reseau-tpg-lignes-de-contact

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

title_for_slug: reseau-tpg-lignes-de-contact

it: Les données vectorielles sont disponibles sous forme de fichiers.zip, incluant la donnée dans le format choisi, sa fiche de métadonnée (.pdf) ainsi que les conditions générales d'utilisation (.pdf). Sauf exception, les formats suivant sont proposés: SHAPE (ESRI) - Geodatabase-File (ESRI) - GML - KML - CSV

fr: Cette couche contient l'ensemble des lignes de contact des voies de tramways et de trolleybus du réseau des Transports Publics Genevois

fr: SITG - Système d'information du territoire à Genève

it: SITG - Sistema informativo territoriale di Ginevra

fr: Le Système d’Information du Territoire à Genève (SITG) est un organisme fondé sur un réseau de partenaires publics ayant pour but de coordonner, centraliser et diffuser les géodonnées relatives au territoire genevois, produites dans le cadre de leurs missions.

de: Das Genfer Geoinformationssystem (SITG) ist eine Organisation zur Koordination, Zentralisierung und Bereitstellung sämtlicher Geodaten, die durch verschiedene öffentliche Einrichtungen im Rahmen ihrer Missionen produziert werden.

fr: RESEAU TPG - LIGNES DE CONTACT

de: RESEAU TPG - LIGNES DE CONTACT

en: RESEAU TPG - LIGNES DE CONTACT

it: RESEAU TPG - LIGNES DE CONTACT


egid-und-gebaudenummer

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

title_for_slug: egid-und-gebaudenummer

label: Web GIS Client des Kanton Uri. Die Daten können direkt via dem Portal in den unterschiedlichsten Datenformaten heruntergeladen werden.

label: geocat.ch permalink

state: active

type: dataset

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

format: WMS

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: EGID und Gebäudenummer. Jedes Gebäude hat eine vortlaufende Nummer die gemeindeweise eindeutig ist.

spatial: Canton of Uri (UR)

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

type: organization

approval_status: approved

value: Uri-Kt - Geocat Harvester

fr: EGID und Gebäudenummer

de: EGID und Gebäudenummer

en: EGID und Gebäudenummer

it: EGID und Gebäudenummer


fixpunkte-ur

title_for_slug: fixpunkte-ur

fr: Die Fixpunkte bilden die Grundlage aller Daten mit Raumbezug. Darunter fallen beispielsweise die Daten der amtlichen Vermessung, die Landeskartenwerke, Leitungskataster, Daten in geographischen Informationssystemen, Zonenpläne etc. Es werden generell zwei Punktarten unterschieden: die Lagefixpunkte (LFP) und die Höhenfixpunkte (HFP).

fr: Fixpunkte (UR)

de: Fixpunkte (UR)

en: Fixpunkte (UR)

it: Fixpunkte (UR)


einzelobjekte-ur

title_for_slug: einzelobjekte-ur

fr: Die Informationsebene Einzelobjekte umfasst Objekte, die Merkmale der Bodenbedeckung enthalten, welche aufgrund ihrer Eigenschaft oder Ausdehnung aber keine oder unwesentliche flächenmässige Bedeutung haben.

fr: Einzelobjekte (UR)

de: Einzelobjekte (UR)

en: Einzelobjekte (UR)

it: Einzelobjekte (UR)


grundbuchplan-ur

title_for_slug: grundbuchplan-ur

fr: plan-de-situation geodonnees-de-base

de: situationsplan geobasisdaten

en: situation-plan official-geodata

it: piano-di-situazione geodati-di-base

fr: Diverse Ebenen aus der Amtlichen Vermessung bilden den bekannten Grundbuchplan. Der Katasterplan A4/A3 als PDF können sie ebenfalls hier direkt beziehen.

fr: Grundbuchplan (UR)

de: Grundbuchplan (UR)

en: Grundbuchplan (UR)

it: Grundbuchplan (UR)


bodenbedeckung-ur

title_for_slug: bodenbedeckung-ur

fr: couverture-du-sol geodonnees-de-base

de: bodenbedeckung geobasisdaten

en: land-cover official-geodata

it: copertura-del-suolo geodati-di-base

fr: Die Informationsebene Bodenbedeckung ist eine generalisierte und kartografisch bearbeitete Darstellung realer Objekte mit flächiger Ausdehnung (Gebäude, Strassen, Gewässer, Wald...).

fr: Bodenbedeckung (UR)

de: Bodenbedeckung (UR)

en: Bodenbedeckung (UR)

it: Bodenbedeckung (UR)


postleitzahl-ur

title_for_slug: postleitzahl-ur

fr: Postleitzahl aus TOPIC «PLZOrtschaft» der amtlichen Vermessung.

fr: Postleitzahl (UR)

de: Postleitzahl (UR)

en: Postleitzahl (UR)

it: Postleitzahl (UR)


geography

fr: Géographie

territory

fr: Territoire et environnement

url: https://geo.ur.ch/?layers=Bodenbedeckung Darstellung schwarz weiss

de: Die Informationsebene Bodenbedeckung ist eine generalisierte und kartografisch bearbeitete Darstellung realer Objekte mit flächiger Ausdehnung (Gebäude, Strassen, Gewässer, Wald...).

fr: Bodenbedeckung Darstellung schwarz weiss (UR)


fr: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

fr: Diverse Ebenen aus der Amtlichen Vermessung bilden den bekannten Grundbuchplan. Den Katasterplan A4/A3 als PDF können sie ebenfalls hier direkt beziehen.

fr: Grundbuchplan Darstellung schwarz-weiss (UR)


gewasserraum-differenz-ur

title_for_slug: gewasserraum-differenz-ur

fr: Ab der öffentlichen Auflage werden folgende Änderungen des Gewässerraums (abgeleitet aus der Nutzungsplanung) und übergangsweise die Gewässerbaulinien (aus der Nutzungsplanung) dargestellt: Neu erfasste Objekte / Gelöschte Objekte

fr: Gewässerraum Differenz (UR)

de: Gewässerraum Differenz (UR)

en: Gewässerraum Differenz (UR)

it: Gewässerraum Differenz (UR)


administrative-einteilung-ur

title_for_slug: administrative-einteilung-ur

fr: repartition-du-plan geodonnees-de-base

de: planeinteilung geobasisdaten

en: plan-division official-geodata

it: ripartizione-del-piano geodati-di-base

fr: Die Toleranzstufen sind ein Teil des Datenmodells DM01 und geben an, wie genau die Objekte der AV aufgenommen sein müssen. In den entsprechenden Verordnungen ist definiert, welche Standardabweichungen für die einzelnen Aufnahmepunkte sicherzustellen sind.

fr: Administrative Einteilung (UR)

de: Administrative Einteilung (UR)

en: Administrative Einteilung (UR)

it: Administrative Einteilung (UR)


rebbaukataster-ur

agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

en: Agriculture, forestry

it: Agricoltura, selvicoltura

geography

de: Geographie

title_for_slug: rebbaukataster-ur

fr: perimetre geodonnees-de-base

de: perimeter geobasisdaten

en: perimeter official-geodata

it: perimetro geodati-di-base

fr: Der Rebbaukataster umfasst alle Grundstücke die mit Reben bepflanzt sind oder auf denen Reben angepflanzt werden dürfen.

fr: Rebbaukataster (UR)

de: Rebbaukataster (UR)

en: Rebbaukataster (UR)

it: Rebbaukataster (UR)


hoheitsgrenzen-ur

geography

en: Geography

it: Geografia

territory

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

title_for_slug: hoheitsgrenzen-ur

de: WMS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

fr: Da der Kanton Uri keine Bezirke hat, bestehen die Hoheitsgrenzen ausschliesslich aus den Gemeindegrenzen.

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

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

fr: Hoheitsgrenzen (UR)

de: Hoheitsgrenzen (UR)

en: Hoheitsgrenzen (UR)

it: Hoheitsgrenzen (UR)


gewasserraum-projektiert-ur

geography

fr: Géographie

territory

fr: Territoire et environnement

title_for_slug: gewasserraum-projektiert-ur

fr: alignement geodonnees-de-base

de: baulinie geobasisdaten

en: building-line official-geodata

it: linea-di-edificazione geodati-di-base

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: Ab der öffentlichen Auflage werden die Gewässerräume sind die Gewässerräume, welche gemäss Art. 36a GSchG gestützt auf Art. 12 Abs. 2 KUG in der gemeindlichen Nutzungsplanung ausgeschieden werden dargestellt. Aus den dort festgelegten Gewässerraumzonen (Grundnutzung sowie überlagerte Nutzung) wird der Gewässerraum gemäss MGDM ID=190 abgeleitet. Übergangsweise werden auch die Gewässerbaulinien (aus der Nutzungsplanung) zum Gewässerraum hinzugezählt.

fr: Gewässerraum projektiert (UR)

de: Gewässerraum projektiert (UR)

en: Gewässerraum projektiert (UR)

it: Gewässerraum projektiert (UR)


gebaudeadressen-ur

title_for_slug: gebaudeadressen-ur

fr: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

fr: Die Gebäudeadresse setzt sich zusammen aus einer Ortschaft mit Postleitzahl, einem Lokalisationsnamen (in der Regel Strassennamen) und einer Hausnummer. Zusätzlich werden die Strassenstücke und benannten Gebiete der amtlichen Vermessung dargestellt.

fr: Gebäudeadressen (UR)

de: Gebäudeadressen (UR)

en: Gebäudeadressen (UR)

it: Gebäudeadressen (UR)


nomenklatur-ur

title_for_slug: nomenklatur-ur

fr: Flur-, Orts- und Geländenamen (= geografische Namen der amtlichen Vermessung) von geografischen Gebieten, Landschaftsteilen, Flurstücken, topografischen Objekten usw.

fr: Nomenklatur (UR)

de: Nomenklatur (UR)

en: Nomenklatur (UR)

it: Nomenklatur (UR)


liegenschaften-ur

title_for_slug: liegenschaften-ur

fr: terrain geodonnees-de-base

de: grundstuck geobasisdaten

en: site official-geodata

it: fondo geodati-di-base

fr: Die Informationsebene Liegenschaften enthält die Grundstücke gemäss Art. 655 Abs. 2 ZGB: rechtsgültige und projektierte Liegenschaften (Parzellen), selbständige und dauernde Rechte (z.B. Baurecht). Zudem sind ab dem Massstab 1:1'000 auch die Grenzpunkte und Hoheitsgrenzpunkte sichtbar.

fr: Liegenschaften (UR)

de: Liegenschaften (UR)

en: Liegenschaften (UR)

it: Liegenschaften (UR)


maintainer: Direktion der Justiz und des Innern, Fachstelle Kultur

de: kultur corona kulturfinanzierung covid-19

label: Medienmitteilung (04.03.2021)

label: Vorbereiteter Code in R oder Python für jedes Dataset mit csv-Datei(en)

de: Corona-Hilfen im Kulturbereich im Kanton Zürich

de: Die Direktion der Justiz und des Innern des Kantons Zürich, Fachstelle Kultur, veröffentlicht ab dem 04.03.2021 anonymisierte Daten zu den nachgefragten, beschlossenen und ausbezahlten Ausfallentschädigungen. Die Zeitreihe beginnt am 06.04.2020 mit dem ersten eingegangenen Gesuch. Spaltenüberschriften: 'Kategorie' = Antragstellende Kategorie ('Kulturschaffende', 'Kulturunternehmen gemeinnützig' oder 'Kulturunternehmen gewinnorientiert'); 'Sparte' = Kultursparte ('Bereichsübergreifend', 'Bildende Kunst', 'Design', 'Film', 'Kino', 'Klubs und Konzertlokale', 'Literatur', 'Museen', 'Musik' oder 'Tanz/Theater'); 'Nachgefragt' = Nachgefragter Betrag in CHF (gerundet auf 100 CHF); 'Beschluss' = Beschlossener Betrag in CHF (gerundet auf 100 CHF, 'NA' bei Ablehnung); 'Status' = Status des Antrags ('Ablehnung', 'Ausbezahlt' oder 'Saldo offen'); 'Eingangsdatum' = Datum des Eingangs des Gesuchs; 'Beschlussdatum' = Datum des Beschlusses über das Gesuch; 'ID' = anonymisierter Identifikator der antragstellenden natürlichen oder juristischen Person.

format: XLS

media_type: text/csv

format: CSV

mimetype: text/csv

de: Um die wirtschaftlichen Auswirkungen der Massnahmen zur Pandemiebekämpfung abzufedern und die kulturelle Vielfalt zu erhalten, können Kulturschaffende, nicht-gewinnorientierte sowie gewinnorientierte Kulturunternehmen finanzielle Unterstützung anfordern. Bei den Ausfallentschädigungen handelt es sich um nicht-rückzahlbare Beiträge für im Rahmen der COVID-19-Pandemie abgesagte Veranstaltungen oder Projekte und Betriebsschliessungen. Die Daten werden von der Direktion der Justiz und des Innern des Kantons Zürich, Fachstelle Kultur, ab dem 04.03.2021 in unregelmässiger Frequenz aktualisiert, sofern weitere Ausfallentschädigungsgesuche bewilligt werden können. Nachgefragte wie beschlossene Beträge sind gerundet auf 100 CHF; antragstellende natürliche oder juristische Personen sind anonymisiert.

corona

display_name: corona

kultur

display_name: kultur

kulturfinanzierung

display_name: kulturfinanzierung

culture

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

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

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

name: Fachstelle Open Government Data des Kantons Zürich

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


planeinteilungen-ur

geography

de: Geographie

territory

de: Raum und Umwelt

title_for_slug: planeinteilungen-ur

fr: repartition-du-plan geodonnees-de-base

de: planeinteilung geobasisdaten

en: plan-division official-geodata

it: ripartizione-del-piano geodati-di-base

de: WMS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

fr: Die Geometrien und Nummern der Planeinteilung des Planes für das Grundbuch.

fr: Planeinteilungen (UR)

de: Planeinteilungen (UR)

en: Planeinteilungen (UR)

it: Planeinteilungen (UR)


maintainer: Fachstelle Open Government Data des Kantons Zürich

de: gesundheit gemeinden verunreinigung schwellenwert wasser lebensmittel pflanzenschutzmittel wasserversorgung trinkwasser pestizide

label: Trinkwasserqualität der Wohngemeinden (Schweizerischer Verein des Gas- und Wasserfaches SVGW)

de: Netzproben der Trinkwasserqualität

de: Konzentrationsbereiche zur Trinkwasserqualität für verschiedene Analyten aus den im Auftrag der Wasserversorgungen durchgeführten ergänzenden Selbstkontrolluntersuchungen in den Gemeinden des Kantons Zürich - im regulären Trinkwassernetz (ohne Notversorgung, Laufbrunnen und Ressourcen). Die Konzentrationsbereiche zur Trinkwasserqualität aus den Kontrolluntersuchungen durchgeführt durch das Kantonale Labor Kanton Zürich sind im Datensatz "Qualität des Trinkwassers im Kanton Zürich ab 2020" der Gesundheitsdirektion enthalten (siehe Verwandte Datensätze).

gemeinden

display_name: gemeinden

gesundheit

display_name: gesundheit

lebensmittel

display_name: lebensmittel

pestizide

display_name: pestizide

pflanzenschutzmittel

display_name: pflanzenschutzmittel

schwellenwert

display_name: schwellenwert

trinkwasser

display_name: trinkwasser

verunreinigung

display_name: verunreinigung

wasser

display_name: wasser

wasserversorgung

display_name: wasserversorgung

agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

en: Agriculture, forestry

it: Agricoltura, selvicoltura

health

fr: Santé

de: Gesundheit

en: Health

it: Sanità

territory

fr: Territoire et environnement

de: Trinkwasserqualität im Kanton Zürich nach Gemeinden und Verteilzonen (Selbstkontrolle der Wasserversorgungen)


de: gesundheit sars-cov-2 corona schweiz covid-19 krankheiten kantone

label: Update Status Dashboard: Aktuelle SARS-CoV-2 Fallzahlen der Kantone und Fürstentum Liechtenstein

label: Readme: SARS-CoV-2 Cases communicated by Swiss Cantons and Principality of Liechtenstein

de: COVID_19 open government data reported by Swiss Cantons and Principality of Liechtenstein from January 5, 2020

de: Case numbers include persons tested in Switzerland per Canton (26 Cantons) plus Principality of Liechtenstein. For definition of variables see Readme listed below "Further information / Weitere Informationen".

de: Data is generated and validated daily using manual and automated procedures. Note that we only publish data that are reported by the Swiss Cantons and the Principality of Liechtenstein. Thus, gaps result if Swiss Cantons or the Principality of Liechtenstein do not report data for a specific date. Updates of cantonal case numbers during weekends are infrequent.

kantone

display_name: kantone

krankheiten

display_name: krankheiten

schweiz

display_name: schweiz


de: vereine stiftungen shab unternehmen zefix handelsregister wirtschaft gmbh firmen einzelfirmen genossenschaften ehra unternehmensdaten

label: Zentraler Firmenindex Zefix (Eidgenössisches Amt für das Handelsregister)

label: Zentraler Firmenindex Zefix (Linked Data Service LINDAS)

de: Bestand im Handelsregister eingetragener Rechtseinheiten mit Sitz im Kanton Zürich, täglich aktualisiert

media_type: application/ld+json

de: SPARQL-Suchanfrage, um die einmal täglich aktualisierten Daten im RDF-Format via den Linked Data Service LINDAS aus dem zentralen Firmenindex Zefix® abzufragen. Zum Download der Daten (im Format CSV) auf das Download-Icon in der Menu-Leiste oberhalb der Resultate-Tabelle klicken. Die Informationen aller Entitäten beginnend mit "https://register.ld.admin.ch/zefix/company/[ID]..." können im Format JSON-LD bezogen werden: 'legalName' = Name der Rechtseinheit; 'description' = Zweck der Rechtseinheit.

format: JSON-LD

mimetype: application/ld+json

de: Täglich aktualisierte Informationen zu den im Firmenzentralregister des Eidgenössischen Amts für das Handelsregister eingetragenen Rechtseinheiten (Firma / Name) mit Sitz (Domiziladresse) im Kanton Zürich.

ehra

display_name: ehra

einzelfirmen

display_name: einzelfirmen

firmen

display_name: firmen

genossenschaften

display_name: genossenschaften

gmbh

display_name: gmbh

handelsregister

display_name: handelsregister

shab

display_name: shab

stiftungen

display_name: stiftungen

unternehmen

display_name: unternehmen

unternehmensdaten

display_name: unternehmensdaten

vereine

display_name: vereine

wirtschaft

display_name: wirtschaft

zefix

display_name: zefix

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

industry

fr: Industrie, services

de: Industrie, Dienstleistungen

en: Industry and services

it: Industria, servizi

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito

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.

de: Bestandsdaten zum Kanton Zürich aus dem Zentralen Firmenindex (Zefix) des Bundes


label: Öffentlichkeitsprinzip

de: Spalten: 'jahr'; 'organisationseinheit'; 'gesuche_haengig_jan' (am 1. Januar des Jahres); 'gesuche_total' (des gesamten Jahres); 'zugang_uneingeschraenkt_gewaehrt'; 'zugang_teilweise_gewaehrt'; 'zugang_vollstaendig_abgelehnt'; 'anderweitige_erledigung' (z.B. Rückzug, Gegenstandslosigkeit); 'gesuche_haengig_dez' (am 31. Dezember des Jahres).

de: Anzahl und Erledigungsart der schriftlich eingereichten Informationszugangsgesuche in der kantonalen Verwaltung. Nicht enthalten sind die – praxisgemäss viel zahlreicheren – sogenannten formlosen Gesuche. Darunter fallen insbesondere die telefonischen oder per Mail eingereichten Anfragen. Keine Angaben für das Jahr 2021.

direktionen

display_name: direktionen

kantonaleverwaltung

display_name: kantonaleverwaltung

regierungsrat

display_name: regierungsrat

de: Statistik der Informationszugangsgesuche nach IDG des Kantons Zürich ab 2013


de: Verzeichnis der Personenstammdaten ZH - Merkmale zu Verwaltungseinheiten

de: Abkürzungen und Definitionen sind in der Ressource "Verzeichnis der Personenstammdaten ZH - Abkürzungen und Definitionen" erklärt.

de: Verzeichnis der Personenstammdaten ZH - Merkmale zu Registern und Systemen

de: Im Rahmen des Impulsprojekts 3.1 "Strategie Datenmanagement und Data-Governance" wurde ein - nicht abschliessendes - Verzeichnis der Personenstammdaten erarbeitet, die von Einheiten der zentralen Verwaltung des Kantons Zürich zu ihrer fachspezifischen Aufgabenerfüllung verwaltet und/oder genutzt werden. Das Verzeichnis ist eine Grundlage für die Einführung eines koordinierten Stammdatenmanagements. Es wird in maschinenlesbarer Form zur Verfügung gestellt, um zweckmässige Anwendungen zu ermöglichen, mit denen es verwaltet und/oder genutzt werden kann. Das Verzeichnis wird unregelmässig aktualisiert. Die Verwaltungseinheiten sind für ihre Angaben verantwortlich. Bei Fragen, Korrekturen und Ergänzungen wenden Sie sich bitte an die Kontaktstelle.

kantonzuerich

display_name: kantonzuerich

de: Verzeichnis der Personenstammdaten der zentralen Verwaltung des Kantons Zürich


de: kantonzuerich kantonaleverwaltung

label: Datenkatalog

de: Suchbegriffe 2021, 3. Quartal

de: Maximal 1000 häufgste Suchbegriffe, die von Nutzenden im Quartal verwendet worden sind. Personennamen, Beleidigungen oder diskriminierenden Äusserungen wurden entfernt.

de: Suchbegriffe 2021, 2. Quartal

de: Suchbegriffe 2021, 4. Quartal

de: Suchbegriffe 2022, 1. Quartal

de: Nutzungsstatistiken der Metadatensätze von Verwaltungseinheiten und Organen des Kantons Zürich, die im Daten- und Publikationskatalogs des Kantons Zürich findbar sind. Verfügbar sind: von Nutzenden verwendete Suchbegriffe. Hinweise: Die Ressourcen zum Jahr 2020 beginnen ab dem Zeitpunkt der Einführung des neuen kantonalen Webauftritts per Anfang Juli 2020. Die Ressourcen zum Jahr 2021 umfassen alle vier Quartale. Die Ressourcen zum Jahr 2022 umfassen nur das erste Quartal. Ab April 2022 ist die Aktualisierung aufgrund der Einführung einer neuen Version des Katalogs pausiert.

de: Web Analytics des Daten- und Publikationskatalogs des Kantons Zürich ab April 2021 bis März 2022


maintainer: Matthias Haeni

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

en: Data plot of the forest station (ALB)

media_type: application/pdf

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

format: PDF

mimetype: application/pdf

en: Site aerial photo (Alpthal)

media_type: image/jpeg

en: Site aerial photo from the Alpthal forest station. Source: Google. 2016. Site aerial photo from the Alpthal forest station. Retrieved November 11, 2016, from https://www.google.ch/maps

format: SERVICE

mimetype: image/jpeg

en: Forest station data (ALB)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for one meteorological station in Alpthal in Switzerland which is located within a natural coniferous forest (ALB) with Norway spruce (_Picea abies_; 180-230 yrs) as dominant tree species. The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Alpthal is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

value: Envidat Harvester

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


gebaude-und-wohnungen-im-kanton-zurich

maintainer: Amt für Raumentwicklung des Kantons Zürich, Fachstelle Datenlogistik, Koordinationsstelle GWR-ZH

title_for_slug: gebaude-und-wohnungen-im-kanton-zurich

de: wohnung strassen wohnungen heizungsart gebaeude heizung wohnungsbestand gebaeudeart gemeinden

label: Bezug tagesaktueller Daten des eidg. GWR über die Schnittstelle des Bundes

label: Merkmalsbeschreibung des eidg. Gebäude- und Wohnungsregisters

de: Gebäudeeingänge bzw. Adressen pro Gebäude

media_type: application/octet-stream

de: Daten des eidg. GWR mit Bezug zu den einzelnen Eingängen zu einem Gebäude. Adressen beziehen sich auf einzelne Gebäudeeingänge und sind deswegen pro Eingang in diesem File zu finden. Die Merkmale entsprechen denen im Merkmalskatalogs des eidg. GWR (siehe Link unter 'weitere Informationen' im Datensatzbeschrieb) und sind dort beschrieben. Leerwerte wurden in den Gemeinden nicht ausgefüllt, ihr Wert ist unbekannt.

mimetype: application/octet-stream

de: Gebäude

de: Daten des eidg. GWR mit Bezug zu ganzen Gebäuden und ihrer Haustechnik. Aus den Daten lassen sich umfassende Angaben zum Gebäudebestand ablesen, beispielsweise zum Gebäudealter oder den Wärme- und Energiequellen. Die Merkmale entsprechen denen im Merkmalskatalogs des eidg. GWR (siehe Link unter "weitere Informationen" im Datensatzbeschrieb) und sind dort beschrieben. Leerwerte wurden in den Gemeinden nicht ausgefüllt, ihr Wert ist unbekannt. Für die einfachere Nutzung fügt die Fach- und Koordinationsstelle OGD vor der Publikation folgende Merkmale hinzu: Für das Merkmal 'Kanton' wird für alle Beobachtungen ZH abgefüllt. Das Merkmal 'Gemeindename' wird mittels BFS-Nummer entsprechend der Gemeindetabelle des Statistischen Amts ausgegeben. Das Merkmal 'Anzahl_Wohnungen' wird anhand der Ressource Wohnungen berechnet.

de: Wohnungen

de: Daten des eidg. GWR mit Bezug zu den einzelnen Wohnungen in einem Gebäude. Aus den Daten lassen sich beispielsweise Alter, Fläche, Lage im Gebäude und Ausstattungsangaben herauslesen. Die Merkmale entsprechen denen im Merkmalskatalogs des eidg. GWR (siehe Link unter "weitere Informationen" im Datensatzbeschrieb) und sind dort beschrieben. Leerwerte wurden in den Gemeinden nicht ausgefüllt, ihr Wert ist unbekannt.

de: Gebäude und Wohnungen im Kanton Zürich gemäss eidgenössischem Gebäude- und Wohnungsregister (eidg. GWR). Es verzeichnet die Gebäude und jede Wohnung im Kanton umfassend  in Merkmalen gemäss Merkmalsbeschreibung (siehe Link). Die Ressourcen lassen sich über die EGID verknüpfen. Das eidg. GWR wird durch die Gemeinden des Kantons Zürich geführt, die kantonale Koordinationsstelle GWR-ZH begleitet und berät sie dabei. Die Koordinationsstelle GWR-ZH stellt die Daten alle 3 Monate zur Verfügung und werden zum Stichtag vollständig ersetzt. Ein Zeitverlauf ist in den Daten nicht ersichtlich. Datenquelle bildet das eidg. GWR des Bundesamts für Statistik (BFS). Die Daten bilden den Stand des eidg. GWR ab, wie er durch die Gemeinden erfasst wird. Abweichungen vom tatsächlichen Zustand der Gebäude und Wohnungen sind möglich und im Bereich Energiequellen (Solaranlagen) sowie Wärmequellen (Heizungen) wahrscheinlich. Hinweise auf Abweichungen senden Sie bitte direkt an die Gemeinde, auf deren Boden sich das Objekt befindet, respektive an Statistik Stadt Zürich für Daten auf dem Stadtgebiet Zürich.

gebaeude

display_name: gebaeude

gebaeudeart

display_name: gebaeudeart

gemeinden

display_name: gemeinden

heizung

display_name: heizung

heizungsart

display_name: heizungsart

strassen

display_name: strassen

wohnung

display_name: wohnung

wohnungen

display_name: wohnungen

wohnungsbestand

display_name: wohnungsbestand

construction

fr: Construction, logement

de: Bau- und Wohnungswesen

en: Construction and housing

it: Costruzione e abitazione

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.

de: Gebäude und Wohnungen im Kanton Zürich


designprinzipien-fur-behorden

title_for_slug: designprinzipien-fur-behorden

label: UK government's design principles

de: 4 Leiste die harte Arbeit, die Sachen einfach zu machen

de: 7 Verstehe den Kontext

de: 8 Erstelle digitale Dienste, nicht Websites

de: 6 Es ist für alle

de: 10 Mach die Sachen offen: Es macht die Sachen besser

de: 9 Sei konsistent, nicht gleichförmig

de: 3 Gestalte mit Daten

de: 1 Beginne mit den Bedürfnissen der Nutzenden

de: 5 Iteriere. Dann iteriere erneut

de: 2 Mach weniger

de: 2012 hat der britische Government Digital Service (GDS) seine Designprinzipien für Behörden veröffentlicht. 2019 haben Designerinnen und Designer der GDS-Community für nutzerzentriertes Design für jedes Prinzip ein neues Poster gestaltet. Für unsere eigene Arbeit sind die Prinzipien so zentral, dass wir sie auf Deutsch übersetzt haben. Die Gestaltung unserer britischen Kolleginnen und Kollegen haben wir weitgehend übernommen. Unsere Poster stellen wir hier unter einer Creative Commons CC-BY Lizenz zur freien Wiederverwendung zum Download bereit. Auf die Originale des GDS verweisen wir unter «Weitere Informationen». Über unsere praktischen Erfahrungen mit der Anwendung der Prinzipien berichten wir laufend ebenda. Wir freuen uns auf den Erfahrungsaustausch mit anderen Anwenderinnen und Anwendern.

national-economy

de: Volkswirtschaft

de: Designprinzipien für Behörden


de: politischeparteien kantonsrat politik

label: Dokumentation zur Nutzung des Web Service des Geschäftsverwaltungssystems des Kantonsrates des Kantons Zürich

de: Beispielabfrage: Sitzungs- und Geschäftsdokumente des Kantonsrates des Kantons Zürich

media_type: application/xml

de: Sitzungs- und Geschäftsdokumente sind in drei Publikatonsbereichen abgelegt: https://parlzhcdws.cmicloud.ch/parlzh3/cdws/Files, https://parlzhcdws.cmicloud.ch/parlzh5/cdws/Files und https://parlzhcdws.cmicloud.ch/parlzh2/cdws/Files - effektive Enpoints werden gebildet durch Ergänzung um '/{id}/{rendition}/{fileType}'

format: XML

mimetype: application/xml

de: Direktionen und Organe im Gever des Kantonsrates des Kantons Zürich

de: Mitglieder des Kantonsrates des Kantons Zürich

de: https://parlzhcdws.cmicloud.ch/parlzh2/cdws/Index/MITGLIEDER/searchdetails?q=seq>0 and dauer_end >= "2020-11-19 00:00:00" and dauer_start <= "2020-11-19 00:00:00" and gremium all KR and funktion any "Mitglied Präsidium Vizepräsidium" sortBy name/sort.ascending vorname/sort.ascending&l=de-CH

de: Geschäfte des Kantonsrates des Kantons Zürich

de: https://parlzhcdws.cmicloud.ch/parlzh5/cdws/Index/GESCHAEFT/searchdetails?q=krnr any * sortBy beginn_start/sort.descending&l=de-CH&s=1&m=50 - Language: 'l=de-CH'; Query: 'q={searchparams}'; Anzahl Einträge: 'm=50'; Seite: 's=1' (somit erhält man mit 'm=50' die ersten 50 Einträge)

de: Gremientypen im Gever des Kantonsrates des Kantons Zürich

de: Sitzungen (Agenda) des Kantonsrates des Kantons Zürich und seiner Organe

de: https://parlzhcdws.cmicloud.ch/parlzh3/cdws/Index/SITZUNGENDETAIL/searchdetails?q=datum_start >= "2020-11-19 00:00:00" sortBy datum_end/sort.ascending uhrzeit/sort.ascending&l=de-CH

de: Parteien im Gever des Kantonsrates des Kantons Zürich

de: Wahlkreise im Gever des Kantonsrates des Kantons Zürich

de: Kommissionsmitglieder des Kantonsrates des Kantons Zürich

de: https://parlzhcdws.cmicloud.ch/parlzh2/cdws/Index/MITGLIEDER/searchdetails?l=de-CH&q=seq>0 and dauer_end >= "2020-11-19 00:00:00" and dauer_start <= "2020-11-19 00:00:00" and gremium adj KBIK sortBy name/sort.ascending vorname/sort.ascending - 'KBIK' = {Kommissionskurzname; Beispiel: Kommission für Bildung und Kultur}

de: Kantonsratsversand des Kantonsrates des Kantons Zürich

de: https://parlzhcdws.cmicloud.ch/parlzh1/cdws/Index/KRVERSAND/searchdetails?q=datum_start < "2020-11-19 00:00:00" sortBy datum_start/sort.descending&m=8&l=de-CH

de: Beispielabfrage: Fraktionsmitglieder des Kantonsrates des Kantons Zürich

de: https://parlzhcdws.cmicloud.ch/parlzh2/cdws/Index/MITGLIEDER/searchdetails?l=de-CH&q=seq>0 and dauer_end >= "2020-11-19 00:00:00" and dauer_start <= "2020-11-19 00:00:00" and gremium adj FRAAL sortBy name/sort.ascending vorname/sort.ascending - 'FRAAL' = {Fraktionskurzname; Beispiel: Fraktion Alternative Liste AL}

de: Fraktionen im Gever des Kantonsrates des Kantons Zürich

de: Kommissionen des Kantonsrates des Kantons Zürich

de: Medienmitteilungen des Kantonsrates des Kantons Zürich

de: Geschäftsarten des Kantonsrates des Kantons Zürich

de: Beispielabfrage: Fraktionsdetails des Kantonsrates des Kantons Zürich

de: https://parlzhcdws.cmicloud.ch/parlzh2/cdws/Index/BEHOERDEN/searchdetails?l=de-CH&q=kurzname adj FRAAL - 'FRAAL' = {Fraktionskurzname; Beispiel: Fraktion Alternative Liste AL}

de: Im Geschäftsverwaltungssystem (Gever) des Kantonsrates des Kantons Zürich werden sämtliche Geschäfte des Kantonsrates bewirtschaftet und dokumentiert. Über den Web Service können die im Internet publizierten Daten zu Geschäften, Sitzungen (Agenda) und (aktuellen) Mitgliedern nach Parteien, Fraktionen und Kommissionen abgerufen werden. Ebenso können Dokumente des Kantonsratsversands (jeweils die letzten 8 Versände) und die Kantonsrats-Protokolle (ab Mai 1995) bezogen werden. Die entsprechenden Endpunkte stehen als Ressourcen im Format XML zur Verfügung. Bei den Ressourcen handelt es sich um Endpunkte (teilweise als parametrisierte Beispielabfragen). Für Fragen und Rückmeldungen zu den Schnittstellen konsultieren Sie die Dokumentation unter "Weitere Informationen" oder wenden Sie sich per E-Mail an die bezeichnete Kontaktstelle.

kantonsrat

display_name: kantonsrat

politik

display_name: politik

politischeparteien

display_name: politischeparteien

politics

fr: Politique

de: Politik

en: Politics

it: Politica


maintainer: Dirk Nikolaus Karger

en: climatology bioclim climate-change free-climate-data temperature precipitation climate climate-layers

en: CHELSA V2.1 (current)

media_type: geotiff

en: CHELSA Version 2.1 based on ERA5 forcings and CMIP6

format: GeoTIFF

en: CHELSA V1.2 (deprecated)

en: CHELSA Version 1.2 based on ERA-Interim forcings and CMIP5

en: CHELSA Technical Documentation

media_type: PDF

en: Technical documentation document including the variable names, units, scaling, offset, and background.

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled temperature and precipitation to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction.

CHELSA data published in EnviDat includes the deprecated version 1.2 (originally published under 10.5061/dryad.kd1d4). Please use the current 2.1 version.

Paper Citation:
 > _Karger DN. et al. Climatologies at high resolution for the earth’s land surface areas, Scientific Data, 4, 170122 (2017) [doi: 10.1038/sdata.2017.122](https://doi.org/10.1038/sdata.2017.122)._

bioclim

display_name: bioclim

climate

display_name: climate

climate-change

display_name: climate-change

climate-layers

display_name: climate-layers

climatology

display_name: climatology

free-climate-data

display_name: free-climate-data

precipitation

display_name: precipitation

education

de: Bildung, Wissenschaft

envidat

de: EnviDat: das Umwelt-Datenportal

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.


de: kantonaleverwaltung kantonzuerich staat regierungsrat

label: Fachausschuss für offene Behördendaten

de: OGD FA Q4/2019 - Folien

media_type: text/html

de: Folien des Fachausschusses für offene Behördendaten des Kantons Zürich vom 5. November 2019.

format: HTML

mimetype: text/html

de: OGD FA Q3/2023 - Protokoll

de: OGD FA Q1/2021 - Folien

de: Folien des Fachausschusses für offene Behördendaten des Kantons Zürich vom 30. März 2021.

de: OGD FA Q3/2021 - Folien

de: Folien des Fachausschusses für offene Behördendaten des Kantons Zürich vom 20. September 2021.

de: OGD FA Q2/2023 - Protokoll

de: Protokoll OGD FA Q4/2022, 10. November 2022

de: OGD FA Q3/2019 - Folien

de: Folien des Fachausschusses für offene Behördendaten des Kantons Zürich vom 20. August 2019.

de: Protokoll OGD FA Q3/2022, 01. September 2022

de: OGD FA Q1/2020 - Folien

de: Folien des Fachausschusses für offene Behördendaten des Kantons Zürich vom 4. Februar 2020.

de: OGD FA Q4/2020 - Folien

de: Folien des Fachausschusses für offene Behördendaten des Kantons Zürich vom 9. Dezember 2020.

de: Protokoll OGD FA Q1/2022, 21. März 2022

de: OGD FA Q1/2023 - Protokoll

de: OGD FA Q2/2021 - Folien

de: Folien des Fachausschusses für offene Behördendaten des Kantons Zürich vom 31. Mai 2021.

de: OGD FA Q4/2021 - Protokoll

de: Protokoll des Fachausschusses für offene Behördendaten des Kantons Zürich vom 29. November 2021.

de: Der OGD-Fachausschuss ist das vom Regierungsrat eingesetzte Koordinationsgremium, das für die einheitliche Publikation offener Behördendaten sorgt. Er betreut die dazu notwendigen Standards, Vorgaben, Empfehlungen und sorgt für ihre bedarfsgerechte Weiterentwicklung. Er trifft sich mindestens dreimal jährlich. In ihm sind mindestens alle Verwaltungseinheiten und Organe des Kantons Zürich vertreten, die offene Daten bereitstellen.

kantonaleverwaltung

display_name: kantonaleverwaltung

kantonzuerich

display_name: kantonzuerich

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.

de: Unterlagen und Protokolle des Fachausschusses für offene Behördendaten des Kantons Zürich


disdrometer-data-gotschnagrat

maintainer: EnviDat Support

title_for_slug: disdrometer-data-gotschnagrat

en: disdrometer precipitation raclets hydrometeors visibility

en: Disdrometer Data Gotschnagrat

media_type: application/zip

en: The zip folder contains one netCDF file per day for Gotschnagrat from February 11 to March 27 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Gotschna_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

format: ZIP

mimetype: application/zip

en: A laser optical disdrometer (Parsivel² , OTT Hydromet) was deployed at Gotschnagrat (LON: 9.849, LAT: 46.859) to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms. The dataset contains information on precipitation amount and type for the period of February 11 to March 27 2019 at Gotschnagrat.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

raclets

display_name: raclets

visibility

display_name: visibility

education

de: Bildung, Wissenschaft

envidat

de: EnviDat: das Umwelt-Datenportal

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.


maintainer: Jonas Stillhard

en: long-term-data-sets forest primeval-beech-forest fagus-sylvatica stand-inventory-data carpathian-biosphere-reserve forest-dynamics permanent-forest-plot-data dem forest-structure

en: Data description

en: Available online on publishers website

en: Dataset

en:
In 2000, a permanent forest plot of 10 ha has been established in the core zone of the primeval beech forest of Uholka.
 All living and dead trees with a diameter at breast height (DBH) ≥ 60 mm were identified to species, DBH measured, stems tagged and mapped.
Since then, the plot has been remeasured in 2005, 2010, and 2015. In total, 4,820 individual trees were measured with 14,116 individual measurements throughout all four inventories.
In spring 2018, an Airborne Laser Scan was carried out, covering the Uholka‐Shyrokyi Luh forest. This data set allows us to derive a high‐resolution digital elevation model (DEM) of the plot area.
The data set allows for important insights into the development and the spatial and temporal dynamics of primeval beech forests.

carpathian-biosphere-reserve

display_name: carpathian-biosphere-reserve

dem

display_name: dem

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-structure

display_name: forest-structure

long-term-data-sets

display_name: long-term-data-sets

permanent-forest-plot-data

display_name: permanent-forest-plot-data

primeval-beech-forest

display_name: primeval-beech-forest

stand-inventory-data

display_name: stand-inventory-data

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Stand inventory data from the 10‐ha forest research plot in Uholka, Ukraine


maintainer: Mahdi Jafari

en: numerical-simulation snow-density-profile openfoam vapor-transport convection-in-snow

en: snowpackBuoyantPimpleFoam

media_type: ZIP

en:
This zipped folder includes (1) the source code files, (2) an example case for simulation, and (3) an instruction how to compile and use the new solver.

Note that the most updated version of snowpackBuoyantPimpleFoam can be found in the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/snow-models/snowpackbuoyantpimplefoam

en: snowpackBuoyantPimpleFoam is a two-phase solver implemented to model convection of water vapor with phase change in snowpacks. This new solver is based on the standard solver of buoyantPimpleFoam in the open-source fluid dynamics software, OpenFOAM 5.0 (www.openfoam.org).

convection-in-snow

display_name: convection-in-snow

numerical-simulation

display_name: numerical-simulation

openfoam

display_name: openfoam

snow-density-profile

display_name: snow-density-profile

vapor-transport

display_name: vapor-transport

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: snowpackBuoyantPimpleFoam: an OpenFOAM Eulerian–Eulerian two-phase solver for modelling convection of water vapor in snowpacks


wind-crust-formation-snowmicropen-data

title_for_slug: wind-crust-formation-snowmicropen-data

en: wind-crust snow snowmicropen smp wind-packing

en: README

media_type: text/plain

en: Describes the dataset in detail

format: TXT

mimetype: text/plain

en: Processing scripts

en: Contains the R-scripts used to process the SMPs

en: SMP data

media_type: Link

en: Links to the dataset

en:
This dataset contains the SnowMicroPen (SMP) data from 38 wind tunnel experiments on wind-packing / wind crust formation. These experiments were performed in the winters 2015/16 and 2016/17 and include more than 1000 SMP measurements.

The SMPs are organized per experiment. Each experiment subfolder contains the processed SMP profiles and some additional files.

Please refer to the README for more details on the data. The processing scripts are available for download as well. The scripts are mainly provided as documentation and would need to be adjusted to be used.

This dataset is the basis of the following publication:

Sommer C.G., Lehning M., & Fierz C. (2017). Wind tunnel experiments: Saltation is necessary for wind-packing. Journal of Glaciology, 63(242), 950-958. doi:10.1017/jog.2017.53

smp

display_name: smp

snow

display_name: snow

snowmicropen

display_name: snowmicropen

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

en: Wind crust formation: SnowMicroPen data


en: minimum-temperature free-climate-data climate precipitation maximum-temperature century air-temperature timeseries climate-layers

en: Data Access

en: CHELSA Technical Documentation

en: As the CHELSA project is continuously expanded, certain new parameters, time scales etc. are not included anymore in the original publication (Karger et al. 2017). We are therefore provide this document as a guideline of the current climatic parameters available and will expand it as new parameters or time periods will become available. Please refer to the version history for changes made in the document.

en:
CHELSAcruts is a delta change monthly climate dataset for the years 1901-2016 for mean monthly maximum temperatures, mean monthly minimum temperatures, and monthly precipitation sum. Here we use the delta change method by B-spline interpolation of anomalies (deltas) of the CRU TS 4.01 dataset. Anomalies were interpolated between all CRU TS grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2 (Karger et al. 2017, Scientific Data). This method has the assumption that climate only varies on the scale of the coarser (CRU TS) dataset, and the spatial pattern (from CHELSA) is consistent over time. This is certainly a rather crude assumption, and for time periods for which more accurate data is available CHELSAcruts should be avoided if possible (e.g. use CHELSA V1.2 for 1979-2015). Different to CHELSA V1.2, CHELSAcruts does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages.

CHELSAcruts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

century

display_name: century

climate

display_name: climate

climate-layers

display_name: climate-layers

free-climate-data

display_name: free-climate-data

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation

timeseries

display_name: timeseries

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: CHELSAcruts -  High resolution temperature and precipitation timeseries for the 20th century and beyond


en: climate-change snowmelt precipitation discharge soil-moisture hydrology

en: Shapefile of 307 catchments in Switzerland

en: Shapefile of the 307 medium-sized catchments in Switzerland. The "gridcode" provides the ID of the catchment used in the datafiles.

en: Daily simulated data for the future period

en: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the period 1981-2100 in mm for the 307 catchments.

en: Daily simulated data for the reference period

en: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the reference period 1981-2017 in mm.

en:
Daily discharge and the related hydro-meteorological variables precipitation, snowmelt, and soil moisture are provided for current (1981-2017) and for future climate conditions (1981-2100) for 307 medium-sized catchments in Switzerland. The catchments have a median catchment area of 117 km². The 307 catchments together form a set representative of the climatological conditions and runoff characteristics in Switzerland. The four variables were simulated at a daily resolution using the hydrological model PREVAH. PREVAH is a conceptual process-based model that was run in this study in its fully distributed version on a 500 m grid (Viviroli et al. 2009a). For the calibration, runoff time series from 140 mesoscale catchments covering the different runoff regimes were used. The model calibration was conducted over the period 1993-1997. Verification was performed on the period 1983-2005 using (i) volumetric deviation (Viviroli et al. 2007) and (ii) benchmark efficiency (Schäfli et al 2007) as objective functions. The calibration and validation procedures are described in detail in Köplin et al. (2010). The parameters for each model grid cell were derived by regionalizing the parameters obtained for the 140 catchments with a procedure based on ordinary kriging (Viviroli et al. 2009b, Köplin et al. 2010).
The calibrated and validated model was then driven with transient meteorological data (precipitation, temperature, radiation, and wind) representing both reference (1981-2017) and future climate conditions (2018-2099). The data were derived from the CH2018 climate scenarios (NCCS 2018) provided by the Swiss National Centre for Climate Services (NCCS). They were obtained from climate experiments produced with different climate modeling chains, consisting of a global and a regional circulation model each, within EUROCORDEX for three representative concentration pathways (RCP) emission scenarios. Downscaled output of ten climate model chains derived by quantile mapping were considered. The focus was on the chains of the EUR-11 domain with a horizontal resolution of 0.11 degrees (roughly 12.5 km). The climate model chains (GCM, RCM, RCP, and grid resolution) used are listed below:

- ICHEC-EC-EARTH	DMI-HIRHAM5	2.6	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	4.5	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	8.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	2.6	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	4.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	8.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	4.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	8.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	4.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	8.5	EUR-11

*References*:

-	Köplin, N., D. Viviroli, B. Schädler, and R. Weingartner (2010), _How does climate change affect mesoscale catchments in Switzerland? - A framework for a comprehensive assessment_, Advances in Geosciences, 27, 111-119, doi:10.5194/adgeo-27-111-2010.
-	National Centre for Climate Services (2018), CH2018 - _Climate Scenarios for Switzerland_, Tech. rep., NCCS, Zurich.
-	Schäfli, B., and H. V. Gupta (2007), _Do Nash values have value?_, Hydrological Processes, 21, 2075-2080, doi:10.1002/hyp.6825.
-	Viviroli, D., J. Gurtz, and M. Zappa (2007), _The hydrological modelling system PREVAH. Part II - Physical model description_, Geographica Bernensia, 40, 1-89.
-	Viviroli, D., M. Zappa, J. Gurtz, and R. Weingartner (2009a), _An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools_, Environmental Modelling & Software, 24, 1209-1222, doi:10.1016/j.envsoft.2009.04.001.
-	Viviroli, D., H. Mittelbach, J. Gurtz, and R. Weingartner (2009b), _Continuous simulation for flood estimation in ungauged mesoscale catchments of Switzerland-Part II: Parameter regionalisation and flood estimation results_, Journal of Hydrology, 377 (1), 208-225, doi:10.1016/j.jhydrol.2009.08.022.

climate-change

display_name: climate-change

discharge

display_name: discharge

hydrology

display_name: hydrology

snowmelt

display_name: snowmelt

soil-moisture

display_name: soil-moisture

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: Simulated future discharge and climatological variables for medium-sized catchments in Switzerland


photogrammetric-drone-data-dorfberg

title_for_slug: photogrammetric-drone-data-dorfberg

en: dsm uav drone-data snow snow-depth-mapping snow-distribution photogrammetry orthophoto

en: Data Access

media_type: TIF

en:
- 3cm-resolution Orthophoto
- 10cm-resolution DSM
- 10cm-resolution snow depth raster
- original RGB images
- Agisoft Metashape Report

All products are also available as a cloud optimized geotiff.

en: The data was collected with a Wingtra Gen II drone and a Sony RX1R II sensor. In total, 10 flights were conducted at different dates, both in summer and winter. A DSM, an orthophoto, a snow depth raster and the original drone images from every flight are available at a high resolution (10cm and 3cm, respectively).

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

snow

display_name: snow

snow-depth-mapping

display_name: snow-depth-mapping

snow-distribution

display_name: snow-distribution

uav

display_name: uav

en: Photogrammetric Drone Data Dorfberg


maintainer: Christian G. Sommer

en: snow wind-tunnel kinect wind-crust wind-packing

en: Kinect data

en: Links to the dataset

en: Processing scripts

en: Contains the Matlab- and R-scripts used to process the Kinect data

en: README

en: Describes the dataset in detail

en:
This data sets contains the Microsoft Kinect data from 15 wind tunnel experiments on wind-packing / wind crust formation. These experiments were performed in the winter 2016/17. The Kinect measures distributed snow depth.

The Kinect data is organized per experiment. Each experiment subfolder contains the processed Kinect depth images and some additional files.

Please refer to the README for more details on the data. The processing scripts are available for download as well. The scripts are mainly provided as documentation and would need to be adjusted to be used.

This dataset is the basis of the following publication:

Sommer C.G., Lehning M. & Fierz C. (2018). Wind Tunnel Experiments: Influence of Erosion and Deposition on Wind-Packing of New Snow. Front. Earth Sci. 6:4. doi: 10.3389/feart.2018.00004

kinect

display_name: kinect

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

wind-tunnel

display_name: wind-tunnel

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Wind crust formation: Microsoft Kinect data


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

en: Wetlands 1850 - 2010 (shapefiles)

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

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

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

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

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

ecology

display_name: ecology

environmental---history

display_name: environmental---history

environmental--policy

display_name: environmental--policy

historical-carthography

display_name: historical-carthography

switzerland

display_name: switzerland

wetlands

display_name: wetlands

en: 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: History of wetlands in Switzerland since 1850


en: visual-attractiveness online-questionnaire-survey adults-and-teenagers nfi-photos perception-of-ecosystem-services

en: Codebook to SPSS-file

en: SPSS-Dataset

en: Questionnaire French

media_type: .pdf

en: Questionnaire German

en: Dataset in csv-format

en: Questionnaire Italian

en: This questionnaire survey was conducted as an online survey and aimed at investigating the relationship between physical forest characteristics, visual attractiveness of forest and the perception of ecological and cultural ecosystem services in urban forests. Each participant was shown 6 photos out of a pool of 50 photos taken from the Swiss National Forest Inventory (NFI) database. Physical forest characteristics were derived from the photos. The study was conducted as part of the "WaMos meets LFI" (WML) project.

adults-and-teenagers

display_name: adults-and-teenagers

nfi-photos

display_name: nfi-photos

online-questionnaire-survey

display_name: online-questionnaire-survey

perception-of-ecosystem-services

display_name: perception-of-ecosystem-services

visual-attractiveness

display_name: visual-attractiveness

en: Relationship between physical forest characteristics, visual attractiveness and perception of ecosystem services in urban forests


maintainer: Peter Bebi

en: carbon-dioxide climate-change vegetation experiment soil-temperature stillberg

en: Data FACE Stillberg

en: Folder in .zip format containing the FACE datasets.

en: Project Description FACE Stillberg

media_type: HTML

en: Link to FACE project description on the WSL website.

en: Metadata FACE Stillberg Data File Description

media_type: CSV

en: List of descriptions for each of the .csv FACE data files.

en: Metadata FACE Stillberg Experimental Design

en: Schematic illustration and tabular listing of the FACE experimental design.

en:
 Background information

High elevation ecosystems are important in research about environmental change because shifts in climate associated with anthropogenic greenhouse gas emissions are predicted to be more pronounced in these areas compared to most other regions of the world. This project involved a Free Air CO2 Enrichment (FACE) and soil warming experiment located in a natural treeline environment near Davos, Switzerland (Stillberg, 2200 m a.s.l.). Elevated atmospheric CO2 concentrations (+200 ppm) were applied from 2001 until 2009, and a soil warming treatment (+4 °C) was applied from 2007 until 2012. The combined CO2 enrichment and warming treatment reflects conditions expected to occur in this region in approximately 2050. A broad range of ecological and biogeochemical research was carried out as part of this environmental change project.

 Experimental design

The experiment consisted of 40 hexagonal 1.1 m² plots, 20 with a *Pinus mugo* ssp. *uncinata* (mountain pine, evergreen) individual in the centre and 20 with a *Larix decidua* (European larch, deciduous) individual in the centre. A dense cover of understorey vegetation surrounded the tree in each plot, including the dominant dwarf shrub species *Vaccinium myrtillus* (bilberry), *Vaccinium gaultherioides* (group *V. uliginosum agg.*, northern bilberry) and *Empetrum nigrum* ssp. *hermaphroditum* (crowberry) plus several herbaceous and non-vascular species.
At the beginning of the experimental period, the 40 plots were assigned to ten groups of four neighbouring plots (two larch and two pine trees per group) in order to facilitate the logistics of CO2 distribution and regulation. Half of these groups were randomly assigned to an elevated CO2 treatment, while the remaining groups served as controls and received no additional CO2. In spring 2007, one plot of each tree species identity was randomly selected from each of the 10 CO2 treatment groups and assigned a soil warming treatment, yielding a balanced design with a replication of five individual plots for each combination of CO2 level, warming treatment and tree species.

 Data description

Soil and air conditions have been monitored closely throughout the study period, with most measurements made during the combined CO2 x warming experiment (2007-2009). The data comprise of air temperature, soil temperature, soil moisture, sapflow, tree diameter and CO2 measurements.

carbon-dioxide

display_name: carbon-dioxide

climate-change

display_name: climate-change

experiment

display_name: experiment

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

vegetation

display_name: vegetation

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: FACE: Stillberg CO2 enrichment and soil warming study


digitizing-historical-plague

maintainer: Christian Ginzler

title_for_slug: digitizing-historical-plague

en: plague-mapping bubonic-plague yersinia-pestis palaeo-epidemiology plague-outbreaks historical-plague plague-inventory black-death

en: We present newly digitized data on 6,929 plague outbreaks that occurred between 1347 and 1900 AD across Europe. The data base on an inventory initially published 1976. For georeferencing the information of Tele Atlas 2009 was used. The coordinates are in the reference systems ETRS89 and WGS84.

black-death

display_name: black-death

bubonic-plague

display_name: bubonic-plague

historical-plague

display_name: historical-plague

palaeo-epidemiology

display_name: palaeo-epidemiology

plague-inventory

display_name: plague-inventory

plague-mapping

display_name: plague-mapping

plague-outbreaks

display_name: plague-outbreaks

yersinia-pestis

display_name: yersinia-pestis

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: Digitizing historical plague


en: soil-ph ecological-maps plants soil-mapping landolt soil-moisture ecological-indicator-values switzerland

en: Predictors

en: Predictors generated and used in Descombes et al. (2020)

en: Description

en: Description of the predictors provided in this dataset

en:
Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we derived environmental data layers by mapping ecological indicator values (EIVs) in space by using a large set of environmental predictors in Switzerland.

This dataset contains the predictors (raster layers) generated and used in the following publication (Descombes et al. 2020). Only predictors for which we have the rights to share them are provided. Other datasets and predictors can be accessed via the original data provider. Details on the predictors and sources are fully described in the publication. The predictors are provided as GeoTIFF files, at 93 m spatial resolution and Mercator projection ("+proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"). The excel file (xlsx) provides a short description of the raster layers.

Paper Citation:

Descombes, P. et al. (2020). Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes. Ecography. (accepted)

ecological-indicator-values

display_name: ecological-indicator-values

ecological-maps

display_name: ecological-maps

landolt

display_name: landolt

plants

display_name: plants

soil-mapping

display_name: soil-mapping

soil-moisture

display_name: soil-moisture

soil-ph

display_name: soil-ph

switzerland

display_name: switzerland


maintainer: James W. Kirchner

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

en: 7-hourly stable water istopes

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

en: Weekly stable water isotopes

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

en: Data Set Documentation

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

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

catchment

display_name: catchment

chloride

display_name: chloride

deuterium

display_name: deuterium

plynlimon

display_name: plynlimon

precipitation

display_name: precipitation

stable-water-isotopes

display_name: stable-water-isotopes

streamflow

display_name: streamflow

tracer

display_name: tracer

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


en: forest-inventory structure-from-motion terrestrial-laser-scanning lidar 3d-point-cloud terrestrial-photogrammetry unmanned-aerial-vehicle-laser-scanning mobile-laser-scanning

en:
Close Range Remote Sensing Benchmark for different LiDAR and photogrammetric Sensors in a mixed temperate forest.
Benchmarks are needed to evaluate the performance of different close-range remote sensing devices and approaches, both in terms of efficiency as well as accuracy. In this study we evaluate the performance of two terrestrial (TLS), one handheld mobile (PLS) and two drone based (UAVLS) laser scanning systems to detect trees and extract the diameter at breast height (DBH) in three plots with a steep gradient in tree and understorey vegetation density. As a novelty, we also tested the acquisition of 3D point-clouds using a low-cost action camera (GoPro) in conjunction with the Structure from Motion (SfM) technique and compared its performance with those of the more costly LiDAR devices.

forest-inventory

display_name: forest-inventory

lidar

display_name: lidar

mobile-laser-scanning

display_name: mobile-laser-scanning

structure-from-motion

display_name: structure-from-motion

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

terrestrial-photogrammetry

display_name: terrestrial-photogrammetry

unmanned-aerial-vehicle-laser-scanning

display_name: unmanned-aerial-vehicle-laser-scanning

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Ramerenwald Close Range Remote Sensing Benchmark


wind-lidar-davos-wolfgang

title_for_slug: wind-lidar-davos-wolfgang

en: profiles wind wolfgangpass raclets lidar

en: Wind LIDAR data Wolfgang

en: A Leosphere WidCube 100S was deployed at Davos Wolfang, measuring wind profiles as well as performing PPI and RHI scans. Time format is in UTC with highest time resolution of 5 seconds.

en: Scanning wind Lidar from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 200 m above ground to 8100 m. The time resolution is up to 5 seconds. The Lidar was measuring wind profiles but also performed plan position indicator (PPI) and range height indicator (RHI) scans.

profiles

display_name: profiles

raclets

display_name: raclets

wind

display_name: wind

wolfgangpass

display_name: wolfgangpass

en: Wind LIDAR Davos Wolfgang


en: snow-avalanche snow-mechanics acoustic-emissions viscous-deformation sintering snow snow-failure fiber-bundle-model

en: fiber-bundle-model-for-snow-failure

en: Data underlying Figures in publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted to "Geophysical Research Letters"

en:
This dataset contains modeled and experimental results for laboratory snow failure experiments and the concurrent acoustic emissions signatures for different loading rates. For modelling the snow failure we used a fiber bundle model that includes sintering and viscous deformation.

The data underlay the figures in the publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted for publication to "Geophysical Research Letters".

acoustic-emissions

display_name: acoustic-emissions

fiber-bundle-model

display_name: fiber-bundle-model

sintering

display_name: sintering

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-mechanics

display_name: snow-mechanics

viscous-deformation

display_name: viscous-deformation

en: Fiber Bundle Model for snow failure and concurrent Acoustic Emissions


maintainer: Andrin Caviezel

en: stonenodedata deposition-points natural-hazards stonenode rockfall sensor-stream rockfall-runout dem induced-rockfall rockfall-experiments

en: Induced Rockfall Data, Tschamut, GR

en:
 Induced Rockfall Experimental Data, Tschamut, GR, Switzerland

The archive contains site specific geographical data as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally availabe are the StoneNode v1.0 sensor streams for the equipped rocks.

The _OverviewFigures_ file serves as quick representation of the included data. It also contains the overview table for the rock masses in order to set the dimensions accordingly in RAMMS::ROCKFALL.

The archive contains the following folders:
<\ul>
* DEM: ArcGIS compatible DEM Tschamut_DEM_2m (grid resolution of 2 m) as well as the .asc grid used in RAMMS::ROCKFALL simulations
* _DepositionPoints_: containing two folders _RF Tschamut Frozen_ and _RF Tschamut WET_ containing each a shapefile with the complete deposition data of each series as well as deposition shapfiles for each rock shape.
* _DigitizedRocks_: Digitized point clouds of the used rocks as used for RAMMS::ROCKFALL simulations (.pts files) (dimensions have to be checked).
* _Orthofoto_: Orthophoto of the experimental site obtained via UAV with 5 cm resolution.

en: StoneNode v1.0 Data for equipped experimental Runs.

en: Corresponding StoneNode v1.0 data streams belonging to the deposition points.

en:
 Dataset of an experimental campaign of induced rockfall in Tschamut, Grisons, Switzerland.

The data archive contains site specific geographical data such as DEM and orthophoto as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally available are all the StoneNode data streams for rocks equipped with a sensor. The data set consists of

* Deposition points from two series (wet (27/10/2016) and frozen (08/12/2016) ground)
* Digital Elevation Model (grid resolution 2 m) obtained via UAV
* Orthophoto (5 cm resolution) obtained via UAV
* Digitized rock point clouds (.pts input files for RAMMS::ROCKFALL)
* StoneNode v1.0 raw data stream for equipped rocks.

Further information is found in

* A. Caviezel et al., _Design and Evaluation of a Low-Power Sensor Device for Induced Rockfall Experiments_, IEEE Transactions on Instrumentation and Measurement, 2018, 67, 767-779, http://ieeexplore.ieee.org/document/8122020/
* P. Niklaus et al., _StoneNode: A low-power sensor device for induced rockfall experiments_, 2017 IEEE Sensors Applications Symposium (SAS), 2017, 1-6, http://ieeexplore.ieee.org/document/7894081/

dem

display_name: dem

deposition-points

display_name: deposition-points

induced-rockfall

display_name: induced-rockfall

natural-hazards

display_name: natural-hazards

rockfall

display_name: rockfall

rockfall-experiments

display_name: rockfall-experiments

rockfall-runout

display_name: rockfall-runout

sensor-stream

display_name: sensor-stream

stonenode

display_name: stonenode

stonenodedata

display_name: stonenodedata

en: Induced Rockfall Dataset (Small Rock Experimental Campaign), Tschamut, Grisons, Switzerland


en: biomass lidar terrestiral-laserscanning single-tree forest-inventory tree-volume

en: Individual tree parameters and volume estimates based on TLS point clouds and allometric models

en:
"ASM" denotes volume estimates calculated by allometric scaling models (as used in Swiss NFI), based on tree height, DBH and D7.
"QSM" denotes volume estimates derived from TLS point clouds by quantitative structure models (QSM).
The remaining variables are geometrical features directly calculated from single tree TLS point clouds.
For more detailed variable descriptions see related publication.

en:
 Dataset
This dataset is based on terrestrial laser scanning (TLS) data acquired during winter 2020/2021 in leaf-off conditions, with a Leica BLK 360 instrument following a tree-centric scanning pattern.
The data was acquired on two sites (47.42°N 8.49°E and 47.504°N, 7.78°E), both of which were managed mixed temperate forest stands.
Individual trees were semi-automatically segmented from the co-registered TLS point clouds.

 Background
Accurate estimates of individual tree volume or biomass within forest inventories are essential for calibration and validation of biomass mapping products based on Earth observation data.
Terrestrial laser scanning (TLS) enables detailed and non-destructive volume estimation of individual trees, with existing approaches ranging from simple geometrical features to virtual 3D reconstruction of entire trees. Validating such approaches with weight measurements is a key step before the integration of TLS or other close-range technologies into operational applications such as forest inventories.
In this study, we firstly evaluate individual tree volume estimation approaches based on 3D reconstruction through quantitative structure models (QSM) against destructive reference data of 60 trees and compare them to operational allometric scaling models (ASM).
Secondly, we determine the explanatory power of TLS-derived geometric parameters regarding total tree, stem, coarse wood and fine branch volume.

biomass

display_name: biomass

forest-inventory

display_name: forest-inventory

lidar

display_name: lidar

single-tree

display_name: single-tree

terrestiral-laserscanning

display_name: terrestiral-laserscanning

tree-volume

display_name: tree-volume

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Individual tree TLS point clouds for tree volume estimation


maintainer: Chunhong Zhao

en: austin urban-morphology land-dynamics land-use landscape

en: Land use dynamics in Austin since 1992

media_type: img

en: The present dataset is part of the published scientific paper Zhao C, Weng Q, Hersperger A M. Characterizing the 3-D urban morphology transformation to understand urban-form dynamics: a case study of Austin, Texas, USA. Landscape and urban planning, 2020, 203:103881. The overall objective of this paper is to understand urban form dynamics in the Austin metropolitan area for the periods 2006–2011 and 2011–2016. The study also aims to understand to what extent the changes in the built environment (in terms of ‘efficient growth’ versus ‘inefficient growth’) from the 1990s to 2016 in the Austin metropolitan area corresponded with ‘compact and efficient growth’ planning policy documents. The UMT distribution can be found in the paper. The area of transitioning UMT was provided in Table 2 and Table 3 can be found in the Appendix of the paper. A protocol was developed to perform the content analysis of the strategic plans and gather the data. The detailed list of protocol items can be found in Appendix B of the paper. This study demonstrates the advantage of applying Lidar data to characterize 3-D urban morphology type (UMT) transition and understand its dynamics, which helps develop a comprehensive understanding of the urbanization process and provides a tool for planning intentions and policies evaluation on urban development over time. The UMT maps can be found in Appendix A of the paper. The Lidar point datasets and the 30 × 30 m National Land Cover Database (NLCD) are the two main data sources of UMT mapping. Lidar datasets were gathered from different projects that had been conducted and collected by state agencies and other organizations between 2007 and 2017. Table A1 in the appendix in the paper shows the accuracies and acquisition parameters of the Lidar projects from 2007 to 2017. Land use/cover dynamics in Austin metropolitan area dataset provides Land use/cover patterns in the years 1992, 2001, 2004, 2006, 2008, 2011, 2013, 2016 with a spatial resolution of 30 meters. Since NLCD 1992 used a different classification system for the urban land classes, we first reclassified the NLCD 1992 using a customized Arcpy package.

austin

display_name: austin

land-dynamics

display_name: land-dynamics

land-use

display_name: land-use

landscape

display_name: landscape

urban-morphology

display_name: urban-morphology

en: Land use/cover dynamics in Austin metropolitan area since 1992


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

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

en: CORE Dataset (80 GB)

media_type: CORE

media_type: .sh

en:
Shell script to extract data from the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en:
Shell script to reproduce the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software for working with CORE will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en:
DISCLAIMER: CORE is still in development. Interested parties are warmly invited to join common development, to comment, discuss, find bugs, etc.

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

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

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

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

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

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

CORE Specifications:

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

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

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

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

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

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

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

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

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

Major issues to be solved:

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

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

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

Example

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

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

For full reproducibility, we provide the original data set and results, as well scripts for data encoding and extraction (see resources).

core

display_name: core

geodata

display_name: geodata

gridded-data

display_name: gridded-data

raster

display_name: raster

research-data-management

display_name: research-data-management

time-series

display_name: time-series

video-encoding

display_name: video-encoding


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

en: StationData

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

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


en: snow-sublimation isotopic-distillation stable-water-isotopes evaporation antarctica backward-trajectories lagrangian-analysis

en: Python scripts for data visualization

en: Scripts for generating the figures of the related research article and generating the data files (csv) from the model output

en: Data

media_type: zip-compressed folder of csv

en: Modeled data including the data shown in the figures of the related research article

en: Model code

en: Model Sublimation and Model Air Parcel (python scripts)

en: Readme

media_type: TXT

en: Meta data

en:
 Summary

This data set contains Python programming code and modeled data discussed in a related research article. We developed a simple isotope model to study the drivers of the particularly depleted vapour isotopic composition measured on the ship of the Antarctic Circumnavigation Expedition close to the outlet of the Mertz glacier, East Antarctica, in the 6-day period from 27 January 2017 to 1 February 2017. The model considers the stable water isotopologues H2(16O), H2(18O), and HD(16O). It uses data from the ERA5 reanalysis product with a spatial resolution of 0.25° x 0.25° (Hersbach et al., 2018) and 10-day backward trajectories for the location of the ship, published by Thurnherr et al. (2020a). Our data set includes the model code, Python scripts for visualizing the results, and data produced by the model including the results shown in the figures of the related research article. Here, we summarize the most important model characteristics while further details can be found in the readme.txt file and the related research article including its supporting information.

 Main model characteristics

The modeling approach consists of two steps called *Model Sublimation* and *Model Air Parcel*. The former estimates the isotopic compositions of the snow and sublimation flux across the Antarctic Ice Sheet using an Eulerian frame of reference while the latter models the vapour isotopic composition and specific humidity along air parcel trajectories using a Lagrangian frame of reference. The isotope effects of most phase changes are represented by equilibrium fractionation. Only for ocean evaporation, kinetic fractionation is additionally taken into account (original Craig-Gordon formula). For snow sublimation, two assumptions are tested: *Run E* assumes that sublimation is associated with equilibrium fractionation while *Run N* assumes that sublimation occurs without isotopic fractionation.

 Model Sublimation
Model Sublimation uses a simple one-dimensional mass-balance approach in each grid cell, considering snow accumulation due to snowfall and vapour deposition and snow ablation due to sublimation. The snowpack is represented by 100 layers of equal thickness (e.g., 1 cm) and density (350 kg m-3). The isotopic composition of snowfall is parameterized by generalizing a site-specific, empirical relationship between the daily mean air temperature and snowfall isotopic composition. In the case of vapour deposition, Model Sublimation assumes equilibrium fractionation and estimates the isotopic composition of the atmospheric vapour as the average value for two idealized situations: (i) locally sourced vapour which has the same isotopic composition as the sublimation flux; (ii) non-locally sourced vapour in isotopic equilibrium with snowfall. Model Sublimation is run with a time step of 1 h, independently of Model Air Parcel.

 Model Air Parcel
Every hour, an ensemble of trajectories arrives at different heights in the ABL above the ship. For each of these trajectories, we consider an air parcel with a constant volume of 1 x 1 x 1 m3. The air parcels are initialized at the first suitable time when the trajectories are located in the ABL, either over the ice-free ocean in conditions of evaporation or over snow (Antarctic Ice Sheet or sea ice). Subsequently, the masses of the water isotopologues in the air parcels are simulated with a time step of 3 h, considering vapour uptake or removal due to the moisture flux at the snow or liquid ocean surface (only if the parcel is in the ABL) and cloud/precipitation formation (if the saturation specific humidity is reached). Sea ice is taken into account in a very simplified way. We represent the sea ice by grid cells with a sea-ice cover of more than 90% and assume the isotopic composition of the sublimation flux to be identical to that in the nearest grid cell of the Antarctic Ice Sheet. The isotopic composition of the sublimation flux is taken from Model Sublimation whereas the isotopic composition of the vapour deposition flux (over snow) and condensation flux (over ice-free ocean) is simulated assuming an isotopic equilibrium with the air parcel. Isotope effects of cloud/precipitation formation are represented using the classic Rayleigh distillation model with equilibrium fractionation, where the cloud water is assumed to precipitate immediately after formation.

 References

Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horanyi, A., Munoz Sabater, J.,... others (2018). *ERA5 hourly data on single levels from 1979 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS)*. doi: 10.24381/cds.bd0915c6

Thurnherr, I., Wernli, H., & Aemisegger, F. (2020a). *10-day backward trajectories from ECMWF analysis data along the ship track of the Antarctic Circumnavigation Expedition in austral summer 2016/2017*. Zenodo. doi: 10.5281/zenodo.4031705

antarctica

display_name: antarctica

backward-trajectories

display_name: backward-trajectories

evaporation

display_name: evaporation

isotopic-distillation

display_name: isotopic-distillation

lagrangian-analysis

display_name: lagrangian-analysis

snow-sublimation

display_name: snow-sublimation

stable-water-isotopes

display_name: stable-water-isotopes

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Modeled Isotopic Composition of Water Vapour Along Air Parcel Trajectories in the Antarctic