de: polygondaten stzh vektordaten geoportal geodaten

de:
Gebietsgrenzen der evangelisch-reformierten Kirchenkreise in der Stadt Zürich

**Zweck**: Verwaltung

geoportal

display_name: geoportal

polygondaten

display_name: polygondaten

geography

de: Geographie

stadt-zurich

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

de: Gebietseinteilung der evangelisch-reformierten Kirchenkreise der Stadt Zürich


de: geobasidaten geodaten polygondaten stzh adressen punktdaten av geoportal vermessung bodenbedeckung liegenschaften archiv liniendaten

state: active

type: dataset

media_type: gpkg

format: GPKG

media_type: dxf

format: DXF

de: Web Map Tile Service

media_type: text/xml

format: XML

mimetype: text/xml

media_type: SHP

format: SHP

de: Web Feature Service

media_type: WFS

format: WFS

de: Web Map Service

media_type: WMS

format: WMS

de:
Die amtliche Vermessung (AV) liefert geometrische Daten zum Grundeigentum und ist die Grundlage für viele weitere Geodaten und Anwendungen in Wirtschaft, Verwaltung und Privatleben.
Achtung: Dies ist der Jahresendstand 2022 der AV-Daten!

**Zweck**: Als amtliche Vermessung im Sinne von Artikel 950 ZGB gelten die zur Anlage und Führung des Grundbuchs vom Kanton genehmigten und vom Bund anerkannten Vermessungen. Die Daten der amtlichen Vermessung sind Georeferenzdaten, die von Behörden des Bundes, der Kantone und der Gemeinden sowie von der Wirtschaft, der Wissenschaft und Dritten zur Gewinnung von Geoinformationen verwendet werden. Auf dem GeoServer sind für die stadtinternen Nutzenden optimierte Tabellenstrukturen aufgeschaltet.

adressen

display_name: adressen

archiv

display_name: archiv

av

display_name: av

bodenbedeckung

display_name: bodenbedeckung

geobasidaten

display_name: geobasidaten

geodaten

display_name: geodaten

liegenschaften

display_name: liegenschaften

liniendaten

display_name: liniendaten

punktdaten

display_name: punktdaten

stzh

display_name: stzh

vermessung

display_name: vermessung

construction

fr: Construction, logement

de: Bau- und Wohnungswesen

en: Construction and housing

it: Costruzione e abitazione

geography

fr: Géographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

name: Kataster, Geomatik + Vermessung, Tiefbau- und Entsorgungsdepartement

fr: Ville de Zurich

de: Stadt Zürich

en: City of Zurich

it: Cità di Zurigo

fr: Vous trouverez ici les données de la ville de Zürich. En parallèle, Open Data Zürich a son propre portail Open Data où vous pouvez trouver également des manuels et des documents sur le traitement des données. À de rares exceptions près, toutes les données publiées par Open Data Zürich sont sous une licence «Creative Commons Zero».

en: Here you find all publicly available data published by Open Data Zürich. In addition, the city of Zurich runs its own Open Data Portal, where you find manuals and documentation about the handling of datasets. With only a few exceptions, all datasets from Open Data Zürich are licensed under «Creative Commons Zero».

it:
Open Data Zürich propone qui dati pubblici della città di Zurigo, pronti alla libera utilizzazione.
La città di Zurigo dispone parallelamente di un proprio portale Open Data, sul quale sono disponibili anche istruzioni e documentazioni per contestualizzare i datasets.
A parte poche eccezioni tutte le datasets della città di Zurigo hanno una licenza «Creative Commons Zero».

political_level: commune

type: organization

approval_status: approved

key: guid

key: uri

value: ZH - DCAT Harvester

de: Amtliche Vermessungsdaten Stadt Zürich Jahresendstand 2022


de: geoportal stzh polygondaten zonenplan erganzungsplane geodaten abstandslinien liniendaten nutzungsplanung bauordnung vektordaten bzo

media_type: JSON

format: JSON

de:
Geodaten des Zonenplans und der Ergänzungspläne gemäss Art. 2 BauO.
Es handelt sich um ein Extrakt des Geodatensatzes "ÖREB-Kataster-STZH" und wird stadtintern als "Sekundärdatensatz ÖREB Nutzungsplaung" bezeichnet.

**Zweck**: Der Datensatz ist Teil der Bau- und Zonenordnung und somit gesetzlich vorgeschrieben.

abstandslinien

display_name: abstandslinien

bauordnung

display_name: bauordnung

bzo

display_name: bzo

erganzungsplane

display_name: erganzungsplane

nutzungsplanung

display_name: nutzungsplanung

vektordaten

display_name: vektordaten

zonenplan

display_name: zonenplan

administration

fr: Administration

de: Verwaltung

en: Administration

it: Amministrazione

name: Raumentwicklung & Architektur, Amt für Städtebau, Hochbaudepartement

de: Nutzungsplanung - kommunale Bau- und Zonenordnung (BZO)


adressen-stadt-zurich

maintainer: Open Data Zürich

title_for_slug: adressen-stadt-zurich

de: punktdaten vektordaten geoportal adressen stzh geodaten

media_type: CSV

format: CSV

de:
Die Gebäudeadressen der Stadt Zürich werden aus den amtlichen Vermessungsdaten erstellt und mit einem Hausnummernsortierschlüssel und mit Informationen (PLZ, Liegenschaften, etc.) ergänzt.

**Zweck**: Diese Daten werden von städtischen Dienstabteilungen in Applikationen mit Adresssuche und Info-Abfragen genutzt.

adressen

display_name: adressen

geoportal

display_name: geoportal

name: GIS-Zentrum, Geomatik + Vermessung, Tiefbau- und Entsorgungsdepartement

de: Adressen Stadt Zürich


de: stzh geoportal vektordaten parkanlagen punktdaten geodaten

de: Park.json (GeoJSON-Services)

de:
Standorte der Parkanlagen in der Stadt Zürich

**Zweck**: Auffinden und Darstellen der Daten im Kontaktparagraphen der städtischen Internetseiten sowie im Stadtplan.

parkanlagen

display_name: parkanlagen

geography

de: Geographie

population

fr: Population

de: Bevölkerung

en: Population

it: Popolazione

name: Park- und Grünanlagen, Grün Stadt Zürich, Tiefbau- und Entsorgungsdepartement

stadt-zurich

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

de: Park


landpreiszonen-zur-gebuhrenordnung

title_for_slug: landpreiszonen-zur-gebuhrenordnung

de: Web Feature Service

de: Web Map Tile Service

de: Web Map Service

de:
Die Gebührenordnung zum Sondergebrauchsregelemt der Stadt Zürich (GOSGR) regelt die Berechnung der Gebühr für die bauliche Inanspruchnahme öffentlichen städtischen Grundes zu privaten Zwecken. Dazu ist u.a. der Landwert am Ort der Benützung zu berücksichtigen.

**Zweck**: Der Datensatz dient der Festlegung, in welchem Gebiet die Nutzung stattfindet und welcher Tarif zur Anwendung kommt.

polygondaten

display_name: polygondaten

construction

de: Bau- und Wohnungswesen

name: Fachstelle Konzessionen, Tiefbauamt, Tiefbau- und Entsorgungsdepartement

de: Landpreiszonen zur Gebührenordnung


gastwirtschaftsbetriebe

title_for_slug: gastwirtschaftsbetriebe

de: adressen bar stzh geodaten standort ausgang geoportal sachdaten gastronomie essen vektordaten gastro punktdaten trinken

de:
Aktuelle Gastwirtschaftsbetriebe der Stadt Zürich, welche von der Fachgruppe «Bewilligung Gastro» der Stadtpolizei Zürich bewilligt wurden.

**Zweck**: Administration der Gastro-Bewilligungen.

ausgang

display_name: ausgang

bar

display_name: bar

essen

display_name: essen

gastro

display_name: gastro

gastronomie

display_name: gastronomie

geodaten

display_name: geodaten

sachdaten

display_name: sachdaten

standort

display_name: standort

trinken

display_name: trinken

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito

name: Bewilligung Gastro, Stadtpolizei, Sicherheitsdepartement

stadt-zurich

de: Stadt Zürich


widmungstafel

title_for_slug: widmungstafel

de: Widmungstafel.json (GeoJSON-Services)

de:
Widmungstexte zu den Strassenbenennungen mit den Positionen über die ganze Stadt Zürich

**Zweck**: Ist die Datengrundlage für den Unterhalt und Neubestellungen der Strassenbenennungsschilder.

punktdaten

display_name: punktdaten

stzh

display_name: stzh

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

name: Werkhof Zürich Nord, Tiefbauamt, Tiefbau- und Entsorgungsdepartement

de: Widmungstafel


de: fussverkehr geoportal frequenzen punktdaten verkehrszahlung stzh veloverkehr geodaten vektordaten

de:
Das Tiefbauamt erhebt seit 2009 die Velofrequenzen in der Stadt Zürich mit Hilfe automatischer Zählgeräte. Der Fussverkehr wird seit 2012 mit Geräten gezählt. Das Zählstellennetz wurde schrittweise gemäss einem definierten Standortkonzept ausgebaut und umfasst jeweils rund 20 - 25 Querschnitten im gesamten Stadtgebiet. Die damit erhobenen Daten bilden eine wichtige quantitative Grundlage zur Beurteilung der Veloförderung im Sinne von «Stadtverkehr 2025» und dem Masterplan Velo. Die Daten liegen richtungsgetrennt und auf Viertelstundenwerte aggregiert vor. Die Daten stellen Gerätewerte dar. Um die effektiven Frequenzen im Fuss- oder Veloverkehr zu bestimmen, müssen die angegebenen Korrekturfaktoren angewandt werden.
In diesem Datensatz sind nur die eigentlichen Standorte enthalten. Die dazugehörenden Zählwerte sind über Open Data Zürich erhältlich (https://data.stadt-zuerich.ch/dataset/ted_taz_verkehrszaehlungen_werte_fussgaenger_velo).

**Zweck**: Die erhobenen Daten werden für das Controlling von Stadtverkehr 2025 und Masterplan Velo benötigt. Sie bilden zudem eine wichtige Grundlage zur Dokumentation der Bedeutungen des Fuss- und Veloverkehrs und für die Erfolgskontrolle deren Förderung.

frequenzen

display_name: frequenzen

fussverkehr

display_name: fussverkehr

vektordaten

display_name: vektordaten

veloverkehr

display_name: veloverkehr

verkehrszahlung

display_name: verkehrszahlung

geography

de: Geographie

name: Grundlagen + Strategien, Tiefbauamt, Tiefbau- und Entsorgungsdepartement

stadt-zurich

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

de: Standorte der automatischen Fuss- und Velozählungen


de: geoportal vektordaten suchtbehandlung punktdaten gesundheit stzh geodaten

de: Web Map Service

de: Web Map Tile Service

de: Suchtbehandlung.json (GeoJSON-Services)

de: Web Feature Service

de:
Standorte der Suchtbehandlungen in der Stadt Zürich

**Zweck**: Auffinden und Darstellen der Daten im Kontaktparagraphen der städtischen Internetseiten sowie im Stadtplan.

geoportal

display_name: geoportal

gesundheit

display_name: gesundheit

suchtbehandlung

display_name: suchtbehandlung

health

fr: Santé

de: Gesundheit

en: Health

it: Sanità

de: Suchtbehandlung


de:
Standorte der Kehrichtcontainer im öffentlichen Raum für die Sammlung von Haushalts- und Betriebskehricht.

**Zweck**: Übersicht über die bestehende Entsorgungsinfrastruktur für Planungszwecke. ERZ intern werden die Daten zusätzlich zur Planung der Leerungen und zum betrieblichen Unterhalt der Sammelstellen verwendet.

administration

de: Verwaltung

name: Datenmanagement, Entsorgung + Recycling Zürich, Tiefbau- und Entsorgungsdepartement

stadt-zurich

de: Stadt Zürich

de: ERZ Kehrichtcontainer im öffentlichen Raum


strassenlarmemissionen-fur-bauherren

title_for_slug: strassenlarmemissionen-fur-bauherren

de: vektordaten geoportal strassenlarm larmgutachten liniendaten sonroad18 geodaten polygondaten stzh punktdaten iso9613-2

de:
Der Datensatz enthält Emissionen, Höhenpunkte, Gebäudedaten, Lärmschutzwände und die Bodenbedeckung.
Diese sind optimiert für Lärmberechnungstools um eine Lärmberechnung gemäss sonROAD18 / Iso9613-2 vorzunehmen.
Der Datensatz entspricht nicht dem Geobasisdatenmodell Strassenlärmbelastungskataster gemäss GeoIV144.
Die Emissionen sind Behördenverbindlich.

**Zweck**: Der Datensatz dient als Basis für Akustikgutachten nach sonROAD18 / Iso9613-2 die durch Bauherren bzw. Akustikbüros erstellt werden.
Der Datensatz, speziell die Emissionen, sind nicht für darstellungszwecke geeignet.
Für Darstellungszwecke wird der Datensatz "Strassenlärmkataster der Stadt Zürich" empfohlen, welcher dem Geobasisdatenmodell Strassenlärmbelastungskataster gemäss GeoIV144 entspricht.

larmgutachten

display_name: larmgutachten

liniendaten

display_name: liniendaten

polygondaten

display_name: polygondaten

strassenlarm

display_name: strassenlarm

territory

de: Raum und Umwelt

name: Lärmschutz, Umwelt- und Gesundheitsschutz, Gesundheits- und Umweltdepartement

de: Strassenlärmemissionen für Bauherren (inkl. 3D)


luftqualitat

title_for_slug: luftqualitat

de: vektordaten punktdaten __ stzh geoportal no2 geodaten

de: Luftqualitaet.json (GeoJSON-Services)

de:
Verschiedene Datensätze zur Luftqualität

**Zweck**: Beurteilung der Luftqualität

geodaten

display_name: geodaten

geography

de: Geographie

stadt-zurich

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

de: Luftqualität (3D)


friedhofkreise

title_for_slug: friedhofkreise

de: vektordaten friedhof geoportal stzh polygondaten geodaten

de: Web Feature Service

de: Web Map Service

de: Friedhofkreise.json (GeoJSON-Services)

de: Web Map Tile Service

de:
Administrative Einteilung der Stadt nach Friedhofzugehörigkeit

**Zweck**: Lokalisierung des zugehörigen Friedhofs.

friedhof

display_name: friedhof

name: Bestattungs- und Friedhofamt, Bevölkerungsamt, Präsidialdepartement

de: Friedhofkreise


recyclinghof

title_for_slug: recyclinghof

de: cargo abfall punktdaten sammelstelle vektordaten geoportal geodaten stzh

de: Recyclinghof.json (GeoJSON-Services)

de:
Standorte Recyclinghof

**Zweck**: Lokalisation der Standorte Recyclinghof

abfall

display_name: abfall

cargo

display_name: cargo

sammelstelle

display_name: sammelstelle

administration

de: Verwaltung

stadt-zurich

de: Stadt Zürich

de: Recyclinghof


de: rasterdaten richtplanung stzh verdichtung geodaten freiraumplanung raumentwicklung polygondaten liniendaten innenentwicklung geoportal offentliche-bauten-und-anlagen

media_type: TIFF

format: TIFF

de:
Der komm. Richtplan bezeichnet Gebiete für die qualitätsvolle bauliche Verdichtung, Flächen für die Versorgung mit öffent. Freiräumen sowie kommunalen öffent. Bauten und Anlagen. Er koordiniert die Themen Verkehr, Angebot erneuerbarer Energie sowie umwelt- und sozialverträgliche Entwicklung. Diese Geodatensätze zeigen die Konzept- und Hinweiskarten des Richtplantextes.

Wichtiger Hinweis zu den Vektordaten. Diese wurden initial im Adobe Illustrator im Massstab 1: 90'000 entwickelt und nun nachträglich ins Vektorformat überführt. Die Genauigkeit der Vektordaten und im speziellen die Abgrenzungen der Flächen ist daher immer kritisch zu hinterfragen und die Verwendung der Daten ist allenfalls nicht für alle Anwendungsfälle sinnvoll.

Stand: Festsetzung des Gemeinderats

**Zweck**: Kommunale Richtplanung

freiraumplanung

display_name: freiraumplanung

innenentwicklung

display_name: innenentwicklung

offentliche-bauten-und-anlagen

display_name: offentliche-bauten-und-anlagen

rasterdaten

display_name: rasterdaten

raumentwicklung

display_name: raumentwicklung

richtplanung

display_name: richtplanung

stzh

display_name: stzh

verdichtung

display_name: verdichtung

construction

de: Bau- und Wohnungswesen

energy

fr: Energie

de: Energie

en: Energy

it: Energia

population

de: Bevölkerung

territory

de: Raum und Umwelt

de: Kommunaler Richtplan Siedlung Landschaft öffentliche Bauten und Anlagen - Textkarten


de: luftbild geoportal rasterdaten orthophoto 1990 geodaten historisch stzh

de: Web Map Service

de:
Dieses historische Orthofoto wurde anhand analoger CIR-Luftbildern (Grün- Rot und IR-Kanal) von 1990 und dem Digitalen Geländemodell (DTM AV) inkl. Bruchkanten im Jahr 2015 erstellt. Das Farbbild (RGB) wurde anhand eines internen Prozesses berechnet. Die Auflösung (Raster) des Orthofotos ist 0.2cm.

**Zweck**: Georeferenzdaten Stadt Zürich

geoportal

display_name: geoportal

historisch

display_name: historisch

luftbild

display_name: luftbild

orthophoto

display_name: orthophoto

geography

de: Geographie

stadt-zurich

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

de: Orthofoto 1990 Stadt Zürich - Sommer


unuberbaute-bauzonen-in-kraft-genehmigt

title_for_slug: unuberbaute-bauzonen-in-kraft-genehmigt

de: gebaude-und-anlagen nutzungsplanung raumplanung wirtschaftliche-aktivitaten zonenplan

label: geocat.ch permalink

spatial: Kanton Luzern

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

format: SERVICE

de: Überbauungsgrad der unüberbauten Bauzonen des genehmigten Zonenplans, laufend aktualisiert

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

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

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

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

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

political_level: canton

capacity: public

value: LU-Kt - Geocat Harvester

de: Unüberbaute Bauzonen, in Kraft (genehmigt)


briefliche-stimmbeteiligung

title_for_slug: briefliche-stimmbeteiligung

de: demokratie abstimmung wahlen

de: json

media_type: application/json

de: Briefliche Stimmbeteiligung (json)

mimetype: application/json

license: CC BY 3.0 CH

de: csv

media_type: text/csv

de: Briefliche Stimmbeteiligung (csv)

mimetype: text/csv

de: Dieser Datensatz zeigt die briefliche Stimmbeteiligung der Urnengänge für die Stadt Basel. Vor Urnengängen informiert die Staatskanzlei regelmässig über den Stand der Stimmbeteiligung per brieflicher Abgabe.Die effektive Stimm-/Wahlbeteiligung inkl. persönlicher Stimmabgabe an der Urne steht erst nach der Auszählung am Abstimmungssontag fest und wird ebenfalls auf diesem Datenportal zur Verfügung gestellt (Kennzahlen Wahlen/Abstimmungen).

abstimmung

display_name: abstimmung

demokratie

display_name: demokratie

wahlen

display_name: wahlen

politics

fr: Politique

de: Politik

en: Politics

it: Politica

kanton-basel-stadt

fr: Canton de Bâle-Ville

de: Kanton Basel-Stadt

en: Canton of Basel-City

it: Cantone di Basilea-Città

de: Der Kanton Basel-Stadt veröffentlicht nach und nach Open Government-Datensätze von kantonalen Ämtern und Dienststellen. Die kantonale Fachstelle für Open Government Data ist als Koordinationsorgan zuständig für die Unterstützung der datenpublizierenden Verwaltungsstellen.

value: BS Kanton Stadt - DCAT Harvester

de: Briefliche Stimmbeteiligung


maintainer: Staatskanzlei Zug

fr: votation federal

de: abstimmung national

it: votazione nazionale

label: Descripziun dal format

label: Description du format

label: Formatbeschreibung

label: Descrizione del formato

identifier: csv

identifier: json

rm: Resultats finals da la votaziun federala "Volksinitiative vom 2. April 2019 «Löhne entlasten, Kapital gerecht besteuern» ", 26 da settember 2021, Kanton Zug, ordinà tenor vischnancas.

fr: Résultats finaux du vote fédéral "Volksinitiative vom 2. April 2019 «Löhne entlasten, Kapital gerecht besteuern» ", 26 septembre 2021, Kanton Zug, répartis par municipalités.

de: Schlussresultate der eidgenössischen Abstimmung "Volksinitiative vom 2. April 2019 «Löhne entlasten, Kapital gerecht besteuern» ", 26. September 2021, Kanton Zug, aufgeschlüsselt nach Gemeinden.

it: Risultati finali della votazione federale "Volksinitiative vom 2. April 2019 «Löhne entlasten, Kapital gerecht besteuern» ", 26 settembre 2021, Kanton Zug, suddivisi per municipalit.

federal

display_name: federal

national

display_name: national

nazionale

display_name: nazionale

plaun-naziunal

display_name: plaun-naziunal

votation

display_name: votation

votazione

display_name: votazione

votaziun

display_name: votaziun

staatskanzlei-zug

de: Staatskanzlei Zug

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

value: ZG-Kt - Staatskanzlei - DCAT Harvester


geography

fr: Géographie

de: Geographie

it: Geografia

territory

de: Raum und Umwelt

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

de: Datenshop

de: Produktansicht Geodatenshop

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

de: Geoinformation Kanton Luzern

de: Kataster der belasteten Standorte (KbS)


de: glassammelstelle altol geodaten geoportal sammelstellen altmetall glassammelstellen recycling punktdaten ol sammelstelle oel altglas glas wertstoff texttilien stzh metall

de: Web Feature Service

de: Web Map Service

de: Sammelstelle.json (GeoJSON-Services)

de: Web Map Tile Service

de:
Standorte der Wertstoffsammelstellen (Glas, Kleinmetall, Altöl und Textilien) in der Stadt Zürich

**Zweck**: Lokalisation der Standorte Wertstoffsammelstellen

altglas

display_name: altglas

altmetall

display_name: altmetall

altol

display_name: altol

geodaten

display_name: geodaten

glas

display_name: glas

glassammelstelle

display_name: glassammelstelle

glassammelstellen

display_name: glassammelstellen

metall

display_name: metall

oel

display_name: oel

ol

display_name: ol

punktdaten

display_name: punktdaten

recycling

display_name: recycling

sammelstelle

display_name: sammelstelle

sammelstellen

display_name: sammelstellen

texttilien

display_name: texttilien

wertstoff

display_name: wertstoff

administration

de: Verwaltung

stadt-zurich

de: Stadt Zürich

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.


media_type: gdb

format: GDB

de:
Dieser Datensatz beinhaltet nebst den aktuellen 3D-Modellen der Gebäude der Stadt Zürich auch jene, welche voraussichtlich in den nächsten ca. 3 Jahren realisiert werden (kurzfristigen Zukunft). Er ist eine Kombination der beiden Originaldatensätzen '3D-Dachmodell LoD2' und '3D-Blockmodell LoD1'. Teil dieses Datensatzes sind Gebäude, welche in der Amtlichen Vermessung den Status "real", "erstellt", "freigegeben" oder "eingereicht" haben. Somit handelt es sich um den Bestand in der kurzfristigen Zukunft (inkl. projektierten Gebäuden). Um eine bessere Verständlichkeit des Datensatzes zu erreichen, wurden gegenüber den Originaldatensätzen einige Attribute umbenannt, angereichert oder entfernt.
Grundriss und Fassade der 3D-Modelle basieren auf den Gebäudegrundrissen der Amtlichen Vermessung. Die Dachstrukturen sind auf Basis von Luftbildern photogrammetrisch bestimmt worden. Neuere oder projektierte Gebäude, von welchen noch keine detaillierten 3D-Dachmodelle vorhanden sind, sind vereinfacht als Blockmodelle modelliert.

**Zweck**: Ein 3D-Stadtmodell liefert die Grundlagen für folgende, wichtige Einsatzgebiete:
- Lärmkataster
- Sichtbarkeitsanalysen
- Schattenberechnungen
- Visualisierungen grosser Bau- und Infrastrukturprojekte
- Stadtplanung
- Städtebauliche Betrachtungen
- Fahrsimulatoren
- Einsatzunterstützung Blaulichtorganisationen
- Standortmarketing
- Tourismus
- Solarenergiepotentialberechnungen
- ...

geoportal

display_name: geoportal

polygondaten

display_name: polygondaten

stzh

display_name: stzh

vektordaten

display_name: vektordaten

construction

fr: Construction, logement

de: Bau- und Wohnungswesen

it: Costruzione e abitazione

geography

de: Geographie

name: Geoinformatik, Geomatik + Vermessung, Tiefbau- und Entsorgungsdepartement

de: Bauten - Kombinierte Darstellung kurzfristige Zukunft (3D)


maintainer: Fachstelle für OGD Basel-Stadt

de: richterin gericht richter wahlen

de: csv

de: Wahl von fünf Präsidentinnen oder Präsidenten des Appellationsgerichts (csv)

de: json

de: Wahl von fünf Präsidentinnen oder Präsidenten des Appellationsgerichts (json)

de: Dieser Datensatz zeigt die Schlussresultate des 1. Wahlgangs der Wahl von fünf Präsidentinnen oder Präsidenten des Appellationsgerichts Basel-Stadt vom 9. Mai 2021.

gericht

display_name: gericht

richter

display_name: richter

richterin

display_name: richterin

wahlen

display_name: wahlen

legislation

fr: Législation

de: Gesetzgebung

en: Legislation

it: Legislazione

politics

de: Politik

kanton-basel-stadt

de: Kanton Basel-Stadt

de: Der Kanton Basel-Stadt veröffentlicht nach und nach Open Government-Datensätze von kantonalen Ämtern und Dienststellen. Die kantonale Fachstelle für Open Government Data ist als Koordinationsorgan zuständig für die Unterstützung der datenpublizierenden Verwaltungsstellen.


ausbauetappen-fernwarme-ewz

title_for_slug: ausbauetappen-fernwarme-ewz

de: stzh polygondaten fernwarme vektordaten ausbauetappen geoportal geodaten

de: Web Map Service

de: Web Feature Service

de: Web Map Tile Service

de:
Definition der Perimeter der Ausbauetappen der Fernwärmeversorgung in den neuen Fernwärmegebieten Höngg und Altstetten Nord (nördlich der SBB-Bahnlinie)

**Zweck**: Planung des  Ausbaus der Wärmeverteilung in den neuen Fernwärmegebieten

ausbauetappen

display_name: ausbauetappen

fernwarme

display_name: fernwarme

geodaten

display_name: geodaten

administration

de: Verwaltung

energy

de: Energie

name: Q, ewz, Elektrizitätswerk der Stadt Zürich, Departement der Industriellen Betriebe

stadt-zurich

fr: Ville de Zurich

it: Cità di Zurigo

fr: Vous trouverez ici les données de la ville de Zürich. En parallèle, Open Data Zürich a son propre portail Open Data où vous pouvez trouver également des manuels et des documents sur le traitement des données. À de rares exceptions près, toutes les données publiées par Open Data Zürich sont sous une licence «Creative Commons Zero».

it:
Open Data Zürich propone qui dati pubblici della città di Zurigo, pronti alla libera utilizzazione.
La città di Zurigo dispone parallelamente di un proprio portale Open Data, sul quale sono disponibili anche istruzioni e documentazioni per contestualizzare i datasets.
A parte poche eccezioni tutte le datasets della città di Zurigo hanno una licenza «Creative Commons Zero».

de: Ausbauetappen Fernwärme (ewz)


maintainer: Bundesamt für Energie BFE

title_for_slug: Publikationen des Bundesamtes für Energie und des Programms EnergieSchweiz

de: berichte studien dokumente publikationen medien broschuren flyer ogd98-bfe

fr: Publications de l'Office fédéral de l'énergie et du programme SuisseEnergie

fr:
Cette liste contient toutes les publications de l'Office fédéral de l'énergie et du programme SuisseEnergie qui sont disponibles gratuitement et en téléchargement direct.

Les conditions d'utilisation (O-By) se réfèrent uniquement au contenu de cette liste et non au contenu des documents.

de:
Diese Liste enthält alle Publikationen des Bundesamts für Energie und des Programms Energieschweiz, die kostenlos und als direkter Download zur Verfügung stehen.

Die Nutzungsbedingungen (O-By) beziehen sich nur auf den Inhalt dieser Liste und nicht auf den Inhalt der Dokumente.

berichte

display_name: berichte

broschuren

display_name: broschuren

dokumente

display_name: dokumente

flyer

display_name: flyer

medien

display_name: medien

publikationen

display_name: publikationen

studien

display_name: studien

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

industry

fr: Industrie, services

de: Industrie, Dienstleistungen

en: Industry and services

it: Industria, servizi

mobility

de: Mobilität und Verkehr

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

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

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

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

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

political_level: confederation


maintainer: Staatsarchiv des Kantons Zürich

de: Erlasse der Zürcher Gesetzessammlung ab 1803

media_type: application/zip

format: ZIP

mimetype: application/zip

de: Sämtliche Erlasse der Zürcher Gesetzessammlung von 1803 bis 1998. Umgesetzt als XML Dateien nach Vorgaben der TEI. Die Daten stehen unter einer Creative Commons CC-BY-SA 4.0 Lizenz zur Verfügung.

regierungsrat

display_name: regierungsrat

agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

en: Agriculture, forestry

it: Agricoltura, selvicoltura

construction

de: Bau- und Wohnungswesen

en: Construction and housing

crime

fr: Criminalité, droit pénal

de: Kriminalität, Strafrecht

en: Crime, criminal justice

it: Criminalità, diritto penale

national-economy

fr: Economie nationale

de: Volkswirtschaft

it: Economia

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

energy

fr: Energie

mobility

fr: Mobilité et transports

it: Mobilità e trasporti

politics

de: Politik

social-security

fr: Protection sociale

de: Soziale Sicherheit

en: Social security

it: Sicurezza sociale

staatsarchiv-kanton-zuerich

de: Staatsarchiv Kanton Zürich

de: Das Staatsarchiv ist das Archiv des Kantons Zürich und seiner Rechtsvorgänger. Es bewertet, übernimmt, erschliesst und konserviert Unterlagen aus über tausend Jahren Zürcher Geschichte. Durch die Aufbewahrung dieser Unterlagen macht es staatliches Handeln nachvollziehbar und ermöglicht historische Forschung. Das Staatsarchiv gewährt allen Interessierten Einsicht in diejenigen Bestände, die keinen Beschränkungen mehr unterliegen. Der grösste Teil der Findmittel zu den Archivbeständen kann online abgefragt werden.

value: ZH-Kt Staatsarchiv - DCAT Harvester


maintainer: EnviDat Support

en: strategic-plans europe urban-region development-priorities spatial-information

en: Planning intentios

en:
The present dataset is part of the report titled Gradinaru S.R., Hersperger A.M., Schmid F. (2021). Deriving Planning Intentions from written planning documents. Report on CONCUR Project- From plans to land change: how strategic spatial planning contributes to the development of urban regions.
The data corresponds to the data collected as part of the DPI Method for deriving all PIs contained in a plan (open coding) as detailed in section 4 of the report. The method involved reading the plans to break down of information in meaningful discrete “incidents” or planning intentions. To identify the planning intentions, the starting points were represented by a) the structuring of the plans in chapters and sub chapters and b) the themes that the plans addressed. Thus, the collected information was not grouped according to pre-defined categories of planning intentions, but rather put together as a list of intentions as revealed by each plan. As a result, we provide, for each case study, a document (named [Urban region name] PI as defined in the plan) which contains:
	Date when the information was filled in.
	Name of the urban region and analysed strategic spatial plan .
	A list of all planning intentions contained in a plan, with each PI being addresses as follows:
	Name of PI as it appears in the plan
	Translated name of the PI (i.e. short name for easy understanding of the meaning)
	Explanation regarding the meaning of the PI
	Why the PI is considered a priority for the urban region
	Spatial information on the PI (text and cartographic representations).
In total, 14 documents are available, one for each case study. Documents contain up to 20 pages of information extracted from the plans together with explanations and notes taken during plan reading.

development-priorities

display_name: development-priorities

europe

display_name: europe

spatial-information

display_name: spatial-information

strategic-plans

display_name: strategic-plans

urban-region

display_name: urban-region

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: Planning intentions in strategic plans of European urban regions


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

en: README

media_type: text/plain

en: Describes the dataset in detail

format: TXT

mimetype: text/plain

en: Dataset

media_type: Link

en: Links to the dataset

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

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

This dataset is the basis of the following publication:

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

antarctica

display_name: antarctica

drifting-snow

display_name: drifting-snow

mass-flux

display_name: mass-flux

meteorological-data

display_name: meteorological-data

snowmicropen

display_name: snowmicropen

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

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


fr: bilan-electricite ogd51-bfe production-nette production-d-electricite statistique-electricite energie-hydraulique consommation-de-courant saldo-import energies-renouvelables consommation-nationale pompes-d-accumulation energie-atomique production-d-electricite-thermique

de: stromverbrauch thermische-stromproduktion landesverbrauch elektrizitaetsbilanz nettoerzeugung wasserkraft kernkraft ogd51-bfe elektrizitaetsstatistik importsaldo speicherpumpen stromproduktion erneuerbare-energien

it: produzione-netta produzione-d-elettricita energie-rinnovabili saldo-importazioni pompe-d-accumulo consumo-nazionale bilancio-elettricita energia-idrica statistica-elettricita produzione-d-elettricita-termica ogd51-bfe energia-atomica consumo-di-corrente

fr: Statistiques heddomadaires: production et consommation d'énergie électrique en Suisse

it: Bilancio dell'elettricità: statistica settimanale - produzione e consumo di energia elettrica in Svizzera

author: Bundesamt für Energie BFE

label: BFE - Elektrizitätsstatistik

media_type: SERVICE

mimetype: SERVICE

fr: Cette statistique, élaborée chaque mercredi, recense la production, l'importation, l'exportation et la consommation d'électricité en Suisse. Elle présente la production hydraulique (centrales au fil de l'eau/centrales à accumulation), la production des centrales nucléaires ainsi que la production thermique classique et d'autres modes de production. Elle indique aussi la consommation des installations de pompage d'accumulation. Elle est établie dans le cadre de la Statistique de l'électricité, qui fait partie de la statistique publique de la Suisse (base légale: LSF).

de: Die Wochenstatistik Elektrizitätsbilanz - Erzeugung und Abgabe elektrischer Energie in der Schweiz gibt Auskunft über Produktion, Import / Export und Verbrauch von Elektrizität in der Schweiz jeweils am Mittwoch auf wöchentlicher Basis. Bei der Produktion werden die Hydrologische Erzeugung (Lauf- und Speicherwerke), die Erzeugung der Kernkraftwerke sowie die Konv.-therm. und andere Erzeugung unterschieden. Der Verbrauch der Speicherpumpen wird ausgewiesen. Die Wochenstatistik Elektrizitätsbilanz wird im Rahmen der Elektrizitätsstatistik erhoben, welche Teil der öffentlichen Statistik der Schweiz ist (gesetzliche Grundlage: BStatG).

bilan-electricite

display_name: bilan-electricite

bilancio-elettricita

display_name: bilancio-elettricita

consommation-de-courant

display_name: consommation-de-courant

consommation-nationale

display_name: consommation-nationale

consumo-di-corrente

display_name: consumo-di-corrente

consumo-nazionale

display_name: consumo-nazionale

elektrizitaetsbilanz

display_name: elektrizitaetsbilanz

elektrizitaetsstatistik

display_name: elektrizitaetsstatistik

energia-atomica

display_name: energia-atomica

energia-idrica

display_name: energia-idrica

energie-atomique

display_name: energie-atomique

energie-hydraulique

display_name: energie-hydraulique

energie-rinnovabili

display_name: energie-rinnovabili

energies-renouvelables

display_name: energies-renouvelables

erneuerbare-energien

display_name: erneuerbare-energien

importsaldo

display_name: importsaldo

kernkraft

display_name: kernkraft

landesverbrauch

display_name: landesverbrauch

nettoerzeugung

display_name: nettoerzeugung

pompe-d-accumulo

display_name: pompe-d-accumulo

pompes-d-accumulation

display_name: pompes-d-accumulation

production-d-electricite

display_name: production-d-electricite

production-d-electricite-thermique

display_name: production-d-electricite-thermique

production-nette

display_name: production-nette

produzione-d-elettricita

display_name: produzione-d-elettricita

produzione-d-elettricita-termica

display_name: produzione-d-elettricita-termica

produzione-netta

display_name: produzione-netta

saldo-import

display_name: saldo-import

saldo-importazioni

display_name: saldo-importazioni

speicherpumpen

display_name: speicherpumpen

statistica-elettricita

display_name: statistica-elettricita

statistique-electricite

display_name: statistique-electricite

stromproduktion

display_name: stromproduktion

stromverbrauch

display_name: stromverbrauch

thermische-stromproduktion

display_name: thermische-stromproduktion

wasserkraft

display_name: wasserkraft

statistical-basis

fr: Bases statistiques

de: Statistische Grundlagen

en: Statistical basis

it: Basi statistiche

national-economy

en: National economy

bundesamt-fur-energie-bfe

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


maintainer: Marcus Schaub

en: tree-species scots-pine dbh drought diameter-at-breast-height crown-condition tree forest swiss-forest-lab lwf irrigation

media_type: XLSX

format: XLS

en: Shapefile	of measurement location

media_type: URL

en: Swiss Forest Health Inventory

media_type: text/html

format: HTML

mimetype: text/html

en: Site photo 3

media_type: JPEG

en: Site photo 1

en: Site photo 2

en: Long-term Irrigation	Experiment Pfynwald homepage

en: To study the performance of mature Scots pine (_Pinus sylvestris_ L.) under chronic drought conditions in comparison to their immediate physiological response to drought release, a controlled long-term and large-scale irrigation experiment has been set up in 2003. The experiment is located in a xeric mature Scots pine forest in the Pfynwald (46° 18' N, 7° 36' E, 615 m a.s.l.) in one of the driest inner-Alpine valleys of the European Alps, the Valais (mean annual temperature: 9.2°C, annual precipitation sum: 657 mm, both 1961-1990). Tree age is on average 100 years, the top height is 10.8 m and the stand density is 730 stems ha-1 with a basal area of 27.3 m2 ha-1. The forest is described as _Erico Pinetum sylvestris_ and the soil is a shallow pararendzina characterized by low water retention. The experimental site (1.2 ha; 800 trees) is split up into eight plots of 1'000 m2 each. During April-October, irrigation is applied on four randomly selected plots with sprinklers of 1 m height at night using water from an adjacent water channel. The amount of irrigation corresponds to a supplementary rainfall of 700 mm year-1. Trees in the other four plots grow under naturally dry conditions. Soil moisture has been monitored since the beginning of the project at 3 soil depths (10, 20 and 60 cm). The crown condition of each tree is being assessed each year since 2003. Tree measurement data such as diameter at breast height, tree height, and social status were assessed in 2002, 2009 and 2014. The duration of the irrigation experiment is planned for 20 years.

crown-condition

display_name: crown-condition

dbh

display_name: dbh

diameter-at-breast-height

display_name: diameter-at-breast-height

drought

display_name: drought

forest

display_name: forest

irrigation

display_name: irrigation

lwf

display_name: lwf

scots-pine

display_name: scots-pine

swiss-forest-lab

display_name: swiss-forest-lab

tree

display_name: tree

tree-species

display_name: tree-species

education

en: Education and science

en: Tree measurements 2002-2016 from the long-term irrigation experiment Pfynwald, Switzerland


root-traits

maintainer: Ivano Brunner

title_for_slug: root-traits

en: drought soil-coring belowground-biomass fine-root-traits ingrowth-cores

en: Root-traits

en:
Fine-root traits of Scots pine in response to enhanced soil water availability deriving from long-term irrigation in the Pfynwald

Data_Fig.1.xlsx
Fine-root biomass of the topsoil (0-10 cm) in the dry and irrigated treatment of the Scots pine forest of the years 2003 to 2016 recorded by soil coring

Data_Tab1+2_2005.xlsx
Fine-root traits from roots of ingrowth cores from 2005 after two years of growth in the dry and irrigated treatment of the Scots pine forest

Data_Tab1+2_2016.xlsx
Fine-root traits from roots of ingrowth cores from 2016 after two years of growth, and from roots of the soil-coring sampling from 2016 in the dry and irrigated treatment of the Scots pine forest

belowground-biomass

display_name: belowground-biomass

fine-root-traits

display_name: fine-root-traits

ingrowth-cores

display_name: ingrowth-cores

soil-coring

display_name: soil-coring

envidat

en: EnviDat: the Environmental Data Portal

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


maintainer: Andrin Caviezel

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

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

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

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

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

en: StationData

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

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

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

Publications:

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

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

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

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

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

orographic-precipitation

display_name: orographic-precipitation

precipitation-variability

display_name: precipitation-variability

snow-precipitation

display_name: snow-precipitation

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


maintainer: Henning Löwe

en: snow-mechanics 3d-ct-images unconfined-compression-experiments discrete-element-modelling spherical-model-snow microstructure

en: Data Structure (Python Notebook)

media_type: ipynb

en: Data Structure (Python Notebook - view online)

en: Data Access

media_type: HTTPS

en:
For the investigation of microstructural and mechanical properties of snow unconfined compression experiments and 3D computed tomography (CT) imaging were performed on sintered rounded grain snow and spherical model snow. The spherical model snow was generated to create geometrically simplified, well-defined microstructures for calibration of numerical models, such as discrete element models (DEM) in which the microstructure is represented by spherical particles.
In the experiments, microstructural variation was created by varying the sintering time (contact size) and the density of the ice sphere samples (number of contacts). The 3D CT images allow for a complete reconstruction of the entire experimental sample (cylindrical sample dimension: diameter = 33.6 mm; height = 14 mm).

discrete-element-modelling

display_name: discrete-element-modelling

microstructure

display_name: microstructure

snow-mechanics

display_name: snow-mechanics

spherical-model-snow

display_name: spherical-model-snow

unconfined-compression-experiments

display_name: unconfined-compression-experiments

education

en: Education and science

en: Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples


data-analysis-toolkits

title_for_slug: data-analysis-toolkits

en: statistics data-analysis bayesian-inference uncertainty hypothesis-testing error-propagation

en: Toolkit 1: graphically displaying data distributions

media_type: application/pdf

format: PDF

mimetype: application/pdf

en: Toolkit 4: confidence intervals

en: Toolkit 11: serial correlation

en: Tools for detecting and correcting for serial correlation in analyses of time series

en: Toolkit 9: Experimentwise error rates and statistical fishing expeditions

media_type: .pdf

en: Statistical fishing expeditions, and how to avoid being misled by them

en: Toolkit 5: uncertainty analysis and error propagation

en: Gaussian error propagation, monte carlo methods, and first-order, second-moment error propagation

en: Toolkit 7: hypothesis testing, significance, and power

en: An overview of basic concepts -- and common pitfalls -- in statistical hypothesis testing, statistical significance, and power analysis

en: Toolkit 10: linear regression

en: An overview of the math, logic, and pitfalls of ordinary least-squares linear regression

en: Toolkit 3: tools for transforming data

en: The ladder of powers and a few other cool transformations

en: Toolkit 8: Hodges-Lehmann estimators

en: A quick introduction to Hodges-Lehmann estimators (nonparametric measures of effect size)

en: Toolkit 12: weighted averages and their uncertainties

en: There are two different ways to calculate the uncertainty of a weighted average. Software packages often don't tell you which one they are reporting, and the resulting errors can be huge.

en: Toolkit 2: quantifying data distributions using descriptive statistics

en: toolkit 6: averaging in nonlinear functions

en: The average of a nonlinear function will not equal the function evaluated at its average inputs (the mean of the function will differ from from the function of the mean). This toolkit shows how to estimate that averaging bias.

en:
These are condensed notes covering selected key points in data analysis and statistics. They were developed by James Kirchner for the course "Analysis of Environmental Data" at Berkeley in the 1990's and 2000's. They are not intended to be comprehensive, and thus are not a substitute for a good textbook or a good education!

License: These notes are released by James Kirchner under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.

bayesian-inference

display_name: bayesian-inference

data-analysis

display_name: data-analysis

error-propagation

display_name: error-propagation

hypothesis-testing

display_name: hypothesis-testing

statistics

display_name: statistics

uncertainty

display_name: uncertainty

envidat

en: EnviDat: the Environmental Data Portal

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


maintainer: Felix Neff

en: insects restoration long-term-experiment functional-diversity functional-traits topsoil-removal diversity grassland

en: Insect abundance

en:
Abundance of adult insects recorded in the samplings on all experimental sites

- **Plot**: ID of Plot
- **Treatment**: Experimental treatment
- **Species**: Insect species name (following [Fauna Europaea](https://fauna-eu.org))
- **Author**: Author and year of species' description (following [Fauna Europaea](https://fauna-eu.org))
- **Group**: Insect group as used in the analyses
- **Number_Adults**: Number of adult individuals recorded
- **Herbivore**: Logical indicating whether the species is feeding as a herbivore (*TRUE*) or not (*FALSE*)

en: Insect traits

en:
Functional traits of all herbivorous insect species sampled in the study.

- **Species**: Insect species name (following [Fauna Europaea](https://fauna-eu.org))
- **Author**: Author and year of species' description (following [Fauna Europaea](https://fauna-eu.org))
- **Group**: Insect group as used in the analyses
- **Body volume**: Body volume determined by body length, body width and body height (in mm$^3$)
- **Body_shape**: Ratio of body length to body width
- **Hind_femur_shape**: Ratio of hind-femur length to hind-femur width
- **Hind_front_leg_ratio**: Ratio of front-leg length to hind-leg length (leg length = femur length + tibia length)
- **Wing_length_rel**: Ratio of wing length to body length
- **Leg_length_rel**: Ratio of front-leg length to body length (leg length = femur length + tibia length)
- **Antenna_length_rel**: Ratio antenna length to body length
- **Eye_width_rel**: Ratio of eye width to head width (Auchenorrhyncha, Heteroptera) / to head height (Orthoptera)
- **Feeding_specialization**: Insect specialization on food source (*m*: monophagous, *o*: oligophagous, *p*: polyphagous)
- **Feeding_tissue**: Feeding tissue used for feeding (*c*: chewers, *x*: xylem, *p*: phloem, *m*: mesophyll, *m-p/r*: mesophyll as well as phloem and/or reproductive organs, *r*: reproductive organs, *se*: ripe seeds)
- **Hibernation**: Hibernation stage (*e*: egg, *e/n*: egg and nymph, *n*: nymph, *a*: adult)
- **Generations**: Number of generations per year (*1.5* stands for *1-2* generations per year)
- **Moisture_pref_mean**: mean of preferred habitat moistures (*1*: xerophilous, *2*: moderately xerophilous, *3*: moderately mesohygrophilous, *4*: mesohygrophilous, *5*: moderately hygrophilous, *6*: hygrophilous, *7*: moderately hydrophilous, *8*: hydrophilous)
- **Moisture_pref_range**: range of preferred habitat moistures (indicating degree of specialization)

en: Plot information

en:
Information on the experimental plots.

- **Plot**: ID of Plot
- **Treatment**: Experimental treatment
- **Landuse_history**: recent agricultural use for Initial; agricultural use before restoration for all restored sites
- **Last_tilled**: Last time the site was tilled
- **Intensity**: Frequency and intensity of mowing and manuring (*intensity1*: mowing once and no manure, i*ntensity2*: 2-3 times mowing and no manure, *intensity3*: 2-3 times mowing and manuring, *intensity4*: 4-5 times mowing and manuring)
- **Slope**: slope gradient according to classes defined by FAO (1990)
- **X**: X coordinate of the plot (CH1903)
- **Y**: Y coordinate of the plot (CH1903)
- **Cluster**: Spatial cluster of the plot

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

**Paper Citation**:

Neff, F., Resch, M. C., Marty, A., Rolley, J. D., Schütz, M., Risch, A. C, Gossner, M. M. 2020. Long-term restoration success of insect herbivore communities in semi-natural grasslands: a functional approach. Ecological Applications, 30, e02133. [10.1002/eap.2133](https://doi.org/10.1002/eap.2133)

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

 Methods

 Study site
The study area is situated within and nearby to Eigental nature reserve (47°27’36” to 47°29’06” N, 8°37’12” to 8°37’44” E, 461 to 507 m a.s.l.) in the vicinity of Zurich airport (Canton Zurich, Switzerland). Mean annual precipitation and temperature is 903 ± 136 mm and 9.14°C ± 0.50°C (mean ± SD for 2007-2017 (*MeteoSchweiz 2018*)). In 1967, the Eigental nature reserve was established to protect small and isolated remnants of species-rich, semi-natural grasslands (roughly 12 ha), which were embedded in an otherwise intensively managed landscape. It is characterized by oligo- to mesotrophic Molinion (semi-wet, matrix species *Molinia caerulea*) and Mesobromion (semi-dry, matrix species *Bromus erectus*) meadows (*Delarze et al. 2015*), reflecting small-scale habitat heterogeneity, mainly due to site-specific groundwater levels and slope inclination. As in most Central European grasslands, management is necessary to prevent shrub and tree invasions as well as to secure low levels of available soil nutrients and thus to maintain these species-rich habitats ([*Poschlod and WallisDeVries 2002*](https://doi.org/10.1016/S0006-3207(01)00201-4)).
In 1990, the government of the Canton Zurich decided to enlarge the Eigental nature reserve as a counter measure against degradation and biodiversity loss in semi-natural grasslands due to overutilization and the excessive input of nutrients (mostly nitrogen). Eleven patches of adjacent intensively managed grassland (in total roughly 20 ha) were targeted to be transformed into semi-natural grasslands. As a first restoration measure, fertilization was ceased, and biomass harvested three times to remove excessive soil nutrients from the original system and thus benefit plant species with low competitive ability on the long run. In 1995, the restoration efforts were increased and a large-scale experiment comprising three restoration measures with increasing intervention intensities was implemented:

- **Harvest only**: Initial restoration measures were continued with mowing and removing of the aboveground biomass two times a year (early summer and autumn).
- **Topsoil**: Removal of topsoil, depending on the thickness of the A horizon the upper 10 to 20 cm, in four randomly selected areas within the eleven patches in late autumn 1995. The size of the restoration area depended on individual patch size (2700 to 7000 m2).
- **Topsoil + Propagules**: Plant propagules were added on half of the area where topsoil was removed via application of fresh, seed-containing hay and hand-collected propagules of target species originating from semi-dry and semi-wet species-rich grasslands with local and regional provenance (within radius of 7 to 30 km) (1995, 1996, 1997).

Management of *Topsoil* and *Topsoil + Propagules* started five years after treatment implementation and included yearly mowing and removing of aboveground biomass (late summer or early autumn). The experiment was complemented with intensively managed grassland sites that share the same agricultural history as the restored sites (**Initial**; swards dominated by *Lolium perenne*, *L. multiflorum* and *Trifolium repens*): mowing and subsequent fertilizing (manure) up to five times a year, as well as different tillage regimes. Finally, sites were selected in target semi-dry and semi-wet grasslands (**Target**) located within the Eigental nature reserve and another nature reserve nearby (Altläufe der Glatt; 47°28’29” to 47°27’41” N, 8°31’56” to 8°32’26” E, 418 to 420 m a.s.l.). The selected target sites are mown and aboveground biomass removed once a year in late summer or early autumn. For each of the five treatments, we selected eleven plots (5 m × 5 m) spread across the sites. Altogether, the experiment included 55 plots.

 Arthropod sampling
Aboveground arthropods were sampled using suction sampling on four consecutive days in early July 2017 before the grasslands were mown. Arthropods were sampled in two locations on each 5 m × 5 m plot, once in the south-western and once in the north-eastern corner to account for possible spatial heterogeneity within the plots. Arthropods were sorted to order or lower taxonomic levels and individuals were identified to species level. We focused on three groups (Hemiptera: Auchenorrhyncha, Hemiptera: Heteroptera, Orthoptera),

 Functional traits
We used two sets of functional traits in this study.

**Morphometric traits**:
Body volume, body shape, hind femur shape, hind/front leg ratio, wing length, leg length, antenna length and eye width. We used trait measurements from [*Simons et al. (2016)*](http://dx.doi.org/10.1890/15-0616.1) and [*Neff et al. (2019)*](https://doi.org/10.1007/s10980-019-00872-1) and complemented them with measurements on study specimens. These measurements were conducted using a high-resolution measuring stereo microscope (Leica DVM6, Leica Microsystems) including automated high-resolution photo stacking with the software Leica Application Suite X (LAS X, © 2018 Leica Microsystems CMS GmbH) and Leica Map Premium (Leica Microsystems, © 1996-2017 Digital Surf) at WSL Birmensdorf. The eight morphometric traits were calculated from direct measurements of body parts on specimens of all sampled species. From each species, we measured at least one female and one male specimen. Additionally, for species that show wing dimorphism, we included the different wing morphs and weighted them by their prevalence reported in literature. For few species, of which not all wing morphs were available for measurements (10 cases), we estimated relative wing length from congeneric species or from the literature.

**Life-history traits**
Based on an existing data set collected by [*Gossner et al. (2015)*](http://dx.doi.org/10.1890/14-2159.1). We included traits describing different life-history characteristics of herbivore insect species, namely: feeding specialization, feeding tissue, hibernation stage and number of generations per year, which are related to insect species’ vulnerability to changes in plant community composition, microhabitat use and disturbance tolerance. To represent potential changes in habitat moisture with abandonment of intensive land use (e.g., change in ground-water level), we also included two traits related to preferred habitat moisture of the study species: moisture preference, describing species’ optimum habitat moisture, and moisture range, which describes the species’ range of preferable moisture conditions.

 References

Delarze, R., Y. Gonseth, S. Eggenberg, and M. Vust. 2015. Lebensräume der Schweiz: Ökologie - Gefährdung - Kennarten. 3rd ed. Ott, Bern.

Gossner, M. M., N. K. Simons, R. Achtziger, T. Blick, W. H. O. Dorow, F. Dziock, F. Köhler, W. Rabitsch, and W. W. Weisser. 2015. A summary of eight traits of Coleoptera, Hemiptera, Orthoptera and Araneae, occurring in grasslands in Germany. Scientific Data 2:150013.

MeteoSchweiz. 2018. Klimabulletin Jahr 2017. MeteoSchweiz, Zürich.

Neff, F., N. Blüthgen, M. N. Chisté, N. K. Simons, J. Steckel, W. W. Weisser, C. Westphal, L. Pellissier, and M. M. Gossner. 2019. Cross-scale effects of land use on the functional composition of herbivorous insect communities. Landscape Ecology 34:2001–2015.

Poschlod, P., and M. F. WallisDeVries. 2002. The historical and socioeconomic perspective of calcareous grasslands—lessons from the distant and recent past. Biological Conservation 104:361–376.

Simons, N. K., W. W. Weisser, and M. M. Gossner. 2016. Multi-taxa approach shows consistent shifts in arthropod functional traits along grassland land-use intensity gradient. Ecology 97:754–764.

diversity

display_name: diversity

functional-diversity

display_name: functional-diversity

functional-traits

display_name: functional-traits

grassland

display_name: grassland

insects

display_name: insects

long-term-experiment

display_name: long-term-experiment

restoration

display_name: restoration

topsoil-removal

display_name: topsoil-removal

education

en: Education and science

en: Grassland restoration: insects and insect traits


en: precipitation-amount shortwave-radiation humidity longwave-radiation snow-depth air-temperature

en: Overview plot

media_type: PNG

en: Overview plots of all variables in timeseries.

format: PNG

en: STB2 CSV

en: Stillberg meteo as CSV (see smet for metadata header)

en: DATA ACCESS

media_type: SMET

en: Meteorological station data 1975-2016. Outlier analysis and general quality control has been carried out. Station was completely renovated in 2007 and instruments changed. A complete air temperature timeseries can be obtained by combining parameters "TA" and "AIR_TEMP_FUEHLER".

en: Site photo 1

en: Snow sensor perpendicular to slope.

en: README

media_type: TXT

en: Description of station parameters and history.

en: Latest data from Stillberg climate station

en: This dataset represents the latest data from the Stillberg climate station updated daily. Automated quality control procedures are applied but no manual checks as in the main dataset.

en: Site photo 3

en: Site photo 2

en: Longterm meteorological and snow station on a steep (c. 40 degrees) North-East exposed slope at 2090 m a.s.l above Davos, Switzerland. Established 1975 and ongoing measurements made, although instruments have changed during this period. The station is located within a experimental plantation that serves as avalanche protection to downslope communities as well as a unique site for treeline dynamics research.

air-temperature

display_name: air-temperature

humidity

display_name: humidity

longwave-radiation

display_name: longwave-radiation

precipitation-amount

display_name: precipitation-amount

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

en: Long-term meteorological and snow station at 2090 m a.s.l., Stillberg, Davos, Switzerland (1975 - present)


en: snow-stratigraphy snowpack snow-profiles snow-instability snowpack-simulation failure-layer rutschblock

en: Simulated snow profiles

media_type: .csv

en: Simulated snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding observed profile in the "observed_profiles" folder. One row corresponds to one simulated snow layer. The content of the columns 1-7 is described in Table 3 of the ReadMe file. The remaining columns (8-31) contain all features that were used in the development of the RF model and are described in Table 1 of the ReadMe file.

en: DAV data set: Properties of observed snow profiles and simulated failure layers

media_type: CSV

en:
For each profile pair from the DAV data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. The content of the columns is explained in Table 1 of the ReadMe file. Only those profile pairs which fulfilled predefined similarity criteria (column
"similarity_obs_sim" = 1) and which belonged to the stability classes "stable" and "unstable" (column "stability_class"
= 0 or 1) were used to train the RF model. Please note that for each of the two snow profiles with RB score 7 (profile
IDs 7228 and 9526), three additional layers were included in this data set to obtain a balanced set of training data (73
unstable and 73 stable profiles).

en: Observed snow profiles

en: Observed snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding simulated profile in the "simulated_profiles" folder. One row corresponds to one observed snow layer. The content of the columns is described in Table 2 of the ReadMe file.

en: SWISS data set: Properties of observed snow profiles and simulated failure layers

en: For each profile pair from the SWISS data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. Please note that only those profile pairs which fulfilled the similarity criteria (column similarity_obs_sim = 1, 121 profiles) were used to validate the RF model. The content of the columns is explained in Table 1 of the ReadMe file.

en: ReadMe

en: ReadMe file explaining data structure and content

en:
This data set includes information on all observed and simulated snow profiles that were used to train and validate the
random forest model described in Mayer et al. (2022). The RF model was trained to assess snow instability from simulated snow stratigraphy. The data set contains observed snow profiles from the region of Davos (DAV subset, 512 profiles) and from all over Switzerland (SWISS subset, 230 profiles). For each observed snow profile, there is a corresponding simulated profile which was obtained using meteorological input data for the numerical snow cover model SNOWPACK. The information on the observed snow profile contains a Rutschblock test result including the depth of the failure interface. As part of the study described in Mayer et al. (2022), each observed snow profile was manually compared to its simulated counterpart and the simulated layer corresponding to the Rutschblock failure layer was identified.

The data are provided in the following form: one file each per observed and simulated snow profile (2x512 files DAV, 2x230 files SWISS), two files (1 file DAV, 1 file SWISS) containing the observed information on snow instability, the allocation between observed and simulated failure layer, and all features extracted from the simulated weak layers that were used to develop the RF model.

failure-layer

display_name: failure-layer

rutschblock

display_name: rutschblock

snow-instability

display_name: snow-instability

snow-profiles

display_name: snow-profiles

snow-stratigraphy

display_name: snow-stratigraphy

snowpack

display_name: snowpack

snowpack-simulation

display_name: snowpack-simulation

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: Observed and simulated snow profile data


maintainer: Alexandre Buttler

en: biogeochemisty climate-change silvopastoral-systems soil transplantation-experiment

en: Dataset

media_type: application/zip

en: Zip archive of all datasets detailed in study.

en:
Silvopastoral systems are highly productive and combine long-term wood production with annual provision of forage for livestock. In the Swiss Jura Mountains these systems are a key component of the landscape. As in other cold biomes, climate change can potentially accelerate landscape change within these historically sustainable systems.

In order to anticipate the evolution of subalpine wooded pasture ecosystems under future climate and land-use changes, this project focused on the interplay between soil, vegetation and climate. It was aimed at providing experimental evidence for chief ecosystem processes, with emphasis on the quality of the ecosystem services provided. The main interest was placed on vegetation turf resistance to climate change along an unwooded – sparsely wooded - densely wooded pasture gradient (land-use intensity), where plant productivity, diversity and succession along with rates of carbon cycling and microbial activity provided measures of ecosystem functioning at both plot and landscape level.

Experimental transplantation of monolith soil turfs to lower altitudes allowed to simulate soil warming and reduced annual precipitation. In order to simulate a year-round warmer and drier climate the natural climate variation along an altitudinal gradient was used as a proxy. The aim was to simulate realistic climate change scenarios for the second half of the 21st century predicted by the IPCC report and downscaled for Switzerland providing regionalized interpolated projections integrating therein trends for temperature increase and precipitation decrease. By using permanent meteorological stations within the network of the Federal Office of Meteorology and Climatology (MeteoSwiss), we obtained high resolution regional data on the variation of mean annual temperature (MAT) and mean annual precipitation (MAP) in relation to altitude in the Swiss Jura Mountains. We observed a general increase of +0.5 K in MAT and a decrease of -20 % MAP for each 100 m decrease in altitude along the SE slope of the Swiss Jura Mountains. These relationships served for the selection of the transplantation sites such that in comparison to a control site at 1350 m a.s.l. (Combe des Amburnex, N 46°54’, E 6°23’) a +2 K MAT and -20 % MAP was achieved at 1010 m a.s.l. (Saint-George, N 46°52’, E 6°26’), a +4 K MAT and -40 % MAP at 570 m a.s.l., (Arboretum d’Aubonne, N 46°51’, E 6°37’), and a +5 K MAT and -50 % MAP at 395 m a.s.l. (Les Bois Chamblard, N 46°47’, E 6°41’). The two stations at 1010 m a.s.l. and 570 m a.s.l. corresponded to the IPCC scenario A1B for a moderate increase in greenhouse gas emissions and to scenario A2 for a high increase in greenhouse gas emissions, respectively. The station at 395 m a.s.l. was chosen to represent an extreme scenario with climate variables lying at the positive tail distribution of model predictions under the A2 scenario.

Soil cores were assembled into rectangular PVC boxes of 60  80 cm2 size and of 35 cm height. All mesocosms were dug down to surface level into previously prepared trenches in the ground thus preventing lateral heat exchange with the atmosphere. Since at each site the mesocosms were placed in a common garden with no light interception, mesocosms with turfs from the two wooded pastures were shaded from direct sun light to simulate the natural light conditions in the corresponding habitats. Each mesocosm was equipped with a drainage system and was connected to a water tank thus representing a zero potential lysimeter collecting soil solution and precipitation/snowmelt runoff. ECH2O EC-TM sensor probes coupled to Em50 data-loggers (Decagon Devices, Inc., USA) recorded soil temperature and volumetric water content in each mesocosm at the top-soil (0 to -3 cm) every minute and data were averaged over one hour intervals. Climate parameters at each transplantation site were monitored continuously throughout the experiment by means of automated weather stations (Sensor Scope Sàrl, Switzerland), measuring rain precipitation (non-heated tipping bucket gauges) and air temperature and humidity 2 m above the ground surface at one minute intervals.

A list of above- and belowground variables were measured to assess the resilience of biogeochemical processes, plant productivity, tree regeneration, and carbon sequestration for each respective land-use practice. Furthermore, the experimental data were used to improve on (parameterization) the existing spatially explicit, dynamic model WoodPaM and refine the modelʼs climatic and land-use variables so that different scenarios of climate change and land use change could be simulated. Natural and management induced disturbance patterns were incorporated into the model.
The data have been made available within the project CCES Mounted. The climate stations Sensorscope are still in use within the project CLIMARBRE (Wald und Klimawandel, WSL/BAFU).

#References

1. Puissant, J., Cécillon, L., Mills, R.T.E., Robroek, B.J.M. Gavazov, K., De Danieli, S., Spiegelberger, T., Buttler, A., Brun, J.J. 2015. Seasonal influence of climate manipulation on microbial community structure and function in mountain soils. Soil Biology and Biochemistry 80: 296–305.
2. Mills, R., K. Gavazov, T. Spiegelberger, D. Johnson and A. Buttler 2014. Diminished soil functions occur under simulated climate change in a sup-alpine pasture, but heterotrophic temperature sensitivity indicates microbial resilience. Science of the Total Environment, vol. 473–474(0): 465-472.
3. Gavazov, K., Spiegelberger, T. and Buttler, A. 2014. Transplantation of subalpine wood-pasture turfs along a natural climatic gradient reveals lower resistance of unwooded pastures to climate change compared to wooded ones. Oecologia (174) : 1425-1435.
4. Peringer A., Siehoff S., Chételat J., Spiegelberger T., Buttler A. & Gillet F. 2013. Past and future landscape dynamics in pasture-woodlands of the Swiss Jura Mountains under climate change. Ecology and Society, 18, 3: 11. DOI: 10.5751/ES-05600-180311. [online] URL: http://www.ecologyandsociety.org/vol18/iss3/art11/
5. Gavazov, K. S., A. Peringer, A. Buttler, F. Gillet and T. Spiegelberger. 2013. Dynamics of Forage Production in Pasture-woodlands of the Swiss Jura Mountains under Projected Climate Change Scenarios. Ecology and Society 18 (1): 38. [online] URL: http://www.ecologyandsociety.org/vol18/iss1/art38/

biogeochemisty

display_name: biogeochemisty

climate-change

display_name: climate-change

silvopastoral-systems

display_name: silvopastoral-systems

soil

display_name: soil

transplantation-experiment

display_name: transplantation-experiment

en: Biogeochemical data from a transplantation experiment of monolith soil turfs along an altitudinal gradient to simulate climate change scenarios


rorcc

maintainer: Tobias Wechsler

title_for_slug: rorcc

en: environmental-flow hydropower design-discharge run-of-river-power-plants climate-change

en: RoRCC

media_type: XLS

en:
The dataset “RoRCC” consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
-	metadata on the RoR power plants under consideration
-	annual and seasonal production scenarios differentiated into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)
-	annual and seasonal production loss due to environmental flow requirements
-	annual and seasonal the technical increase potential (via design discharge optimisation)
-	annual and seasonal changes in the hydrological cycle for the three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)

en:
The dataset "RoRCC" consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
1) metadata on the RoR power plants under consideration, 2) annual and seasonal production potential scenarios under into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099), 3) annual and seasonal streamflow scenarios, 4) annual and seasonal production loss due to environmental flow requirements, 5) annual and seasonal the technical increase potential (via design discharge optimisation) and 6) annual and seasonal changes in the hydrological cycle.

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants


maintainer: Yohann Chauvier

en: independent-dataset random-stratified-sampling background-data plant-species target-group environmental-stratification survey-effort point-process-model cluster covariate-correction

media_type: ZIP

en: Non-copyright data, scripts, diversity outputs

en:
Aim: While species distribution models (SDMs) are standard tools to predict species distributions, they can suffer from observation and sampling biases, particularly presence-only SDMs that often rely on species observations from non-standardized sampling efforts. To address this issue, sampling background points with a target-group strategy is commonly used, although more robust strategies and refinements could be implemented. Here, we exploited a dataset of plant species from the European Alps to propose and demonstrate efficient ways to correct for observer and sampling bias in presence-only models.

Innovation: Recent methods correct for observer bias by using covariates related to accessibility in model calibrations (classic bias covariate correction, Classic-BCC). However, depending on how species are sampled, accessibility covariates may not sufficiently capture observer bias. Here, we introduced BCCs more directly related to sampling effort, as well as a novel corrective method based on stratified resampling of the observational dataset before model calibration (environmental bias correction, EBC). We compared, individually and jointly, the effect of EBC and different BCC strategies, when modelling the distributions of 1’900 plant species. We evaluated model performance with spatial block split-sampling and independent test data, and assessed the accuracy of plant diversity predictions across the European Alps.

Main conclusions: Implementing EBC with BCC showed best results for every evaluation method. Particularly, adding the observation density of a target group as bias covariate (Target-BCC) displayed most realistic modelled species distributions, with a clear positive correlation (r≃0.5) found between predicted and expert-based species richness. Although EBC must be carefully implemented in a species-specific manner, such limitations may be addressed via automated diagnostics included in a provided R function. Implementing EBC and bias covariate correction together may allow future studies to address efficiently observer bias in presence-only models, and overcome the standard need of an independent test dataset for model evaluation.

background-data

display_name: background-data

cluster

display_name: cluster

covariate-correction

display_name: covariate-correction

environmental-stratification

display_name: environmental-stratification

independent-dataset

display_name: independent-dataset

plant-species

display_name: plant-species

point-process-model

display_name: point-process-model

random-stratified-sampling

display_name: random-stratified-sampling

survey-effort

display_name: survey-effort

target-group

display_name: target-group

en: Novel methods to correct for observer and sampling bias in presence-only species distribution models


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

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

education

en: Education and science

en: History of wetlands in Switzerland since 1850


maintainer: Leonie Schönbeck

en: photosynthesis drought gas-exchange fluorescence acclimation pinus-sylvestris vpd

en: Instrument details

en:
Instrument details for all LiCor instruments used during collection of dataset.

Metatdata created following guidelines from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Methods fluorescence

en:
Parameters and methodology for Fluorescence measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Variable names and units

en: Variable names, description and units for the Pfynwald Gas exchange data

en: Methods survey

en: Parameters and methods for point measurements / survey measurements

en: Methods light response

en: Methods and parameters for light response curves

en: Methods diurnal measurements

en:
Parameters and methodology for diurnal measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Methods ACi curves

en:
Parameters and methods for CO2 response curves of Photosynthesis.

Metatdata format by
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Pfynwald gas exchange

en:
Full dataset of Pfynwald gas exchange data taken in the period from June 2013 to October 2020.
All metdata can be found in attached documents.
Data uploaded after quality control using guidelines by Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds.
All metadata can be found in the attached documents.

acclimation

display_name: acclimation

drought

display_name: drought

fluorescence

display_name: fluorescence

gas-exchange

display_name: gas-exchange

photosynthesis

display_name: photosynthesis

pinus-sylvestris

display_name: pinus-sylvestris

vpd

display_name: vpd

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: 2013-2020 gas exchange at Pfynwald


en: seilaplan swiss-geodata swiss-geo-downloader qgis-plugin cable-yarding digital-planning open-source geoinformation-system digital-elevation-model

en: Herunterladen des DHM mit SwissGeoDownloader

en: View video on youtube!

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. The plugin ‘Swiss Geo Downloader’, which is available for the open source geoinformation software QGIS, allows freely available Swiss geodata to be downloaded and displayed directly within QGIS. It was developed in 2021 by Patricia Moll in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. In this tutorial we describe how to download the high accuracy elevation model ‘swissALTI3D’ with the help of the ‘Swiss Geo Downloader’ and how to use it for digital planning of a cable line with the plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to the Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

Link to Seilaplan website: https://seilaplan.wsl.ch

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

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Das Plugin Swiss Geo Downloader, welches für das Open Source Geoinformationssystem QGIS zur Verfügung steht, ermöglicht frei verfügbare Schweizer Geodaten direkt innerhalb von QGIS herunterzuladen und anzuzeigen. Es wurde 2021 von Patricia Moll in Zusammenarbeit mit der eidgenössischen Forschungsanstalt Wald, Schnee und Landschaft WSL entwickelt. In diesem Tutorial beschreiben wir, wie man mit Hilfe des Swiss Geo Downloaders das hochgenaue Höhenmodell swissALTI3D herunterladen und für die Seillinienplanung mit dem Plugin Seilaplan verwenden kann.

Link zum Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

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

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geo-downloader

display_name: swiss-geo-downloader

swiss-geodata

display_name: swiss-geodata

education

en: Education and science

en: Seilaplan Tutorial: DTM download with SwissGeoDownloader


maintainer: Amt für Abfall, Wasser, Energie und Luft des Kantons Zürich, Abteilung Luft, Klima und Strahlung - Sektion Monitoring

de: lufttemperaturen luft

label: LoRa-Datenbeschrieb

de: LoRa-Sensor-Messwerte 2022/03

media_type: text/csv

de: LoRa-Sensor-Messwerte 2020/01

de: LoRa-Sensor-Messwerte 2022/05

de: LoRa-Sensor-Messwerte 2021/01

de: LoRa-Sensor-Messwerte 2022/02

de: LoRa-Sensor-Messwerte 2019/12

de: LoRa-Sensor-Messwerte 2022/12

de: LoRa-Sensor-Messwerte 2019/07

de: LoRa-Sensor-Messwerte 2019/05

de: LoRa-Sensor-Messwerte 2022/04

de: LoRa-Sensor-Messwerte 2021/11

de: LoRa-Sensor-Messwerte 2019/08

de: LoRa-Sensor-Messwerte 2021/08

de: LoRa-Sensor-Messwerte 2020/11

de:
Seit Frühjahr 2019 betreibt das AWEL des Kantons Zürich ein Messnetz aus rund 40 Lufttemperatur und -feuchte Sensoren (LoRa). Die Sensor-Standorte befinden sich hauptsächlich im städtischen Raum, verdichtet in der Stadt Zürich, aber auch in weiteren Gemeinden im Kanton Zürich. Ziel des Messnetzes ist es, Messdaten für Stadtklima-Analysen bereitzustellen, damit Aspekte des Lokalklimas und Klimawandels stärker sichtbar werden und in der Raumplanung und Stadtentwicklung berücksichtigt werden können. Mit Hilfe dieser Daten lassen sich u.a. die Auswirkungen von Hitzewellen im städtischen Raum beschreiben. Das Messnetz wird durch das AWEL betrieben, unter Beteiligung der Stadt Zürich; die weiteren Standort-Gemeinden sind über die Messaktivität informiert.
Der hier verfügbare Datensatz wird täglich aktualisiert und umfasst alle, für die Standorte gültigen Messwerte im 10 Minuten Mittel, inklusive entsprechender Standortinformationen. Weitere Angaben zu Datensatz-Struktur und verwendeten Sensoren sind im Datensatz-Beschrieb zu finden.

awel-kanton-zuerich

de: Amt für Abfall, Wasser, Energie und Luft Kanton Zürich

de: Das Amt für Abfall, Wasser, Energie und Luft (AWEL) des Kantons Zürich hat den Auftrag, der Bevölkerung im Kanton Zürich eine gesunde, sichere und attraktive Umwelt zu bieten. Zu den Themen Abfall, Wasser, Energie und Luft stellt das AWEL Fachleuten und Interessierten Informationen zur Verfügung.

de: Lufttemperatur und Luftfeuchte LoRa-Sensor-Messwerte