en:
Background information
The availability of nitrogen (N) and phosphorus (P) is considered to be a major factor limiting growth and productivity in terrestrial ecosystems globally. This project aimed to determine whether the growth stimulation documented in previous short‐term fertilisation trials persisted in a longer‐term study (12 years) in the treeline ecotone, and whether possible negative effects of nutrient addition offset the benefits of any growth stimulation.
Over the course of the 12 study years, NPK fertiliser corresponding to 15 or 30 kg N ha−1 a−1 was added annually to plots containing 30‐year‐old *Larix decidua* or 32‐year-old *Pinus uncinata* individuals with an understorey of mainly ericaceous dwarf shrubs. To quantify growth, annual shoot increments of trees and dwarf shrubs as well as radial growth increments of trees were measured. Nutrient concentrations in the soil were also measured and the foliar nutritional status of trees and dwarf shrubs was assessed.
 Experimental design
Over an elevation gradient of 140 m across the treeline afforestation site Stillberg, 22 locations were chosen that covered the whole range of microenvironmental conditions (*see* Nutrient addition experimental design.png). Half of the blocks included European larch (*L. decidua*) and the other half included mountain pine (*P. uncinata*). Within each block, three plantation quadrats were randomly selected as experimental plots and each plot was assigned to a control (no fertilisation) or to one of two fertiliser dose treatments (15 kg and 30 kg N ha−1 a−1). Treatments were assigned randomly but confined so that the location of fertilised plots within a block was not directly above control plots to avoid nutrient input from drainage. For details about the experiment, *see* Möhl et al (2019).
 Data description
The available datasets contain climate variables (2004-2016), nutrient isotope measurements (2010 & 2016), shrub growth measurements (2004-2016), soil parameter measurements and annual ring and shoot measurements (2004-2016). All data can be found here:
-https://figshare.com/articles/dataset/Twelve_years_of_low_nutrient_input_stimulates_growth_of_trees_and_dwarf_shrubs_in_the_treeline_ecotone/7025858-

en: tree-rings nitrogen-isotope dwarf-shrubs stillberg fertilization treeline

en: Nutrient addition experiment at the Alpine treeline site Stillberg, Switzerland

de:
Resource Title: Metadata Nutrient Addition Stillberg Experimental Design
    Size: 1327266 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/3bc7cad9-38af-453a-8f1e-3afb23000c62/resource/3874f6f4-be83-403a-b2f8-ab1a0dd465d3/download/nutrient_addition_experimental_design.png
    Description: Nutrient addition map of the study area with the investigated plots. Each circle (study block) contains one control plot and two plots that received NPK fertilizer corresponding to 15 (NPK15) or 30 (NPK30) kg N ha-1 a-1. Contour lines specify the elevation (m a.s.l.) in steps of 10 m.

format: PNG

media_type: image/png

de:
Resource Title: Data Nutrient Addition Stillberg
    Size: 339539 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3bc7cad9-38af-453a-8f1e-3afb23000c62/resource/1eb39a79-2953-4aee-b7f0-b63744fef1e0/download/7025858.zip
    Description: This link leads to the figshare repository, which contains all nutrient addition data.

dwarf-shrubs

display_name: dwarf-shrubs

fertilization

display_name: fertilization

nitrogen-isotope

display_name: nitrogen-isotope

stillberg

display_name: stillberg

tree-rings

display_name: tree-rings

treeline

display_name: treeline


experimental-rockfall-trilogy-of-surava

$oid: OBSOLETE

en: We performed an experimental trilogy of induced rockfall experiments in a spruce stand in Surava (CH) within (i) the original forest, (ii) after a logging job, resulting in lying deadwood and (iii) the cleared, deadwwod-free state. The three experimental set-ups allow quantifying the deadwood effect on overall rockfall risk for the same forest (slope, species) in three different conditions.

en: forest gyroscope induced-rockfall rockfall gnss deposition-points lying-deadwood in-situ acceleration

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

en: Experimental rockfall trilogy of Surava

title_for_slug: experimental-rockfall-trilogy-of-surava

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

de:
Resource Title: StoneNode Data Analysis Surava
    Size: 37282 bytes
    Format: application/vnd.wolfram.mathematica.package
    URL: https://www.envidat.ch/dataset/4da88d3f-5627-40d2-843d-c884a31238b1/resource/a1df211b-e2f9-40b7-86fe-b39624fe195a/download/surava_gyr_analysis_20210928_vfinal.m
    Description: Matlab script to detect frontal impacts (FI) on opposing objects within the in situ gathered StoneNode gyroscopic data of the Surava rockfall trilogy.

de:
Resource Title: In situ sensor data cleared area
    Size: 50806879 bytes
    Format: application/x-matlab
    URL: https://www.envidat.ch/dataset/4da88d3f-5627-40d2-843d-c884a31238b1/resource/dbad6e48-4c45-4e81-9345-fdb98c37c584/download/clr_data.mat
    Description: Matlab structure of all used StoneNode sensors which were several times released into the cleared forest state.

de:
Resource Title: ReleasePoint
    Size: 2360 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4da88d3f-5627-40d2-843d-c884a31238b1/resource/e57401a7-b80d-4055-838c-5582710f870b/download/release_lv95.zip
    Description: Zipped shape file of releasepoint used in RAMMS::ROCKFALL Simulations. Slightly shiftet from originally measured in DNSS Position, as this position was on the flat forest road.

format: ZIP

media_type: application/zip

de:
Resource Title: Trees_Surava_DW_CLR
    Size: 29181 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4da88d3f-5627-40d2-843d-c884a31238b1/resource/f1fea988-8bb2-40b4-a085-d2f2b3bea9e4/download/surava_trees_dw_clr.zip
    Description: Standing trees after forest management intervention

de:
Resource Title: In situ sensor data original forest
    Size: 49732594 bytes
    Format: application/x-matlab
    URL: https://www.envidat.ch/dataset/4da88d3f-5627-40d2-843d-c884a31238b1/resource/dde076b7-f5a8-4943-953d-8a66559d1b4d/download/org_data.mat
    Description: Matlab structure of all used StoneNode sensors which were several times released into the original forest state.

de:
Resource Title: DEM_Surava_5cm_Resolution
    Size: 116938116 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/4da88d3f-5627-40d2-843d-c884a31238b1/resource/f75eab92-8c62-45e0-b2b9-4729e244b241/download/dhm.asc
    Description: Used DEM of the site, based on the LiDAR Pointcloud

format: pgp-keys

de:
Resource Title: In situ sensor data deadwood
    Size: 19834192 bytes
    Format: application/x-matlab
    URL: https://www.envidat.ch/dataset/4da88d3f-5627-40d2-843d-c884a31238b1/resource/9ab17365-ef04-4fce-b9bc-8fa50a57123c/download/dw_data.mat
    Description: Matlab structure of each In situ StoneNode sensor installed in different rocks and several released through the Deadwood forest state.

de:
Resource Title: Trees_Surava_ORG
    Size: 25380 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4da88d3f-5627-40d2-843d-c884a31238b1/resource/9dd5d8be-6e7e-429d-a6c2-3237cfc6dc84/download/trees_surava.zip
    Description: Zipped shapefile of the measured and in RAMMS::ROCKFALL used trees for the original (ORG) forest state.

acceleration

display_name: acceleration

deposition-points

display_name: deposition-points

forest

display_name: forest

gnss

display_name: gnss

gyroscope

display_name: gyroscope

in-situ

display_name: in-situ

induced-rockfall

display_name: induced-rockfall

lying-deadwood

display_name: lying-deadwood

rockfall

display_name: rockfall


ensemble-hydrograph-separation-scripts

en:
Calculation scripts that perform ensemble hydrograph separation.  Identical scripts in R and MATLAB are provided, along with demonstration input time series and the corresponding outputs.  These scripts were tested on R version 3.6.2 (2019-12-12) and on MATLAB versions 2018b and 2109b.
These scripts are made publicly available under GNU General Public License 3; for details see https://www.gnu.org/licenses/.
ETH Zurich, WSL, James Kirchner, and Julia Knapp make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose.  Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

en: catchment runoff tracers isotopes hydrograph-separation streamflow

en: Ensemble hydrograph separation scripts

title_for_slug: ensemble-hydrograph-separation-scripts

de:
Resource Title: R scripts and demonstration files
    Size: 235119 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ddc39d77-c0a3-4a8c-858a-efda8b6dffd9/resource/212f3a19-0530-4cd9-b10d-cd387ac98018/download/ehs-v1.4-r-scripts-and-demo-files.zip
    Description: The ensemble hydrograph separation functions themselves are in EHS_v1.4.R.

EHS_demo_v1.4.R is a demonstration script that calls EHS_v1.4.R to analyze the demo input files.  The resulting output files are in the "demo output files" folder.

de:
Resource Title: *deprecated* MATLAB scripts and demonstration files (*deprecated version* - build 20200718 - do not use!)
    Size: 227403 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ddc39d77-c0a3-4a8c-858a-efda8b6dffd9/resource/bd43b9fb-7fda-4c26-a38c-31016f035429/download/ehs-v1.4-matlab-scripts.zip
    Description: The ensemble hydrograph separation functions themselves are in EHS_Fnew.m, EHS_profile.m, and EHS_TTD.m.

EHS_demo_RUN_THIS.m is a demonstration script that calls the EHS functions to analyze the demo input files. The resulting output files are in the "demo output files" folder.  These were generated by the R versions of the scripts but have been verified to be numerically equal to the MATLAB outputs, within machine precision.

de:
Resource Title: MATLAB scripts and demonstration files (current version - build 20201119)
    Size: 178465 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ddc39d77-c0a3-4a8c-858a-efda8b6dffd9/resource/27da91e3-24b1-4d76-883e-37619652d785/download/ehs-v1.4-matlab-scripts-build-20201119.zip
    Description: The ensemble hydrograph separation functions themselves are in EHS_Fnew.m, EHS_profile.m, and EHS_TTD.m.

Build 20201119 has improved commenting, naming, and structuring, and also minor bug fixes in EHS_Fnew, EHS_TTD, and EHS_profile.  Build 20200718 has been deprecated.  Use build 20201119 instead.

EHS_demo_RUN_THIS.m is a demonstration script that calls the EHS functions to analyze the demo input files. The resulting output files are in the "demo output files" folder.  These were generated by the R versions of the scripts but have been verified to be numerically equal to the MATLAB outputs, within machine precision.

catchment

display_name: catchment

hydrograph-separation

display_name: hydrograph-separation

isotopes

display_name: isotopes

runoff

display_name: runoff

streamflow

display_name: streamflow

tracers

display_name: tracers


en:
Alpine3D (A3D) runs between 1950 and 2022 in hourly resolution. Simulations are run for every year separately (year n = Sept. n-1 to Aug. n), starting again with no snow every 1st of September (i.e. there is no snow accumulation from year to year).
Meteorological conditions over the past 70 years were obtained from several datasets: ERA5 providing the hourly data over the full 1950-2022 period, IMIS and MeteoSuisse allowing to validate and correct the downscaled ERA5 data. ERA5 data were downscaled to a 50m grid using Toposcale (Fiddes et al., 2015) (see also https://github.com/joelfiddes/toposcale). This downscaling tool allowed us to obtain a 50 m grid from the ERA5 data including the effect of the local topography. The meteorological input data was further sued to run the 3-dimensional snow model Alpine 3D.
Temperature correction is based on an additive delta change correction following the procedure using harmonic functions filtering described by Michel et al. (2021). Given the hourly timestep provided by ERA5 and Toposcale, we defined an hourly delta change. In practice, this was done by repeating 24 times the delta-change derivation from Michel et al.  (2021) to obtain a day-of-the-year delta for each of the 24 hours of the day.
The simulation covers the slope at Spitze Stei region with  precipitation scaled using snow height measured by a drone flight. One of the 70 years runs was computed with a precipitation redistribution with the idea to mimic snow transport and preferential deposition. The precipitation redistribution grid was based on a single snow height measurement: one snow-free drone flight on 01.10.2021 and one peak snow season flight on 27.03.2022. The precipitation on each pixel is computed as i) multiplying the disaggregated KAS precipitation by the average slope elevation. ii) multiplying that value on each pixel with the weight obtain from the snow height as HS pixel/HS mean.

en: Alpine3D Climate Data

snow-climatology

display_name: snow-climatology

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth


en:
The data consists of a collection of environmental data, tree-ring width and intra-annual δ13C measurements of tree rings of three conifer species (Pinus sylvestris, Picea abies, Abies alba), and the R scripts that were used to analyse the data. Data was collected at two pairs of north and south exposed sites in Switzerland, in the Eastern Grisons (Surava North and Surava South) and Central Valais (Buthan and Lens).
Intra-annual δ13C measurements were obtained using the laser ablation technique, which involved 10 sequential shots per ring. Shot 1 represents the δ13C value at the start of the ring, while Shot 10 corresponds to the δ13C value at the end of the ring's formation. Overall, the datasets consist of 400 profiles and 4000 isotope measurements.
Environmental data was collected at each site over decade, from 2012 to 2023. Key environmental variables include temperature, vapour pressure deficit (VPD), and soil water potential (SWP). Precipitation data was obtained from the EOBS v29.0e dataset (https://www.ecad.eu/download/ensembles/download.php) from the closest grid point. All data was aggregated on an hourly to daily scale.
In addition to environmental data, dendrometer data was used to derive the onset days, beginning of growth for each site (Onset_days.Rds). The data captures the dynamic relationship between environmental factors, such as soil and air moisture, and tree physiological responses, as reflected in δ13C variation. This dataset provides insights into the intra-seasonal interactions between environmental conditions and tree physiology. We provide the scripts for the main analyses performed in the Vitali, V. et al. 2025 article listed below, including the correlation of the isotope intra-annual time series with environmental variables.
This dataset contains all data on which the publication listed below is based.
Please cite this paper together with the citation for the datafile.

en: tree-ring stable-isotopes pinus-sylvestris vpd soil-water abies-alba picea-abies drought dendrochronology

en: 10 years of intra-annual carbon isotopes in tree rings from 3 conifer species

abies-alba

display_name: abies-alba

dendrochronology

display_name: dendrochronology

drought

display_name: drought

picea-abies

display_name: picea-abies

pinus-sylvestris

display_name: pinus-sylvestris

soil-water

display_name: soil-water

stable-isotopes

display_name: stable-isotopes

tree-ring

display_name: tree-ring

vpd

display_name: vpd


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.

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

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

de:
Resource Title: README
    Size: 827 bytes
    Format: No Info
    URL: https://www.envidat.ch/dataset/eca24fe5-ed00-4ff6-9482-414ff98161d1/resource/312e0c4c-e5c6-447b-8c39-5fd9c7ba4adc/download/readme-2
    Description: Top level README file explaining the organization of the data

de:
Resource Title: wfj_rhossa_data
    Size: 427819008 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.151/2020_rhossa_paper_calonne_tc
    Description: Link to data

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: Meteorological data used to run SNOWPACK for 58 catchments in the Swiss Alps. The data consists of a 2 km grid of "virtual meteorological stations" for each catchment. It was used to simulate snow cover processes during rain-on-snow events, therefore meteorological data of each catchment contains at least one rain-on-snow event. Further information can be found in the attached readme.txt and in Würzer & Jonas et al. (2017), currently under review in Hydrological Processes.

en: snow-hydrology snowpack catchment-data rain-on-snow meteorological-data

envidat

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.

en: Meteorological data for investigation of rain-on-snow events in 58 catchments in Switzerland

de:
Resource Title:
    Size: 1534677078 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.305/ros_data/ros_data.zip
    Description: The file contains all data needed to run simulations with the snow cover model SNOWPACK.

de:
Resource Title:
    Size: 768 bytes
    Format: text/plain
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.305/ros_data/readme.txt
    Description: Readme.txt

format: TXT

media_type: text/plain

catchment-data

display_name: catchment-data

meteorological-data

display_name: meteorological-data

rain-on-snow

display_name: rain-on-snow

snow-hydrology

display_name: snow-hydrology

snowpack

display_name: snowpack


en: paleo-climate air-temperature orography precipitation last-glacial-maximum glaciers

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.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

de: EnviDat

en: CHELSA-TraCE21k: Downscaled transient temperature and precipitation data since the last glacial maximum

envi

de: Umwelt

de:
Resource Title: Data Access
    Size: 3848290697216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav1%2F&prefix=chelsa_trace%2F
    Description: High resolution, downscaled climate model data are used in a wide variety of applications in environmental sciences. Here we present the CHELSA-TraCE21k downscaling algorithm to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100 year time steps for the last 21,000 years. Paleo orography at high spatial resolution and at each timestep is created by combining high resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases with the interpolation of a dynamic ice sheet model (ICE6G) and a coupling to mean annual temperatures from CCSM3-TraCE21k. Based on the reconstructed paleo orography, mean annual temperature and precipitation was downscaled using the CHELSA V1.2 algorithm.

The data is published under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

de:
Resource Title: Technical documentation
    Size: 478853 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/c88baa58-dbae-452c-8c2c-343e4c9fb885/resource/613fcb27-3649-4b5f-8880-984403cccd62/download/chelsa-trace21k_technical_documentation.pdf
    Description: Technical documentation containing file metadata and variable descriptions.

format: PDF

media_type: application/pdf

air-temperature

display_name: air-temperature

glaciers

display_name: glaciers

last-glacial-maximum

display_name: last-glacial-maximum

orography

display_name: orography

paleo-climate

display_name: paleo-climate

precipitation

display_name: precipitation


en:
Outlines of 18'737 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 24 January 2018. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping.pdf)
The generation of the data is described in:
Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.
Abstract.
Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12’500 km2).
We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18’737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.
This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data is of great value to validate avalanche bulletins, complete existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.
Koordinate System: CH1903+ LV95 LN02

en: hazard-mapping satellite snow avalanche natural-hazard

en: SPOT6 Avalanche outlines 24 January 2018

envi

en: Environment

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


en:
**for English see below**
*******************************************************************************
-br/- -/br-
 Datenbeschrieb
-br/- -/br-
Dieser Datensatz enthält die **Umrisse der 11'120 Lawinen** die aus schwarzweiss Luftbildern, welche zwischen dem 25.2.1999 und dem 1.3.1999 aufgenommen wurden, kartiert wurden. Die Lawinenumrisse haben verschiedene Attribute welche im **beigelegten Beispielschlüssel** beschrieben sind (Beispielschluessel_1999_d.pdf).
Es gibt drei Shapefiles:
* **avalanches1999_endversion1.shp**: die kartierten Lawinen (für Attribute siehe Beispielschlüssel!)
* **area_images_1999.shp**: Fläche die durch die Luftbilder abgedeckt wurde
* **clouds_1999.shp**: grobe Umrisse der Wolken in den Bildern
 Bildverfügbarkeit:
Die entzerrten Luftbilder können von der [Swisstopo](https://s.geo.admin.ch/rpq3hufnb588) einzeln über den Downloadlink heruntergeladen werden (herzlichen Dank an Holger Heisig für die Prozessierung und ans BAFU für die Finanzierung der Prozessierung!!). Über "Erweiterte Werkzeuge"/ "Datei importieren" können die Bilder nach hereinziehen des Orthofotolinks direkt im map.geo.admin.ch angezeigt werden.
 Weiterführende Litertaur:
Details zu den Luftbildern und zur Kartierung, sowie eine kleine Analyse und Empfehlungen zur Verwendung der Daten finden sich unter
- Hafner, E., Margreth, S., and Bühler, Y.: Die grossflächigen Lawinenkartierungen 1999, 2018 und 2019: ein Überblick für die Praxis, FAN Agenda, 1/2025, 15 - 21, 2025.
- Dal, F. J., Hafner, E. D., Peters, T., Narnhofer, D., Caye Daudt, R., Heisig, H., & Bühler, Y. (2024). Automated snow avalanche mapping with deep learning in aerial imagery from the extreme avalanche winter of 1999. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1264-1271). Norwegian Geotechnical Institute.
- Hafner, E. D., Techel, F., Heisig, H., Dal, J. F., & Bühler, Y. (2024). Remotely sensed avalanche activity during three extreme avalanche periods in Switzerland. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1222-1229). Norwegian Geotechnical Institute.
*******************************************************************************
-br/- -/br-
 Data description
-br/- -/br-
This dataset contains the **outlines of 11'120 avalanches** mapped from panchromatic aerial imagery taken between February 25, 1999 and March 1, 1999. The avalanche outlines have various attributes which are described in the **attached example key** (ExampleKey_AvalMapping_1999_e.pdf).
There are three shapefiles:
* **avalanches1999_endversion1.shp**: the mapped avalanches (for attributes see example key!)
**area_images_1999.shp**: Area covered by the aerial images
**clouds_1999.shp**: rough outlines of the clouds in the images
 Image availability:
The rectified aerial images can be downloaded individually from [Swisstopo](https://s.geo.admin.ch/bg6beetinfdc) via the download link (many thanks to Holger Heisig for processing and to BAFU for financing the processing!!). The images can be displayed directly in map.geo.admin.ch via “Advanced tools”/“Import file” after dragging in the orthophoto link.
 Further Reading:
Details on the aerial images and mapping, as well as a brief analysis and tips on using the data can be found at
- Hafner, E., Margreth, S., and Bühler, Y.: Die grossflächigen Lawinenkartierungen 1999, 2018 und 2019: ein Überblick für die Praxis, FAN Agenda, 1/2025, 15 - 21, 2025.
- Dal, F. J., Hafner, E. D., Peters, T., Narnhofer, D., Caye Daudt, R., Heisig, H., & Bühler, Y. (2024). Automated snow avalanche mapping with deep learning in aerial imagery from the extreme avalanche winter of 1999. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1264-1271). Norwegian Geotechnical Institute.
- Hafner, E. D., Techel, F., Heisig, H., Dal, J. F., & Bühler, Y. (2024). Remotely sensed avalanche activity during three extreme avalanche periods in Switzerland. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1222-1229). Norwegian Geotechnical Institute.

en: avalanche-activity avalanche-mapping remote-sensing aerial-imagery avalanche

en: Avalanche outlines February and March 1999 from aerial imagery

aerial-imagery

display_name: aerial-imagery

avalanche-activity

display_name: avalanche-activity

avalanche-mapping

display_name: avalanche-mapping

remote-sensing

display_name: remote-sensing


en: This dataset contains bryophyte species count data and information about the observers bryophyte expertise for 2332 relevés conducted from 2011 to 2021 on 10-m2 plots in a long-term monitoring program in Switzerland. Plots were situated in raised bogs and fens of national importance, which were distributed across the whole country. The majority of the plots is represented by two relevés as sites are revisited every six years. **The dataset was prepared for usage in an unpublished article with the title of this dataset. Due to improvements in the analysis, results turned out to be more nuanced and it was found that the title of the data set is no longer valid.** A new dataset was created and is available here: [https://www.doi.org/10.16904/envidat.683](https://www.doi.org/10.16904/envidat.683)

en: fen observer-bias raised-bog liverworts mosses cover biodiversity-monitoring sphagnum

en: Greater observer expertise leads to higher estimates of bryophyte species richness

format: CSV

biodiversity-monitoring

display_name: biodiversity-monitoring

cover

display_name: cover

fen

display_name: fen

liverworts

display_name: liverworts

mosses

display_name: mosses

observer-bias

display_name: observer-bias

raised-bog

display_name: raised-bog

sphagnum

display_name: sphagnum


en:
This dataset comprises of a post-processed set of terrestrial laser scans (TLS’s) of Antarctic sea ice obtained during the Sea Ice Physics and Ecosystem Experiment-2 (SIPEX-2, http://seaice.acecrc.org.au/sipex2012/) in September-November 2012. The post-processing steps include the registration of the individual scans into a single 3-dimensional point cloud, the removal of unwanted noise caused by particles in the air (i.e., snow crystals), and the final generation of surface grids based on the cleaned individual point returns. The final product includes the ‘xyz’ coordinates of the individual point measurements, and gridded surfaces covering study areas of 100m x 100 m, and at resolutions of 0.01 m, 0.1 m, 0.25 m, 0.5 m and 1 m for each of the survey dates. Additionally, subgrid statistics that include the mean elevation, standard deviation, minimum and maximum elevations, range, and number of point returns in each gridcell are generated. The final product is provided in space-delimited text files, with the surface grids provided in Digital Terrain Model (DTM) format ready for visualization in any GIS software.
How to cite:
Please also cite the original publication when using this data set.: Trujillo, E., K. Leonard, T. Maksym, and M. Lehning (2016), Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice, J. Geophys. Res. Earth Surf., 121, doi:[10.1002/2016JF003893](https://dx.doi.org/10.1002/2016JF003893).

en: tls terrestrial-laser-scans sea-ice sea-ice-elevation polar

en: High resolution sea ice surface topography from the SIPEX-2 expedition, East Antarctica, 2012

de:
Resource Title: Data processing documentation
    Size: 848896 bytes
    Format: application/msword
    URL: https://www.envidat.ch/dataset/c88b82ed-d54e-43e6-b4e4-7ae1ee06a014/resource/bb51210c-6738-41d4-b4a4-31dd08f4725e/download/tlssipex-2metadata.doc
    Description:

format: msword

de:
Resource Title: Post Processed TLS's
    Size: 932144467 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c88b82ed-d54e-43e6-b4e4-7ae1ee06a014/resource/2557ecb5-e65d-4d60-97ce-fd6696ee2d00/download/10-16904-9sipex2dat.zip
    Description: Compressed dat files

polar

display_name: polar

sea-ice

display_name: sea-ice

sea-ice-elevation

display_name: sea-ice-elevation

terrestrial-laser-scans

display_name: terrestrial-laser-scans

tls

display_name: tls


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

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

de:
Resource Title: map preview 0.5MB
    Size: 482223 bytes
    Format: image/jpeg
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.68/gisdata/tiny_map_preview.jpg
    Description:

format: jpeg

de:
Resource Title: Bulk Data Access
    Size: 111669149696 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.68%2F
    Description: Link to the S3 bucket where all the data resources can be downloaded in bulk

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis


en:
This dataset contains the data used  and collected to investigate the reliability of avalanche size estimates and avalanche outlines (see related publications). Namely this is
 Avalanche size estimates
* the 10 pictures depicting avalanches
* the survey results from the 170 participants
 Avalanche outlines mapped from oblique photographs
* the pictures of the six avalanches
* the avalanche outlines mapped by the 10 participants
* the reference mapped from the georeferenced photographs
 Avalanche outlines from remotely-sensed imagery
* the orthophotos in the four different resolutions (2m, 1m, 50cm, 25cm)
* the area of interest (AoI) delimiting the research area
* the avalanche mappings in each resolution for all five participants
* the shade masks used to separate illuminated and shaded areas
The acquisition of the orthophotos has been partially supported by the Swiss National Science Foundation (SNF; Grant N°200021_172800).

en: avalanche-size-estimation remote-sensing avalanche reliability avalanche-mapping

envidat

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

en: EnviDat: the Environmental Data Portal

en: Data reliability study: avalanche size estimates and outlines

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

avalanche-size-estimation

display_name: avalanche-size-estimation

reliability

display_name: reliability

remote-sensing

display_name: remote-sensing


en:
We developed a workflow to generate Large Scale Hazard Simulations for avalanches based on digital elevation models and information on the protective function of the forest. This datasets contains the potential avalanche release areas (PRA) as polygons, the simulation outputs (maximum pressure, maximum flow velocity and maximum flow height) as .tif rasters and the outlines of the simulated avalanches (polygon) for the entire area of the canton of Grisons (7105 km2). The simulations are performed for the scenarios wit return periods of 10, 30, 100 and 300 years, once with (FOR) and once without (NoFor) taking the effect of the forest into account.
The details can be found in this publication:
Bühler, Y., Bebi, P., Christen, M., Margreth, S., Stoffel, L., Stoffel, A., Marty, C., Schmucki, G., Caviezel, A., Kühne, R., Wohlwend, S., and Bartelt, P.: Automated avalanche hazard indication mapping on state wide scale, Nat. Hazards Earth Syst. Sci. Discuss., 2022, 1-22, 10.5194/nhess-2022-11, 2022.

en: modelling hazard-mapping avalanche release ramms impact-pressure

en: Large Scale Hazard Indication Simulations for avalanches, canton of Grisons

envi

en: Environment

de:
Resource Title: Scenario 10 years without forest
    Size: 924911068 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/60fe952f-bdec-418b-9399-36bdb4ef2faf/download/10ynofor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 100 years with forest
    Size: 805376043 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/01d6b5be-6c29-4e2e-99da-f964c91de64f/download/100yfor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 10years with Forest
    Size: 661720583 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/d3574570-66a9-4c25-b196-727a7123dd7a/download/10yfor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 300 years with forest
    Size: 846835441 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/3d0bff73-c8e1-4f2e-9a38-f83b3a4b98ee/download/300yfor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 30 years without forest
    Size: 945391364 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/d332e2fd-d8b0-4d4b-9c3e-fefed822908a/download/30ynofor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 30 years with forest
    Size: 692742534 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/5986053e-b75f-484b-8adc-c3e19261adef/download/30yfor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 100 years without forest
    Size: 1020375084 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/d5c001b9-1321-4f3d-9f93-89b0c9479dd0/download/100ynofor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Extent of the canton of Grisons
    Size: 685814 bytes
    Format: application/json
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/70e9127c-8510-497c-a3f5-9637aa6d2b8e/download/extent_kt_gr.json
    Description:

format: JSON

media_type: application/json

de:
Resource Title: Scenario 300 years without forest
    Size: 1042271198 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/953acbf3-3a6a-4df1-acf8-ef4108f5f0a9/download/300ynofor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

hazard-mapping

display_name: hazard-mapping

impact-pressure

display_name: impact-pressure

modelling

display_name: modelling

ramms

display_name: ramms

release

display_name: release


en:
Outlines of 6'041 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 16 January 2019. The dataset was acquired following a period with very high avalanche danger. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping16012019.pdf)
The generation of the data is described in:
Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.
The data was comprehensivly validated in a subset area in
Hafner, E.D.; Techel, F.; Leinss, S.; Bühler, Y., 2021: Mapping avalanches with satellites - evaluation of performance and completeness. Cryosphere, 15, 2: 983-1004. doi: 10.5194/tc-15-983-2021

en: natural-hazard hazard-mapping satellite snow avalanche

envidat

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.

de: EnviDat: das Umwelt-Datenportal

de: EnviDat

en: SPOT6 Avalanche outlines 16 January 2019

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


en:
Validation points, validation area, ground truth coverage, SPOT 6 avalanche outlines, Sentinel-1 avalanche outlines, Sentinel-2 avalanche outlines, Davos avalanche mapping (DAvalMap) avalanche outlines as shapefiles and a detailed attribute description (DataDescription_EvalSatMappingMethods.pdf).
Coordinate system: CH1903+_LV95
The generation of this dataset is described in detail in:
Hafner, E. D., Techel, F., Leinss, S., and Bühler, Y.: Mapping avalanches with satellites – evaluation of performance and completeness, The Cryosphere, https://doi.org/10.5194/tc-2020-272, 2021.

en: avalanche-hazard-mapping validation satellite snow avalanche

en: Satellite avalanche mapping validation data

envi

de: Umwelt

avalanche-hazard-mapping

display_name: avalanche-hazard-mapping

validation

display_name: validation


en:
This data set contains the produced snow depth maps as well as the reference data set (manual and snow pole measurements) from our paper "Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping".
Abstract. Snow depth has traditionally been estimated based on point measurements collected either manually or at automated weather stations. Point measurements, though, do not represent the high spatial variability of snow depths present in alpine terrain. Photogrammetric mapping techniques have progressed in recent years and are capable of accurately mapping snow depth in a spatially continuous manner, over larger areas, and at various spatial resolutions. However, the strengths and weaknesses associated with specific platforms and photogrammetric techniques, as well as the accuracy of the photogrammetric performance on snow surfaces have not yet been sufficiently investigated. Therefore, industry-standard photogrammetric platforms, including high-resolution satellites (Pléiades), airplane (Ultracam Eagle M3), Unmanned Aerial System (eBee+ with S.O.D.A. camera) and terrestrial (single lens reflex camera, Canon EOS 750D), were tested for snow depth mapping in the alpine Dischma valley (Switzerland) in spring 2018. Imagery was acquired with airborne and space-borne platforms over the entire valley, while Unmanned Aerial Systems (UAS) and terrestrial photogrammetric imagery was acquired over a subset of the valley. For independent validation of the photogrammetric products, snow depth was measured by probing, as well as using remote observations of fixed snow poles.
When comparing snow depth maps with manual and snow pole measurements the root mean square error (RMSE) values and the normalized median deviation (NMAD) values were 0.52 m and 0.47 m respectively for the satellite snow depth map, 0.17 m and 0.17 m for the airplane snow depth map, 0.16 m and 0.11 m for the UAS snow depth map. The area covered by the terrestrial snow depth map only intersected with 4 manual measurements and did not generate statistically relevant measurements. When using the UAS snow depth map as a reference surface, the RMSE and NMAD values were 0.44 m and 0.38 m for the satellite snow depth map, 0.12 m and 0.11 m for the airplane snow depth map, 0.21 and 0.19 m for the terrestrial snow depth map. When compared to the airplane dataset over a large part of the Dischma valley (40 km2), the snow depth map from the satellite yielded a RMSE value of 0.92 m and a NMAD value of 0.65 m. This study provides comparative measurements between photogrammetric platforms to evaluate their specific advantages and disadvantages for operational, spatially continuous snow depth mapping in alpine terrain over both small and large geographic areas.

en: airplane snow-depth snow-water-equivalent terrestrial uas photogrammetry satellite

en: Photogrammetric snow depth maps from satellite-, airplane-, UAS and terrestrial platforms from the Davos region (Switzerland)

de:
Resource Title: Snow depth map terrestrial (Canon EOS 750D), Schürlialp, Davos, Switzerland
    Size: 141435530 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/78c3e0a0-c377-4421-86c4-550c38ebcd14/download/hs_ground_based_20180407_0_11.tif
    Description: Resolution 0.11 m
Coordinate system: LV95 LHN95

format: TIFF

media_type: image/tiff

de:
Resource Title: Manual and snow pole measurements, Schürlialp, Davos, Switzerland
    Size: 4150 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/1021ffa6-1311-45d3-a47d-61a0a18987cd/download/schneehohenzusammenfassung_fur_publikation.txt
    Description: This text file contains the average value for each manual snow depth measurements and the measured value of the snow pole measurements. The coordinates are in the horizontal Swiss coordinate system LV95. These values are used as reference measurement for comparison 1 as descriped in the paper.

de:
Resource Title: Snow depth map satellite (Pléiades), Schürlialp, Davos, Switzerland
    Size: 2662248 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/d1d2303e-db33-4a7b-b517-452c7f68d3d6/download/hs_pleiades_2m_aligned_on_ebee.tif
    Description: Resolution: 2 m
Coordinate system: LV95 LHN95
© CNES 2018, Distribution Airbus DS

de:
Resource Title: Snow depth map UAS (eBee+), Schürlialp, Davos, Switzerland
    Size: 1063331206 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/bc0acce9-36df-4c77-a83a-2a959ff34b23/download/hs_20180407_schurlialp_ebee_0_09m.tif
    Description: Resolution: 0.9 m
Coordinate system: LV95 LHN95

de:
Resource Title: Snow depth map airplane (Ultracam Eagle M3), Schürilalp, Davos, Switzerland
    Size: 474100554 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/bb6310e8-dfa1-4dc7-b7a6-823cbaca24f8/download/hs_ultracam_20180411_0_11_ebee.tif
    Description: Resolution: 0.11 m
Coordinate system: LV95 LHN95

de:
Resource Title: Snow depth map airplane (Ultracam Eagle M3), Dischma valley, Davos, Switzerland
    Size: 455957254 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/94e7debd-7500-444e-8727-56e18a3aa583/download/hs_ultracam_lhn95_als_0_5m.tif
    Description: Resolution: 0.5 m
Coordinate system: LV95 LHN95

de:
Resource Title: Snow depth map satellite (Pléiades), Dischma valley, Davos, Switzerland
    Size: 48454014 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/e33b05cc-077b-4ad8-8449-095d4c6d2761/download/hs_pleiades_lh95_2m_on_al.tif
    Description: Resolution: 2 m
Coordinate system: LV95 LHN95
© CNES 2018, Distribution Airbus DS

airplane

display_name: airplane

photogrammetry

display_name: photogrammetry

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent

terrestrial

display_name: terrestrial

uas

display_name: uas


en:
This data set contains roughly 5600 photographs of plants and plant parts from 153 sites recorded in all major biogeographic regions of Switzerland using smartphone cameras. Image names contain a letter referring to depicted plant parts: b = bark, i = inflorescence, f = infructescense, s = several parts, v = vegetative parts.
Photos are grouped in folders by observation (individual or population), i.e., photos in the same folder are of the same species, observed at the same time and sampling plot. At a higher organisational level, these folders are grouped by sampling plot (usually 3×3 m in open areas and 10×10 m in forests). The main folder contains metadata including taxon name, sampling time and location, as well as the TypoCH habitat type encoded as integers.
This data set accompanies the following publication:
Popp, M. R., Zimmermann, N. E. & Brun, P. Evaluating the use of automated plant identification tools in biodiversity monitoring—a case study in Switzerland. _Ecological Informatics_ **103316** (2025) doi:[10.1016/j.ecoinf.2025.103316](https://doi.org/10.1016/j.ecoinf.2025.103316).

en: testing vascular-plants plant-species photo species-observations

en: Photos of vegetative and reproductive parts of 560 vascular plant species taken in all biogeographic regions of Switzerland

photo

display_name: photo

plant-species

display_name: plant-species

species-observations

display_name: species-observations

testing

display_name: testing

vascular-plants

display_name: vascular-plants


en: “Flavescence dorée” (FD) is a quarantine grapevine disease associated with FD phytoplasmas (FDp). In Switzerland, FD was identified in 2004 in the southernmost part of Canton Ticino (TI) and then rapidly propagated throughout the entire regional winegrowing area despite the mandatory control measures. The reported widespread distribution of gone-wild grapevines (GWGV) in TI raised the hypothesis of a potential role of GWGV as an FDp reservoir and as a habitat for FDp vectors. To test this assumption, GWGV and FDp vectors were sampled in 13 plots to attest their infection status and compare the FDp genetic profiles. The primary (Scaphoideus titanus) and best-candidate alternative (Orientus ishidae) vectors were collected throughout the season and were found in moderate to high abundance in all the study area. The infection rate of both GWGV and S. titanus followed the historical gradient of S. titanus arrival and dispersal in TI with a clear geographic distinction between the southern and northern part of TI. Interestingly, the rate measured for S. titanus was similar to that observed in highly FD-infested cultivated vineyards. Moreover, the genetic profiles of the infected GWGV and S. titanus samples were identical to those commonly observed in cultivated vineyards (map M54). Importantly, four specimens of O. ishidae were also found harboring the same genotype. This study emphasizes the importance of GWGV (and abandoned vineyards) and alternative vectors for the FD epidemics in FD-infested regions, as well as a potential origin for FD outbreaks in areas currently designated as FDp-free.

en: genotyping orientus-ishidae switzerland scaphoideus-titanus grapevine-yellows southern-switzerland flavescence-doree

envidat

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

en: EnviDat: the Environmental Data Portal

en: Gone-wild grapevines in forests host phytoplasma genotypes linked to grapevines Flavescence doree epidemics in cultivated vineyards and competent vectors

de:
Resource Title: Fig1.tif
    Size: 9840462 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/7f549751-89fa-4ec7-bff2-2ebe6dbb752c/download/fig1.tif
    Description: Location of the experimental plots in Canton Ticino
(a) Location of the study area within Switzerland; T = Ticino
(b) Black dots: plots hosting GWGVs monitored for the presence of FDp-infected insect and plant samples.
Sopra = Sopraceneri (Ticino); Sotto = Sottoceneri (Ticino). Grey areas = cultivated vineyard area.

de:
Resource Title: Online_Resource_1.docx
    Size: 28482 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/5cb014fc-23e8-48dc-a60d-fdadd4630c78/download/online_resource_1.docx
    Description: Phytoplasma sequences from this work and reference strains with their GenBank accession number, hosts, geographic origin and reference.

de:
Resource Title: Table_1.docx
    Size: 20794 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/82445fda-75b9-490c-a8e8-a71958f2e3db/download/table_1.docx
    Description: Plot characteristics in terms of coordinates, region, mean slope, closest distance from nearest cultivated vineyard (DV), distance range between yellow sticky trap and nearest forest edge (DF), last time registered as cultivated vineyard (Last_T); absolute captures (N) and mean captures per hundred leaves (mean/100 leaves ± SE) during nymph collection for Scaphoideus titanus and Orientus ishidae, absolute captures (N) and mean captures per single yellow sticky trap (mean/trap ± SE).

de:
Resource Title: Table_3.docx
    Size: 15404 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/cfc1e011-612e-48ce-99ee-73427264ab12/download/table_3.docx
    Description: Results of molecular analysis for the detection of Flavescence dorée phytoplasma in symptomatic and asymptomatic leaf samples collected from gone-wild grapevines; number of analyzed and infected leaf samples, and map genotype (conducted on all FDp-infected samples).

de:
Resource Title: Table_2.docx
    Size: 16961 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/bade5ec3-6d04-4fcb-a35f-dccec84dd114/download/table_2.docx
    Description: Molecular characterization of the Flavescence dorée phytoplasma detected in Scaphoideus titanus and Orientus ishidae specimens collected on gone-wild grapevines; number of analyzed and infected insect specimens and genotype profile for the map, vmpA and malG genes.

de:
Resource Title: Fig3.jpg
    Size: 3981322 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/8649c388-56cc-44eb-8ae5-10c43a41fecf/download/fig3.jpg
    Description: Phylogenetic tree of the map (a; partial) and vmpA (b) genes sequences from Scaphoideus titanus, Orientus ishidae and gone-wild grapevines obtained in this work and reference strains from Genbank (see Online Resource 1). Maximum likelihood phylogeny based on nucleotide sequences of (A) map (543 bp) and (B) vmpA (465 bp) genes. The numbers on branches indicate the level of bootstrap support (500 replicates). Support values above 70% are labeled. The scale bar shows the number of substitutions per site.

de:
Resource Title: Fig2a.tif
    Size: 27909824 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/8ef34548-f561-4866-91d4-d9eb418f0fe1/download/fig2a.tif
    Description: Flavescence dorée detection on the analyzed insect (a) and gone-wild grapevine (b) samples
(a)	Circles: location with insect vectors tested for Flavescence dorée phytoplasma; horizontal bar: S. titanus FDp-infected with map-genotype M54; diagonal line top right to bottom left; O. ishidae FDp-infected with map-genotype M54; diagonal line top left to bottom right: O. ishidae FDp-infected with map-genotype M50
(b)	Circles: Gone-wild grapevines (GWGV) tested for FDp; vertical bar: symptomatic and FDp-infected samples; horizontal bar: asymptomatic and FDp-infected samples. Sopra = Sopraceneri (Ticino); Sotto = Sottoceneri (Ticino). Grey areas = cultivated vineyard area.

flavescence-doree

display_name: flavescence-doree

genotyping

display_name: genotyping

grapevine-yellows

display_name: grapevine-yellows

orientus-ishidae

display_name: orientus-ishidae

scaphoideus-titanus

display_name: scaphoideus-titanus

southern-switzerland

display_name: southern-switzerland

switzerland

display_name: switzerland


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.

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

envidat

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.

de: EnviDat: das Umwelt-Datenportal

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

envi

en: Environment

de:
Resource Title: Matlab Data
    Size: 1008529 bytes
    Format: application/x-matlab
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/2cbff0e6-bf62-4476-a533-10cb745520ed/download/edebeli_acp_2020__data.mat
    Description: All data as Matlab mat file

de:
Resource Title: Matlab Script to view and plot data
    Size: 9299 bytes
    Format: application/vnd.wolfram.mathematica.package
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/b718b5db-b15c-4f88-95a9-ce649b79308a/download/edebeli_acp_2019__snowbrmet.m
    Description:

de:
Resource Title: Readme file
    Size: 503143 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/d41fa166-35e9-430f-b96d-a5862556d9cd/download/edebeli_acp_2019__snowbrmet.pdf
    Description: This file shows data, code, and plots.

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


hymenoptera

en:
Hymenopteran data from all historic up to the recent projects (29.10.2019) of WSL, collected with various standardized methods in landscapes of different types.
Data are provided on request to contact person against bilateral agreement.

en: urban arthropoda agricultural hymenoptera hautfluger forests

de: EnviDat

en: Hymenoptera

title_for_slug: hymenoptera

envi

de: Umwelt

agricultural

display_name: agricultural

arthropoda

display_name: arthropoda

forests

display_name: forests

hautfluger

display_name: hautfluger

hymenoptera

display_name: hymenoptera

urban

display_name: urban


en:
Important note: From 2025 the NEAD format is being transformed into the interoperable CSV (iCSV) format, a formalized and standardized evolution of the NEAD format. Furthermore, iCSV should be backwards compatible with NEAD. More information on the new iCSV format will be linked here in due time.
Acknowledgement: The NEAD format includes NetCDF metadata and is proudly inspired by both SMET and NetCDF formats. NEAD is designed as a long-term data preservation and exchange format.
The NEAD specifications were presented at the "WMO Data Conference 2020 - Earth System Data Exchange in the 21st Century" (Virtual Conference).
-----------------------
Summary:
The Non-Binary Environmental Data Archive (NEAD) format is being developed as a generic and intuitive format that combines the self-documenting features of NetCDF with human readable and writeable features of CSV. It is designed for exchange and preservation of time series data in environmental data repositories.
License: The NEAD specifications are released to the public domain under a Creative Commons CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

en: meteorological-data-format csv nead metadata-convention research-data-management

en: Non-Binary Environmental Archive Data (NEAD) format

de:
Resource Title: NEAD on GitHub
    Size: 1024 bytes
    Format: No Info
    URL: https://github.com/GEUS-PROMICE/NEAD
    Description:

de:
Resource Title: NEAD syntax v0.1 (EBNF)
    Size: 3383 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d51285c9-953d-42e5-a925-20209cde10e5/resource/bf21243d-cdb9-47a8-a15b-d42efaef5d82/download/ebnf.txt
    Description:

de:
Resource Title: PyNEAD (future reference implementation)
    Size: 1024 bytes
    Format: No Info
    URL: https://github.com/GEUS-PROMICE/pyNEAD
    Description:

de:
Resource Title: MeteoIO (future reference implementation)
    Size: 1024 bytes
    Format: text/html
    URL: https://www.slf.ch/en/services-and-products/meteoio.html
    Description:

format: HTML

media_type: text/html

csv

display_name: csv

metadata-convention

display_name: metadata-convention

meteorological-data-format

display_name: meteorological-data-format

nead

display_name: nead

research-data-management

display_name: research-data-management


en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present downscaled climate data for the CORDEX EUR11 domain at a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperature lapse rates. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height. The resulting data consist of a daily temperature and precipitation timeseries.
The data is distributed under a: Creative Commons: Attribution 4.0 International (CC BY 4.0) license.

en: minimum-temperature europe air-temperature eur11 precipitation maximum-temperature cordex daily-climate

en: High resolution climate data for Europe

de:
Resource Title: CHELSA_EUR11 technical documentation
    Size: 713475 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/9e2c4a69-443d-4eb1-b8ab-697fd50bc7d2/resource/bc1df26a-0b8f-4547-872d-f00ed45db554/download/chelsa_eur11_technical_documentation.pdf
    Description: Technical documentation of the data with variable names and methodology.

de:
Resource Title: Data Access
    Size: 2199023255552 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav2&prefix=EUR11%2F
    Description:

air-temperature

display_name: air-temperature

cordex

display_name: cordex

daily-climate

display_name: daily-climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation


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.

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

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

de:
Resource Title: Data Set Documentation: alptal_Isotopes_daily_2015-2019_v2
    Size: 158372 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6a2fefc6-ce6d-4eb7-9ea9-c37b64959437/resource/d26ca42e-4cdb-4ef8-bf35-a87d5239757d/download/data-set-documentation_sdata-21-00930.pdf
    Description: Documentations contains meta data of the data columns and information about the study catchments.

de:
Resource Title: Alptal_Isotopes_daily_2015-2019_v2.txt
    Size: 760332 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/6a2fefc6-ce6d-4eb7-9ea9-c37b64959437/resource/7865517d-357b-4e08-8b6a-b405eca4e547/download/alptal_isotopes_daily_2015-2019_v2.txt
    Description: Version 2 of the dataset contains additional information on:
- line-conditioned (lc) excess
- precipitation sample volumes
- isotope data quality

de:
Resource Title: Alptal_Isotopes_daily_2015-2019
    Size: 717293 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/6a2fefc6-ce6d-4eb7-9ea9-c37b64959437/resource/8a06beab-3092-45d3-ad41-a59d79e6cb71/download/alptal_isotopes_daily_2015-2019.txt
    Description: 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

alptal

display_name: alptal

catchment

display_name: catchment

hydrology

display_name: hydrology

stable-water-isotope

display_name: stable-water-isotope

stream-water

display_name: stream-water


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.

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

envidat

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

en: EnviDat: the Environmental Data Portal

en: Angle of repose experiments with natural and spherical snow

de:
Resource Title: README.txt
    Size: 1024 bytes
    Format: text/plain
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.149/2020_aor_paper_willibald_jog/readme.txt
    Description:

de:
Resource Title: Angle of repose and 3D CT images
    Size: 4831838208 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.149/2020_aor_paper_willibald_jog
    Description: 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)

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


en:
This data set includes material and results described in the related research article:
Bergfeld, B., van Herwijnen, A., Reuter, B., Bobillier, G., Dual, J., and Schweizer, J.: Dynamic crack propagation in weak snowpack layers: Insights from high-resolution, high-speed photography, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2020-360, in review, 2021.
 Context:
In order to study crack propagation in weak snowpack layers in great detail, we recorded Propagation Saw Test (PST) experiments using a high-speed camera and applied digital image correlation (DIC) to derive displacement and strain fields in the slab, weak layer, and substrate. We demonstrated the versatility and accuracy of the DIC method by showing measurements from three PST experiments, resulting in slab fracture, crack arrest and full propagation in the related publication.
 Content:
- Supplementary material for related publication
- Ilustrative videos showing crack propagation
- High-speed recordings of the Experiments
(the raw .cine files are available upon request)
Processed Data containing:
   - displacement, velocity and acceleration fields for the three PSTs
   - speed and touchdown dataset

en: snow-avalanche snow-mechanics experiment crack-propagation snow

envidat

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.

de: EnviDat: das Umwelt-Datenportal

en: Dataset for "Dynamic crack propagation in weak snowpack layers: Insights from high-resolution, high-speed photography"

envi

en: Environment

de:
Resource Title: Crack speed and Touchdown distance data
    Size: 1818413 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/be3f7643-88ab-456c-9554-aa068ac76bb7/resource/4d88c59e-44a7-4c9f-84b8-ffd6f499f05f/download/speeds_and_touchdown_datasets.zip
    Description: Data is stored as netcdf files as python/xarray Datasets.
Datasets are self-explaining and contain the necessary information and metadata.
Information on how to load the netCDF files (datasets) can be found at "http://xarray.pydata.org/en/stable/"

de:
Resource Title: Supplementary material
    Size: 299124 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/be3f7643-88ab-456c-9554-aa068ac76bb7/resource/89d474b4-0965-4b96-ac8e-ff80e5aa0bd5/download/2020_bergfeld_crack_propagation_dynamics-supplement.pdf
    Description: # Supplementary material to the publication Bergfeld et al 2021
- description of the reverse crack
- additional snowpack parameters derived from the SMP measurements

de:
Resource Title: Videos
    Size: 17687958 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/be3f7643-88ab-456c-9554-aa068ac76bb7/resource/a2beba55-6766-4666-b03a-24673b2d1f8e/download/reduced_raw_videos.zip
    Description: The videos are .mp4 exports of the raw files (reduced 50 times in time)

de:
Resource Title: DIC Data
    Size: 28991029248 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.231/bergfeld_et_al_2021/
    Description: Data contains the displacement, strain, velocity and acceleration fields measured during the crack propagation process in our three example Propagation Saw Tests (PSTs). Data is stored as netcdf files as python/xarray Datasets. Datasets are self-explaining and contain the necessary metadata (field notes on the PSTs, camera settings, Digital Image Corrrelation parameters, preprocessing parameters).

Information on how to load the netCDF files (datasets) can be found at "http://xarray.pydata.org/en/stable/"

de:
Resource Title: Videos of crack propagation
    Size: 421948545 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/be3f7643-88ab-456c-9554-aa068ac76bb7/resource/08523c06-7691-4a95-ac18-9782e3fc0306/download/cracking_videos.zip
    Description: The videos show the cracking process in three example Propagation Saw Tests (flat field). The upper panel shows strain on top of the recorded movie frames. The second row shows vertical (*w*, blue line) and horizontal (*u*, orange line) displacement fields. The third and fourth row show the first and second time derivatives, namely the velocity and acceleration field.

crack-propagation

display_name: crack-propagation

experiment

display_name: experiment

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-mechanics

display_name: snow-mechanics


en:
This dataset contains data and scripts for "CRYOWRF - a validation and the effect of blowing snow on the Antarctic SMB" (Gerber et al., submitted).
* Simulation_setup: Namelists and input information to run the simulation. Some input files need to be downloaded from Sharma et a., 2021.
* Static_input: Static topography input file of WRF (geo_em.d01).
* WRF_27km_NoahMP: Preprocessed WRF output of the simulation run with the WRF using the surface parameterization Noah-MP to reproduce the figures and results in the paper.
* WRF_27km_CRYOWRF: Preprocessed WRF output of the simulation run with CRYOWRF to reproduce the figures and results in the paper.
* Scripts_Reproducibility: Python scripts to reproduce the figures and results in the paper.
Note:
* To run some of the scripts Atmospheric Weather station data needs to be prepared using Gerber and Lehning, 2022.
* AWS data is not provided and needs to be downloaded from the corresponding databases. Please make sure to comply with the respective terms and conditions.

en: blowing-snow cryowrf surface-mass-balance reproducibility antarctica

de: EnviDat

en: Reproducibility dataset for CRYOWRF validation

envi

de: Umwelt

de:
Resource Title: Scripts_Reproducibility_v2
    Size: 3051205 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/d05a9210-b303-45cc-8f2d-f4292951df2e/download/scripts_reproducibility_v2.zip
    Description: Python scripts to reproduces figures in Gerber et al., 2022, revised

de:
Resource Title: WRF_27km_NoahMP
    Size: 6657199309 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.347/WRF_27km_NoahMP.zip
    Description: Processed WRF output (run with Noah-MP land surface model) used for the analysis and the figures in the paper.

de:
Resource Title: Static_input
    Size: 5034051 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/aa57ffee-2ec1-4561-8673-cf3d03cedeaf/download/static_input.zip
    Description: Static input data from the WRF simulations (used in the python scripts in Scripts_Reproducibility).

de:
Resource Title: Scripts_Reproducibility_v1
    Size: 3227134 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/65815232-fd6a-4d1d-a280-a1ebc1c30375/download/scripts_reproducibility.zip
    Description: Python scripts to reproduces figures in Gerber et al., 2022, submitted.

de:
Resource Title: WRF_27km_CRYOWRF
    Size: 28991029248 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.347/WRF_27km_CRYOWRF.zip
    Description: Processed CRYOWRF output used for the analysis and the figures in the paper.

de:
Resource Title: Simulation_setup
    Size: 10669 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/79646165-0b4f-4495-b06a-dcd52d403019/download/simulation_setup.zip
    Description: Namelist and input files and information to run the WRF and CRYOWRF simulations used in the paper.

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

cryowrf

display_name: cryowrf

reproducibility

display_name: reproducibility

surface-mass-balance

display_name: surface-mass-balance


en:
Data accompanying David Wagners' Dissertation.
Covers model results and various input from ALPINE3D and SNOWPACK adjusted for sea ice during MOSAiC.

en: snow-distribution drifting-and-blowing-snow surface-mass-balance arctic-sea-ice spatial-variability

en: MOSAIC Snow on Sea Ice Data

de:
Resource Title: SNOWPACK setup for MOSAiC
    Size: 2386070 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.381/snowpack_jgr.zip
    Description:  The zip file contains both input and output data as well as the model configuration as used in the submitted manuscript "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

The zip file contains 2 main folders:
* SNOWPACK_JGR_ALPHA1
* SNOWPACK_JGR_ALPHA3

In the SNOWPACK_JGR_ALPHA1 (reference "SP_R" simulation) and SNOWPACK_JGR_ALPHA3 (comparison "SP_C" scenario) folders you find the corresponding inputs, outputs and configuration as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each SNOWPACK_JGR_ALPHA/setup/io.ini file. The input data is already linked accordingly in each io.ini file.

To reproduce the results, download and compile the source code for the adjusted SNOWPACK model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/snowpack.git under the "snowpack_mosaic" branch. After installing, you can run the provided model setup uploaded here.

de:
Resource Title: ALPINE3D setup for MOSAiC
    Size: 9663676416 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.381/a3d_jgr.zip
    Description: The zip file contains a folder structure that must be kept as it is in order to run the simulation in the current configuration.
The setup contains both input and output data as well as the model configuration as used in the submitted manuscript
"Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

The zip file contains 3 main folders:
* base_setup_files
* a3d_jgr_alpha1
* a3d_jgr_alpha3

The "base_setup_files" contains all input files that are necessary to run the reference (R) simulation ("a3d_jgr_alpha1" folder) and the comparison "C" scenario ("a3d_jgr_alpha3") folder. In the a3d_jgr_alpha1 and a3d_jgr_alpha3 folders you find the corresponding outputs as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each a3d_jgr_alphax/setup/io.ini file. The input data is already linked accordingly in each io.ini file.

a3d_jgr_alpha1 also contains the detailed snow profiles for each point along the transects.

To reproduce the results, download and compile the source code for the adjusted ALPINE3D model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/alpine3d.git under the "alpine3d_mosaic" branch. After installing, you can run the provided model setup uploaded here.

arctic-sea-ice

display_name: arctic-sea-ice

drifting-and-blowing-snow

display_name: drifting-and-blowing-snow

snow-distribution

display_name: snow-distribution

spatial-variability

display_name: spatial-variability


en:
This dataset provides a Swiss-wide mosaic of night-time lights, derived from SDGSAT-1 GLI satellite imagery. The mosaic contains median radiance values based on observations from winter 2023/24. Poor-quality images (due to factors such as clouds, inconsistent geometric accuracy or excessive noise) have been manually excluded.
The potential of SDGSAT-1 night-time lights data for ecological applications is discussed in Weber et al. ([2025](https://doi.org/10.1002/rse2.70011)).
**Two mosaic types are available**
-PAN Radiance (10 m resolution) with three bands: Panchromatic Low (PL), Panchromatic High (PH), and High Dynamic Range (HDR)
-RGB Radiance (40 m resolution) with three bands: Red, Green, and Blue
**Additional layers for PAN/RGB include**
-Number of observations per pixel (OBS)
-Standard deviation of radiance values per pixel (SD)
**Additional information**
-Radiance values were calculate based on the calibration values (gain, bias) V3.0
-Radiance values were converted to nW/cm^2/sr
-Of the three panchromatic bands, HDR is recommended for use as it is the weighted average of 50% of the PL and PH data.
-Access and more information about SDGSAT-1 data: [sdgsat.ac.cn](https://www.sdgsat.ac.cn)
**Attribution**
This dataset is based on SDGSAT-1 imagery provided by the International Research Center of Big Data for Sustainable Development Goals (CBAS). It is acknowledged that the SDGSAT-1 data are kindly provided by CBAS for non-commercial use.
For questions or collaboration, contact: dominique.weber@wsl.ch

en: remote-sensing alan sdgsat-1 conservation ecology light-pollution

envidat

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.

en: SDGSAT-1 Night-Time Lights Mosaic for Switzerland

de:
Resource Title: SDGSAT-1 RGB SD
    Size: 49250595 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/ba3f98b9-2a9d-49b4-aa44-17549fa73d5d/download/sdgsat1_gli_2023-2024_rgb_sd.tif
    Description: Standard deviation (SD) of all radiance values which were used to generate the RGB mosaic.

- GeoTIFF, 40 m resolution, EPSG:2056
- Band 1: SD of RED, Band 2: SD of GREEN, Band 3: SD of BLUE

de:
Resource Title: SDGSAT-1 PAN Radiance
    Size: 260859708 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/9c85891b-eac8-46b3-91d9-c0abf10ac640/download/sdgsat1_gli_2023-2024_pan_median_radiance.tif
    Description: Swiss-wide panchromatic night-time lights mosaic showing median radiance values from SDGSAT-1 GLI observations in winter 2023/2024.

- GeoTIFF, 10 m resolution, EPSG:2056
- Band 1: PL, Band 2: PH, Band 3: HDR

de:
Resource Title: SDGSAT-1 RGB Radiance
    Size: 26283647 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/b93e8d1e-8f29-40b9-a120-e363f9617bb7/download/sdgsat1_gli_2023-2024_rgb_median_radiance.tif
    Description: Swiss-wide RGB night-time lights mosaic showing median radiance values from SDGSAT-1 GLI observations in winter 2023/2024.

- GeoTIFF, 40 m resolution, EPSG:2056
- Band 1: RED, Band 2: GREEN, Band 3: BLUE

de:
Resource Title: SDGSAT-1 PAN SD
    Size: 728641887 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/72b94910-5a08-4d43-8023-8c8ddcaf8168/download/sdgsat1_gli_2023-2024_pan_sd.tif
    Description: Standard deviation (SD) of all radiance values which were used to generate the panchromatic mosaic.

- GeoTIFF, 10 m resolution, EPSG:2056
- Band 1: SD for PL, Band 2: SD for PH, Band 3: SD for HDR

de:
Resource Title: SDGSAT-1 PAN OBS
    Size: 33168454 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/8849653f-4efb-4f50-bb15-05542f229615/download/sdgsat1_gli_2023-2024_pan_nbr_obs.tif
    Description: Number of observations (OBS) which were used to generate the panchromatic mosaic.

- GeoTIFF, 10 m resolution, EPSG:2056
- OBS with identical values for each band

de:
Resource Title: SDGSAT-1 RGB OBS
    Size: 3384417 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/96befb49-9ab3-419f-abc9-694ecd0c1257/download/sdgsat1_gli_2023-2024_rgb_nbr_obs.tif
    Description: Number of observations (OBS) which were used to generate the RGB mosaic.

- GeoTIFF, 40 m resolution, EPSG:2056
- OBS with identical values for each band

alan

display_name: alan

conservation

display_name: conservation

ecology

display_name: ecology

light-pollution

display_name: light-pollution

remote-sensing

display_name: remote-sensing


en:
This dataset contains datasets of sub-canopy meteorological variables acquired in coniferous forest stands in Switzerland (Davos, Engadine) and Finland (Sodankylä) during the winters 2018 and 2019. The data are presented and used in the publication:
Mazzotti, G., Essery, R., Webster, C., Malle, J.,  & Jonas T. (2020)
Process-level evaluation of a high-resolution forest snow model using observations from mobile multi-sensor platforms
Water Resources Research, under review
The above publication must be cited when using this dataset, and the user is referred to the publication for additional detail.
Data are grouped into 4 folders:
1) Point data includes wind speed data measured with stationary meteorological stations
2) Transect data includes data of incoming short- and longwave radiation, air and snow surface temperature acquired with an automated calblecar system along within-stand transects
3) Grid data includes data of incoming short- and longwave radiation, air and snow surface temperature acquired on 40x40m gridded plots using a handheld instrument, as well as snow depth data measured at the same grids.
Canopy structure information derived from hemispherical images is included for each all surveyed locations as well, and an overview of the field sites is provided.

en: snow-models forest-structure meteorological-data forest-snow snow-energy-balance

envidat

de: EnviDat: das Umwelt-Datenportal

de: EnviDat

en: Distributed sub-canopy datasets from mobile multi-sensor platforms (CH / FIN, 2018-2019) for hyper-resolution forest snow model evaluation

de:
Resource Title: Point data
    Size: 195016 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0fb10027-6f49-4953-8683-76fc83ea1154/resource/05210541-6b04-487b-bf39-8817d31d5106/download/point_data.zip
    Description: Wind speed data acquired with the portable meteorological stations

de:
Resource Title: Grid data
    Size: 11193263 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0fb10027-6f49-4953-8683-76fc83ea1154/resource/a5d954ef-a693-4e43-8e66-75ed21178a92/download/grid_data.zip
    Description: Canopy structure and snow depth data at the grids

de:
Resource Title: Transect data
    Size: 1360922505 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0fb10027-6f49-4953-8683-76fc83ea1154/resource/f2dc7eef-dc3c-46f5-99ca-9c12ac154175/download/transect_data.zip
    Description: All meteorological and canopy structure data acquired at cable car transects

de:
Resource Title: Site overview
    Size: 203756 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/0fb10027-6f49-4953-8683-76fc83ea1154/resource/b6151bb0-2568-4ae8-b91a-7e2d572e01b9/download/field_sites_overview.jpg
    Description: Overview of field sites

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

meteorological-data

display_name: meteorological-data

snow-energy-balance

display_name: snow-energy-balance

snow-models

display_name: snow-models


en:
This dataset contains all data, on which the following publication below is based.
**Paper Citation**:
Neff, F., Korner-Nievergelt, F., Rey, E., Albrecht, M., Bollmann, K., Cahenzli, F., Chittaro, Y., Gossner, M. M., Martínez-Núñez, C., Meier, E. S., Monnerat, C., Moretti, M., Roth, T., Herzog, F., Knop, E. 2022. Different roles of concurring climate and regional land-use changes in past 40 years' insect trends. Nature Communications, DOI: [10.1038/s41467-022-35223-3](https://doi.org/10.1038/s41467-022-35223-3)
Please cite this paper together with the citation for the datafile. Please also refer to this publication for details on the methods.
 Summary
Mean annual occupancy estimates for 390 insect species (215 butterflies [Papilionoidea, incl. Zygaenidae moths], 103 grasshoppers [Orthoptera], 72 dragonflies [Odonata]) for nine bioclimatic zones in Switzerland. Covers the years 1970-2020 (for butterflies) and 1980-2020 (for grasshoppers and dragonflies). Mean occupancy denotes the average number of 1 km x 1 km squares in a zone occupied by the focal species. Occupancy estimates stem from occupancy-detection models run with species records data hosted and curated by [info fauna](http://www.infofauna.ch). Data on the level of single MCMC iterations of model fitting are included (4000 sampling iterations). The nine bioclimatic zones were defined based on biogeographic regions and two elevation classes (square above or below 1000 m. asl)

en: elevation infospecies occupancy-models insects switzerland butterflies insect-decline biogeographical-region

envidat

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

en: EnviDat: the Environmental Data Portal

en: Mean insect occupancy 1970–2020

envi

de: Umwelt

biogeographical-region

display_name: biogeographical-region

butterflies

display_name: butterflies

elevation

display_name: elevation

infospecies

display_name: infospecies

insect-decline

display_name: insect-decline

insects

display_name: insects

occupancy-models

display_name: occupancy-models

switzerland

display_name: switzerland