maintainer: Giulia Mazzotti

en: snow-distribution snow-modelling forest-snow snow-energy-balance forest-structure

en: Canopy data

en: Includes all canopy structure metrics computed at all surveyed locations

en: Coordinates data

en: Includes coordinate information of each surveyed point (7 x 276 = 1932 forest points, 2 open areas)

en: Grid point nomenclature

en: The grid structure of each forest site and the respective nomenclature applied to label individual points within each grid are outlined here.  Each point marks the location of snow depth measurements and co-located canopy structure parameters.

en: Snow depth data open sites

en: Contains all snow detph data accquired at open sites nearby the forest stands during the same period.

en: Snow depth data forest sites

en: Contains all snow depth data acquired at all forest sites during winters 2012/13, 2013714 and 2014/15.

en: Meteo data to drive FSM2 model

en: Includes meteorological driving data used to run the forest snow model FSM2, processed and parsed in text files that match the format required by FSM2. Separate files are available for each field area (Laret, Drusatscha and Ischlag) and season (2012/13, 2013/14, 2014/15). Each file includes data for the period from October 1st to May 31st at hourly resolution.

en:
This dataset contains all snow, canopy and meteorological data presented and used in the publication: Mazzotti, G., Essery, R., Moeser, D. & Jonas T. (2020) 'Resolving spatial variability of forest snow using an energy-balance model with a 1-layer canopy'. Water Resources Research, https://doi.org/10.1029/2019WR026129.
This publication must be cited when using this dataset.

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

snow-distribution

display_name: snow-distribution

snow-energy-balance

display_name: snow-energy-balance

snow-modelling

display_name: snow-modelling

en: Snow depth, canopy structure and meterorological datasets from the Davos area, Switzerland, Winters 2012/13-2014/15, used for high-resolution forest snow modelling


maintainer: EnviDat Support

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

state: active

type: dataset

media_type: text/csv

en: Tree species profiles for 2020, Red band

format: CSV

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

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

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

en: Tree species profiles for 2020, NDMI index

en: Tree species profiles for 2019, Blue band

en: Tree species profiles for 2019, CIre Index

en: Tree species profiles for 2020, Blue band

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

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

en: Tree species profiles for 2019, EVI index

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

en: Tree species profiles for 2020, CIre index

en: Tree species profiles for 2019, NIR band

en: Tree species profiles for 2019, Green band

en: Tree species profiles for 2020, CCI index

en: Tree species profiles for 2020, NIR band

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

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

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

en: Tree species profiles for 2020, NDVI index

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

en: Tree species profiles for 2019, NDVI index

en: Tree species profiles for 2019, Red band

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

en: Tree species profiles for 2020, EVI index

en: Tree species profiles for 2019, CCI index

en: Tree species profiles for 2020, Green 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

educ

fr: Éducation, culture et sport

envidat

fr: EnviDat: le portail de données environnementales

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.


maintainer: Jana von Freyberg

en: snowmelt-lysimeter snowmelt-rate solutes stable-water-isotopes snowpack-outflow

en: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution. 10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

format: XLS

en:
This data contain volumes, solutes and isotopes of snowpack outflow measured by a snowmelt lysimeter system at three locations in the southern Alp catchment, situated Central Switzerland. The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.
The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (snowpack outflow volumes) at daily intervals from several sampling locations. Additionally, the data measured by the snowmelt lysimeter system are provided in 10-minute resolution.

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes

stable-water-isotopes

display_name: stable-water-isotopes

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Daily data of the volumes, solutes and isotopes in snowpack outflow measured at three locations in the southern Alp catchment


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

en: View video on youtube!

format: SERVICE

en: DHM-Kacheln zusammenfügen

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. In this tutorial video, we show how to merge multiple DTM raster tiles into one file, using the QGIS tool ‘Virtual Raster’. This simplifies the digital planning of a cable line using the QGIS plugin ‘Seilaplan’. Please note that the tutorial language is German!

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

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

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. In diesem Tutorialvideo zeigen wir, wie man mit dem QGIS-Plugin Virtuelles Raster mehrere DHM-Kacheln zu einem einzigen Rasterfile zusammenfügen und abspeichern kann. Für die Seillinienplanung mit Seilaplan muss nun nur noch eine Datei, mein neues virtuelles Raster, ausgewählt werden.

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

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geodata-processing

display_name: geodata-processing

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

raster-processing

display_name: raster-processing

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

en: Seilaplan Tutorial: Merge DTM tiles


tree-ring-laser-ablation-data

maintainer: Paula Ballikaya

title_for_slug: tree-ring-laser-ablation-data

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

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


maintainer: Giulia Francesca Azzurra Donati

en: biodiversity ecological-corridors urban-planning network-analysis circuit-theory ecosystem-services

en: Amphibian movement resistance layers and scripts for connectivity modelling - part 2

en: The zipped folder includes the script to create and analyse the networks from Circuitscape outputs. The subfolders “Boundaries”, “Layers”, and “Reference_net” contain files either called by the code or created in the process. The subfolder “Outputs_from_Circuitscape” contains the outputs from Circuitscape including node and branch cumulative currents in a network format.

en: Amphibian movement resistance layers and scripts for connectivity modeling - part 1

en: The zipped folder includes the script to aggregate the resistance layers into squared and hexagonal grids. The subfolders “Boundaries”, “Layers”, “Reference_grids”, and “Resistance_from_SDMs” contain files either called by the code or created in the process.The subfolder “Inputs_for_Circuitscape” contains the inputs to run Circuitscape, after doing some subsequent processing steps in QGIS (listed in the R script) with the files created with the script.

en: This data includes (1) Scripts to aggregate landscape resistance layers into squared and hexagonal grids (i.e., different representations and resolutions), (2) Input resistance layers and focal nodes in .txt format to run in Circuitscape (Python implementation v4.0.5). Circuitscape is a software tool for modeling and analyzing landscape connectivity, which simulates movement of organisms across landscapes by estimating resistance to movement across each point of the landscape. (3) Scripts for the ecological network analysis, and (4) environmental predictors for amphibian whole-life cycle habitats used to describe the local environment for BGI design (i.e. topographic, hydrologic, edaphic, vegetation, land-use derived, movement-ecology related).

biodiversity

display_name: biodiversity

circuit-theory

display_name: circuit-theory

ecological-corridors

display_name: ecological-corridors

ecosystem-services

display_name: ecosystem-services

network-analysis

display_name: network-analysis

urban-planning

display_name: urban-planning

en: Multi-Scale Prioritization framework for Urban Blue-Green Infrastructure Planning to Support Biodiversity: Data & Codes


en: uav wingtra photogrammetry dsm drone-data

en: Data Access

en:
- DSM 10cm resolution
- Orthomosaic 3cm resolution
- Agisoft Metashape Processing Report
- original RGB images

All generated products are also available as a cloud optimized geotiff.

en: We conducted four drone flights in Davos Wolfgang Arelen, in 2020/21 and 2022 to obtain data for the generation of DSMs and orthomosaics at a high resolution. The data was processed with the Agisoft Metashape Professional Software.

drone-data

display_name: drone-data

dsm

display_name: dsm

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

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: Photogrammetric Drone Data Wolfgang Arelen


en: snow wagital snow-water-equivalent meteodat-gmbh gcos

media_type: text/plain

format: TXT

en:
Total water reserves of the snow cover [mio m3] for Wägital catchment, Switzerland, for reference date April 1. Data is separated in 2 elevation zones 900m-1500m asl and 1500m-2300m asl. Time period 1943-2025, status 2025-04-30.

Funded currently or in the past by:

- Federal Office of Meteorology and Climatology MeteoSwiss in the context of GCOS Switzerland
- Meteodat GmbH
- Institute of Geography, University of Zurich
- WSL Institute for Snow and Avalanche Research SLF
- Institute of Geography, ETH Zurich (IAC ETH Zurich)
- AG Kraftwerk Wägital (AXPO and EWZ)

See also https://www.meteodat.ch/waegital.html

gcos

display_name: gcos

meteodat-gmbh

display_name: meteodat-gmbh

snow

display_name: snow

snow-water-equivalent

display_name: snow-water-equivalent

wagital

display_name: wagital

en: Snow water equivalent for reference date April 1 for Wägital catchment, starting 1943


maintainer: Albrecht von Boetticher

en: hangmuren interfoam shallow-landslide murgang finite-volumes dberisintermixing natural-hazard debris-flow barrier-impact-simulation

media_type: application/pdf

en:
Please install OpenFOAM 7 on a UBUNTU Linux system following the instructions given in readme_debrisintermixing-7.pdf
After a successful OpenFOAM installation, copy the applications-Folder from putMyContent-.zip into the OpenFOAM-User directory and follow the instructions in readme_debrisintermixing-7.pdf to install debrisInterMixing 7.

If you use UBUNTU 24-04 you might have troubles getting openmpi, I attached a modifiesd instruction installtionOF7Ubuntu20.04.5LTS.txt for a workaround.

format: PDF

media_type: application/zip

en:
This version of debrisInterMixing is based on OpenFOAM Version 4.x and was tested on Ubuntu 18.04.1 LTS.
Please follow the instructions given in ReadMe_debrisInterMixing4.pdf for installation.

format: ZIP

mimetype: application/zip

en: Installation Instructions for debrisInterMixing-6

en: These are the installation instructions for debrisInterMixing6

mimetype: application/pdf

en: debrisInterMixing for OF-Version 6

en: These are the installation instructions for debrisInterMixing4

en:
Here debrisInterMixing until version 7 is provided for download. Further versions as well as installation instructions and tutorials and discussion forums (mostly in german) can be acessed at murgang.org (choose "als Gast anmelden" and then scroll to the bottom). The first OpenFoam-compatible Version 2.3.x are available as supplement to v. Boetticher, A., Turowski, J. M., McArdell,W. B., Rickenmann, D., Hürlimann, M., Scheidl, C., and Kirchner, J. W.: DebrisInterMixing-2.3: A Finite Volume solver for three dimensional debris flow simulations based on two calibration parameters. Part two: model validation with experiments. Geoscientific Model Development, 10, 11: 3963-3978. doi: 10.5194/gmd-10-3963-2017.
DebrisInterMixing is a Volume-of-Fluid based Finite Volume code that accounts for shear-thinning sensitive shares of fine sediment suspension together with pressure-sensitive components of the gravel grains within debris flow mixtures. All model properties can be derived from a material sample except for a grid-sensitive calibration parameter.
For more information, please contact albrecht.vonboetticher@wasserbau.ch.

For a recent summary on applications see the DFHM8 contribution at https://www.e3s-conferences.org/articles/e3sconf/abs/2023/52/e3sconf_dfhm82023_02024/e3sconf_dfhm82023_02024.html - DOI: https://doi.org/10.1051/e3sconf/202341502024

UPDATE: DebrisInterMixing for OpenFOAM-7 is available, please contact albrecht.vonboetticher@wasserbau.ch. DebrisInterMixing with OpenFOAM-10 is ready but not yet validated.

barrier-impact-simulation

display_name: barrier-impact-simulation

dberisintermixing

display_name: dberisintermixing

debris-flow

display_name: debris-flow

finite-volumes

display_name: finite-volumes

hangmuren

display_name: hangmuren

interfoam

display_name: interfoam

murgang

display_name: murgang

natural-hazard

display_name: natural-hazard

shallow-landslide

display_name: shallow-landslide

en: Three-dimensional debris flow simulation tool debrisInterMixing


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

en: Data plot of the field station (NEF)

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

en: Site photo of the forest station (NEB)

en: Site photo of the forest station from below (viewing upwards the slope).

mimetype: image/jpeg

en: Data plot of the forest station (NEB)

en: Site photo of the field station (NEF)

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

en: Site aerial photo (Neunkirch)

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

en: Field station data (NEF)

en: Data file.

mimetype: text/csv

en: Forest station data (NEB)

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 Neunkirch in Switzerland where one station is located within a natural deciduous forest stand (NEB) with European beech (_Fagus sylvatica_; 160 yrs), sycamore maple (_Acer pseudoplatanus_; 160 yrs) and lime trees (_Tilia sp._; 110 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NEF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Neunkirch 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

precipitation

display_name: precipitation

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: Neunkirch, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: Beat Frey

en: database conservation soil-organisms info-fauna fungi fauna lichens red-list soil-quality soil-dependency eco-fauna ecosystem-protection soil-biodiversity

en: Raw dataset of species and their soil dependency as well as endangerment status.

en: Overview over the soil dependency and endangerment status of different groups of organisms.

en: Proportion of endangered species grouped by the four soil dependency classes.

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

Paper Citation:
Frey B., Maurer C., Schneider K. (2023) Informationen zum Boden anhand der Gebundenheit der Rote-Liste Arten BAFU. Bundesamt für Umwelt BAFU. 26 p.

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

Soil is the habitat and basis of life for countless creatures. The great importance of soil organisms for the fertility of our soils is widely recognized, but information is sparse on their distribution and possible endangerment in Switzerland. In the present project, target species, i.e. species that are closely linked to the soil, were identified, and for the the first time, information was gathered on the degree of endangerment of the soil ecosystem in Switzerland on the basis of Red List species. For eleven Red List groups, the species' soil dependency was determined, i.e. whether their life cycle includes stages in or on the soil. The assessment of soil dependency was made using four classes, which enabled the classification not only of insects but also of vertebrates, land snails, lichens and fungi.

conservation

display_name: conservation

database

display_name: database

eco-fauna

display_name: eco-fauna

ecosystem-protection

display_name: ecosystem-protection

fauna

display_name: fauna

fungi

display_name: fungi

info-fauna

display_name: info-fauna

lichens

display_name: lichens

red-list

display_name: red-list

soil-biodiversity

display_name: soil-biodiversity

soil-dependency

display_name: soil-dependency

soil-organisms

display_name: soil-organisms

soil-quality

display_name: soil-quality

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: Information on soil based on the soil dependency of the FOEN red list species


maintainer: Milojevic

en: reservoir-inflow return-periods low-flow alpine-precipitation extreme-values

en: Daily Luzzone Reservoir Inflow 01-01-2000 to 31-12-2019

en: Daily total water inflow to Luzzone reservoir. Natural inflow (LUZ_inflow_raw) is back-calculated based on daily water level in reservoir (removing hydropower inputs and spills). Linear interpolation between daily values is used to bring all inflow values into positive space (LUZ_inflow_intrp).

en: R codes for Extreme Values Analysis

en: Zip file containing R codes for running extreme value analyses for high precipitation and inflow events as well as code for determining return levels of low inflow and low precipitation events

en:
 Summary

* Dataset of daily inflow to Luzzone reservoir in Ticino, Switzerland

* R scripts used to generate return levels for low reservoir inflow, low precipitation, high inflow, and extreme high precipitation based on various methods from extreme value analysis

 Data
The dataset included here is the "natural" reservoir inflow for the Luzzone reservoir.
Additional analyses were conducted on daily total precipitation of 6 meteorological stations (abbreviations: TIOLI, TIOLV, COM, VRN, VLS, ZEV). These precipitation data are freely available for teaching and research from the MeteoSwiss IDAweb portal (https://www.meteoswiss.admin.ch/services-and-publications/service/weather-and-climate-products/data-portal-for-teaching-and-research.html).

 Codes
R scripts used to determine return levels of the data set are included for both extreme high events and low events. The scripts include the following methods for calculating return levels:

* GEV (Generalized Extreme Value)

* GPD and GPDd (Generalized Pareto Distribution including declustered version)

* eGPD (extended Generalized Pareto Distribution)

* MEV (Metastatistical Extreme Value)

alpine-precipitation

display_name: alpine-precipitation

extreme-values

display_name: extreme-values

low-flow

display_name: low-flow

reservoir-inflow

display_name: reservoir-inflow

return-periods

display_name: return-periods

en: Data and Code on Extreme Inflow and Lowflow Analysis for Alpine Reservoirs


maintainer: Felix Gugerli

en: genetic-structure genetic-diversity conservation-genetics melanargia-galathea monitoring

en:
Individual genotypes assessed at six nuclear microsatellite loci (two alleles per locus) for individuals of the butterfly Melanargia galathea (Marbled white) that were collected throughout Switzerland, along the regular grid of the Biodiversity Monitoring (BDM) of Switzerland. For each individual, the sampling site (number) and the genotype are given. Note that due to privacy restrictions, the original geographic coordinates remain disclosed. For original coordinates, data holders should be contacted (Swiss Federal Office for the Environment; Biodiversity Monitoring Switzerland).
The data refer to the following publication: Terzer et al., Distinct spatial patterns of genetic structure and diversity in the butterfly Marbled White (Melanargia galathea) inhabiting fragmented grasslands. Conservation Genetics, https://doi.org/0.1007/s10592-023-01593-4.

conservation-genetics

display_name: conservation-genetics

genetic-diversity

display_name: genetic-diversity

genetic-structure

display_name: genetic-structure

melanargia-galathea

display_name: melanargia-galathea

monitoring

display_name: monitoring

en: Nuclear microsatellite genotypes of the butterfly Melanargia galathea


en: snow-height snow-water-equivalent gcos snow snow-profile

en: STATION METADATA

mimetype: text/plain

en: DATA ACCESS

en:
This dataset contains long-term snow water equivalent and corresponding snow depth data 11 observer sites in Switzerland between 1200 and 2500 m a.s.l. compiled for the Global Climate Observing System (GCOS) and supported by MeteoSwiss. Snow depth (cm) and snow water equivalent (mm) are manually recorded every 2 weeks since the 1947 (depending on station). The attached metadata file gives details for each station.
The measurement series agree with GCOS objectives according to the GCOS Implementation Plan: This inlcudes:
• Raw data are archived in the snow and avalanche database at SLF.
• Measuring techniques are traceable and documented as snow depth and snow water equivalent have in general remained the same since beginning up to now. When planning new systems or changes of existing systems in the future, their impact will be assessed prior to implementation.
• Historical data of these 11 stations have been digitized and all data have been quality controlled.
• Detailed metadata (location of measurements) are available.
• Public availability of the data has been ensured by publishing the data on the Envidat portal (https://www.envidat.ch/dataset/gcos-swe-data).

gcos

display_name: gcos

snow

display_name: snow

snow-height

display_name: snow-height

snow-profile

display_name: snow-profile

snow-water-equivalent

display_name: snow-water-equivalent

en: GCOS SWE data from 11 stations in Switzerland


maintainer: Dominique Weber

en: use-intensity management landsat land-use mowing sentinel-2 remote-sensing grassland

en: Preview number of grassland management events 2020

media_type: image/png

en: Spatial distribution of the number of management events for Switzerland and for three zoomed-in regions (a, b, c). The three zoomed-in regions show different grassland-use intensities, which are reflected in the distribution of management frequency (Weber et al., 2023; IN REVIEW)

format: PNG

en: Readme

en: Metadata and description of the maps and webcam-based reference data.

en: Grassland-use intensity map 2020

en: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2020. See readme file for more details.

format: GeoTIFF

en: Grassland-use intensity map 2019

en: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2019. See readme file for more details.

en: Preview time of 1st grassland management event 2020

en: Spatial distribution of the timing (day of year; DOY) of the first management event for Switzerland and for three zoomed-in regions (a, b, c). The three zoomed-in regions show different grassland-use intensities, which are reflected in the timing of the first event of the year (Weber et al., 2023; IN REVIEW)

en: Grassland-use intensity map 2018

en: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2018. See readme file for more details.

en: Webcam-based reference data

en: Webcam-based reference data from 2020 and 2021 (see readme).

en: Grassland-use intensity map 2021

en: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2021. See readme file for more details.

en:
A rule-based algorithm [(Schwieder et al., 2022)](https://doi.org/10.1016/j.rse.2021.112795) was used to produce annual maps for 2018–2021 of grassland-management events, i.e. mowing and/or grazing, for Switzerland using Sentinel-2 and Landsat 8 satellite time series. All satellite images were processed with the [FORCE](https://force-eo.readthedocs.io) framework.

The resulting maps provide information on the number and timing of grassland-management events at a spatial resolution of 10 m × 10 m for the whole of Switzerland. For the final maps, permanent grasslands were masked using a variety of land-use layers, according to [Huber et al. (2022)](https://doi.org/10.1002/rse2.298) but replacing the crop mask with the agricultural-use data from the cantons.

We assessed the detection of management events based on independent reference data, which we acquired from daily time series of publicly available webcams that are widely distributed across Switzerland. We further tested the ecological relevance of the generated intensity measures in relation to nationwide biodiversity data (see [Weber et al., 2023](https://doi.org/10.1002/rse2.372)).

The webcam-based reference data used for verification was subsequently added on 14.02.2024.

grassland

display_name: grassland

land-use

display_name: land-use

landsat

display_name: landsat

management

display_name: management

mowing

display_name: mowing

remote-sensing

display_name: remote-sensing

use-intensity

display_name: use-intensity

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: Grassland-use intensity maps for Switzerland


en: geology landscape-evolution endemism flora madagascar

en: Data v1.0

en: Escarpment evolution drives the diversification of the Madagascar flora

en: This upload contains the data (species checklist, species range maps, time-calibrated phylogenies, topographic change, etc.) generated, analyzed, and presented in the paper .

en: Although much of the endemic biodiversity of Madagascar can be attributed to its isolation as an island in the Indian Ocean, the high rates of speciation throughout its geologic history suggest an influence of local-scale landscape dynamics. The topographic evolution of Madagascar is dominated by the formation of high-relief continental rift escarpment and we argue that the erosion and landward retreat of this topography creates habitat heterogeneity that has served as a speciation pump for the island. The highest plant richness is found along the escarpment and is characterized by steady diversification rates over the last 45 Ma. Modeled landscape evolution by escarpment retreat demonstrates opportunities for allopatric speciation by transient habitat fragmentation through multiple mechanisms, including catchment expansion, isolation of highland remnants and formation of topographic and river barriers The segregation of floral phylogenetic turnover parallel to the escarpment is consistent with these mechanisms and indicates the importance of erosion-driven landscape dynamics on speciation.

endemism

display_name: endemism

flora

display_name: flora

geology

display_name: geology

landscape-evolution

display_name: landscape-evolution

madagascar

display_name: madagascar


maintainer: Stefan Klesse

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

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: 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: 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

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


maintainer: Frank Hagedorn

en: biogeochemical-cycling drought plfa microbial-biomass forest c13-labeling

en: Gao_Frank_C13 pulse labeling.xlsx

en:
Data of manuscript by Gao t al. : Drought resistance and resilience of rhizosphere communities in forest soils from the cellular to ecosystem scale – insights from 13C pulse labeling
Inludes data on 13C pulse-labeling experiment in young beech model ecosystems and a mature pine forest. Data of soil climate, total PLFA, 13C label strength in PLFA of pulse-labeling carried out under drought and after rewetting

en: Data of 13C-pulselabeling experiments in a young beech model ecosystem and a mature pine forest exposed to drought and rewetting. Data include microclimate during the experiment, total PLFA contents, d13C signatures in PLFA , microbial biomass, soil-respired CO2 measure during 30 days following 3-4 hour long pulse labeling with highly 13C-enriched CO2.

biogeochemical-cycling

display_name: biogeochemical-cycling

drought

display_name: drought

forest

display_name: forest

microbial-biomass

display_name: microbial-biomass

plfa

display_name: plfa

en: Gao_Drought resistance and resilience of rhizosphere communities_13C-PLFA


maintainer: Felix Kienast

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

en:
This is the compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.
Column description:
X01 = Planning_units (PUs)
X02 = incl.OS. number of times pu was selected in MARXAN when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)
geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).

en:
This study examines the siting scenarios for renewable energy infrastructure (REI) in Switzerland, incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed.
MARXAN was run for 2 versions: a) without ground-mounted open space PV infrastructure (excl. OS) and b) with ground-mounted open space PV infrastructure (incl. OS). In each version optimization was done using ecological costs (ECUess) or social costs (ECUsoc) in a regular grid of 4x4km (planning unit).

File:
PU_data.shp: compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.

Headers are described below:
X01 = Planning_units (PUs)

X02 = incl.OS. number of times pu was selected in MARXAN when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)

geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).

For MARXAN optimizations (for meaning of standard files in MARXAN see https://scholar.google.ch/scholar_url?url=https://courses.washington.edu/cfr590/software/Marxan1810/marxan_manual_1_8_2.pdf&hl=de&sa=X&ei=NAWHZI6JJ8PFmAGMo47oDQ&scisig=AGlGAw-DBrsV4kUzkR6GkN1jtG66&oi=scholarr), pu_data.shp was used to generate MARXAN files input.dat, pu.dat, puvfeat.dat, spec.dat.
Coordinate Reference System: CH1903 / LV03. EPSG: 21781.

ecosystem-services

display_name: ecosystem-services

energy

display_name: energy

landscape

display_name: landscape

marxan

display_name: marxan

optimization

display_name: optimization

photovoltaic

display_name: photovoltaic

social-acceptance

display_name: social-acceptance

spatial-planning

display_name: spatial-planning

wind-power

display_name: wind-power

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: Optimizing renewable energy siting in the Swiss landscape


maintainer: Ionuț Iosifescu Enescu

en: Bulk Data Access

en: Link to the S3 bucket where all the data resources can be downloaded in bulk

en: map preview 0.5MB

en:
The attached data are some large GIS raster files (GeoTIFFs) made with Natural Earth data. Natural Earth is a free vector and raster map data @ naturalearthdata.com. The data used for creating these large files was the "Cross Blended Hypso with Shaded Relief and Water". Data was concatenated to achieve larger and larger files. Internal pyramids were created, in order that the files can be opened easily in a GIS software such as QGIS or by a (future) GIS data visualisation module integrated in EnviDat.

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis

en: Large GIS raster data derived from Natural Earth Data (Cross Blended Hypso with Shaded Relief and Water)


maintainer: Thorsten Bartels-Rausch

en: reaction solution ozone arctic snow interface laboratory-study heterogeneous brine chemistry antarctica alpine metamorphism

en: Matlab Script to view and plot data

en: Matlab Data

en: All data as Matlab mat file

en: Readme file

en: This file shows data, code, and plots.

en: Earth’s snow cover is very dynamic on diurnal time scales. The changes to the snow structure during this metamorphism have wide ranging impacts such as on avalanche formation and on the capacity of surface snow to exchange trace gases with the atmosphere. Here, we investigate the influence of dry metamorphism, which involves fluxes of water vapor, on the chemical reactivity of bromide in the snow. For this, the heterogeneous reactive loss of ozone at a concentration of 5-6E12 molecules cm-3 is investigated in artificial, shock-frozen snow samples doped with 6.2 uM sodium bromide and with varying metamorphism history. The oxidation of bromide in snow is one reaction initiating polar bromine releases and ozone depletions.

alpine

display_name: alpine

antarctica

display_name: antarctica

arctic

display_name: arctic

brine

display_name: brine

chemistry

display_name: chemistry

heterogeneous

display_name: heterogeneous

interface

display_name: interface

laboratory-study

display_name: laboratory-study

metamorphism

display_name: metamorphism

ozone

display_name: ozone

reaction

display_name: reaction

snow

display_name: snow

solution

display_name: solution

en: Data set on bromide oxidation by ozone in snow during metamorphism from laboratory study


maintainer: Izabela Bujak-Ozga

en: catchment stream-water hydrogen-isotopes groundwater oxygen-isotopes catchment-data solutes

en: This document provides a detailed description of the hydrochemical dataset, including, among other things, an overview of the dataset content, an explanation of the column headers, a description of the locations where samples were collected, and an explanation of the abbreviations used in the dataset.

en: This dataset includes mean concentrations of solutes (Calcium, Iron, Magnesium, Sodium, Potassium, Boron, Nitrate, Sulfate, and Chloride) and stable isotope values (hydrogen and oxygen) in water molecules. These were measured in precipitation, groundwater, soil water, and surface water samples collected from the Haute-Mentue catchment in Switzerland during Spring and Fall 2022. Detailed information is available in the accompanying documentation (documentation_for_the_hydrochemical_data_collected_during_spring_fall_2022_in_the_haute-mentue_catchment.pdf).

en: The dataset contains hydrochemical data collected from spring to fall 2022 in the Haute-Mentue catchment, Switzerland. This hydrochemical data includes solute concentrations and stable isotopes of oxygen and hydrogen in water molecules, measured in streamwater, soil water, groundwater, and rainfall samples. Samples were collected during eight rainfall events with higher temporal resolution (hourly) as well as at lower resolution between events. A detailed description of the dataset is provided in the documentation.

catchment

display_name: catchment

catchment-data

display_name: catchment-data

groundwater

display_name: groundwater

hydrogen-isotopes

display_name: hydrogen-isotopes

oxygen-isotopes

display_name: oxygen-isotopes

solutes

display_name: solutes

stream-water

display_name: stream-water

educ

en: Education, culture and sport

en: Hydrochemical Data Collected during Spring-Fall 2022 in the Haute-Mentue Catchment


maintainer: Rebecca Mott

en: snow-patch patchy-snow-covers dischmex eddy-covariance-measurements turbulent-sensible-heat-fluxes

en: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 3.5 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific Inc.) in 1.7 m on a daily basis.

en: Output explanation

en: Gletschboden setup

en: Background map based on data © 2014/2016 swisstopo (JD100042)

mimetype: image/png

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.2 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 0.7 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 3.3 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific Inc.) in 3.2 m on a daily basis.

en: Eddy-covariance measurement with an ultrasonic anemometer (DA-600, Kaijo-Denki) in 0.3 m on a daily basis.

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.6 m.

en:
This dataset contains eddy-covariance measurements in the ablation period of 2014-2016. Measurements were taken from two turbulence towers over a long-lasting snow patch, which are 5 m apart from each other (2014 and 2015). The turbulence towers were equipped with two YOUNG ultrasonic anemometers mounted 0.7 m (in 2014) and 3.3 m (in 2015) above snow-free ground, two ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) mounted at 2.6 m (in 2014) and 2.2 m (in 2015) above snow-free ground and one anemometer (DA-600, Kaijo Denki) mounted at 0.3 m above snow surface.

The measurement setup changed in 2016 and includes a measurement above the snow-free ground in upwind direction (Swiss coordinates: 790191/176689). The measurement tower is equipped with one ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 3.3 m above the snow-free ground. Additionally, one measurement tower is installed above the long-Lasting snow patch and equipped with the same setup as 2015.

Turbulence data were sampled at a frequency of 20 Hz. The processing of the data to quality controlled fluxes has been done with the Biomicrometeorology flux software (Thomas et al., 2009). The program applies plausibility tests and a despiking test after Vickers and Mahrt (1997) on the measured data. The routine further applies a time-lag correction and considers the deployment (e.g. the sonic azimuth). A frequency response correction (Moore, 1986) is done and a three-dimensional rotation is performed. Finally, quality assurance/quality control (QA/QC) flags after Foken et al., (2004) are issued and fast Fourier transform power and co-spectra are calculated. The change in snow height is considered in the post-processing for every measurement day. The turbulence data were averaged to 30 minute intervals.

dischmex

display_name: dischmex

eddy-covariance-measurements

display_name: eddy-covariance-measurements

patchy-snow-covers

display_name: patchy-snow-covers

snow-patch

display_name: snow-patch

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

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 - Impact of extreme land-surface heterogeneity on micrometeorology over spring snow-cover


en: sustainability outdoor-lighting artificial-lighting alan ecosystem-services

en: R code for PERMANOVA Analysis of flight-active insects.

format: OCTET

en: Raw data for ground-dwelling arthropod NMDS analysis

en: Raw data for flying insects NMDS analysis

en: R code of ground-dwelling arthropod analysis.

en: Raw data Moran's I test

en: Raw data for flying insects analysis

en: R code for NMDS of ground-dwelling arthropods

en: Raw data for flying insects and ground-dwelling arthropod combined analysis

en: Raw data for ground-dwelling arthropod analysis

en: R code of flight-active insects analysis.

en: R code for PERMANOVA Analysis of ground-dwelling arthropods.

en: R code for NMDS of flight-active insects

en: R code of flight-active and ground-dwelling arthropod combined analysis.

en: Raw data and R Code to do all the analysis performed for the paper "Advancing sustainable LED solutions to mitigate light-pollution impacts on arthropods". Including data for both flight-active insects and ground-dwelling arthropods combined (PT_TRF_all.csv), flight-active insects alone (ALANeX_PT_all_clean_control.csv) and ground-dwelling insects alone (ALANeX_TRF_all_clean_control.csv). For the NMDS analysis, there is a data set for the flight-active insects (ALANeX_PT_NMDS.csv) and the ground-dwelling arthropods (ALANeX_TRF_NMDS.csv). For the Morans I use the 'ALANeX_MoransI.csv' dataset.

alan

display_name: alan

artificial-lighting

display_name: artificial-lighting

ecosystem-services

display_name: ecosystem-services

outdoor-lighting

display_name: outdoor-lighting

sustainability

display_name: sustainability

educ

en: Education, culture and sport


maintainer: Frank Techel

en: avalanche-forecasting verification avalanche-danger-level avalanche-bulletin avalanche-forecast

en: D_QC for forecasting seasons 2020/2021 - 2022/2023.

en: Data for the 2023/2024 forecasting season. It was added on 26 Aug 2024 by F. Techel.

en: D_QC for forecasting seasons 2001/2002 until 2019/2020.

en:
The data set contains the re-analyzed (or quality-checked) regional avalanche danger levels (D_QC) for Switzerland.

D_QC relates to dry-snow avalanche conditions only. Measuring the avalanche danger level D is not possible; forecast, nowcast, and hindcast assessments of D are judgments by humans interpreting data. However, combining several pieces of information indicating the same D, it can be expected that it is more likely that D_QC represents the avalanche conditions well.

For the **forecasting seasons 2001/2002 until 2019/2020**, the approach to obtain D_QC is described in detail in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

For the **forecasting seasons 2020/2021 and later**, D_QC is derived using the following approach:
1. *Combination of forecast (D_forecast) and nowcast (D_nowcast)*: If there was only one assessment available by an observer after a day in the field for a region, and if D_forecast = D_nowcast --> D_QC = D_forecast.
2. *Combination of several nowcast assessments (D_nowcast)*: If two (or more) observers agreed (or majority opinion) in their (independent) assessments of D_nowcast after a day in the field in the same warning region. --> D_QC = D_nowcast.
3. *Hindcast analysis (D_hindcast)*: In Switzerland, avalanche forecasters re-evaluate all situations when D = 4 (high) or D = 5 (very high) were either forecast, should have been forecast, or when forecasters discussed given one of these two levels but had not given them. Generally, two forecasters assess each situation. In these cases, D_QC = D_hindcast. The hindcast analysis, only available since the forecasting season 2020/2021, replaces what was step (2) in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

All other cases - ties in case of (1) or (2), no new information from the warning region in question, or if no D_hindcast was available - are not considered quality-checked, and are, thus, not contained in the data set.

In addition to D_QC, the file contains information on the elevation and aspect, where D_QC likely prevails.
- The indicated elevation is the mean of the respective elevations in (1), (2), or (3). At danger level 1 (low), when no elevation is indicated in the Swiss forecast, a value of 1500 m is set.
- For the four cardinal aspects N, E, S, and W, a value of 1 means that there was agreement that D was reached in this aspect and a value of 0 means that there was agreement that D was not reached in this aspect. Intermediate values correspondingly mark disagreements in the assessments.

avalanche-bulletin

display_name: avalanche-bulletin

avalanche-danger-level

display_name: avalanche-danger-level

avalanche-forecast

display_name: avalanche-forecast

avalanche-forecasting

display_name: avalanche-forecasting

verification

display_name: verification

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: Re-analyzed regional avalanche danger levels in Switzerland


en: red-list endemic range-size conservation-priority europe rarity bryophytes

en: This dataset provides data on the occurrence of 672 European bryophyte species in European countries or territories. All species which are considered threatened or near threatened according to the European Red List (Hodgetts et al. 2019) are included (553 species). Further, all species evaluated in the European Red List assessed as LC, DD, NE and EX, which at the same time are either endemic, near endemic or globally rare, are included (119 species). Therefore, the list contains not only all European bryophyte species that are threatened or near threatened, but also all species endemic or near endemic to Europe as well as all globally rare species occurring in Europe. For each of the 553 threatened or near threatened species, we provide a conservation a priority score which was calculated based the Red List status and the proportion of the European population of the global population or the global rarity of the species. For details on the prioritisation approach see Bisang et al. (2025).

bryophytes

display_name: bryophytes

conservation-priority

display_name: conservation-priority

endemic

display_name: endemic

europe

display_name: europe

range-size

display_name: range-size

rarity

display_name: rarity

red-list

display_name: red-list

en: Priority ranking for the conservation of all European bryophyte species - dataset


dataset-on-new-snow-water-equivalent

maintainer: EnviDat Support

title_for_slug: dataset-on-new-snow-water-equivalent

en: snowfall precipitation data-assimilation new-snow snow-modelling

en: The .zip file contains all data as described in this repository and associated publication. The .zip file contains a readme file describing its content in detail.

en:
This dataset includes quality-controlled measurements of new snow depth (HN), new snow water equivalent (HNW), snow depth (HS), and snow water equivalent (SWE) from 41 stations located in Switzerland for the period from 2016-09-01 to 2022-08-31.
These data are the basis of the following publication: Magnusson J., Cluzet B., Quéno L., Mott R., Oberrauch M., Mazzotti G., Marty C., Jonas T., 2025, Evaluating methods to estimate the water equivalent of new snow from daily snow depth recordings, Cold Regions Science and Technology, https://doi.org/10.1016/j.coldregions.2025.104435.
Abstract
The water equivalent of new snow (HNW) plays a crucial role in various fields, including hydrological modeling, avalanche forecasting, and assessing snow loads on structures. However, in contrast to snow depth (HS), obtaining HNW measurements is challenging as well as time-consuming and is hence rarely measured. Therefore, we assess the reliability of two semi-empirical methods, HS2SWE and ΔSNOW, for estimating HNW. These methods are designed to simulate continuous water equivalent of the snowpack (SWE) from daily HS only, with changes in SWE yielding daily HNW estimates. We compare both parametric methods against HNW predictions from a physics-based snow model (FSM2oshd) that integrates daily HS recordings using data assimilation. Our findings reveal that all methods exhibit similar performance, with relative biases of less than ~3 % in replicating SWE observations commonly used for model evaluations. However, the ΔSNOW model tends to underestimate daily HNW by ~17 %, whereas HS2SWE and FSM2oshd combined with a particle filter data assimilation scheme provide nearly unbiased estimates, with relative biases below ~5 %. In contrast to the parsimonious parametric methods, we show that the physics-based approach can yield information about unobserved variables, such as total solid precipitation amounts, that may differ from HNW due to concurrent melt. Overall, our results underscore the potential of utilizing commonly available daily HS data in conjunction with appropriate modeling techniques to provide valuable insights into snow accumulation processes. Our study demonstrates that daily SWE observations or supplementary measurements like HNW are important for validating the day-to-day accuracy of simulations and should ideally already be incorporated during the calibration and development of models.
Acknowlegements
These data were recorded by SLF observers and staff members. Their contribution is gratefully acknowledged.

data-assimilation

display_name: data-assimilation

new-snow

display_name: new-snow

precipitation

display_name: precipitation

snow-modelling

display_name: snow-modelling

snowfall

display_name: snowfall

en: Dataset on new snow water equivalent


en: chemistry ice atmosphere laboratory-study snow-atmosphere-interactions

en: Processed data as shown in Figure 4 of publication. X-ray energy in eV in column one, electron count intensity in arb. units in column 2.

en:
The table lists all NEXAFS raw data with the following columns:

* name:						raw file name
* xRayEkinRange_eV: 		Smallest and largest X-ray photon energy in eV
* scientaPassEnergy_eV: 	Pass energy of electron analyzer in eV
* scientaDwellTime_ms: 		Dwell time of electron analyzer in ms
* regionName:				O K-edge for all data
* scientaAcquisitionMode: 	Fixed energy (snapshot) mode
* scientaEkinRange_eV: 		Smallest and largest energy of the kinetic energy window used for detection in this work
* scientaEkinStep_eV		Not defined in fixed energy mode
* scientaLensMode:			Tune table
* scientaRegionIterations: 	Iterations (sweeps)
* scientaSequenceIterations: Iterations (sweeps)
* sampleTemp_dC: 			Temperature as monitored at the sample holder in °C
* cellPressure_mbar: 		Total pressure in measurement cell in mbar
* iceTemp_dC: 				Temperature of ice sample calculated based on vapour pressure (assuming total pressure equals partial pressure of water) in °C
* smplX_mm: 				positon of measurement spot, x dimension in mm
* smplY_mm: 				positon of measurement spot, y dimension in mm
* smplZ_mm: 				positon of measurement spot, z dimension in mm
* sealingTemp:				temperature at base of sample manipulator
* lastModifiedDatestr: 		time and date when data aquisition was finished
* sample: 					sample description

en: Near Ambient Pressure partial Auger-Meitner electron yield X-ray absorption spectra and photon flux data. X-ray energy in eV in column 1, analyzer electron count intensity in arb. units in column 2.

en: Data are compiled that have been used to demonstrate the impact of high water partial pressure on X-ray absorption spectra of ice.

atmosphere

display_name: atmosphere

chemistry

display_name: chemistry

ice

display_name: ice

laboratory-study

display_name: laboratory-study

snow-atmosphere-interactions

display_name: snow-atmosphere-interactions

en: An ice oxygen K-edge NEXAFS spectroscopy data set on gas-phase processing


maintainer: Markus Schlegel

en: spore-dispersal monitoring air-sampling environmental-dna metabarcoding

en: Data files and analysis scripts (Version 1)

en: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of fungi". Please refer to README.pdf inside the archive for more information.

en: Data files and analysis scripts (Version 2)

en: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of macrofungi". Please refer to README.pdf inside the archive for more information.

en:
Resources associated with the manuscript *A case study on the application of spore sampling for the monitoring of macrofungi* ([Schlegel et al. 2024](https://doi.org/10.1111/1755-0998.13941)).
Airborne environmental DNA (eDNA) monitoring of fungi was evaluated on a species-rich grassland site. Extensive fruiting body surveys yielded 29 waxcap and clavarioid species, 19 of which were also detectable in air eDNA. The analysis indicates that spores of locally occurring fruiting bodies were detected, in addition to a large diversity of common fungal species, while rare and threatened species were under-represented in the air.
*Version 1* of the dataset was submitted during the review phase. *Version 2* contains minor changes and clarifications, and is up to date with the [published supplement](https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F1755-0998.13941&file=men13941-sup-0001-AppendixS1.pdf) of the study.
The contents of the ZIP archive:
* analysis scripts in [R-Markdown](https://rmarkdown.rstudio.com) format, including the rendered PDF output with figures and tables (*analysis* directory)
* eDNA sample metadata (*amplicon_meta*) and results of the amplicon clustering (*amplicon_data*) and the source code of the pipeline (*amplicon_pipeline*)
* positions of all fruiting body groups found in the surveys (3838 GPS points) (*surveys*)
* positions of the spore traps, taxonomy of studied grassland fungi and red-list species, and many more resources
Please refer to `README.pdf` inside the archive for a complete description of the file structure and information on how to reproduce the analyses.

air-sampling

display_name: air-sampling

environmental-dna

display_name: environmental-dna

metabarcoding

display_name: metabarcoding

monitoring

display_name: monitoring

spore-dispersal

display_name: spore-dispersal

educ

en: Education, culture and sport

en: Supporting information for case study on the application of spore sampling for the monitoring of macrofungi


maintainer: Axel Volkwein

en: experiment mass-movements rockfall field-tests natural-hazards field-data experiments trajectory field-test

en: Block trajectories recorded from local positioning system

en: This file contains more than 80 rockfall trajectories projected onto the terrain, i.e. the positions of the single blocks over time during the single tests that were recorded by the local positioning system with about 10Hz. It contains the detected positions as well as a smoothened path (see Volkwein et al., Geosciences, 2018). The table also contains the derived velocities and accelerations along the slope (attention: these accelerations are the once that occur during an impact).

en: These data contain the point clouds obtained from laser scanning the test slope and the six test blocks used for the experiments. The coordinates of the slope are given in CH-1903 format. The coordinates of the block point clouds are kept in a lokal x/y/z coordinate system.

en: Jumps and impacts

en: This table contains data of more than 2200 of each jumps and impacts of the test blocks on a grassy slope. It gives there durations in combination with acting accerlartions and the rotational speed of the blocks. The data were retrieved using the block internal accelerometer and rotation sensors. The combination of these data with the measurement from the local positioning system allows the deduction of jump lengths, slope gradient etc.

en: Overview of all tests

en:
This table gives an overview on all tests performed including
- block used
- start & end position
- number of jumps
- etc.
-

en:
In summer 2014, 6 rock blocks between 20 and 80kg have been thrown in total 111 times down a slope at the Swiss Oberalppass close to the village Tschamut. The slope was mainly covered by grass and its lower part was flat and large enough to provide natural runouts of the single trajectories.

An extensive measurement program has been set up to measure the block trajectories: With surveyor's instruments the slope and the six used rock blocks were scanned and the start and end positions of each test were recorded. During the single events two cameras filmed the trajectories. A special sensor device located within the blocks recorded the acting accelerations and rotational speeds over time. Further, the device emitted a Wifi signal that got detected from eight receivers around the slope. Based on this signal the block position has been recorded over time.

The dataset contains all data that were gathered through above field campaign.

experiment

display_name: experiment

experiments

display_name: experiments

field-data

display_name: field-data

field-test

display_name: field-test

field-tests

display_name: field-tests

mass-movements

display_name: mass-movements

natural-hazards

display_name: natural-hazards

rockfall

display_name: rockfall

trajectory

display_name: trajectory

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: Repetitive trajectory testing in Tschamut 2014


en: forecast-models avalanche-release-probability machine-learning avalanche-forecast spatial-modelling

en: Human-triggered avalanches 2022/2023

en: The file contains the reported human-triggered avalanches. The variables are as follows: id, release date (date), name, Swiss coordinates (x,y), elevation (ele), remark, reported avalanche size expressed using avalanche activity index (sizeAAI), aspect, event type (type), event (yes = 1, no = 0)

en: Snowline estimates 2023/2024

en: Daily snowline estimates provided by observers for North (aspect = 0) and South (aspect = 180) slopes for the 2023/2024 season. For aspects in between North and South, values are interpolated. Contains observation date (date), coordinates (Swiss coordinates x, y), snowline elevation (snowline), and aspect.

en: Avalanche forecast

en: Data contains forecasts relating to dry-snow avalanche conditions only. Forecast issued at 17.00 local time. Contains variables for the warning region (sector_id), publication date (date), danger level - sub-level combination expressed using numeric values (integer value of danger level -0.33 for sub-level minus, -0 for sub-level neutral, +0.33 for sub-level plus, altitude as indicated in the bulletin, and whether aspect (North = 0, Northeast = 45, ...) was indicated in the bulletin (no: 0, yes: 1).

en: Randomly sampled subset of grid points from 1 km DEM

en: Contains the randomly sampled subset of grid points from 1 km DEM. Three variables: coordinates (x, y) and elevation (elev).

en: Natural avalanches 2022/2023

en: Natural avalanche observation (dry avalanches). 2022-2023 forecasting season.

en: GPS data and human-triggered avalanches

en: Contains (1) the subset of points extracted from GPS tracks recorded during backcountry touring and uploaded to the website skitourenguru.ch and (2) the corresponding subset of human-triggered avalanches. Data (1) was provided by Skitourenguru GmbH and data (2) was collected by SLF. - Variables contained are date, Swiss coordinates (x, y), aspect (N = 0, NE = 45, ...), elevation (ele), and event (event = 1, non-event = 0).

en: Snowline estimates 2022/2023

en: Daily snowline estimates provided by observers for North (aspect = 0) and South (aspect = 180) slopes for the 2022/2023 season. For aspects in between North and South, values are interpolated. Contains observation date (date), coordinates (Swiss coordinates x, y), snowline elevation (snowline), and aspect.

en: Natural avalanches 2023/2024

en: Natural avalanche observation (dry avalanches). 2023/2024 forecasting season.

en: Model predictions (raw data)

en: Model predictions (raw data) for three models, in nowcast and forecast mode. Not all models are available for both seasons. - These data are the basis for the interpolated predictions, which can be found in the other zip-folder

en: Model predictions (interpolated)

en: The zip file contains csv-files the interpolated model predictions for three models, in forecast and nowcast-mode, for the three different data sets, as described in the publication.

en: Human-triggered avalanches 2023/2024

en:
This data set was used in the analysis by Techel et al. **Can model-based avalanche forecasts match the discriminatory skill of human danger level forecasts? A comparison from Switzerland**. Please note that the title of the preprint was *Forecasting avalanche danger: human-made forecasts vs. fully automated model-driven predictions*, submitted to *Natural Hazards Earth System Sciences* on 20 Aug 2024.
The final manuscript used data from three forecasting seasons (2022/2023, 2023/2024, 2024/2025) , the preprint two forecasting seasons (2022/2023, 2023/2024) .
Currently, the repository contains data from two avalanche forecasting seasons in Switzerland. The third season will be added (to be done, 30 June 2025).
**Interpolated predictions**
- The .zip file contains the interpolated predictions for the three models in nowcast- and forecast- mode. This data is needed to reproduce the figures and tables in the submitted preprint.
The other data are the **raw data** underlying the interpolations:
- Avalanche forecast by WSL Institute for Snow and Avalanche Research SLF, published at 17.00 local time, valid for the following 24 hours and relating to dry snow avalanche conditions.
- Model predictions in *nowcast*- and *forecast*-mode for three models (*danger level*, *instability*, *natural avalanche*), valid for 12.00 local time
- Subset of points extracted from GPS tracks (courtesy of Skitourenguru GmbH)
- Avalanche observations - natural avalanches and human-triggered avalanches
- Estimates of the snowline
- Randomly chosen subset of grid points used for generating reference distributions
For details regarding the data sets refer to the publication.

avalanche-forecast

display_name: avalanche-forecast

avalanche-release-probability

display_name: avalanche-release-probability

forecast-models

display_name: forecast-models

machine-learning

display_name: machine-learning

spatial-modelling

display_name: spatial-modelling

en: Evaluating the predictive performance of human avalanche forecasts and model predictions in Switzerland


present-weather-sensor-klosters

maintainer: Maxime Hervo

title_for_slug: present-weather-sensor-klosters

en: precipitation raclets visibility sensor weather

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

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.


de: Datenstruktur auf Englisch

en: Data structure in English

media_type: application/json

format: JSON

de: Datenstruktur auf Deutsch

en: Data structure in German

de: Datenwürfel auf Deutsch

en: Data cube in German

media_type: text/html

format: HTML

de: Datenwürfel auf Englisch

en: Data cube in English

de: Schulpersonal an Schulen bei Schuljahr, Schultyp, Personalkategorie und Geschlecht

en: School staff in schools by School year, School type, Category of staff and Sex

schools

display_name: schools

schulen

display_name: schulen

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

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

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

value: DCAT Harvester Amt für Statistik FL

de: Schulpersonal an Schulen nach Schuljahr, Schultyp, Personalkategorie und Geschlecht seit 2010/2011

en: School staff in schools by School year, School type, Category of staff, and Sex since 2010/2011


de: 463.002 Unfälle und Unfälle pro 1000 versicherte Beschäftigte nach Versicherungszweig und Art des Unfalls bei Jahr, Einheit, Versicherungszweig und Art des Unfalls

accident-insurers

display_name: accident-insurers

unfallversicherer

display_name: unfallversicherer

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

de: 463.002 Unfälle und Unfälle pro 1000 versicherte Beschäftigte nach Versicherungszweig und Art des Unfalls seit 2005


de: Erwerbstätige ständige Bevölkerung nach Jahr, Wirtschaftszweig, Geschlecht und Wohngemeinde

en: Permanent resident population in gainful employment by Year, Economic activity, Sex and Municipality of residence

erwerbstatigkeit

display_name: erwerbstatigkeit

population-in-gainful-employment

display_name: population-in-gainful-employment

de: Erwerbstätige ständige Bevölkerung nach Wirtschaftszweig, Geschlecht und Wohngemeinde seit 2006

en: Permanent resident population in gainful employment by economic activity, sex and municipality of residence since 2006


de: Steuerpflichtige Personen bei Jahr, Altersklasse, Einkommen und Einkommensklasse

en: Taxable persons by Year, Age group, Income and Income category

vermogens--und-einkommensverteilung

display_name: vermogens--und-einkommensverteilung

wealth-and-income-distribution

display_name: wealth-and-income-distribution

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

de: Steuerpflichtige Personen nach Einkommens- und Altersklasse seit 2020

en: Taxable persons by Income category and age group since 2020


de: Motorräderbestand nach Stichtag, Hubraumklasse und Gemeinde

fahrzeugbestand

display_name: fahrzeugbestand

licensed-vehicles

display_name: licensed-vehicles

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

de: Motorräderbestand nach Hubraumklasse und Gemeinde seit 2013


de: Datenwürfel auf Deutsch

de: Datenstruktur auf Deutsch

de: Datenwürfel auf Englisch

de: Datenstruktur auf Englisch

de: Wohneinheiten nach Stichtag, Gebäudeart, Eigentümertyp und Gemeinde

en: Housing units by Reference date, Type of building, Type of ownership and Municipality

buildings-dwellings

display_name: buildings-dwellings

gebaude-wohnungen

display_name: gebaude-wohnungen

de: Wohneinheiten nach Gebäudeart, Eigentümertyp und Gemeinde

en: Housing units by type of building, type of ownership and municipality


en: Data structure in German

de: Personenwagenbestand nach Stichtag, Hubraumklasse und Gemeinde

amt-fuer-statistik-fl

de: Amt für Statistik

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

de: Personenwagenbestand nach Hubraumklasse und Gemeinde seit 2013


en: Data structure in English

en: Data cube in German

de: Internes F+E-Personal bei Jahr, Sektor, Tätigkeit und Kennzahl

en: Internal R+D personnel by Year, Sector, Function and Key figure

forschung-und-entwicklung

display_name: forschung-und-entwicklung

research-and-development

display_name: research-and-development

tech

fr: Science et technologie

de: Wissenschaft und Technologie

en: Science and technology

it: Scienza e tecnologia

de: Internes F+E-Personal nach Sektor, Tätigkeit, Geschlecht und Staatsbürgerschaft seit 2019

en: Internal R+D personnel by sector, function, sex and citizenship since 2019


en: Data cube in English

de: Gestorbene bei Jahr, Geschlecht und Monat

en: Deaths by Year, Sex and Month

births-deaths

display_name: births-deaths

geburten-todesfalle

display_name: geburten-todesfalle

soci

de: Bevölkerung und Gesellschaft

amt-fuer-statistik-fl

en: Office of Statistics

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

de: Gestorbene nach Geschlecht und Monat seit 1999

en: Deaths by sex and month since 1999


de: Einzelbasis - Bilanz (Passiven) bei Jahr, Passiven, Währungsgebiet und Währung

en: Individual basis - Balance sheet (liabilities) by Year, Liabilities, Currency area and Currency

banken

display_name: banken

banking-institutions

display_name: banking-institutions

econ

de: Wirtschaft und Finanzen

en: Economy and finance

de: Einzelbasis - Bilanz (Passiven) nach Währungsgebiet und Währung seit 2017

en: Individual basis - Balance sheet (liabilities) by currency area and currency since 2017


de: Datenwürfel auf Deutsch

de: Datenstruktur auf Deutsch

de: Datenwürfel auf Englisch

de: Arbeitsplätze nach Jahr, Voll-/ Teilzeit, Wohnsitz, Arbeitsgemeinde und Geschlecht

en: Jobs by Year, Part-/ full-time, Place of residence, Municipality of work and Sex

enterprises-jobs

display_name: enterprises-jobs

unternehmen-arbeitsplatze

display_name: unternehmen-arbeitsplatze

de: Arbeitsplätze nach Voll-/ Teilzeit, Wohnsitz, Arbeitsgemeinde und Geschlecht seit 2008

en: Jobs by part-/ full-time, place of residence, municipality of work and sex since 2008


de: 463.003 Betriebsrechnung bei Jahr, Kennzahl und Versicherungszweig

accident-insurers

display_name: accident-insurers

unfallversicherer

display_name: unfallversicherer

heal

de: Gesundheit

en: Health

amt-fuer-statistik-fl

de: Amt für Statistik

de: 463.003 Betriebsrechnung in CHF nach Bilanzposition und Versicherungszweig seit 2005


maintainer: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

fr: BAG-OFSP-UFSP-FOPH Website

de: BAG-OFSP-UFSP-FOPH Website

en: BAG-OFSP-UFSP-FOPH Website

it: BAG-OFSP-UFSP-FOPH Website

fr: Salmonellose - système de déclaration obligatoire

de: Salmonellose - Obligatorisches Meldesystem

en: Salmonellosis - mandatory reporting system

it: Salmonellosi - 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 salmonellose 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 Salmonellose 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 salmonellosis 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 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

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: Salmonellose

de: Salmonellose

en: Salmonellosis

it: Salmonellosi


hepatitis-a

title_for_slug: hepatitis-a

name: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

fr: Hépatite A - système de déclaration obligatoire

de: Hepatitis A - Obligatorisches Meldesystem

en: Hepatitis A - mandatory reporting system

it: Epatite A - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle des cas d'hépatite A 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 hepatitis A 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 Hepatitis A 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 epatite A in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

epatite-a-ufsp

display_name: epatite-a-ufsp

hepatite-a-ofsp

display_name: hepatite-a-ofsp

hepatitis-a-bag

display_name: hepatitis-a-bag

hepatitis-a-foph

display_name: hepatitis-a-foph

fr: Hépatite A

de: Hepatitis A

en: Hepatitis A

it: Epatite A


tigermucken-bekampfungszone

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

title_for_slug: tigermucken-bekampfungszone

author: Landwirtschaft Aargau

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

it: geocat.ch link permanente

de: AGIS Direktdownload

de: Tigermücken Bekämpfungszone

de: Landwirtschaft Aargau

de: AGIS Service Center Kanton Aargau

de: Das AGIS Service Center unterstützt als kantonale Koordinationsstelle die Bereitstellung von Geoinformationen und Metadaten der kantonalen Verwaltung. Die zuständigen kantonalen Fachstellen stellen die öffentlichen Geodaten des Kantons Aargau mittels der Infrastruktur des AGIS Service Center in der Informatik Aargau als Webservices und zum Download bereit.

political_level: canton

value: Aargau-Kt - Geocat Harvester


knp-verkehr-festlegungen-flache

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

tran

de: Verkehr

en: Transport

title_for_slug: knp-verkehr-festlegungen-flache

author: Abteilung Verkehr

de: Der Datensatz enthält die flächenbezogenen überlagernden rechtskräftigen Festlegungen, die im Verfahren einer kantonalen Nutzungsplanung im Bereich Verkehr genehmigt worden sind: • Zu-/Wegfahrtbeschränkungen • Sondernutzungsvorschriften

de: Abteilung Verkehr

de: Kantonaler Nutzungsplan Verkehr: Festlegungen (Flächen)


kantonaler-nutzungsplan-verkehr

title_for_slug: kantonaler-nutzungsplan-verkehr

de: Kantonaler Nutzungsplan Verkehr: Perimeter

format: WMS

de: Der Datensatz bildet die Perimeter aller gültigen Kantonalen Nutzungspläne (KNP) im Bereich Verkehr mit rechtskräftigen Festsetzungen ab. Diese Pläne und die zugehörigen Vorschriften sind in der §10 des Baugesetzes, BauG (altrechtlich auch als "Überbauungspläne" bezeichnet) geregelt. Die KNP Verkehr decken die strategischen Freihalteinteressen für Strassenbauvorhaben ab. Ihre Festsetzungen sind öffentlich-rechtliche Eigentumsbeschränkungen (ÖREB); dieser Datensatz gehört zum Bereich Raumnutzung des ÖREB-Katasters. Sie können folgenden Festsetzungen enthalten: • Baulinien: sie gehen anderen Abstandsvorschriften vor. Sie treten an Stelle der generellen Abstandsvorschriften. Baulinien begrenzen die Bebauung und dienen, insbesondere der Sicherung bestehender und geplanter Anlagen und Flächen sowie der baulichen Gestaltung. • Sichtlinien • Zu-/Wegfahrtbeschränkungen • Strassenlinien • Sondernutzungsvorschriften


author: Abteilung Raumentwicklung

de: Nutzungsplanung: Grundnutzung (im Bauzonen- und Kulturlandplan)

de: Nutzungsplanung: linienbezogene Überlagerungen (im Bauzonen- und Kulturlandplan)

de: Nutzungsplanung: objektbezogene Überlagerungen (im Bauzonen- und Kulturlandplan)

de: Nutzungsplanung: flächenbezogene Überlagerungen inkl. Sondernutzungspläne (im Bauzonen- und Kulturlandplan)

de: Die Geobasisdaten richten sich nach dem minimalen Datenmodell des Bundes Nr. 73 Nutzungsplanung. Sie beinhalten Geoinformationen auf kommunaler, kantonaler und Bundes-Ebene.

de: Abteilung Raumentwicklung

de: 73C-CH Nutzungsplanung (kommunal)


agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

regi

de: Regionen und Städte

de: geocat.ch Permalink

de: AGIS Direktdownload

de: Die Polygone zeigen die 1 km-Umkreise um die Fundorte der invasiven Asiatischen Hornisse im Kanton Aargau.

de: Landwirtschaft Aargau

de: Asiatische Hornisse 1km Puffer


knp-verkehr-festlegungen-linien

envi

de: Umwelt

tran

de: Verkehr

title_for_slug: knp-verkehr-festlegungen-linien

de: Der Datensatz enthält die linienbezogenen überlagernden rechtskräftigen Festlegungen, die im Verfahren einer kantonalen Nutzungsplanung im Bereich Verkehr genehmigt worden sind: • Baulinien: sie gehen anderen Abstandsvorschriften vor. Sie treten an Stelle der generellen Abstandsvorschriften. Baulinien begrenzen die Bebauung und dienen, insbesondere der Sicherung bestehender und geplanter Anlagen und Flächen sowie der baulichen Gestaltung. • Sichtlinien • Zu-/Wegfahrtbeschränkungen • Strassenlinien

de: Abteilung Verkehr

de: AGIS Service Center Kanton Aargau

de: Das AGIS Service Center unterstützt als kantonale Koordinationsstelle die Bereitstellung von Geoinformationen und Metadaten der kantonalen Verwaltung. Die zuständigen kantonalen Fachstellen stellen die öffentlichen Geodaten des Kantons Aargau mittels der Infrastruktur des AGIS Service Center in der Informatik Aargau als Webservices und zum Download bereit.

de: Kantonaler Nutzungsplan Verkehr: Festlegungen (Linien)


maintainer: Immobilienamt des Kantons Zürich, Facility Management und Entwicklung

de: fahrzeuge elektrizitaet kantonzuerich

fr: RRB über die Beschaffung und Bewirtschaftung von Ladestationen für die Elektromobilität (RRB 1259/2020)

de: Ladevorgänge der kantonalen e-Ladestationen

de: Ladevorgänge der E-Ladestationen für die Elektrofahrzeuge der kantonalen Fahrzeugflotte. Die Ladestationen werden ausschliesslich durch die Betriebs- und Dienstfahrzeuge der kantonalen Verwaltung genutzt. Das Immobilienamt des Kantons Zürich bestellt und bewirtschaftet die E-Ladestationen für die Kantonale Verwaltung. Der Datensatz zeigt die einzelnen Ladevorgänge an, wie sie im System verzeichnet sind, es finden keine nachträglichen Korrekturen statt.

elektrizitaet

display_name: elektrizitaet

fahrzeuge

display_name: fahrzeuge

kantonzuerich

display_name: kantonzuerich

ima-kanton-zuerich

de: Immobilienamt des Kantons Zürich

de: Der Kanton Zürich verfügt über eines der grössten Immobilienportfolios der öffentlichen Hand in der Schweiz. Das Immobilienamt ist als Eigentümervertretung des Kantons mit der Steuerung, Entwicklung und Bewirtschaftung dieses Portfolios betraut.

value: DCAT Harvester Immobilienamt Kt. ZH

de: E-Ladestationen der kantonalen Verwaltung Zürich


maintainer: Service du Cadastre, Responsable de diffusion

name: Service du Cadastre, Gestionnaire de la donnée

fr: Métadonnée complète sur viageo.ch

de: Métadonnée complète sur viageo.ch

en: Métadonnée complète sur viageo.ch

it: Métadonnée complète sur viageo.ch

fr: Métadonnée sur geocat.ch

de: Métadonnée sur geocat.ch

en: Métadonnée sur geocat.ch

it: Métadonnée sur geocat.ch

fr: Guichet cartographique de Lausanne

fr: Guichet en ligne : Guichet cartographique de Lausanne

fr: LiDAR 2019 - Ombrage du MNT (GEOTIFF)

fr: Commander sur viageo.ch

fr: Télécharger sur viageo.ch

fr:
Cette carte d’ombrage est une image raster obtenue par ombrage du MNT qui offre une représentation précise du relief.

Ces ombrages ont été réalisés par la méthode standard : illumination virtuelle d’un azimut de 315° et une élévation de 45° sont appliquées. La grille est à 0.5m de résolution.

regi

de: Regionen und Städte

fr: Lausanne

lausanne

fr: Ville de Lausanne

fr: Le service de la mobilité et de l’aménagement des espaces publics (MAP) de la Ville de Lausanne publie ses géodonnées sous forme de fichiers à télécharger. Toutes les géodonnées actuellement disponibles et soumises aux conditions générales d'aquisition et d'utilisation des géodonnées de base en libre accès sont listées ici.

political_level: commune

value: Stadt Lausanne - DCAT Harvester

fr: LiDAR 2019 - Ombrage du MNT


de: geocat.ch Permalink

fr: WFS-Dienst des Kantons Schwyz

de: WFS-Dienst des Kantons Schwyz

en: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

format: WFS

fr: Planungszonen kommunal

de: Planungszonen kommunal

en: Planungszonen kommunal

it: Planungszonen kommunal

fr: Planungszonen kantonal

de: Planungszonen kantonal

en: Planungszonen kantonal

it: Planungszonen kantonal

fr: Planungszonen andere

de: Planungszonen andere

en: Planungszonen andere

it: Planungszonen andere

fr: ÖREB: Planungszonen kommunal

de: ÖREB: Planungszonen kommunal

en: ÖREB: Planungszonen kommunal

it: ÖREB: Planungszonen kommunal

fr: ÖREB: Planungszonen kantonal

de: ÖREB: Planungszonen kantonal

en: ÖREB: Planungszonen kantonal

it: ÖREB: Planungszonen kantonal

fr: ÖREB: Planungszonen andere

de: ÖREB: Planungszonen andere

en: ÖREB: Planungszonen andere

it: ÖREB: Planungszonen andere

fr: MGDM CH Datenmodell, geodienste.ch (INTERLIS, GeoPackage, Shapefile)

fr: MGDM CH Datenmodell, geodienste.ch

de: MGDM CH Datenmodell, geodienste.ch

en: MGDM CH Datenmodell, geodienste.ch

it: MGDM CH Datenmodell, geodienste.ch

fr: Planungszonen sind Gebiete, in denen ein vorsorgliche Bauverbot gilt. Müssen Nutzungspläne angepasst werden oder liegen keine vor, so kann die zuständige Behörde für genau bezeichnete Gebiete Planungszonen bestimmen. Innerhalb der Planungszonen darf nichts unternommen werden, was die Nutzungsplanung erschweren könnte. Planungszonen sind auf maximal 5 Jahre befristet. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB).

amt-geoinformation-sz

de: Das Amt für Geoinformation verwaltet und veröffentlicht die Geodaten des Kantons Schwyz als OGC-Geodienste und als Datei-Download. Alle aktuell verfügbaren Geodaten, welche dem OGD unterliegen, sind hier aufgeführt.


verkehrszahlung

regi

fr: Régions et villes

tran

fr: Transports

de: Verkehr

it: Trasporti

title_for_slug: verkehrszahlung

fr: geocat.ch permalien

fr: Verkehrszählung

de: Verkehrszählung

en: Verkehrszählung

it: Verkehrszählung

fr: Strassenverkehrszählung: Messstelle

de: Strassenverkehrszählung: Messstelle

en: Strassenverkehrszählung: Messstelle

it: Strassenverkehrszählung: Messstelle

fr: Das Tiefbauamt (TBA) betreibt auf dem Hauptstrassennetz des Kantons Schwyz Verkehrsmessstellen. Die erhobenen Daten dienen als wichtige Grundlage und Information für verkehrstechnische Aufgaben und Strassenbauprojekte. Weiter finden sie Anwendung im Verkehrsmodell und bei der Berechnung des Lärmbelastungskatasters und für Verkehrsauskünfte innerhalb der kantonalen Verwaltung als auch an Dritte. Die Kennwerte der permanenten Verkehrserhebung geben zudem Aufschluss über die Verkehrsentwicklung.

spatial: Kanton Schwyz (SZ)

fr: SZ Tiefbauamt

de: SZ Tiefbauamt

en: SZ Tiefbauamt

it: SZ Tiefbauamt

de: Amt für Geoinformation Kanton Schwyz

value: SZ-Kt Geoinformation - Geocat Harvester