en: atmospheric-turbulence drifting-snow blowing-snow meteorological-measurements antarctica

en: (a) Metadata

en: General and specific metadata for all files.

en: (d) Sonic data 1

en: Ultrasonic anemometer data in the period from 30 September to 11 October 2000.

en: (k) Wind speed profiles

en: Average vertical profiles of horizontal wind speed based on the ultrasonic anemometer data.

en: (l) AWS data

en: Automatic weather station data with 10-min intervals.

en: (j) Spike percentage

en: Percentage of spikes removed from the ultrasonic anemometer data per 5-min interval.

en: (c) SPC average profiles

en: Average vertical profiles of the horizontal snow mass flux, particle number size distribution, and mean and standard deviation of the particle diameter.

en: (h) Sonic data 5

en: Ultrasonic anemometer data in the period from 6 to 13 November 2000.

en: (g) Sonic data 4

en: Ultrasonic anemometer data in the period from 30 October to 6 November 2000.

en: (i) Sonic data 6

en: Ultrasonic anemometer data in the period from 13 to 18 November 2000.

en: (b) SPC time series

en: Data from the snow particle counters with 1-s intervals.

en: (m) Weather observations

en: Weather elements and phenomena observed by the Japanese Meteorological Agency.

en: (f) Sonic data 3

en: Ultrasonic anemometer data in the period from 21 to 30 October 2000.

en: (e) Sonic data 2

en: Ultrasonic anemometer data in the period from 11 to 21 October 2000.

en:
This data was collected at Mizuho Station (44.315°E, 70.71°S, 2230 m a.s.l.), East Antarctica, from **30 September to 22 November 2000** during the 41st Japanese Antarctic research expedition. Vertical profiles of the horizontal mass flux and particle number size distribution of drifting and blowing snow were measured in the lowest 10 m of the atmosphere using four **snow particle counters** (SPCs). Three 3-dimensional **ultrasonic anemometers** were deployed in the lowest 25 m of the atmosphere to record the wind velocity components and sonic temperature at a high frequency of 100 Hz. Additionally, an **automatic weather station** provided air temperature, relative humidity, air pressure, shortwave and longwave downward and upward radiation fluxes, surface temperature, snow temperatures at depths of 0.1 and 0.4 m below the surface, wind speed, and wind direction. The data is complemented by **weather observations** performed twice to eleven times per day by the Japanese Meteorological Agency.
Most of the time, the lowest SPC was situated at a height of 0.05 or 0.1 m above the snow surface. During certain periods called profile runs, the height of the lowest SPC was systematically varied between 0.02 and 0.2 m to increase the vertical resolution of the measured profiles. The other SPC's were installed at fixed heights of 1.1, 3.1, and 9.6 m. During each profile run, the lowest SPC was kept at a specific height for approximately 10 min before changing the height. If the wind speed remained approximately constant throughout a profile run, the data was used to compute the average snow-transport profile in that period. In total, 24 of such average profiles were obtained. A part of these SPC measurements are discussed in Nishimura and Nemoto (2005).
The ultrasonic anemometers were placed at heights of 0.3, 1, and 25 m. However, the height of the lowest ultrasonic anemometer was changed several times in the measurement period and ranged from 0.05 to 0.32 m. On top of that, 19 short periods (each lasting 15 to 160 min) were used to systematically vary the height of the lowest ultrasonic anemometer and thus increase the vertical resolution of the measured wind speed profile. Occasionally, drifting and blowing snow particles perturbed the ultrasonic measurement signal and electrically-charged particles caused an electric charge of the anemometers, leading to artifacts such as spikes and dropouts in the measured time series. These artifacts were largely removed and replaced by NaN, using the statistical spike removal algorithm of Mauder et al. (2013). However, the artifact removal was sometimes incomplete for the lowest anemometer because of very intense snow transport close to the surface. While temporal averages are barely affected by the artifacts, the high-frequency data of the lowest anemometer should be used carefully when computing turbulent fluxes using the eddy-covariance method. Further important explanations are provided in the file Readme.pdf in data resource '(a) Metadata'.
References
- Mauder, M., Cuntz, M., Drüe, C., Graf, A., Rebmann, C., Schmid, H.P., Schmidt, M., Steinbrecher, R. (2013). A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements. Agric For Meteorol 169:122–135. https://doi.org/10.1016/j.agrformet.2012.09.006
- Nishimura, K., Nemoto M. (2005). Blowing snow at Mizuho station, Antarctica. Phil. Trans. R. Soc. A. 363: 1647–1662. https://doi.org/10.1098/rsta.2005.1599

antarctica

display_name: antarctica

atmospheric-turbulence

display_name: atmospheric-turbulence

blowing-snow

display_name: blowing-snow

drifting-snow

display_name: drifting-snow

meteorological-measurements

display_name: meteorological-measurements

en: Profile measurements of snow transport and micrometeorology at Mizuho Station in Antarctica


rorcc

maintainer: Tobias Wechsler

title_for_slug: rorcc

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

state: active

type: dataset

en: RoRCC

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

format: XLS

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

climate-change

display_name: climate-change

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester


maintainer: Christian G. Sommer

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

en: Processing scripts

media_type: application/zip

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

format: ZIP

mimetype: application/zip

en: Kinect data

en: Links to the dataset

format: SERVICE

en: README

media_type: text/plain

en: Describes the dataset in detail

format: TXT

mimetype: text/plain

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

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

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

This dataset is the basis of the following publication:

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

kinect

display_name: kinect

snow

display_name: snow

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

wind-tunnel

display_name: wind-tunnel

en: Wind crust formation: Microsoft Kinect data


tree-ring-laser-ablation-data

maintainer: Paula Ballikaya

title_for_slug: tree-ring-laser-ablation-data

en: tree-rings dendrochronology air-pollution laser-ablation dendrochemistry

en: Laser ablation data

en:
This dataset contains the values of several chemical elements (Mg, Al, Si, S, K, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, Tl, Pb, Bi) measured in the latewood of tree rings of Mongolian oak from Harbin, China, at a 5-year resolution. Due to the lack of a suitable reference material for wood, absolute concentration was not calculated, and the ratio between the chemical element and 13C was taken as proxy for the element signal.

In Harbin, one of the largest cities and most important industrial centers in northeastern China, air quality monitoring systems were built only by the end of 2015 to meet the national requirements. Thus, dendrochemical analyses could be used as a tool to complement for the lack of air quality data over longer periods of time, allowing for the reconstruction of the temporal trend of trace metals. Our main scopes were to: (a) assess the chemical composition of Quercus mongolica Fisch. ex Ledeb. tree rings from Harbin using a recently developed system of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), (b) identify the main chemical elements which
derived from air pollution and may be used as indicators over the period 1965–2020 in Harbin, while excluding those that were controlled by physiological processes in the tree, and (c) reconstruct the history of pollution in Harbin by comparing the tree-ring chemical composition of recent decades with that of previous decades, in trees growing in the highly polluted city of Harbin and in trees growing in a control site 90 km away from major pollution sources.

Briefly, the temporal trend of some elements was influenced by physiological factors, by environmental factors such as pollution, or influenced by both. Mg, K, Zn, Cu, Ni, Pb, As, Sr and Tl showed changes in pollution levels over time.

air-pollution

display_name: air-pollution

dendrochemistry

display_name: dendrochemistry

dendrochronology

display_name: dendrochronology

laser-ablation

display_name: laser-ablation

tree-rings

display_name: tree-rings

en: Tree-ring laser ablation data


present-weather-sensor-klosters

maintainer: Maxime Hervo

title_for_slug: present-weather-sensor-klosters

en: precipitation raclets weather visibility sensor

en: Present Weather Sensor Klosters

en: Present Weather sensor measuring visibility and weather type installed at Klosters.

en: A present weather sensor (Vaisala PWD22) was deployed in Klosters (LON: 9.880413, LAT: 46.869019) for weather observation, combining the functions of a forwardscatter visibility meter and a present weather sensor. Besides measuring ambient light, it detects the intensity as well as the amount of both liquid and solid precipitation. More information can be found in the [User's Manual](ftp://ftp.cmdl.noaa.gov/aerosol/doc/manuals/PWD22_Manual.pdf).

precipitation

display_name: precipitation

raclets

display_name: raclets

sensor

display_name: sensor

visibility

display_name: visibility

weather

display_name: weather


maintainer: Rebecca Mott

en: terrestrial-laser-scanning riegl-vz6000 snow-ablation-rates patchy-snow-covers tls

en: Gletschboden test site

media_type: application/pdf

format: PDF

mimetype: application/pdf

en: Snowmask 2016

en: Snowmask 2014

en: Digital Elevation Modell 2015

en: Digital Elevation Modell 2016

en: Digital Elevation Modell 2014

en: Snowmask 2015

en: We recorded snow ablation maps with a terrestrial laser scanner (TLS, Riegl-VZ6000) at the Gletschboden area. The TLS position is located approximately 30 vertical meters above the Gletschboden area at a northerly exposed slope. In total 44 TLS measurement sets have been conducted in three consecutive years 2014-2016 (2014: 13 measurements; 2015: 17 measurements; 2016: 14 measurements). The TLS system has a single-point measurement frequency of 300 kHz and a beam divergence of 0.007°. This set-up allows a horizontal resolution of approximately 0.01 m in 100 m distance to the TLS position. One scan of the Gletschboden area lasts approximately 15 minutes. The travel time from the laser scanner towards the surface is recorded and afterwards converted into a point cloud of distances. 5 reflectors located at the Gletschboden area and in the closer surroundings were additionally scanned during each measurement to transform the point cloud from the scanner own coordinate system into Swiss coordinates. Additionally, orthophotos have been created by using pictures recorded from the TLS in order to provide snow mask maps. Snow and bare ground can be distinguished by the RGB color information of the orthophoto. Cells with blue band information greater than 175 were categorized as snow and all cells with values smaller or equal 175 were categorized as bare ground.

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

tls

display_name: tls

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: DISCHMEX - High-resolution daily snow ablation rates in an Alpine environment


maintainer: EnviDat Support

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

en: Data plot of the forest station (LAB)

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

en: Site aerial photo (Lausanne)

en: Site aerial photo from both Lausanne stations. Source: Google. 2016. Site aerial photo from both Lausanne stations. Retrieved November 11, 2016, from https://www.google.ch/maps

mimetype: image/jpeg

en: Site photo of the forest station (LAB)

en: Site photo of the fforest station from the side.

en: Field station data (LAF)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Site photo of the field station (LAF)

en: Site photo of the field station from the side.

en: Data plot of the field station (LAF)

en: Forest station data (LAB)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Lausanne in Switzerland where one station is located within a natural mixed forest stand (LAB) with European beech (_Fagus sylvatica_; 160-170 yrs), European silver fir (_Abies alba_; 160-170 yrs) and Norway spruce (_Picea abies_; 160-170 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, LAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lausanne is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

en: Lausanne, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1996 onwards


en: drought pinus-sylvestris ert drone-data irrigation

en: This .csv file contains the soil water potential data for all treatments (irrigation, irrigation-stop and control) and for the whole year of 2022. The data is given as a mean value and with an upper and lower uncertainty bound, given from the manufacturer. The depth of the sensor is given in cm, and the measured values are in units of kPa.

en: This zip file contains all raw and processed data for the electrical resistivity and drone campaigns that took place in Pfynwald, 2022

en:
This collection of datasets consists of various measurements taken during the year 2022 in Pfynwald. It combines 2 electrical resistivity transects which were monitored in May and July, before and after the irrigation season. The transects transverse all treatments (irrigation, control, irrigation stop). Each transect was repeated twice during the day for a period of 3 days to a week.
In addition there are raw and post-processed drone images (and resulting PRI maps), which were used to compare the below ground responses (from resistivity) to the above ground (crown) stress.
Here, the raw data is stored and a link to a git project is provided where python code is stored to reproduce all the results the published manuscript: "Does optimality partitioning theory fail for belowground traits? Insights from geophysical imaging of a drought-release experiment in a dry Scots Pine forest", New Phytologist, Shakas et al., 2024. The in-depth explanations from each processing step are found in the code (git project).

drone-data

display_name: drone-data

drought

display_name: drought

ert

display_name: ert

irrigation

display_name: irrigation

pinus-sylvestris

display_name: pinus-sylvestris

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Pfynwald Geoelectric Experiment 2022


en: crispr-cas field-based-protocol african-manatee environmental-dna edna threatened-species qpcr crispr-dx biodiversity-monitoring

en: Description of project and folders and files

en: File containing overview of site names and extract number (field-based or lab-based extraction). The extract_number_field_based corresponds to the identically called column in CRISPR_field_based_classifications.csv file in the data folder, as the extract_number_lab_based to the column in the file CRISPR_lab_based_classifications.csv file and the qPCR_Cp_2nd_derivative.csv file (also in the data folder). The file includes the GPS coordinates of the sampling location (transect start point).

en:
Folder containing the data files with Cp values (qPCR) and the CRISPR-Dx classifications. CRISPR_field_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection) for the African manatee (Trichechus senegalensis).
CRISPR_lab_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection).
qPCR_Cp_2nd_derivative.csv file contains the Cp value of the 8 replicates of each extract.

en:
Data associated to the publication "Rapid field-based detection of a threatened and elusive species with environmental DNA and CRISPR-Dx"

 Authors:

Flurin Leugger, Martina Lüthi, Michel Schmidlin, Zacharias Kontarakis and Loïc Pellissier

 Contact:

flurinleugger@gmail.com
loic.pellissier@usys.ethz.ch

 Project description:

We collected eDNA samples in the Conkouati-Douli National Park in the Republic of Congo in 2023 in collaboration with Beauval Nature and HELP Congo. We analyzed the samples on site in the national park using CRISPR-Dx assays to detect the African manatee (*Trichechus senegalensis*). Additionally, we transported the remaining samples (buffer) to Switzerland and used a high-sensitivity protocol with CRISPR-Dx assays and a qPCR assay to verify the field-based detections. The qPCR of Hunter et al. (2018) detects the genus manatee (Trichechus). See publication for more details (doi will be added after publication).

 Folders:

 lateral_flow_tests_images\:

Images of the lateral flow tests used to analyze the eDNA extracts in the national park. File names correspond to the site names. At each site, we took two filter replicates. We ran 8 PCRs per filter/extract and pooled two PCRs together, resulting in 4 CRISPR-Dx assays per extract. The EVE number on top of the tests indicates the environmental extract number we use to track the extracts in our data base. It corresponds to the extract_number_field_based in the metadata and data folder. The negative extraction control with the strongest "band" was placed right to the eDNA extract on each image (labelled hand written with NC x.y).

 metadata\:

File containing overview of site names and extract number (field-based or lab-based extraction). The extract_number_field_based corresponds to the identically called column in CRISPR_field_based_classifications.csv file, as the extract_number_lab_based to the column in the file CRISPR_lab_based_classifications.csv file and the qPCR_Cp_2nd_derivative.csv file. The file includes the GPS coordinates of the sampling location (transect start point).

 data\:

Folder containing the files with Cp values (qPCR) and the CRISPR-Dx classifications. CRISPR_field_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection) for the African manatee (Trichechus senegalensis).
CRISPR_lab_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection).
qPCR_Cp_2nd_derivative.csv file contains the Cp value of the 8 replicates of each extract.

african-manatee

display_name: african-manatee

biodiversity-monitoring

display_name: biodiversity-monitoring

crispr-cas

display_name: crispr-cas

crispr-dx

display_name: crispr-dx

edna

display_name: edna

environmental-dna

display_name: environmental-dna

field-based-protocol

display_name: field-based-protocol

qpcr

display_name: qpcr

threatened-species

display_name: threatened-species

en: Field-based eDNA analysis to detect the threatened and elusive African manatee


maintainer: Marcia Phillips

en: meteo-station permos permafrost ritigraben borehole

en: DATA ACCESS

en: Meterological station at the [Ritigraben permafrost borehole](http://www.envidat.ch/dataset/rit1) (RIT_0102) in canton Valais, Switzerland. The station is located at 2690 m asl on a flat site.

borehole

display_name: borehole

meteo-station

display_name: meteo-station

permafrost

display_name: permafrost

permos

display_name: permos

ritigraben

display_name: ritigraben

en: RIT2: Meteorological station at Ritigraben borehole site


en: spruce oxygen-isotopes isotopes forest ecohydrology xylem-water hydrogen-isotopes fagus-sylvatica picea-abies cryogenic-extraction critical-zone hydrology beech europe soil-water water-isotopes

en: WATSON_Canopy_Pictures (individual JPG files)

en: All canopy pictures as individual files.

en: Dataset containing information about sample weights, cryogenic water extraction and the actual hydrogen and oxygen isotope data of the study.

en: Dataset containing the information on the canopy cover.

en: Dataset containing the metadata of the sampling sites, including site-, soil-, tree-specific information.

en: All canopy pictures in one ZIP file.

en: Here, we present a comprehensive isotope dataset of soil and stem xylem water collected during two pan-European sampling campaigns in spring and summer 2023. The dataset includes samples from 40 forest sites featuring beech (Fagus sylvatica), spruce (Picea abies), or mixed beech-spruce forests, and is supplemented with detailed site-specific, soil-specific, and tree-specific metadata. Samples and metadata were collected by various researchers across Europe following a standardized protocol. Soil samples were taken at up to five depths (ranging from 0 to 90 cm), and stem xylem samples were collected from three beech and/or spruce trees at each site. All samples were sent to a single laboratory for analysis, where water was extracted using cryogenic vacuum distillation and analyzed with an isotope laser spectrometer. Additionally, a subset of the samples underwent analysis with an isotope ratio mass spectrometer. The complete description of the data can be found in a publication in Earth System Science Data (in review).

beech

display_name: beech

critical-zone

display_name: critical-zone

cryogenic-extraction

display_name: cryogenic-extraction

ecohydrology

display_name: ecohydrology

europe

display_name: europe

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

hydrogen-isotopes

display_name: hydrogen-isotopes

hydrology

display_name: hydrology

isotopes

display_name: isotopes

oxygen-isotopes

display_name: oxygen-isotopes

picea-abies

display_name: picea-abies

soil-water

display_name: soil-water

spruce

display_name: spruce

water-isotopes

display_name: water-isotopes

xylem-water

display_name: xylem-water

en: Soil and stem xylem water isotope data from two pan-European sampling campaigns


en: temperature-reconstruction wood-anatomy mxd tree-ring paleoclimate

en: This dataset contains the mean chronologies of MXD and QWA of the relict and living wood material presented in Figure 3. It also contains the JJA temperature record of the Salekhard Meteo station.

en:
This dataset contains data presented in Figure 2 in the paper "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy".

Sample ID = Sample ID
group = living or relict wood material
Bulk wood density = volumetric measured density (kg / m^3)
Mean Tree Ring Density	= Density derived via X-ray densitometry (kg / m^3)
Cellulose_to_wood ratio = Holo-cellulose-to-wood ratio
Anatomical density = Area of cell wall / (area of cell wall + lumen area)

en: Data (Quantitative Wood Anatomy, Maximum Latewood Density, Volumetric Density, holo-cellulose-to-wood-ratio) used in the manuscript "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy". Wood samples stem from Larix sibirica collected in the Yamal region, northeastern Siberia, Russia. We investigated wood properties of living trees and subfossil wood buried in riverbank sediments, dated to approximately -2760 to -2600 BCE. Our goal was to evaluate the integrity of climate proxies in sub-fossil wood and develop practical methods to detect wood degradation when reconstructing Late Holocene and Common Era climate conditions using tree-ring data.

mxd

display_name: mxd

paleoclimate

display_name: paleoclimate

temperature-reconstruction

display_name: temperature-reconstruction

tree-ring

display_name: tree-ring

wood-anatomy

display_name: wood-anatomy

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Quantitative Wood Anatomy and Maximum Latewood Density from Yamal peninsula


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

en: README

en: Describes the dataset in detail

en: Dataset

en: Links to the dataset

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

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

This dataset is the basis of the following publication:

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

antarctica

display_name: antarctica

drifting-snow

display_name: drifting-snow

mass-flux

display_name: mass-flux

meteorological-data

display_name: meteorological-data

snowmicropen

display_name: snowmicropen

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

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


en: sentinel-2 time-series tree-species switzerland remote-sensing

en: Tree species profiles for 2019, Green band

en: Tree species profiles for 2020, Green band

en: Tree species profiles for 2019, SWIR-1 band

en: Tree species profiles for 2019, NIR band

en: Tree species profiles for 2020, Red-Edge-2 band

en: Tree species profiles for 2020, Red-Edge-3 band

en: Tree species profiles for 2019, Red band

en: Tree species profiles for 2019, NDVI index

en: Tree species profiles for 2019, SWIR-2 band

en: Tree species profiles for 2020, EVI index

en: Tree species profiles for 2020, NIR band

en: Tree species profiles for 2020, Red-Edge-1 band

en: Tree species profiles for 2019, CCI index

en: Tree species profiles for 2020, CCI index

en: Tree species profiles for 2019, CIre Index

en: Tree species profiles for 2020, Blue band

en: Tree species profiles for 2019, Red-Edge-2 band

en: Tree species profiles for 2020, NDVI index

en: Tree species profiles for 2019, Red-Edge-1 band

en: Tree species profiles for 2019, Blue band

en: Tree species profiles for 2020, Red band

en: Tree species profiles for 2019, Red-Edge-3 band

en: Tree species profiles for 2019, NDMI/NDWI index

en: Tree species profiles for 2020, NDMI index

en: Tree species profiles for 2020, SWIR-1 band

en: Tree species profiles for 2019, EVI index

en: Tree species profiles for 2020, CIre index

en: Tree species profiles for 2020, SWIR-2 band

en:
 Tree species profiles from Sentinel-2 time series
We obtained tree species-specific Sentinel-2 time series for the years 2019 and 2020. The Sentinel-2 time series originated from [here](https://www.envidat.ch/#/metadata/sentinel-2-time-series-of-switzerland), and the tree species information was derived from pure plots of the Swiss National Forest Inventory, spread all over Switzerland.
In addition to the 10 and 20 m bands from Sentinel-2 (Blue, Green, Red, Red-Edge-1, Red-Edge-2, Red-Edge-3, NIR, SWIR-1, SWIR-2), we calculated indices (CCI, CIre, EVI, NDMI/NDWI, NDVI).
In total, tree species profiles of 763 pixels for 2020 and 562 pixels for 2019 are available for seven tree species (*Abies alba*, *Castanea sativa*, *Fagus sylvatica*, *Fraxinus excelsior*, *Larix* spp., *Picea abies*, *Pinus sylvestris*).

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

time-series

display_name: time-series

tree-species

display_name: tree-species


maintainer: Frank Techel

en: alps snow observations avalanches shapefile

en: Selected wet snow avalanche activity data Davos, Switzerland (2011-2014)

en: Zip archive with shapefiles for the selected wet snow avalanche polygons, including metadata.

en:
Polygons of wet snow avalanches in the Davos area, as documented by the Swiss avalanche warning service. The georeferenced outlines of the avalanches contain both the release as well as the deposit area, but without separating between both.

The dataset is a subset of the total record of 1615 avalanches classified as wet snow avalanches from October 2011 - September 2014, containing those 255 avalanches exceeding 0.0125 km^2. Every polygon comes with meta data, including the date of occurrence.

This dataset is the underlying dataset to:
Wever, N., Vera Valero, C. and Techel, F. (2018) _Coupled snow cover and avalanche dynamics simulations to evaluate wet snow avalanche activity_. Submitted to J. Geophys. Res., in review.

alps

display_name: alps

avalanches

display_name: avalanches

observations

display_name: observations

shapefile

display_name: shapefile

snow

display_name: snow

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


automatic-classification-of-avalanches

maintainer: Alec van Herwijnen

title_for_slug: automatic-classification-of-avalanches

en: seismic machine-learning avalanche monitoring localization

en:
This tar file contains classification results for two seismic geophone arrays deployed above Davos, Switzerland. The of the first array located at the Dischma Valley was used to automatically identify all seismic events produced by avalanches, whereas the classification perfomed at the second array located at the Wannengrat field site was used to identify airplanes and earthquakes.
Furthermore, this tar file also contains the median back-azimuth of all classified events at the Dischma field site.

mimetype: application/x-tar

en: This dataset contains the classification and localization results obtained during the automatic classification of avalanches during the winter season 2017.

avalanche

display_name: avalanche

localization

display_name: localization

machine-learning

display_name: machine-learning

monitoring

display_name: monitoring

seismic

display_name: seismic

en: Automatic Classification of Avalanches


maintainer: Amelie Fees

en: glide-snow-avalanche avalanche-activity avalanche snowpack-simulation time-lapse-photography

en: Glide distances for opening glide-cracks

en: This folder contains all glide-cracks where glide-distances were extracted from time-lapse photographs. Glide-distances were calculated in x-direction (width) and y-direction (downslope, length) by georeferencing the images.

en: README

en: README.txt explaining the dataset and columns of tables in more detail.

en: Glide-snow avalanche activity

en: Table that contains all glide-snow avalanche events that were detected in time-lapse photographs (season 2008/09 to 2021/22). The columns are explained in the README.txt

en: SNOWPACK simulations

en: SNOWPACK simulations (.pro and .smet) covering season 2008/09 to 2021/22 at 10 virtual locations on Dorfberg. The locations correspond to the most common glide-snow avalanche paths.

en:
This dataset includes the processed data of the glide-snow avalanche activity and dynamics on Dorfberg (Davos, Switzerland) covering seasons 2008/09 to 2021/22. This dataset was described in the research article:

Fees, A., van Herwijnen A., Altenbach, M., Lombardo, M., Schweizer, J.: Glide-snow avalanche characteristics at different time-scales extracted from time-lapse photography, Annals of Glaciology, 91

We extracted the dynamics of opening glide-cracks and the glide-snow avalanche activity from time-lapse photographs. Glide-snow avalanches were separated into surface and interface events using the liquid water content which was simulated with SNOWPACK at 10 virtual stations on Dorfberg.

avalanche-activity

display_name: avalanche-activity

glide-snow-avalanche

display_name: glide-snow-avalanche

snowpack-simulation

display_name: snowpack-simulation

time-lapse-photography

display_name: time-lapse-photography

en: Glide-snow avalanche activity on Dorfberg, Davos, Switzerland


maintainer: Nander Wever

en: snow-depth longwave-radiation shortwave-radiation precipitation-amount snow-ice-temperature air-temperature wind-direction humidity wind-speed

en: Version 7 (current)

en:
Release notes:

Bug fix: in previous versions, snow lysimeter data from September 2010 onwards was erroneously reported for UTC+2, instead of UTC+1 (i.e., reported one hour later than should have been).

Update: dataset extended to 2017-07-11T00:30.

en: Undercatch correction

en: This document describes how the undercatch correction for the Weissfluhjoch measurement site was determined.

en: Version 1

en:
Deprecated version. Release notes:

First release of dataset.

en: SNOWPACK sno file

en: This sno-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en: SNOWPACK ini file (new syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using the new MeteoIO Filter, Generator and Interpolation syntax.

en: Version 2

en:
Deprecated version. Release notes:

Bug fix: in v1, incoming radiation components were taken from WFJ_Gipfel station, instead of WFJ Versuchsfeld.

en: All versions

en: Version 5

en:
Deprecated version. Release notes:

Update: using the incoming and outgoing short- and longwave radiation data from the new processing chain from 2010 onwards, filling also data gaps in pre-2010 data.

Update: dataset extended to 2016-10-04T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 4

en:
Deprecated version. Release notes:

Update: dataset extended to 2016-09-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 3

en:
Deprecated version. Release notes:

Bug fix: in version 2, the undercatch correction was not applied correctly

Bug fix: in version 2, snow lysimeter data was missing for extended periods of time

Update: dataset extended to 2016-01-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: SNOWPACK ini file (old syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en: Version 6

en:
Deprecated version.

Release notes:

- Missing ISWR for 2009-09-30 and 2010-04-30 has been replaced by data from WFJ Gipfel

This dataset is the basis for the Weissfluhjoch dataset in ESM-SnowMIP (doi: http://dx.doi.org/10.16904/16).

en:
Dataset of meteorological and snowpack measurements from the automatic weather station at Weissfluhjoch, Davos, Switzerland, suitable for driving snowpack models. The dataset contains standard meteorological measurements, and additionally snowpack runoff data from a snow lysimeter. Where possible, data is quality checked and missing data are replaced from backup sensors from the measurement site itself, or (in only a few cases) from the MeteoSwiss weather station at 470 m distance and 150 m above the measurement site.

Publication
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M. Verification of the multi-layer SNOWPACK model with different water transport schemes. 2015. The Cryosphere. Volume 9. 2271-2293. http://dx.doi.org/10.5194/tc-9-2271-2015.

air-temperature

display_name: air-temperature

humidity

display_name: humidity

longwave-radiation

display_name: longwave-radiation

precipitation-amount

display_name: precipitation-amount

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

snow-ice-temperature

display_name: snow-ice-temperature

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: WFJ_MOD: Meteorological and snowpack measurements from Weissfluhjoch, Davos, Switzerland


maintainer: Paraskevi Georgakaki

en: swiss-alps wrf blowing-snow ice-water-content ice-crystal-number-concentration liquid-water-content jungfraujoch secondary-ice-production

en: Observational data

en:
The .zip file contains 6 .csv files including all microphysical measurements taken at the Jungfraujoch station during the two periods of interest:

* 25-28 January 2014 : northwesterly-winds (NW)
* 29 January - 1 February 2014 : southeasterly-winds (SE)

The total Ice Crystal Number Concentration (ICNC; reported in L⁻¹) is measured by the two-dimensional stereo hydrometeor spectrometer (2D-S; Lawson et al., 2006) over the size range 10-1280 μm. The total ice water content (IWC; reported in gm⁻³) is also derived by the 2D-S data using the Brown and Francis (1995) mass-diameter relationship. Finally, the quantification of the liquid water content (LWC; reported in gm⁻³) is based on the liquid droplet size distribution data derived from a DMT cloud droplet probe (CDP; Lance et al., 2010) over the size range 2-50 μm. The frequency of the measurements in the .csv files is 30 min, to match the output frequency of the model. Datetime is also reported in the files (DD/MM/YYYY h:mm) in UTC.

Acknowledgment: Collection and pre-processing of the microphysical measurements has been performed by Gary Lloyd (gary.lloyd@manchester.ac.uk). More details about the instrumentation during the CLACE2014 campaign can be found in Lloyd et al. (2015).

en: WRF outputs

en:
The .zip file contains all the NetCDF outputs produced by the mesoscale Weather Research and Forecasting (WRF) model (version: 4.0.1). Two case studies were simulated in this study, between 25-28 January 2014 (00:00 UTC) and 29 January - 1 February 2014 (00:00 UTC), respectively. The former is denoted as "NW" and the latter as "SE", owing to the prevailing wind conditions at the Jungfraujoch (JFJ) station.

The outputs come from the innermost domain of the simulations with a spatial resolution of 1 km and are extracted from the nearest to JFJ model grid point (46.55°N 7.98°E). The dimensions of each model variable is [145,100], which corresponds to time and height, respectively. The frequency of the outputs is 30 min. Note that the first 24 hours of each simulation (i.e., the first 48 outputs) were considered spin up time.

The following sets of sensitivity simulations were presented in this study:

* CNTRL_NW.nc, CNTRL_SE.nc : Sensitivity simulations performed with the default version of WRF
* DS_PHILL_NW.nc, DS_PHILL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Phillips et al. (2018)
* DS_SULL_NW.nc, DS_SULL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Sullivan et al. (2018)
* PHILL_NW.nc, PHILL_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Phillips et al. (2017)
* TAKAH_NW.nc, TAKAH_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Sullivan et al. (2018) based on Takahashi et al. (1995)
* TAKAHrim_NW.nc, TAKAHrim_SE.nc : Same set-up as before but applied only to collisions between rimed ice particles
* BIPS_Xk0_DY_NW.nc, BIPS_Xk0_DY_SE.nc : Sensitivity simulations including a source of Xk0 (either 10.0 or 100.0 L⁻¹) ice crystals with sizes of DY (either 10 or 100 μm) in the first atmospheric level of the model
* BIPS100_PHILL_NW.nc, BIPS100_PHILL_SE.nc : Sensitivity simulations where the combined effect of blowing snow and ice-ice collisional break-up is examined

en:
This repository contains all WRF model outputs and observational data sets used for the paper:
Georgakaki, P., Sotiropoulou, G., Vignon, É., Billault-Roux, A.-C., Berne, A., and Nenes, A.: Secondary ice production processes in wintertime alpine mixed-phase clouds, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-760, in review, 2021.

blowing-snow

display_name: blowing-snow

ice-crystal-number-concentration

display_name: ice-crystal-number-concentration

ice-water-content

display_name: ice-water-content

jungfraujoch

display_name: jungfraujoch

liquid-water-content

display_name: liquid-water-content

secondary-ice-production

display_name: secondary-ice-production

swiss-alps

display_name: swiss-alps

wrf

display_name: wrf

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: Data for the publication "Secondary ice production processes in wintertime alpine mixed-phase clouds"


maintainer: Andrin Caviezel

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

en: Induced Rockfall Data, Tschamut, GR

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

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

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

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

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

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

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

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

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

Further information is found in

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

dem

display_name: dem

deposition-points

display_name: deposition-points

induced-rockfall

display_name: induced-rockfall

natural-hazards

display_name: natural-hazards

rockfall

display_name: rockfall

rockfall-experiments

display_name: rockfall-experiments

rockfall-runout

display_name: rockfall-runout

sensor-stream

display_name: sensor-stream

stonenode

display_name: stonenode

stonenodedata

display_name: stonenodedata

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


snow-drift-station-flowcapt

maintainer: Benjamin Walter

title_for_slug: snow-drift-station-flowcapt

en: wind-speed flowcapt snowdrift acoustic-mass-flux snow-blowing raclets

en: avergaged mass flux

en: Average mass flux of 10 min measurement interval. The Cycle duration is 1 min which includes 6 s observation and 54 s stand-by. The time is given in UTC+1.

en: minimum wind spees

en: The data file contains the minimum wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: maximum mass flux

en: The data file contains the maximum mass flux of 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: average wind speed

en: The data file contains the average wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: maximum wind speed

en: The data file contains the maximum wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6 s observations and 54 s stand-by. The time is given in UTC+1.

en: minimum mass flux

en: The data file contains the minimum mass flux of 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: The FlowCapt is an ultra-robust instrument measuring solid particle acoustic mass - flux intensities (g m‾ ² s‾ ¹) and wind speeds (m s‾ ¹). It was deployed at Gotschnagrat (LON: 46.859 LAT: 9.849). The vertical tube with a length of 1 m monitors snowdrift and snow-blowing; and is mounted at a height between 0.1 an 1.1 m above snow surface. The time within each data set is given in UTC+1.

acoustic-mass-flux

display_name: acoustic-mass-flux

flowcapt

display_name: flowcapt

raclets

display_name: raclets

snow-blowing

display_name: snow-blowing

snowdrift

display_name: snowdrift

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Snow Drift Station - Flowcapt


de: volkswirtschaft statistische-grundlagen gemeinden verwaltung gemeindebudgets sachkonto offentliche-finanzen artenkonto funktion gemeindefinanzen

fr: Statistique des finances communales canton de Lucerne: budgets annuels

en: Municipal Finance Statistics Canton Lucerne: annual budgets

de: Gemeindefinanzstatistik Kanton Luzern: Budgets

it: Statistica finanziaria comunale cantone di Lucerna: bilanci annuali

de: Das Datenset beinhaltet die Budgetdaten der  Gemeindefinanzstatistik des Kantons Luzern seit 2020 gemäss dem HRM2-Standard. Es werden für jede Gemeinde die Funktionen, die Kontoarten und die entsprechenden Saldi ausgewiesen. Es ist der Gebietsstand des jeweiligen Jahres aufgeführt. Die Daten wurden direkt bei den Gemeinden erhoben und bilden einen Auszug aus deren Buchhaltungssystem ab. Statistische Korrekturen zwecks Gewährleistung der Konformität mit dem kantonalen Kontenrahmen wurden in Einzelfällen vorgenommen.

en: The dataset contains the budget data of the Municipal Finance Statistics of the Canton Lucerne since 2020 in accordance with the HRM2 standard. The table shows the cost centers or the cost units, the account types and the corresponding account balances for each municipality. The territorial status of the respective year is disclosed. The data was collected directly from the municipalities and represents an extract of their accounting system. Statistical corrections were made in exceptional cases to ensure conformity with the cantonal chart of accounts.

artenkonto

display_name: artenkonto

funktion

display_name: funktion

gemeindebudgets

display_name: gemeindebudgets

gemeindefinanzen

display_name: gemeindefinanzen

gemeinden

display_name: gemeinden

offentliche-finanzen

display_name: offentliche-finanzen

sachkonto

display_name: sachkonto

statistische-grundlagen

display_name: statistische-grundlagen

verwaltung

display_name: verwaltung

volkswirtschaft

display_name: volkswirtschaft

spatial: Kanton Luzern

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

lustat

fr: LUSTAT statistique Lucerne

de: LUSTAT Statistik Luzern

en: LUSTAT Statistics Lucerne

it: LUSTAT statistica Lucerna

fr:
LUSTAT statistique Lucerne est le centre de compétences et de services pour la statistique publique du canton de Lucerne. Avec ses informations statistiques objectives, LUSTAT accompagne les processus de formation d'opinion et de prise de décision dans la politique, l'administration, la société et les affaires.
LUSTAT statistique Lucerne publie ici progressivement des jeux de données appropriées de la statistique cantonale sous forme de données OGD.

en:
LUSTAT Statistics Lucerne is the competence and service center for public statistics in the Canton of Lucerne. With its objective statistical information, LUSTAT accompanies opinion-forming and decision-making processes in politics, administration, society and business.
LUSTAT Statistics Lucerne is gradually publishing here suitable datasets from the cantonal statistics as OGD data.

de:
LUSTAT Statistik Luzern ist das Kompetenz- und Dienstleistungszentrum der öffentlichen Statistik im Kanton Luzern. Mit ihren objektiven statistischen Informationen begleitet LUSTAT Meinungsbildungs- und Entscheidungsprozesse in Politik, Verwaltung, Gesellschaft und Wirtschaft.
LUSTAT Statistik Luzern veröffentlicht hier schrittweise geeignete Datensammlungen der kantonalen Statistik als OGD-Daten.

it:
LUSTAT statistica Lucerna è il centro di competenza e servizi per la statistica pubblica nel cantone di Lucerna. Con le sue informazioni statistiche oggettive, LUSTAT accompagna i processi di formazione delle opinioni e decisionali in politica, amministrazione, società e affari.
LUSTAT statistica Lucerna sta gradualmente pubblicando qui oportuni set di dati della statistica cantonale come dati OGD.

political_level: canton

value: I14Y DCAT Harvester LUSTAT


de: volkswirtschaft funktion gemeinderechnungen verwaltung gemeinden statistische-grundlagen artenkonto offentliche-finanzen sachkonto gemeindefinanzen finanzkennzahlen

de: Jahresrechnungen Erfolgsrechnung: Aufwand und Ertrag (Kontofuntktion und Kontoart)

de:
Erfolgsrechnungsdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis dreistufiger Kontofunktion kombiniert mit zwei- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Aufwand nach einstufiger Kontofunktion und zweistufiger Kontoart
- Ertrag nach einstufiger Kontofunktion und zweistufiger Kontoart
- Aufwand nach einstufiger Kontofunktion und dreistufiger Kontoart
- Ertrag nach einstufiger Kontofunktion und dreistufiger Kontoart
- Aufwand nach einstufiger Kontofunktion und vierstufiger Kontoart
- Ertrag nach einstufiger Kontofunktion und vierstufiger Kontoart
- Aufwand nach zweistufiger Kontofunktion und zweistufiger Kontoart
- Ertrag nach zweistufiger Kontofunktion und zweistufiger Kontoart
- Aufwand nach zweistufiger Kontofunktion und dreistufiger Kontoart
- Ertrag nach zweistufiger Kontofunktion und dreistufiger Kontoart
- Aufwand nach zweistufiger Kontofunktion und vierstufiger Kontoart
- Ertrag nach zweistufiger Kontofunktion und vierstufiger Kontoart
- Aufwand nach dreistufiger Kontofunktion und zweistufiger Kontoart
- Ertrag nach dreistufiger Kontofunktion und zweistufiger Kontoart
- Aufwand nach dreistufiger Kontofunktion und dreistufiger Kontoart
- Ertrag nach dreistufiger Kontofunktion und dreistufiger Kontoart
- Aufwand nach dreistufiger Kontofunktion und vierstufiger Kontoart
- Ertrag nach dreistufiger Kontofunktion und vierstufiger Kontoart

identifier: gefis-lu-jr-er-fkt-art

de: Jahresrechnungen Erfolgsrechnung: Aufwand, Ertrag und Nettoaufwand (funktionelle Gliederung)

de:
Erfolgsrechnungsdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis dreistufiger Kontofunktion. Datensammlung umfasst folgende Arbeitsblätter:
- Aufwand nach einstufiger Kontofunktion
- Ertrag nach einstufiger Kontofunktion
- Nettoaufwand nach einstufiger Kontofunktion
- Aufwand nach zweistufiger Kontofunktion
- Ertrag nach zweistufiger Kontofunktion
- Nettoaufwand nach zweistufiger Kontofunktion
- Aufwand nach dreistufiger Kontofunktion
- Ertrag nach dreistufiger Kontofunktion
- Nettoaufwand nach dreistufiger Kontofunktion

identifier: gefis-lu-jr-er-fkt

de: Jahresrechnungen Investitionsrechnung: Investitionsausgaben und Investitionseinnahmen (Kontofuntktion und Kontoart)

de:
Investitionsrechnungsdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis dreistufiger Kontofunktion kombiniert mit zwei- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Investitionsausgaben nach einstufiger Kontofunktion und zweistufiger Kontoart
- Investitionseinnahmen nach einstufiger Kontofunktion und zweistufiger Kontoart
- Investitionsausgaben nach einstufiger Kontofunktion und dreistufiger Kontoart
- Investitionseinnahmen nach einstufiger Kontofunktion und dreistufiger Kontoart
- Investitionsausgaben nach einstufiger Kontofunktion und vierstufiger Kontoart
- Investitionseinnahmen nach einstufiger Kontofunktion und vierstufiger Kontoart
- Investitionsausgaben nach zweistufiger Kontofunktion und zweistufiger Kontoart
- Investitionseinnahmen nach zweistufiger Kontofunktion und zweistufiger Kontoart
- Investitionsausgaben nach zweistufiger Kontofunktion und dreistufiger Kontoart
- Investitionseinnahmen nach zweistufiger Kontofunktion und dreistufiger Kontoart
- Investitionsausgaben nach zweistufiger Kontofunktion und vierstufiger Kontoart
- Investitionseinnahmen nach zweistufiger Kontofunktion und vierstufiger Kontoart
- Investitionsausgaben nach dreistufiger Kontofunktion und zweistufiger Kontoart
- Investitionseinnahmen nach dreistufiger Kontofunktion und zweistufiger Kontoart
- Investitionsausgaben nach dreistufiger Kontofunktion und dreistufiger Kontoart
- Investitionseinnahmen nach dreistufiger Kontofunktion und dreistufiger Kontoart
- Investitionsausgaben nach dreistufiger Kontofunktion und vierstufiger Kontoart
- Investitionseinnahmen nach dreistufiger Kontofunktion und vierstufiger Kontoart

identifier: gefis-lu-jr-ir-fkt-art

de: Jahresrechnungen Investitionsrechnung: Investitionsausgaben, Investitionseinnahmen und Nettoinvestitionen (funktionelle Gliederung)

de:
Investitionsrechnungsdaten  der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis dreistufiger Kontofunktion. Datensammlung umfasst folgende Arbeitsblätter:
- Investitionsausgaben nach einstufiger Kontofunktion
- Investitionseinnahmen nach einstufiger Kontofunktion
- Nettoinvestitionen nach einstufiger Kontofunktion
- Investitionsausgaben nach zweistufiger Kontofunktion
- Investitionseinnahmen nach zweistufiger Kontofunktion
- Nettoinvestitionen nach zweistufiger Kontofunktion
- Investitionsausgaben nach dreistufiger Kontofunktion
- Investitionseinnahmen nach dreistufiger Kontofunktion
- Nettoinvestitionen nach dreistufiger Kontofunktion

identifier: gefis-lu-jr-ir-fkt

de: Jahresrechnungen Erfolgsrechnung: Aufwand und Ertrag (Artengliederung)

de:
Erfolgsrechnungsdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Aufwand nach einstufiger Art
- Ertrag nach einstufiger Art
- Aufwand nach zweistufiger Art
- Ertrag nach zweistufiger Art
- Aufwand nach dreistufiger Art
- Ertrag nach dreistufiger Art
- Aufwand nach vierstufiger Art
- Ertrag nach vierstufiger Art

identifier: gefis-lu-jr-er-art

de: Jahresrechnungen Investitionsrechnung: Investitionsausgaben und Investitionseinnahmen (Artengliederung)

de:
Investitionsrechnungsdaten der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Investitionsausgaben nach einstufiger Art
- Investitionseinnahmen nach einstufiger Art
- Investitionsausgaben nach zweistufiger Art
- Investitionseinnahmen nach zweistufiger Art
- Investitionsausgaben nach dreistufiger Art
- Investitionseinnahmen nach dreistufiger Art
- Investitionsausgaben nach vierstufiger Art
- Investitionseinnahmen nach vierstufiger Art

identifier: gefis-lu-jr-ir-art

de: Jahresrechnungen Bilanz: Aktiven und Passiven (Artengliederung)

de:
Bilanzdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Aktiven nach einstufiger Art
- Passiven nach einstufiger Art
- Aktiven nach zweistufiger Art
- Passiven nach zweistufiger Art
- Aktiven nach dreistufiger Art
- Passiven nach dreistufiger Art
- Aktiven nach vierstufiger Art
- Passiven nach vierstufiger Art

identifier: lustat-gefis-lu-jr-bl-art

de: Jahresrechnungen: Bilanz, Erfolgsrechnung und Investitionsrechnung (Kontofunktion und Kontoart)

de: Daten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern im höchsten Detaillierungsgrad der Kontofunktion und Kontoart (aggregiert auf Minimalvorgabe vom Kanton: Stufen 3 oder 4 bei Kontofunktion und Stufen 4, 5 oder 6 bei Kontoart)

identifier: lustat-gefis-lu-jr

de: Das Datenset beinhaltet die Jahresrechnungen der  Gemeindefinanzstatistik des Kantons Luzern seit 2019 gemäss dem HRM2-Standard. Es werden für jede Gemeinde die Funktionen, die Kontoarten und die entsprechenden Saldi ausgewiesen. Es ist der Gebietsstand des jeweiligen Jahres aufgeführt. Die Daten wurden direkt bei den Gemeinden erhoben und bilden einen Auszug aus deren Buchhaltungssystem ab. Statistische Korrekturen zwecks Gewährleistung der Konformität mit dem kantonalen Kontenrahmen wurden in Einzelfällen vorgenommen.

en: The dataset contains the annual accounts of the Municipal Finance Statistics of the Canton Lucerne since 2019 in accordance with the HRM2 standard. The table shows the cost centers or the cost units, the account types and the corresponding account balances for each municipality. The territorial status of the respective year is disclosed. The data was collected directly from the municipalities and represents an extract of their accounting system. Statistical corrections were made in exceptional cases to ensure conformity with the cantonal chart of accounts.

finanzkennzahlen

display_name: finanzkennzahlen

gemeinderechnungen

display_name: gemeinderechnungen

fr: Statistique des finances communales canton de Lucerne: comptes annuels

de: Gemeindefinanzstatistik Kanton Luzern: Jahresrechnungen

en: Municipal Finance Statistics Canton Lucerne: annual accounts

it: Statistica finanziaria comunale cantone di Lucerna: conti annuali


de: offentliche-finanzen statistische-grundlagen ressourcenausgleich gemeinden gemeindefinanzen volkswirtschaft lastenausgleich finanzausgleich verwaltung

fr: Compensation des charges dues à des facteurs socio-démographiques

en: Socio-demographic cost compensation

de: Soziallastenausgleich

de: Die Datensätze enthalten alle Kennzahlen seit 2020, die für die Berechnung der fünf Ausgleichsgefässe des kantonalen Finanzausgleichs des Kantons Luzern gemäss Finanzausgleichsgesetz und -verordnung erforderlich sind. Die Verrechnung der Kennzahlen zu Indikatoren und die Verteilung der Mittel wird in den Anhängen der Finanzausgleichsverordnung detailliert beschrieben. Die Kennzahlen stammen aus verschiedenen Datenquellen, die zum Teil in der Verordnung explizit genannt werden.

fr: Compensation des charges d'infrastructure

de: Infrastrukturlastenausgleich

en: Infrastructure load compensation

identifier: lustat-fa-lu-ila

fr: Compensation des charges de l'éducation

de: Bildungslastenausgleich

en: Equalisation of educational burdens

it: Perequazione degli oneri educativi

identifier: lustat-fa-lu-bla

fr: Compensation des charges dues à des facteurs géo-topographiques

en: Topographic cost compensation

de: Topografischer Lastenausgleich

identifier: lustat-fa-lu-tla

fr: Péréquation des ressources

de: Ressourcenausgleich

en: Equalisation of resources

it: Perequazione delle risorse

identifier: lustat-fa-lu-ra

fr: Les jeux de données contiennent tous les indicateurs depuis 2020 nécessaires au calcul des cinq enveloppes de péréquation de la péréquation financière cantonale du canton de Lucerne, conformément à la loi et à l'ordonnance sur la péréquation financière. L'imputation des chiffres clés aux indicateurs et la répartition des moyens sont décrites en détail dans les annexes de l'ordonnance sur la péréquation financière. Les indicateurs proviennent de différentes sources de données, dont certaines sont explicitement mentionnées dans l'ordonnance.

en: The data sets contain all key figures since 2020 that are required for the calculation of the fiscal equalization and cost compensation of the Canton of Lucerne in accordance with the Financial Equalization Act and Ordinance. The calculation of the indicators based on the key figures and the distribution of the funds is described in detail in the annexes to the Fiscal Equalization Ordinance. The key figures come from various data sources, some of which are explicitly mentioned in the ordinance.

finanzausgleich

display_name: finanzausgleich

lastenausgleich

display_name: lastenausgleich

ressourcenausgleich

display_name: ressourcenausgleich

gove

de: Regierung und öffentlicher Sektor

econ

de: Wirtschaft und Finanzen

lustat

de: LUSTAT Statistik Luzern

de:
LUSTAT Statistik Luzern ist das Kompetenz- und Dienstleistungszentrum der öffentlichen Statistik im Kanton Luzern. Mit ihren objektiven statistischen Informationen begleitet LUSTAT Meinungsbildungs- und Entscheidungsprozesse in Politik, Verwaltung, Gesellschaft und Wirtschaft.
LUSTAT Statistik Luzern veröffentlicht hier schrittweise geeignete Datensammlungen der kantonalen Statistik als OGD-Daten.

fr: Péréquation financière canton de Lucerne

en: Financial equalization canton of Lucerne

it: Perequazione comunale del cantone di Lucerna


de: kandidierende kommunale-wahlen wahlen gewahlte gemeinderatswahlen politik

fr: Élections communales canton de Lucerne de 2020

de: Gemeinderatswahlen Kanton Luzern seit 2020

en: Municipal council elections Canton Lucerne since 2020

it: Elezioni del consiglio comunale cantone di Lucerna dal 2020

de: Kandidierende und Gewählte bei den Gemeinderatswahlen seit 2020 im Kanton Luzern

identifier: lustat-grwahlen-lu

gemeinderatswahlen

display_name: gemeinderatswahlen

gewahlte

display_name: gewahlte

kandidierende

display_name: kandidierende

kommunale-wahlen

display_name: kommunale-wahlen

politik

display_name: politik

wahlen

display_name: wahlen


de: befragung lebensbedingungen lebensqualitat subjektive-lebensbedingungen bevolkerung

en: population subjective-living-conditions survey living-conditions quality-of-life

de: Grundgesamtheit

en: Universe

identifier: bbf-lu-grundgesamtheit

de: Antworten zu den Fragen

en: Answers to the questions

identifier: bbf-lu-antworten

de:
Die Datensammlung zur Bevölkerungsbefragung Kanton Luzern 2023 besteht aus zwei Distributionen/Ressourcen:
- Individualdaten mit den Antworten zu den Fragen (bbf-lu-antworten.csv)
- Angaben zur Grundgesamtheit der gewichtungsrelevanten Variablen für die Endlichkeitskorrektur (bbf-lu-grundgesamtheit.csv)

en:
The data set for the population survey Canton of Lucerne 2023 consists of two distributions/resources:
- Individual data with the answers to the questions (bbf-lu-antworten.csv)
- Information on the population of the weighting-relevant variables for the finiteness correction (bbf-lu-grundgesamtheit.csv)

befragung

display_name: befragung

bevolkerung

display_name: bevolkerung

lebensbedingungen

display_name: lebensbedingungen

lebensqualitat

display_name: lebensqualitat

living-conditions

display_name: living-conditions

population

display_name: population

quality-of-life

display_name: quality-of-life

subjective-living-conditions

display_name: subjective-living-conditions

subjektive-lebensbedingungen

display_name: subjektive-lebensbedingungen

survey

display_name: survey

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

en: Population survey Canton of Lucerne 2023


de: bevolkerungsentwicklung bevolkerung bevolkerungsszenarien wachstum gemeinden bevolkerungswachstum

fr: Scénario haut 2023 - 2050

de: Hohes Szenario 2023 - 2050

en: High scenario 2023 - 2050

it: Scenario alto 2023 - 2050

fr: Le scénario haut combine des hypothèses favorables à la croissance démographique et économique. La croissance démographique est donc estimée plus élevée que dans le scénario de référence.

de: Beim hohen Szenario werden Hypothesen kombiniert, die das Bevölkerungs- und Wirtschaftswachstum begünstigen.

en: The high scenario combines hypotheses that favor population and economic growth. Population growth is therefore estimated to be higher than in the reference scenario.

it: Lo scenario alto combina ipotesi che favoriscono la popolazione e la crescita economica. La crescita della popolazione è quindi stimata superiore a quella dello scenario di riferimento.

fr: Scénario bas 2023 - 2050

en: Low scenario 2023 - 2050

de: Tiefes Szenario 2023 - 2050

it: Scenario basso 2023 - 2050

fr: Le scénario bas repose sur des hypothèses qui orientent moins le niveau d'instruction et la croissance économique, réduisant ainsi la croissance démographique par rapport au scénario de référence.

de: Das tiefe Szenario basiert auf Hypothesen, welche das Bildungsniveau und das Wirtschaftswachstum weniger vorantreiben und somit das Bevölkerungswachstum im Vergleich zum Referenzszenario mindern.

en: The low scenario is based on hypotheses that drive educational attainment and economic growth less, thus reducing population growth compared to the reference scenario.

it: Lo scenario basso si basa su ipotesi che spingono meno il livello di istruzione e la crescita economica, riducendo così la crescita della popolazione rispetto allo scenario di riferimento.

fr: Scénario moyen (référence) 2023 - 2050

de: Mittleres Szenario (Referenz) 2023 - 2050

en: Medium scenario (reference) 2023 - 2050

it: Scenario medio (riferimento) 2023 - 2050

fr: Le scénario moyen (scénario de référence) tient compte des hypothèses du modèle qui extrapolent les évolutions démographiques des dernières décennies. Dans la perspective actuelle, il représente un cours probable.

en: The medium scenario (reference scenario) takes into account model assumptions that extrapolate the demographic developments of the last decades. It represents a probable course – from the current perspective.

de: Das mittlere Szenario (Referenzszenario) berücksichtigt Modellannahmen, welche die demografischen Entwicklungen der letzten Jahrzehnte fortschreiben. Es stellt dabei einen – aus gegenwärtiger Sicht – wahrscheinlichen Verlauf dar.

it: Lo scenario medio (scenario di riferimento) tiene conto delle ipotesi del modello che estrapolano gli sviluppi demografici degli ultimi decenni. Dal punto di vista attuale, rappresenta un corso probabile.

fr: Les scénarios de population LUSTAT pour le canton de Lucerne sont des modèles de calcul qui extrapolent l'évolution de la population résidente permanente au niveau communal. Trois variantes ont été calculées pour chaque scénario, qui diffèrent par les hypothèses sous-jacentes. Ils tiennent compte des hypothèses des modèles qui sont basées sur les tendances démographiques et socio-économiques des dernières décennies. L'année de calcul des chiffres clés sur lesquels se basent les calculs correspond à l'année 2023. Les scénarios partent de la population résidente permanente au 31 décembre 2022 et, en outre, aux personnes bénéficiant d'un statut de protection S.

de: Die LUSTAT-Bevölkerungsszenarien für den Kanton Luzern sind Modellberechnungen, welche die Entwicklung der ständigen Wohnbevölkerung auf kommunaler Ebene fortschreiben. Für die Szenarien wurden jeweils drei Varianten berechnet, welche sich in den zugrundeliegenden Hypothesen unterscheiden. Sie berücksichtigen Modellannahmen, welche auf demografischen und sozioökonomischen Trends der letzten Jahrzehnte beruhen. Das Berechnungsjahr der, bei den Berechnungen zugrundeliegenden, Kennziffern entspricht dem Jahr 2023. Als Anfangsbestand dient den Szenarien die ständige Wohnbevölkerung per 31.12.2022 plus die Personen mit Schutzstatus S.

en: The LUSTAT population scenarios for the canton of Lucerne are model calculations that extrapolate the development of the permanent resident population at the municipal level. Three variants were calculated for each scenario, which differ in the underlying hypotheses. They take into account model assumptions based on demographic and socioeconomic trends of recent decades. The year of calculation of the key figures on which the calculations are based on corresponds to the year 2023. The permanent resident population as of 31.12.2022 and additionally persons with protection status S is used as the initial stock for the scenarios.

it: Gli scenari demografici LUSTAT per il Cantone di Lucerna sono modelli di calcolo che estrapolano l'evoluzione della popolazione residente permanente a livello comunale. Per ogni scenario sono state calcolate tre varianti, che si differenziano per le ipotesi sottostanti. Prendono in considerazione le ipotesi del modello che si basano sulle tendenze demografiche e socioeconomiche degli ultimi decenni. L'anno di calcolo per le cifre chiave su cui si basano i calcoli corrisponde all'anno 2023. Gli scenari iniziano con la popolazione residente permanente al 31 dicembre 2022 e inoltre le persone con status di protezione S.

bevolkerungsentwicklung

display_name: bevolkerungsentwicklung

bevolkerungsszenarien

display_name: bevolkerungsszenarien

bevolkerungswachstum

display_name: bevolkerungswachstum

gemeinden

display_name: gemeinden

wachstum

display_name: wachstum

lustat

en: LUSTAT Statistics Lucerne

en:
LUSTAT Statistics Lucerne is the competence and service center for public statistics in the Canton of Lucerne. With its objective statistical information, LUSTAT accompanies opinion-forming and decision-making processes in politics, administration, society and business.
LUSTAT Statistics Lucerne is gradually publishing here suitable datasets from the cantonal statistics as OGD data.

fr: Scénarios d’évolution démographique des communes du canton de lucerne

de: Szenarien zur Bevölkerungsentwicklung der Luzerner Gemeinden

en: Scenarios for population development of the communes of Canton Lucerne

it: Scenari per l'evoluzione demografica per comune di cantone di Lucerna


name: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

label: BAG-OFSP-UFSP-FOPH Website

fr: Covid-19 - surveillance génomique

de: Covid-19 - Genomische Überwachung

en: Covid-19 - genomic surveillance

it: Covid-19 - monitoraggio genomico

fr: Les données se fondent sur les informations tirées du Programme national de surveillance génomique du SARS-CoV-2, auquel participent, à l’heure actuelle, des laboratoires des hôpitaux universitaires et de grands hôpitaux régionaux de Suisse, ainsi qu’une plateforme de séquençage.

en: The data are based on information from the national genomic SARS-CoV-2 surveillance programme. Currently participating in the programme are laboratories of the university hospitals and larger regional hospitals in Switzerland, as well as a sequencing platform.

de: Die Daten basieren auf Informationen aus dem nationalen genomischen SARS-CoV-2 Überwachungsprogramm. An diesem beteiligen sich aktuell Laboratorien der Universitätsspitäler und grösserer Regionalspitäler der Schweiz sowie eine Sequenzierungsplattform.

it: I dati si basano sulle informazioni ricavate dal programma nazionale di sorveglianza genomica del SARS-CoV-2, al quale attualmente aderiscono i laboratori degli ospedali universitari e dei maggiori ospedali regionali della Svizzera, nonché una piattaforma di sequenziamento.

fr: Virus respiratoire - Monitorage des eaux usées

en: Respiratory viruses - wastewater monitoring

de: Respiratorische Viren - Abwassermonitoring

it: Virus respiratori - Monitoraggio delle acque reflue

fr: Die Daten basieren auf Informationen aus dem nationalen Abwassermonitoring der Schweiz und des Fürstentums Liechtenstein. Dieses Monitoring erfasst seit Januar 2022 die Viruslast von SARS-CoV-2 und seit Juli 2023 die Viruslast von Influenza und RSV in Abwasserproben der teilnehmenden Abwasserreinigungsanlagen (ARA).

fr: Covid-19 - Système de déclaration obligatoire

de: Covid-19 - Obligatorisches Meldesystem

en: Covid-19 - mandatory reporting system

it: Covid-19 - Sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires, les médecins et les hôpitaux ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

de: Die Daten basieren auf Informationen, die Laboratorien, Ärztinnen und Ärzte sowie Spitäler dem BAG im Rahmen der Meldepflicht übermittelt haben.

en: The data are based on information that laboratories, doctors and hospitals have submitted to the FOPH under the mandatory reporting requirement.

it: I dati si basano su informazioni comunicate dai laboratori, dai medici e dagli ospedali all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

fr: Covid-19 - Sentinella

de: Covid-19 - Sentinella

en: Covid-19 - sentinella

it: Covid-19 - Sentinella

fr: Les données se fondent sur les informations recueillies par le système Sentinella. Dans le cadre de ce système de déclaration, les médecins transmettent depuis mars 2020 des informations sur les premières consultations de patients présentant une infection respiratoire aiguë dans leur cabinet ou lors de visites à domicile.

en: The data are based on information from the Swiss Sentinel Surveillance Network (SSSN, Sentinella) monitoring system. Since March 2020, the system has been used by doctors working on an outpatient basis to submit information on initial consultations in medical practices and during home visits for patients with acute respiratory infections (ARIs).

de: Die Daten basieren auf Informationen aus dem Sentinella-Meldesystem. Im Rahmen dieses Meldesystems übermitteln ambulant tätige Ärztinnen und Ärzte seit März 2020 Informationen zu Erstkonsultationen von Patientinnen und Patienten mit akuter respiratorischer Infektion (ARI) in Arztpraxen und bei Hausbesuchen.

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Nel quadro di questo sistema di dichiarazione, dal marzo 2020 i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano un’infezione respiratoria acuta (acute respiratory infection, ARI).

fr: Virus respiratoire - Sentinella

de: Respiratorische Viren - Sentinella

en: Respiratory viruses - sentinella

it: Virus respiratori - Sentinella

fr: Les données se fondent sur les informations recueillies par le système de déclaration Sentinella. Dans le cadre de ce système, les médecins transmettent des informations sur les premières consultations en raison d’une infection respiratoire aiguë (ARI) ou d’une affection grippale (ILI) dans leurs cabinets ou lors de visites à domicile.

de: Die Daten basieren auf Informationen aus dem Sentinella-Meldesystem. Im Rahmen dieses Meldesystems übermitteln ambulant tätige Ärztinnen und Ärzte Informationen zu Erstkonsultationen aufgrund akuter respiratorischer Infektion (ARI) oder grippeähnlicher Erkrankung (ILI) in Arztpraxen und bei Hausbesuchen.

en: The data are based on information from the Swiss Sentinel Surveillance Network (SSSN, Sentinella) monitoring system. Within the framework of this reporting system, outpatient doctors send information on initial consultations due to acute respiratory infection (ARI) or influenza-like illness (ILI) in medical practices and during home visits.

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Nel quadro di questo sistema di dichiarazione, i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano un’infezione respiratoria acuta (acute respiratory infection, ARI) o una sindrome simil-influenzale (influenza-like illness, ILI).

fr: SARS-CoV-2 (Covid-19) - monitorage des variants dans les eaux usées

en: SARS-CoV-2 (Covid-19) -  monitoring of variants in wastewater

de: SARS-CoV-2 (Covid-19) - Virusvarianten im Abwasser

it: SARS-CoV-2 (Covid-19) - monitoraggio delle varianti nelle acque reflue

fr: Les données se fondent sur les informations issues du monitorage des variants dans les eaux usées de la Suisse. Ce monitorage enregistre la répartition des variants celle du SARS-CoV-2 dans des échantillons des stations d’épuration des eaux usées (STEP) participantes depuis février 2021.

de: Die Daten basieren auf Informationen aus dem Variantenmonitoring im Abwasser der Schweiz . Dieses Monitoring erfasst seit Februar 2021 die Verteilung der Virusvarianten von SARS-CoV-2 in Abwasserproben der teilnehmenden Abwasserreinigungsanlagen (ARA).

en: The data are based on information from the monitoring programme of variants in wastewater of Switzerland. This monitoring programme has been recording the distribution of variants of SARS-CoV-2 since February 2021 in wastewater samples from participating wastewater treatment plants (WWTPs).

it: I dati pubblicati di seguito si basano sulle informazioni ricavate dalmonitoraggio delle varianti nelle acque reflue della Svizzera. Questo monitoraggio registra la distribuzione delle varianti del SARS-CoV-2 dal febbraio 2021 nei campioni di acque reflue degli impianti di depurazione delle acque reflue (IDA) partecipanti.

fr: Données concernant la propagation et l’évolution temporelle des infections au SARS-CoV-2 et des cas de COVID-19 en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur la charge virale dans les eaux usées provenant du monitorage correspondant, sur les consultations ambulatoires provenant du système de déclaration Sentinella, sur les variantes de virus provenant de la surveillance génomique et sur sur les cas, hospitalisations, décès et tests provenant du système de déclaration obligatoire.

en: Data on the spread and development of SARS-CoV-2 infections and Covid-19 cases in Switzerland and the Principality of Liechtenstein. You will find data of the viral load in wastewater from the wastewater monitoring system, of outpatient consultations from the Sentinella reporting system, of virus variants from the genomic surveillance system and of cases, hospitalisations, deaths and tests from the obligatory reporting system.

de: Daten zur Verbreitung und zeitlichen Entwicklung von SARS-CoV-2 Infektionen und Covid-19 Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zur Viruslast im Abwasser aus dem Abwassermonitoring, zu ambulanten Konsultationen aus dem Sentinella-Meldesystem, zu Virusvarianten aus der genomischen Überwachung und zu Fällen, Hospitalisationen, Todesfällen und Tests aus dem obligatorischen Meldesystem.

it: Dati della diffusione e dell’evoluzione temporale delle infezioni da SARS-CoV-2 e dei casi di COVID-19 in Svizzera e nel Principato del Liechtenstein. Qui trovate dati della carica virale nelle acque reflue basate sul sistema di monitoraggio delle acque reflue, dati delle consultazioni ambulatoriali basate sul sistema di dichiarazione Sentinella, dati delle varianti del virus basate sul sistema di sorveglianza genomica e dati di casi, ospedalizzazioni, decessi e test basate sul sistema di dichiarazione obbligatoria.

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

abteilung-uebertragbare-krankheiten

fr: Division Maladies transmissibles

de: Abteilung Übertragbare Krankheiten

en: Communicable Diseases Division

it: Divisione Malattie trasmissibili

fr: Les maladies transmissibles constituent une menace pour la santé publique. La division les surveille, publie régulièrement des rapports sur la situation épidémiologique, définit des stratégies de prévention et de contrôle, et les met en œuvre.

en: Communicable diseases pose a risk to public health. The division monitors these diseases, publishing regular reports on the epidemiological situation, laying down and implementing prevention and control strategies.

de: Übertragbare Krankheiten gefährden die öffentliche Gesundheit. Die Abteilung überwacht diese Krankheiten, publiziert regelmässig Berichte zur epidemiologischen Situation, legt Präventions- und Kontrollstrategien fest und setzt sie um.

it: Le malattie trasmissibili mettono in pericolo la salute pubblica. La divisione Malattie trasmissibili le monitora, pubblica regolarmente rapporti sulla situazione epidemiologica, stabilisce strategie di prevenzione e di controllo e le attua.

political_level: confederation

value: DCAT-BAG-IDD Harvester

fr: SARS-CoV-2 (Covid-19)

en: SARS-CoV-2 (Covid-19)

de: SARS-CoV-2 (Covid-19)

it: SARS-CoV-2 (Covid-19)


fr: Salmonellose - système de déclaration obligatoire

de: Salmonellose - Obligatorisches Meldesystem

en: Salmonellosis - mandatory reporting system

it: Salmonellosi - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle des cas de salmonellose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

en: Data on the spread and development of salmonellosis infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Salmonellose Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

it: Dati della diffusione e dell’evoluzione temporale dei casi di salmonellosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

salmonellose-bag

display_name: salmonellose-bag

salmonellose-ofsp

display_name: salmonellose-ofsp

salmonellosi-ufsp

display_name: salmonellosi-ufsp

salmonellosis-foph

display_name: salmonellosis-foph

fr: Salmonellose

en: Salmonellosis

de: Salmonellose

it: Salmonellosi


fr: Virus respiratoire - Monitorage des eaux usées

en: Respiratory viruses - wastewater monitoring

de: Respiratorische Viren - Abwassermonitoring

it: Virus respiratori - Monitoraggio delle acque reflue

fr: Die Daten basieren auf Informationen aus dem nationalen Abwassermonitoring der Schweiz und des Fürstentums Liechtenstein. Dieses Monitoring erfasst seit Januar 2022 die Viruslast von SARS-CoV-2 und seit Juli 2023 die Viruslast von Influenza und RSV in Abwasserproben der teilnehmenden Abwasserreinigungsanlagen (ARA).

fr: Données concernant la propagation et l’évolution temporelle des infections virales respiratoires et des cas de maladies respiratoires en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les consultations ambulatoires provenant du système de déclaration Sentinella et sur la charge virale dans les eaux usées provenant du monitorage correspondant.

de: Daten zur Verbreitung und zeitlichen Entwicklung von respiratorischen Virusinfektionen und Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu ambulanten Konsultationen aus dem Sentinella-Meldesystem und zur Viruslast im Abwasser aus dem Abwassermonitoring.

en: Data on the spread and development of respiratory virus infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on outpatient consultations from the Sentinella reporting system and on the viral load in wastewater from the wastewater monitoring system.

it: Dati della diffusione e dell’evoluzione temporale delle infezioni virali respiratorie e dei casi di malattie respiratorie in Svizzera e nel Principato del Liechtenstein. Qui trovate dati delle consultazioni ambulatoriali basate sul sistema di dichiarazione Sentinella e dati della carica virale nelle acque reflue basate sul sistema di monitoraggio delle acque reflue.

fr: Virus respiratoires

de: Respiratorische Viren

en: Respiratory viruses

it: Virus respiratori


fr: Campylobactériose - système de déclaration obligatoire

de: Campylobacteriose - Obligatorisches Meldesystem

en: Campylobacteriosis - mandatory reporting system

it: Campilobatteriosi - sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires, les médecins et les hôpitaux ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

de: Die Daten basieren auf Informationen, die Laboratorien, Ärztinnen und Ärzte sowie Spitäler dem BAG im Rahmen der Meldepflicht übermittelt haben.

en: The data are based on information that laboratories, doctors and hospitals have submitted to the FOPH under the mandatory reporting requirement.

it: I dati si basano su informazioni comunicate dai laboratori, dai medici e dagli ospedali all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

fr: Données concernant la propagation et l’évolution temporelle des cas de campylobactériose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Campylobacteriose Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of campylobacteriosis infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di campilobatteriosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

campilobatteriosi-ufsp

display_name: campilobatteriosi-ufsp

campylobacteriose-bag

display_name: campylobacteriose-bag

campylobacteriose-ofsp

display_name: campylobacteriose-ofsp

campylobacteriosis-foph

display_name: campylobacteriosis-foph

fr: Campylobactériose

de: Campylobacteriose

en: Campylobacteriosis

it: Campilobatteriosi


fr: Tularémie - Système de déclaration obligatoire

de: Tularämie - Obligatorisches Meldesystem

en: Tularaemia - mandatory reporting system

it: Tularemia - Sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle des cas de tularémie en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

en: Data on the spread and development of tularemia infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on  cases from the mandatory reporting system.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Tularämie Infektionen Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu laborbestätigten Fällen aus dem obligatorischen Meldesystem.

it: Dati della diffusione e dell’evoluzione temporale dei casi di tularemia in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

tularaemia-foph

display_name: tularaemia-foph

tularamie-bag

display_name: tularamie-bag

tularemia-ufsp

display_name: tularemia-ufsp

tularemie-ofsp

display_name: tularemie-ofsp

fr: Tularémie

en: Tularemia

de: Tularämie

it: Tularämie


fr: Virus respiratoire - Sentinella

en: Respiratory viruses - sentinella

de: Respiratorische Viren - Sentinella

it: Virus respiratori - Sentinella

fr: Les données se fondent sur les informations recueillies par le système de déclaration Sentinella. Dans le cadre de ce système, les médecins transmettent des informations sur les premières consultations en raison d’une infection respiratoire aiguë (ARI) ou d’une affection grippale (ILI) dans leurs cabinets ou lors de visites à domicile.

de: Die Daten basieren auf Informationen aus dem Sentinella-Meldesystem. Im Rahmen dieses Meldesystems übermitteln ambulant tätige Ärztinnen und Ärzte Informationen zu Erstkonsultationen aufgrund akuter respiratorischer Infektion (ARI) oder grippeähnlicher Erkrankung (ILI) in Arztpraxen und bei Hausbesuchen.

en: The data are based on information from the Swiss Sentinel Surveillance Network (SSSN, Sentinella) monitoring system. Within the framework of this reporting system, outpatient doctors send information on initial consultations due to acute respiratory infection (ARI) or influenza-like illness (ILI) in medical practices and during home visits.

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Nel quadro di questo sistema di dichiarazione, i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano un’infezione respiratoria acuta (acute respiratory infection, ARI) o una sindrome simil-influenzale (influenza-like illness, ILI).

fr: Influenza - Système de déclaration obligatoire

de: Influenza - Obligatorisches Meldesystem

en: Influenza - mandatory reporting system

it: Influenza - Sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires en Suisse et dans la Principauté de Liechtenstein ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

en: The data are based on information that laboratories have submitted to the FOPH under the mandatory reporting requirement.

de: Die Daten basieren auf Informationen, die Laboratorien dem BAG im Rahmen der Meldepflicht übermittelt haben.

it: I dati si basano su informazioni comunicate dai laboratori in Svizzera e nel Principato del Liechtenstein all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

de: Die Daten basieren auf Informationen aus dem nationalen Abwassermonitoring der Schweiz und des Fürstentums Liechtenstein. Dieses Monitoring erfasst seit Januar 2022 die Viruslast von SARS-CoV-2 und seit Juli 2023 die Viruslast von Influenza und RSV in Abwasserproben der teilnehmenden Abwasserreinigungsanlagen (ARA).

fr: Influenza - Sentinella

en: Influenza - sentinella

de: Influenza - Sentinella

it: Influenza - Sentinella

fr: The data are based on information from the Swiss Sentinel Surveillance Network (Sentinella, SSSN) monitoring system. Since 1987, outpatient doctors have been submitting information on initial consultations in medical practices and during home visits for patients with influenza-like illness (ILI).

fr: Données concernant la propagation et l’évolution temporelle des infections grippales et des cas de grippe en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les consultations ambulatoires provenant du système de déclaration Sentinella, sur les cas confirmés en laboratoire provenant du système de déclaration obligatoire et sur la charge virale dans les eaux usées provenant du monitorage des eaux usées.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Influenza Infektionen und Grippe Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu ambulanten Konsultationen aus dem Sentinella-Meldesystem, zu laborbestätigten Fällen aus dem obligatorischen Meldesystem und zur Viruslast im Abwasser aus dem Abwassermonitoring.

en: Data on the spread and development of influenza infections and cases in Switzerland and the Principality of Liechtenstein. You will find data of outpatient consultations from the Sentinella reporting system and of cases from the obligatory reporting systemand of the viral load in wastewater from the wastewater monitoring system,.

it: Dati della diffusione e dell’evoluzione temporale delle infezioni e dei casi di influenza in Svizzera e nel Principato del Liechtenstein. Qui trovate dati delle consultazioni ambulatoriali basate sul sistema di dichiarazione Sentinella, dati dei casi confermati in laboratorio basate sul sistema di dichiarazione obbligatoria e dati della carica virale nelle acque reflue basate sul sistema di monitoraggio delle acque reflue.

bag-grippe-influenza

display_name: bag-grippe-influenza

foph-seasonal-flu-influenza

display_name: foph-seasonal-flu-influenza

ofsp-grippe-saisonniere-influenza

display_name: ofsp-grippe-saisonniere-influenza

ufsp-influenza-stagionale-influenza

display_name: ufsp-influenza-stagionale-influenza

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

abteilung-uebertragbare-krankheiten

fr: Division Maladies transmissibles

fr: Influenza

en: Influenza

de: Influenza

it: Influenza