en: typoch habitat milieux-naturels random-forest shrub-forest ensemble-modelling forest lebensraum remote-sensing grassland wetlands modelling lebensraumkarte

en: The Habitat Map of Switzerland FR v1 20220316, Canton Fribourg, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Fribourg, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland BS v1 20220316, Canton Basel-Stadt, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Basel-Stadt, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland GL v1 20220316, Canton Glarus, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Glarus, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland LU v1 20220316, Canton Lucerne, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Lucerne, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland SH v1 20220316, Canton Schaffhausen, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Schaffhausen, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland AG v1 20220316, Canton Aargau, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Aargau, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland SG v1 20220316, Canton St Gallen, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton St Gallen, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland CH v1 20220316, file geodatabase

en:
The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert).
V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: Data Description

en: Metadata document describing the methodology used to develop the dataset

en: The Habitat Map of Switzerland SZ v1 20220316, Canton Schwyz, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Schwyz, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland ZH v1 20220316, Canton Zurich, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Zurich, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland GE v1 20220316, Canton Geneva, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Geneva, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland TG v1 20220316, Canton Thurgau, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Thurgau, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland GR v1 20220316, Canton Grisons, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Grisons, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland NW v1 20220316, Canton Nidwalden, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Nidwalden, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland BL v1 20220316, Canton Basel-Landschaft, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Basel-Landschaft, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland NE v1 20220316, Canton Neuchatel, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Neuchatel, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland AR v1 20220316, Canton Appenzell Ausserrhoden , file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Appenzell Ausserrhoden, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland OW v1 20220316, Canton Obwalden, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to the borders of canton Obwalden, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert)

en: The Habitat Map of Switzerland VD v1 20220316, Canton Vaud, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Vaud, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland BE v1 20220316, Canton Bern, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Bern, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland JU v1 20220316, Canton Jura, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Jura, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland TI v1 20220316, Canton Ticino, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Ticino, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland UR v1 20220316, Canton Uri, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Uri, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland ZG v1 20220316, Canton Zug, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Zug, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland AI v1 20220316, Canton  Appenzell Innerrhoden, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Appenzell Innerrhoden, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland SO v1 20220316, Canton Solothurn, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Solothurn, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland VS v1 20220316, Canton Valais, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Valais, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en:
Lebensraumkarte der Schweiz/La carte des milieux naturels de Suisse
The FOEN funded project ‘Developing a Habitat Map of Switzerland’ conducted at the WSL, has produced a map of Swiss habitats according to the TypoCH classification (Delarze et al. 2015) wall-to-wall across the whole of Switzerland, to at least the classification’s 2nd level of detail (where possible to the 3rd level of detail). The implementation of the Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only.
Habitats are mapped through a variety of approaches that can be grouped as either:
1: Derived from the existing Swiss-wide high quality landcover mapping from Swisstopo’s Topographical Landscape Model (TLM), 2: Modelled within the project using Random Forest or Ensemble Modelling techniques to model the spatial distribution of individual habitat types, 3: Combining existing species distribution models to determine habitat types, or 4: Classification with relatively simple rule-sets based on auxiliary spatial datasets, i.e. vegetation height models, the digital terrain model, the normalised difference vegetation index (NDVI) derived from aerial imagery and/or time-series of growing season Sentinel-2 satellite imagery. Further detail on the methodology can be found within the README document.

ensemble-modelling

display_name: ensemble-modelling

forest

display_name: forest

grassland

display_name: grassland

habitat

display_name: habitat

lebensraum

display_name: lebensraum

lebensraumkarte

display_name: lebensraumkarte

milieux-naturels

display_name: milieux-naturels

modelling

display_name: modelling

random-forest

display_name: random-forest

remote-sensing

display_name: remote-sensing

shrub-forest

display_name: shrub-forest

typoch

display_name: typoch

wetlands

display_name: wetlands


maintainer: EnviDat Support

en: antarctica meteorological-data large-eddy-simulations eddy-covariance-measurements blowing-snow turbulence micro-rain-radar drifting-snow mass-flux

state: active

type: dataset

en: Simulation data for a situation with significant snow transport

en: Data from two LES-LSM simulations called Drift_1 and Drift_2, which reproduce the conditions observed at the S17 site on 11th January 2019, 00:40 to 00:50 UTC.

format: SERVICE

en: Readme

media_type: text/plain

en: Meta data

format: TXT

en: Simulation data for a situation with negligible snow transport

en: Results from two LES-LSM simulations called NoDrift_1 and NoDrift_2, which reproduce the conditions observed at the S17 site on 12th January 2019, 05:40 to 05:50 UTC.

en: Measurement data from Micro Rain Radar (MRR)

en: Remote sensing data of blowing snow from a Micro Rain Radar (MRR).

en: Measurement data from micro-meteorological station

en: Automatic in-situ measurements of micro-meteorology and snow transport

en: Source code of the large-eddy simulations coupled with a Lagrangian stochastic model (LES-LSM), available on GitLab.

en: Measurement data from snow particle counter at MRR site

en: Near-surface observations of drifting snow from a Snow Particle Counter (SPC) installed at the location of the Micro Rain Radar.

en:
This dataset contains measurement and simulation data. The measurements characterize the standard meteorology, turbulence, and snow transport at the S17 site near Syowa Station in East Antarctica during an expedition in austral summer 2018/2019. Large-eddy simulations with sublimating particles provide additional insight into the latent and sensible heat exchange between snow and air in two example situations observed at the S17 site.

A part of the measurement data was recorded by an automatic measurement station from 10th January 2019 to 26th January 2019. This measurement station was equipped with standard meteorological sensors, a three-dimensional ultrasonic anemometer, an open-path infrared gas analyzer, a snow particle counter, an infrared radiometer for measurements of the surface temperature, and a sonic ranging sensor measuring changes in snow surface elevation.

At a horizontal distance of approximately 500 m, a Micro Rain Radar (MRR) was installed in a tilted configuration with an elevation angle of 7° for remote sensing of blowing snow between 25th December 2018 and 24th January 2019. In addition, near-surface in-situ measurements of snow transport were performed at the location of the MRR by deploying a snow particle counter from 27th December 2018 to 24th January 2019.

The simulations cover a 18 x 18 x 6 m³ domain and reproduce the steady-state conditions during a 10-min interval with significant snow transport and another 10-min interval with negligible snow transport. We provide the model source code and the post-processed simulation data, i.e., horizontally averaged quantities as a function of height and time.

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

drifting-snow

display_name: drifting-snow

eddy-covariance-measurements

display_name: eddy-covariance-measurements

large-eddy-simulations

display_name: large-eddy-simulations

mass-flux

display_name: mass-flux

meteorological-data

display_name: meteorological-data

micro-rain-radar

display_name: micro-rain-radar

turbulence

display_name: turbulence

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Meteorology and snow transport at S17 near Syowa, Antarctica, in austral summer 2018/2019


en: oshd seasonal-snow-data snow-cover-fraction snow-depth-distribution snow-melt

en: Data Access

en: This dataset includes gridded data on snow depth (m), snow water equivalent (mm), runoff from snow melt (mm) and snow cover fraction for Swtzerland. The data is spanning the water years 2016-2022 at a high spatial resolution of 250 m. Data are stored as daily results.

oshd

display_name: oshd

seasonal-snow-data

display_name: seasonal-snow-data

snow-cover-fraction

display_name: snow-cover-fraction

snow-depth-distribution

display_name: snow-depth-distribution

snow-melt

display_name: snow-melt

en: Seasonal snow data for Switzerland OSHD - FSM2sohd


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

en: Illgraben debris-flow characteristics 2019-2022

media_type: application/zip

format: ZIP

en:
List of key debris flow variables from the WSL Illgraben monitoring station (2019-2022) such as occurrence date and time, peak flow depth, peak flow velocity, total volume and bulk density.
This table contains values based on our current analysis methods. The list will be updated annually after each debris flow season, and as our methods continue to improve, individual values may change slightly in the future.

debris-flow

display_name: debris-flow

force-plate

display_name: force-plate

illgraben

display_name: illgraben

magnitude

display_name: magnitude

monitoring-station

display_name: monitoring-station


biomass-of-lying-dead-trees

title_for_slug: biomass-of-lying-dead-trees

en:
Dry weight (mass) of dead, lying trees and shrubs starting at 12 cm dbh. This consists of the tree parts: roots, stemwood and also, depending on the degree of decomposition of the stem, the branch coarse wood.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

biogeographical-region

display_name: biogeographical-region

biomass-of-lying-dead-trees

display_name: biomass-of-lying-dead-trees

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

en: Biomass of lying dead trees


maintainer: Matthias Haeni

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

en: Data plot of the forest station (CIB)

media_type: application/pdf

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

format: PDF

mimetype: application/pdf

en: Site aerial photo (Chironico)

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

mimetype: image/jpeg

en: Site photo of the field station (CIF)

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

en: Data plot of the field station (CIF)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Site photo of the forest station (CIB)

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

en: Forest station data (CIB)

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 Chironico in Switzerland where one station is located within a natural coniferous forest stand (CIB) with Norway spruce (_Picea abies_; 160-180 yrs) and European silver fir (_Abies alba_; 140-160 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CIF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Chironico 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: Chironico, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 2000 onwards


data-analysis-toolkits

title_for_slug: data-analysis-toolkits

en: hypothesis-testing error-propagation uncertainty data-analysis bayesian-inference statistics

en: Toolkit 11: serial correlation

en: Tools for detecting and correcting for serial correlation in analyses of time series

en: Toolkit 1: graphically displaying data distributions

en: toolkit 6: averaging in nonlinear functions

en: The average of a nonlinear function will not equal the function evaluated at its average inputs (the mean of the function will differ from from the function of the mean). This toolkit shows how to estimate that averaging bias.

en: Toolkit 10: linear regression

en: An overview of the math, logic, and pitfalls of ordinary least-squares linear regression

en: Toolkit 8: Hodges-Lehmann estimators

en: A quick introduction to Hodges-Lehmann estimators (nonparametric measures of effect size)

en: Toolkit 9: Experimentwise error rates and statistical fishing expeditions

en: Statistical fishing expeditions, and how to avoid being misled by them

en: Toolkit 12: weighted averages and their uncertainties

en: There are two different ways to calculate the uncertainty of a weighted average. Software packages often don't tell you which one they are reporting, and the resulting errors can be huge.

en: Toolkit 2: quantifying data distributions using descriptive statistics

en: Toolkit 3: tools for transforming data

en: The ladder of powers and a few other cool transformations

en: Toolkit 4: confidence intervals

en: Toolkit 5: uncertainty analysis and error propagation

en: Gaussian error propagation, monte carlo methods, and first-order, second-moment error propagation

en: Toolkit 7: hypothesis testing, significance, and power

en: An overview of basic concepts -- and common pitfalls -- in statistical hypothesis testing, statistical significance, and power analysis

en:
These are condensed notes covering selected key points in data analysis and statistics. They were developed by James Kirchner for the course "Analysis of Environmental Data" at Berkeley in the 1990's and 2000's. They are not intended to be comprehensive, and thus are not a substitute for a good textbook or a good education!

License: These notes are released by James Kirchner under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.

bayesian-inference

display_name: bayesian-inference

data-analysis

display_name: data-analysis

error-propagation

display_name: error-propagation

hypothesis-testing

display_name: hypothesis-testing

statistics

display_name: statistics

uncertainty

display_name: uncertainty

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: Data analysis toolkits


en: forest-inventory single-tree terrestiral-laserscanning biomass tree-volume lidar

en: Individual tree parameters and volume estimates based on TLS point clouds and allometric models

en:
"ASM" denotes volume estimates calculated by allometric scaling models (as used in Swiss NFI), based on tree height, DBH and D7.
"QSM" denotes volume estimates derived from TLS point clouds by quantitative structure models (QSM).
The remaining variables are geometrical features directly calculated from single tree TLS point clouds.
For more detailed variable descriptions see related publication.

en:
 Dataset
This dataset is based on terrestrial laser scanning (TLS) data acquired during winter 2020/2021 in leaf-off conditions, with a Leica BLK 360 instrument following a tree-centric scanning pattern.
The data was acquired on two sites (47.42°N 8.49°E and 47.504°N, 7.78°E), both of which were managed mixed temperate forest stands.
Individual trees were semi-automatically segmented from the co-registered TLS point clouds.

 Background
Accurate estimates of individual tree volume or biomass within forest inventories are essential for calibration and validation of biomass mapping products based on Earth observation data.
Terrestrial laser scanning (TLS) enables detailed and non-destructive volume estimation of individual trees, with existing approaches ranging from simple geometrical features to virtual 3D reconstruction of entire trees. Validating such approaches with weight measurements is a key step before the integration of TLS or other close-range technologies into operational applications such as forest inventories.
In this study, we firstly evaluate individual tree volume estimation approaches based on 3D reconstruction through quantitative structure models (QSM) against destructive reference data of 60 trees and compare them to operational allometric scaling models (ASM).
Secondly, we determine the explanatory power of TLS-derived geometric parameters regarding total tree, stem, coarse wood and fine branch volume.

biomass

display_name: biomass

forest-inventory

display_name: forest-inventory

lidar

display_name: lidar

single-tree

display_name: single-tree

terrestiral-laserscanning

display_name: terrestiral-laserscanning

tree-volume

display_name: tree-volume

en: Individual tree TLS point clouds for tree volume estimation


lwf-novaggio-long-term-research-site

title_for_slug: lwf-novaggio-long-term-research-site

en: forest meteorological-data lwf meteorological-measurements swiss-forest-lab plot infrastructure

en: Novaggio Meteorological Data LWF

en: LWF plot Novaggio. Photo: Peter Waldner, 2010

en:
![alt text](https://www.envidat.ch/dataset/e87358e9-4beb-487e-af68-66633e9cfc96/resource/91bd053a-61c4-4b20-b0d3-a572c983e647/download/lwf_novaggio.jpg "LWF Novaggio")

LWF Plot Novaggio

- Community: Novaggio / canton TI
- Date of installation: 8.3.95
- Size of the plot: 1.5 ha
- Altitude (m): 902-997
- Mean slope: 68%
- Geology (in German): Untergrund: Südalpin, präpermisches Grundgebirge; Orthogneis, schiefriger Biotitplagioklasgneis - Oberfläche: Quartär; karbonatfreie würmeiszeitliche Moräne
- Provisional soil type (WSL): Kryptopodzole
- Woodland association after EK72: 42: Phyteumo betonicifoliae-Quercetum castanosum
- Main tree species: Quercus cerris
- Management system: former coppice
- Silvicultural system: unmanaged
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 27.0 cm
- Number of trees BHD >= 12 cm (2011): 1130
- Maximum tree age: Castanea sativa 90 yr- Betula pendula 70 yr - Quercus cerris 70 yr

More Information: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf/sites/novaggio.html

forest

display_name: forest

infrastructure

display_name: infrastructure

lwf

display_name: lwf

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

plot

display_name: plot

en: LWF Novaggio long-term research site


maintainer: Milojevic

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

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: Jana von Freyberg

en: stable-water-isotope precipitation alptal catchment stream-water hydrology

en:
Version 2 of the dataset contains additional information on:
- line-conditioned (lc) excess
- precipitation sample volumes
- isotope data quality

en: Data Set Documentation: alptal_Isotopes_daily_2015-2019_v2

en: Documentations contains meta data of the data columns and information about the study catchments.

en: Single comma-separated txt-file with daily data of stable water isotopes measured in streamwater and precipitation in the Swiss Alptal catchment and two of its tributaries (Erlenbach and Vogelbach), as well as daily data of key hydrometeorological variables from the Alptal valley

en: This dataset contains four years of daily measurements of the natural isotopic composition (2H, 18O) of precipitation and stream water at the Alp catchment (area 47 km2) in Central Switzerland and two of its tributaries (0.73 km2 and 1.55 km2). In addition, the dataset contains daily measurements of key hydrometeorological variables.

alptal

display_name: alptal

catchment

display_name: catchment

hydrology

display_name: hydrology

precipitation

display_name: precipitation

stable-water-isotope

display_name: stable-water-isotope

stream-water

display_name: stream-water

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: Four years of daily stable water isotope data in stream water and precipitation from three Swiss catchments


en: pinus tomicus bark-beetles phaenops decline ips-acuminatus pissodes defoliation sirex wood-wasps

en: see ReadMe

en: After a major dieback of Scots pines in the Valais, an inner Alpine valley in Switzerland, the colonization of differently vigorous pines by stem and branch insects was investigated to assess their role in tree mortality. At 2 locations, the needle loss (defoliation) of some 500 pine trees was assessed twice a year. Of these trees, 34-36 trees were cut each year between 2001-2005 across all defoliation classes. From each tree, two 75-cm bolts were cut from both the stem and thick branches. They were incubated in photo-eclectors (metal cabinets) set up in a greenhouse where the insects could develop under the bark. The emerged adults were collected in water-filled eclector boxes and identified to species level by specialists. Attack time was estimated from the development time of each insect species emerged. The colonisation densities of the trees were related to the transparency level of each host tree at the time of attack.

bark-beetles

display_name: bark-beetles

decline

display_name: decline

defoliation

display_name: defoliation

ips-acuminatus

display_name: ips-acuminatus

phaenops

display_name: phaenops

pinus

display_name: pinus

pissodes

display_name: pissodes

sirex

display_name: sirex

tomicus

display_name: tomicus

wood-wasps

display_name: wood-wasps

en: Infestation of Scots pines with different vitalities by bark and wood boring insects


en: hydrology soil-moisture-water-content landslides meadow water-table

en: Data Soil water content TDR.xlsm

en: Four test pits were excavated in summer 2010 along the slope to install vertical profiles of Time Domain Reflectometry sensors [Topp et al., 1980] to measure soil water content at depths of 0.25 m, 0.7 m, 1.1 m and 1.5 m. The 15 cm long TDR rods were inserted horizontally into the vertical walls of the pits, and the four pits were carefully refilled with the excavated soil. The water content was recorded from summer 2010 to fall 2011 at 10-minute time intervals using a Campbell TDR 100 system.

en: Data Lateral subsurface water flow.xlsm

en: Data Groundwater level in Soil.xlsx

format: XLS

en: Data Groundwater level in Bedrock.xlsx

en: We drilled six boreholes in two clusters. The boreholes reached a depth between 2 and 9 m below the ground surface. The lower half of boreholes BH1 and BH6 were cored with a 9 cm-diameter rotational diamond drilling head. The other boreholes were drilled destructively with an 11 cm-diameter Mitsubishi hammer system. Boreholes BH1, BH2 and BH5 were equipped with open standpipe piezometers, whereas BH3, BH4 and BH6 were equipped with a special piezometer system composed of an enclosed measuring cell at the bottom of a 1 inch-PVC tube. The free groundwater level in the PVC tube is measured in the standpipe piezometer, but it doesn’t necessarily represent the water table in the soil layer because the pressure sensor is located in the sealed lower part of the piezometer in the enclosed measuring cell and thus is not in contact with the air. This system allows the hydraulic pressure of lithologies with low permeability to be measured directly. Two piezometers were installed in BH6 at different depths. The PVC tubes were slotted at the bottom for 0.5, 1 or 2 meters and the boreholes were sealed carefully with clay pellets above this filter section to avoid by-pass and infiltration from the surface. DCX-22 pressure sensors from Keller AG Winterthur, with integrated data loggers, were installed in each piezometer to measure the relative hydraulic pressure at a 30 minute-intervals from November 2010 to November 2011. The data were corrected for in-situ air-pressure fluctuations.

en:
Rufiberg is a pre-alpine meadow site in Switzerland where shallow landslides have been observed after past intense rain storms. In order to assess the triggering mechanisms of these landslides, a comprehensive investigation was conducted within the project TRAMM from Nov 2009 to Oct 2012. It included meteorological observations, soil moisture measurements, bedrock groundwater measurements. The Rufiberg is located at the NW side of the Gnipen to the north of the village Arth-Goldau in the Canton of Schwyz. In the summer months, the site is used for pasturing. Usually, from December to March a snow cover is present at the Rufiberg. The site is at an altitude between 1080 – 1180 m asl, is ENE oriented, and has an average slope of 30 -35°. The Subalpine Molasse in the region is inclined with 30 - 35° to SE. In the area of the field site, beds of conglomerate with several m of thickness alter with beds of sandstone and marlstone. A ca. 2 – 5 m thick eluvium/colluvium layer composed of silty and sandy clay covers the bedrock. This site has been chosen because on one hand, during heavy rainfall events, e.g. autumn 2005, numerous landslides occur in the region of the Gnipen and the Rufiberg. On the other hand, the Rufiberg is very appropriate for experiments due its location away from infrastructures and due to its accessibility. The goal of the investigation was to understand the hydrology and hydrogeology of the slope with regard to shallow landslides.

More information: Brönnimann, C., Stähli, M., Schneider, P., Seward, L. and Springman, S.M. 2013. Bedrock exfiltration as a triggering mechanism for shallow landslides. Water Resources Research, 49 (9): 5155–5167. DOI: 10.1002/wrcr.20386.

landslides

display_name: landslides

meadow

display_name: meadow

soil-moisture-water-content

display_name: soil-moisture-water-content

water-table

display_name: water-table

en: TRAMM project - experimental hydrological and hydrogeological dataset of a landslide prone hillslope. Rufiberg, Switzerland


maintainer: Giulia Francesca Azzurra Donati

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

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: 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: 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

educ

en: Education, culture and sport

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


stemflow-lwf

title_for_slug: stemflow-lwf

en: icp-forests long-term-forest-ecosystem-research swiss-forest-lab stemflow chemical-composition

en: Data Request

en:
Stemflow (portion of precipitation running down the branches and the trunk and depositing at the base of the tree) can represent a substantial fraction of the total water and nutrient input in stands of smoothbarked species with upright branches. Stemflow was measured with silicone gutters installed on the trunk of 5 trees at three LWF plots during 1-2 years. High capacity containers were used at Novaggio. An automated tipping bucket system, allowing continuous recording of volumes and sampling of representative proportional fraction, is currentlx used at the LWF sites Laegeren, Lausanne, Othmarsingen and Schänis.

 Purpose:

To quantify the contribution of stemflow to the water and nutrient budget and to the atmospheric deposition in selected forests stands.

 Manual Citation:

 * Thimonier, A., Brang, P., Wenger, K., 1997. Kapitel C4. Atmosphärische Deposition: Freiland- und Bestandesniederschläge, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-48.

 * Clarke N, Žlindra D, Ulrich E, Mosello R, Derome J, Derome K, König N, Lövblad G, Draaijers GPJ, Hansen K, Thimonier A, Waldner P, 2016: Part XIV: Sampling and Analysis of Deposition. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute  of  Forest  Ecosystems,  Eberswalde,  Germany,  32  p.  +  Annex  [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)

chemical-composition

display_name: chemical-composition

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

stemflow

display_name: stemflow

swiss-forest-lab

display_name: swiss-forest-lab

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: Stemflow LWF


en: xml semantic numerical-model gui generation ini

en: Release 2.0.4 from https://models.slf.ch/p/inishell-ng/source/tree/v2.0.4/

en: This is the source code of the Inishell-2.0.4 flexible Graphical User Interface. It is configured through an XML file for applications that themselves need to be configured via ini-files. It allows to set constraints regarding the sections, keys and values that may be present in the ini-files that are produced by the end user. It is released under the GPL-v3 or later license. Precompiled binaries are available at https://models.slf.ch/p/inishell-ng/downloads/ while the development takes place at https://code.wsl.ch/snow-models/inishell (gitlab forge).

generation

display_name: generation

gui

display_name: gui

ini

display_name: ini

numerical-model

display_name: numerical-model

semantic

display_name: semantic

xml

display_name: xml


maintainer: Leonie Schönbeck

en: fluorescence photosynthesis vpd acclimation gas-exchange drought pinus-sylvestris

en: Variable names and units

en: Variable names, description and units for the Pfynwald Gas exchange data

en: Methods ACi curves

en:
Parameters and methods for CO2 response curves of Photosynthesis.

Metatdata format by
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Pfynwald gas exchange

en:
Full dataset of Pfynwald gas exchange data taken in the period from June 2013 to October 2020.
All metdata can be found in attached documents.
Data uploaded after quality control using guidelines by Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Methods survey

en: Parameters and methods for point measurements / survey measurements

en: Methods fluorescence

en:
Parameters and methodology for Fluorescence measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Methods diurnal measurements

en:
Parameters and methodology for diurnal measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Methods light response

en: Methods and parameters for light response curves

en: Instrument details

en:
Instrument details for all LiCor instruments used during collection of dataset.

Metatdata created following guidelines from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds.
All metadata can be found in the attached documents.

acclimation

display_name: acclimation

drought

display_name: drought

fluorescence

display_name: fluorescence

gas-exchange

display_name: gas-exchange

photosynthesis

display_name: photosynthesis

pinus-sylvestris

display_name: pinus-sylvestris

vpd

display_name: vpd

en: 2013-2020 gas exchange at Pfynwald


number-of-young-forest-plants-by-damage

title_for_slug: number-of-young-forest-plants-by-damage

en:
Number of regeneration trees starting at 10 cm height up to 11.9 cm dbh with a particular type of damage or with no damage. The attribute is recorded by targeting the next regeneration tree in the centre of the subplot during NFI’s regeneration survey. A regeneration tree may have more than one type of damage, which means it may contribute to the total number of regeneration trees for several different types of damage.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

damage-of-young-forest-plant

display_name: damage-of-young-forest-plant

economic-region

display_name: economic-region

number-of-young-forest-plants-by-damage

display_name: number-of-young-forest-plants-by-damage

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

young-forest-plant-class

display_name: young-forest-plant-class

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: Number of young forest plants by damage


title_for_slug: diversity-of-woody-species

en:
Index based on the number of tree and shrub species starting at 12 cm dbh in the upper layer and the occurrence of especially ecologically valuable tree and shrub species starting at 12 cm dbh in the upper layer.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

altitudinal-vegetation-zone

display_name: altitudinal-vegetation-zone

diversity-of-woody-species

display_name: diversity-of-woody-species

en: Diversity of woody species


stem-number

title_for_slug: stem-number

en:
Number of stems of living trees and shrubs (standing and lying) starting at 12 cm dbh.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

conifers-broadleaves

display_name: conifers-broadleaves

diameter-classes

display_name: diameter-classes

exotic-species-neophytes

display_name: exotic-species-neophytes

forest-type-and-stage-of-development

display_name: forest-type-and-stage-of-development

important-exotic-species-neophytes

display_name: important-exotic-species-neophytes

lower-higher-altitudinal-zones

display_name: lower-higher-altitudinal-zones

main-tree-species

display_name: main-tree-species

number-of-damages

display_name: number-of-damages

ownership

display_name: ownership

stage-of-stand-development

display_name: stage-of-stand-development

stem-number

display_name: stem-number

tree-species-woody-species

display_name: tree-species-woody-species

en: Stem number


en: swiss-forest-lab plot lwf meteorological-measurements infrastructure forest meteorological-data

en: LWF plot Bettlachstock. Foto: Matthias Haeni, 2019

en: Bettlachstock Meteorological Data LWF

en:
![alt text](https://www.envidat.ch/dataset/8f67193b-12cf-4871-9a9e-750b816e9d10/resource/b05db334-5bf6-42d6-a985-a5253366259d/download/lwf_bettlachstock.jpg "LWF Bettlachstock")

LWF Plot Bettlachstock

- Community: Bettlachstock / canton SO
- Date of installation: 6 June 1995
- Size of the plot: 1.28 ha
- Altitude: 1101-1196 m
- Mean slope: 66%
- Geology (in German): Kettenjura; Jura: Dogger, oberer Hauptrogenstein
- Soil types (WSL) : Rendzic Leptosols; Calcaric Cambisols
- Woodland association after EK72: 13 h: Cardamino-Fagetum tilietosum
- Main tree species: Fagus sylvatica
- Management system: high forest
- Silvicultural system: forest reserve
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 49.5 cm
- Number of trees BHD >= 12 cm (2011): 632
- Maximum tree age: Fagus sylvatica 170-190 yr - Picea abies 200 yr - Fraxinus excelsior 170 yr - Ulmus glabra 160 yr - Abies alba 190 yr

More Information: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf/sites/bettlachstock.html

forest

display_name: forest

infrastructure

display_name: infrastructure

lwf

display_name: lwf

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

plot

display_name: plot

swiss-forest-lab

display_name: swiss-forest-lab

en: LWF Bettlachstock long-term research site


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

en: Data plot of the forest station (CLB)

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

en: Site photo of the forest station (CLB)

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

en: Site photo of the field station (CLF)

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

en: Data file.

en: Data plot of the field station (CLF)

en: Site aerial photo (Celerina)

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

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 Celerina in Switzerland where one station is located within a natural coniferous forest stand (CLB) with Swiss pine (_Pinus cembra_; 210-250 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CLF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Celerina 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

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


maintainer: Thorsten Bartels-Rausch

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

en: Acetone data

en:
intensity of the acetone-water-cluster and water-cluster (as derived by a chemical ionisation mass spectrometer) with time in the carrier gas downstream of packed bed flow tube holding the snow sample or the by-pass, respectively. Time "0" denotes the time when the mass spectrometer data acquisition was started. When the carrier
gas with acetone was passed via the packed bed flow tube, that is switched from by-pass to pass the snow, acetone concentration in the carrier gas rapidly dropped due to surface adsorption and slowly recovered as the adsorption sites saturate. From this, the surface area can be obtained.

en: Matlab Data

en: All data as Matlab mat file

en: Readme file

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

en: Matlab Script to view and plot data

en: Ozone data

en: Trend of ozone mixing ratio ( _O3mixingRatio_ppb_ with time ( _time_s_ ) as measured downstream of the snow sample during the experiments. Time "0" denotes the time when data acquisition with ozone analyser was started. And, ozone (_nOzone_molec_per_s_ ) loss for each experiment with duration of ozone exposure ( _duration_s_ ) of ozone exposure, as derived from the ozone trends shown above. Time "0" denotes the time when the carrier gas with ozone was passed via the snow sample.

en: Data Figure 1

en: Data of published Figure

en: data list

en: Lists file names, snow sample properties, and flow settings for each data-set.

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

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


en: microstructure weissfluhjoch specific-surface-area density snow-stratigraphy snowmicropen

en: Link to data

en: README

en: Top level README file explaining the organization of the data

en:
The WFJ_RHOSSA dataset contains multi-instrument, multi-resolution snow stratigraphy measurements for the seasonal evolution of the snowpack from the Weissfluhjoch research site, Davos, Switzerland.

The measurements were initiated during the RHOSSA field campaign conducted in the winter season 2015–2016 with a focus on density (RHO) and specific surface area (SSA) measurements.

The Instruments and methods used in the campaign at different spatial and temporal resolution are: SnowMicroPen, Density Cutter, IceCube, Traditional profiles, Stability tests and X-ray tomography. The measurements are complemented by simulation data from the model SNOWPACK.

density

display_name: density

microstructure

display_name: microstructure

snow-stratigraphy

display_name: snow-stratigraphy

snowmicropen

display_name: snowmicropen

specific-surface-area

display_name: specific-surface-area

weissfluhjoch

display_name: weissfluhjoch

en: WFJ_RHOSSA: Multi-instrument stratigraphy data for the seasonal evolution of an alpine snowpack


en: lichen biodiversity switzerland lichen-conservation swisslichens lichen-distribution national-data-centre

en: data extract 20191113

en:
This dataset provides distribution data of lichens in Switzerland of the National Data and Information Centre, called Swiss Lichens. SwissLichens is a partner of InfoSpecies, the network of Swiss data and information centres for fauna, flora and fungi. One of its main objectives is to document the spatial and temporal distribution of species in Switzerland.

The SwissLichens database currently contains more than 120’000 georeferenced lichen observations, distributed throughout Swizerland. The oldest observations date back to 1790. A large portion of the records dtae from the last two decades of the last century to the present day. The database is continuously updated with new findings. The data have been validated and originate from national inventories, from research projects, from floristic observations by volunteers as well as from private and public herbaria and from the literature.

Each record consists of the species name, information of the location (Swiss Coordinates, precision of the coordinates, elevation above sea level, municipality and canton), the date of observation, the ecotype (epiphytic, terricol, lignicol, saxicol), as well as information on the conservation status of the species (red list status, conservation priority status, status in the Nature and Cultural Heritage Act). Information on the ecology (habitat, substrate) is partially available.
They are free of charge for research projects and can be requested from InfoSpecies using a form.

Licence under www.infospecies.ch. Data is free of charge for research projects and available on request.

biodiversity

display_name: biodiversity

lichen

display_name: lichen

lichen-conservation

display_name: lichen-conservation

lichen-distribution

display_name: lichen-distribution

national-data-centre

display_name: national-data-centre

swisslichens

display_name: swisslichens

switzerland

display_name: switzerland

en: SwissLichens - Distribution of lichens in Switzerland


maintainer: Mahdi Jafari

en: openfoam numerical-simulation vapor-transport snow-density-profile convection-in-snow

en: snowpackBuoyantPimpleFoam

en:
This zipped folder includes (1) the source code files, (2) an example case for simulation, and (3) an instruction how to compile and use the new solver.

Note that the most updated version of snowpackBuoyantPimpleFoam can be found in the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/snow-models/snowpackbuoyantpimplefoam

en: snowpackBuoyantPimpleFoam is a two-phase solver implemented to model convection of water vapor with phase change in snowpacks. This new solver is based on the standard solver of buoyantPimpleFoam in the open-source fluid dynamics software, OpenFOAM 5.0 (www.openfoam.org).

convection-in-snow

display_name: convection-in-snow

numerical-simulation

display_name: numerical-simulation

openfoam

display_name: openfoam

snow-density-profile

display_name: snow-density-profile

vapor-transport

display_name: vapor-transport

en: snowpackBuoyantPimpleFoam: an OpenFOAM Eulerian–Eulerian two-phase solver for modelling convection of water vapor in snowpacks


en: atmospheric-conditions precipitation wind radiation temperature-profiles

en: Latest data from Stillberg climate station

en: This dataset is outdated and has been replaced with an updated version (see description).

en: Site photo 1

en: This site photo is outdated and has been replaced with an updated version (see description).

en: Overview plot

media_type: image/png

en: This overview plot is outdated and has been replaced with an updated version (see description).

format: PNG

en: DATA ACCESS

en: This data access is outdated and has been replaced with an updated version (see description).

en: STB2 CSV

en: This description is outdated and has been replaced with an updated version (see description).

en: Site photo 3

en: Site photo 2

en:
 Important

This EnviDat entry is outdated. The most recent, usable version of the data can be found under the new EnviDat entry "Long-term meteorological station Stillberg, Davos, Switzerland at 2090 m a.s.l.." The entry can be found under this link <https://www.envidat.ch/dataset/meteo-stillberg> and with this DOI https://doi.org/10.16904/envidat.396.

atmospheric-conditions

display_name: atmospheric-conditions

precipitation

display_name: precipitation

radiation

display_name: radiation

temperature-profiles

display_name: temperature-profiles

wind

display_name: wind

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: Long-term meteorological and snow station at 2090 m a.s.l., Stillberg, Davos, Switzerland (1975 - present)


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

en: Site aerial photo (Bettlachstock)

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

en: Site photo of the forest station (BTB)

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

en: Data plot of the field station (BTF)

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

en: Data plot of the forest station (BTB)

en: Data file.

en: Site photo of the field station (BTF)

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

en: Field station data (BTF)

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 Bettlachstock in Switzerland where one station is located within a natural mixed forest stand (BTB) with European beech (_Fagus sylvatica_; 170-190 yrs), European silver fir (_Abies alba_; 190 yrs) and Norway spruce (_Picea abies_; 200 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Bettlachstock is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


en: insect-decline long-term switzerland time-series biodiversity

en: Climate data

en: Additional climate data on climate trend

en: Body size lookup-table

en: Syrphidae

en: Climate data of the respective sampling years

en: Data extract from WSL Fauna Database containing arthropod species and abundance data from 1987, 1997, 2019

en: Sites and traps

en: Lookup table of trap and site locations

en: Coleoptera

en: Species incidence per year

en: Total abundance of species per year

en: Fused catching data 1987, 1997, 2019

en: Complete dataset of species and abundances per year an trap

en: Master thesis of Regula Gygax, 1999, at University of Zürich

en: The study is comparing in 1997 the trapping efficiency of a newly developed combination trap with traditional window traps and yellow pan traps. Study locations in the Limpach valley matched with a subset from a larger study, which was conducted in 1987.

en: Input data - species list and trophic guilds

en: List of found species and associated trophic guild

en: Neuropteroidae

en: Staphylinidae

en: R code

en: R code for data analyses

en: Capture data with size and mass

en: Complete capture data including body sizes and biomass values

en: Aculeata

en: R code for data editing

en: Species number and abundances per trap

en: Sum of species and abundances listed per trap

en: SQL query executed on WSL Fauna Database to retrieve the data

en:
Recent publications about declines in arthropod biomass, abundance and species diversity
raise concerns and call for measures. Agricultural intensification is likely one cause for the negative trends. But rare long-term arthropod surveys conceal trends in arthropod communities in agricultural land. Here, we report about a standardized sampling of arthropod fauna in a Swiss agricultural landscape, repeated over 32 years (1987, 1997 and 2019). We sampled 8 sites covering 4 semi-natural and agricultural habitat types. Four trap types were used to capture a wide range of flying and ground dwelling arthropods between May and July. Over the three sampling periods, 58’255 specimens of 1’343 species were analysed. Mean arthropod biomass, abundance and species richness per trap was significantly higher in 2019 than in prior years and gamma diversity of the study area was highest in 2019. Biomass and abundance increased stronger in the flight traps than in the pitfall traps. The implementation of agri-environmental schemes has improved habitat quality since 1993, while landscape composition and pesticide and fertilizer use remained stable over the study period, both contributing to the findings. The results of this study contrast with outcomes of comparable investigations and highlight the importance of further long-term investigations on arthropod dynamics.

Data are provided on request to contact person against bilateral agreement.

en: Arthropod biomass, abundance and species richness trends over 32 years in the agricultural Limpach valley, Switzerland


en: snow-melt snow-water-equivalent snow-cover-fraction snow-climatology operational-snow-hydrological-service

en: Data package

en: This dataset comprises the climatology on gridded data of snow water equivalent and snow melt runoff spanning 1998-2022, with a spatial resolution of 1 km and daily temporal resolution. This data was produced with the conceptual OSHD model (Temperature Index Model).

operational-snow-hydrological-service

display_name: operational-snow-hydrological-service

snow-climatology

display_name: snow-climatology

snow-cover-fraction

display_name: snow-cover-fraction

snow-melt

display_name: snow-melt

snow-water-equivalent

display_name: snow-water-equivalent

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: Climatological snow data since 1998, OSHD


greenland-climate-network-gc-net-data

title_for_slug: greenland-climate-network-gc-net-data

en: net-radiation automatic-weather-station climate aws air-temperature greenland

en: 22-Petermann ELA

en: GC Net Config for Stations

media_type: application/json

en: Stations Config from the static bucket

format: JSON

en: Access the latest L1 data

en:
The GC-Net is kindly continued by the Geological Survey of Denmark and Greenland (GEUS).

Starting October 3, 2022, the access to the latest versions of the "ready to use" L1 data has been migrated to GEUS, (doi:10.22008/FK2/VVXGUT). Future versions will be available from GEUS, while the initial version of L1 data has been archived.

en: GC Net Chart Parameters

en: Stations parameters from static bucket

en: Archived GC-Net Data (deprecated)

en:
The GC-Net is kindly continued by the Geological Survey of Denmark and Greenland (GEUS).

Starting October 3, 2022, the access to the latest versions of the "ready to use" L1 data has been migrated to GEUS, (doi:10.22008/FK2/VVXGUT). Future versions will be available from GEUS, while the initial versions of L0 and L1 data have been archived.

en:
In Memory of Dr. Konrad (Koni) Steffen

Update October 2022: The GC-Net is kindly continued by the Geological Survey of Denmark and Greenland (GEUS).
Starting October 3, 2022, the access to the latest versions of the "ready to use" L1 data has been migrated to GEUS. Future data versions will be available at: [https://doi.org/10.22008/FK2/VVXGUT](https://doi.org/10.22008/FK2/VVXGUT)
 Background
Starting with a single station in 1991, the Greenland Climate Network (commonly known as GC-Net) is a set of Automatic Weather Stations (AWS) set up and managed by the late Prof. Dr. Konrad (Koni) Steffen, and spanning the Greenland Ice Sheet (GrIS). This first station was "Swiss Camp" or the "ETH-CU" camp (GC-Net station 01) which was used as a field science and education site by Koni for years. The GC-Net was expanded with multiple NASA, NOAA, and NSF grants throughout the years, and then supported by WSL in the later years. These data (see "C-file" below) were previously hosted by the Cooperative Institute for Research in Environmental Sciences (CIRES) in Boulder, Colorado.

 Overview
Provided in this dataset are the 16 longest running stations in the network, which are spread over a significant area of the GrIS and the majority of the unique climatic zones. From the South Dome high point in the South, to the Western Jakobshavn ablation region in the west, to the Petermann glacier in the North across east of the Northeast Greenland Ice Stream to the east, GC-Net is the longest running climatological record of Greenland.

 The standard GC-Net station consists of:
* Air temperature measurements at 2 heights above the surface
* Temperature and humidity measurements at 2 heights above the surface
* Wind speed and direction measured at 2 heights above the surface
* Sonic distance sounder measurements for 2 snow height and distance of instruments to surface
* Incoming shortwave radiation measurement
* Reflected shortwave radiation measurement
* Net broadband radiation (long- and short-wave) measurement
* Air pressure measurement
Data have often been repatriated in near-real time using one of either the GOES geostationary satellite or the ARGOS polar orbiting satellite transmission system. The stations were visited typically every 1-2 years for maintenance and service, and to download full uncorrupted data directly from the dataloggers. GC-Net stations were visited by Twin Otter equipped with snow skids to land directly on the open-ice at the AWS locations, or by helicopter near the west coast. The AWSs operate on solar and battery power and occasionally lost power during the dark and cold winter months, particularly when the batteries were aging.

 Dataset
This dataset consists of 2 main data levels; Level 0 and Level 1.
Level 0 is the raw data from the dataloggers, historical processing codes, satellite transmissions, and Koni’s personal data archive. Level 0 data (.zip) directories contain subdirectories:
* “C file” - contains the historical processed datafile for each station.
* “Campbell logger files” - contains the raw csv datafiles from the stations’ Campbell Scientific dataloggers since the CR1000 era (~2007-2008 for most stations).
* “Photos” - contains photographs of the station when available marked by year.
Level 1 is the appended, calibrated, cleaned, and quality flagged data. The full processing scheme is open-source and publicly available on the following GitHub repository (please also check GitHub for the latest L1 data):
[GC-Net L1 data on GitHub](https://github.com/GEUS-Glaciology-and-Climate/GC-Net-level-1-data-processing "GC-Net-level-1-data-processing")
Level 1 data is provided in the newly described csv-compatible [NEAD format](https://www.envidat.ch/#/metadata/nead "NEAD format").

 Additional Details
Dataset description publication will be forthcoming.
The Geological Survey of Denmark and Greenland (GEUS) has been imperative in the reprocessing and continuity mission of GC-Net. Multiple GC-Net stations have been replaced with updated and upgraded AWS hardware at the same coordinates by GEUS. This effort will ensure continuity of the GC-Net dataset into the future.

air-temperature

display_name: air-temperature

automatic-weather-station

display_name: automatic-weather-station

aws

display_name: aws

climate

display_name: climate

greenland

display_name: greenland

net-radiation

display_name: net-radiation

en: Greenland Climate Network (GC-Net) Data


maintainer: Avalanche Warning Service SLF

en: Avalanche fatalities per year in Switzerland since 1936/1937

en:
Attention: this data is not updated after 2022 anymore.
This dataset contains the statistics on the number of avalanche fatalities per hydrological year in Switzerland. The data set commences with the beginning of the hydrological year 1936/37 on 01/10/1936. After the completion of a hydrological year, the new data is appended to the existing dataset.
The following information is contained (by column and column title):
 - hydrological year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)
The definition for these four categories as described in the guidelines to the avalanche accident database:
**tour**:
activities include back-country ski, snowboard or snow-shoe touring
**offpiste**:
access from ski area, generally from the top of a skilift with short hiking distances
**transportation.corridors** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people travelling or recreating on open or temporarily closed
transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)
**buildings** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people inside or just outside buildings, and workers on high alpine building
sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

en: Number of avalanche fatalities per hydrological year in Switzerland since 1936-1937


en: streamflow alptal stable-water-isotopes runoff groundwater

en: Deuterium rainfall event B

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

en: Precipitation and discharge event A

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

en: Deuterium rainfall extra event

en: Deuterium streamwater event B

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

en: Deuterium rainfall event A

en: Deuterium streamwater event C

en: Deuterium streamwater event A

en: Deuterium rainfall event C

en: Deuterium groundwater and baseflow October 2016

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

Date: Date (year-month-day)
Location: Well number or outlet
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)
riparian: riparian wells (i.e. from the riparian-like cluster as presented in Kiewiet et al. (2019)) are marked a one, all other wells are marked a zero
d.D (per mil): Deuterium composition (per mil)

en: Precipitation and discharge extra event

en: Deuterium groundwater and baseflow October 2017

en: Deuterium streamwater extra event

en: Deuterium groundwater and baseflow August 2017

en: Precipitation and discharge event B

en: Precipitation and discharge event C

en:
This dataset includes discharge and rainfall measurements and deuterium compositions of streamflow, rainfall and groundwater, for four rainfall events and three baseflow snapshot campaigns in the Studibach (Alptal, Switzerland). More specifically, we present the following data:

- Specific discharge at the catchment outlet at 5-minute resolution (mm per hour);
- Rainfall at 5-minute resolution (mm per hour);
- Rainfall deuterium composition (‰);
- Stormflow deuterium composition (‰);
- Groundwater and baseflow deuterium compositions (‰).

For the files containing rainfall and discharge timeseries (QP), and rainfall and streamwater deuterium compositions ("Deuterium_Rainfall" and "Deuterium_Streamwater"), we added the corresponding event identifier (A, B, C or extra) to the file names. For the files containing the groundwater and baseflow deuterium values ("Deuterium_Snapshot") we added the sample collection date to the file name. We included the X and Y coordinates for each data point (coordinate system: CH1903 LV3) as well as the date and time (UTC).

More information on the data collection and preparation can be found in Kiewiet et al. (in review). A detailed description of the baseflow snapshot campaigns can also be found in Kiewiet et al., 2019.

envidat

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

en: Discharge, rainfall, and deuterium compositions of streamwater, rainwater and groundwater, for four rainfall events in the Studibach, Alptal, Switzerland


maintainer: Henning Löwe

en: discrete-element-modelling fast-sintering angle-of-repose granular-snow grain-shape

mimetype: text/plain

en: Angle of repose and 3D CT images

en:
5 Snow types were examined and glass beads as a cohesion-less reference, named as follows:

RG: rounded grains (sieved with 0.7 - 1.4 mm)

FC: faceted grains (1.4 - 2 mm)

FCS: small faceted grains (0.7 - 1.4 mm)

IB: ice beads (4 mm)

IBS: small ice beads (2 - 2.2 mm)

GB: glass beads(2 mm)

en:
Angle of repose experiments were performed with different snow types at temperatures between -2 and -40°C. They were used to examine granular snow dynamics on the grain-scale with focus on the role of grain shape and cohesion. The angle of repose was observed by sieving snow onto a round, freestanding base until a stationary heap was formed.

This dataset consists of 1) the images of the experimental heaps that were taken to determine the angle of repose, 2) one binary 3D micro computed tomography image of each snow type. The CT images were taken with the SLF micro-CT40 to characterize snow properties and grain shape.

The experiments with natural snow types (rounded and faceted grains) and spherical model snow allowed for an examination of the differences in granular properties between natural grain shapes and spherical particles in view of Discrete Element Modelling. With the chosen temperatures, the effect of sintering could be observed that increases the angle of repose with increasing temperature.

angle-of-repose

display_name: angle-of-repose

discrete-element-modelling

display_name: discrete-element-modelling

fast-sintering

display_name: fast-sintering

grain-shape

display_name: grain-shape

granular-snow

display_name: granular-snow

educ

en: Education, culture and sport

en: EnviDat: the Environmental Data Portal

en: Angle of repose experiments with natural and spherical snow


maintainer: Leo Gallus Bont

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

en: View video on youtube!

en: Herunterladen des DHM mit SwissGeoDownloader

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. The plugin ‘Swiss Geo Downloader’, which is available for the open source geoinformation software QGIS, allows freely available Swiss geodata to be downloaded and displayed directly within QGIS. It was developed in 2021 by Patricia Moll in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. In this tutorial we describe how to download the high accuracy elevation model ‘swissALTI3D’ with the help of the ‘Swiss Geo Downloader’ and how to use it for digital planning of a cable line with the plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to the Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

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

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

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Das Plugin Swiss Geo Downloader, welches für das Open Source Geoinformationssystem QGIS zur Verfügung steht, ermöglicht frei verfügbare Schweizer Geodaten direkt innerhalb von QGIS herunterzuladen und anzuzeigen. Es wurde 2021 von Patricia Moll in Zusammenarbeit mit der eidgenössischen Forschungsanstalt Wald, Schnee und Landschaft WSL entwickelt. In diesem Tutorial beschreiben wir, wie man mit Hilfe des Swiss Geo Downloaders das hochgenaue Höhenmodell swissALTI3D herunterladen und für die Seillinienplanung mit dem Plugin Seilaplan verwenden kann.

Link zum Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

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

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geo-downloader

display_name: swiss-geo-downloader

swiss-geodata

display_name: swiss-geodata

en: Seilaplan Tutorial: DTM download with SwissGeoDownloader


en: tree-ring-width dendrochronology swiss-forest-lab tree-selection-effects icp-forests long-term-forest-ecosystem-research

en: Data Request

en:
Two stem core samples of all trees of a subplot of approximately 1 a. Basal Area, Wood volume increment per area estimation

 Purpose:

Investigation of the relation between dendroparameters of dominance/surpression and stem growth. Abgleich Jahrringdaten mit Inventurdaten.

 Paper Citation:

 * Nehrbass-Ahles C, Babst F, Klesse S, Nötzli M, Bouriaud O, Neukom R, Dobbertin M, Frank D (2014) The influence of sampling design on tree-ring-based quantification of forest growth. Global Change Biology, 20 (9): 2867–2885. [doi: 10.1111/gcb.12599](http://doi.org/10.1111/gcb.12599)

 * Klesse S, Etzold S, Frank D (2016) Integrating tree-ring and inventory-based measurements of aboveground biomass growth: research opportunities and carbon cycle consequences from a large snow breakage event in the Swiss Alps. European Journal of Forest Research, 135 (2): 297-311.

dendrochronology

display_name: dendrochronology

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

swiss-forest-lab

display_name: swiss-forest-lab

tree-ring-width

display_name: tree-ring-width

tree-selection-effects

display_name: tree-selection-effects

en: Dendrochronological analyses of tree core samples (subplot) LWF