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

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

envidat

en: EnviDat: the Environmental Data Portal

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

en:
Resource Title: WRF outputs
    Size: 741751014 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a014f39f-34c3-499f-9627-0efde504d2e1/resource/45b96d72-d1ef-4208-8b22-6c6ab546208b/download/wrf-outputs.zip
    Description: The .zip file contains all the NetCDF outputs produced by the mesoscale Weather Research and Forecasting (WRF) model (version: 4.0.1). Two case studies were simulated in this study, between 25-28 January 2014 (00:00 UTC) and 29 January - 1 February 2014 (00:00 UTC), respectively. The former is denoted as "NW" and the latter as "SE", owing to the prevailing wind conditions at the Jungfraujoch (JFJ) station.

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

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

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

en:
Resource Title: Observational data
    Size: 4448 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a014f39f-34c3-499f-9627-0efde504d2e1/resource/4ea9d0c6-106e-424a-9d61-9fc1dc99f576/download/observations.zip
    Description: The .zip file contains 6 .csv files including all microphysical measurements taken at the Jungfraujoch station during the two periods of interest:

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

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

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

blowing-snow

display_name: blowing-snow

ice-crystal-number-concentration

display_name: ice-crystal-number-concentration

ice-water-content

display_name: ice-water-content

jungfraujoch

display_name: jungfraujoch

liquid-water-content

display_name: liquid-water-content

secondary-ice-production

display_name: secondary-ice-production

swiss-alps

display_name: swiss-alps

wrf

display_name: wrf


$oid: OBSOLETE

en:
Data associated to the publication "Environmental DNA sequences from aquatic insects indicate freshwater ecosystem state"
 Authors:
Flurin Leugger, Martina Lüthi, Meret Jucker, Virginie Marques, Sarah Thurnheer, Zacharias Kontarakis and Loïc Pellissier
 Contact:
flurinleugger@gmail.com
loic.pellissier@usys.ethz.ch
 Project description:
In this project, we aimed to compare kick-sampling-derived taxa lists and ecosystem state classifications (IBCH: Indece biologique Suisse) with eDNA metabarcoding and CRISPR-Dx. Additionally, we calculated the association with environmental variables and ecosystem state.
We retrieved the kick-sampling-derived data from Haberthür et al. (2021) and Keck et al. (2023). We collected eDNA samples in 36 sites in the Rhine catchment in Switzerland (lowland) which are used for the national monitoring of freshwater in Summer 2024. We extracted the samples in the clean lab at ETH using the protocol described in Leugger et al. (2025). We used the 16S Ins primer (Elbrecht et al. 2016) for metabarcoding and for CRISPR analysis. To select indicator eDNA metabarcoding sequences, we applied a machine learning approach combining LASSO and rpart decision trees. For CRISPR-Dx, we used the rules of Leski et al. (2023) to in silicon predict detections based on the metabarcoding sequences and used the same machine learning approach as for the indicator metabarcoding eDNA sequences (see publication for more details). The data for the environmental variables is from the SWECO25 database (https://zenodo.org/communities/sweco25/records?q=&l=list&p=1&s=10&sort=newest; Külling et al. 2024).
 Folders:
 catchments\:
Catchments in Switzerland, downloaded from https://data.geo.admin.ch/browser/index.html/collections/ch.bafu.wasser-einzugsgebietsgliederung/items/wasser-einzugsgebietsgliederung?.language=en&.asset=asset-wasser-einzugsgebietsgliederung_2056-gpkg-zip
The subfolder upstream_catchments includes the catchment for each buffer size tested.
comparison_classification_methods\:
File with the ecosystem state classification based on kick-sampling, indicator eDNA metabarcoding sequences (using the rpart decision tree) and CRISPR-Dx (using predicted, lab and retrained rpart trees).
 eDNA\:
 Folder metabarcoding\:
Raw and cleaned metabarcoding data (ASVs) per environmental extract (EVE), including taxa information from Ecotag reference data base. Additionally, the rpart trees for indicator sequences only from Ephemeroptera and all EPT are provided.
Columns which might not be self explanatory
taxon: identified taxon
rank: rank of identified taxon
nb_reads: read numbers
EVS and metabarcoding: key columns to link with metadata files
ASV_cleaned_by_site.csv: Read count by site (after cleaning)
ASV_raw_by_site.csv: Read count by site (before cleaning), column 'NC' is for the negative controls
sequence_count_per_site.csv: Comparison of reads per site before and after cleaning/filtering. 'NC' refers again to Negative Controls.
 Folder CRISPR\:
crispr_by_site.csv: Lab-based detection of the guide per site. Maximum number of detections is 6, as each site had two environmental extracts (EVE), and the PCR replicates were combined in 3 pools each. GRN refers to lab internal numbering of CRISPR-Dx assays.
detection_matrix_Ephemeroptera_28_site.csv: Predicted detection based on eDNA metabarcoding sequences and the model of Leski et al 2023 per site.
rpart_model_Ephemeroptera.rds: best performing rpart model for ecosystem state classification using the predicted CRISPR-Dx detections
rpart_model_retrained.rds: best performing rpart model for ecosystem state classification using the actual lab-based CRISPR-Dx detections (thus "retrained" based on actual detections).
 IBCH\:
IBCH_classification_filtered_and_extended.csv: includes IBCH_cat (ecosystem category from kick-sampling with IBCH 2019 categorization).
IBCH_taxa_kick-sampling.csv: contains taxa detect per site (site_code as column name to link with metadata or eDNA data)
kicknet_Trend_IBCH_sites.csv: taxa detected by site, raw data
 metadata\:
Folder containing files with overview of site names, extract number and coordinates. Columns named "metabarcoding" (and "EVS") are keys to link rows from the different tables.
 SWECO25\:
Folder containing raster stack from SWECO25 data (Külling et al. 2024) used in the article and a table with the extracted variable value per site/catchment with the different upstream buffer sizes tested.
site_code: Code for the sampling site, see also metadata to link to EVS
Temperature_avg: annual mean temperature in upstream catchment [°C]
Precip_annual: annual precipitation [mm]
Population_density: mean population density in 25m cells
Traffic_noise: noise levels
EVI, NDVI and LAI: each standard deviation (sd) and average (avg) value per upstream catchment
Natural rivers: proportion of upstream river length which is classified as natural
Little-disturbed_rivers: proportion of upstream river length which is classified as little disturbed
Heavily-disturbed_rivers: proportion of upstream river length which is classified as heavily disturbed
unnatural_rivers: proportion of upstream river length which is classified as unnatural
culverted_rivers: proportion of upstream river length which is culverted
Forest_edges: proportion of forest edges in upstream catchment
Forest: proportion of forest in upstream catchment
Crops: proportion of crops in upstream catchment
Built_environment: proportion of built environment in upstream catchment
buffer: buffer width for upstream catchment area [m]
catchment_area_m2: upstream catchment area in square meters
 References:
Elbrecht, V., Taberlet, P., Dejean, T., Valentini, A., Usseglio-Polatera, P., Beisel, J. N., Coissac, E., Boyer, F., & Leese, F. (2016). Testing the potential of a ribosomal 16S marker for DNA metabarcoding of insects. PeerJ, 2016(4). https://doi.org/10.7717/peerj.1966
Haberthür, M. (2021). Ergebnisse der 3. Erhebung NAWA-Trend Los 2, Makrozoobenthos. https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://www.bafu.admin.ch/dam/bafu/de/dokumente/wasser/externe-studien-berichte/nawa_trend_biologie_2019-teil_makrozoobenthos.pdf.download.pdf/nawa_trend_biologie_2019-teil_makrozoobenthos.pdf&ved=2ahUKEwjI5crG-IaPAxUF_gIHHQisBZEQFnoECBgQAQ&usg=AOvVaw1QL3GRZdTllPsHLQ6hQtlP
Külling, N., Adde, A., Fopp, F., Schweiger, A. K., Broennimann, O., Rey, P. L., Giuliani, G., Goicolea, T., Petitpierre, B., Zimmermann, N. E., Pellissier, L., Altermatt, F., Lehmann, A., & Guisan, A. (2024). SWECO25: a cross-thematic raster database for ecological research in Switzerland. Scientific Data, 11(1). https://doi.org/10.1038/s41597-023-02899-1
Leski, T. A., Spangler, J. R., Wang, Z., Schultzhaus, Z., Taitt, C. R., Dean, S. N., & Stenger, D. A. (2023). Machine learning for design of degenerate Cas13a crRNAs using lassa virus as a model of highly variable RNA target. Scientific Reports, 13(1), 6506. https://doi.org/10.1038/s41598-023-33494-4
Leugger, F., Lüthi, M., Schmidlin, M., Kontarakis, Z., & Pellissier, L. (2025). Rapid field-based detection of a threatened and elusive species with environmental DNA and CRISPR-Dx. Global Ecology and Conservation, 59, e03518. https://doi.org/10.1016/j.gecco.2025.e03518

en: dna-metabarcoding biomonitoring river-restoration aquatic-invertebrates crispr-dx landuse biodiversity-monitoring conservation edna

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

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: Assessing ecosystem state with environmental DNA of aquatic insects

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: metadata.zip
    Size: 18080 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/2596f08b-959e-45d1-9aaa-6694b81e43c2/download/metadata.zip
    Description:

format: ZIP

media_type: application/zip

en:
Resource Title: IBCH.zip
    Size: 13178 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/02849ade-2de9-43ce-b2bb-c99b0749f52f/download/ibch.zip
    Description:

en:
Resource Title: comparison_classification_methods.zip
    Size: 1165 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/a64df406-4654-423e-b5d5-a3835fb1ddc1/download/comparison_classification_methods.zip
    Description:

en:
Resource Title: eDNA.zip
    Size: 885782 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/d1e0c8df-b744-44f4-9721-e95e144bd7cc/download/edna.zip
    Description:

en:
Resource Title: catchments.zip
    Size: 244292996 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/352b1914-eab0-44eb-af50-1629b7c59060/download/catchments.zip
    Description:

en:
Resource Title: Readme.txt
    Size: 6898 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/f477b2e4-59f5-495d-b7fa-7a611161fb36/download/readme.txt
    Description:

format: TXT

media_type: text/plain

aquatic-invertebrates

display_name: aquatic-invertebrates

biodiversity-monitoring

display_name: biodiversity-monitoring

biomonitoring

display_name: biomonitoring

conservation

display_name: conservation

crispr-dx

display_name: crispr-dx

dna-metabarcoding

display_name: dna-metabarcoding

edna

display_name: edna

landuse

display_name: landuse

river-restoration

display_name: river-restoration


functional-invertebrate-groups-dataset

en: Collected Invertebrate data using pitfall traps at streetlights with different characteristics at three different sites in Switzerland (Birmensdorf, Lägern & Alpthal). LED characteristics are LED color temperature, light level and luminaire shape (K, L_level, Diff). Additionally, we had two pitfall trap positions: Center (C; 100% light intensity)) and  Periphery (P; 10% light intensity). The traps were emptied weekly over a period of two summers (2021 & 2022). The samples were sorted into 40 different taxonomic invertebrate groups. We included weeks where we turned of the light for a different experiement, these weeks were excluded from this dataset.

en: led invertebrates light-pollution artificial-lighting community-composition functional-groups alan

en: Functional Invertebrate Groups - Dataset

title_for_slug: functional-invertebrate-groups-dataset

format: CSV

alan

display_name: alan

artificial-lighting

display_name: artificial-lighting

community-composition

display_name: community-composition

functional-groups

display_name: functional-groups

invertebrates

display_name: invertebrates

led

display_name: led

light-pollution

display_name: light-pollution


en:
Raw data of paper: A recent ash dieback infection neither affects emerald ash borer
performance nor triggers a substantial systemic phytochemical
defense response in European ash (https://doi.org/10.1007/s10340-025-01981-4)
Raw data on emerald ash borer (EAB) weight gain, mortality, development and longevity. Raw data of ash phloem and leaf chemistry. Raw data of ash dieback (ADB) lesion length.

en: pest-invasion agrilus-palnipennis fraxinus-excelsior metabolomics ash-dieback

envidat

en: EnviDat: the Environmental Data Portal

en: Raw data-A recent ash dieback infection neither affects emerald ash borer performance nor triggers a substantial systemic phytochemical defense response in European ash

format: XLS

agrilus-palnipennis

display_name: agrilus-palnipennis

ash-dieback

display_name: ash-dieback

fraxinus-excelsior

display_name: fraxinus-excelsior

metabolomics

display_name: metabolomics

pest-invasion

display_name: pest-invasion


en:
The SwissRad10 dataset contains light availability maps at 10 m and hourly resolution across an entire annual cycle with wall-to-wall coverage across the whole of Switzerland.
Areas below and within 25 m of forests include light availability calculated for both leaf-on and leaf-off canopy structure, and terrain only data is available across the full domain.
The variables sky-view factor and direct-beam transmissivity are both included, allowing estimation of both direct and diffuse light at the ground surface.
The dataset was calculated using the detailed synthetic hemispheric image-based ray-tracing Canopy Radiation Model (CanRad) with the latest airborne lidar and terrain surface data from the swissSURFACE3D dataset.

en: shortwave-radiation terrain forests solar-irradiance lidar radiation-transfer light-availability transmissivity solar-energy sky-view-fraction

en: SwissRad10 Hourly light availability maps at 10 m resolution over Switzerland

forests

display_name: forests

lidar

display_name: lidar

light-availability

display_name: light-availability

radiation-transfer

display_name: radiation-transfer

shortwave-radiation

display_name: shortwave-radiation

sky-view-fraction

display_name: sky-view-fraction

solar-energy

display_name: solar-energy

solar-irradiance

display_name: solar-irradiance

terrain

display_name: terrain

transmissivity

display_name: transmissivity


en:
This repository contains data related to an interdisciplinary study on playgrounds, looking at both playground vegetation and the well-being of pre-school children using those playgrounds. This project was funded by and initiated at the Institute for Landscape Planning and Ecology (ILPÖ) of the University of Stuttgart, Germany. Data was collected by ILPÖ. The project was finalised in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). The aim of the study was to (1) describe playground vegetation (species richness and diversity at the ground, shrub and tree layers; habitat structure); (2) describe preschool children’s well-being and nature-connectedness; and (3) investigate whether there is a relationship between plant diversity and well-being while exploring potential other predictors of well-being, including children’s and parents’ or carer’s nature-connectedness, greenspace exposure, seasonality, and socio-demographic background.
We sampled ground (-1m height), shrub (1-2m height) and tree (-2m hieght) vegetation of 29 playgrounds of Stuttgart's inner city. Sampling took place between May 25 and July 01, 2021. Ground layer vegetation was sampled in ten one-by-one m2 quadrats per playground, within which we recorded the cover of each species based on the Braun-Blanquet scale. Woody vegetation was exhaustively sampled within the playgrounds and in a surrounding two meters buffer, recording each individual plant. Vegetation cover was visually estimated as a percentage for each vegetation layer, namely the ground, shrub and tree (canopy) layers.
In parallel, we distributed questionnaires to parents and carers to assess the well-being and connectedness-to-nature of preschool children (aged 6 or younger) across the seasons. The questionnaire covered children's (1) use of greenspaces, (2) nature-connectedness, (3) well-being, and (4) socio-demographic variables. Questionnaires were distributed accross all seasons: sampling seasons included autumn (Oct-Nov 2021), winter (Jan-Feb 2022), spring (April-May 2022) and summer (June-July 2022). Ethical approval was granted by the University of Stuttgart Commission on Responsibility in Research (Az. 21-033).

en: urban well-being seasons biodiversity green-spaces

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: Playground biodiversity and preschool children well-being

envi

en: Environment

en:
Resource Title: Spielplatz Fragebogen_Russisch.pdf
    Size: 357530 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/53481be4-b668-48c6-98df-c58961caf97b/download/spielplatz-fragebogen_russisch.pdf
    Description: This document includes the Russian version of the questionnaire administered to carers of pre-school children.

format: PDF

media_type: application/pdf

en:
Resource Title: Spielplatz Fragebogen_Deutsch.pdf
    Size: 364554 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/deca6461-d9a1-4cf4-8739-480e13432408/download/spielplatz-fragebogen_deutsch.pdf
    Description: This document includes the German version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Englisch.pdf
    Size: 340244 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/b87bc6b7-9aaa-4c86-adfc-52dcf47bcfb4/download/spielplatz-fragebogen_englisch.pdf
    Description: This document includes the English version of the questionnaire administered to carers of pre-school children. This was the original questionnaire, later translated in the 10 most spoken languages in Baden-Württemberg (DE).

en:
Resource Title: Spielplatz Fragebogen_Französisch.pdf
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    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/872f9d84-d7a4-498d-9f3e-5851bd9bddfd/download/spielplatz-fragebogen_franzosisch.pdf
    Description: This document includes the French version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Arabisch.pdf
    Size: 397855 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/56c767f8-0b3d-45c3-9209-2bce6dac682f/download/spielplatz-fragebogen_arabisch.pdf
    Description: This document includes the Arabic version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Türkisch.pdf
    Size: 346481 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/f49040c1-0140-4b98-8b3a-b8b6be4fd565/download/spielplatz-fragebogen_turkisch.pdf
    Description: This document includes the Turkish version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Italienisch.pdf
    Size: 322529 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/6971a33d-2b7d-40d4-8d99-d583aed944d2/download/spielplatz-fragebogen_italienisch.pdf
    Description: This document includes the Italian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Spanisch.pdf
    Size: 345221 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/c57948ab-c230-45c0-a9b2-b60eb3460cfd/download/spielplatz-fragebogen_spanisch.pdf
    Description: This document includes the Spanish of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Rumänisch.pdf
    Size: 349716 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/0ac43c39-4a0d-40c2-a544-e2a4e6109213/download/spielplatz-fragebogen_rumanisch.pdf
    Description: This document includes the Romanian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Well-being.xlsx
    Size: 184576 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/8b624832-b01e-4728-95cc-22644320da26/download/well-being.xlsx
    Description: This file contains the anonymised well-being and nature-connectedness data for the manuscript "Playground tree diversity: a driver of well-being in preschool children".

en:
Resource Title: Plant and playground data.xlsx
    Size: 97321 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/eb12671e-2a17-4acf-b181-a68e40fd1fe5/download/plant-and-playground-data.xlsx
    Description: This file contains the playground and plant diversity data for the manuscript "Playground tree diversity: a driver of well-being in preschool children".
The file is separated in five tabs containing:
(1) the overview of the playgrounds,
(2) the overview of all plant species, with their life-history traits and the diversity indexes per layer,
(3) the tree (canoy) layer abundance of each plant species, measured exhaustively in each playground,
(4) the shrub layer abundance of each plant species, measured exhaustively in each playground, and
(5) the ground layer abundance of each plant species, estimated with the Braun-Blanquet scale in 10 quadrats per playground.

en:
Resource Title: Spielplatz Fragebogen_Ukrainian.pdf
    Size: 1015736 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/1ae17430-7011-40f1-87d5-48f642e997ea/download/spielplatz-fragebogen_ukrainian.pdf
    Description: This document includes the Ukrainian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Polnisch.pdf
    Size: 361073 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/024bbf41-00b5-4c84-ba75-28e136050d41/download/spielplatz-fragebogen_polnisch.pdf
    Description: This document includes the Polish version of the questionnaire administered to carers of pre-school children.

biodiversity

display_name: biodiversity

green-spaces

display_name: green-spaces

seasons

display_name: seasons

urban

display_name: urban

well-being

display_name: well-being


en:
This repository contains data related to the field experiment of the WP3 (social impacts) of the ALANeX project. This project is a collaboration between the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and Elektrizitätswerk des Kantons Zürich (EKZ). It has received funding from the WSL programme EXtremes. The overall objective of the ALANeX project was to assess the ecological and social impact of anthropogenic light at night.
We conducted a randomized field experiment to compare the well-being benefits of exposure to streetlights of different correlated colour temperatures (CCT) during a 20-min stay in the centre of Richterswil, Swizerland, to explore:
 - the impact of exposure to streetlamps of different CCT on affect, self-reported stress and cortisol levels
- the differences in impression of artificial light and of the feeling of safety provided by streetlamps based on its CCT.

en: stress field-data urban-landscape artificial-lighting well-being

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: 01_Information sheet.pdf
    Size: 90044 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/9dd17102-a6b3-4a71-b3d3-89b1f198c3f9/download/01_information-sheet.pdf
    Description: This file includes the information sheet provided to participants before they consented to take part in the study.

en:
Resource Title: 05_Anonymised dataset.xlsx
    Size: 35941 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/fb8c2b1b-d969-4087-9606-f0944391938f/download/05_anonymised-dataset.xlsx
    Description: This file contains data for the manuscript "Randomised trial reveals a mismatch between preferences for and hormonal responses to anthropogenic light colour temperatures".

en:
Resource Title: 02_Particiants consent form.pdf
    Size: 121509 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/5817334b-fad2-47ce-972c-0ac3fb6758d9/download/02_informed-consent.pdf
    Description: This file contains the informed consent document that participants signed to participate in the study.

en:
Resource Title: 03_Questionnaire_t1.pdf
    Size: 70927 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/94abc98c-0c0b-482c-bf2d-9981f191ef4e/download/02_questionnaire_t1.pdf
    Description: This document includes the questionnaire administered at the first measurement time point (before exposure).

en:
Resource Title: 04_Questionnaire_t2.pdf
    Size: 486850 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/ca5b4cb0-bc6e-46c0-b177-a92505aedd1e/download/04_questionnaire_t2.pdf
    Description: This document includes the questionnaire administered at the second measurement time point (after exposure).

artificial-lighting

display_name: artificial-lighting

field-data

display_name: field-data

stress

display_name: stress

urban-landscape

display_name: urban-landscape


wasserschloss-europas

en:
*english description below
Die Schweiz als „Wasserschloss Europas“ ist eine etablierte Bezeichnung im öffentlichen Diskurs, die sich im Laufe der Zeit zu einer identitätsstiftenden Metapher entwickelt hat. Die Zeitungsanalyse der letzten 100 Jahre zeigt, wie sich die Verwendung dieser Metapher unter dem Einfluss äusserer Faktoren gewandelt hat. Das Jahr mit den meisten Zeitungsartikeln, in denen die Metapher verwendet wurde, war der Hitzesommer 2003. Weitere Jahre mit häufigem Vorkommen der Metapher fallen mit internationalen Ausstellungen (Expos) zusammen, bei denen sich die Schweiz als „Wasserschloss Europas“ präsentierte oder entsprechende Bezüge herstellte. Dabei diente die Metapher einerseits als Symbol für den Wasserreichtum des Landes, andererseits unterstrich sie die Rolle der Schweiz im Umweltschutz, deren Verantwortung gegenüber den Unterliegern; zudem diente sie der touristischen Vermarktung der Naturlandschaft. Lange Zeit galt der Wasserreichtum in der Schweiz als selbstverständlich, angesichts der rasanten Klimaerwärmung und des damit einhergehenden steigenden Nutzungsdrucks auf die Ressource Wasser und die aquatischen Lebensräume erscheint die Verwendung dieser beschaulichen Metapher als überholt.
Switzerland, as the “Wasserschloss Europas”, is an established term in public discourse that has evolved over time into an identity-shaping metaphor. A newspaper analysis spanning the last 100 years shows how the use of this metaphor has changed in response to external factors. The year with the highest number of newspaper articles employing the metaphor was the heatwave summer of 2003. Other years with high numbers of occurrences coincide with international exhibitions (Expos), where Switzerland presented itself as the “Wasserschloss Europas” or made related references. The metaphor served as a symbol of the country’s abundance of water and, highlighted Switzerland’s role in environmental protection and its responsibility towards downstream countries; it also supported the tourist marketing of its natural landscapes. For a long time, Switzerland’s water wealth was taken for granted. In view of rapid climate warming and the resulting increasing pressure on water resources and aquatic habitats, the use of this idyllic metaphor now seems outdated.

en: wasserschloss wasserressourcen metapher zeitungsartikelanalyse wasserwirtschaft

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: Wasserschloss Europas

title_for_slug: wasserschloss-europas

envi

en: Environment

en:
Resource Title: Kodierungsschema_Wasserschloss_Europas.pdf
    Size: 56023 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/83825ceb-c5ca-4c11-882e-235fd121734b/resource/1ff678b7-aa77-47ae-8fa7-7f78fbc5af34/download/kodierungsschema_wasserschloss_europas.pdf
    Description: Kodierungsschema für die Zeitungsartikelanalyse.

en:
Resource Title: Wasserschloss_Europas.xlsx
    Size: 72827 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/83825ceb-c5ca-4c11-882e-235fd121734b/resource/a2ec7e2b-4c6e-4787-94be-2ee0f3a78455/download/wasserschloss_europas.xlsx
    Description: Sammlung der 226 verwendeten Zeitungsartikel.

en:
Resource Title: Wasserschloss_Europas.csv
    Size: 128150 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/83825ceb-c5ca-4c11-882e-235fd121734b/resource/73611293-12d3-496b-a721-85b5d0eba126/download/wasserschloss_europas.csv
    Description:

metapher

display_name: metapher

wasserressourcen

display_name: wasserressourcen

wasserschloss

display_name: wasserschloss

wasserwirtschaft

display_name: wasserwirtschaft

zeitungsartikelanalyse

display_name: zeitungsartikelanalyse


en: These datasets and code support research on the community assemblage of aquatic macroinvertebrates in ephemeral microhabitats, specifically water-filled tree holes (WTH), in three biogeographically and climatically distinct old-growth forests: Temperate-Mediterranean (France), Neotropical (Brazil) and Palaeotropical (India). By integrating standardised biological sampling, detailed environmental measurements and spatial analysis, the dataset allows for an in-depth examination of how local habitat conditions and spatial configuration influence taxonomic and functional beta-diversity patterns. The data capture the variation in species composition and ecological traits in 35 WTH per forest site and are particularly important for understanding how environmental filtering and spatial processes shape beta-diversity in natural forest ecosystems.

en: water-filled-tree-holes metacommunity taxonomic-diversity functional-diversity spatial-factors environmental-factors beta-diversity community-assembly

en: Spatial factors shape taxonomic and functional beta-diversity in water-filled tree holes in different biogeographical regions

en:
Resource Title: Beta_diversity_analysis_across_sites_code.R
    Size: 43312 bytes
    Format: text/x-r
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/Beta_diversity_analysis_across_sites_code.R
    Description: Code to do the analysis and figures of the paper.

en:
Resource Title: Fig_1_Data.csv
    Size: 637 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/Fig_1_Data.csv
    Description: This dataset contains values of taxonomic and functional β-diversity for each study site, along with their respective components: species richness difference vs. turnover (taxonomic), and functional richness difference vs. functional turnover (functional). Used to generate Fig. 1.

media_type: text/csv

en:
Resource Title: EnvironmentalVariables.csv
    Size: 12854 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/EnvironmentalVariables.csv
    Description: This dataset includes physical and environmental characteristics of water-filled tree holes (WTHs), such as water depth, height, opening size, hole origin and orientation, circumference at breast height, WTH type, and water volume. It also contains physico-chemical parameters, nutrient concentrations (ammonium, nitrogen, phosphate, sulfate, chloride), CDOM, Chlorophyll-A, turbidity, and dry organic matter (FPOM, CPOM, total).

en:
Resource Title: CoordinatesIndia.csv
    Size: 1027 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/CoordinatesIndia.csv
    Description: This dataset provides the geographic coordinates (latitude and longitude) of each sampled water-filled tree hole (WTH) for the Indian forest plot.

en:
Resource Title: TraitFrance.csv
    Size: 1123 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/TraitFrance.csv
    Description: This dataset contains trait information used to characterize the macroinvertebrates in our study, for the French forest plot. The dataset includes seven trait groups: aquatic developmental stage, maximum body size, locomotion, dispersal mode, respiration mode, feeding group, and cohort production interval. These trait groups are further divided into 32 distinct categories.

en:
Resource Title: CoordinatesFrance.csv
    Size: 983 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/CoordinatesFrance.csv
    Description: This dataset provides the geographic coordinates (latitude and longitude) of each sampled water-filled tree hole (WTH) for the French forest plot.

en:
Resource Title: CoordinatesBrazil.csv
    Size: 1010 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/CoordinatesBrazil.csv
    Description: This dataset provides the geographic coordinates (latitude and longitude) of each sampled water-filled tree hole (WTH) for the Brazilian forest plot.

en:
Resource Title: TraitBrazil.csv
    Size: 2078 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/TraitBrazil.csv
    Description: This dataset contains trait information used to characterize the macroinvertebrates in our study, for the Brazilian forest plot. The dataset includes seven trait groups: aquatic developmental stage, maximum body size, locomotion, dispersal mode, respiration mode, feeding group, and cohort production interval. These trait groups are further divided into 32 distinct categories.

en:
Resource Title: TraitIndia.csv
    Size: 1932 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/TraitIndia.csv
    Description: This dataset contains trait information used to characterize the macroinvertebrates in our study, for the Indian forest plot. The dataset includes seven trait groups: aquatic developmental stage, maximum body size, locomotion, dispersal mode, respiration mode, feeding group, and cohort production interval. These trait groups are further divided into 32 distinct categories.

en:
Resource Title: CommunitiesFinal.csv
    Size: 12550 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/CommunitiesFinal.csv
    Description: This dataset describes the animal community composition sampled from 35 water-filled tree holes (WTHs) per site. It includes abundance and taxonomic identification (to morphospecies level) of aquatic macroinvertebrates and Chordata.

en:
Resource Title: Metadata.xlsx
    Size: 74562 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/Metadata.xlsx
    Description: This Excel file contains metadata that provides detailed information about all other files included here. It describes the ten accompanying datasets, outlining the type of data each contains, the variables used, their descriptions, and the units of measurement (where applicable).

en:
Resource Title: Fig_2_Data.csv
    Size: 3183 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.673/Fig_2_Data.csv
    Description: This dataset includes results from  variation partitioning analysis used to assess the relative contributions of environmental and spatial factors to taxonomic and functional β-diversity and their components across biogeographic regions. It contains site-level values for pure and shared effects of predictors. Used to generate Fig_2.

beta-diversity

display_name: beta-diversity

community-assembly

display_name: community-assembly

environmental-factors

display_name: environmental-factors

functional-diversity

display_name: functional-diversity

metacommunity

display_name: metacommunity

spatial-factors

display_name: spatial-factors

taxonomic-diversity

display_name: taxonomic-diversity

water-filled-tree-holes

display_name: water-filled-tree-holes


en: Countrywide vegetation height models (VHM) were generated for Armenia based on Copernicus Sentinel-2 imagery within the framework of the FORACCA project. “The Forest Restoration and Climate Change in Armenia” (FORACCA) project is funded by the Swiss Agency for Development and Cooperation (SDC). The project is implemented by the Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL) in collaboration with Zoï Environment Network as well as the Forest Alliance of Armenia. A Convolutional Neural Network (CNN) model was trained in Switzerland to estimate the maximum vegetation height at the spatial resolution of the Sentinel-2 pixel of 10 m. Vegetation heights from the spatially higher-resolved VHM Lidar NFI were used as reference data for the CNN training. Then, the model was spatially transferred and VHMs for Armenia were generated annually based on available Sentinel-2 imagery from May – September of the respective year. Further details on the dataset and model to create the Sentinel-2 VHMs can be found in the paper Jiang et al. (2023, https://doi.org/10.1016/j.srs.2023.100099). Contains modified Copernicus Sentinel data.

en: remote-sensing armenia vegetation-height foracca cnn forest sentinel-2

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: Sentinel-2 Vegetation Height Model Armenia

envi

en: Environment

en:
Resource Title: S2-VHM_2023_max.tif
    Size: 3189013217 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/692904ba-e575-4e69-8950-288ffe11a952/download/s2-vhm_2023_max.tif
    Description:

format: TIFF

media_type: image/tiff

en:
Resource Title: S2-VHM_2018_max.tif
    Size: 3167538381 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/cf0e2bc7-a73a-477a-86bc-6ed8e7cd8e8d/download/s2-vhm_2018_max.tif
    Description:

en:
Resource Title: S2-VHM_2021_max.tif
    Size: 2834678415 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/5b72d532-7a61-45a2-a09a-d83dfa61f9f2/download/s2-vhm_2021_max.tif
    Description:

en:
Resource Title: S2-VHM_2017_max.tif
    Size: 3178275799 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/511abee2-19eb-45e9-b28c-23a3f8cada46/download/s2-vhm_2017_max.tif
    Description:

en:
Resource Title: S2-VHM_2019_max.tif
    Size: 3178275799 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/7bde832d-dcba-4df3-b2ff-e01941712029/download/s2-vhm_2019_max.tif
    Description:

en:
Resource Title: S2-VHM_2022_max.tif
    Size: 3178275799 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/f0b468d3-1f4b-454d-93dc-d01a72902001/download/s2-vhm_2022_max.tif
    Description:

en:
Resource Title: S2-VHM_2025_max.tif
    Size: 3167538381 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/f1b1e699-6f6c-4bb0-89f6-89d8c455c5a2/download/s2-vhm_2025_max.tif
    Description:

en:
Resource Title: S2-VHM_2020_max.tif
    Size: 3178275799 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/1ccbef32-82b2-463e-a109-80f4f40037cd/download/s2-vhm_2020_max.tif
    Description:

en:
Resource Title: S2-VHM_2024_max.tif
    Size: 3189013217 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/98667a97-fe5d-4d46-a0a0-93a0e951c7e4/download/s2-vhm_2024_max.tif
    Description:

armenia

display_name: armenia

cnn

display_name: cnn

foracca

display_name: foracca

forest

display_name: forest

remote-sensing

display_name: remote-sensing

vegetation-height

display_name: vegetation-height


en:
This repository hosts the experimental data accompanying our publication "The influence of snow microstructure on the compressive mechanical properties of weak snowpack layers" feautured in Acta Materialia.
- Experimental Data and microstructural descriptors:
Full dataset used for the main analysis of the paper. Contains the measured mechanical properties, µCT parameters, further analysis, etc. The column "ID" (e.g. 363)  links this data with the 3D µCT dataset  (e.g. e0000363).
- 3D Data of the segmented µCT scans:
Full dataset containing the raw segmented µCT scans in the MetaIO format. They can be opened using the SimpleITK package (`pip install SimpleITK`).
Note: the Files can be idenfied by their scan number in the filename, (e.g, e0000363)
 `import SimpleITK as sitk `
 `img = sitk.ReadImage("e0000363_crop_seg.mhd") `
 `array = sitk.GetArrayFromImage(img) `  shape: [z, y, x]
`array_xyz = np.transpose(array, (2, 1, 0))`  (Optional) for array axes in [x, y, z]
 `spacing = img.GetSpacing() `                  voxel size (x,y,z)

en: snow-avalanche snow-microstructure snow snow-mechanics lab-experiment

en:
Resource Title: 3D_CT_files
    Size: 6442450944 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.648%2F
    Description: MetaIO_files

en:
Resource Title: Dataset_v1.csv
    Size: 64099 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e3ac64e4-3204-4edb-8b10-b458373d9e1f/resource/5b516f93-a87b-4315-9a02-325e2400ee81/download/dataset_v1.csv
    Description: Dataset containing both the experimental results and microstructural parameters.

lab-experiment

display_name: lab-experiment

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-mechanics

display_name: snow-mechanics

snow-microstructure

display_name: snow-microstructure


en:
This repository hosts the experimental data accompanying our publication, “On the compressive strength of weak snow layers of depth hoar,” featured in the Journal of Glaciology.
-Compressive Strength Data:
Measurements of the compressive strength for 92 artificially grown weak snow samples.
-Microstructural CT Data:
CT-derived microstructural information for each sample, including:
Density
Specific surface area
Connectivity density
Correlation lengths
Anisotropy
-Additional CT Data:
Parent Sample Variability: CT data used to assess the variability of the parent samples.
Temporal Evolution: CT data capturing the evolution within the artificial weak layers.
Reference Data: Information on the reference CT data sourced from the RHOSSA and MOSAiC campaigns.

en: snow slab-avalanche snow-mechanics microstructure depth-hoar strength

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:
Resource Title: ReferenceDataCT.csv
    Size: 8841 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f428c8e6-191b-45d4-8b92-239b5f056338/resource/e8f6bc95-aff3-437e-a5a2-b04cb020f330/download/ct_references.csv
    Description: CT Reference Data: Contains sample names, positions, evaluated regions and microstructural parameters based on data from the RHOSSA and MOSAiC campaigns.

MOSAiC:
https://mosaic-portal.org/data/open-mcs/vessel/polarstern/sn_microct/sn_microct/exdata/
https://doi.org/10.1594/PANGAEA.952794

RHOSSA:
https://doi.org/10.16904/envidat.151

en:
Resource Title: TimeSeriesData.csv
    Size: 4202 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f428c8e6-191b-45d4-8b92-239b5f056338/resource/f100da36-5f10-49ba-a38d-140aed84c664/download/timeseriesdata.csv
    Description: Time series data: Contains the CT data of upper slab, weak layer and lower slab used to evaluate the temporal evolution within the artificial samples.

en:
Resource Title: ParentSampleVariability.csv
    Size: 1406 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f428c8e6-191b-45d4-8b92-239b5f056338/resource/83b74fbf-3d28-4a2e-b856-92573f39977c/download/parent_sample_variability.csv
    Description: Parent sample variability: Contains the CT data used to estimate the parent sample variability.

en:
Resource Title: ExperimentalData.csv
    Size: 5928 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f428c8e6-191b-45d4-8b92-239b5f056338/resource/adb3a453-f03a-44cc-b74b-ff9cb12878ec/download/experimentaldata.csv
    Description: Experimental Data: Contains results of the compression experiments and microstructural parameters.

depth-hoar

display_name: depth-hoar

microstructure

display_name: microstructure

slab-avalanche

display_name: slab-avalanche

strength

display_name: strength


en:
The available datasets are snow depth maps with a spatial resolution of 0.5 m derived from images of the survey camera Vexcel Ultracam mounted on a piloted airplane. Image acquisition was carried out during the approximately peak of winter (time when the thickest snowpack is expected) in spring. The snow depth maps are calculated by the subtraction of a summer-DTM from the processed winter- DSM of the corresponding date. The summer-DTM used was derived from a point cloud of an airborne laser scanner from 2020.
Due to the occurrence of inaccuracies of the calculated snow depth values caused by the photogrammetric method, we applied different masks to significantly increase the reliability of the snow depth maps. We masked out settled areas, high-frequented streets and technical constructions, pixels with high vegetation (height - 0.5 m) , outliers and unrealistic snow depth values. In addition, we modified the snow depth values of snow-free pixels to 0.
The information on buildings and infrastructure comes from the exactly classified ALS point cloud and the TLM dataset from Swisstopo (https://www.swisstopo.admin.ch/de/geodata/landscape/tlm3d.htmllinks). High vegetation is also derived from the classification and the calculated object height from the point cloud.
Outliers and unrealistic snow depth values are defined as negative snow depth values and snow depths exceeding 10 m. The classification of each pixel of the corresponding orthophoto into snow-covered or snow-free is based on the application of a threshold of the NDSI or manually determined ratios of the RGB values.
An extensive accuracy assessment proves the high accuracy of the snow depth maps with a root mean square error of 0.25 m for the year 2017 and 0.15 m for the following snow depth maps.
The work is published in:

en: snow-depth-distribution snow-hydrology dischma photogrammetry avalanches davos

envidat

en: EnviDat: the Environmental Data Portal

en: Snow depth mapping by airplane photogrammetry (2017 -  ongoing)

envi

en: Environment

avalanches

display_name: avalanches

davos

display_name: davos

dischma

display_name: dischma

photogrammetry

display_name: photogrammetry

snow-depth-distribution

display_name: snow-depth-distribution

snow-hydrology

display_name: snow-hydrology


en: This research data is used to re includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions. This research data includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions.

en: habitat-heterogeneity hypervolume hengduan-mountains phytodiversity model-residuals

en: Phytodiversity is associated with habitat heterogeneity from Eurasia to Hengduan

en:
Resource Title: HDM heterogeneity scales
    Size: 210551963 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/092b3ec7-afab-4692-9547-1aacba54f89e/download/hdm_heterogeneity_scales.zip
    Description: The Heterogeneity matrics in the Hengduan mountain scale

en:
Resource Title: Hengduan plant family richness map
    Size: 159254007 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/fd56e712-502c-4c52-9ec4-fe7f0b461393/download/hengduan-plant-richness.zip
    Description: This is the family level plant richness map in the Hengduan mountain scale at 1km resoution

en:
Resource Title: Eurasia plant family richness map
    Size: 1149466779 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/8b94b856-31b3-42e3-bfb3-e77d7a54e209/download/eurasia_fam.zip
    Description: This is the plant family level richness map at the Eurasia scale calculated from https://www.nature.com/articles/s41597-021-00997-6

en:
Resource Title: Eurasia SR and heteorgeneity
    Size: 33861 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/f80b00d6-7381-4789-873c-c2bb4d2aa932/download/sr_eurasia_revision.csv
    Description: This table is used for the Eurasia scale analyses, including both family level species richness map and different heterogeneity predictors

en:
Resource Title: Plant range map at Hengduan scale
    Size: 635180593 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/95b657e6-4f16-4d44-aea1-6014d6560b54/download/three_models.7z
    Description: This is the plant range map at the Hengduan mountain scale based on species distribution model, elevation, and county level distribution information

habitat-heterogeneity

display_name: habitat-heterogeneity

hengduan-mountains

display_name: hengduan-mountains

hypervolume

display_name: hypervolume

model-residuals

display_name: model-residuals

phytodiversity

display_name: phytodiversity


en:
The TreeMig framework allows for an easy application of the forest landscape model TreeMig for simulating forest dynamics in space under changing environmental and land use conditions.
Here, case study examples in Switzerland are given that simulate the dynamics and spatial spread of competing tree species in a region in Switzerland, the invasion of a hypothetical invasive tree species, and the control of this species via a management model coupled to TreeMig.  The datasets consist of the installation- and GUI starting-script,  example environmental input data for Switzerland, the simulation environment, and further R-scripts for running the simulations and plotting the simulation results directly from R and for coupling TreeMig to the forest management model.

en: land-use forest-dynamics forest-management forest r-package species-migration climate-change bioclimatic-variables treemig spatial-modelling example-applications

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: Case study applications demonstrating the use and potential of the TreeMig framework v1

en:
Resource Title: readme_descriptioninputdata.pdf
    Size: 269312 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/3db8ca57-2838-4b26-82a9-9770b75b7096/download/readme_descriptioninputdata.pdf
    Description: Where the environmental and land use input data come from and how they were processed

en:
Resource Title: installAndRunTreeMigWrapperAndGUI_std.R
    Size: 553 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/916c8a50-1d57-4e28-97c8-f50b8a9f7bf7/download/installandruntreemigwrapperandgui_std.r
    Description: R-script to install the TreeMig framework and start the graphical user interface

en:
Resource Title: ExampleApplicationsTreeMig.zip
    Size: 1686005000 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/0f59997f-3e90-4b25-9e5b-37b641d9769b/download/exampleapplicationstreemig.zip
    Description: 1) Simulation environment TMEnvironmentExampleApplications for the simulation of the case study applications. It contains a) simulation settings (folder C),  b) species parameters (folder P), c) folders S, R and P for the state files and results and plots to be produced, and the binaries of the TreeMig model.
2) Input data for Switzerland in TMInputData (Climate, soil, land cover, DEM)
3) Several R scripts (folder Scripts) to run and plot the simulations directly from R without having to use the graphical user interface.
For learning how to use TreeMig we recommend the starter kit https://www.doi.org/10.16904/envidat.533.

en:
Resource Title: InstructionsForRunningTheSimulations.pdf
    Size: 127302 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/32c74611-c61e-48be-998b-6722bbb697c8/download/instructionsforrunningthesimulations.pdf
    Description: A condensed instruction for running the presented simulations.

en:
Resource Title: InstructionsForRunningTheSimulations.pdf
    Size: 68995 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/830a45db-7985-42f6-8864-4961fe5ef5a2/download/instructionsforrunningthesimulations.pdf
    Description: A condensed instruction for running the presented simulations.

en:
Resource Title: ExampleApplicationsTreeMig.zip
    Size: 1676301558 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/609e85c8-98d0-4043-be91-48bd32c162ea/download/exampleapplicationstreemig.zip
    Description: 1) Simulation environment TMEnvironmentExampleApplications for the simulation of the case study applications. It contains a) simulation settings (folder C),  b) species parameters (folder P), c) folders S, R and P for the state files and results and plots to be produced, and the binaries of the TreeMig model.
2) Input data for Switzerland in TMInputData (Climate, soil, land cover, DEM)
3) Several R scripts (folder Scripts) to run and plot the simulations directly from R without having to use the graphical user interface.
For learning how to use TreeMig we recommend the starter kit https://www.doi.org/10.16904/envidat.533.

bioclimatic-variables

display_name: bioclimatic-variables

climate-change

display_name: climate-change

example-applications

display_name: example-applications

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-management

display_name: forest-management

land-use

display_name: land-use

r-package

display_name: r-package

spatial-modelling

display_name: spatial-modelling

species-migration

display_name: species-migration

treemig

display_name: treemig


en:
The cold habitats of the Swiss Alps and the Arctic are undergoing change and are at risk of disappearing completely or partially in the future. Along with them, a poorly known diversity of microorganisms that have adapted to life in these supposedly hostile places. By cryopreserving microorganisms from these habitats, some of today's biodiversity can be preserved in biobanks.
The collection contains cryopreserved bacteria and fungi isolated from permafrost and active layer of Muot da Barba Peider and Val Lavirun, from the glacier forefield and glacier toe of the Damma glacier, from active layer in northern Greenland and from plastic waste in Svalbard, as well as isolates from plastic incubations in Muot da Barba Peider, northern Greenland and arctic Russian soils.
Project overview: https://www.wsl.ch/en/projects/life-at-chilly-temperatures-a-collection-of-microorganisms-from-extreme-habitats/

en: swiss-alps conservation plastisphere arctic bacteria biobank extreme-habitat fungi biodiversity collections active-layer glaciers permafrost

envidat

en: EnviDat: the Environmental Data Portal

en: Life at chilly temperatures - A collection of microorganisms from extreme habitats

envi

en: Environment

active-layer

display_name: active-layer

arctic

display_name: arctic

bacteria

display_name: bacteria

biobank

display_name: biobank

biodiversity

display_name: biodiversity

collections

display_name: collections

conservation

display_name: conservation

extreme-habitat

display_name: extreme-habitat

fungi

display_name: fungi

glaciers

display_name: glaciers

permafrost

display_name: permafrost

plastisphere

display_name: plastisphere

swiss-alps

display_name: swiss-alps


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

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

en: Gao_Drought resistance and resilience of rhizosphere communities_13C-PLFA

biogeochemical-cycling

display_name: biogeochemical-cycling

drought

display_name: drought

forest

display_name: forest

microbial-biomass

display_name: microbial-biomass

plfa

display_name: plfa


en:
DESCRIPTION
The dataset is used to run snowpack simulations with various forcing data at different resolutions with the Flexible Snow Model (FSM2oshd). A dynamical downscaling model (HICAR) and a semi-statistical downscaling approach (COSD) are used to downscale COSMO data to resolutions of 250 m, 100 m and 50 m. Simulations are run with the operational snow cover model and a model extension including wind- and gravity-induced snow redistribution (FSM2trans).
 Input Data
This paragraph describes the input data used to run simulations with FSM2trans
 HICAR
The HICAR input data is created by the High-resolution Intermediate Complexity Atmospheric Research model. The input data is available for different resolutions (250m, 100m and 50m) for a domain covering complex terrain in the Swiss Alps (Dischma)
 COSD
The COSD data was statistically downscaled within the OSHD framework to different resolutions (250m, 100m, 50m) for a domain covering complex terrain in the Swiss Alps (Dischma)
 Simulation files
For the Simulations, a landuse file and a namelist file with the parametrizations need to be supplied to the model
 simulation output
This simulation output that is used for the analysis of the study is provided.

en: fsm2trans dischma hicar fsm2 snow-hydrology snowpack

en: FSM2trans snowpack simulations with HICAR input

en:
Resource Title: 2017.07_HICAR_250.zip
    Size: 349289674 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/520f9b5e-953b-4ac2-b14d-774b3802e6ca/download/2017.07_hicar_250.zip
    Description: Input data July 2017 HICAR 250m resolution

en:
Resource Title: 2016.11_COSD.zip
    Size: 264224065 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/b4507205-372a-42fb-a9c1-e8d92552d040/download/2016.11_cosd.zip
    Description: input data november 2016 COSD

en:
Resource Title: 2017.03_HICAR_50.zip
    Size: 1238243000 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/71eb5579-653e-44d0-a76e-102ae9616b3e/download/2017.03_hicar_50.zip
    Description: Input data March 2017 HICAR 50m resolution

en:
Resource Title: 2016.12_COSD.zip
    Size: 266020075 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/3a541855-fcd5-4308-904e-279f26c08079/download/2016.12_cosd.zip
    Description: input data january 2016 COSD

en:
Resource Title: 2017.01_HCIAR_50.zip
    Size: 1204154523 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/ccdeef06-535f-4735-a626-8d641701e305/download/2017.01_hciar_50.zip
    Description: Input data January 2017 HICAR 50m resolution

en:
Resource Title: output_validation_LiDAR.zip
    Size: 3626428 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/a24da30f-627b-413c-9ed9-aad3acaef5e2/download/output_validation_lidar.zip
    Description: snowheight output of validation days (LiDAR days) for all simulation runs
- 20.03.2027
- 31.03.2017
- 17.05.2017

en:
Resource Title: 2016.10_HICAR_250.zip
    Size: 342373326 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/b9b3253d-0e25-4051-b9c3-3156a532850b/download/2016.10_hicar_250.zip
    Description: Input data October 2016 HICAR 250m resolution

en:
Resource Title: 2017.03_HICAR_100.zip
    Size: 571345359 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/0cbd4ca1-2bb7-4e95-a68f-aa1cab01552c/download/2017.03_hicar_100.zip
    Description: Input data March 2017 HICAR 100m resolution

en:
Resource Title: 2016.11_HICAR_100.zip
    Size: 549614230 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/668af1cb-d429-4163-82ed-175818ba5870/download/2016.11_hicar_100.zip
    Description: Input data november 2016 HICAR 100m resolution

en:
Resource Title: 2017.05_HICAR_250.zip
    Size: 352928870 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/f6a4bef4-46e0-479c-a0d5-641881a0f6f7/download/2017.05_hicar_250.zip
    Description: Input data May 2017 HICAR 250m resolution

en:
Resource Title: 2017.03_HICAR_250.zip
    Size: 340805883 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/0b313459-557e-4e48-aaa5-3f3ecea99ef1/download/2017.03_hicar_250.zip
    Description: Input data March 2017 HICAR 250m resolution

en:
Resource Title: 2017.01_HICAR_100.zip
    Size: 556488789 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/44b7b48e-3424-4725-9d46-ae5b80d06357/download/2017.01_hicar_100.zip
    Description: Input data January 2017 HICAR 100m resolution

en:
Resource Title: 2017.01_COSD.zip
    Size: 272140667 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/b9490aeb-da86-494f-877c-9eb6be651d8c/download/2017.01_cosd.zip
    Description: Input data January 2017 COSD

en:
Resource Title: 2017.04_HICAR_50.zip
    Size: 2446451988 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/f3b1699c-2b57-4461-9a06-f9d2d2b6f68e/download/2017.04_hicar_50.zip
    Description: Input data April 2017 HICAR 50m resolution

en:
Resource Title: output_time_series.zip
    Size: 81853 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/2ac4c04e-5ea3-452e-9805-6acda2dc3ea4/download/output_time_series.zip
    Description: time series of daily averages of the whole domain for each simulation run
- rainfall
- snowfall
- runoff
- snowmelt
- temperature

en:
Resource Title: 2017.05_COSD.zip
    Size: 301461076 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/fc51e6dc-0217-4260-acdd-4774487412d4/download/2017.05_cosd.zip
    Description: Input data May 2017 COSD

en:
Resource Title: 2017.04_HICAR_100.zip
    Size: 565969532 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/b9ec85e4-e78a-4c97-9fd6-1a2dede5e261/download/2017.04_hicar_100.zip
    Description: Input data April 2017 HICAR 100m resolution

en:
Resource Title: 2017.02_HICAR_50.zip
    Size: 1097463760 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/35a80379-3a54-4792-aa57-30d77f5cab02/download/2017.02_hicar_50.zip
    Description: Input data February 2017 HICAR 50m resolution

en:
Resource Title: 2017.07_HICAR_50.zip
    Size: 1277440392 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/34e952ac-5973-4da0-997f-ab88dfcbd564/download/2017.07_hicar_50.zip
    Description: Input data July 2017 HICAR 50m resolution

en:
Resource Title: 2017.06_HICAR_100.zip
    Size: 573560621 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/78ed5fc9-112a-48dd-996a-f84b26b3263c/download/2017.06_hicar_100.zip
    Description: Input data June 2017 HICAR 100m resolution

en:
Resource Title: 2017.06_COSD.zip
    Size: 294775835 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/14c5c921-6d52-409b-a542-04e46024f319/download/2017.06_cosd.zip
    Description: Input data June 2017 COSD

en:
Resource Title: FSM_sntrans.zip
    Size: 117802989 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/4a6c39e8-ef52-439e-9f68-ac4f17423188/download/fsm_sntrans.zip
    Description: Available input files for running with FSM2trans

en:
Resource Title: 2017.02_HICAR_100.zip
    Size: 507866833 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/177e8244-a298-498e-b2c2-613a34e43768/download/2017.02_hicar_100.zip
    Description: Input data February 2017 HICAR 100m resolution

en:
Resource Title: 2017.06_HICAR_250.zip
    Size: 340448153 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/a0d70e21-c08f-4bf8-9043-8c061a63473c/download/2017.06_hicar_250.zip
    Description: Input data June 2017 HICAR 250m resolution

en:
Resource Title: 2017.07_COSD.zip
    Size: 301251879 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/8a792b31-ff97-439d-8eb3-2515cf2499c6/download/2017.07_cosd.zip
    Description: Input data July 2017 COSD

en:
Resource Title: 2017.02_HICAR_250.zip
    Size: 303548366 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/ec1636b8-1bce-4cff-b1f1-a38069ac89c1/download/2017.02_hicar_250.zip
    Description: Input data February 2017 HICAR 250m resolution

en:
Resource Title: 2016.12_HICAR_250.zip
    Size: 314433953 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/5f573752-59a4-42d6-952b-2c01b9cf1d06/download/2016.12_hicar_250.zip
    Description: Input data December 2016 HICAR 250m resolution

en:
Resource Title: 2016.11_HICAR_50.zip
    Size: 1186232457 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/5581cabf-14c4-464b-9c4f-b4067d14f051/download/2016.11_hicar_50.zip
    Description: Input data November 2016 HICAR 50m resolution

en:
Resource Title: 2017.05_HICAR_50.zip
    Size: 2561728437 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/d0e98236-f5fc-495d-a6e2-2ed08fd62f2f/download/2017.05_hicar_50.zip
    Description: Input data May 2017 HICAR 50m resolution

en:
Resource Title: FSM.zip
    Size: 33570817 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/969d40cd-9460-4500-8a49-3ec7d0e13b70/download/fsm.zip
    Description: Available input files for running with FSM2

en:
Resource Title: 2017.07_HICAR_100.zip
    Size: 588530697 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/38eb4592-9dc7-4128-8b10-5c7bab86e461/download/2017.07_hicar_100.zip
    Description: Input data July 2017 HICAR 100m resolution

en:
Resource Title: 2016.11_HICAR_250.zip
    Size: 326225322 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/87223396-acb5-4f85-8969-e9c1e37be822/download/2016.11_hicar_250.zip
    Description: Input data November 2016 HICAR 250m resolution

en:
Resource Title: 2016.12_HICAR_100.zip
    Size: 529826318 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/99285212-c956-46c7-b286-2138e9e0a0b3/download/2016.12_hicar_100.zip
    Description: Input data December 2016 HICAR 100m resolution

en:
Resource Title: 2017.06_HICAR_50.zip
    Size: 1248134155 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/06001feb-2337-46e6-884d-8d1f6b27472e/download/2017.06_hicar_50.zip
    Description: Input data June 2017 HICAR 50m resolution

en:
Resource Title: 2017.05_HICAR_100.zip
    Size: 590876781 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/c80ce909-8175-4c97-83b9-d26b26965151/download/2017.05_hicar_100.zip
    Description: Input data May 2017 HICAR 100m resolution

en:
Resource Title: 2016.10_HICAR_100.zip
    Size: 577152229 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/d1950e5f-834f-43af-8b77-faa0645830cb/download/2016.10_hicar_100.zip
    Description: Input data october 2016 HICAR 100m resolution

en:
Resource Title: 2016.10_HICAR_50.zip
    Size: 1249412855 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/de489e7c-ea5e-425a-9028-df8f4eaa43c6/download/2016.10_hicar_50.zip
    Description: Input data october 2016 HICAR 50m resolution

en:
Resource Title: 2016.12_HICAR_50.zip
    Size: 1146348392 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/085643a0-d8a9-4051-9b40-dc31f36b90a5/download/2016.12_hicar_50.zip
    Description: Input data December 2016 HICAR 50m resolution

en:
Resource Title: 2016.10_COSD.zip
    Size: 278982217 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/f8e29340-2c65-40c8-97c0-d72389c3f6e7/download/2016.10_cosd.zip
    Description: input data october 2016 COSD

en:
Resource Title: 2017.04_COSD.zip
    Size: 288051313 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/4aae6922-c820-4e83-9387-c1d810896431/download/2017.04_cosd.zip
    Description: Input data April 2017 COSD

en:
Resource Title: 2017.03_COSD.zip
    Size: 288438593 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/f71d4daa-b6ac-40e8-aff0-2bffd45ce846/download/2017.03_cosd.zip
    Description: Input data March 2017 COSD

en:
Resource Title: 2017.04_HICAR_250.zip
    Size: 338504059 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/8b697f7e-d86b-42ec-b514-b1cf61afae87/download/2017.04_hicar_250.zip
    Description: Input data April 2017 HICAR 250m resolution

en:
Resource Title: 2017.01_HICAR_250.zip
    Size: 331441414 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/190d102a-93f1-4a8e-9373-3442681efe51/download/2017.01_hicar_250.zip
    Description: Input data January 2017 HICAR 250m resolution

en:
Resource Title: 2017.02_COSD.zip
    Size: 251637401 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/2b9d9c27-0e23-47c5-8e88-bc6406fcb01f/download/2017.02_cosd.zip
    Description: Input data February 2017 COSD


distributed-acoustic-sensing-brienz

en:
This dataset contains the Distributed Acoustic Sensing (DAS), radar detection data used for training and result analysis in the GRL paper titled `Automatic Monitoring of Rock-Slope Failures Using Distributed Acoustic Sensing and Semi-Supervised Learning`.
The DAS dataset (both waveform and cross-spectral density matrices), extracted features, labeled dataset, two trained models (feature extraction model and xgboost classification model), scripts to reproduce the whole training and classification processes, and a notebook to replicate the result analysis part are provided under the MIT license. To provide a reasonable data size, we chunked the raw data to a few hundred channels which we used in our project.
Abstract:
Effective use of the wealth of information provided by Distributed Acoustic Sensing (DAS) for mass movement monitoring remains a challenge. We propose a semi-supervised neural network tailored to screen DAS data related to a series of rock collapses leading to a major failure of approximately 1.2 million cubic meters on 15 June 2023 in Brienz, Eastern Switzerland. Besides DAS, the dataset from 16 May to 30 June 2023 includes Doppler radar data for partially ground-truth labeling. The proposed algorithm is capable of distinguishing between rock-slope failures and background noise, including road and train traffic, with a detection precision of over 95%. It identifies hundreds of precursory failures and shows sustained detection hours before and during the major collapse. Event size and signal-to-noise ratio (SNR) are the key performance dependencies. As a critical part of our algorithm operates unsupervised, we suggest that it is suitable for general monitoring of natural hazards.

en: seismic natural-hazard rockfall machine-learning landslide early-warning

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: Distributed Acoustic Sensing Brienz

title_for_slug: distributed-acoustic-sensing-brienz

envi

en: Environment

early-warning

display_name: early-warning

landslide

display_name: landslide

machine-learning

display_name: machine-learning

natural-hazard

display_name: natural-hazard

rockfall

display_name: rockfall

seismic

display_name: seismic


bats-in-beaver-systems

en:
This dataset contains processed bat acoustic data collected to evaluate the ecological impacts of beaver-engineered ponds on bat species richness, activity, and feeding activity. It includes nightly activity and feeding call counts identified to species or species group level, site and treatment information (beaver pond vs. control areas along the same stream), and associated environmental covariates such as deadwood volume, arthropod abundance, and vegetation structure.
Methods: Bats were recorded using passive acoustic detectors placed at paired beaver-influenced and control sites. The resulting data was processed in the software Batscope. Arthropod abundance was estimated using flight-interception traps. The amount of deadwood and vegetation cover was measured in the field. Canopy cover and canopy heterogeneity were modelled from GIS models.
Temporal and Spatial Coverage:
Data were collected from eight sites in Switzerland between June and July 2022, each site sampled for 16 nights.

en: castor nature-conservation chiroptera habitat-heterogeneity wetland deadwood ecosystem-engineer flying-arthropods beaver

en: Bats in beaver systems

title_for_slug: bats-in-beaver-systems

en:
Resource Title: arthropods_flying.csv
    Size: 1822 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/22214e46-c662-4398-91da-197fa844c656/download/arthropods_flying.csv
    Description: arthropods_flying the arthropod abundance with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"community" (species group),
"month" (sampling month),
"abundance" (number of flying arthropods)

en:
Resource Title: bats_raw_values_overview.R
    Size: 8975 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/f7d9750d-6dcd-4fa9-856e-c810d08c9708/download/bats_raw_values_overview.r
    Description: bats_raw_values_overview to produce raw value summaries and tables

format: OCTET

en:
Resource Title: bats_glmm.R
    Size: 44503 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/ba5c25fd-9c4b-480f-8f89-29449bbddfd7/download/bats_glmm.r
    Description: R script bats_glmm to test the influence of beavers on bat richness, activity and feeding activity

en:
Resource Title: bats_biodiv.day.guilds.csv
    Size: 53549 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/78d66f28-1f5a-43f9-8cfe-e5edf12055d8/download/bats_biodiv.day.guilds.csv
    Description: bats_biodiv.day.guilds with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"community" (species group),
"date" (sampling date),
"month" (sampling month),
"guild" (which feeding guild information),
"feeding" (number of feeding buzzes summed per 5 minutes and identification level), "abundance" (sequences per 5 minutes and identification level),
"richness" (species richness),
"richness_feeding" (species richness of feeding bats)

en:
Resource Title: data_bats.xlsx
    Size: 7453297 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/bab1affd-1f46-41bd-b405-364af91da886/download/data_bats.xlsx
    Description: Raw data data_bats with columns:
“Categories” (empty or "feeding", indicating that call sequence contains feeding buzz)
“Sequence” (sequence number)
“Timestamp” (recording time)
“Temperature” (temperature recorded by batlogger in degree celcius)
“Serial” (serial number of bat logger)
“Duration” (duration of call sequence in seconds)
“Call.Count” (call count number, how many calls could be detected)
“Verification.1” (bat sequence verification)
“Notes” (remarks for identification)
“treatment” (treatment ctrl = Control and Pool)
“slot” (slot number, 4 slots, two in June, two in July)
“Laufnummer” (unique identifier per sampling point)

en:
Resource Title: bats_SEM.R
    Size: 69411 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/d682ac4b-8266-4fc8-ad06-0cbc03709b47/download/bats_sem.r
    Description: R script bats_SEM to test the influence of the beaver on bat richness, activity and feeding activity through feeding and habitat heterogeneity

en:
Resource Title: bats_pool_size.R
    Size: 7169 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/664b4516-22a3-4509-bec6-ccbd57f4ee8c/download/bats_pool_size.r
    Description: R script bats_pool_size to test the beaver pool size on bat richness, activity and feeding activity

en:
Resource Title: README.txt
    Size: 6009 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/03d87d3e-c9f0-4e53-b1fc-531dd2087e8f/download/readme.txt
    Description: README text file providing context for the data. Please do not hesitate to contact us if you have any questions

en:
Resource Title: gewichtungsfaktor.csv
    Size: 9392 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/b3f59232-46fa-4068-ad06-15947d042c16/download/gewichtungsfaktor.csv
    Description: gewichtungsfaktor with columns
"Project" (sampling site),
"Treatment" (sampling location within site, with levels ctrl for Control and pool for Pool),
"date" (sampling date),
"gew" (weighting factor to standardize night length)

en:
Resource Title: bats_biodiv.day.csv
    Size: 16681 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/56b11b90-7932-434b-a089-f3ff14b3f7d7/download/bats_biodiv.day.csv
    Description: bats_biodiv.day with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"community" (species group),
"date" (sampling date),
"month" (sampling month),
"feeding" (number of feeding buzzes summed per 5 minutes and identification level), "abundance" (sequences per 5 minutes and identification level),
"richness" (species richness),
"richness_feeding" (species richness of feeding bats)

en:
Resource Title: bats_age.R
    Size: 6554 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/0e7ad52e-0545-4eec-98bc-ee80e4d27a90/download/bats_age.r
    Description: R script bats_age to test the beaver pool age effect on bat richness, activity and feeding activity

en:
Resource Title: dead_wood.csv
    Size: 40298 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/3985310a-835b-4fdf-a66e-5ec0a92ab490/download/dead_wood.csv
    Description: dead_wood for deadwood with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"type" (deadwood type),
"height_length" (the height or lenghth of a piece of deadwood in m),
"DBH_diamlarge" (diameter at breast height or diameter of larger end if lying in m),
"diamsmall (diameter of smaller end if lying in m",
"volume" (calculated volume in m3)

en:
Resource Title: bats.environment.xlsx
    Size: 10844 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/ad5c3240-15c9-4330-9677-9786ef447662/download/bats.environment.xlsx
    Description: bats.environment with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"canopy" (modelled tree canopy cover, averaged across radius of 100 m, unitless),
"structure_ruggedness" (mean ruggedness of the total vertical structure > 3 m, averaged across radius of 100 m, unitless), "vegetation_ruggedness" (mean ruggedness of the canopy > 3 m, later called canopy_heterogenneity, averaged across radius of 100 m, unitless),
"pool_size" (maximum width of beaver pool in m),
"area_deadwood_monitoring" (total area of deadwood moonitoring in m3),
"age" (beaver presence in years)

en:
Resource Title: bat_guilds.CSV
    Size: 2607 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/9dbe3429-5669-4b2c-a83c-a643411b06b5/download/bat_guilds.csv
    Description: bat_guilds with columns
"SP" (identification level),
"EndGuilde" (information on feeding guild)

en:
Resource Title: bats_data_exploration_Figure_nighly.R
    Size: 65739 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/d59bb90b-29b3-4908-a692-17fdd8e79486/download/bats_data_exploration_figure_nighly.r
    Description: R script bats_data_exploration_Figure_nighly to explore the data and display nightly species richness, activity and feeding activity

en:
Resource Title: sampling dates.xlsx
    Size: 10360 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/6f9bce17-7b4b-4176-a3b8-8a32a0475b60/download/sampling-dates.xlsx
    Description: For the time information about the research data, created (2022-09-23 to 2022-09-23) refers to the GIS data, collected (2022-06-13 to 2022-07-31) to the field sampling. Details can be found in the csv “sampling_dates”.

sampling_dates with columns
"site" (sampling site),
"bats_1" (first period of bat survey in June),
"bats_2" (second period of bat survey in June),
"bats_3" (first period of bat survey in July),
"bats_4" (second period of bat survey in July),
"flying_arthropods_1" (arthropod sampling in June),
"flying_arthropods_2" (arthropod sampling in July),
"deadwood survey" (date of deadwood survey),
"vegetation survey" (date of vegetation survey)

en:
Resource Title: site_info.csv
    Size: 4452 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/0a4317c7-3251-4c37-8519-26f542ed56a5/download/site_info.csv
    Description: site_info contains columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"location" (sampling location row within site),
"sample_nr" (sampling number within location)

en:
Resource Title: bats_data_cleaning.R
    Size: 28317 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/9c5e13fb-5c1a-4990-af1d-576832120846/download/bats_data_cleaning.r
    Description: R script bats_data_cleaning to clean the raw data

en:
Resource Title: vegetation_characteristics.csv
    Size: 2769 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/f60cdb2f-d4bc-454a-9fed-058c86234b5e/download/vegetation_characteristics.csv
    Description: vegetation_characteristics data on vegetation_cover and cumulative_cover with columns "laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"Vegetation_cover" (estimated vegetation cover over 5x1 m plot in %),
"Cumulative cover" (summed up cover over tree, shrub and herb layer in %),
"Cumulative cover trees" (tree cover level, higher than 3 metres in %),

beaver

display_name: beaver

castor

display_name: castor

chiroptera

display_name: chiroptera

deadwood

display_name: deadwood

ecosystem-engineer

display_name: ecosystem-engineer

flying-arthropods

display_name: flying-arthropods

habitat-heterogeneity

display_name: habitat-heterogeneity

nature-conservation

display_name: nature-conservation

wetland

display_name: wetland


en:
This dataset contains the fire events, drivers and auxillery datasets analyzed in the study "Compounding preconditions of wildfires vary in time and space within Europe" of Miller et al. (2025) (DOI: 10.1038/s43247-025-02955-1).
A Jupyter-Notebook explaining the fire event datasets and code to reproduce the figures of Miller et al. (2025) are available on gitlab (see https://gitlab.com/jumi26/wildfire-drivers-in-europe).

en: event-analysis driver mountains forest-fire observations europe

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: Wildfire events and drivers across Europe

envi

en: Environment

driver

display_name: driver

europe

display_name: europe

event-analysis

display_name: event-analysis

forest-fire

display_name: forest-fire

mountains

display_name: mountains

observations

display_name: observations


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

en: atmospheric-conditions wind radiation temperature-profiles precipitation

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

en:
Resource Title: DATA ACCESS
    Size: 2684354560 bytes
    Format: application/x-smet
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.43/dps/STB2_L3.smet
    Description: This data access is outdated and has been replaced with an updated version (see description).

en:
Resource Title: Site photo 1
    Size: 2643479 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/938e0cc0-0f75-41da-a358-679f27c254d4/resource/17df9e78-39eb-453e-a69d-3b71de67ff48/download/046.jpg
    Description: This site photo is outdated and has been replaced with an updated version (see description).

format: jpeg

en:
Resource Title: README
    Size: 1383 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/938e0cc0-0f75-41da-a358-679f27c254d4/resource/0fa6c765-9e81-49b3-9c11-83a0043bf653/download/metadatastillberg.txt
    Description: This description is outdated and has been replaced with an updated version (see description).

en:
Resource Title: STB2 CSV
    Size: 65410290 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/938e0cc0-0f75-41da-a358-679f27c254d4/resource/2e3b9d07-fb9e-4668-a2d0-0d3f07c7128c/download/stb2.csv
    Description: This dataset is outdated and has been replaced with an updated version (see description).

en:
Resource Title: Site photo 3
    Size: 3044052 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/938e0cc0-0f75-41da-a358-679f27c254d4/resource/74d417de-a852-41d6-a6dc-194b0d144bee/download/050.jpg
    Description: This site photo is outdated and has been replaced with an updated version (see description).

en:
Resource Title: Latest data from Stillberg climate station
    Size: 1 bytes
    Format: No Info
    URL: https://doi.org/10.16904/envidat.396
    Description: This dataset is outdated and has been replaced with an updated version (see description).

en:
Resource Title: Site photo 2
    Size: 3453733 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/938e0cc0-0f75-41da-a358-679f27c254d4/resource/93f3b3d4-955d-4cd8-a7ad-0fdea9f5a937/download/048.jpg
    Description: This site photo is outdated and has been replaced with an updated version (see description).

en:
Resource Title: Overview plot
    Size: 440583 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/938e0cc0-0f75-41da-a358-679f27c254d4/resource/81d220e5-4cc5-4ac8-8e9d-f5eb149fbfa5/download/stillbergclimate.png
    Description: This overview plot is outdated and has been replaced with an updated version (see description).

format: PNG

media_type: image/png

atmospheric-conditions

display_name: atmospheric-conditions

precipitation

display_name: precipitation

radiation

display_name: radiation

temperature-profiles

display_name: temperature-profiles

wind

display_name: wind