baugesuche-im-kanton-zurich

de:
In diesen Daten finden Sie sämtliche Bauvorhaben, die im Kanton Zürich beantragt wurden. Die Daten werden im Kanton Zürich erfasst, da für jedes Bauvorhaben ein Baugesuch eingereicht werden muss. Seit 2019 werden diese Gesuche ausschließlich in digitaler Form veröffentlicht.  Die Fach- und Koordinationsstelle OGD (FK OGD) sammelt diese Daten allerdings erst seit dem Herbst 2024, wobei Bauvorhaben mit einigen Ausnahmen bloss ein Jahr in der Datenbank des Amtsblatts öffentlich einsehbar sind. Als Grundlage dafür dienen die Informationen der Gemeinden. Diese erfassen die Baueingaben und übermitteln sie direkt über eine Schnittstelle an die digitale Version des Amtsblatts (siehe "Landing Page"), wo sie gesammelt und der Öffentlichkeit zugänglich gemacht werden. Damit diese Baugesuche in diesem OGD-Datensatz in einer einzelnen Datei bereit gestellt werden können, prüft die FK OGD täglich und automatisiert, ob es neue Baugesuche gegeben hat und fügt allfällige neue Bauvorhaben dem bestehenden Datensatz hinzu. Dabei dienen die Baugesuche nicht nur der Informations- und Dokumentationsfunktion, sondern bilden auch die Grundlage für mögliche Rekurse. Das blosse Baugesuch sagt jedoch nichts darüber aus, was effektiv gebaut wird und es ist mit den vorhandenen Daten nicht möglich, nachzuvollziehen, ob ein Projekt umgesetzt wurde.

Die original Gesuche enthalten genaue Information zu natürlichen und juristischen Personen wie z.B. den Gesuchsstellenden oder der Bauherrschaft. Informationen wie Namen oder Adressen werden in diesen Datensatz jedoch bewusst entfernt. Projektstandorte inkl. BFS- und Kataster-Nummer und Projektbeschriebe werden beibehalten.

de: Baugesuche im Kanton Zürich

de: gemeindeverwaltung wohnungsbau umbau landparzellen infrastruktur bautaetigkeit bauvorhaben bauzonen gemeinden wohnbautaetigkeit

de: baupub-Repository auf GitHub zum Erstellen des OGD-Datensatzes und interaktiver Karten

de: Variablenbeschreibung

en: Variablenbeschreibung

fr: Variablenbeschreibung

it: Variablenbeschreibung

title_for_slug: baugesuche-im-kanton-zurich

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

fr: Gouvernement et secteur public

it: Governo e settore pubblico

regi

de: Regionen und Städte

de: Für eine Beschreibung der einzelnen Variablen siehe "weitere Informationen" auf der Startseite des Datensatzes.

de: Die API des Amtsblattportals bietet maschinellen Zugriff auf amtliche Bekanntmachungen aus der Schweiz. Sie erlaubt die strukturierte Abfrage und Integration von Publikationen (z. B. Ausschreibungen, Baugesuche, rechtliche Mitteilungen) in digitale Anwendungen. Die Daten können zum Beispiel nach Kriterien wie Kanton, Zeitraum oder Publikationstyp gefiltert werden.

de: Dokumentation Amtsblattportal API

de: Seit 2025 ist für jede Publikation die BFS-Nummer verfügbar, welche in Kombination mit der Kataster-Nummer eine eindeutige Identifikationen der involvierten Liegenschaft(en) zulässt. Es gilt jedoch zu erwähnen, dass die Gemeinden keinen gemeinsamen Standard für die Bereitstellung der Kataster-Nummern haben und daher eine Zuordnung nicht immer möglich ist. Dieses Geo-Package verknüpft die ausgewiesenen Parzellen der Baupublikationen mit dem Liegenschaften-Layer des Kanton Zürichs, was eine räumliche Darstellung der Baugesuche ermöglicht. Eine Code-Vorlage zur Erstellung einer interaktiven Karte findet man im verlinkten GitHub-Repository unter "weitere Informationen" auf der Startseite des Datensatzes.

de: Georeferenzierte Baugesuche im Kanton Zürich ab 2025

de: Das Erstellen oder Umbauen jeglicher Art von Bauten setzt in der Regel eine Baubewilligung der zuständigen Gemeinde voraus. Dafür muss ein Baugesuch eingereicht werden, das die geplanten Bauarbeiten detailliert beschreibt. Die Karte zeigt alle Baugesuche der letzten 20 Tage im Kanton Zürich. Diese Zeitspanne entspricht auch der gesetzlichen Einsprachefrist. Jeder eingefärbte Standort auf der Karte repräsentiert ein Grundstück mit einem laufenden Baugesuchsverfahren. Weitere Nutzungshinweise sind via dem «Info»-Button am linken Rand der Karte aufrufbar.

de: Karte der Baugesuche innerhalb der Auflagefrist

bautaetigkeit

display_name: bautaetigkeit

bauvorhaben

display_name: bauvorhaben

bauzonen

display_name: bauzonen

gemeindeverwaltung

display_name: gemeindeverwaltung

infrastruktur

display_name: infrastruktur

landparzellen

display_name: landparzellen

umbau

display_name: umbau

wohnbautaetigkeit

display_name: wohnbautaetigkeit

wohnungsbau

display_name: wohnungsbau


$oid: OBSOLETE

de: Dieser Datensatz enthält die Web Analytics des Datenkatalogs des Kantons Zürich (www.zh.ch/daten). Die Daten zeigen, welche Datensätze (dataset) und Ressourcen (distribution) (siehe Definition in DCAP-AP CH, unten verlinkt) wie oft aufgerufen und besucht wurden. Die Aufrufe und Besuche von externen Webseiten, welche den Datenkatalog eingebunden haben, werden mitgezählt. Aus technischen Gründen werden nicht alle Zugriffe registriert (bei Verwendung von Werbeblockern z.B 'Ad-Blocker'). Wir beziehen die Daten von mehreren Matomo APIs. Datensätze und Ressourcen mit 0 Aufrufen/Besuchenden sind nicht ausgewiesen. Aufrufe über Metadatenkatalog wie opendata.swiss sind nicht ausgewiesen.

statistisches-amt-kanton-zuerich

approval_status: approved

de: Das Amt für Statistik und Daten umfasst das Kompetenzzentrum Daten des Kantons Zürich, organisiert, koordiniert und steuert die politische Teilhabe inkl. der Wahlen und Abstimmungen im Kanton und beobachtet die Entwicklung des Kantons mit statistischen Methoden. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Information und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.

de: Amt für Statistik und Daten Kanton Zürich

political_level: canton

state: active

type: organization

kanton-zuerich

capacity: public

de: DCAT-AP CH – The Swiss Application Profile for Data Portals and Catalogues

type: dataset

key: guid

key: uri

value: ZH-Kt Statistisches Amt - DCAT Harvester

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

it: Economia e finanze

de: Zeigt die Anzahl Klicks und Besuchende pro Datensatz und Tag.  'Datensatz' entspricht 'dataset' nach DCAP-AP CH.

de: Web Analytics auf Ebene Datensatz

format: CSV

media_type: text/csv

de: Zeigt die Anzahl Klicks auf die 'Herunterladen' oder 'Konvertiere zu Excel' Schaltflächen und die Anzahl Besuchenden welche mindestens einen Klick auf die 'Herunterladen' oder 'Konvertiere zu Excel' Schaltfläche pro Ressource und Tag gemacht haben. 'Ressource' entspricht 'distribution' nach DCAP-AP CH. Zusätzlich wird die Anzahl Downloads (wie oft die Ressource aufgerufen wurde) ausgewiesen. In der Regel sollte die Anzahl Downloads immer höher oder gleich als die Anzahl Klicks auf die Schaltflächen im Datenkatalog sein. Da aber im Zeitraum von September 2023 bis heute aus nicht bekannten Gründen, nicht alle Zugriffe detektiert werden, sind die Zahlen zu den Downloads in diesem Zeitraum nicht abschliessend. Die Anzahl Downloads von Ressourcen, welche nicht auf unserem Webserver gespeichert sind, werden nicht gezählt und ist der Grund warum es bei den Anzahl Downloads zu leeren Werten kommen kann.

de: Web Analytics zu den Zugriffen auf Ebene Ressource

format: OCTET

de: Zeigt die Anzahl Klicks und Besuchende der Informationsseite der Ressourcen (Klick auf "Details anzeigen") pro Ressource und Tag. 'Ressource' entspricht 'distribution' nach DCAP-AP CH.

de: Web Analytics 'Details anzeigen' zu Ressourcen

de: Zeigt die Anzahl Klicks und Besuchende pro verwandten Datensatz und Tag. 'Datensatz' entspricht 'dataset' nach DCAP-AP CH. Die Merkmale 'datensatz_id' und 'datensatz_titel' zeigen, von welchem Datensatz aus der Klick auf den verwandten Datensatz erfolgte.

de: Web Analytics auf Ebene verwandter Datensatz

statistik

display_name: statistik


name: Dienststelle Landwirtschaft und Wald (lawa)

de: Neophytenbeobachtungen (invasive gebietsfremde Pflanzen) aus der Datenbank von Info Flora. Ein Punkt repräsentiert eine Beobachtung zu einem bestimmten Zeitpunkt.

de: Neophyten

de: landschaftsschutz naturschutz umweltschutz wald

buwd-lawa

de:
Die Dienststelle Landwirtschaft und Wald fördert die Land- und Forstwirtschaftsbetriebe und schafft bessere Rahmenbedingungen für die primäre Produktion. Sie strebt artenreiche, naturnahe ländliche Räume an und stellt die nachhaltige Nutzung des staatlichen Fischerei- und Jagdregals sicher.

Die Dienststelle umfasst die Abteilungen Landwirtschaft, Wald, Natur, Jagd und Fischerei sowie Zentrale Dienste.

en:
The Department of Agriculture and Forestry supports agricultural and forestry operations and creates better conditions for primary production. It strives to foster biodiverse, near-natural rural areas and ensures the sustainable use of the state’s fishing and hunting rights.

The department comprises the divisions of Agriculture, Forestry, Nature, Hunting, and Fisheries, as well as Central Services.

fr:
L'office de l'agriculture et des forêts soutient les exploitations agricoles et forestières et crée des conditions-cadres plus favorables à la production primaire. Il œuvre en faveur d'espaces ruraux riches en biodiversité et proches de la nature, et veille à l'exploitation durable des droits de pêche et de chasse appartenant à l'État.

Le Service comprend les départements de l'agriculture, des forêts, de la nature, de la chasse et de la pêche, ainsi que les services centraux.

en: Department of Agriculture and Forestry

de: Dienststelle Landwirtschaft und Wald

fr: Office de l'agriculture et des forêts

de: Kanton Luzern, Abteilung Geoinformation

de: geocat.ch Permalink

fr: geocat.ch permalien

it: geocat.ch link permanente

en: geocat.ch permalink

spatial: Kanton Luzern

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

fr: Agriculture, pêche, sylviculture et alimentation

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

de: Produktansicht Geodatenshop

de: Datenshop

value: Kt. LU LAWA - geocat harvester


de: Der Waldrand angrenzend an Bauzonen ist als statische Waldgrenze grundeigentümerverbindlich festgelegt und im Zonenplan eingetragen.

de: Statische Waldgrenzen

de: baulinie nutzungsplanung zonenplan wald eigentumsbeschrankungoreb


de: Zeigt für die landwirtschaftliche Nutzung besonders gut geeignetes, ackerfähiges Kulturland.

de: Fruchtfolgeflächen

de: boden bodennutzung landwirtschaft landwirtschaftliche-nutzung raumplanung fruchtfolgeflache

buwd-rawi

de:
Die Dienststelle Raum und Wirtschaft gestaltet die räumliche und wirtschaftliche Entwicklung im Kanton Luzern. Sie unterstützt Gemeinden, Wirtschaft und Bevölkerung mit Geoinformationen, koordiniert Baubewilligungen und erarbeitet gemeinsam mit Partnern zukunftsfähige Lösungen.

Die Dienststelle umfasst die Abteilungen Baubewilligungen, Geoinformation, Raumentwicklung, Wirtschaftsentwicklung sowie Digitalisierung, Innovation und Services.

en:
The Department of Spatial Planning and Economy shapes spatial and economic development in the Canton of Lucerne. It supports municipalities, businesses, and residents with geoinformation, coordinates building permits, and works with partners to develop sustainable solutions.

The office comprises the departments of Building Permits, Geoinformation, Spatial Development, Economic Development, and Digitalization, Innovation, and Services.

fr:
L'office du territoire et de l'économie pilote le développement territorial et économique du canton de Lucerne. Il apporte son soutien aux communes, aux acteurs économiques et à la population grâce à des informations géospatiales, coordonne les permis de construire et élabore, en collaboration avec ses partenaires, des solutions tournées vers l'avenir.

Le service comprend les divisions suivantes : Permis de construire, Information géospatiale, Développement territorial, Développement économique, ainsi que Numérisation, Innovation et Services.

de: Dienststelle Raum und Wirtschaft

fr: Office du territoire et de l'économie

value: Kt. LU RAWI - geocat harvester


erdwarmenutzung

de: Zeigt an welchen Orten der Einsatz von Erdwärmesonden zulässig ist und wo bereits Erdwärmenutzungsanlagen in Betrieb sind.

de: Erdwärmenutzung

de: energie erdwarme geologie gewasserschutz grundwasser bewilligungen ver--und-entsorgung

buwd-uwe

de:
Zum Leistungsauftrag der Dienststelle Umwelt und Energie gehören die Umweltbeobachtung, Information und Beratung, die Prüfung von umweltrelevanten Vorhaben, der Schutz von Umweltgütern (z.B. Grundwasser), die Kontrolle u.a. von Abfallanlagen und Feuerungen sowie die Förderung von erneuerbaren Energien und Energieeffizienz.

Die Dienststelle umfasst die Abteilungen Gewässer und Boden, Entsorgung und Risiko, Energie, Luft, Lärm & Strahlen sowie die Zentralen Dienste.

en:
The mandate of the Department of Environment and Energy includes environmental monitoring, providing information and advice, reviewing environmentally relevant projects, protecting environmental resources (e.g., groundwater), inspecting waste facilities and combustion plants, among other things, and promoting renewable energy and energy efficiency.

The department comprises the divisions of Water and Soil, Waste Management and Risk, Energy, Air, Noise & Radiation, and Central Services.

fr:
Le mandat de prestations de l'Office de l'environnement et de l'énergie comprend la surveillance de l'environnement, l'information et le conseil, l'examen des projets ayant une incidence sur l'environnement, la protection des ressources environnementales (par exemple les eaux souterraines), le contrôle, entre autres, des installations de traitement des déchets et des installations de combustion, ainsi que la promotion des énergies renouvelables et de l'efficacité énergétique.

L'Office comprend les divisions Eaux et sols, Gestion des déchets et risques, Énergie,  Air, bruit et rayonnements, ainsi que les services centraux.

en: Department of Environment and Energy

de: Dienststelle Umwelt und Energie

title_for_slug: erdwarmenutzung

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

fr: Éducation, culture et sport

it: Istruzione, cultura e sport

ener

de: Energie

en: Energy

fr: Énergie

it: Energia

value: Kt. LU UWE - geocat harvester


erdwarmenutzung-anlagen

de: Übersicht der Standorte von Erdwärmenutzungsanlagen, welche Erdwärmesonden, Energiepfähle, Erdregister und Erdwärmekörbe zur Wärmegewinnung nutzen.

de: Erdwärmenutzung: Anlagen

de: energie erdwarme geologie gewasserschutz grundwasser ver--und-entsorgung

buwd-uwe

fr: Office de l'environnement et de l'énergie

de: Kanton Luzern, Abteilung Geoinformation

de: geocat.ch Permalink

title_for_slug: erdwarmenutzung-anlagen

envi

de: Umwelt

de: Produktansicht Geodatenshop


raumliche-energieplanungen

de: Die Kollektion zeigt regionale und kommunale räumliche Energieplanungen im Kanton Luzern. Dies beinhaltet eine Übersicht über den Planungsstand der Energieplanungen, die Energieträger für die thermische Netze und die individuelle Wärmeversorgung sowie Informationen zur Gasstillegung wie auch zur Gebieten wo der Einsatz von Luft-Wasser-Wärmepumpen oder Erdsonden aufgrund zu erwartender Lärmemissionen oder thermischer Beeinflussung koordiniert werden soll.

de: Räumliche Energieplanungen

de: richtplanung energie erdwarme klima raumplanung umweltschutz gebaude-und-anlagen

title_for_slug: raumliche-energieplanungen

de: Datenshop


name: Dienststelle für Verkehr und Infrastruktur (vif)

de: Der Datensatz umfasst Informationen bisher bekannten Naturgefahrenereignisse, unterteilt in die Prozessgruppen Lawine, Rutschung, Sturz, Wasser und Einsturz/Absenkungen (gemäss Art. 27 WBV, Art. 15 WaV).

de: Naturereigniskataster

de: naturgefahren risiken schadenereignis umweltbeobachtung

buwd-vif

de:
Die Dienststelle Verkehr und Infrastruktur (vif) stellt die Mobilität der Bevölkerung und Wirtschaft sicher. Sie ist verantwortlich für Planung, Bau, Betrieb und Werterhaltung von Kantonsstrassen und sorgt für Verbesserungen der Infrastrukturen für den öffentlichen Verkehr sowie den Fuss- und Veloverkehr. Zudem gehört der Schutz von Menschen, Tieren und Sachwerten vor Hochwassergefahren zum Grundauftrag der Dienststelle.

Die Dienststelle umfasst die Abteilungen Mobilität, Planung Strassen, Realisierung Strassen, zentras - Betrieb Strassen, Naturgefahren sowie Zentrale Dienste und Finanzen.

en: The Department of Traffic and Infrastructure (vif) ensures mobility for residents and businesses. It is responsible for the planning, construction, operation, and maintenance of cantonal roads and works to improve infrastructure for public transportation, as well as for pedestrians and cyclists. In addition, protecting people, animals, and property from flood hazards is part of the agency’s core mission.

fr: L'Office de la circulation et de l'infrastructure (vif) assure la mobilité de la population et des entreprises. Il est chargé de la planification, de la construction, de l'exploitation et de l'entretien des routes cantonales et veille à l'amélioration des infrastructures destinées aux transports publics, ainsi qu'aux piétons et aux cyclistes. La protection des personnes, des animaux et des biens contre les risques d'inondation fait également partie de la mission fondamentale du service.

de: Dienststelle Verkehr und Infrastruktur

regi

de: Regionen und Städte

en: Regions and cities

fr: Régions et villes

it: Regioni e città

value: Kt. LU VIF- geocat harvester


verkehrssicherheit

de: Aktive Baustellen entlang der Kantonsstrassen für die eine Baustellenmeldung erfolgt ist.

de: Verkehrssicherheit

de: sicherheit strasse strassenverkehr

buwd-vif

en: Department of Traffic and Infrastructure

fr: Office de la circulation et de l'infrastructure

title_for_slug: verkehrssicherheit

tran

de: Verkehr

en: Transport

fr: Transports

it: Trasporti


schutzbauten-zivilschutz

name: Dienststelle Militär, Zivilschutz und Justizvollzug, Zivilschutz

de: Aktive Schutzbauten des Zivilschutzes zur Unterbringung der Bevölkerung oder Kulturgütern im Ereignisfall. Dargestellt werden private und öffentliche Gebäude mit aktiven Schutzräumen oder Schutzanlagen. Schutzbauten, die nicht einem Gebäude zugeordnet werden können, sind als Punkt verortet.

de: Schutzbauten Zivilschutz

de: bevolkerung sicherheit zivilschutz bewilligungen gebaude-und-anlagen

lu-mzj

de:
Die Dienststelle Militär, Zivilschutz und Justizvollzug ist eine Leistungserbringerin für die öffentliche Sicherheit und stellt die gesetzlich geforderten Aufgaben zugunsten der Armee, des Zivilschutzes, des Justizvollzuges sicher.

Die Dienststelle umfasst die Abteilungen Militär, Zivilschutz, Bevölkerungsschutz/KFS, Vollzugs- und Bewährungsdienst, die Justizvollzugsanstalt Grosshof sowie die Justizvollzugsanstalt Wauwilermoos.

en:
The Department of Military, Civil Defense, and Execution of Penal Sentences and Justice is a service provider for public safety and carries out the tasks required by law on behalf of the armed forces, civil defense, and the corrections system.

The department comprises the Military, Civil Defense, Civil Protection/KFS, and Corrections and Probation divisions, as well as the Grosshof Correctional Facility and the Wauwilermoos Correctional Facility.

fr:
L'Office des affaires militaires, de la protection civile et de l'exécution des peines est un prestataire de services dans le domaine de la sécurité publique et assure les missions prévues par la loi au profit de l'armée, de la protection civile et de l'exécution des peines.

L'Office comprend les divisions suivantes : affaires militaires, protection civile, protection de la population/KFS, service d'exécution des peines et de probation, ainsi que les établissements pénitentiaires de Grosshof et de Wauwilermoos.

de: Kanton Luzern, Abteilung Geoinformation

de: geocat.ch Permalink

title_for_slug: schutzbauten-zivilschutz

gove

de: Regierung und öffentlicher Sektor

fr: Gouvernement et secteur public

value: Kt. LU MZJ - geocat harvester


name: Direction de l'information du territoire

fr: Depuis décembre 2003, toutes les parcelles avant modification par une mutation juridique, soit par division ou réunion, sont transférées par duplication en couche historique des parcelles de la mensuration. Entre juin 2006 et février 2008 en plus de la règle ci-dessus, une partie des biens-fonds modifiés par numérisation (amélioration de sa précision planimétrique) furent intégrés dans cette classe d'entités. Depuis mars 2008, tout bien-fonds subissant une modification géométrique ou attributaire est intégré dans cette classe d'entités. Voir couche en vigueur : CAD_PARCELLE_MENSU

fr: Historique des parcelles de la mensuration

canton-geneve

fr: Le canton de Genève s'est engagé dans une démarche d’ouverture des données publiques depuis plusieurs années. Sur ce portail, vous trouvez toutes les données provenant de l'administration cantonale genevoise qui répondent aux principes de l'Open Government Data, ainsi que les géodonnées OpenData du Système d’Information du Territoire à Genève (SITG).

de: Der Kanton Genf verfolgt seit einigen Jahren eine Open Data Strategie. Auf diesem Portal finden Sie Daten aus der kantonalen Verwaltung die die Prinzipien des Open Government Data erfüllen, sowie sämtliche "Open-Geodaten" des Genfer Geoinformationssystems (SITG). ***Die Datensätze finden Sie unter der betreffenden Organisation***

en: The canton of Geneva has been committed to making public data open for a few years now. On this portal, you will find all the data from the Geneva cantonal administration that meet the principles of Open Government Data, as well as geodata from the geographic information system of Geneva (SITG) that fall under the OpenData policy.

it: Il cantone di Ginevra si è impegnato in un processo di apertura dei dati pubblici per diversi anni. Su questo portale, è possibile trovare tutti i dati dell'amministrazione del cantone di Ginevra che soddisfano i principi del Open Government Data, inoltre ai geodati OpenData del Sistema Informativo Territoriale di Ginevra (SITG).

de: Kanton Genf

en: Canton of Geneva

fr: Canton de Genève

it: Cantone di Ginevra

spatial: GE

envi

de: Umwelt

format: API

format: WFS

format: WMS

fr: Serveur de fichiers Opendata

fr: CSV

fr: GDB

format: ZIP

fr: GML

format: GML

fr: KML

format: KML

fr: SHP

format: SHP

value: GEOCAT canton GE


windmessungen-surpierre-cheiry

name: Centre de compétences et de coordination OGD / Kompetenz- und Koordinationszentrum für OGD

fr: Ce jeu de données fournit des mesures de vent enregistrées toutes les 10 minutes pour le périmètre « Surpierre-Cheiry » , situé dans le canton de Fribourg. Collectées dans le cadre du mandat du Grand Conseil pour la planification éolienne cantonale, ces données comprennent la vitesse et la direction du vent, la température, l'humidité relative à différentes hauteurs, ainsi que le potentiel de production éolienne (productible éolien). Ces informations sont essentielles pour la planification énergétique et sont mises à disposition en libre accès sur la plateforme Open Government Data du canton de Fribourg dans un souci de transparence et d'accès à l'information pour tous. Le périmètre « Surpierre-Cheiry » se situe dans le district de la Broye à environ 680 mètres d’altitude, dans une enclave du canton de Vaud.L'heure UTC (temps universel coordonné) sert de référence mondiale et ne change pas avec les saisons. Pour obtenir l'heure locale, ajoutez 1 heure en hiver (UTC+1) et 2 heures en été (UTC+2).Pour plus d'informations : [https://www.fr.ch/fribourg-vents/surpierre-cheiry](https://www.fr.ch/fribourg-vents/surpierre-cheiry)

fr: Mesures de vents - Surpierre-Cheiry

fr: vent energie eolienne mesures

ssd

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.

en: The Statistics and Data Service is the cantonal competence center for public statistics. It collects, analyzes, and disseminates statistical data on the situation and development of the canton, supports state services in data management, and coordinates the dissemination of administrative data in open access.

de: Das Amt für Statistik und Daten ist das kantonale Kompetenzzentrum für die öffentliche Statistik. Es erhebt, analysiert und verbreitet statistische Daten über die Lage und die Entwicklung des Kantons, unterstützt die Dienststellen des Staats bei der Verwaltung ihrer Daten und koordiniert die Veröffentlichung der offenen Verwaltungsdaten.

it: Il Servizio Statistiche e Dati è il centro di competenza cantonale per la statistica pubblica. Raccoglie, analizza e diffonde dati statistici sulla situazione e l'evoluzione del cantone, supporta i servizi statali nella gestione dei dati e coordina la diffusione dei dati amministrativi ad accesso aperto.

de: Amt für Statistik und Daten Freiburg

en: Statistics and Data Service Fribourg

fr: Service de la statistique et de la donnée Fribourg

it: Servizio Statistiche e Dati Friburgo

de: ssd

title_for_slug: windmessungen-surpierre-cheiry

value: DCAT Harvester Kt. FR

ener

de: Energie

fr: Énergie

fr: Mesures de vents - Surpierre-Cheiry (csv)

fr: csv

fr: Mesures de vents - Surpierre-Cheiry (json)

fr: json

format: JSON

media_type: application/json

fr: Mesures de vents - Surpierre-Cheiry (jsonl)

fr: jsonl

fr: Mesures de vents - Surpierre-Cheiry (parquet)

fr: parquet

format: PARQUET

fr: Mesures de vents - Surpierre-Cheiry (rdfxml)

fr: rdfxml

format: RDF XML

media_type: application/rdf+xml

fr: Mesures de vents - Surpierre-Cheiry (jsonld)

fr: jsonld

format: JSON-LD

fr: Mesures de vents - Surpierre-Cheiry (turtle)

fr: turtle

format: RDF Turtle

media_type: text/turtle

fr: Mesures de vents - Surpierre-Cheiry (n3)

fr: Mesures de vents - Surpierre-Cheiry (xlsx)

fr: xlsx

format: XLS

energie

display_name: energie

eolienne

display_name: eolienne

mesures

display_name: mesures

vent

display_name: vent


fr: Ce jeu de données présente les prénoms attribués aux nouveau-né·e·s dans le canton de Fribourg, ventilés par genre (garçon, fille), région linguistique (francophone, germanophone) et année, dès 1987. Les effectifs correspondent au nombre d'enfants nés vivants enregistrés au cours de l'année considérée. Seul le premier prénom attribué à l'enfant est pris en compte. Les variantes orthographiques liées aux accents sont regroupées. Les données proviennent de la Statistique du mouvement naturel de la population (BEVNAT) établie par l'Office fédéral de la statistique. Pour plus d'informations: [https://www.bfs.admin.ch/bfs/fr/home/statistiques/population/enquetes/bevnat.assetdetail.35996254.html](https://www.bfs.admin.ch/bfs/fr/home/statistiques/population/enquetes/bevnat.assetdetail.35996254.html)

fr: Prénoms, dès 1987

fr: demographie nouveau-ne-e prenom

ssd

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.

fr: Service de la statistique et de la donnée Fribourg

soci

de: Bevölkerung und Gesellschaft

en: Population and society

fr: Population et société

it: Popolazione e società

fr: Prénoms, dès 1987 (csv)

fr: Prénoms, dès 1987 (json)

fr: Prénoms, dès 1987 (jsonl)

fr: Prénoms, dès 1987 (parquet)

fr: Prénoms, dès 1987 (rdfxml)

fr: Prénoms, dès 1987 (jsonld)

fr: Prénoms, dès 1987 (turtle)

fr: Prénoms, dès 1987 (n3)

fr: Prénoms, dès 1987 (xlsx)

demographie

display_name: demographie

nouveau-ne-e

display_name: nouveau-ne-e

prenom

display_name: prenom


fr:
Ce jeu de données présente le parc annuel des bâtiments à usage d'habitation de 2010 à 2019, par commune, selon la catégorie de bâtiment, le nombre de niveaux, le nombre de logements, l'époque de construction, le générateur de chaleur et la source de chaleur pour le chauffage et l'eau chaude sanitaire.Données selon la dernière version du [catalogue des caractères](https://www.housing-stat.ch/fr/docs/catalog/index.html) du Registre fédéral des bâtiments et des logements (RegBL).
Si la valeur indiquée pour le nombre de logements est nulle, c'est qu'elle ne peut être indiquée (ex. hôtels, homes pour personnes âgées, etc.). Liens utiles : [Page OFS](https://stats.swiss/?pg=0&fc=Th%C3%A8me&fs[0]=Th%C3%A8me%2C1%7CConstruction%20et%20logement%2309%23%7CB%C3%A2timents%2309-02%23&bp=true&snb=6), [Page d'accueil du domaine SSD](https://www.fr.ch/deef/ssd/statistiques-par-themes/batiments).

fr: batiments logements chauffage energie commune

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, de 2010 à 2019 (csv)

fr: csv

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, de 2010 à 2019 (json)

fr: json

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, de 2010 à 2019 (jsonl)

fr: jsonl

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, de 2010 à 2019 (parquet)

fr: parquet

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, de 2010 à 2019 (rdfxml)

fr: rdfxml

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, de 2010 à 2019 (jsonld)

fr: jsonld

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, de 2010 à 2019 (turtle)

fr: turtle

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, de 2010 à 2019 (n3)

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, de 2010 à 2019 (xlsx)

batiments

display_name: batiments

chauffage

display_name: chauffage

commune

display_name: commune

logements

display_name: logements


windmessungen-massif-du-gibloux

fr: Ce jeu de données fournit des mesures de vent enregistrées toutes les 10 minutes pour le périmètre « Massif du Gibloux », situé dans le canton de Fribourg. Collectées dans le cadre du mandat du Grand Conseil pour la planification éolienne cantonale, ces données comprennent la vitesse et la direction du vent, la température, l'humidité relative à différentes hauteurs, ainsi que le potentiel de production éolienne (productible éolien). Ces informations sont essentielles pour la planification énergétique et sont mises à disposition en libre accès sur la plateforme Open Government Data du canton de Fribourg dans un souci de transparence et d'accès à l'information pour tous. Le périmètre « Massif du Gibloux » se situe entre les districts de la Glâne, de la Sarine et de la Gruyère, à environ 950 mètres d’altitude pour la partie sud et 1 200 mètres d’altitude pour sa partie nord.L'heure UTC (temps universel coordonné) sert de référence mondiale et ne change pas avec les saisons. Pour obtenir l'heure locale, ajoutez 1 heure en hiver (UTC+1) et 2 heures en été (UTC+2).Pour plus d'informations : [https://www.fr.ch/fribourg-vents/massif-du-gibloux](https://www.fr.ch/fribourg-vents/massif-du-gibloux)

fr: Mesures de vents - Massif du Gibloux

fr: vent energie eolienne mesures

ssd

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.

fr: Service de la statistique et de la donnée Fribourg

title_for_slug: windmessungen-massif-du-gibloux

ener

fr: Énergie

fr: Mesures de vents - Massif du Gibloux (csv)

fr: Mesures de vents - Massif du Gibloux (json)

fr: Mesures de vents - Massif du Gibloux (jsonl)

fr: Mesures de vents - Massif du Gibloux (parquet)

fr: Mesures de vents - Massif du Gibloux (rdfxml)

fr: Mesures de vents - Massif du Gibloux (jsonld)

fr: Mesures de vents - Massif du Gibloux (turtle)

fr: Mesures de vents - Massif du Gibloux (n3)

fr: Mesures de vents - Massif du Gibloux (xlsx)

fr: xlsx


windmessungen-schwyberg

fr:
Ce jeu de données fournit des mesures de vent enregistrées toutes les 10 minutes pour le périmètre « Schwyberg », situé dans le canton de Fribourg. Collectées dans le cadre du mandat du Grand Conseil pour la planification éolienne cantonale, ces données comprennent la vitesse et la direction du vent, la température, l'humidité relative à différentes hauteurs, ainsi que le potentiel de production éolienne (productible éolien). Ces informations sont essentielles pour la planification énergétique et sont mises à disposition en libre accès sur la plateforme Open Government Data du canton de Fribourg dans un souci de transparence et d'accès à l'information pour tous. Le périmètre « Schwyberg » se situe dans le district de la Singine sur la crête du Schwyberg à environ 1 610 mètres d’altitude.L'heure
UTC (temps universel coordonné) sert de référence mondiale et ne change pas
avec les saisons. Pour obtenir l'heure locale, ajoutez 1 heure en hiver (UTC+1)
et 2 heures en été (UTC+2).Pour plus d'informations : [https://www.fr.ch/fribourg-vents/schwyberg](https://www.fr.ch/fribourg-vents/schwyberg)

fr: Mesures de vents - Schwyberg

title_for_slug: windmessungen-schwyberg

fr: Mesures de vents - Schwyberg (csv)

fr: csv

fr: Mesures de vents - Schwyberg (json)

fr: json

fr: Mesures de vents - Schwyberg (jsonl)

fr: jsonl

fr: Mesures de vents - Schwyberg (parquet)

fr: parquet

fr: Mesures de vents - Schwyberg (rdfxml)

fr: rdfxml

fr: Mesures de vents - Schwyberg (jsonld)

fr: jsonld

fr: Mesures de vents - Schwyberg (turtle)

fr: turtle

fr: Mesures de vents - Schwyberg (n3)

fr: Mesures de vents - Schwyberg (xlsx)


fr: Ce jeu de données présente le parc annuel des bâtiments à usage d'habitation par commune, selon la catégorie de bâtiment, le nombre de niveaux, le nombre de logements, l'époque de construction, le générateur de chaleur et la source de chaleur pour le chauffage et l'eau chaude sanitaire dès 2020.Données selon la dernière version du [catalogue des caractères](https://www.housing-stat.ch/fr/docs/catalog/index.html) du Registre fédéral des bâtiments et des logements (RegBL).Si la valeur indiquée pour le nombre de logements est nulle, c'est qu'elle ne peut être indiquée (ex. hôtels, homes pour personnes âgées, etc.). Liens utiles : [Page OFS](https://stats.swiss/?pg=0&fc=Th%C3%A8me&fs[0]=Th%C3%A8me%2C1%7CConstruction%20et%20logement%2309%23%7CB%C3%A2timents%2309-02%23&bp=true&snb=6), [Page d'accueil du domaine SSD](https://www.fr.ch/deef/ssd/statistiques-par-themes/batiments).

fr: batiments logements chauffage energie commune

ssd

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.

fr: Service de la statistique et de la donnée Fribourg

econ

fr: Économie et finances

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, dès 2020 (csv)

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, dès 2020 (json)

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, dès 2020 (jsonl)

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, dès 2020 (parquet)

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, dès 2020 (rdfxml)

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, dès 2020 (jsonld)

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, dès 2020 (turtle)

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, dès 2020 (n3)

fr: Bâtiments à usage d'habitation selon différentes caractéristiques, dès 2020 (xlsx)

fr: xlsx


mesures-de-vents-collines-de-la-sonnaz

fr: Ce jeu de données fournit des mesures de vent enregistrées toutes les 10 minutes pour le périmètre « Collines de la Sonnaz » , situé dans le canton de Fribourg. Collectées dans le cadre du mandat du Grand Conseil pour la planification éolienne cantonale, ces données comprennent la vitesse et la direction du vent, la température, l'humidité relative à différentes hauteurs, ainsi que le potentiel de production éolienne (productible éolien). Ces informations sont essentielles pour la planification énergétique et sont mises à disposition en libre accès sur la plateforme Open Government Data du canton de Fribourg dans un souci de transparence et d'accès à l'information pour tous. Le périmètre « Collines de la Sonnaz » se situe dans les districts de la Sarine et du Lac à environ 650 mètres d’altitude au nord-ouest de la ville de Fribourg.

fr: vent energie eolienne mesures

title_for_slug: mesures-de-vents-collines-de-la-sonnaz

ener

fr: Énergie

fr: Mesures de vents - Collines de la Sonnaz (csv)

fr: csv

fr: Mesures de vents - Collines de la Sonnaz (json)

fr: json

fr: Mesures de vents - Collines de la Sonnaz (jsonl)

fr: jsonl

fr: Mesures de vents - Collines de la Sonnaz (parquet)

fr: parquet

fr: Mesures de vents - Collines de la Sonnaz (rdfxml)

fr: rdfxml

fr: Mesures de vents - Collines de la Sonnaz (jsonld)

fr: jsonld

fr: Mesures de vents - Collines de la Sonnaz (turtle)

fr: turtle

fr: Mesures de vents - Collines de la Sonnaz (n3)

fr: Mesures de vents - Collines de la Sonnaz (xlsx)


mesures-de-vents-autour-de-lesserta

fr: Ce jeu de données fournit des mesures de vent enregistrées toutes les 10 minutes pour le périmètre de l'Esserta, situé dans le canton de Fribourg. Collectées dans le cadre du mandat du Grand Conseil pour la planification éolienne cantonale, ces données comprennent la vitesse et la direction du vent, la température, l'humidité relative à différentes hauteurs, ainsi que le potentiel de production éolienne (productible éolien). Ces informations sont essentielles pour la planification énergétique et sont mises à disposition en libre accès sur la plateforme Open Government Data du canton de Fribourg dans un souci de transparence et d'accès à l'information pour tous. Le périmètre de l'Esserta se situe à cheval sur les districts de la Glâne, de la Veveyse et de la Gruyère.L'heure UTC (temps universel coordonné) sert de référence mondiale et ne change pas avec les saisons. Pour obtenir l'heure locale, ajoutez 1 heure en hiver (UTC+1) et 2 heures en été (UTC+2).Pour plus d'informations : [Autour de l’Esserta | Fribourg vents](https://www.fr.ch/fribourg-vents/autour-de-lesserta)

fr: Mesures de vents - Autour de l'Esserta

fr: vent energie eolienne mesures

ssd

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.

fr: Service de la statistique et de la donnée Fribourg

title_for_slug: mesures-de-vents-autour-de-lesserta

ener

fr: Énergie

fr: Mesures de vents - Autour de l'Esserta (csv)

fr: Mesures de vents - Autour de l'Esserta (json)

fr: Mesures de vents - Autour de l'Esserta (jsonl)

fr: Mesures de vents - Autour de l'Esserta (parquet)

fr: Mesures de vents - Autour de l'Esserta (rdfxml)

fr: Mesures de vents - Autour de l'Esserta (jsonld)

fr: Mesures de vents - Autour de l'Esserta (turtle)

fr: Mesures de vents - Autour de l'Esserta (n3)

fr: Mesures de vents - Autour de l'Esserta (xlsx)

fr: xlsx


en:
This data set includes 589 snow profile observations including a rutschblock test, observations of signs of instability and an assessment of the local avalanche danger level, mainly recorded in the region of Davos (eastern Swiss Alps) during the winter seasons 2001-2002 to 2018-2019.
These data were analyzed and results published by Schweizer et al. (2021). They characterized the avalanche danger levels based on signs of instability (whumpfs, shooting cracks, recent avalanches), snow stability class and new snow height.
The data are provided in a csv file (589 records); the variables are described in the corresponding read-me file.
These data are the basis of the following publication: Schweizer, J., Mitterer, C., Reuter, B., and Techel, F.: Avalanche danger level characteristics from field observations of snow instability, Cryosphere, 15, 3293-3315, https://doi.org/10.5194/tc-15-3293-2021, 2021.
 Acknowlegements
Many of the data were recorded by SLF observers and staff members, among those Roland Meister, Stephan Harvey, Lukas Dürr, Marcia Phillips, Christine Pielmeier and Thomas Stucki. Their contribution is gratefully acknowledged.

en: avalanche-forecasting avalanche-danger danger-level snow-instability snow avalanche

envidat

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.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

de: EnviDat

value: Envidat Harvester

envi

en: Environment

fr: Environnement

en:
Resource Title: Read-me file
    Size: 133885 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/321f2050-93be-4772-b5d8-562f46658256/resource/b3aeef4d-1b54-467c-88b4-4d2da8076885/download/read-me.pdf
    Description: This read-me file contains the descriptions of the variables.

format: PDF

media_type: application/pdf

en:
Resource Title: Field observations of snow instabilities
    Size: 107300 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/321f2050-93be-4772-b5d8-562f46658256/resource/5927f50c-3a33-4ceb-91bf-d583efd14cfe/download/snow_instability_field_data.csv
    Description: This data set includes 589 snow profile observations including a rutschblock test, observations of signs of instability and an assessment of the local avalanche danger level, mainly recorded in the region of Davos (eastern Swiss Alps) during the winter seasons 2001-2002 to 2018-2019.

avalanche

display_name: avalanche

avalanche-danger

display_name: avalanche-danger

avalanche-forecasting

display_name: avalanche-forecasting

danger-level

display_name: danger-level

snow

display_name: snow

snow-instability

display_name: snow-instability


en:
Atmospheric drought (high vapor pressure deficit, VPD) and soil drought frequently co-occur, yet plants respond to these stressors through partially distinct physiological pathways, potentially altering source (photosynthesis) and sink (growth and respiration) activities. Despite significant advances in understanding drought impacts on photosynthesis and plant hydraulics, the independent and interactive effects of soil vs. atmospheric drought on whole-tree carbon balance, including non-structural carbohydrate (NSC) dynamics, allocation priorities, and growth, remain insufficiently understood.
This project aims to disentangle the effects of soil and atmospheric droughts on tree sink and source dynamics in European forests, by studying leaf-to-whole-tree ecophysiological processes that drive growth, carbon sequestration and tree mortality. Research will primarily be conducted in Pfynwald (Valais, Switzerland), as part of the VPDrought experiment, where mature Scots pines (Pinus sylvestris) are exposed to increased soil drought and reduced VPD.
Our study addresses the research question: how do soil and atmospheric droughts differentially affect tree carbon uptake and allocation to growth? We hypothesize that atmospheric drought primarily limits carbon assimilation via stomatal closure, leading to reduced growth and respiration (sink activity), whereas soil drought suppresses both carbon uptake (source activity) and sink strength (growth and respiration), leading to stronger shifts in carbon allocation and early reductions in sink demand. Soil drought restricts carbon transport to belowground sinks, while atmospheric drought promotes NSC accumulation in source tissues due to stomatal closure and reduced sink demand.
**Methods:**
Four campaigns (~4 days each) will be conducted at VPDrought during the summer of 2026-2028, covering four experimental treatments: 1) soil drought + ambient air, 2) soil drought + reduced VPD, 3) irrigation + ambient air, 4) irrigation + reduced VPD. Each treatment will include 6-9 replicates.
During the campaigns, gas exchange measurements will be performed, including net photosynthesis, stomatal conductance, temperature responses of photosynthesis and respiration, and A/Ci curves, using three LI-COR systems (LI-6800). Twig water potential (pre-dawn and midday) will be measured with a Scholander pressure chamber (PMS, model 1505D). Twig, needles, and root samples will be collected across treatments for non-structural carbohydrate (NSC) analyses. Stem respiration measurements will be taken using a custom-made chamber and analyzed with the LI-COR (LI-8100A). In addition, stem radial growth (measured with dendrometers) and leaf area development (using Lidar measurements) will be utilized as proxies for sink activity and carbon allocation to structural growth.  Measurements will be repeated across all years, with additional assessments in 2027 and 2028, including resin flow and phloem transport efficiency using a 13C pulse labeling approach.

en: Carbon balance under dual droughts: Disentangling the effects of soil and atmospheric moisture on tree sink and source dynamics in European forests.

en: gas-exchange vpd carbon-dynamics pinus-sylvestris soil-drought

format: TXT

carbon-dynamics

display_name: carbon-dynamics

gas-exchange

display_name: gas-exchange

pinus-sylvestris

display_name: pinus-sylvestris

soil-drought

display_name: soil-drought

vpd

display_name: vpd


en:
The dataset includes spatially aggregated canopy temperature measurements (°C) of one to two tree crowns obtained using infrared (IR) point sensors.
The dataset was quality screened using a multi-step outlier detection procedure based on Median Absolute Deviation (MAD) statistics within a defined analysis period (= 1 year).
**Three complementary quality-control checks were applied**:
1\. Global MAD screening – detects observations that strongly deviate from the overall distribution of each individual sensor time series.
2\. Local spike detection – identifies short-term anomalous spikes within each sensor time series using rolling median and rolling MAD statistics.
3\. Cross-sensor consistency screening – compares measurements across all sensors recorded at the same timestamp to identify extreme deviations relative to the network-wide median behaviour.
Each observation received individual QC flags for all three checks, followed by a combined final quality flag. Observations passing all criteria were labelled as `good`, while flagged observations were labelled as `outlier` if considered suspect, or as `bad` if associated with known sensor drifts. Observations labelled as `outlier` may still represent physically plausible values, while observations labelled as `bad` should not be considered for further analysis. All observations were retained in the exported dataset for traceability.

en: Pfynwald VPDrought experiment canopy temperature parameter

en: pinus-sylvestris irrigation ir-sensor transpiration cooling pfynwald vpdrought heat-stress

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_1min_2024.zip
    Size: 51370310 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/966309dc-3bf5-4bbc-9964-6af79bf294fd/download/pfynwald_vpdrought_canopy_temperature_1min_2024.zip
    Description:

media_type: application/zip

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_1min_2025.zip
    Size: 50905903 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/3ed284f7-5ca4-4b25-9441-00722b92e58d/download/pfynwald_vpdrought_canopy_temperature_1min_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_10min_2024.zip
    Size: 5872908 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/212221fb-14a0-4157-97e9-1670e221959d/download/pfynwald_vpdrought_canopy_temperature_10min_2024.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_10min_2025.zip
    Size: 5833672 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/66747b91-d345-4e98-97c7-9d7b3ce92266/download/pfynwald_vpdrought_canopy_temperature_10min_2025.zip
    Description:

cooling

display_name: cooling

heat-stress

display_name: heat-stress

ir-sensor

display_name: ir-sensor

irrigation

display_name: irrigation

pfynwald

display_name: pfynwald

transpiration

display_name: transpiration

vpdrought

display_name: vpdrought


en:
The dataset refers to samples collected across 6 farms in the Bega Valley region of Australia. The farms are located in the grassy woodland ecoregion and are extensively managed with sheep and cattle grazing. Livestock shares the landscape with native mammalian and invertebrate herbivores. On each farm, two nested fenced exclosure systems were established. These included an open area, a fence excluding livestock but allowing access to native mammals and invertebrates and a fence excluding all mammals but allowing access to invertebrates. In each farm, one of these systems was located in a zone dominated by the native Kangaroo grass, and another in a zone co-dominated by the Invasive African lovegrass. The sample and treatment numbering, as well as a summary of the aggregated indicators is provided in the file Indicator_summary.
Leaf swab s(phyllosphere) samples were taken and DNA was extracted and amplified for 16s and ITS markers. The resulting metabarcoding derived tables are presented (Bacteria_swabs and Fungi_swabs respectively), as are the inferred functional profiles for bacteria at the pathway level (PICRUSt2_pathways), as derived by the PICRUSt2 pipeline.
Two 20 by 100 cm strips had their vegetation removed and their living and litter biomass quantified by dry weight (Biomass). Sensors measuring temperature 10 cm above the soil surface were installed in each plot and their output is presented in Climate. Invertebrates were collected with both pitfall traps and sweepnets and the counts for both sampling techniques can be found in Invertebrates. Damage scores across different categories were collected on 5 leaves of the two species in each plot and the average scores can be found in Leaf_damage.

en: Herbivory disrupts invasion_associated phyllosphere and arthropod community shifts in grasslands

en: biological-invasions phyllosphere grassland invertebrates herbivore-exclusion

en:
Resource Title: Indicator_summary.csv
    Size: 19067 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/d68e884c-0153-4d0f-95c6-eb5702972cce/download/indicator_summary.csv
    Description: Sample metadata and aggregate indicators

format: CSV

en:
Resource Title: PICRUSt2.csv
    Size: 469821 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/665f8907-396a-4b1e-b564-fa100a2b5968/download/picrust2.csv
    Description: Predicted pathway profiles of sampled phyllosphere bacterial communities

en:
Resource Title: Fungi_swabs.csv
    Size: 1059062 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/02fb3082-a33e-4af4-8ea1-d4c4953eec4e/download/fungi_swabs.csv
    Description: OTU table of fungal phyllosphere communities

en:
Resource Title: Climate.csv
    Size: 5096079 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/787a3947-a316-4ac5-aeda-ffacfd832bed/download/climate.csv
    Description: Sensor collected soil surface temperatures

en:
Resource Title: Invertebrates.csv
    Size: 18842 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/493ae610-9929-4499-8dfb-fdb7c8feafed/download/invertebrates.csv
    Description: Counts of invertebrates collected with pitfall traps and sweepnets

en:
Resource Title: Biomass.csv
    Size: 3031 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/ac6aecef-5a8d-4539-b231-3403691fc3f9/download/biomass.csv
    Description: Dry biomass weight of collected plant material

en:
Resource Title: Bacteria_swabs.csv
    Size: 1153434 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/f97a1423-4749-45fa-a07e-93697dd72676/download/bacteria_swabs.csv
    Description: OTU table of bacterial phyllosphere communities

en:
Resource Title: Leaf_damage.csv
    Size: 2007 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/5c2f7e5f-cc22-4ac6-aa16-f3ef13d27ea7/download/leaf_damage.csv
    Description: Aggregated leaf damage scores for African lovegrass and Kangaroo grass

biological-invasions

display_name: biological-invasions

grassland

display_name: grassland

herbivore-exclusion

display_name: herbivore-exclusion

invertebrates

display_name: invertebrates

phyllosphere

display_name: phyllosphere


en:
Dataset content
Continuous soil measurements (10-min resolution) from the Pfynwald long-term irrigation experiment, covering five treatments: **control, irrigation, irrigation+VPD, roof, roof+VPD**.
Measurements were taken at multiple plots and at three depths (-0.1, -0.8, -1.2 m below soil surface).
Sensors include TEROS-21 (matric potential), TEROS-12 (volumetric water content), TEROS-21 (soil temperature), and TEROS-12 (electrical conductivity).
 Processing steps
**1. Raw retrieval** from the LWF database (`ada.v_messvar`, project `Pfynwald irrigation`), 10-min cadence.
**2. Range filtering** to remove physically implausible values:
   - SWP: drop values ≥ 0 kPa or ≤ −8000 kPa
   - VWC: drop values ≤ 0 or - 0.8 m³/m³
   - TEM: drop values - 40 °C or - −20 °C
**3. Duplicate aggregation** within the same 10-min timestamp by mean (median for SWP).
**4. Temperature correction (SWP_TC)**: matric potential is temperature-corrected using the TEROS-21 manufacturer equation referenced to T_ref = 20 °C:
   - Convert SWP (kPa) to head h = |SWP|·10.197, then pF = log10(h)
   - ΔpF = (919.890694·ΔT − 6.945352·ΔT²)·exp(−150.754657 / (pF + 9.153084))
   - SWP_TC = −10^(pF + ΔpF) / 10.197
**5. No gap filling applied.** Missing values remain absent from the delivered CSV.
 Methods
- Database query and aggregation: R, `data.table`, `rLWFpg`
- Temperature correction: in-house implementation of TEROS-21 manufacturer formula
- See repository / script reference below
 Limitations
- Values flagged out of range during step 2 are absent (not interpolated)
- Winter periods may include frozen-soil readings — these pass the range filter as physical sensor outputs but should be interpreted with caution by downstream users
- SWP_TC rows carry the messvar_id of the underlying SWP sensor; the corresponding TEM sensor used for correction is paired via site/plot/depth/datetime but not encoded in the messvar_id
- Sensor calibration uses manufacturer defaults; site-specific calibration was not performed
- Roofs were installed in spring 2024. Readings under "roof" / "roof_vpd" treatments before that reflect ambient conditions, not the experimental treatment.
- In 2025, three additional TEROS-21 sensors were added per roofed treatment at 10 cm depth to obtain a balanced sample relative to roof position (under panels, at panel edges, and in inter-panel gaps).
  This expansion means roofed treatments have six positions at 10 cm from 2025 onward, compared to three before.

en: Pfynwald VPDrought experiment soil parameters

en: teros-21 irrigation pfynwald soil-moisture vpdrought teros-12 irrigation-manipulation water-potential electrical-conductivity soil-temperature pinus-sylvestris drought-experiment

envidat

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: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: pfynwald_vpdrought_soil_10Minutes_2025.zip
    Size: 66201780 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/12bc2274-e48f-4ff1-8961-b86699aaa450/resource/edaa3e3a-1045-4d2f-952f-e23689c20bb9/download/pfynwald_vpdrought_soil_10minutes_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_soil_10Minutes_2024.zip
    Size: 59025329 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/12bc2274-e48f-4ff1-8961-b86699aaa450/resource/3606ad5b-f308-4bfc-8aa4-db5b017ee47a/download/pfynwald_vpdrought_soil_10minutes_2024.zip
    Description:

drought-experiment

display_name: drought-experiment

electrical-conductivity

display_name: electrical-conductivity

irrigation-manipulation

display_name: irrigation-manipulation

soil-moisture

display_name: soil-moisture

soil-temperature

display_name: soil-temperature

water-potential

display_name: water-potential


en:
Description
This dataset contains continuous sap-flow measurements and derived whole-tree transpiration estimates for 45 Pinus sylvestris trees at the Pfynwald experimental platform in southwestern Switzerland during 2024–2025. Trees were distributed across five treatment combinations established within the VPDrought experiment: Control, Irrigation, Irrigation + VPD reduction, Roof, and Roof + VPD reduction. Sap flux density was measured every 10 min using heat-ratio sap-flow sensors (IX-SF30, Implexx, Melbourne, Australia) installed at breast height on the north-facing side of each tree.
Raw temperature signals were converted to sap flux density following the heat ratio method (Marshall 1958; Burgess et al. 2001; Forster 2019). Thermal diffusivity and related wood properties were parameterized using increment cores collected near the site and tree-specific allometric relationships. Probe misalignment was corrected by estimating a zero-flow offset from nighttime measurements during well-watered, low-VPD conditions in February 2024 and subtracting this offset from the full time series.
Sap flux density measurements at 0.5 and 1.5 cm sapwood depth were combined to total sap flow for the depth where the sensors were installed. Whole-tree transpiration can be calculated by integrating sap flux density across concentric sapwood depth of 2 cm.
The dataset includes processed sap flux density values together with metadata on treatment, tree identity, sensor depth, and quality-control corrections. Limitations include possible residual uncertainty due to sensor drift, assumptions in the sapwood depth, and the replacement of two trees that died during summer 2024 and lost parts of their crown in 2025.
 Additional Information
Data processing was performed in an R environment following the heat ratio method workflow described by Forster (2019). Raw heat-pulse measurements were converted to sap flux density and subsequently corrected for thermal diffusivity, and probe misalignment. Outliers and implausible values were identified and removed using the R package datacleanr (Hurley et al. 2022). Sensor needle misalignment was corrected by defining a zero-flow offset during periods of low atmospheric demand and assumed zero sap flow (i.e. rainy periods), and subtracting this offset from the time series. The processing script used to derive the dataset is available from the authors upon request.
Relevant literature:
- Burgess S.S.O., Adams M.A., Turner N.C., Beverly C.R., Ong C.K., Khan A.A.H. & Bleby T.M. (2001) An improved heat pulse method to measure low and reverse rates of sap flow in woody plants†. Tree Physiology 21, 589–598.
- Forster M.A. (2019) The Dual Method Approach (DMA) Resolves Measurement Range Limitations of Heat Pulse Velocity Sap Flow Sensors. Forests 10.
- Hurley A.G., Peters R.L., Pappas C., Steger D.N. & Heinrich I. (2022) Addressing the need for interactive, efficient, and reproducible data processing in ecology with the datacleanr R package. PLOS ONE 17, e0268426-.
- Marshall D.C. (1958) Measurement of Sap Flow in Conifers by Heat Transport. 1. Plant Physiology 33, 385–396.

en: Pfynwald VPDrought  experiment sap flow parameter

en: transpiration vpd xylem-flux pinus-sylvestris drought-experiment sap-flow irrigation continuous-monitoring tree-transpiration reduction forest-ecophysiology rhone-valley pfynwald rain-exclusion vpdrought

en:
Resource Title: pfynwald_vpdrought_sapflow_10Minutes_2024.zip
    Size: 53546175 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9e439e5-827a-40a7-956c-1a05699e6adc/resource/6a0cd3b8-8e29-4b85-9296-86196808fd32/download/pfynwald_vpdrought_sapflow_10minutes_2024.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_sapflow_10Minutes_2025.zip
    Size: 53424631 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9e439e5-827a-40a7-956c-1a05699e6adc/resource/455662d6-f0b7-4ea8-8cb6-d31eb714952e/download/pfynwald_vpdrought_sapflow_10minutes_2025.zip
    Description:

continuous-monitoring

display_name: continuous-monitoring

forest-ecophysiology

display_name: forest-ecophysiology

pinus-sylvestris

display_name: pinus-sylvestris

rain-exclusion

display_name: rain-exclusion

reduction

display_name: reduction

rhone-valley

display_name: rhone-valley

sap-flow

display_name: sap-flow

tree-transpiration

display_name: tree-transpiration

vpd

display_name: vpd

xylem-flux

display_name: xylem-flux


en:
Project description:
Forest soils are among the largest terrestrial carbon pools. How soil carbon (C) responds to changing water availability is still poorly understood, particularly in already water-limited systems. This project investigates the composition and persistence of soil organic matter (SOM) and associated microbial communities in a dry inner-Alpine Scots pine forest exposed to long-term changes in precipitation and atmospheric demand. Earlier work showed that 19 years of irrigation redistributed bulk soil C from the organic layer into the mineral soil. Although total soil C stocks remained unchanged, a higher incorporation into mineral soils may increase long-term C storage (Guidi et al., 2022; Minich et al., 2026). We now ask, how persistent this redistributed C is, in which soil C fraction (particulate or mineral-associated) it resides, and which microbial communities are associated with it.
The work is based at Pfynwald, where a long-term irrigation experiment (since 2003) and the recently installed [VPDrought platform](https://vpdrought.wsl.ch/de/) together span three precipitation regimes (≈300, 600, and 1200 mm per year) crossed with manipulation of atmospheric vapour-pressure deficit. This setup allows us to disentangle the effects of soil and atmospheric drought, which typically co-vary in nature but may shape soil carbon dynamics through distinct pathways. SOM is separated by physical fractionation into particulate (POM) and mineral-associated (MAOM) fractions, characterized through elemental and isotopic analyses (C, N, δ¹³C, δ¹⁵N, ¹⁴C) and fraction-specific microbial community profiling. At the bulk soil level, we measure nutrient pools and extracellular enzyme activities, continue year-round soil respiration, and complement them by CH4 fluxes. Together, these data will reveal how soil carbon stocks and microbial processing respond to changing precipitation in a water-limited pine forest.

en: Soil organic matter dynamics under altered precipitation in a dry Scots pine forest

en: som microbial-communities drought pfynwald radiocarbon

drought

display_name: drought

microbial-communities

display_name: microbial-communities

pfynwald

display_name: pfynwald

radiocarbon

display_name: radiocarbon

som

display_name: som


historical-vegetation-height-model-nfi

en:
The main datasets available are 4 nationwide **Digital Surface Models (DSMs)** and corresponding **Vegetation Height Models (VHMs)** with a spatial resolution of 1 m.
The Vegetation Height Models are calculated by subtraction of a Digital Terrain Model (swissAlti3d version 2017, swisstopo) from the generated DSMs. DSMs were derived by image matching of **scanned historical images** (panchromatic 8-bit) acquired with a RC10 frame camera, in the context of the swisswide image acquisition campaigns of swisstopo.
Nationwide products could be generated for the **four epochs**
 1979-1985 / 1985-1991 / 1990-1998 / 1998-2006.
Additional information about successful image matching vs. interpolation of pixels and about the year of image acquisition are available in the corresponding files (**matched_area_xxxx_xxxx_binay.tif** and **meta_acquisition_year_xxxx_xxxx.json**, respectively).
To separate vegetation from non-vegetation areas a mask derived from a combination of information of the Topographic landscape model - TLM (swisstopo) and a NDVI layer was used and is supplied as **"TLM_mask.tif"**
Due to the occurrence of unrealistic vegetation height values caused by the failure of the image matching process (mainly overexposed images and clouds or very steep rocky terrain), pixel values - 60 m were set to NoData and - 0 m to 0.
All datasets are available in the Reference System **LV95 (EPSG: 2056) LN02 (EPSG: 5728)** and share the common **extent definition** (xmin ymin xmax ymax): 2480000 1070000 2840000 1300000

en: Historical Vegetation Height Model NFI

en: historical dsm nfi forest vhm photogrammetry

title_for_slug: historical-vegetation-height-model-nfi

en:
Resource Title: 1990-1998 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1990-1998_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: readme.txt
    Size: 2045 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d16d27e5-b239-4909-b914-1b0b5337dab3/resource/f6cabeaa-bf7c-4141-bea9-af99d3224487/download/readme.txt
    Description: Description of available data

media_type: text/plain

en:
Resource Title: 1979-1985 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1979-1985_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1985-1991 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1985-1991_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1998-2006 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1998-2006_vegetation_height_model_nfi%2F
    Description:

dsm

display_name: dsm

forest

display_name: forest

historical

display_name: historical

nfi

display_name: nfi

photogrammetry

display_name: photogrammetry

vhm

display_name: vhm


vegetation-height-model-lidar-nfi

en:
Countrywide **vegetation height models (VHM)** were generated for Switzerland based on
LiDAR data acquired in the framework of the **swissSURFACE3D** campaign (swisstopo).
To derive vegetation height, the classified point cloud got normalized by calculating height above ground for all points not belonging to the class ground (2). Vegetation point (class 3,4,5) got then rasterized to a grid size of 0.5 m using an interpolation distance of one grid cell. Raster cells not belonging to a vegetation class got set to 0 m above ground.
These VHM's are produced in the framework of the Swiss National forest Inventory (NFI).
Each year about 1/6 of switzerland surface is updated using swissSURFACE3D data in leaf-off state.

en: Vegetation Height Model LiDAR NFI

en: vegetation three-dimensional forest vegetation-classification vegetation-height point-cloud nfi

envidat

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: EnviDat: the Environmental Data Portal

title_for_slug: vegetation-height-model-lidar-nfi

envi

en: Environment

en:
Resource Title: 2024 Vegetation Height Model LiDAR NFI
    Size: 149786984448 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2024%2F
    Description: Vegetation Height Model of Switzerland for the year 2024 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

en:
Resource Title: 2025 Vegetation Height Model LiDAR NFI (current)
    Size: 160202280141 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2025%2F
    Description: Vegetation Height Model of Switzerland for the year 2025 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

point-cloud

display_name: point-cloud

three-dimensional

display_name: three-dimensional

vegetation

display_name: vegetation

vegetation-classification

display_name: vegetation-classification

vegetation-height

display_name: vegetation-height


en:
The data show locations of the most recent outdoor activity (referred to as restorative location, RL) of Swiss residents, and descriptive characteristics of these places. The data was collected via an online participatory mapping survey targeting residents of urban, peri-urban, and rural areas across Switzerland. Respondents were selected using a stratified random sampling method, considering the greenness and noise exposure of their home locations, and demographic factors such as age, gender, and language region.
The survey was conducted using Maptionnaire software (https://maptionnaire.com). Participants were asked to map the location of their most recent outdoor activity (referred to as restorative location, RL) and provide additional information on their experience in these places. The responses were integrated with the quantitative spatial information (biophysical landscape characteristics, referred to as metrics) on the visited locations, obtained from spatial and remote sensing data.

en: Restorative locations from participatory mapping by Swiss residents

en: soundscape restorative-environments gis-analysis traffic-noise sensory-perception quiet-areas

gis-analysis

display_name: gis-analysis

quiet-areas

display_name: quiet-areas

restorative-environments

display_name: restorative-environments

sensory-perception

display_name: sensory-perception

soundscape

display_name: soundscape

traffic-noise

display_name: traffic-noise


en:
This study examines the siting scenarios for renewable energy infrastructure (REI) in Switzerland, incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed.
MARXAN was run for 2 versions: a) without ground-mounted open space PV infrastructure (excl. OS) and b) with ground-mounted open space PV infrastructure (incl. OS). In each version optimization was done using ecological costs (ECUess) or social costs (ECUsoc) in a regular grid of 4x4km (planning unit).
File:
PU_data.shp: compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.
Headers are described below:
X01 = Planning_units (PUs)
X02 = incl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)
geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).
For MARXAN optimizations (for meaning of standard files in MARXAN see https://scholar.google.ch/scholar_url?url=https://courses.washington.edu/cfr590/software/Marxan1810/marxan_manual_1_8_2.pdf&hl=de&sa=X&ei=NAWHZI6JJ8PFmAGMo47oDQ&scisig=AGlGAw-DBrsV4kUzkR6GkN1jtG66&oi=scholarr), pu_data.shp was used to generate MARXAN files input.dat, pu.dat, puvfeat.dat, spec.dat.
Coordinate Reference System: CH1903 / LV03. EPSG: 21781.

en: Optimizing renewable energy siting in the Swiss landscape

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

ecosystem-services

display_name: ecosystem-services

energy

display_name: energy

landscape

display_name: landscape

marxan

display_name: marxan

optimization

display_name: optimization

photovoltaic

display_name: photovoltaic

social-acceptance

display_name: social-acceptance

spatial-planning

display_name: spatial-planning

wind-power

display_name: wind-power


alan-spongy-moth-laboratory-experiment

en:
Data and Code for ALAN Spongy Moth lab experiment
In this repository you will find all the raw datasets used for the data analysis performed in our paper about the impacts of artificial light at night (ALAN) on the development of Spongy Moth caterpillars. The files are attached as a csv file.
Also attached is all the R-code later used for the statistical analysis and for generating the graphics displayed in the paper. This files are attached as an R.file.

en: ALAN Spongy Moth Laboratory Experiment

en: lab-experiment spongy-moth alan light-pollution insect-development

title_for_slug: alan-spongy-moth-laboratory-experiment

en:
Resource Title: SM_R_NvK.csv
    Size: 56547 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/c93124fd-448c-403b-bc42-70f4b6722636/download/sm_r_nvk.csv
    Description: Raw data used for the Pupation and Cox Hazard/Kaplan Meier Analysis.

en:
Resource Title: SM_R_long_NvK.csv
    Size: 567035 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/401242a6-4430-4725-8c41-263a4f769041/download/sm_r_long_nvk.csv
    Description: Raw data modified and used for the Bodymass Analysis

en:
Resource Title: CoxHazard_KaplanMeier_Mort_Pup.R
    Size: 3933 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/0a205353-8812-4f39-af3f-8d67d2d1495c/download/coxhazard_kaplanmeier_mort_pup.r
    Description: R code for the Cox hazard analysis and producing the Kaplan Meier survival curves for both Mortality and Pupation.

format: OCTET

en:
Resource Title: BodyMass_analysis.R
    Size: 4254 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/0ff15832-2eb3-4420-9afd-869e36ce92ef/download/bodymass_analysis.r
    Description: R code for the bodymass analysis and producing the graphics.

en:
Resource Title: Pupation_analysis.R
    Size: 7606 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/f5ad6fb7-b540-4742-8b77-e5fa86855b1d/download/pupation_analysis.r
    Description: R code for the pupation analysis and producing the graphics.

alan

display_name: alan

insect-development

display_name: insect-development

lab-experiment

display_name: lab-experiment

light-pollution

display_name: light-pollution

spongy-moth

display_name: spongy-moth


forest-canopy-layer

en: This dataset provides a LiDAR-based classification of the forest canopy layer for selected Swiss cantons. Combining an area-based and tree-centred approach, forest areas are categorised into four canopy layering classes that differentiate between single-layered and multi-layered canopies.

en: Forest Canopy Layer

en: forest-structure forest-management mountain-forest forest-canopy nfi lidar

envidat

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: EnviDat: the Environmental Data Portal

title_for_slug: forest-canopy-layer

envi

en: Environment

en:
Resource Title: IFA_Data.csv
    Size: 3837 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/a15b3bdb-c45e-4a8a-b526-8d43b265862c/download/ifa_data.csv
    Description: Validation data from the Independent Forester Assessment (IFA). x- /y-coordinate (CH1903+ LV03) and layer (1: single-layered; 2: multi-layered; -999: NA).

en:
Resource Title: ForestCanopyLayer.qml
    Size: 8139 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/378dbed2-33a3-4398-8a41-5c341d27557d/download/forestcanopylayer.qml
    Description: QGIS QML file with stored layer style definitions for the ForestCanopyLayer.tif.

en:
Resource Title: ForestCanopyLayer.tif
    Size: 558505541 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/90bcde13-c71d-4618-a198-362ebccd0516/download/forestcanopylayer.tif
    Description: Forest Canopy Layer (class 1: single-layered; class 2: probably single-layered; class 3: probably multi-layered; class 4: multi-layered).

format: TIFF

media_type: image/tiff

forest-canopy

display_name: forest-canopy

forest-management

display_name: forest-management

forest-structure

display_name: forest-structure

lidar

display_name: lidar

mountain-forest

display_name: mountain-forest

nfi

display_name: nfi


en:
This dataset contains the input data generated for the pseudo-global warming (PGW) experiments used in the study of the March 2022 Antarctic heatwave with the CRYOWRF model. It includes:
- PGW delta fields derived from CMIP6 simulations, used to perturb ERA5 reanalysis data for past and  future storyline experiments.
- Model configuration files required to reproduce the CRYOWRF simulations.
These resources allow researchers to reproduce the experimental setup and generate model outputs consistent with the results presented in the study.

en: Storylines of the March 2022 heatwave event at Concordia - East Antarctica

en: era5 extreme-events event-attribution atmospheric-rivers climate-change antarctica cmip6 heatwave

en:
Resource Title: PGW_deltas.tar
    Size: 3701853962 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/79b7c457-e689-49bd-8330-29b0508d2b2c/resource/9936c23c-dc86-4eaa-8a6f-5a49cffb338c/download/pgw_deltas.tar
    Description: PGW delta fields derived from CMIP6 simulations, used to perturb ERA5 reanalysis data for future storyline experiments.

en:
Resource Title: CRYOWRF_ANT_20220315_ConfigFiles.tar
    Size: 912259096 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/79b7c457-e689-49bd-8330-29b0508d2b2c/resource/7f77d116-cd3b-4eec-a6d6-061b0d7b43f6/download/cryowrf_ant_20220315_configfiles.tar
    Description: Model configuration files required to reproduce the CRYOWRF simulations over Antarctica.

antarctica

display_name: antarctica

atmospheric-rivers

display_name: atmospheric-rivers

climate-change

display_name: climate-change

event-attribution

display_name: event-attribution

extreme-events

display_name: extreme-events

heatwave

display_name: heatwave


en:
This dataset contains gridded snow depth projections for Switzerland at 1km X 1km resolution. This study was supported by Speed2Zero. The dataset contains the following structure:
- data/data_reference/hs_reference_1991_2020.nc
- data/data_projection_flat/hs_projection_flat.nc
- data/data_projection_aspect/hs_projection_aspect.nc
The data is based on climatological SPASS dataset (Marty et al., 2015) using the reference period 1991-2020. For this reference data, median snow depth evolution, as well as 5th and 95th percentile were computed for each grid point and can be found in this dataset (data/data_reference/*). Future snow depth evolutions for the flat field (data/data_projection_flat/*) were projected for the temperature scenarios +1°C, +2°C, +3°C and +4°C (deviation from 1991-2020 annual mean temperature in Switzerland) following the literature-based approach of Richter and Marty, 2026. Furthermore, this dataset contains gridded projections for north- and south-facing ascpects with a slope anle of 15° (data/data_projection_aspect/*). Detailed can be found in the related publication Richter et al., in preparation.
The files in this data set have a similar structure. Each file is a NetCDF-file containing snow depths (median, 5th, 95th percentile) for each day of the year, coordinate, temperature scenario (data_projection_flat and data_projection_aspect) and aspect (data_projection_aspect).
References:
Marty, C., Michel, A., Jonas, T., Steijn, C., Muelchi, R., and Kotlarski, S.: SPASS – new gridded climatological snow datasets for Switzerland: potential and limitations, The Cryosphere, 19, 4391–4407, https://doi.org/10.5194/tc-19-4391-2025, 2025.
Richter, B. and Marty, C.: Technical note: Literature based approach to estimate future snow, Hydrol. Earth Syst. Sci., 30, 659–670, https://doi.org/10.5194/hess-30-659-2026, 2026.
Richter et al., Gridded snow depth projections, in prepration.

en: Gridded projections of snow depth for Switzerland

en: snow-depth climate-projections swiss-alps gridded-data scenario future switzerland climate-change snow

climate-projections

display_name: climate-projections

future

display_name: future

gridded-data

display_name: gridded-data

scenario

display_name: scenario

snow

display_name: snow

snow-depth

display_name: snow-depth

swiss-alps

display_name: swiss-alps

switzerland

display_name: switzerland


individual-detected-trees

en: This dataset provides individual detected trees for selected Swiss Cantons (Appenzell Outer-Rhodes - AR, Grisons - GR, Nidwald - NW, Obwald - OW and St. Gall - SG), including the derived diameter at breast height and the derived NFI development stage. Data show the Individual detected trees (ITD) with the x- and y-positions of each detected tree based on a spike-free vegetation height model based on nationwide LiDAR data. The shapefile contains the following attributes: tree height [m] (Height), estimated diameter at breast height [cm] (BHD), and the NFI development stage (Ent; 1: young growth/thicket (- 12 cm); 2: pole timber (12-30 cm); 3: young timber (31-40 cm); 4: medium timber (41-50 cm); 5: old timber (- 50 cm).

en: Individual Detected Trees

en: itd forest-structure forest-management mountain-forest nfi development-stage

title_for_slug: individual-detected-trees

development-stage

display_name: development-stage

forest-management

display_name: forest-management

forest-structure

display_name: forest-structure

itd

display_name: itd


en:
This dataset contains all necessary data to reproduce the validation simulations performed in the linked manuscript.
The validation data includes:
- 2 cm DEM of the study site Weissfluhjoch. For the 3 cm DEM of the study site Chant Sura, see [this dataset](https://www.doi.org/10.16904/envidat.174).
- roughness index rasters for both study sites
- rock point clouds of EOTA and Real Equant shapes
- release points used in the validation simulations of both study sites
- a sample XML input file for the rockfall simulator

en: Validation Data for Rockfall Simulations with Geometric Roughness Model

en: surface-roughness numerical-simulation validation rockfall natural-hazards

envidat

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:
Resource Title: Release Points
    Size: 4649 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/636d34b5-5031-4bb6-aa28-b3d1cb11b80e/download/release.zip
    Description: Release points used in the validation simulations of both study sites. Use the *.txt files as input for the simulator.

en:
Resource Title: Roughness Index Rasters
    Size: 36884 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/2c863503-c73d-4b97-a660-d2998b717093/download/roughness.zip
    Description: Roughness index rasters used for the validation simulations. They have a resolution of 3 m.

en:
Resource Title: Sample Simulation
    Size: 126372 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/230c5218-e7a2-4e4f-8633-0c00695cff71/download/sample_sim.zip
    Description: This dataset contains a small sample simulation to showcase the recommended folder/file structure to run rockfall simulations. The input parameters for the simulation can be changed in the XML file, which is then also used as input for the rockfall simulator.

en:
Resource Title: Rock Pointclouds
    Size: 3779 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/c99baa33-50ba-480a-8e4b-82450130900b/download/rocks.zip
    Description: Rock point clouds of EOTA and Real Equant shapes

en:
Resource Title: DEM Weissfluhjoch
    Size: 1005521469 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/9598c524-85b4-4dad-981c-59a126314973/download/dem_weissfluhjoch_2cm.tif
    Description: Digital Elevation Model (DEM) of validation test site Weissfluhjoch with a grid resolution of 2 cm. The DEM for test site Chant Sura can be found in the linked dataset.

natural-hazards

display_name: natural-hazards

numerical-simulation

display_name: numerical-simulation

rockfall

display_name: rockfall

surface-roughness

display_name: surface-roughness

validation

display_name: validation


iwet-insect-weight-estimation-tool

en:
Because of some corrections, a new version of the whole Dataset will be published soon.
We present a novel tool called IWET (Insect Weight Estimation Tool) for estimating morphometrics of arthropod samples using image analysis. IWET is a Java application built around ImageJ libraries and is designed to estimate length, width, area and body mass of individual arthropods from images of specimens sorted into pre-defined taxonomic groups. Using allometric relationships from Sohlströhm et al. (2018), we developed specific regression models to calculate both the individual body mass and the total biomass of arthropod taxonomic groups. IWET provides several advantages: it is non-destructive, cost-effective, and capable of processing large numbers of samples, making it particularly well-suited for biodiversity monitoring projects investigating changes in abundance and biomass, as well as for automating measurements such as specimen length, width and area.

en: IWET – Insect Weight Estimation Tool

en: arthropods biomass image-analysis body-size temperate allometric automatic-detection

envidat

en: EnviDat: the Environmental Data Portal

title_for_slug: iwet-insect-weight-estimation-tool

envi

en: Environment

en:
Resource Title: IWET_EnviDat.zip
    Size: 10255073 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/3d7e7b44-af7f-4824-84b8-fc2abd1f04b3/resource/7f5681bf-cf49-47b0-a8cc-a1e8dde61354/download/iwet_envidat.zip
    Description: IWET-Software with prorpriety and model files (inkl. materials)

en:
Resource Title: R-Script_and_suppl.zip
    Size: 2243953 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/3d7e7b44-af7f-4824-84b8-fc2abd1f04b3/resource/6ca41ee8-bda9-4e65-b859-1dd9c0184c50/download/r-script_and_suppl.zip
    Description: R Script for Regression models

allometric

display_name: allometric

arthropods

display_name: arthropods

automatic-detection

display_name: automatic-detection

biomass

display_name: biomass

body-size

display_name: body-size

image-analysis

display_name: image-analysis

temperate

display_name: temperate


sliding-deadwood-geometry-generator

en: This dataset contains a python code to create deadwood log geometries as well as sample data used for simulations of sliding deadwood with RAMMS::Rockfall.

en: Sliding Deadwood Geometry Generator

en: deadwood natural-hazards forest-management mass-movements protection-forest

title_for_slug: sliding-deadwood-geometry-generator

en:
Resource Title: Sample Data
    Size: 108780 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/a6325cb3-bdb3-4b7c-90f6-1ca41c159918/resource/5ba5fd5d-1b1e-485f-ab24-422df5a509ac/download/sample_data.zip
    Description: Contains all necessary data to do a sample simulation of sliding deadwood:
- Deadwood log geometries (*.pts)
- Release points of the logs (*.shp)
- Treefiles (*.txt), containing the locations, heights, BHD and energy absorption capacities of the standing trees

The data is from the two case studies Gruobenwald and Rhäzüns presented in the linked publication. The DEM for these case studies can be downloaded from swisstopo (swissALTI3D dataset)

en:
Resource Title: Sliding deadwood geometry generator
    Size: 6062 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/a6325cb3-bdb3-4b7c-90f6-1ca41c159918/resource/6fc08e26-7bbe-45c9-8ea1-ab85c36c1793/download/sliding_deadwood_geometry-main.zip
    Description: Python code to create deadwood logs as input for RAMMS::Rockfall.

This version was used for the linked publication. The most recent version and the full documentation can be found in the [GitHub Repository](https://github.com/joelborner/sliding_deadwood_geometry)

deadwood

display_name: deadwood

mass-movements

display_name: mass-movements

protection-forest

display_name: protection-forest


en:
The dataset contains the time series of: overland flow (OF) and topsoil interflow (TIF) measured at two large runoff plots (8 m large by 10 m long), streamflow from two sub-catchments of the Studibach catchment, and streamflow from the outlet of the Studibach and Erlenbach catchments. The time series cover 12 rainfall events in the summer 2022.
OF, TIF and the streamflow of the sub-catchments and the Studibach catchment outlet were measured at a 5-min resolution. The streamflow at the Erlenbach catchment outlet was measured at 10-min resolution.
The precipitation was measured with a tipping bucket at the Erlenhöhe meteorological station and has a 10-min resolution.

en: Time serie of overland flow, topsoil interflow and stream flow in the Studibach Catchment and streamflow in the Erlenbach catchment - summer 2022

en: alptal erlenbach upscaling runoff-plot streamflow studibach topsoil-interflow overland-flow

envidat

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.

alptal

display_name: alptal

erlenbach

display_name: erlenbach

overland-flow

display_name: overland-flow

runoff-plot

display_name: runoff-plot

streamflow

display_name: streamflow

studibach

display_name: studibach

topsoil-interflow

display_name: topsoil-interflow

upscaling

display_name: upscaling