it:
Dal 1° luglio 2012, in Svizzera, come nell'UE, sono in vigore prescrizioni in materia di emissioni di CO2 per le autovetture nuove. Esse obbligano gli importatori svizzeri di automobili a ridurre le emissioni delle autovetture immatricolate per la prima volta in Svizzera.

Il 1° gennaio 2020 il valore obiettivo di CO2 è stato inasprito, passando da 130 g CO2/km a 95 g CO2/km. Questo valore obiettivo doveva essere raggiunto entro la fine del 2022.

Il 1° gennaio 2021 è cambiato il metodo di misurazione delle emissioni di CO2 e di conseguenza il valore obiettivo di CO2 è stato adeguato da 95 g CO2/km a 118 g CO2/km. A causa di questo cambiamento, alcuni attributi subiscono una discontinuità nella serie temporale (discontinuità tra gli anni di riferimento 2020 e 2021). La comparabilità dei seguenti attributi non è quindi garantita sull'asse temporale, o lo è solo in misura limitata (co2, co2_massgebend, ziel, ziel_abw, sanktion_final, gsc_beansprucht, gsc_reserve).

Il 1° gennaio 2025 il valore obiettivo è st

fr:
Depuis le 1er juillet 2012, des prescriptions en matière d'émissions de CO2 pour les nouvelles voitures de tourisme sont en vigueur en Suisse, comme dans l'UE. Elles obligent les importateurs suisses de voitures à réduire les émissions des voitures immatriculées pour la première fois en Suisse.

Le 1er janvier 2020, la valeur cible de CO2 a été renforcée, passant de 130 g CO2/km à 95 g CO2/km. Cette valeur cible devait être atteinte jusqu'à fin 2022.

Le 1er janvier 2021, la méthode de mesure des émissions de CO2 a changée et en conséquence, la valeur cible de CO2 a été adaptée de 95 g CO2/km à 118 g CO2/km. En raison de ce changement, certains attributs subissent une rupture dans la série chronologique (rupture entre les années de référence 2020 et 2021). La comparabilité des attributs suivants n'est donc pas garantie sur l'axe temporel, ou seulement de manière limitée (co2, co2_massgebend, ziel, ziel_abw, sanktion_final, gsc_beansprucht, gsc_reserve).

Le 1er janvier 2025, la valeur cible a été renforcée

de:
Seit dem 1. Juli 2012 gelten in der Schweiz wie in der EU CO2-Emissionsvorschriften für neue Personenwagen. Diese verpflichten die Schweizer Automobilimporteure, die Emissionen von in der Schweiz erstmals zugelassenen Fahrzeugen zu reduzieren.

Am 1. Januar 2020 wurde der CO2-Zielwert von 130 g CO2/km auf 95 g CO2/km verschärft. Dieser Zielwert sollte bis Ende 2022 erreicht werden.

Am 1. Januar 2021 wurde die Methode zur Messung der CO2-Emissionen geändert und der CO2-Zielwert entsprechend von 95 g CO2/km auf 118 g CO2/km angepasst. Aufgrund dieser Änderung kommt es bei einigen Attributen zu einem Bruch in der Zeitreihe (Bruch zwischen den Referenzjahren 2020 und 2021). Die Vergleichbarkeit der folgenden Attribute ist daher auf der Zeitachse nicht oder nur eingeschränkt gewährleistet (co2, co2_massgebend, ziel, ziel_abw, sanktion_final, gsc_beansprucht, gsc_reserve).

Am 1. Januar 2025 wurde der Zielwert von 118 g CO2/km auf 93,6 g CO2/km verschärft. Überschreitungen des Zielwerts werden mit einer Sanktio

it: automobile grandi-importatori sanzioni

bundesamt-fur-energie-bfe

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

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

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

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

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

fr: Office fédéral de l'énergie OFEN

it: Ufficio federale dell'energia UFE

political_level: confederation

de: Bundesamt für Energie (BFE)

fr: Office fédéral de l'énergie (OFEN)

en: Swiss Federal Office of Energy (SFOE)

it: Ufficio federale dell'energia (UFE)

spatial: Schweiz

fr: Résultats de la mise en oeuvre des prescriptions sur les émissions de CO2 des voitures de tourisme

it: Risultati dell'attuazione delle prescrizioni sulle emissioni di CO2 per le automobili

de: Vollzugsresultate der CO2-Emissionsvorschriften für Personenwagen

value: DCAT I14Y BFE

de: CSVl-Datei mit den Daten

fr: Fichier CSV des données

it: File CSV dei dati

de: Vollzugsresultate der CO2-Emissionsvorschriften PW

fr: Résultats de la mise en oeuvre des prescriptions sur les émissions de CO2 des VT

automobile

display_name: automobile

grand-importateur

display_name: grand-importateur

grandi-importatori

display_name: grandi-importatori

grossimporteur

display_name: grossimporteur

personenwagen

display_name: personenwagen

sanctions

display_name: sanctions

sanktionsdaten

display_name: sanktionsdaten

sanzioni

display_name: sanzioni

voitures-de-tourisme

display_name: voitures-de-tourisme


$oid: OBSOLETE

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

fr: Ce jeu de données présente les estimations annuelles du produit intérieur brut (PIB) et du PIB par habitant pour le canton de Fribourg et  l'ensemble de la Suisse, depuis 1995.Les données sont disponibles en termes nominaux (à prix courants) et en termes réels (aux prix de l'année précédente, c'est-à-dire corrigées de l'influence des prix; année de référence 2020), à la fois sous forme de valeurs brutes (na, non-adjusted) ou corrigées des effets des grands événements sportifs (nasa, sport event adjusted).Les données pour la Suisse proviennent du Secrétariat d'Etat à l'économie (SECO). Les données pour le canton de Fribourg sont estimées par l'Institut d'économie appliqué (CREA) de l'Université de Lausanne sur mandat du Service de la statistique et de la donnée (SSD) du canton de Fribourg. Pour plus d'informations sur la méthodologie du CREA : [https://www.unil.ch/crea/fr/home/menuinst/indicateurs/cantonal-gdp-growth.html](https://www.unil.ch/crea/fr/home/menuinst/indicateurs/cantonal-gdp-growth.html)Dans le cadre d'une révision fondamentale des comptes nationaux, l'ensemble des séries chronologiques ont été actualisées rétroactivement en septembre 2025 (SECO) et en novembre 2025 (CREA). Pour plus d'informations : [https://www.seco.admin.ch/seco/fr/home/wirtschaftslage---wirtschaftspolitik/Wirtschaftslage/bip-quartalsschaetzungen-.html](https://www.seco.admin.ch/seco/fr/home/wirtschaftslage---wirtschaftspolitik/Wirtschaftslage/bip-quartalsschaetzungen-.html)Les chiffres du produit intérieur brut par habitant ont été calculés par le SSD sur la base des estimations du PIB (valeurs brutes, na) du SECO et du CREA, divisées par les valeurs annuelles moyennes de la population résidante permanente, calculées sur la base de la statistique de l’état annuel de la population (ESPOP pour la période 1995-2009 ; STATPOP depuis 2010, y compris toutes les personnes bénéficiant d'un statut de protection S enregistrées en Suisse à la date de référence, indépendamment de la durée de leur séjour antérieur). Il convient toutefois de noter que, pour la période 1995-2009 (ESPOP), cette définition diffère légèrement de celle utilisée par l’Office fédéral de la statistique (OFS) pour le calcul du PIB par habitant : [https://www.bfs.admin.ch/bfs/fr/home/statistiques/economie-nationale/comptes-nationaux/produit-interieur-brut.html](https://www.bfs.admin.ch/bfs/fr/home/statistiques/economie-nationale/comptes-nationaux/produit-interieur-brut.html)

fr: pib taux-de-croissance crea seco conjoncture-fribourgeoise indicateurs-conjoncturels

ssd

approval_status: approved

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

political_level: canton

state: active

type: organization

capacity: public

de: ssd

type: dataset

key: guid

key: uri

value: DCAT Harvester Kt. FR

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

it: Economia e finanze

fr: Produit intérieur brut – valeurs annuelles, dès 1995 (csv)

fr: csv

format: CSV

media_type: text/csv

fr: Produit intérieur brut – valeurs annuelles, dès 1995 (json)

fr: json

format: JSON

media_type: application/json

fr: Produit intérieur brut – valeurs annuelles, dès 1995 (jsonl)

fr: jsonl

fr: Produit intérieur brut – valeurs annuelles, dès 1995 (parquet)

fr: parquet

format: PARQUET

fr: Produit intérieur brut – valeurs annuelles, dès 1995 (rdfxml)

fr: rdfxml

format: RDF XML

media_type: application/rdf+xml

fr: Produit intérieur brut – valeurs annuelles, dès 1995 (jsonld)

fr: jsonld

format: JSON-LD

fr: Produit intérieur brut – valeurs annuelles, dès 1995 (turtle)

fr: turtle

format: RDF Turtle

media_type: text/turtle

fr: Produit intérieur brut – valeurs annuelles, dès 1995 (n3)

fr: Produit intérieur brut – valeurs annuelles, dès 1995 (xlsx)

fr: xlsx

format: XLS

conjoncture-fribourgeoise

display_name: conjoncture-fribourgeoise

crea

display_name: crea

indicateurs-conjoncturels

display_name: indicateurs-conjoncturels

pib

display_name: pib

seco

display_name: seco

taux-de-croissance

display_name: taux-de-croissance


fr: Ce jeu de données présente les projections de la population résidante permanente des districts du canton de Fribourg, ventilées selon le sexe, l'âge et le scénario démographique (bas, moyen, haut), pour la période 2024 à 2055.Les effectifs correspondent au nombre projeté de personnes domiciliées dans le canton au 31 décembre de chaque année.Les projections sont établies par le Service de la statistique et de la donnée (SSD) à partir de la méthode des composantes (naissances, décès, migrations). Pour plus d'informations : [https://www.fr.ch/deef/ssd/statistiques-par-themes/evolution-future-de-la-population](https://www.fr.ch/deef/ssd/statistiques-par-themes/evolution-future-de-la-population)

fr: population-residante projection demographie district scenario evolution-future

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: Evolution future de la population résidante permanente des districts par âge et par sexe, de 2026 à 2055 (csv)

fr: Evolution future de la population résidante permanente des districts par âge et par sexe, de 2026 à 2055 (json)

fr: Evolution future de la population résidante permanente des districts par âge et par sexe, de 2026 à 2055 (jsonl)

fr: Evolution future de la population résidante permanente des districts par âge et par sexe, de 2026 à 2055 (parquet)

fr: Evolution future de la population résidante permanente des districts par âge et par sexe, de 2026 à 2055 (rdfxml)

fr: Evolution future de la population résidante permanente des districts par âge et par sexe, de 2026 à 2055 (jsonld)

fr: Evolution future de la population résidante permanente des districts par âge et par sexe, de 2026 à 2055 (turtle)

fr: Evolution future de la population résidante permanente des districts par âge et par sexe, de 2026 à 2055 (n3)

fr: Evolution future de la population résidante permanente des districts par âge et par sexe, de 2026 à 2055 (xlsx)

demographie

display_name: demographie

district

display_name: district

evolution-future

display_name: evolution-future

population-residante

display_name: population-residante

projection

display_name: projection

scenario

display_name: scenario


fr: Ce jeu de données présente l'aperçu mensuel des nuitées dans les hôtels et les établissements de cure dans le canton de Fribourg et dans l'ensemble de la Suisse, depuis 1992. Aucune donnée n'est disponible pour l'année 2004, la série a été interrompue à fin 2003 par l'OFS et reprise en 2005.

fr: tourisme nuitees hotels etablissements conjoncture-fribourgeoise indicateurs-conjoncturels

econ

fr: Économie et finances

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (csv)

fr: csv

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (json)

fr: json

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (jsonl)

fr: jsonl

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (parquet)

fr: parquet

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (rdfxml)

fr: rdfxml

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (jsonld)

fr: jsonld

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (turtle)

fr: turtle

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (n3)

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (xlsx)

etablissements

display_name: etablissements

hotels

display_name: hotels

nuitees

display_name: nuitees

tourisme

display_name: tourisme


fr: Ce jeu de données présente les projections de la population résidante permanente du canton de Fribourg, ventilées selon le sexe, l'âge et le scénario démographique (bas, moyen, haut), pour la période 2024 à 2055.Les effectifs correspondent au nombre projeté de personnes domiciliées dans le canton au 31 décembre de chaque année.Les projections sont établies par le Service de la statistique et de la donnée (SSD) à partir de la méthode des composantes (naissances, décès, migrations). Pour plus d'informations : [https://www.fr.ch/deef/ssd/statistiques-par-themes/evolution-future-de-la-population](https://www.fr.ch/deef/ssd/statistiques-par-themes/evolution-future-de-la-population)

fr: population-residante projection demographie canton scenario evolution-future

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

fr: Population et société

fr: Evolution future de la population résidante permanente du canton de Fribourg par âge et par sexe, de 2026 à 2055 (csv)

fr: Evolution future de la population résidante permanente du canton de Fribourg par âge et par sexe, de 2026 à 2055 (json)

fr: Evolution future de la population résidante permanente du canton de Fribourg par âge et par sexe, de 2026 à 2055 (jsonl)

fr: Evolution future de la population résidante permanente du canton de Fribourg par âge et par sexe, de 2026 à 2055 (parquet)

fr: Evolution future de la population résidante permanente du canton de Fribourg par âge et par sexe, de 2026 à 2055 (rdfxml)

fr: Evolution future de la population résidante permanente du canton de Fribourg par âge et par sexe, de 2026 à 2055 (jsonld)

fr: Evolution future de la population résidante permanente du canton de Fribourg par âge et par sexe, de 2026 à 2055 (turtle)

fr: Evolution future de la population résidante permanente du canton de Fribourg par âge et par sexe, de 2026 à 2055 (n3)

fr: Evolution future de la population résidante permanente du canton de Fribourg par âge et par sexe, de 2026 à 2055 (xlsx)

fr: xlsx

canton

display_name: canton


de: Konjunkturumfrage (Hemmnisse) bei Wirtschaftszweig, Indikator und Quartal

en: Business Survey (Obstacles) by Economic activity, Indicator and Quartal

amt-fuer-statistik-fl

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

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

de: Amt für Statistik

en: Office of Statistics

political_level: other

de: Konjunkturumfrage (Hemmnisse) nach Wirtschaftszweig seit 2020

en: Business Survey (Obstacles) by Industry since 2020

value: DCAT Harvester Amt für Statistik FL

en: Data structure in German

de: Datenstruktur auf Deutsch

de: Datenwürfel auf Englisch

en: Data cube in English

format: HTML

media_type: text/html

en: Data structure in English

de: Datenstruktur auf Englisch

de: Datenwürfel auf Deutsch

en: Data cube in German

business-tendency-survey

display_name: business-tendency-survey

konjunkturumfrage

display_name: konjunkturumfrage


de: Konjunkturumfrage (Rück-/Ausblick) bei Wirtschaftszweig, Rückblick/Ausblick, Indikator, Einheit und Quartal

en: Business Survey (Review/Outlook) by Economic activity, Review/Outlook, Indicator, Unit and Quartal

de: Konjunkturumfrage (Rück-/Ausblick) nach Wirtschafszweig seit 1990

en: Business Survey (Review/Outlook) by Industry since 1990


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-danger avalanche danger-level avalanche-forecasting snow-instability snow

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

de: EnviDat

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

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.

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

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

en: Restorative locations from participatory mapping by Swiss residents

format: ZIP

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:
ERRA is a data-driven, nonparametric, model-independent method for quantifying rainfall-runoff relationships across a spectrum of time lags, in systems that may be nonlinear, nonstationary, and spatially heterogeneous.
Researchers using ERRA in published work should cite J.W. Kirchner, "Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using Ensemble Rainfall-Runoff Analysis (ERRA): proof of concept", Hydrology and Earth System Sciences, https://doi.org/10.5194/hess-28-4427-2024, 2024 (for ERRA itself) and J.W. Kirchner, "Impulse response functions for nonlinear, nonstationary, and heterogeneous systems, estimated by deconvolution and de-mixing of noisy time series", Sensors, 22(9), 3291, https://doi.org/10.3390/s22093291, 2022 (for the underlying mathematics).
This data set includes two versions of the ERRA script written in the open-source programming language R, a detailed user's guide, and sample scripts and source data for all of the results in Kirchner (2024).
These scripts are made publicly available under GNU General Public License 3; for details see https://www.gnu.org/licenses/.  The data and documentation are made available under Creative Commons Attribution Share-Alike CC-BY-SA.
ETH Zurich, WSL, and James Kirchner make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose. Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

en: ecohydrology nonstationarity time-series streamflow hydrology precipitation nonlinear-deconvolution rainfall-runoff-modelling

en: ERRA -- an R script for Ensemble Rainfall-Runoff Analysis

en:
Resource Title: {{deprecated version}} ERRA_scripts.zip
    Size: 114811 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/9e833898-3a78-4e79-83bd-d23c5ba76765/download/erra_scripts.zip
    Description: Zip-compressed folder containing two versions of the ERRA script.  ERRA_v1.0.R uses Rcpp to speed up several key calculations, but requires a C++ compiler.  ERRA_v1.0_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp.  Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

media_type: application/zip

en:
Resource Title: Demonstration scripts.zip
    Size: 65399685 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/ca1f4818-aff6-4b13-a83d-82376dde2834/download/demonstration-scripts.zip
    Description: Zip-compressed folder containing demonstration scripts, source data, and output files for the ERRA results shown in "Introduction to ERRA" and in J.W. Kirchner, "Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using Ensemble Rainfall-Runoff Analysis (ERRA): proof of concept", Hydrology and Earth System Sciences, 2024.

en:
Resource Title: ERRA_scripts_v1.12.zip
    Size: 2621440 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/11af276e-c779-468c-9504-ef56bd490c7d/download/erra_scripts_v1.12.zip
    Description: Zip-compressed folder containing two versions of the ERRA script. ERRA_v1.12.R uses Rcpp to speed up several key calculations, but requires a C++ compiler. ERRA_v1.12_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp. Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: {{deprecated version}} An introduction to ERRA.pdf
    Size: 3156214 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/51f419cd-f933-4cad-88b4-a20ac7dcf545/download/an-introduction-to-erra.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them.  This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

en:
Resource Title: {{deprecated version}} An introduction to ERRA v1.11.pdf
    Size: 3072328 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/eee3eb76-74b7-4d84-bd23-fa2a97544b58/download/an-introduction-to-erra-v1.11.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them. This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

en:
Resource Title: {{deprecated version}} ERRA_scripts_v1.06.zip
    Size: 114452 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/64819efe-d661-41c8-8410-f61665564c05/download/erra_scripts_v1.06.zip
    Description: Zip-compressed folder containing two versions of the ERRA script. ERRA_v1.06.R uses Rcpp to speed up several key calculations, but requires a C++ compiler. ERRA_v1.06_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp. Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: {{deprecated version}} An introduction to ERRA v1.06.pdf
    Size: 3166700 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/0c048816-816a-4c1f-bedf-32be20e4d4c2/download/an-introduction-to-erra-v1.06.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them. This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

en:
Resource Title: {{deprecated version}} ERRA_scripts_v1.11.zip
    Size: 2621440 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/6e05e468-ccd2-4d42-be7b-b7578a68061e/download/erra_scripts_v1.11.zip
    Description: Zip-compressed folder containing two versions of the ERRA script. ERRA_v1.11.R uses Rcpp to speed up several key calculations, but requires a C++ compiler. ERRA_v1.11_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp. Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: An introduction to ERRA v1.12.pdf
    Size: 3072328 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/927de1da-fef7-4b05-8534-ae8330bbb48c/download/an-introduction-to-erra-v1.12.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them. This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

ecohydrology

display_name: ecohydrology

hydrology

display_name: hydrology

nonlinear-deconvolution

display_name: nonlinear-deconvolution

nonstationarity

display_name: nonstationarity

precipitation

display_name: precipitation

rainfall-runoff-modelling

display_name: rainfall-runoff-modelling

streamflow

display_name: streamflow

time-series

display_name: time-series


en:
The dataset consists of the standardized precipitation (SPI) and the standardized precipitation evapotranspiration index (SPEI) index with a 30 arcsec (~1km) horizontal resolution.
Data for precipitation rates (pr) and potential evapotranspiration (pet) are taken from CHELSA V2.1 (https://doi.org/10.16904/envidat.228.v2.1). Both data sets are monthly time series from 1980 to 2018 at 30 arcsec. and have the unit of kg m-2 month-1. SPEI is a more reliable measure of drought than SPI as it additionally considers the effect of potential evapotranspiration. Potential evapotranspiration (pet) is the amount of water per area per time that can evaporate at the soil surface or be transpired by plants in absence of water supply limitations. SPEI effectively estimates for a given location how the climatic water balance, i.e., the difference between precipitation rate (pr) and potential evapotranspiration (pet), relates to the long-term mean. Here, pet was calculated with the Penman-Montheith approach, assuming surface conductance of a reference crop of 12 cm height following the definition of the Food and Agriculture Organization of the United Nations (FAO), originating from CHELSA-BIOCLIM+ database (https://www.doi.org/10.16904/envidat.332). To obtain global time series of SPEI, in each pixel the frequency distribution of water balance estimates (pr-pet) is approximated with a log-logistic probability distribution function. We calculate monthly SPEI using a 12-month memory and approximate the parameters of the log-logistic probability distribution based on the time series from 1980-2018. Such a 12-month time window is suitable to capture long-term drought events that are long enough to impose substantial impacts on agriculture, hydrology, and ecosystems while ones at shorter time scales would be more appropriate to detect short-term drought. For each month, SPEI is calculated considering the respective water-balance value and the values of the eleven preceding months. Here we use SPEI-12 in December to represent the overall water-balance condition of the respective year. The resulting SPEI data has a horizontal resolution of 130 arcsec (~1km). The calculation of SPI and SPEI is done in R with the package SPEI (https://www.doi.org/10.32614/CRAN.package.SPEI).

en: potential-evapotranspiration extreme-events chelsa megadrought precipitation multi-year-drought drought

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

en: High resolution global standardized drought indices

envi

en: Environment

en:
Resource Title: Multiyear meteorological droughts (MYMD) statistics
    Size: 785961 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/21046cb1-0a1c-4890-8025-aefb5d9f3f1d/download/mymd_stats.csv
    Description: Statistics of the multiyear meteorological droughts, containing the ID, duration, area, and empirical ranking of the droughts.

en:
Resource Title: Multiyear meteorological droughts (MYMD) statistics - Description
    Size: 1114 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/a32ef5b4-fab9-4d15-b6da-c8244029027d/download/mymd_stats_description.csv
    Description: Description of column names, and units of the fields contained in the dataset "Multiyear meteorological droughts (MYMD) statistics".

en:
Resource Title: Kernel Normalized Difference Vegetation Index Anomaly (QKNDVI)
    Size: 6710886 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fannual%2Fqkndvi%2F
    Description: Global annual layers of the the kernel normalized difference vegetation index anomaly (qkndvi) at a 1/12° (~10km) spatial resolution.

en:
Resource Title: Multiyear meteorological droughts (MYMD10) statistics - Description
    Size: 1384 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/c1c0dbc9-ec96-462e-bf62-bc90b6aad3ab/download/mymd10_stats_description.csv
    Description: Description of column names, and units of the fields contained in the dataset "Multiyear meteorological droughts (MYMD10) statistics".

en:
Resource Title: CHELSA-drought-indices Technical Documentation
    Size: 257611 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/3149a573-b55c-499c-9efa-2cbe920bc483/download/chelsa_file_specification_drought_indicies.pdf
    Description: Technical documentation document including the variable names, units, scaling, offset, and background.

en:
Resource Title: Multiyear meteorological droughts (MYMD)
    Size: 368640 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fannual%2Fmymd%2F
    Description: Global annual layers of the multiyear meteorological droughts (MYMD) at a 1/24° (~5km) spatial resolution

en:
Resource Title: Multiyear meteorological droughts (MYMD10)
    Size: 107930 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fannual%2Fmymd10%2F
    Description: Global annual layers of the multiyear meteorological droughts (MYMD) at a 1/12° (~10km) spatial resolution

en:
Resource Title: Multiyear meteorological droughts (MYMD10) statistics
    Size: 928956 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/fa3d92e1-1eb0-478c-900d-dca818e3b4ff/download/mymd10_stats.csv
    Description: Multiyear meteorological droughts (MYMD10) statistics

Statistics of the multiyear meteorological droughts, containing the ID, duration, area, and empirical ranking of the droughts, and the anomalies in kNDVI

en:
Resource Title: CHELSA-drought-indices Technical Documentation
    Size: 335096 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/a4ec699c-1e4a-45ab-8b7c-ccdf09c6e828/download/chelsa_file_specification_drought_indicies.pdf
    Description: Technical documentation document including the variable names, units, scaling, offset, and background.

en:
Resource Title: Standardized Precipitation Index (SPI)
    Size: 209715200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fmonthly%2Fspi12%2F
    Description: Global monthly layers of the Standardized Precipitation Index (SPI) a 30 arcsec (~1km) spatial resolution

en:
Resource Title: Standardised Precipitation Evapotranspiration Index (SPEI)
    Size: 209715200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fmonthly%2Fspei12%2F
    Description: Global monthly layers of the Standardized Precipitation Evapotranspiration Index (SPEI) a 30 arcsec (~1km) spatial resolution

chelsa

display_name: chelsa

drought

display_name: drought

extreme-events

display_name: extreme-events

megadrought

display_name: megadrought

multi-year-drought

display_name: multi-year-drought

potential-evapotranspiration

display_name: potential-evapotranspiration


en:
**CH-POA300** is a dataset of hourly solar irradiance maps projected onto tilted surfaces (analogous to monofacial solar panels).
- **Spatial resolution:** 300 m
- **Coverage:** Switzerland
Two temporal extents are available, depending on the number of surface orientations (azimuth–tilt combinations):
 1. Long-term
- **Period:** 2004–2020
- **Orientations:**
  - Azimuth: 180° (South)
  - Tilts: 0°, 35°, 60°, 90°
 2. Typical year
- **Period:** 2016
- **Orientations:**
  - Azimuths: 0° (North), 90° (East), 135°, 180° (South), 225°, 270° (West)
  - Tilts: 0°, 3°, 8°, 15°, 25°, 35°, 45°, 60°, 80°, 90°
 Notes
- Azimuth angles: 0° = North, 90° = East, 180° = South, 270° = West
- Tilt angles: 0° = horizontal, 90° = vertical
 Additional data
- Seasonal and annual statistics derived from the maps are included.
- Methodology and quality assessment are documented in *CH-POA300-v-specs.pdf*.

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

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

en:
Resource Title: CH-POA300_v1_statistics
    Size: 1445061901 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/ea36025c-c855-488d-857d-f658bace53e2/download/chpoa300_statistics.zip
    Description: Contains seasonal and annual statistics (mean, sum) of the CH-POA300 dataset.

- "yyyy_agg_period_hourly_stat.nc": statistic <stat> for the period <agg_period> of the year <yyyy>
- "all_agg_period_stat_mean.nc": statistic <stat> for the period <agg_period> reduced on the entire dataset (all years).
\
yyyy: [2004, 2020]
agg_period: [winter, summer, annual]
stat: [mean, sum]

en:
Resource Title: Data 2004-2020
    Size: 858993459200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2FCHPOA300/&prefix=2004-2020
    Description:

en:
Resource Title: CH-POA300_v1_specs
    Size: 11472383 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/7146fc4a-df12-44a8-923f-69476b147a55/download/chpoa300_specs_v1.pdf
    Description: This document provides an in-depth description of the CH-POA300 dataset. It includes methodology and validation details.

en:
Resource Title: CH-POA300-v2-statistics
    Size: 1889349528 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/ed1238d2-b8c0-42f1-9b65-b837ac2dd259/download/stats.zip
    Description: Contains seasonal and annual statistics (mean and sum) derived from the CH-POA300 dataset.
File naming conventions:
yyyy_agg_period_hourly_stat.nc : statistic <stat> for aggregation period <agg_period> in year <yyyy>
all_agg_period_stat_mean.nc : statistic <stat> for aggregation period <agg_period> computed over the entire dataset (all years)
Definitions:
yyyy = year (2004–2020)
agg_period = winter, summer, annual
stat = mean, sum

en:
Resource Title: CH-POA300-v2-specs
    Size: 11473219 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/c184fb33-6751-47cd-a936-2f04de24c760/download/ch-poa300-v2-specs.pdf
    Description: This document provides an in-depth description of the CH-POA300 dataset. It includes methodology and validation details.

en:
Resource Title: Data 2016
    Size: 751619276800 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2FCHPOA300%2F&prefix=2016
    Description:

agri-pv

display_name: agri-pv

alpine-pv

display_name: alpine-pv

plane-of-array

display_name: plane-of-array

rooftop-pv

display_name: rooftop-pv

solar-irradiance

display_name: solar-irradiance

sweet-edge

display_name: sweet-edge


en: This data supplement contains the data associated with the manuscript: "Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions" (Janzing et al., 2025). It contains the data to create the figures in the paper and consists of model output from **PCRaster Global Water Balance Model (PCR-GLOBWB) 2.0** model over the larger Alpine region at 30 arcsec resolution. As the full model output takes up very high memory space, we here mostly provide time series for the different measurement stations used for evaluation and some additional maps needed to recreate the figures in the manuscript.

en: large-scale hydrological-simulations european-alps hydrology discharge

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

en: Data supplement to Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions

envi

en: Environment

discharge

display_name: discharge

european-alps

display_name: european-alps

hydrological-simulations

display_name: hydrological-simulations

hydrology

display_name: hydrology

large-scale

display_name: large-scale


en:
Lebensraumkarte der Schweiz v1.2 2025/La carte des milieux naturels de Suisse v1.2 2025
The FOEN funded project ‘The Habitat Map of Switzerland:continual improvement’ conducted at the WSL, has improved on versions 1.0 and 1.1 of a map of Swiss habitats according to the TypoCH classification (Delarze et al. 2015). The datasets is now separated into two data sets:  The Habitat Map of Switzerland v1.2, ground cover layer,  and The Habitat Map of Switzerland v1.2, individual trees and shrubs outside forest v1.0 (above ground) layer.
The Habitat Map of Switzerland maps the TypoCH habitat types wall-to-wall across the whole of Switzerland, to at least the classification’s 2nd level of detail (where possible to the 3rd level of detail).
Habitats are mapped through a variety of approaches that can be grouped as either:
1: Derived from the existing Swiss-wide datasets a) the high quality landcover mapping from Swisstopo’s Topographical Landscape Model (TLM), b) the harmonised mapping of agricultural fields area from the ‘Landwirtschaftliche Nutzfläche’ (LWN) mapping and, in settlements areas, c) the harmonised cadastral data (‘Amitliche Vermessung’ AV).
2: Modelled within the project using Random Forest or Ensemble Modelling techniques to model the spatial distribution of individual habitat types (further detail below),
3: Combining existing species distribution models to determine habitat types, or
4: Classification with relatively simple rule-sets based on auxiliary spatial datasets, i.e. vegetation height models (based on digital aerial photogrammetry and/or SwissSurface3D aerial laser scanning (ALS) data), the digital terrain model, the normalised difference vegetation index (NDVI) derived from aerial imagery and/or time-series of growing season Sentinel-2 or Planet satellite imagery.
Further detail on the methodology can be found within the README document.

en: wetland tof dwarf-shrubs habitat-modelling lidar sentinel-2 shrub-forest remote-sensing random-forest milieux-naturels urban ensemble-modelling forest typoch grasslands lebensraumkarte

en: The Habitat Map of Switzerland v1_2 2025

en:
Resource Title: TypoCH_NUM_LookupTable_26112025.csv
    Size: 46705 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/28aace15-eb00-4ec2-98ef-b55acc18286f/download/typoch_num_lookuptable_26112025.csv
    Description: Look up table for the data N2025_HabitatMap_CH_v1_2_20251211
giving the full text names for habitat types in German, French and Italian for each habitat type as well as the key for the type of methodology used

en:
Resource Title: LUT_einzelbaum_gebuesch_v_1_0.csv
    Size: 216 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/0035dd77-ea6d-4d3a-89bd-3ad6ee36302e/download/lut_einzelbaum_gebuesch_v_1_0.csv
    Description: Look up table for the data N2025_einzelbaum_gebuesche_v1_0_20251216
giving the full text names for each habitat type in German, French and Italian

en:
Resource Title: Data_Description_Lebensraumkarte_v1_2_Dec2025.pdf
    Size: 645376 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/564b16e5-0523-4431-94bc-3e6d1415c5a1/download/data_description_lebensraumkarte_v1_2_dec2025.pdf
    Description: Data description and documentation of methods

en:
Resource Title: symbology_v1_2_2025.zip
    Size: 61778 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/47c0e914-986f-4ad3-9bcf-49160023c030/download/symbology_v1_2_2025.zip
    Description: Symbology for the Habitat Map, ground layer and tree and shrub layer, and in ArcGIS and QGIS layer formats. German, French and Italian versions

en:
Resource Title: N2025_einzelbaum_gebuesche_v1_0_20251216.gdb.zip
    Size: 2469606195 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/cd4e36db-926c-4e2b-bb89-27dbe606dac3/download/n2025_einzelbaum_gebuesche_v1_0_20251216.gdb.zip
    Description: The Habitat Map of Switzerland v1.2, non-forest trees and shrubs layer, v1.0. Vector dataset in file geodatabase format. Complements the ground cover layer dataset

en:
Resource Title: N2025_HabitatMap_CH_v1_2_20251211.gdb.zip
    Size: 7247757312 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/a90d17bf-221e-4819-a8b1-94b807a33720/download/n2025_habitatmap_ch_v1_2_20251211.gdb.zip
    Description: The Habitat Map of Switzerland version 1.2 2025. Ground cover layer, All of Switzerland. Vector data in file geodatabase format. Is complemented by the trees and shrubs layer.

dwarf-shrubs

display_name: dwarf-shrubs

ensemble-modelling

display_name: ensemble-modelling

forest

display_name: forest

grasslands

display_name: grasslands

habitat-modelling

display_name: habitat-modelling

lebensraumkarte

display_name: lebensraumkarte

lidar

display_name: lidar

milieux-naturels

display_name: milieux-naturels

random-forest

display_name: random-forest

remote-sensing

display_name: remote-sensing

shrub-forest

display_name: shrub-forest

tof

display_name: tof

typoch

display_name: typoch

urban

display_name: urban

wetland

display_name: wetland


chelsacerra-daily

en:
CHELSA is a mechanistic downscaling model that links large-scale atmospheric conditions with local topographic factors to produce very high-resolution climate data. It includes commonly used climate variables for impact modeling, such as air temperature, precipitation, humidity, solar radiation, wind speed, and derived variables.
CHELSAcerra daily is a high resolution climate dataset for air-temperatures generated with the CHELSA downscaling model using the Copernicus regional reanalysis for Europe (CERRA).
Daily summaries are provided for: Daily Mean Near-Surface Air Temperature

en: air-temperature maximum-temperature climate minimum-temperature europe reanalysis

en: CHELSAcerra-daily

title_for_slug: chelsacerra-daily

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2015
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2015%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2003
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2003%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2001
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2001%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2014
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2014%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2013
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2013%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2000
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2000%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1997
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1997%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2010
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2010%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2004
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2004%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1992
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1992%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1996
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1996%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2012
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2012%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1989
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1989%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2008
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2008%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2005
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2005%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1987
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1987%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1988
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1988%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1991
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1991%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2009
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2009%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2011
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2011%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1995
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1995%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1994
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1994%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1998
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1998%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2007
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2007%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1993
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1993%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1999
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1999%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1990
    Size: 1 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1990%2FCERRA%2F
    Description:

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1986
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1986%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2002
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2002%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1985
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1985%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2006
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2006%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

air-temperature

display_name: air-temperature

climate

display_name: climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

reanalysis

display_name: reanalysis


en:
List of key debris flow variables from the WSL Illgraben monitoring station (2023) such as occurrence date and time, peak flow depth, peak flow velocity, total volume and bulk density.
This table contains values based on our current analysis methods. The list will be updated annually after each debris flow season, and as our methods continue to improve, individual values may change slightly in the future.

en: force-plate debris-flow monitoring-station illgraben magnitude

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: Illgraben debris-flow characteristics 2023
    Size: 786 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d24373f7-566f-441f-be64-6dbd8d0cc7e4/resource/8483e966-c20d-4403-93ed-26cc8fbf1d4d/download/df_characteristics_illgraben_2023.csv
    Description: List of key debris flow variables from the WSL Illgraben monitoring station (2023)

en:
Resource Title: Readme.txt
    Size: 1523 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d24373f7-566f-441f-be64-6dbd8d0cc7e4/resource/ea1a8f18-6989-493b-ac4d-72b60966f112/download/readme.txt
    Description:

format: TXT

media_type: text/plain

debris-flow

display_name: debris-flow

force-plate

display_name: force-plate

illgraben

display_name: illgraben

magnitude

display_name: magnitude

monitoring-station

display_name: monitoring-station


climarctic-seasons

en: This dataset includes measurements of potential microbial functions (potential extracellular enzyme activities and microbial functional genes abundance) and soil physico-chemical properties (pH, nutrients, texture, etc) in biocrusts and underlying mineral soils in High-Arctic tundra near Ny-Ålesund (Svalbard) during each season along a toposequence.

en: soil arctic greenhouse-gases microbial-functions microbial-biodiversity

en: Climarctic seasons

title_for_slug: climarctic-seasons

arctic

display_name: arctic

greenhouse-gases

display_name: greenhouse-gases

microbial-biodiversity

display_name: microbial-biodiversity

microbial-functions

display_name: microbial-functions

soil

display_name: soil


en:
The data supports the paper "Local and landscape factors shape alpha and beta trophic interaction diversity in urban gardens". It provides:
(1) the host-natural enemy interaction networks and network metrics between cavity-nesting bees and wasps and their natural enemies,
 (2) the explanatory variables reflecting urban intensity, temperature, habitat amount and management intensity.
(3) the questionnaires for assessing management intensity.
(4) a thesaurus for the variable names.
(5) a readme file.
(6) the R script used for the analyses.
The data is part of the BetterGardens project. It was sampled in 85 allotment and home gardens in the ctiy of Zurich in 2015 using standardized trapnests.

en: trap-nest host-enemy-interactions wasps urbanization zurich food-webs urban-ecosystems cavity-nesting hymenoptera urban-ecology management-intensity bees

en: Data on interaction diversity in urban gardens

en:
Resource Title: Not used: raw questionnaires
    Size: 30569 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/13da58d0-ae92-4ed3-8c24-f099c4ce400c/download/raw_questionnaires.csv
    Description:

en:
Resource Title: Raw data nests
    Size: 667409 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/1d6ef3da-b431-4fa9-8463-cad7fc487e6e/download/trapnest_data_bettergardens.csv
    Description: Host-enemy interaction data, used to compute the interaction diversity metrics

en:
Resource Title: Not used: readme
    Size: 6373 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/d35b12e9-ac52-44d3-82d3-102da2190c2d/download/readme.txt
    Description:

en:
Resource Title: Questionnaires management intensity anonymised
    Size: 30557 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/0f2466e6-a748-440e-a690-a13992c3e284/download/raw_questionnaires.csv
    Description: Results from the management intensity questionnaires anonymised. IDs are randomized and don't match those in the study data csv

en:
Resource Title: Script for the analyses v2.0
    Size: 54771 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/94ea4ad2-dbb3-45a6-8782-31ba29b788fb/download/script_betgards_clean.r
    Description: Cleaned script to reproduce the analyses

format: OCTET

en:
Resource Title: Script for the analyses v1.0
    Size: 53666 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/6f3ab130-4a41-4f08-ad61-ef692b41c871/download/script_betgards_clean.r
    Description: Cleaned script to reproduce the analyses

en:
Resource Title: Not used: data of the study
    Size: 15319 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/89ab594f-d989-4b77-afce-c6443cc1089d/download/dataset_betgard_predictors.csv
    Description:

en:
Resource Title: Read me file
    Size: 5214 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/188e4fa7-8cdd-43e5-aae4-ae66c5fa73c5/download/readme.txt
    Description:

en:
Resource Title: Thesaurus
    Size: 9654 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/5f684f4b-8b68-4565-bed4-d7b7782cb036/download/thesaurus_data.xlsx
    Description: Variable names and their description.

en:
Resource Title: Data of the study
    Size: 14672 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/b181b669-3290-4f59-a30d-2933071e1090/download/dataset_betgard_predictors.csv
    Description: The csv. file contains the response variable "interaction diversity" (idiv), and the values of the predictors used in the paper. The "id" column indicates the garden ID, each row in the dataset correspond to a garden and each column to the response (idiv), an explanatory variable or a descriptor (name, Lat, Long). See the thesaurus and the readme file for extended information on the variables.

bees

display_name: bees

cavity-nesting

display_name: cavity-nesting

food-webs

display_name: food-webs

host-enemy-interactions

display_name: host-enemy-interactions

hymenoptera

display_name: hymenoptera

management-intensity

display_name: management-intensity

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wasps

display_name: wasps

zurich

display_name: zurich


en: The dataset contains measured values of soil liquid water content, matric potential, and soil texture of 40 soil samples in Davos, Switzerland. The measurements were used for determining van Genuchten parameter values through fitting of water retention curves, pedotransfer functions, and inverse fitting with Hydrus-1D.

en: glide-snow-avalanche matric-potential soil alpine lwc soil-classification soil-texture measurements

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

en: Soil measurements of Seewer Berg and Davos

envi

en: Environment

en:
Resource Title: texture_data.csv
    Size: 1189 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/c1c4be41-28ff-4d20-97d5-aa6c28e74695/download/texture_data.csv
    Description: Texture data of the soil locations

en:
Resource Title: README.txt
    Size: 1599 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/ffffb46c-fc15-49a7-b179-e20ff120fb48/download/readme.txt
    Description: Detailed information of each file in the dataset

en:
Resource Title: van_genuchten_parameter_values.csv
    Size: 3098 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/810089c7-a4f8-4e9a-a9b9-5d1a55676b81/download/van_genuchten_parameter_values.csv
    Description: Complete list of the van Genuchten parameter values for each soil and method

en:
Resource Title: swb_hydrus_files.zip
    Size: 2906045 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/d7ce01fb-cce5-45ea-85ec-44a25ac49a77/download/swb_hydrus_files.zip
    Description: Hydrus files used for the inverse fitting

en:
Resource Title: coordinates.csv
    Size: 1222 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/7494a93b-068b-4d87-8f33-a16d197d27bf/download/coordinates.csv
    Description: Coordinates of each soil location, location of the snow profiles, and location of the snow liquid water content measurements

en:
Resource Title: swb_px_direct_fitting.csv
    Size: 7529 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/d4114528-bd8a-4335-b9ba-3d8eba7bb1fa/download/swb_px_direct_fitting.csv
    Description: Daily averaged values used for the direct fitting

alpine

display_name: alpine

glide-snow-avalanche

display_name: glide-snow-avalanche

lwc

display_name: lwc

matric-potential

display_name: matric-potential

measurements

display_name: measurements

soil-classification

display_name: soil-classification

soil-texture

display_name: soil-texture


en: This dataset consists of data related to capillary rise experiments performed with neutron radiography. There are 4 videos of capillary rise experiments as well as the files used to perform the inverse fitting with Hydrus. The videos show the upward flow of water in glass columns filled with sand and snow or sand, gravel, and snow. The videos show the 2D evolution of the unitless optical density with time. The Hydrus files were used to fit the parameter values of the Mualem-van Genuchten model. The experiments were performed at the Paul Scherrer Institute (PSI) in Villigen, Switzerland.

en: snow pore-water transport water soil measurements

en: Capillary rise rise experiments in snow using neutron radiography

en:
Resource Title: README.txt
    Size: 1089 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/5631a26d-f9f0-4548-9e78-e6eecdffcee5/download/readme.txt
    Description: Descriptions of the nomenclature, Hydrus files, and videos.

en:
Resource Title: depricated.txt
    Size: 496 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/74c3db20-eaed-40de-a880-f042010cf6cc/download/readme.txt
    Description: Description of the videos

en:
Resource Title: capillary_rise_experiment_videos.zip
    Size: 10552661 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/4d5ee580-c1b4-49d4-868f-971b8383afa7/download/capillary_rise_experiment_videos.zip
    Description: Videos of the capillary rise experiments

en:
Resource Title: Hydrus_inverse_fitting_files.zip
    Size: 749844 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/a4e140c9-e73a-402e-9b59-63b6000d5bb6/download/hydrus_inverse_fitting_files.zip
    Description: The Hydrus files used for the inverse fitting of the hydraulic conductivity.

pore-water

display_name: pore-water

snow

display_name: snow

soil

display_name: soil

transport

display_name: transport

water

display_name: water


c-n-p-release-treeline

en:
1. Chemical characteristics of litter layer sampled along elevation gradient across treeline ecotones in the Khibiny mountains (birch) and South Urals (spruce)
2. Release of C-N-P during decomposition at 5°C and 15° studied in an incubation experiment with microlysimeters
3. Data on microbial biomass C-N-P, potential activity of C-N-P requiring enzymes in the litter layer
4. Mineralization of 13C labeled glucose-6 phosphate, microbial 13C uptake, and net P immobilization of released P to identify microbial processing of labile organic P

en: carbon-cycle microbial-biomass treeline-ecosystems litter-decomposition nutrient-fluxes biogeochemical-cycling climate-change enzymatic-activities

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: C-N-P-Release Treeline

title_for_slug: c-n-p-release-treeline

biogeochemical-cycling

display_name: biogeochemical-cycling

carbon-cycle

display_name: carbon-cycle

climate-change

display_name: climate-change

enzymatic-activities

display_name: enzymatic-activities

litter-decomposition

display_name: litter-decomposition

microbial-biomass

display_name: microbial-biomass

nutrient-fluxes

display_name: nutrient-fluxes

treeline-ecosystems

display_name: treeline-ecosystems


forest-canopy-layer-code

en:
R script for large-scale mapping of forest canopy layering. The approach combines tree-based and area-based methods, using airborne laser scanning point clouds together with individual tree detection (ITD) information (tree height and position) to distinguish between single- and multi-layered forests. The output is a raster layer at 10m x 10m resolution, encoded as follows:
1: single-layered (class 1): Both point cloud and ITD approaches classify the forest as single-layered.
2: probably single-layered (class 2): ITD classifies the forest as single-layered, while the point cloud suggests multi-layered.
3: probably multi-layered (class 3): ITD classifies the forest as multi-layered, while the point cloud suggests single-layered.
4: multi-layered (class 4): Both point cloud and ITD approaches classify the forest as multi-layered.
Next to the R script, we also provide an example data set. The LAZ files in the example dataset are from the nationwide ALS data and are provided by the Federal Office of Topography swisstopo in accordance with its open data policy (swisstopo, 2022a, 2019). The detected individual trees were identified using Dalponte and Coomes' (2016) algorithm on a spike-free vegetation height model (cell size 0.5m). The provided forest mask corresponds to the NFI forest layer definition by Waser et al. (2015). For details and mentioned references, we refer to the related publication by Bast et al. (under revision; JAG).

en: lidar protective-forest vhm forest itd forest-management mountain-forest

envidat

en: EnviDat: the Environmental Data Portal

en: Forest Canopy Layer Code

title_for_slug: forest-canopy-layer-code

envi

en: Environment

forest

display_name: forest

forest-management

display_name: forest-management

itd

display_name: itd

lidar

display_name: lidar

mountain-forest

display_name: mountain-forest

protective-forest

display_name: protective-forest

vhm

display_name: vhm


en:
This dataset originates from a two-year transplant experiment conducted across a temperature gradient in Europe (mean annual temperatures: 8.4–21.8 °C). It includes physiological measurements of one invasive palm species (Trachycarpus fortunei) and two co-occurring native species (Ilex aquifolium and Tilia cordata). The dataset captures plant acclimation responses to air temperature, focusing on photosynthetic and respiratory traits that influence carbon balance.
Variables that can be extracted:
- Optimal temperature of photosynthesis (Topt)
- Photosynthetic rate at optimal temperature (Aopt)
- Thermal breadth of photosynthesis (T80)
- Respiration rate at 25 °C (R25)
- Temperature sensitivity of respiration (Q10)
Raw data are reported for all species across multiple sites and time points, enabling assessment of their acclimation capacity to warming. The dataset supports comparisons of functional plasticity between an invasive species and native taxa, providing insights into climate responses and invasion ecology.

en: acclimation spac-model leaf invasive-species respiration photosynthesis

en: Thermal acclimation fails to confer a carbon budget advantage to invasive species over natives

acclimation

display_name: acclimation

invasive-species

display_name: invasive-species

leaf

display_name: leaf

photosynthesis

display_name: photosynthesis

respiration

display_name: respiration

spac-model

display_name: spac-model


en:
Data and code for the paper published in Ecography: Community structure and range shifts in Arctic marine fish under climate change
Abstract:
Arctic marine ecosystems are rapidly transforming due to climate change. Warming temperatures and shrinking sea ice are enabling boreal fish to expand northward, possibly disturbing cold-adapted Arctic species assemblages. Species range shifts have been documented in the Bering and Barents Seas, raising concerns about ecosystem restructuring. Range shifts are especially difficult to detect in the Arctic due to sparse and inconsistent data. Here, we studied fish composition from eDNA water samples taken in East Greenland, Svalbard, the Barents Sea, and the Kara Sea during the TOPtoTOP and Arctic Century expeditions. We examined the environmental drivers of fish community structure using global dissimilarity models. We calculated the decadal rate of temperature change to identify the fastest-changing areas. We compared fish detections from eDNA with published historical records for the Kara Sea to assess possible range expansions. We found that temperature was the main factor influencing the taxa turnover of fish communities, with Gadidae and Liparis sp. driving the greatest compositional differences. Over the past 30 years, temperatures increased by 0.2 to 0.6°C per decade at our study sites, with the highest increases in western Svalbard and the lowest in the eastern Kara Sea. Despite the apparent dependence on temperature, we identified only one species detected outside its known latitudinal range, and five species in the Kara Sea with recent occurrences or representing an extended distribution. Our study suggests that temperature, the main driver of fish community assembly, is increasing rapidly in the Arctic, and a few species have likely already shifted recently, or at least their detections are new in some areas. While these detections cannot be definitively linked to range shifts, our results highlight the need to improve monitoring of high-latitude fish communities to detect and predict future ecosystem changes.
Article:
Marques, V., Fopp, F., Jaquier, M., Ellingsen, K. E., Yoccoz, N., Jucker, M., ...Pellissier, L. (2025). Community structure and range shifts in Arctic marine fish under climate change. Ecography, e8014. doi: 10.1002/ecog.08014
Data:
The resource contains a zip file with the entire project structure.
Data README:
 Intro
This repo presents data and code associated with the paper "Community structure and range shifts in Arctic marine fish under climate change" published in Ecography
 Usage
Launch the `main.R` script to reproduce the entire analysis.
It executes code blocks to create the data necessary for the analysis and then creates the figures.
💣 attention, total size is expected ~20 Go and the script will query the CMEMS database to fetch environmental data
 Tools
To make the scripts run, you need R, R packages (see session info below), python3, and the copernicusmarine python tool (https://pypi.org/project/copernicusmarine/).
 SessionInfo
```
sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: aarch64-apple-darwin20
Running under: macOS 15.5
Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/Zurich
tzcode source: internal
attached base packages:
[1] stats     graphics  grDevices
[4] utils     datasets  methods
[7] base
other attached packages:
 [1] lwgeom_0.2-14
 [2] metR_0.15.0
 [3] ggtext_0.1.2
 [4] scico_1.5.0
 [5] ggnewscale_0.5.0
 [6] colorspace_2.1-1
 [7] climetrics_1.0-15
 [8] rts_1.1-14
 [9] xts_0.14.0
[10] zoo_1.8-12
[11] ggpubr_0.6.0
[12] adespatial_0.3-23
[13] ggspatial_1.1.9
[14] colorplaner_0.1.4
[15] ape_5.8
[16] factoextra_1.0.7
[17] corrgram_1.14
[18] FactoMineR_2.11
[19] betapart_1.6
[20] gdm_1.5.0-9.1
[21] terra_1.7-78
[22] rnaturalearth_1.0.1
[23] ggrepel_0.9.5
[24] vegan_2.6-6.1
[25] lattice_0.22-6
[26] permute_0.9-7
[27] cowplot_1.1.3
[28] tidyterra_0.6.1
[29] sf_1.0-16
[30] egg_0.4.5
[31] gridExtra_2.3
[32] patchwork_1.2.0
[33] viridis_0.6.5
[34] viridisLite_0.4.2
[35] mgcv_1.9-1
[36] nlme_3.1-165
[37] MBA_0.1-0
[38] reshape2_1.4.4
[39] conflicted_1.2.0
[40] lubridate_1.9.3
[41] forcats_1.0.0
[42] stringr_1.5.1
[43] dplyr_1.1.4
[44] purrr_1.0.2
[45] readr_2.1.5
[46] tidyr_1.3.1
[47] tibble_3.2.1
[48] ggplot2_3.5.1
[49] tidyverse_2.0.0
[50] devtools_2.4.5
[51] usethis_2.2.3
loaded via a namespace (and not attached):
  [1] splines_4.4.0
  [2] later_1.3.2
  [3] bitops_1.0-7
  [4] minpack.lm_1.2-4
  [5] XML_3.99-0.16.1
  [6] lifecycle_1.0.4
  [7] rstatix_0.7.2
  [8] doParallel_1.0.17
  [9] MASS_7.3-60.2
 [10] flashClust_1.01-2
 [11] backports_1.5.0
 [12] magrittr_2.0.3
 [13] rmarkdown_2.27
 [14] yaml_2.3.8
 [15] remotes_2.5.0
 [16] httpuv_1.6.15
 [17] sp_2.1-4
 [18] sessioninfo_1.2.2
 [19] pkgbuild_1.4.4
 [20] mapproj_1.2.11
 [21] pbapply_1.7-2
 [22] DBI_1.2.3
 [23] RColorBrewer_1.1-3
 [24] ade4_1.7-22
 [25] maps_3.4.2
 [26] abind_1.4-5
 [27] pkgload_1.3.4
 [28] RCurl_1.98-1.14
 [29] itertools_0.1-3
 [30] yaImpute_1.0-34
 [31] rcdd_1.6
 [32] units_0.8-5
 [33] adegenet_2.1.10
 [34] codetools_0.2-20
 [35] xml2_1.3.6
 [36] adephylo_1.1-16
 [37] DT_0.33
 [38] tidyselect_1.2.1
 [39] RNeXML_2.4.11
 [40] raster_3.6-26
 [41] farver_2.1.2
 [42] jsonlite_1.8.9
 [43] e1071_1.7-14
 [44] phylobase_0.8.12
 [45] ellipsis_0.3.2
 [46] iterators_1.0.14
 [47] emmeans_1.10.4
 [48] systemfonts_1.1.0
 [49] foreach_1.5.2
 [50] progress_1.2.3
 [51] tools_4.4.0
 [52] ragg_1.3.2
 [53] snow_0.4-4
 [54] Rcpp_1.0.13
 [55] glue_1.8.0
 [56] xfun_0.44
 [57] withr_3.0.0
 [58] fastmap_1.2.0
 [59] boot_1.3-30
 [60] latticeExtra_0.6-30
 [61] fansi_1.0.6
 [62] spData_2.3.1
 [63] digest_0.6.35
 [64] timechange_0.3.0
 [65] R6_2.5.1
 [66] mime_0.12
 [67] estimability_1.5.1
 [68] wk_0.9.1
 [69] textshaping_0.4.0
 [70] jpeg_0.1-10
 [71] utf8_1.2.4
 [72] generics_0.1.3
 [73] data.table_1.15.4
 [74] class_7.3-22
 [75] prettyunits_1.2.0
 [76] httr_1.4.7
 [77] htmlwidgets_1.6.4
 [78] scatterplot3d_0.3-44
 [79] spdep_1.3-5
 [80] pkgconfig_2.0.3
 [81] gtable_0.3.5
 [82] picante_1.8.2
 [83] adegraphics_1.0-21
 [84] htmltools_0.5.8.1
 [85] carData_3.0-5
 [86] profvis_0.3.8
 [87] multcompView_0.1-10
 [88] scales_1.3.0
 [89] leaps_3.2
 [90] png_0.1-8
 [91] doSNOW_1.0.20
 [92] geometry_0.4.7
 [93] rnaturalearthhires_1.0.0.9000
 [94] knitr_1.47
 [95] rstudioapi_0.16.0
 [96] rncl_0.8.7
 [97] uuid_1.2-0
 [98] tzdb_0.4.0
 [99] checkmate_2.3.1
[100] coda_0.19-4.1
[101] magic_1.6-1
[102] proxy_0.4-27
[103] cachem_1.1.0
[104] KernSmooth_2.23-24
[105] parallel_4.4.0
[106] miniUI_0.1.1.1
[107] s2_1.1.6
[108] pillar_1.9.0
[109] grid_4.4.0
[110] vctrs_0.6.5
[111] urlchecker_1.0.1
[112] promises_1.3.0
[113] car_3.1-2
[114] xtable_1.8-4
[115] cluster_2.1.6
[116] evaluate_0.24.0
[117] mvtnorm_1.2-5
[118] cli_3.6.3
[119] compiler_4.4.0
[120] rlang_1.1.4
[121] crayon_1.5.2
[122] ggsignif_0.6.4
[123] labeling_0.4.3
[124] interp_1.1-6
[125] classInt_0.4-10
[126] plyr_1.8.9
[127] fs_1.6.4
[128] stringi_1.8.4
[129] deldir_2.0-4
[130] munsell_0.5.1
[131] Matrix_1.7-0
[132] hms_1.1.3
[133] seqinr_4.2-36
[134] shiny_1.8.1.1
[135] gridtext_0.1.5
[136] igraph_2.0.3
[137] broom_1.0.6
[138] memoise_2.0.1
[139] fastmatch_1.1-4
```
 Data content and reproducibility
Uncleaned raw table out of the bioinformatics pipeline can be found concatenated in `outputs/table_raw_before_cleaning.csv`, yet we caution readers to properly read the cleaning scripts should they wish to reproduce our analysis and this file is presently uncleaned.

en: climate-change fish arctic community-structure environmental-dna

en: Data and code for Community structure and range shifts in Arctic marine fish under climate change

arctic

display_name: arctic

climate-change

display_name: climate-change

community-structure

display_name: community-structure

environmental-dna

display_name: environmental-dna

fish

display_name: fish


en: This dataset contains experimental acoustic and vibration signals recorded by the Phased Microphone Arrays (PMA) system during laboratory impact calibration tests. The PMA system is designed for surrogate monitoring of bedload transport. It consists of a stainless-steel plate mounted on elastomer supports and instrumented with an array of microphone elements and an accelerometer fixed to the internal plate. The microphone sensors (sensitivity = 11.2 mV/Pa, frequency response = 10 Hz - 20 kHz) record air-pressure fluctuations caused by particle impacts, while the accelerometer (sensitivity = 50.0 mV/g, frequency response = 0.5 Hz - ~10 kHz) measures vibrations of the internal plate. All channels were synchronously sampled at 10 kHz using a 16-channel, 24-bit data acquisition system. Additional data and details on experimental setup, signal analysis, and interpretation are available in the associated publication.

en: surrogate-measurement impact-test particle-size localization monitoring-techniques microphone bedload-transport acoustic-signals natural-hazards accelerometer

en: Acoustic Data from the PMA Bedload Monitoring System

accelerometer

display_name: accelerometer

acoustic-signals

display_name: acoustic-signals

bedload-transport

display_name: bedload-transport

impact-test

display_name: impact-test

localization

display_name: localization

microphone

display_name: microphone

monitoring-techniques

display_name: monitoring-techniques

natural-hazards

display_name: natural-hazards

particle-size

display_name: particle-size

surrogate-measurement

display_name: surrogate-measurement


en:
This data include wind speeds, wind directions, turbulence, temperature, pressure and humidity data of 10 LiDAR locations along a transect in the Gotthard wind park taken in during the summer of 2023.
The data is quality controlled and annotated according to CF-1.8 data principles. The methods behind this data collection are explained in an article under review called "Resolving three-dimensional wind velocity fields with sequential wind-Doppler LiDAR for wind energy in the complex terrain - Gotthard Pass, Switzerland".

en: atmospheric-turbulence wind atmospheric-dynamics lidar wind-energy remote-sensing

en: Sequential Wind-Doppler LiDAR wind profile measurements on the Gotthard pass in Switzerland - Summer 2023

atmospheric-dynamics

display_name: atmospheric-dynamics

atmospheric-turbulence

display_name: atmospheric-turbulence

lidar

display_name: lidar

remote-sensing

display_name: remote-sensing

wind

display_name: wind

wind-energy

display_name: wind-energy


en:
This repository contains data from the alpine Dischma watershed and its surroundings in eastern Switzerland and includes: (a) hourly hydrometeorological data with 100m spatial resolution, (b) remotely sensed snow depth data with 100m spatial resolution obtained at peak of winter, and (c) station measurements of variables such as snow depth and catchment runoff.
This dataset is particularly suited for (a) different simulation experiments using distributed and process-based models, including physics-based snow and hydrological models, (b) testing various snow data assimilation schemes, and (c) developing models representing snow-forest interactions.
The dataset is described in detail in:
Magnusson, J., Bühler, Y., Quéno, L., Cluzet, B., Mazzotti, G., Webster, C., Mott, R., and Jonas, T.: High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2024-374, in review, 2024.
This dataset was published within the INARCH project:
https://inarch.usask.ca/

en: inarch cryosphere dischma snow hydrology modelling

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: A high-resolution snow and hydrometeorological dataset for the Dischma region in Switzerland

cryosphere

display_name: cryosphere

dischma

display_name: dischma

hydrology

display_name: hydrology

inarch

display_name: inarch

modelling

display_name: modelling

snow

display_name: snow