en:
This dataset contains three case studies where are compared the latent heat flux calculated using the Eddy Covariance (EC) method, the Monin-Obukhov Similarity Theory (MOST) and the modified Bowen-ratio method presented in the research paper "Using the sensible heat flux eddy covariance based exchange coefficient to calculate latent heat from moisture mean gradients overn snow". We include the datasets, the code and the ini files for reproduce the research.
The dataset contain two files in zip format:
  1. Sowftware-Heat_fluxes_on_snow: Jupyter notebooks to reproduce the method and the figures of the paper.
  2. data.zip: Datasets used to compare the methods

en: meta swiss-alps snow central-asia meteo-station meteo

en: Latent Heat Flux over Snow

envi

en: Environment

de:
Resource Title:
    Size: 29787181 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/fc60c402-dc96-40a0-b780-09404deaa34e/resource/7ab59fe6-dc0b-4dfc-b5c1-e8c3287cb54e/download/data.zip
    Description: This file includes the datasets used to compare the methods. It includes:
- EC Postprocessed heat flux data from sonic anemometer and gas analyzer. Files named: [SITE]_(NO)WatVap_eddypro_OUT_[type].csv
- MOST Postprocessed data from SNOWPACK model. Files named [SITE]_[year]_[METHOD].smet
- Configuration files for SNOWPACK (.ini files) and Eddypro (.eddypro files)

[SITE] correspond to DISHMA/DISH or Alpine Valley, PLATEAU/PLAT for Antarctic Plateau, TAJ for Pamir mountains (no EC)
[type] correspond to fluxnet, full_output or qc_details
[METHOD] indicates the stability model used and/or the roughness length

de:
Resource Title: Sowftware-Heat_fluxes_on_snow
    Size: 3322132 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/fc60c402-dc96-40a0-b780-09404deaa34e/resource/da84224e-d225-43fd-8986-7d8069362adc/download/software.zip
    Description: This file includes the Jupyter notebooks to reproduce the method and the figures of the paper. This consists in:
- 3 files for Alpine Valley
- 3 files for Antarctic Plateau
- 1 file for application at Pamir mountains

central-asia

display_name: central-asia

meta

display_name: meta

meteo

display_name: meteo

meteo-station

display_name: meteo-station

swiss-alps

display_name: swiss-alps


$oid: OBSOLETE

en:
We processed Sentinel-2 images from 2017 to 2023 for Switzerland with the Software FORCE (Frantz 2019). The respective parameter files can be found here: [Github](https://github.com/TLKoch/Sentinel-2_CH). All the images consist of several TB and therefore, access will be granted upon request.
The available bands (in spatial reference system EPSG 3035) are the following:
*Red, Green, Blue, NIR, Red-Edge-1, Red-Edge-2, Red-Edge-3, SWIR-1, SWIR-2*
The available indices (in spatial reference system EPSG 3035) are the following:
*CCI, CIRE, NDWI/NDMI, NDVI, EVI*
Further indices might be provided upon request.
 Processing
After downloading Level 1 data for the 14 Sentinel-2 tiles covering Switzerland (T31TGN, T32TLT, T32TMT, T32UMU, T32TNT, T32TPT, T31TGM, T32TLS, T32TMS, T32TNS, T32TPS, T32TLR, T32TMR, T32TNR) with an estimated cloud cover of less than 80 \%, we processed the data further with FORCE v. 3.7.8-12.
FORCE was used for radiometric correction, including atmospheric and topographic corrections using the digital elevation model from Copernicus Land Monitoring Service (EU-DEM v. 1.1), with a 25 m spatial resolution, a bidirectional reflectance distribution function (BRDF) correction, and an adjacency effect correction. For cloud masking, the improved Fmask algorithm with buffers of 300 m for clouds, 90 m for shadows, and 30 m for snow were used (Frantz et al. 2018; Zhu et al. 2015). All bands were resampled using cubic convolution to 10 m spatial resolution. Shadows, low and poor illumination as well as saturation were masked out. The co-registration of all images  was made with monthly composites of near-infrared Landsat Collection 2 images from 2014 to 2021 (Rengarajan et al. 2020;Rufin et al. 2021). With this the geometric consistency improved. The processed images are available in tiles of 30 by 30 km.
 Example images
Uploaded is an example of the index EVI for one of the generated 30 by 30 km tiles located around the city of Zürich. The values are multiplied by 10.000. The date of the image is 24.07.2018.

en: remote-sensing raster-processing switzerland force sentinel-2

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

en: Sentinel-2 imagery of Switzerland

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

fr: Environnement

it: Ambiente

de:
Resource Title: parameter_file_force_sentinel_level2.prm
    Size: 17892 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/eb913ad8-aec4-472f-a827-179b4ec87371/resource/69490cdd-817f-49f6-b048-e152ba6bff5a/download/sentinel_level2.prm
    Description: Parameter file that defined all the parameters for processing the Sentinel-2 Level 2 imagery

format: OCTET

de:
Resource Title: EVI_20180724_example.tif
    Size: 24317492 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/eb913ad8-aec4-472f-a827-179b4ec87371/resource/5d61e0ec-f785-45ba-8281-8668855ee94b/download/evi_20180724_example.tif
    Description: An example of the index EVI for one of the generated 30 by 30 km tiles located around the city of Zürich. The values are multiplied by 10.000. The date of the image is 24.07.2018.

format: TIFF

media_type: image/tiff

force

display_name: force

raster-processing

display_name: raster-processing

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland


en:
We processed Sentinel-2 image time series from 2017 to 2023 for Switzerland with the Software FORCE (Frantz 2019) on the basis of [Sentinel-2 images](https://envidat.ch//metadata/sentinel-2-imagery-of-switzerland). The respective parameter files can be found here: [Github](https://github.com/TLKoch/Sentinel-2_CH). All the image time series consist of several TB and therefore access will be granted upon request.
The available bands (in spatial reference system EPSG 3035) are the following:
Red, Green, Blue, NIR, Red-Edge-1, Red-Edge-2, Red-Edge-3, SWIR-1, SWIR-2
The available indices (in spatial reference system EPSG 3035) are the following:
CCI, CIRE, NDWI/NDMI, NDVI, EVI
 Processing
On the basis of processed Sentinel-2 images for the 14 Sentinel-2 tiles covering Switzerland (T31TGN, T32TLT, T32TMT, T32UMU, T32TNT, T32TPT, T31TGM, T32TLS, T32TMS, T32TNS, T32TPS, T32TLR, T32TMR, T32TNR), we processed the image time series further with FORCE v. 3.7.8-12.
We generated interpolated Sentinel-2 time series with a 5-day interval, corresponding to the theoretical revisit time of the Sentinel-2 satellites. It's important to note that the 5-day time series consist of interpolated and smoothed composites, not the original images. We used the radial basis convolutional filtering (RBF) available in the FORCE time series analysis (TSA) submodule (Schwieder et al. 2016). The RBF is similar to a spatial moving window average approach over time (Schwieder et al. 2016). We applied kernel width values of 10, 20, 30, and 50 days. We spectrally adjusted all the images to match Sentinel-2A, and we removed curve outliers and pixels that failed the quality checks for clouds and their shadows, snow, saturation, and limited illumination. The processed image time series are available in tiles of 30 by 30 km.
 Example images
Uploaded is an example of the index EVI for one of the generated 30 by 30 km tiles located around the city of Zürich. The values are multiplied by 10.000. The time series spans the month of July from 2018.

en: time-series remote-sensing raster-processing switzerland force sentinel-2

en: Sentinel-2 time series of Switzerland

de:
Resource Title: parameter_file_force_sentinel_tss_tsi.prm
    Size: 27530 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/633ffbf5-756f-4735-af10-909a3b09c7cb/resource/81f234c9-25ea-4927-a3af-92c915236882/download/sentinel_tss_tsi.prm
    Description: Parameter file that defined all the parameters for processing the Sentinel-2 time series

de:
Resource Title: EVI_time_series_201807_example.tif
    Size: 139814053 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/633ffbf5-756f-4735-af10-909a3b09c7cb/resource/959bf57a-1723-4eea-ad89-3c42243ca510/download/evi_time_series_201807_example.tif
    Description:

time-series

display_name: time-series


en:
Introduction
The ZIP file contains all data and code to replicate the analyses reported in the following paper.
Reber, U., Fischer, M., Ingold, K., Kienast, F., Hersperger, A. M., Grütter, R., & Benz, R. (2022). Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics. *Policy Sciences*. [https://doi.org/10.1007/s11077-022-09456-4](https://doi.org/10.1007/s11077-022-09456-4)
If you use any of the material included in this repository, please refer to the paper. If you use (parts of) the text corpus, please also refer to the sources used for its compilation listed below. The content of the texts may not be changed.
 Data folder
The data folder contains the following files.
* _corpus.parquet_: Text corpus of Swiss policy documents
* _dict_de.csv_: Biodiversity dictionary (German)
* _dict_fr.csv_: Biodiversity dictionary (French)
* _dict_it.csv_: Biodiversity dictionary (Italian)
* _topic_labels.csv_: labels/codes for policy sectors
* _topics.csv_: labels/codes for policy sectors
The corpus and the dictionary were compiled by the authors specifically for this project. The labels/codes for policy sectors are based on the [coding scheme](http://ws-old.parlament.ch/affairs/topics) of the Swiss Parliament.
 Text corpus
The text corpus consists of 439,984 Swiss policy documents in German, French, and Italian from 1999 to 2018. The corpus was compiled from the following source between 2020-10-01 and 2021-01-31.
* Transcripts and parliamentary businesses (e.g. questions, motions, parliamentary initiatives) via the [Web Services (WS)](https://www.parlament.ch/de/%C3%BCber-das-parlament/fakten-und-zahlen/open-data-web-services) provided by the Swiss Parliament
* The official compilation of federal legislation ("Amtliche Sammlung", AS) via [opendata.swiss](https://opendata.swiss/de/dataset/official-compilation-of-federal-legislation-bs-as-1947-2018) provided by the Swiss Federal Archives (SFA)
*  The federal gazette ("Bundesblatt") via [fedlex.admin.ch](https://www.fedlex.admin.ch/de/fga/index)
* Decisions of federal courts via [entscheidsuche.ch (ES)](https://entscheidsuche.ch/)
The corpus is stored in a single data frame to use with R saved as [PARQUET](https://parquet.apache.org/) file (corpus.parquet). The data frame has the following structure.
* _text_id_: Unique identifier for each text (source information as prefix, e.g. "t_")
* _doc_type_: Document type (see coding scheme below)
* _branch_: Government branche (1 legislative, 2 executive, 3 judicative)
* _stage_: Stage of policy process (1 drafting, 2 introduction, 3 interpretation)
* _year_: Year of publication
* _topic_: Policy sector (coding scheme in separate file in data folder)
* _lang_: Language (de, fr, it)
* _text_: Text
The following list contains the coding scheme for the doc_type variable.
* 101: Federal gazette // Draft for public consultation ("Vernehmlassungsverfahren")
* 102: Federal gazette // Explanation of draft for parliament ("Botschaft")
* 103: Federal gazette // Strategy, action plan
* 104: Federal gazette // Federal council decree ("Bundesratsbeschluss")
* 105: Federal gazette // (Simple) Federal decree ("(Einfacher) Bundesbeschluss")
* 106: Federal gazette // General decree ("Allgemeinverfügung")
* 107: Federal gazette // Treaty ("Übereinkommen")
* 108: Federal gazette // Treaty ("Abkommen")
* 109: Federal gazette // Draft for parliament ("Entwurf")
* 110: Federal gazette // Report ("Bericht")
* 111: Federal gazette // Report of parliamentary comission ("Bericht")
* 112: Federal gazette // Report of federal council ("Bericht")
* 201: Parl. businesses // Submitted text
* 202: Parl. businesses // Reason text
* 203: Parl. businesses // Federal council response
* 204: Parl. businesses // Initial situation
* 205: Parl. businesses // Proceedings
* 301: Parl. transcripts // Speech of MP
* 302: Parl. transcripts // Speech of federal council
* 401: Federal legislation // Legal text of the official compilation (law, ordinances, etc.)
* 501: Court decisions // Federal Supreme Court
* 502: Court decisions // Federal Criminal Court
* 503: Court decisions // Federal Administrative Court
 Code folder
The code folder contains all R code for the analyses. The files are numbered chronologically.
* _1_classifier_training.R_: Training of classifiers for classification of policy sectors
* _2_classifier_application.R_: Classification of documents in corpus
* _3_dictionary_application.R_: Biodiversity indexing of documents in corpus
* _4_stm_truncation.R_: Truncation of indexed documents to keep only relevant parts
* _5_stm_translation.R_: Translation of FR and IT documents to DE
* _6_stm_model.R_: Preprocesssing and structural topic model
* _7_plots.R_: Plots and numbers as included in the paper
The code/functions folder contains custom functions used in the scripts, e.g. to support topic model interpretation.
Package versions and setup details are noted in the code files.
 Contact
Please direct any questions to Ueli Reber (ueli.reber@eawag.ch).

en: bgb policy-documents biodiversity environmental--policy switzerland policy-analysis text-corpus

en: Replication files for "Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics"

format: ZIP

bgb

display_name: bgb

biodiversity

display_name: biodiversity

environmental--policy

display_name: environmental--policy

policy-analysis

display_name: policy-analysis

policy-documents

display_name: policy-documents

text-corpus

display_name: text-corpus


en:
Swiss National Forest Inventory. Results of the fourth survey 2009–2017.
The collection of data for the fourth National Forest Inventory (NFI) was carried out from 2009 to 2017, on average eight years after the third survey. The findings about state and development of Swiss forests are described and explained in detail. The report is structured according to the European criteria and indicators for sustainable forest management, namely: forest resources, health and vitality, wood production, biological diversity, protection forest and social economy. Finally, conclusions about sustainability are drawn based on the NFI findings.
Keywords: forest area, growing stock, increment, yield, forest structure, forest condition, timber production, biodiversity, protection forest, recreation, sustainability, results National Forest Inventory, Switzerland
Inventaire forestier national suisse. Résultats du quatrième inventaire 2009-2017.
Les relevés du quatrième inventaire forestier national suisse (IFN) ont eu lieu entre 2009 et 2017, en moyenne huit ans après le troisième inventaire. Les résultats sur l’état et l’évolution de la forêt suisse sont présentés et expliqués en détail. Le rapport est structuré thématiquement selon les critères et indicateurs européens pour la gestion durable des forêts : ressources forestières, santé et vitalité, production de bois, diversité biologique, forêt protectrice et socio-économie. L’ouvrage s’achève par un bilan de la durabilité basé sur les résultats de l’IFN.
Mots-clés : surface forestière, volume de bois, accroissement, exploitation, structure de la forêt, état de la forêt, production de bois, biodiversité, forêt protectrice, récréation, durabilité, résultats de l’inventaire forestier national, Suisse
Content license: All rights reserved. Copyright © 2020 by WSL, Birmensdorf.

en: nfi forest 2009-2017 national-forest-inventory lfi

de:
Resource Title: Corrigendum / Erratum
    Size: 518804 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/58cf77e8-78f6-460d-9c1b-5c0857b0cc25/resource/e5620e14-9a81-4d48-9a31-1acf93ff80f5/download/korrigendum_lfi4_fr_tab_155.pdf
    Description:

format: PDF

media_type: application/pdf

de:
Resource Title: ISBN: 978-3-905621-61-7
    Size: 65866156 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/58cf77e8-78f6-460d-9c1b-5c0857b0cc25/resource/149edc8c-30eb-4164-935f-ca53c21e16dd/download/lfi4_fr_web_200603.pdf
    Description:

de:
Resource Title: Registration in DORA
    Size: 1 bytes
    Format: No Info
    URL: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:23455
    Description:

forest

display_name: forest

lfi

display_name: lfi

national-forest-inventory

display_name: national-forest-inventory

nfi

display_name: nfi


en:
The first EVOLTREE Conference, taking place in hybrid format (on-site and online) at WSL Birmensdorf (Switzerland) from 14-17 September, 2021, focuses on the genomics of trees and interacting species from evolutionary, demographic, and ecological perspectives.
EVOLTREE is a European network of institutions engaged in studying the evolution and functioning of forest ecosystems, in particular trees as the foundation species in forest stands. A prime topic in the face of ongoing climate change is to elucidate how trees, together with their associated organisms such as mycorrhizal fungi, respond to rapid environmental changes.
The conference includes contributions that apply innovative approaches and consider the relevance of their research in the context of biodiversity conservation through natural dynamics or silvicultural interference.

en: abstracts genomics evoltree adaptation conference forest-ecosystems

en: Genomics and Adaptation in Forest Ecosystems. Book of Abstracts. EvolTree Conference 2021, 14 – 17 September 2021, Birmensdorf, Switzerland

abstracts

display_name: abstracts

adaptation

display_name: adaptation

conference

display_name: conference

evoltree

display_name: evoltree

forest-ecosystems

display_name: forest-ecosystems

genomics

display_name: genomics


en:
This dataset contains modeled and experimental results for laboratory snow failure experiments and the concurrent acoustic emissions signatures for different loading rates. For modelling the snow failure we used a fiber bundle model that includes sintering and viscous deformation.
The data underlay the figures in the publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted for publication to "Geophysical Research Letters".

en: snow-failure snow-avalanche snow-mechanics snow viscous-deformation fiber-bundle-model acoustic-emissions sintering

en: Fiber Bundle Model for snow failure and concurrent Acoustic Emissions

envi

en: Environment

acoustic-emissions

display_name: acoustic-emissions

fiber-bundle-model

display_name: fiber-bundle-model

sintering

display_name: sintering

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-mechanics

display_name: snow-mechanics

viscous-deformation

display_name: viscous-deformation


en:
This dataset contains the road and plot data used for the geospatial analysis example showcased in "Fostering Open Science at WSL with the EnviDat Environmental Data Portal", a contribution to the 5th Open Source Geospatial Research and Education Symposium (OGRS), 2018.
The example uses Jupyter Notebook to calculate road densities in the neighbourhood of sample plot locations with Python. Road data were extracted from OpenStreetMap, while the point data (sample plots) were generated manually.

en: gis roads buffer jupyter density geospatial

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: Dataset for OGRS 2018 publication

de:
Resource Title: Strassen_OSM
    Size: 394934 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c16efa5-2c29-468a-916a-4a005b3bff02/resource/5d097dde-387f-4ab9-9e95-aa47c14bae75/download/menzbergzero.zip
    Description: Road data from OSM for the surroundings of Menzberg, Switzerland

media_type: application/zip

de:
Resource Title: Road Density Calculation (Python Notebook)
    Size: 8643 bytes
    Format: application/x-ipynb+json
    URL: https://www.envidat.ch/dataset/6c16efa5-2c29-468a-916a-4a005b3bff02/resource/38ba30db-e7cd-45eb-b84e-5d00e1877dd3/download/roaddensitycalculation.ipynb
    Description:

de:
Resource Title: Road Density Calculation (Python Notebook) online
    Size: 0
    Format: application/x-ipynb+json
    URL: https://nbviewer.jupyter.org/urls/www.envidat.ch/dataset/6c16efa5-2c29-468a-916a-4a005b3bff02/resource/38ba30db-e7cd-45eb-b84e-5d00e1877dd3/download/roaddensitycalculation.ipynb
    Description:

de:
Resource Title: Plots
    Size: 1719 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c16efa5-2c29-468a-916a-4a005b3bff02/resource/173de5b0-ae7b-46dc-9b1f-7df640106736/download/plots.zip
    Description: Random plot locations

buffer

display_name: buffer

density

display_name: density

geospatial

display_name: geospatial

gis

display_name: gis

jupyter

display_name: jupyter

roads

display_name: roads


en:
Two data sets obtained for snow farming projects (Fluela, Davos, CH and Martell, IT) in 2015.
The data set contains for each site:
* 10 cm GIS raster of snow depth calculated from terrestrial laserscanning surveys (TLS) in the end of winter season (April/May)
* 10 cm GIS raster of snow depth calculated from TLS in the end of summer season (October)
Input files for SNOWPACK model:
* .sno: snow profile at the end of winter
* .smet: meteorological data measured by weather stations in the area
For more details see  Grünewald, T., Lehning, M., and Wolfsperger, F.: Snow farming: Conserving snow over the summer season, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-93, in review, 2017.

en: snow-farming terrestrial-laser-scanning snowpack winter-tourism snow snow-conservation

en: Snowfarming data set Davos and Martell 2015

de:
Resource Title: HS Martell autumn 2015
    Size: 2412003 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/0d16510c-f1d4-4de2-86f7-b5ef2fb0bd0f/download/20151028_martell_hs.txt
    Description: Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

format: TXT

media_type: text/plain

de:
Resource Title: Martell .sno
    Size: 1761 bytes
    Format: .sno
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/bd5861f8-f17c-4133-9ff2-c8526e67804e/download/martell_1schicht_lwc3.sno
    Description: Input snow profile (.sno file) used for SNOWPACK simulations of the Martell heap

de:
Resource Title: HS Fluela spring 2015
    Size: 1702059 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/a0aef820-34e4-490a-9271-a12646f37b67/download/20150429_fluela_hs.txt
    Description: Snow depth/ height of snow heap in spring 2015 obtained by terrrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903

de:
Resource Title: Martell .smet
    Size: 827214 bytes
    Format: application/x-smet
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/5c4a89bc-c16a-4c37-92e6-183a50438fae/download/meteo_martell.smet
    Description: Meteodata used as input for SNOWAPCK simulations, orginating from Station Hintermartell.

de:
Resource Title: Fluela .sno
    Size: 1919 bytes
    Format: .sno
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/f31e7520-2624-4628-a7a9-bb0bcbeea876/download/fluela_1schicht_40cm_lwc3.sno
    Description: Input snow profile (.sno file) used for SNOWPACK simulations of the Flüela heap

de:
Resource Title: HS Fluela autumn 2015
    Size: 1720506 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/47f70f9b-63df-44aa-836c-02a46bbf4f6b/download/20151008_fluela_hs.txt
    Description: Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903
Nodata: -9999

de:
Resource Title: Fluela .smet
    Size: 889965 bytes
    Format: application/x-smet
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/7e360bad-ec83-4675-802e-05dc7a701a27/download/haufen_vwcor_shade.smet
    Description: Meteodata used as input for SNOWAPCK simulations, orginating from Station Windtunnel and DAV.

de:
Resource Title: HS Martell spring 2015
    Size: 2332516 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/558c33f7-ce57-45b8-a339-f617be015e96/download/20150519_martell_hs.txt
    Description: Snow depth/ height of snow heap in spring 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

snow-conservation

display_name: snow-conservation

snow-farming

display_name: snow-farming

snowpack

display_name: snowpack

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

winter-tourism

display_name: winter-tourism


en: This dataset contains the results obtained by an automatic classification using hidden Markov models of a continuous seismic dataset. To avoid long computational times, we reduced the seismic data using pre-processing step. The start and end times of the windows used for the classification are also included in this dataset. Furthermore, an avalanche reference data set is included and the python scripts used to perform the processing steps and the classification.

en: seismic hidden-markov-model snow monitoring avalanche-activity

envidat

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

de: EnviDat: das Umwelt-Datenportal

de: EnviDat

en: Automatic detection of avalanches

envi

de: Umwelt

avalanche-activity

display_name: avalanche-activity

hidden-markov-model

display_name: hidden-markov-model

monitoring

display_name: monitoring

seismic

display_name: seismic


en:
The data presented here corresponds to the publication "Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain" (Gerber et al., 2018a), which investigates the precipitation variability of snow precipitation in the central northern part of the Grisons (CH) and the publication "The importance of near-surface winter precipitation processes in complex alpine terrain" (Gerber et al., 2018b). The dataset contains:
* WRFsimulations: WRF simulation output for simulations with 4x (14x) terrain smoothing with an output timestep of 30 min/5 min and horizontal grid spacings of 1350 m, 450 m, 150 m and 50 m (currently: data available upon request).
* StationData: Meteorological station data of 18 meteorological stations in the central northern part of the Grisons with 30 minute resolution for the period 1 January 2016 till 1 May 2016.
* ADS80data: Photogrammetrically determined snow depth distribution data over the Dischma valley for the 26 January 2016 and 9 March 2016. Snow heights are corrected for buildings, vegetation (- 1m), outliers, and pixles, which are obivously snow-free on the pictures (Bühler et al., 2015). In addition the snow depth differences (snow depth on 9 March 2016 minus snow depth on 26 January 2016) are provided.
For more details about the simulation and observation data, see Gerber et al., 2018 and Gerber and Sharma (2018).
Publications:
Bühler, Y., Marty, M., Egli, L., Veitinger, J., Jonas, T., Thee, P., and Ginzler, C.: Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9, 229–243, doi:10.5194/tc-9-229-2015, 2015.
Gerber, F., Besic, N., Sharma, V., Mott, R., Daniels, M., Gabella, M., Berne, A., Germann, U., and Lehning, M.: Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain, The Cryosphere, 12, 3137–3160, doi:10.5194/tc-12-3137-2018, 2018.
Gerber, F., Mott, R. and Lehning, M.: The importance of near-surface winter precipitation processes in complex alpine terrain, Journal of Hydrometeorology, accepted, 2018.
Gerber, F., and Sharma, V.:  Running COSMO-WRF on very-high resolution over complex terrain. Laboratory of Cryospheric Sciences CRYOS, École Polytechnique Fédérale de Lausanne EPFL, Lausanne, Switzerland. doi:10.16904/envidat.35, 2018.

en: cosmo-wrf complex-terrain precipitation-variability orographic-precipitation snow-precipitation

en: DISCHMEX - High-resolution WRF simulations in complex alpine terrain and station measurements

de:
Resource Title: ADS80data
    Size: 88940889 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/68536bc6-0990-41c0-a06f-21b19c0f2ffe/resource/dd0a21fc-e609-4a79-ab10-58e7dd9953d4/download/ads80data.zip
    Description: Snow depth maps over Dischma valley for 26 January 2016 and 9 March 2016 and snow depth differences between the two dates.

de:
Resource Title: StationData
    Size: 1161085 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/68536bc6-0990-41c0-a06f-21b19c0f2ffe/resource/096c4c10-1d39-428b-9762-e6c769553cbd/download/stationdata.zip
    Description: Meteorological station data of 18 meteorological stations in the central northern part of the Grisons with 30 minute resolution for the period 1 January 2016 till 1 May 2016.

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

orographic-precipitation

display_name: orographic-precipitation

precipitation-variability

display_name: precipitation-variability

snow-precipitation

display_name: snow-precipitation


en: Five full-scale field tests were conducted with concrete blocks weighting between 800 and 3200 kg being dropped onto the roof of a gallery structure made from reinforced concrete. The impacts were recorded using high-speed video and acceleration measurements at the falling blocks. The dataset contains the raw data as well as the analyses of the block trajectories, i.e. kinetics and dynamics. Setup of the measurements and the analyses conducted are published in Volkwein, A. "Durchführung und Auswertung von Steinschlagversuchen auf eine Stahlbetongalerie", WSL-Berichte, Heft 68, 2018.

en: experiment experiments natural-hazard field-data rockfall rockfall-experiments mass-movements impact-testing field-tests field-test

en: Rockfall gallery testing Parde 2016

de:
Resource Title: Acceleration measurements
    Size: 320251100 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2c3b41a5-0ff2-4d65-b396-19afe029df09/resource/1dd217a8-3975-4ae8-a7fe-83302438a7df/download/parde2016_accelmeas.zip
    Description: The zip file contains five excel files, one for each test conducted. The first sheet contains the raw data and a data set that went through a low-pass filter. The sheet "Allgemein" contains calibration factors for the sensors and time details of a test. The sheets "DiaDaten" and "DiaDatenGefiltert" show the measurements over time. The block and slab kinetics are determined in the sheets "ZeitintegrationBlock" and "ZeitintegrationPlatte". The sheet "VergleichBeschleunigungen" shows the influence of the low-pass-filter and a running average filter on the block accelerations.

de:
Resource Title: Video analysis
    Size: 7038602 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2c3b41a5-0ff2-4d65-b396-19afe029df09/resource/4b0dc245-87aa-4b49-bea5-560b95be025a/download/parde2016_videoanalyses.zip
    Description: The zip contains five Excel-files that in turn contain the results of the performed video analyses. The sheet "Daten" contains the pixels of different positions on the blocks that were tracked by the software "Kinovea". The sheet "Auswertung" determines the block kinetics based on the pixel data over time.

de:
Resource Title: Raw data (high speed videos, acceleration measurements, laboratory tests)
    Size: 276966499 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2c3b41a5-0ff2-4d65-b396-19afe029df09/resource/0ab7ed13-b413-4936-9c2a-04fff646397f/download/parde2016_rohdaten.zip
    Description: This file contains

* the high speed videos showing the concrete blocks impacting the gallery roof.
* the raw data of the acceleration measurements
* the data of Tiefbauamt Graubünden containg the tension tests of gallery reinforcment, ME-testing the cushion layer and the tests on concrete samples.

experiment

display_name: experiment

experiments

display_name: experiments

field-data

display_name: field-data

field-test

display_name: field-test

field-tests

display_name: field-tests

impact-testing

display_name: impact-testing

mass-movements

display_name: mass-movements

natural-hazard

display_name: natural-hazard

rockfall

display_name: rockfall

rockfall-experiments

display_name: rockfall-experiments


en:
Location of data collection
The Swiss National Park (SNP) is located in the southeastern part of Switzerland, and covers an area of 170 km2, 50 km2 of which is forested, 33 km2 is occupied by alpine and 3 km2 by subalpine grasslands. Elevations range from 1350 to 3170 m a.s.l., and mean annual precipitation and temperature are 871 mm and 0.6°C measured at the Park’s weather station in Buffalora (1980 m a.s.l.) between 1960 and 2009 (MeteoSchweiz 2011). Founded in 1914, the SNP received minimal human disturbance for almost 100 years (no hunting, fishing, or camping, visitors are not allowed to leave the trails). Large (- 1 ha) homogeneous patches of short- and tall-grass vegetation characterize the subalpine grasslands. The average vegetation height of short-grass vegetation is 2 to 5 cm. Red fescue (Festuca rubra L.), quaking grass (Briza media L.) and common bent grass (Agrostis tenuis Sipthrob) are the predominating plant species in this vegetation type. Tussocks of evergreen sedge (Carex sempervirens Vill.) and mat grass (Nardus stricta L.) are predominant in the tall-grass vegetation, which averages 20 cm in vegetation height (Schütz and others 2006). Short-grass vegetation developed in areas where cattle and sheep rested (high nutrient input) during agricultural land-use (from 14th century until 1914); tall-grass vegetation developed in areas where cattle and sheep used to graze, but did not rest (Schütz and others 2003, 2006). Herbivores were shown to consume - 60% of the biomass in short-grass compared to - 20% in tall-grass vegetation (Schütz and others 2006). The herbivore community present in the SNP can be divided into four groups based on body size/weight: large [red deer (Cervus elaphus L.) and chamois (Rupricapra rupricapra L.); 30 - 150 kg], medium [marmot (Marmota marmota L.) and snow hare (Lepus timidus L.); 3 – 6 kg], and small vertebrate herbivores (small rodents: e.g. Clethrionomys spp., Microtus spp., Apodemus spp.; 30 – 100 g) as well as invertebrates (e.g. grasshoppers, caterpillars, cicadas, - 5 g).
Experimental design
We selected 18 subalpine grassland sites (9 short-grass, 9 tall-grass vegetation). The sites were spread across the entire park on dolomite parent material at altitudes of 1975 to 2300 meters. At each site we established an exclosure network (fences) in spring 2009 (early June), immediately after snowmelt. Each exclosure network consisted of a total of five 2 × 3 m sized plots that progressively excluded the different herbivores listed above (further labeled according to the herbivore guilds that had access to the respective plots “All”, “Marmot/Mice/Invertebrates”, “Mice/Invertebrates”, “Invertebrates”, “None”). The “All” treatment was thus accessible to all herbivores, was not fenced and was located at least 5 m away from a 2.1 m tall and 7 × 9 m main fence that enclosed the other four treatments. This fence was constructed of 10 × 10 cm wooden posts and electrical equestrian tape (AGRARO ECO, Landi, Bern, Switzerland; 20 mm width) mounted at 0.7 m, 0.95 m, 1.2 m, 1.5 m and 2.1 m above the ground that were connected to a solar charged battery (AGRARO Sunpower S250, Landi, Bern, Switzerland). We also mounted non-electrically charged equestrian tape at 0.5 m to help exclude deer and chamois, yet allow marmots and hares to enter safely. Within each main fenced area we randomly established four 2 × 3 m plots: (1) The “Marmot/Mice/Invertebrates” plot remained unfenced, thus, with the exception of red deer and chamois, all herbivores were able to access the plot, (2) The “Mice/Invertebrates” plot consisted of a 90 cm high electric sheep fence (AGRARO Weidezaunnetz ECO, Landi, Bern, Switzerland; mesh size 10 × 10 cm) connected to the solar panel and excluded all medium sized mammals (marmots, hares), but provided access for small mammals and invertebrates, (3) The “Invertebrates” plot provided access for invertebrates only and was surrounded by 1 m high metal mesh (Hortima AG, Hausen, Schweiz; mesh size 2 × 2 cm), (4) The “None” plot was surrounded by a 1 m tall mosquito net (Sala Ferramenta AG, Biasca, Switzerland; mesh size 1.5 × 2 mm) to exclude all herbivores. This plot was covered with a roof constructed of a wooden frame lined with mosquito mesh that was mounted on the wooden corner posts. We also treated this plot with a biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) when needed to remove insects that might have entered during data collection or that hatched from the soil.
!!! The here published data set only contains data for “All”, and “Marmot/Mice/Invertebrates” (= ungulates excluded) plots !!!
Data collection
In-situ soil CO2 emissions were measured with a PP-Systems SRC-1 soil respiration chamber (closed circuit) attached to a PP-Systems EGM-4 infrared gas analyzer (PP-Systems, Amesbury, MA, USA) on two randomly selected locations on one subplot within each of the 90 plots. For each measurement the soil chamber (15 cm high; 10 cm diameter) was placed on a permanently installed PVC collar (10 cm diameter) driven five centimeters into the soil at the beginning of the study (June 2009). The measurements were conducted between 0900 and 1700 hours every two weeks from early to early September 2009, 2010, 2011 and 2013. Freshly germinated plants growing within the PVC collars were removed prior to each measurement to avoid measuring plant respiration/photosynthesis. The two measurements collected per plot every two weeks were averaged.
Please acknowledge the funding of the study: funded by the Swiss National Science Foundation, SNF grant-no 31003A_122009/1 to Anita C. Risch, Martin Schütz and Flurin Filli

en: ungulates subalpine grazing grassland soil-respiration

en: Soil respiration - exclosure experiment

envi

en: Environment

format: XLS

grassland

display_name: grassland

grazing

display_name: grazing

soil-respiration

display_name: soil-respiration

subalpine

display_name: subalpine

ungulates

display_name: ungulates


en:
Dataset of an experimental campaign of induced rockfall in Tschamut, Grisons, Switzerland.
The data archive contains site specific geographical data such as DEM and orthophoto as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally available are all the StoneNode data streams for rocks equipped with a sensor. The data set consists of
* Deposition points from two series (wet (27/10/2016) and frozen (08/12/2016) ground)
* Digital Elevation Model (grid resolution 2 m) obtained via UAV
* Orthophoto (5 cm resolution) obtained via UAV
* Digitized rock point clouds (.pts input files for RAMMS::ROCKFALL)
* StoneNode v1.0 raw data stream for equipped rocks.
Further information is found in
* A. Caviezel et al., _Design and Evaluation of a Low-Power Sensor Device for Induced Rockfall Experiments_, IEEE Transactions on Instrumentation and Measurement, 2018, 67, 767-779, http://ieeexplore.ieee.org/document/8122020/
*  P. Niklaus et al., _StoneNode: A low-power sensor device for induced rockfall experiments_, 2017 IEEE Sensors Applications Symposium (SAS), 2017, 1-6, http://ieeexplore.ieee.org/document/7894081/

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

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

de:
Resource Title: StoneNode v1.0 Data for equipped experimental Runs.
    Size: 6899716 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/5b7a47bf-cbea-42a0-879f-ea2ccd17e82f/resource/c80b0561-d5f8-4bd6-97e7-ec5a15bfd84e/download/experimentalruns_sensorstreams.7z
    Description: Corresponding StoneNode v1.0 data streams belonging to the deposition points.

de:
Resource Title: Induced Rockfall Data, Tschamut, GR
    Size: 83833546 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/5b7a47bf-cbea-42a0-879f-ea2ccd17e82f/resource/3be3d9f6-cf12-4dbc-bdf1-80e101fb47f7/download/2018_rf_tschamut.7z
    Description: __ Induced Rockfall Experimental Data, Tschamut, GR, Switzerland__

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

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

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

dem

display_name: dem

deposition-points

display_name: deposition-points

induced-rockfall

display_name: induced-rockfall

natural-hazards

display_name: natural-hazards

rockfall-runout

display_name: rockfall-runout

sensor-stream

display_name: sensor-stream

stonenode

display_name: stonenode

stonenodedata

display_name: stonenodedata


en:
In summer 2014, 6 rock blocks between 20 and 80kg have been thrown in total 111 times down a slope at the Swiss Oberalppass close to the village Tschamut. The slope was mainly covered by grass and its lower part was flat and large enough to provide natural runouts of the single trajectories.
An extensive measurement program has been set up to measure the block trajectories: With surveyor's instruments the slope and the six used rock blocks were scanned and the start and end positions of each test were recorded. During the single events two cameras filmed the trajectories. A special sensor device located within the blocks recorded the acting accelerations and rotational speeds over time. Further, the device emitted a Wifi signal that got detected from eight receivers around the slope. Based on this signal the block position has been recorded over time.
The dataset contains all data that were gathered through above field campaign.

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

en: Repetitive trajectory testing in Tschamut 2014

de:
Resource Title: Overview of all tests
    Size: 44962 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6a7664a6-77a9-49c9-9498-4b63c018fa09/resource/467dc8f8-9069-4c87-8856-3d12817633be/download/overviewalltests.zip
    Description: This table gives an overview on all tests performed including
- block used
- start & end position
- number of jumps
- etc.
-

de:
Resource Title: Block trajectories recorded from local positioning system
    Size: 6430962 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6a7664a6-77a9-49c9-9498-4b63c018fa09/resource/b6dc0f14-5b86-4353-a2a6-ef06c0ddf0ad/download/trajectoriesfromlps.zip
    Description: This file contains more than 80 rockfall trajectories projected onto the terrain, i.e. the positions of the single blocks over time during the single tests that were recorded by the local positioning system with about 10Hz. It contains the detected positions as well as a smoothened path (see Volkwein et al., Geosciences, 2018). The table also contains the derived velocities and accelerations along the slope (attention: these accelerations are the once that occur during an impact).

de:
Resource Title: Tschamut2014_Slope+BlockScans
    Size: 1779331 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6a7664a6-77a9-49c9-9498-4b63c018fa09/resource/8cf275ca-06d0-47cf-b67f-48780b019ae6/download/geosciences-08-00088-s001.zip
    Description: These data contain the point clouds obtained from laser scanning the test slope and the six test blocks used for the experiments. The coordinates of the slope are given in CH-1903 format. The coordinates of the block point clouds are kept in a lokal x/y/z coordinate system.

de:
Resource Title: Jumps and impacts
    Size: 1051503 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6a7664a6-77a9-49c9-9498-4b63c018fa09/resource/e2f0958e-2b51-49ce-ba25-40c4ffd331a7/download/jumpsandimpacts.zip
    Description: This table contains data of more than 2200 of each jumps and impacts of the test blocks on a grassy slope. It gives there durations in combination with acting accerlartions and the rotational speed of the blocks. The data were retrieved using the block internal accelerometer and rotation sensors. The combination of these data with the measurement from the local positioning system allows the deduction of jump lengths, slope gradient etc.

experiment

display_name: experiment

experiments

display_name: experiments

field-data

display_name: field-data

field-test

display_name: field-test

field-tests

display_name: field-tests

mass-movements

display_name: mass-movements

trajectory

display_name: trajectory


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

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

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

de:
Resource Title: DEM 2016
    Size: 73447711 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/787f969b-71db-4ec9-967b-7e0198dd9d71/download/2016dem.zip
    Description: Digital Elevation Modell 2016

de:
Resource Title: Gletschboden test site
    Size: 352578 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/645e45ec-fc90-432c-a29e-d1d79781d5b2/download/dischma_neu.pdf
    Description:

de:
Resource Title: DEM 2015
    Size: 85474333 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/9d19c582-76ca-45df-b032-46d8346f45be/download/2015dem.zip
    Description: Digital Elevation Modell 2015

de:
Resource Title: Snowmask 2015
    Size: 6736562 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/89c08602-142c-4fdb-9c76-3993a9d0dbfc/download/2015snowmask.zip
    Description:

de:
Resource Title: Snowmask 2016
    Size: 1979860 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/2b54670d-74e9-4ea5-8fcd-4ea98ad26ed6/download/2016snowmask.zip
    Description:

de:
Resource Title: Snowmask 2014
    Size: 2069460 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/5a5b22eb-a0ae-4552-a7b3-34631c3ae998/download/2014snowmask.zip
    Description:

de:
Resource Title: DEM 2014
    Size: 76297946 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/299a98ef-94e5-4bdd-912f-24b347d20da6/download/2014dem.zip
    Description: Digital Elevation Modell 2014

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

tls

display_name: tls


en: This Weissfluhjoch dataset is a processed version  of the Weissfluhjoch dataset version 6 from https://doi.org/10.16904/6. This dataset was specially created for the ESM-SnowMIP project. Here it is documented how this dataset has been created.

en: snow-depth snow snow-models esm-snowmip weissfluhjoch

envidat

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

de: EnviDat: das Umwelt-Datenportal

de: EnviDat

en: Weissfluhjoch dataset for ESM-SnowMIP

envi

de: Umwelt

de:
Resource Title: Conversion script
    Size: 900 bytes
    Format: text/x-sh
    URL: https://www.envidat.ch/dataset/a9264e9f-ea9b-4c89-b471-464efb891826/resource/aa8942dc-5fe5-4792-bf4b-1b950d9c6204/download/createwfjdataset.sh
    Description: Use this script to convert WFJ_optimaldataset_v6.smet to wfj.smet, the file that is used for the ESM-SnowMIP project. It also requires the file: WFJ_AirPressure_Data.zip

Use: bash create_wfj_dataset.sh > input/wfj.smet

de:
Resource Title: WFJ_AirPressure_Data.zip
    Size: 4688961 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9264e9f-ea9b-4c89-b471-464efb891826/resource/b834a645-c5e0-4bf1-bceb-17a2eb62b61a/download/wfjairpressuredata.zip
    Description: WFJ_AirPressure_Data.zip

de:
Resource Title: ini file
    Size: 1410 bytes
    Format: text/x-ini
    URL: https://www.envidat.ch/dataset/a9264e9f-ea9b-4c89-b471-464efb891826/resource/c7f7533e-03f2-42c2-ad82-36d3c6ab8fd2/download/io.ini
    Description: This ini file is required by data-converter from MeteoIO version 1887 (http://models.slf.ch/p/meteoio/)

de:
Resource Title: Dataset Weissfluhjoch for ESM-SnowMIP
    Size: 11596605 bytes
    Format: application/x-smet
    URL: https://www.envidat.ch/dataset/a9264e9f-ea9b-4c89-b471-464efb891826/resource/a5918c50-6716-4dcf-b462-e1970ae1e072/download/wfj.smet
    Description: Dataset Weissfluhjoch for ESM-SnowMIP

esm-snowmip

display_name: esm-snowmip

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-models

display_name: snow-models

weissfluhjoch

display_name: weissfluhjoch


en:
Stable water isotopes (δ18O) obtained from snow and ice samples of polar regions are used to reconstruct past climate variability, but heat and mass transport processes can affect the isotopic composition. Here we present an experimental study on the effect on the snow isotopic composition by airflow through a snow pack in controlled laboratory conditions. The influence of isothermal and controlled temperature gradient conditions on the δ18O content in the snow and interstitial water vapor is elucidated. The observed disequilibrium between snow and vapor isotopes led to exchange of isotopes between snow and vapor under non-equilibrium processes, significantly changing the δ18O content of the snow. The type of metamorphism of the snow had a significant influence on this process.
Ebner, P. P., Steen-Larsen, H. C., Stenni, B., Schneebeli, M., and Steinfeld, A.: Experimental observation of transient δ18O interaction between snow and advective airflow under various temperature gradient conditions, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-16, accepted, 2017.

en: stable-water-isotope snow advection metamorphism 18o

en: Experiments on stable water isotopes,  snow metamorphism, and advection

de:
Resource Title: Read-me
    Size: 974 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/f87efc01-9914-4a75-998f-7dfc1fcef563/resource/92a315fd-1e17-4b9e-bce3-e69a3fac0d0a/download/readme.txt
    Description: A short description of the data contained in the zipped-file. Recommended for reading before downloading the dataset.

de:
Resource Title: Data files and read-me
    Size: 8226023 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f87efc01-9914-4a75-998f-7dfc1fcef563/resource/e133ed87-de41-4595-87c9-b07f696c5cce/download/archive.zip
    Description: raw data and micro-CT data available from contacts

advection

display_name: advection

metamorphism

display_name: metamorphism

stable-water-isotope

display_name: stable-water-isotope


en:
Dataset of meteorological and snowpack measurements from the automatic weather station at Weissfluhjoch, Davos, Switzerland, suitable for driving snowpack models. The dataset contains standard meteorological measurements, and additionally snowpack runoff data from a snow lysimeter. Where possible, data is quality checked and missing data are replaced from backup sensors from the measurement site itself, or (in only a few cases) from the MeteoSwiss weather station at 470 m distance and 150 m above the measurement site.
Publication
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M. Verification of the multi-layer SNOWPACK model with different water transport schemes. 2015. The Cryosphere. Volume 9. 2271-2293. http://dx.doi.org/10.5194/tc-9-2271-2015.

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

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

envi

en: Environment

de:
Resource Title: Version 2
    Size: 0
    Format: application/x-smet
    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset_v2.smet
    Description: Deprecated version. Release notes:

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

de:
Resource Title: Version 1
    Size: 0
    Format: application/x-smet
    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset.smet
    Description: Deprecated version. Release notes:

First release of dataset.

de:
Resource Title: Undercatch correction
    Size: 59121 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/022a5232-e9a6-4972-a59a-f1aedc2697d3/download/undercatch.pdf
    Description: This document describes how the undercatch correction for the Weissfluhjoch measurement site was determined.

de:
Resource Title: Version 4
    Size: 0
    Format: application/x-smet
    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset_v4.smet
    Description: Deprecated version. Release notes:

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

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

de:
Resource Title: Version 3
    Size: 0
    Format: application/x-smet
    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset_v3.smet
    Description: Deprecated version. Release notes:

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

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

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

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

de:
Resource Title: SNOWPACK ini file (new syntax)
    Size: 2490 bytes
    Format: text/x-ini
    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/8d201858-fba9-449c-b41b-4e49624fa6cc/download/iowfjref.ini
    Description: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using the new MeteoIO Filter, Generator and Interpolation syntax.

de:
Resource Title: All versions
    Size: 0
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=slf/snow_and_permafrost/wfj_mod/
    Description:

de:
Resource Title: Version 5
    Size: 0
    Format: application/x-smet
    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset_v5.smet
    Description: Deprecated version. Release notes:

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

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

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

de:
Resource Title: Version 7 (current)
    Size: 35666937 bytes
    Format: application/x-smet
    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/3074d1dc-6083-4025-9ac4-484cfa88658b/download/wfj_optimaldataset_v7.smet
    Description: Release notes:

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

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

de:
Resource Title: SNOWPACK sno file
    Size: 1095 bytes
    Format: .sno
    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/ec0609f1-42fa-4a20-945e-6809bb15a8a0/download/wfj2.sno
    Description: This sno-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

de:
Resource Title: Version 6
    Size: 0
    Format: application/x-smet
    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset_v6.smet
    Description: Deprecated version.

Release notes:

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

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

de:
Resource Title: SNOWPACK ini file (old syntax)
    Size: 2223 bytes
    Format: text/x-ini
    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/e51b83ae-99a6-42f0-add4-8da9590c6573/download/iowfjref.ini
    Description: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

air-temperature

display_name: air-temperature

humidity

display_name: humidity

longwave-radiation

display_name: longwave-radiation

precipitation-amount

display_name: precipitation-amount

shortwave-radiation

display_name: shortwave-radiation

snow-ice-temperature

display_name: snow-ice-temperature

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed


en:
The data correspond to the experiments presented and discussed in a paper regarding the interaction between turbulent wind fluctuations and snow saltation mass-fluxes (Paterna, 2016). Each of the nine data files corresponds to a different experiment presented in the paper and conducted in the winter 2014/2015 in the WSL/SLF cold wind tunnel in Davos. For each file the five columns indicate the time from the beginning of the experiment, the streamwise (u’) and the vertical (w’) wind velocity fluctuations, the streamwise (qx) and the vertical (qz) snow mass-flux components. From these time-series the scales of the snow saltation and of the turbulent flow are obtained with respect to the eddy-cycles and snow saltation cycles. From spectral analysis of the time-series a decoupling of the snow saltation from the turbulence forcing reveals two regimes of interaction: a turbulence-dependent regime occurring with weak saltation, and a turbulence-independent regime with strong saltation. Further details can be found at the link below.
Publication http://onlinelibrary.wiley.com/doi/10.1002/2016GL068171/abstract

en: vertical-wind-motion snow-depth saltation boundary-layer-winds snow-cover

envidat

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

de: EnviDat

en: Wind tunnel measurement data of drifting snow and turbulent wind fluctuations

envi

de: Umwelt

boundary-layer-winds

display_name: boundary-layer-winds

saltation

display_name: saltation

snow-cover

display_name: snow-cover

vertical-wind-motion

display_name: vertical-wind-motion


en:
In 2013–2014, a survey was conducted in Switzerland to update the Forest Access Roads geo-dataset within the framework of the Swiss National Forest Inventory (NFI). The resulting nationwide dataset contains valuable information on truck-accessible forest roads that can be used to transport wood. The survey involved interviewing staff from the approximately 800 local forest services in Switzerland and recording the data first on paper maps and then in digitized form. The data in the NFI on the forest roads could thus be updated and additional information regarding their trafficability for specific categories of truck included. The information has now been attached to the geometries of the Roads and Tracks of the swissTLM3D (release 2012) of the Federal Office of Topography swisstopo. The resulting data are suitable for statistical analyses and modeling, but further (labour-intensive) validation work would be necessary if they are to be used as a basis for applications requiring more spatial accuracy, such as navigation systems. The data are managed at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and are available for third parties for non-commercial use provided they have purchased a TLM license.
Related Publication: [doi: 10.3188/szf.2016.0136](http://dx.doi.org/10.3188/szf.2016.0136)

en: trucks timber-harvesting forest-transportation-systems forest-access-roads trafficability

en: Forest Access Roads 2013

forest-access-roads

display_name: forest-access-roads

forest-transportation-systems

display_name: forest-transportation-systems

timber-harvesting

display_name: timber-harvesting

trafficability

display_name: trafficability

trucks

display_name: trucks


en: Long-term data on precipitation and runoff are essential to draw firm conclusions about the behavior and trends of hydrological catchments that may be influenced by land-use and climate change. Here the longest continuous runoff records (1903 - 2015) from small catchments (less than 1 km2) in Switzerland (and possibly worldwide) are provided as a data set. The history of the hydrological monitoring in the Sperbel- and Rappengraben (Emmental) is summarized in Stähli et al., Environ Monit Assess (2011). The runoff stations operated safely for more than 90% of the summer months when most of the major flood events occurred. Nevertheless, the absolute values of peak runoff during the largest flood events are subject to considerable uncertainty (also discussed in Stähli et al., 2011). This treasure trove of data can be used in various ways, eg. for analysis of the generalized extreme value distributions of the two catchments, of the mechanisms governing the runoff behavior of small catchments, as well as for testing stochastic and deterministic models.

en: watershed-drainage-basins precipitation air-temperature runoff snow-depth

en: More than one century of hydrological monitoring in two small catchments with different forest coverage, Sperbelgraben and Rappengraben (Switzerland)

air-temperature

display_name: air-temperature

precipitation

display_name: precipitation

runoff

display_name: runoff

snow-depth

display_name: snow-depth

watershed-drainage-basins

display_name: watershed-drainage-basins


en:
Dataset (Model input, snow distribution and validation) for the precipitation scaling paper, which should be cited along with the data set citation.
This data is useful for distributed hydrological modelling or other tasks that involve the study of snow distribution and precipitation in the high Alpine.
The format of the data is for Alpine3D (models.slf.ch) model runs but other models could be used, too.
Please cite:
_Vögeli, C., Lehning, M., Wever, N., Bavay M., 2016: Scaling Precipitation Input to Spatially Distributed Hydrological Models by Measured Snow Distribution., Front. Earth Sci. 4: 108. doi: 10.3389/feart.2016.00108._
Dataset is provided as a single zip file.
The archive contains two directories, the valuable distributed snow depth maps for the landscape Davos and the simulation input.
The archive also contains the file: "ReadMeMetadataDataSetPrecipitationScaling" which explains the data structure.

en: snow-distribution snow-cover snow-hydrology snow alpine3d alpine3d-simulations alpine-precipitation

en: Precipitation Scaling Data Set (Vögeli et al., Frontiers)

alpine-precipitation

display_name: alpine-precipitation

snow

display_name: snow

snow-distribution

display_name: snow-distribution

snow-hydrology

display_name: snow-hydrology


en:
During the last 45 years, about 100 people lost their lives in avalanches in the European Alps each year. Avalanche fatalities in settlements and on transportation corridors have considerably decreased since the 1970s. In contrast, the number of avalanche fatalities during recreational activities away from avalanche-secured terrain doubled between the 1960s and 1980s and has remained relatively stable since, despite a continuing strong increase in winter backcountry recreational activities.
Data complementing Figure 2 in:
_"Avalanche fatalities in the European Alps: long-term trends and statistics"_, by Techel, F., Jarry, F., Kronthaler, G., Mitterer, S., Nairz, P., Pavšek, M., Valt, M., and Darms, G.
Data description:
please refer to section 2 (Data and Methods) in the mentioned publication

en: long-term-trends avalanche-accident avalanche-statistics avalanche-fatalities avalanche-accident-statistics

en: Avalanche fatalities in the European Alps (1969/1970 - 2014/2015)

avalanche-accident

display_name: avalanche-accident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

avalanche-statistics

display_name: avalanche-statistics

long-term-trends

display_name: long-term-trends


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 afforestation experiment at the Alpine treeline site Stillberg, Switzerland." The entry can be found under this link -https://www.envidat.ch/dataset/afforestation-stillberg-  and with this DOI 10.16904/envidat.397.

en: afforestation mountain-forest stillberg long-term-experiment treeline

en: Long-term treeline research dataset at Stillberg, Davos

envi

en: Environment

de:
Resource Title: Documentation
    Size: 57344 bytes
    Format: application/msword
    URL: https://www.envidat.ch/dataset/b72cc62e-cf31-4f4c-b89e-eba90f27ac50/resource/545c2ff6-8fdb-4ea0-85a8-49f49d877022/download/documentationstillberg1520160325.doc
    Description: This data documentation is outdated and has been replaced with an updated version (see description).

format: msword

de:
Resource Title: Dataset V1
    Size: 18459904 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/b72cc62e-cf31-4f4c-b89e-eba90f27ac50/resource/f488643a-8f64-4427-8b08-a947c47a1302/download/stillberggis.zip
    Description: This dataset is outdated and has been replaced with an updated version (see description).

de:
Resource Title: Site photo
    Size: 32941 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/b72cc62e-cf31-4f4c-b89e-eba90f27ac50/resource/ca3ffbc8-b692-4f9c-ab49-f1c09fdb4e69/download/stillpic.jpeg
    Description: This site photo is outdated and has been replaced with an updated version (see description).

format: jpeg

afforestation

display_name: afforestation

long-term-experiment

display_name: long-term-experiment

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline

display_name: treeline


en:
This snow depth map was generated 14 January 2015, close to peak of winter accumulation, applying Unmanned Aerial System digital surface models with a spatial resolution of 10 cm. The covered area is 285'000 m2 at the top of Brämabüel, 2490 m a.s.l. covering all expositions. Coordinate system: CH1903LV03.
A detailed description is given here:
Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075-1088, 10.5194/tc-10-1075-2016, 2016.
Abstract:
Detailed information on the spatial and temporal distribution, and variability of snow depth (HS) is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Nowadays, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network is not able to capture the large spatial variability of snow depth in alpine terrain.
Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, such data acquisition is costly, if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand, is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UAS), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Such systems have the advantage that they are comparatively cost-effective and can be applied very flexibly to cover also otherwise inaccessible terrain. In this study we map snow depth at two different locations: a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and b) an exposed location (2500 m a.s.l.) on a peak in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) better than 0.07 to 0.15 m on meadows and rocks and a RMSE better than 0.30 m on sections covered by bushes or tall grass. This new measurement technology opens the door for efficient, flexible, repeatable and cost effective snow depth monitoring for various applications, investigating the worlds cryosphere.

en: uas remote-sensing snow-depth swe snow

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: UAS based snow depth maps Brämabüel, Davos, CH

de:
Resource Title: .tfw file
    Size: 89 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/84db9938-9af5-4ae1-8e30-cb45c61fc274/resource/95509c9f-8a0a-4f7f-a46e-9db9a9c795fa/download/snowdepth_20150414_10cm_reffromsummer_setnull_final.tfw
    Description: coordinates for the .tif raster

de:
Resource Title: HS map Brämabül, 14. April 2015
    Size: 163529181 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/84db9938-9af5-4ae1-8e30-cb45c61fc274/resource/22d008e7-8312-4676-8792-81ed927e4951/download/snowdepth_20150414_10cm_reffromsummer_setnull_final.tif
    Description: 10 cm resolution
15 cm accuracy

remote-sensing

display_name: remote-sensing

swe

display_name: swe

uas

display_name: uas


en: Dataset of manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland. Typical snow profile measurements and observations are included (temperature, density, grain size, grain type, hardness, wetness), following the guidelines of the The International Classification for Seasonal Snow on the Ground (ICSSG) [Fierz, C., Armstrong, R.L., Durand, Y., Etchevers, P., Greene, E., McClung, D.M., Nishimura, K., Satyawali, P.K. and Sokratov, S.A. 2009. The International Classification for Seasonal Snow on the Ground. IHP-VII Technical Documents in Hydrology N°83, IACS Contribution N°1, UNESCO-IHP, Paris].

en: snow-ice-temperature snow-water-equivalent snow-density weisfluhjoch snow-stratigraphy

en: Manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland

de:
Resource Title: README
    Size: 5514 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/0b294122-015c-46bf-b5c5-cc6d0a6f67c1/resource/8b7b0710-a781-41c4-9345-b31a5e93982b/download/readme.txt
    Description: README file giving use metadata.

de:
Resource Title: WFJ Snow Profiles 1999-2014
    Size: 237845 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0b294122-015c-46bf-b5c5-cc6d0a6f67c1/resource/f64d8a9f-36ea-40f6-9874-bc9071050d0a/download/wfjsnowprofiles19992014.zip
    Description: Biweekly manual snow profiles from Weissfluhjoch, Davos, Switzerland.
Version: 2015-09-14T16:25

snow-density

display_name: snow-density

snow-ice-temperature

display_name: snow-ice-temperature

snow-stratigraphy

display_name: snow-stratigraphy

snow-water-equivalent

display_name: snow-water-equivalent

weisfluhjoch

display_name: weisfluhjoch


en:
A landslide testsite dataset related to pore water pressure perturbations on the stability of unsaturated silty sand slopes leading to the initiation and propagation of the shear deformations and eventual rapid mass movements. This project was initiated and led by the Institute of Geotechnical Engineering (IGT) of the Swiss Federal Institute of Technology (ETH Zurich) and was incorporated in a Swiss national (TRAMM) and a European Union (SafeLand) multidisciplinary research project. Field site: The experimental slope is 7.5 m wide by 35 m long, located in the Swiss lowlands on an east facing slope over-looking the river Rhine, at an altitude of ~ 350 masl. Originally there were forestry covertures of circa 80%, heights of 5-20 m. Shrubs up to 1-5 m high and a free herb layer covered ~ 50% of the surface. The average gradient was determined to be from 38° to 43° with a slightly concave surface. The underlying rock consists mainly of Molasse, which is formed by alternate layers of sea deposits under the Tethys Sea (Seawater Molasse) and land deposits (Freshwater Molasse). Several augured samples, as well as an outcrop of the bedrock about 20 m above the selected field, revealed horizontal layering of fine grained sand- and marlstone at the test site. The sandstone was later proven to be highly permeable and fissured. Grain-size distributions were determined and the soil was classified as medium-low plasticity silty sand. Site instrumentation:Measurements of soil suction, groundwater level, soil volumetric water content, rain intensity and soil temperature were taken and combined with geophysical monitoring using Electrical Resistance Tomography (ERT) and investigations into subsurface flow by means of tracer experiments. Deformations were monitored during the experiment, both on the surface via photogrammetrical methods and within the soil mass, using a flexible probe equipped with strain gauges at different points and two axis inclinometers on the top and acoustic sensors. Instruments were installed mainly in three clusters at depths of 15, 30, 60, 90, 120, and 150 cm below the ground surface over the slope, including jet-fill tensiometers, TDRs, Decagon TDRs, piezometers, soil temperature sensors, deformation probes, earth pressure cells, acoustic sensors and rain gauges. A ring-net barrier (provided by Geobrugg AG) was set up at the foot of the slope to protect the road. Experiments: A sprinkling experiment was carried out in September 2008 to investigate the hydrological and mechanical response of the slope (Experiment 1), followed by a second one to trigger a landslide in March 2009 (Experiment 2).
Publications
1. Lehmann, P., F. Gambazzi, B. Suski, L. Baron, A. Askarinejad, S. M. Springman, K. Holliger, and D. Or (2013), Evolution of soil wetting patterns preceding a hydrologically induced landslide inferred from electrical resistivity survey and point measurements of volumetric water content and pore water pressure, Water Resour. Res., 49, 7992–8004, doi:[10.1002/2013WR014560](http://dx.doi.org/10.1002/2013WR014560).
2. Springman, S. M., Kienzler, P., Casini, F., & Askarinejad, A. (2009). Landslide triggering experiment in a steep forested slope in Switzerland. In 17th International Conference of Soil Mechanics and Geotechnical Engineering, Alexandria, Egypt (pp. 1698-1701). doi: [10.3233/978-1-60750-031-5-1698](http://dx.doi.org/10.3233/978-1-60750-031-5-1698)

en: landslides pore-water cces landslide-testsite pressure-perturbations tramm

en: TRAMM project Ruedlingen experimental landslide dataset, Switzerland

cces

display_name: cces

landslide-testsite

display_name: landslide-testsite

landslides

display_name: landslides

pore-water

display_name: pore-water

pressure-perturbations

display_name: pressure-perturbations

tramm

display_name: tramm


en:
The article "EnviDat Supports Open Science" originally appeared in WSLintern No. 3 (2020), page 14-15 and it is republished here with permission from the WSLintern editorial team. It contains guidelines for WSL scientists about the main issues behind Open Science and how to pragmatically approach the complexities of doing Open Science with EnviDat’s support.
License: This article is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

en: wsl envidat juypter-notebooks research-data-management open-science

en: EnviDat Supports Open Science

envidat

display_name: envidat

juypter-notebooks

display_name: juypter-notebooks

open-science

display_name: open-science

research-data-management

display_name: research-data-management

wsl

display_name: wsl


en:
Swiss National Forest Inventory. Results of the fourth survey 2009–2017.
The collection of data for the fourth National Forest Inventory (NFI) was carried out from 2009 to 2017, on average eight years after the third survey. The findings about state and development of Swiss forests are described and explained in detail. The report is structured according to the European criteria and indicators for sustainable forest management, namely: forest resources, health and vitality, wood production, biological diversity, protection forest and social economy. Finally, conclusions about sustainability are drawn based on the NFI findings.
Keywords: forest area, growing stock, increment, yield, forest structure, forest condition, timber production, biodiversity, protection forest, recreation, sustainability, results National Forest Inventory, Switzerland
Schweizerisches Landesforstinventar. Ergebnisse der vierten Erhebung 2009–2017.
In den Jahren 2009 bis 2017 fanden die Erhebungen zum vierten Schweizerischen Landesforstinventar (LFI) statt,
im Durchschnitt acht Jahre nach der dritten Erhebung. Die Resultate über den Zustand und die Entwicklung des Schweizer Waldes werden umfassend dargestellt und erläutert. Der Bericht ist thematisch strukturiert nach den europäischen Kriterien und Indikatoren zur nachhaltigen Bewirtschaftung des Waldes: Waldressourcen, Gesundheit und Vitalität, Holzproduktion, biologische Vielfalt, Schutzwald und Sozioökonomie. Eine Bilanz zur Nachhaltigkeit, basierend auf LFI-Ergebnissen, schliesst die Publikation ab.
Keywords: Waldfläche, Holzvorrat, Zuwachs, Nutzung, Waldaufbau, Waldzustand, Holzproduktion, Biodiversität, Schutzwald, Erholung, Nachhaltigkeit, Ergebnisse Landesforstinventar, Schweiz
Content license: All rights reserved. Copyright © 2020 by WSL, Birmensdorf.

en: nfi forest 2009-2017 national-forest-inventory lfi

de:
Resource Title: ISBN: 978-3-905621-60-0
    Size: 65939779 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/18f5aeda-93f3-422d-9aa3-41724378bbd2/resource/a0ee1a9b-c2e1-4732-8a5d-487ae75611b4/download/lfi4_de_web_200603.pdf
    Description:

de:
Resource Title: Corrigendum / Korrigendum
    Size: 519543 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/18f5aeda-93f3-422d-9aa3-41724378bbd2/resource/18f37116-75eb-4bad-b6b7-d85bae72e1e0/download/korrigendum_lfi4_de_tab_155.pdf
    Description:

de:
Resource Title: Registration in DORA
    Size: 1 bytes
    Format: No Info
    URL: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:23454
    Description:

forest

display_name: forest

lfi

display_name: lfi

national-forest-inventory

display_name: national-forest-inventory

nfi

display_name: nfi


en:
Carabidae data from all historic up to the recent projects (21.10.2019) of WSL, collected with various methods in forests of different types.
Version 2 ('FIDO_global_extract 2019-11-22_18-11-24 WSL-Forest-Carabidae') contains additional data field PROJ_FALLENBEZEICHNUNG.
Data are provided on request to contact person against bilateral agreement.

en: coleoptera running-beetles forest insects trapping arthropoda carabidae

en: Carabid beetles in forests

envi

en: Environment

de:
Resource Title: FIDO_global_extract 2019-10-21_15-36-33 WSL-Forest-Carabidae.sql
    Size: 7054 bytes
    Format: application/x-sql
    URL: https://www.envidat.ch/dataset/9e84cac9-f613-48ee-b784-4839e2e4d66b/resource/c1ac034b-97ff-40af-bf44-7980f4862773/download/fido_global_extract-2019-10-21_15-36-33-wsl-forest-carabidae.sql
    Description: Data query used on Fauna Database to retrieve the submitted data.

de:
Resource Title: FIDO_global_extract 2019-11-22_18-11-24 WSL-Forest-Carabidae.sql
    Size: 7228 bytes
    Format: application/x-sql
    URL: https://www.envidat.ch/dataset/9e84cac9-f613-48ee-b784-4839e2e4d66b/resource/2ed9a413-7520-49ce-88fd-4558f80ff952/download/fido_global_extract-2019-11-22_18-11-24-wsl-forest-carabidae.sql
    Description: SQL query used to extract the data from fauna database.

de:
Resource Title: FIDO_global_extract 2019-11-22_18-11-24 WSL-Forest-Carabidae.txt
    Size: 26421343 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/9e84cac9-f613-48ee-b784-4839e2e4d66b/resource/31809c51-86a7-4d35-8b2f-8979c105598f/download/fido_global_extract-2019-11-22_18-11-24-wsl-forest-carabidae.txt
    Description: Tab-delimited data of the according sql query.

de:
Resource Title: FIDO_global_extract 2019-10-21_15-36-33 WSL-Forest-Carabidae.txt
    Size: 26257912 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/9e84cac9-f613-48ee-b784-4839e2e4d66b/resource/59e9fccd-cc64-41c4-80a4-25f947d3a0d6/download/fido_global_extract-2019-10-21_15-36-33-wsl-forest-carabidae.txt
    Description: Data extract in TAB-delimted format. First row is header, first column is counter.

arthropoda

display_name: arthropoda

carabidae

display_name: carabidae

coleoptera

display_name: coleoptera

insects

display_name: insects

running-beetles

display_name: running-beetles

trapping

display_name: trapping


en:
The present dataset is part of the published scientific paper Hersperger, A.M., Bürgi, M., Wende, W., Bacău, S. and Grădinaru, S.R., 2020. Does landscape play a role in strategic spatial planning of European urban regions?. Landscape and Urban Planning, 194, p.103702.
The goal of this research was to assess the role of landscape in contemporary strategic spatial planning.  In order to assess the role of “landscape” in the strategic spatial plans, we focused on how plans took advantage of landscape’s integrative power, how plans are based on knowledge on functioning of landscape systems, and how plans show the contribution of landscapes to human well-being. For each aspect, a number of items (detailed in Table 1 of the paper) were selected to assist the assessment.
This study is based on content analysis of the strategic spatial plans of 18 European urban regions. The strategic spatial plans were retrieved from the planning authorities’ websites.  The cases study regions as well as the analyzed strategic spatial plans are presented in Table 2 of the paper.
The authors developed a protocol containing  28 items, out of which 16 were directly derived from information presented in Table 1. As a result, we provide the following outputs:
•	Protocol_items.docx – freely available - Detailed description of all the protocol items used to conduct the analysis.
•	Coding results.xlsx – available on request - Results of the coding procedure. Data were used to create Figures 2, 3, 4, 5, 6 and to qualitatively present the results in the research paper.

en: landscape-principles green-infrastructure plan-evaluation strategic-plan governance

envidat

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

en: Landscape in contemporary strategic spatial plans of European Urban regions

de:
Resource Title: Coding results
    Size: 3846 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ce7486ec-fd91-479c-87a3-7c44b9d0178d/resource/724ff9bb-68ef-4a5b-bcae-2278b1347261/download/coding-results.csv
    Description: o	Results of the coding procedure. Data were used to create Figures 2, 3, 4, 5, 6 and to qualitatively present the results in the research paper.

format: CSV

media_type: text/csv

de:
Resource Title: Protocol_items
    Size: 211462 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/ce7486ec-fd91-479c-87a3-7c44b9d0178d/resource/b59155ed-45d2-42ac-b9da-285808ee6c25/download/protocol_items_landscape.pdf
    Description: o	Detailed description of all the protocol items used to conduct the analysis and the way each question was coded

governance

display_name: governance

green-infrastructure

display_name: green-infrastructure

landscape-principles

display_name: landscape-principles

plan-evaluation

display_name: plan-evaluation

strategic-plan

display_name: strategic-plan


en:
This folder contains documents relevant to the project step Konzeptionelles Systemmodell. It specifically contains the following documents:
1. 0201_Konzeptionelles Systemmodell_20221027: This document is the final version of the Konzeptionelles Systemmodell. The underlying structure of the Konzeptionelles Systemmodell is explained in chapter 4.4 of the document 0202_Masterarbeit Elena Siegrist_UniBern_Herbstsemester 2022 also deposited in this folder. The document contains 3 sheets. The sheet "Bausteine" shows the different possible options for table columns of the type Bausteine (see chapter 4.4 of Masterarbeit), the sheet "Direkte Effekte" contains identified direct impact pathways and the sheet "Indirekte Effekte" contains identified indirect impact pathways.
2. 0202_Masterarbeit Elena Siegrist_UniBern_Herbstsemester 2022: This document is the Master Thesis of Elena Grace Siegrist submitted to and accepted by the University of Bern in the Autumn Semester 2022. Chapter 4.4 of the document explains the underlying structure of the Konzeptionelles Systemmodell.
3. 0203_Literaturverzeichnis_konzeptionelles Systemmodell_20221026: This document lists all literature and documents cited in the Konzeptionelle Systemmodell.

en: landscape-change climate-change scenarios policy-action qualitative-research

de: EnviDat

en: Data Konzeptionelles Systemmodell

envi

de: Umwelt

de:
Resource Title: 0202_Masterarbeit Elena Siegrist_UniBern_Herbstsemester 2022
    Size: 20498856 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/63cdd109-d84d-4664-b9c8-cabff7206265/resource/59a6d667-fa1c-48c9-b219-56e6b60c0e6a/download/0202_masterarbeit-elena-siegrist_unibern_herbstsemester-2022.pdf
    Description:

de:
Resource Title: 0203_Literaturverzeichnis_konzeptionelles Systemmodell_20221026
    Size: 135744 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/63cdd109-d84d-4664-b9c8-cabff7206265/resource/a0b05adc-77b0-4c7e-bf7b-d073974e2cd8/download/0203_literaturverzeichnis_konzeptionelles-systemmodell_20221026.pdf
    Description:

de:
Resource Title: 0201_Konzeptionelles Systemmodell_20221027
    Size: 51597723 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/63cdd109-d84d-4664-b9c8-cabff7206265/resource/6943041d-18c9-4ef4-b114-1269f9d78811/download/0201_konzeptionelles-systemmodell_20221027.xlsx
    Description:

climate-change

display_name: climate-change

landscape-change

display_name: landscape-change

policy-action

display_name: policy-action

qualitative-research

display_name: qualitative-research

scenarios

display_name: scenarios


en:
This dataset contains the spatial layers showing future land change pathways in Europe between 2015 and 2050, as simulated by the CLUMondo model and according to the Agricultural Futures Framework (AFF) scenarios.
Three scenarios are included:
- Land for Food and Land for Nature (LFLN)
- Land as Culture (LaC)
- Land for Society (LfS)

en: land-use-modelling pathways agriculture scenarios land-change

en: AFF agricultural land change scenarios in Europe 2015-2050

de:
Resource Title: AFF_agricultural land_change scenarios_Europe_2015_2050.zip
    Size: 3851250 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/15ae8f00-310e-4cee-95ed-d00f0aa25dbe/resource/a8d3393e-178f-43a7-9538-1437b0afd8b3/download/aff_agricultural-land_change-scenarios_europe-2015_2050.zip
    Description: This dataset contains the spatial layers showing future land change pathways in Europe between 2015 and 2050, as simulated by the CLUMondo model according to the Agricultural Futures Framework (AFF) scenarios.

de:
Resource Title: ReadMe.pdf
    Size: 87640 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/15ae8f00-310e-4cee-95ed-d00f0aa25dbe/resource/573e45b3-27b1-4139-b61b-06c3adc8871e/download/readme.pdf
    Description:

agriculture

display_name: agriculture

land-change

display_name: land-change

land-use-modelling

display_name: land-use-modelling

pathways

display_name: pathways


en:
This dataset includes data on species richness of vascular plants and bryophytes in 55 wetlands of the canton of Zürich (Switzerland) as well as recent and historic data on the area and connectivity of these 55 wetlands and was used for the paper Jamin A., Peintinger M., Gimmi U., Holderegger R., Bergamini A. (2020) Evidence for a possible extinction debt in Swiss wetland specialist plants. Ecology and Evolution.
Species richness data are available for vascular plants and bryophytes. The field survey was carried out between June 5 and August 10, 2012. The survey covered all wetland (fen) types in the canton of Zürich. For data collection, at least half a day per wetland was spent searching for species. Within each wetland all different vegetation types were covered until no new species were found to get as complete species lists as possible. In the Excel file information on species richness of the following groups is provided: (1) all vascular plant species; (2) wetlands specialists among vascular plants; (3) generalists, which were all non-specialist vascular plant species; (4) short-lived vascular plant specialists; (5) long-lived vascular plant specialists; (6) short-lived vascular plant generalists; (7) long-lived vascular plant generalists; (8) bryophyte species. Specialist vascular plant species included all characteristic species listed in Appendix 1a of the wetland inventory of Switzerland (BUWAL, 1990).
Based on the data of Gimmi et al. (2011), the area of all wetlands in 1850, 1900, 1950 and 2000 were determined as well as the wetland area within buffers 2km in radius with the center of the wetland as starting point. These data are also provided in the Excel sheet.
Moreover, for each wetland mean indicator values according to Landolt et al. (2010) and the standard deviation of these indicator values based on presence-absence data of vascular plants were calculated and are provided in Excel sheet. Indicator values for temperature, light availability, moisture, acidity, nutrients, amount of humus and soil aeration were considered.

en: bryophytes species-richness vascular-plants habitat-area nature-conservation habitat-fragmentation extinction-debt wetlands

en: Wetlands of the canton of Zürich (Switzerland): Data on species richness and recent and historic area and connectivity of 55 fens

bryophytes

display_name: bryophytes

extinction-debt

display_name: extinction-debt

habitat-area

display_name: habitat-area

habitat-fragmentation

display_name: habitat-fragmentation

nature-conservation

display_name: nature-conservation

species-richness

display_name: species-richness

vascular-plants

display_name: vascular-plants

wetlands

display_name: wetlands