losses comprised between 10% and 15%, are averaged hourly and added to the measured DC power.

	Misc.:
	⁃	P_AC is computed for each segment based on the measured DC power and the average inverter’s efficiency (96.1%).
	⁃	As described in [1], the peak power of the installed module, used to compute the final yield is slightly different from the values announced by the manufacturer.
Mean uptime:
	Raw:
	⁃	95.2%
	Processed:
	⁃	100%
References:
[1] 	D. Anderegg, S. Strebel, and J. Rohrer, “Alpine Photovoltaik Versuchsanlage Davos Totalp : Erkenntnisse aus 5 Jahren Betrieb,” de, Sep. 	2023, Accepted: 2023-09-29T09:13:16Z Publisher: ZHAW Zürcher Hochschule für Angewandte Wissenschaften.DOI: 10.21256/	zhaw-2524. [Online]. Available: https://digitalcollection.zhaw.ch/handle/11475/28797 (visited on 12/15/2023).

en:
On this repository you can find the monitoring data of the 3 PV power-plants analysed in the article _"Confirmation of the power gain for solar photovoltaic systems in alpine areas"_ (doi: 10.3389/fenrg.2024.1372680) . Each folder contains the following two elements:
1. **README.txt** : describes the content of the folder. Especially it describes the plant's monitoring system's architecture and relates it to the various files included in the data sub-folder. It also provides a detailed description of all processing steps leading to the data sets as available in the data sub-folder and used in the pre-cited article.
3. **data/** : sub-folder containing the file(s) used in the referenced article.

alps

display_name: alps

bifaciality

display_name: bifaciality

photovoltaic

display_name: photovoltaic

snow

display_name: snow

winter-electricity

display_name: winter-electricity

en: Monitoring data sets of alpine photovoltaic power-plants


maintainer: Leo Gallus Bont

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

en: Herunterladen des DHM von swisstopo Website

en: View video on youtube!

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

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

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

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

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

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

Link zur Seilaplan-Website: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-software

display_name: geoinformation-software

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

swisstopo

display_name: swisstopo

en: Seilaplan Tutorial: DTM download from swisstopo website