fr: Les surfaces bien exposées situées sur les bâtiments peuvent être exploitées pour valoriser l'énergie solaire au niveau thermique et couvrir en partie les besoins de CHAUFFAGE et d'ECS. Différents indicateurs énergétiques, économiques et environnementaux ont été calculés. La couche du potentiel de production de chauffage et d'eau chaude sanitaire (ECS) par bâtiment représente et regroupe les informations relatives au potentiel de production d'énergie thermique tenant compte: - des surfaces bien exposées (qui ont une irradiation solaire brute annuelle supérieure à 1000 [kWh/m2 an], nommées ci-après surfaces utiles), - des besoins en chauffage impliquant au préalable une rénovation de l'enveloppe pour les bâtiments anciens et peu performants (Qh - indice utile de chauffage - considéré : max 155 MJ/m2/an), - des besoins en chaude sanitaire (ECS). Ces informations de potentiels portent notamment sur la quantité d'énergie thermique annuelle et mensuelle valorisable pour les besoins propres du bâtiment, les éventuels surplus thermiques (en particulier pendant la période estivale), le taux de couverture des besoins, la surface des capteurs, la part de la surface occupée par les capteurs, des données environnementale (tonne de CO2 potentiellement économisée) et des données économiques (frais d'investissement, charges, recettes). Cette couche est élaborée à l'échelle du Grand Genève qui englobe le Canton de Genève, le District de Nyon (Canton de Vaud) et plusieurs communautés de communes francaises des départements de l'Ain et de la Haute-Savoie. La présente version de la couche s'appuie sur les données LIDAR 2017 pour le Canton de Genève, LIDAR 2015 pour la partie vaudoise, et LIDAR 2014 pour la partie francaise (les potentiels calculés ne tiennent pas compte de bâtiments construits après cette date). L'élaboration de cette couche, en automne 2019, s'inscrit dans le cadre du programme INTERREG V France-Suisse et du projet G2 Solaire. Ce dernier permet à la fois de mettre à jour le précédent cadastre solaire genevois de 2016 (sous mandat de l'OCEN - Office cantonal de l'énergie - et des SIG - Services industriels genevois), et de l'étendre sur le reste du Grand Genève. Plus d'information sur cette couche et sa méthodologie d'élaboration sont disponibles au travers du rapport - CADASTRE SOLAIRE DU CANTON DE GENEVE - Phase 2 - Analyse du potentiel de production énergétique par les panneaux solaires thermique et PV - Rapport final - Hepia v17.10.2014.

fr: Potentiel solaire de production de chauffage et d'ECS par bâtiment

regi

fr: Régions et villes


$oid: OBSOLETE

fr: Cette couche est une première version de la compilation de l'ensemble des données à disposition sur les installations de chaleur. Elle fera l'objet d'amélioration par la suite.

canton-geneve

approval_status: approved

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

political_level: canton

state: active

type: organization

fr: Office cantonal de l'énergie

de: geocat.ch Permalink

fr: geocat.ch permalien

it: geocat.ch link permanente

en: geocat.ch permalink

spatial: GE

fr: Installations Productrices De Chaleur (Public)

type: dataset

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

format: XML

media_type: application/xml

fr: Serveur de fichiers Opendata

fr: CSV

format: CSV

media_type: text/csv

fr: GDB

format: ZIP

media_type: application/zip

fr: GML

format: GML

fr: KML

format: KML

fr: SHP

value: GEOCAT canton GE


fr: Cette couche comprend les surfaces utiles où l'irradiation solaire brute annuelle dépasse 1000 kWh/m2.an. Elle est élaborée à l'échelle du Grand Genève qui englobe le Canton de Genève, le District de Nyon (Canton de Vaud) et plusieurs communautés de communes francaises des départements de l'Ain et de la Haute-Savoie. Sur le Canton de Genève, les surfaces utiles sont découpées aux limites des toitures (voir la couche CAD_BATIMENT_HORSOL_TOIT). Sur le Canton de Vaud et la partie francaise, les surfaces sont découpées aux limites des bâtiments (voir la couche RTGE_BATIMENT_ENERGIE). Sur le Canton de Genève, cette couche comprend également les surfaces utiles pouvant se trouver sur des couverts ou des parkings (en tant que couverts potentiels). La présente version de la couche s'appuie sur les données LIDAR 2017 pour le Canton de Genève, LIDAR 2015 pour la partie vaudoise, et LIDAR 2014 pour la partie francaise (les potentiels calculés ne tiennent pas compte de bâtiments construits après cette date). L'élaboration de cette couche, en automne 2019, s'inscrit dans le cadre du programme INTERREG V France-Suisse et du projet G2 Solaire. Ce dernier permet à la fois de mettre à jour le précédent cadastre solaire genevois de 2016 (sous mandat de l'OCEN - Office cantonal de l'énergie - et des SIG - Services industriels genevois), et de l'étendre sur le reste du Grand Genève. Plus d'information sur cette couche et sa méthodologie d'élaboration sont disponibles au travers du rapport - CADASTRE SOLAIRE DU CANTON DE GENEVE - Phase 2 - Analyse du potentiel de production énergétique par les panneaux solaires thermique et PV - Rapport final - Hepia v17.10.2014.

fr: Potentiel solaire - Irradiation brute par surface utile (y compris couvert et parking)

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

it: Economia e finanze


fr: AGREGATION DES STATISTIQUES CANTONALES DE LA POPULATION ET DU PARC IMMOBILIER (Information à la commune) Les informations sur la population proviennent de la statistique cantonale de la population, celles sur les bâtiments et les logements proviennent de la statistique du parc immobilier. La statistique cantonale de la population prend en compte les personnes d'origine suisse et les ressortissants étrangers titulaires d'une autorisation de séjour officielle qui habitent effectivement dans le canton. Elle se fonde sur les informations détenues par l'Office cantonal de la population et des migrations (OCPM). 'Pour plus d'informations sur les bases méthodologiques de cette statistique: https://statistique.ge.ch/domaines/01/01_01/methodologie.asp La statistique du parc immobilier repose sur le Registre fédéral des bâtiments et des logements (RegBL). Pour des raisons liées au rythme de mise à jour de l'information, il est possible que des bâtiments présents dans le RegBL soient absents du SITG. En effet, le RegBL présente un état en fin de trimestre, alors que les informations du SITG sont actualisées quotidiennement. La date de mise à jour est de 2 mois après la fin d'un trimestre Pour plus d'informations sur cette statistique: https://statistique.ge.ch/domaines/09/09_02/methodologie.asp#1

fr: Office cantonal de la statistique

fr: Agrégation statistiques population et parc immobilier (communes)

soci

de: Bevölkerung und Gesellschaft

en: Population and society

fr: Population et société

it: Popolazione e società


sous-secteurs-statistiques-girec

name: Direction de l'information du territoire

fr: Les sous-secteurs statistiques couvrent une entité territoriale à une échelle intermédiaire entre la parcelle et la commune. Ils permettent de distinguer, dans les zones urbaines, les différents quartiers, ou dans les zones rurales, des villages et hameaux des zones agricoles ou forestières. Le canton de Genève a été découpées en 394 sous-secteurs en 1990. Une mise à jour en 2004 à fait passer le nombre de sous-secteurs à 475. En 2023, les limites du découpage ont été légèrement modifiées pour s'adapter aux évolutions des rives du Léman. Le code d'identification a été complété par un 7ème chiffre - 1er et 2ème : numéro fédéral de la commune (sur 2 chiffres --> 6638 = 38) - 3ème et 4ème: numéro du secteur (Ville de Genève uniquement) - 5ème à 7ème: numéro du sous-secteur Le 7ème chiffre du code permet d'identifier les modifications par rapport au découpage d'origine - nn0 sous-secteur sans modification - nn1 à nn4 sous-secteur créé par subdivision - nn9 sous-secteur avec adaptation des limites (modifications mineures)

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).

fr: Canton de Genève

fr: Sous-secteurs statistiques (GIREC)

title_for_slug: sous-secteurs-statistiques-girec

regi

fr: Régions et villes


fr: Les informations au sous-secteur statistique sur les bâtiments et les logements proviennent de la statistique du parc immobilier, qui repose sur le Registre fédéral des bâtiments et des logements (RegBL). Pour plus d'informations sur cette statistique: https://statistique.ge.ch/domaines/09/09_04/methodologie.asp La date de mise à jour est de 2 mois après la fin d'un trimestre Pour des raisons liées au rythme de mise à jour de l'information, il est possible que des bâtiments présents dans le RegBL soient absents du SITG. En effet, le RegBL présente un état en fin de trimestre, alors que les informations du SITG sont actualisées quotidiennement.

fr: geocat.ch permalien

fr: Statistique cantonale des bâtiments et logements (information au sous-secteur)

fr: Serveur de fichiers Opendata

fr: CSV

fr: GDB


fr: AGREGATION DES STATISTIQUES CANTONALES DE LA POPULATION ET DU PARC IMMOBILIER (Information aux secteurs de la ville de Genève) Les informations sur la population proviennent de la statistique cantonale de la population, celles sur les bâtiments et les logements proviennent de la statistique du parc immobilier. La statistique cantonale de la population prend en compte les personnes d'origine suisse et les ressortissants étrangers titulaires d'une autorisation de séjour officielle qui habitent effectivement dans le canton. Elle se fonde sur les informations détenues par l'Office cantonal de la population et des migrations (OCPM). Pour plus d'informations sur les bases méthodologiques de cette statistique: https://statistique.ge.ch/domaines/01/01_01/methodologie.asp La statistique du parc immobilier repose sur le Registre fédéral des bâtiments et des logements (RegBL).Pour des raisons liées au rythme de mise à jour de l'information, il est possible que des bâtiments présents dans le RegBL soient absents du SITG. En effet, le RegBL présente un état en fin de trimestre, alors que les informations du SITG sont actualisées quotidiennement. La date de mise à jour est de 2 mois après la fin d'un trimestre. Pour plus d'informations sur cette statistique: https://statistique.ge.ch/domaines/09/09_02/methodologie.asp#1

fr: Agrégation statistiques population et parc immobilier (secteurs ville de Genève)

fr: GML

fr: KML

fr: SHP


fr: Selon la statistique structurelle des entreprises (STATENT), toute personne qui exerce une activité professionnelle indépendante ou salariée et dont le revenu est obligatoirement soumis à une cotisation AVS représente un emploi. Les résultats sont arrondis à l'entier. Par conséquent, leur somme peut ne pas correspondre exactement au total ou aux sous-totaux publiés par l'OCSTAT. Pour plus d'informations sur cette statistique: https://statistique.ge.ch/domaines/06/06_02/methodologie.asp

fr: Office cantonal de la statistique

fr: Statistique structurelle des entreprises (information à la commune)

soci

fr: Population et société


fr: Le concept cantonal du sport prévoit la mise à jour régulière du recensement des infrastructures liées au sport. Dans cette optique, l'Observatoire Universitaire du Sport et des Loisirs de l'Université de Lausanne a été chargé par le DIP de mettre à jour le répertoire des installations sportives. Ces données s'adressent aux autorités cantonales (département de la cohésion sociale (DCS) - Service cantonal du sport) et communales (Service des sports des communes), mais également aux associations sportives, aux clubs sportifs et aux particuliers (pratiquants). Ainsi, chaque décideur, association ou sportif obtient une image complète du parc d'installations sportives. Lieux de sport : il s'agit d'un lieu spécifique où il est possible de pratiquer un sport déterminé en respectant les règles usuelles. Ce lieu est associé nécessairement à un équipement qui possède les caractéristiques indispensables (marquages au sol, matériel spécifique comme des buts, des paniers, plongeoirs, etc.).

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).

fr: Canton de Genève

fr: Service cantonal du sport

fr: Installations sportives - Lieux de sports

heal

de: Gesundheit

en: Health

fr: Santé

it: Salute


fr: Secteur des établissements médico-sociaux (EMS)

fr: Direction générale de la santé

fr: geocat.ch permalien

fr: Secteurs des établissements médico-sociaux

fr: Serveur de fichiers Opendata

fr: CSV


fr: Le concept cantonal du sport prévoit la mise à jour régulière du recensement des infrastructures liées au sport. Dans cette optique, l'Observatoire Universitaire du Sport et des Loisirs de l'Université de Lausanne a été chargé par le département de la formation et de la jeunesse (DFJ) de mettre à jour le répertoire des installations sportives. Ces données s'adressent aux autorités cantonales (département de la cohésion sociale (DCS) - Service cantonal du sport) et communales (Service des sports des communes), mais également aux associations sportives, aux clubs sportifs et aux particuliers (pratiquants). Ainsi, chaque décideur, association ou sportif obtient une image complète du parc d'installations sportives. Les équipements sportifs : il s'agit d'une infrastructure spécifique où peut être pratiqué un sport, voire plusieurs, et qui peut être associée à un ou plusieurs autres équipements au sein d'une installation. Une salle de gymnastique, des terrains de football, une piste d'athlétisme ou une piscine constituent des exemples d'équipements sportifs. A noter qu'un équipement sportif peut être constitué de plusieurs objets, à condition que ces objets soient identiques (dimensions, revêtement de sol, sports praticables).

fr: Installations sportives - Équipements sportifs

fr: GDB

fr: GML

fr: KML

fr: SHP


fr: Les établissements médico-social (EMS) autorisés par le secteur des structures pour seniors (StS) du DCS, répertoriés et localisés.

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).

fr: Établissements médico-sociaux (EMS)


uvres-dart-dans-lespace-public

fr: Cartographie des œuvres d'art dans l'espace public qui appartiennent au Fonds cantonal d'art contemporain (FCAC) et se trouvent sur le territoire cantonal, à l'extérieur dans l'espace urbain ou à l'intérieur de bâtiments publics. Pour plus d'informations : https://fcac.ch/ Visualiser la carte des œuvres d'art dans l'espace public ici : https://url.sitg.ge.ch/oeuvres-art

fr: Canton de Genève

fr: Office de l'urbanisme

fr: Œuvres d'art dans l'espace public

title_for_slug: uvres-dart-dans-lespace-public

soci

fr: Population et société

regi

fr: Régions et villes


fr: Le concept cantonal du sport prévoit la mise à jour régulière du recensement des infrastructures liées au sport. Dans cette optique, l'Observatoire Universitaire du Sport et des Loisirs de l'Université de Lausanne a été chargé par le DIP de mettre à jour le répertoire des installations sportives. Ces données s'adressent aux autorités cantonales (département de la cohésion sociale (DCS) - Service cantonal du sport) et communales (Service des sports des communes), mais également aux associations sportives, aux clubs sportifs et aux particuliers (pratiquants). Ainsi, chaque décideur, association ou sportif obtient une image complète du parc d'installations sportives.

fr: Service cantonal du sport

fr: geocat.ch permalien

fr: Installations sportives - Parcours mesurés

heal

fr: Santé

fr: Serveur de fichiers Opendata


installations-sportives

fr: Cette couche de données géographiques recense l'ensemble des installations sportives du canton de Genève. Elle comprend des informations détaillées sur chaque équipement sportif, qu'il s'agisse de terrains de sport, de piscines, de salles omnisports ou de tout autre infrastructure dédiée à la pratique sportive. Pour chaque installation, la couche renseigne les caractéristiques techniques (dimensions, revêtement, équipements), les conditions d'accès (transports publics, mobilité réduite, parking), les informations pratiques, ainsi que les coordonnées de contact. Cette donnée permet notamment de localiser, d'identifier et de caractériser l'offre sportive sur l'ensemble du territoire genevois.

fr: Installations sportives

title_for_slug: installations-sportives


fr: Le Canton de Genève, la Ville de Genève et l'Association des communes genevoises ont créé un organe commun de concertation, de collaboration et de coordination en matière de politique culturelle, la Conférence culturelle genevoise. Celle-ci a pour mission de mieux coordonner la vie culturelle dans le canton. Elle est notamment chargée d'évaluer la nécessité et la faisabilité de projets communs. Sur cette couche d'information figurent les salles (de spectacle, communales, de conférence, de répétition, de théâtre), les bibliothèques et médiathèques, les musées et sites archéologiques, les cinémas, les lieux d'enseignement culturel (écoles de musique et de danse) et les lieux extérieurs (scènes pour concerts d'été). Les églises, les ateliers d'artistes, les galeries privées, les aulas et bibliothèques scolaires, les centres de loisirs, les maisons de quartier, les espaces verts ou les infrastructures sportives accueillant de rares manifestations n'ont pas été retenus.

fr: Service cantonal de la culture

fr: Infrastructures culturelles

fr: CSV

fr: GDB

fr: GML

fr: KML

fr: SHP


musees

fr: Localisation des Musées, Collections, Vivariums etc..

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).

fr: Canton de Genève

fr: Direction de l'information du territoire

fr: Musées

title_for_slug: musees

soci

fr: Population et société


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

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

wsl

capacity: public

de: EnviDat

key: guid

key: uri

value: Envidat Harvester

envi

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


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

en: Sliding Deadwood Geometry Generator

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

forest-management

display_name: forest-management

mass-movements

display_name: mass-movements

natural-hazards

display_name: natural-hazards

protection-forest

display_name: protection-forest


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

en: IWET – Insect Weight Estimation Tool

title_for_slug: iwet-insect-weight-estimation-tool

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


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

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

envi

en: Environment

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


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

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: Restorative locations from participatory mapping by Swiss residents

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

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

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: {{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 v1.11.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}} 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 v1.06.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: 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}} 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: {{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/

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

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

en: High resolution global standardized drought indices

envi

en: Environment

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: 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".

format: XLS

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: 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: 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

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: 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: 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.

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

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

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:

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: 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-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: 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_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]

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

en: The Habitat Map of Switzerland v1_2 2025

envi

en: Environment

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: 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_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.

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: 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: 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

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


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

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

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


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

en: CHELSAcerra-daily

title_for_slug: chelsacerra-daily

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 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 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 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 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 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 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 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 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 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 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

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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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

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

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: 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

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)

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

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

en: Data on interaction diversity in urban gardens

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: 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: 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: 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: 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: 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: 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.

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: 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: 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

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

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: 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: 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_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: 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

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: 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

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


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

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

en: Forest Canopy Layer Code

title_for_slug: forest-canopy-layer-code

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

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

arctic

display_name: arctic

community-structure

display_name: community-structure

environmental-dna

display_name: environmental-dna

fish

display_name: fish


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 photosynthesis respiration leaf invasive-species spac-model

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

en: Acoustic Data from the PMA Bedload Monitoring System

envi

en: Environment

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 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: snow hydrology inarch modelling dischma cryosphere

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


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

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