maintainer: EnviDat Support

en: environmental---history historical-carthography switzerland wetlands ecology environmental--policy

en: Wetlands 1850 - 2010 (shapefiles)

en:
 History of wetlands - GIS-Layers
 Location of wetlands based on signatures in topographic maps
* Basis 1850: original measuring table sheets Dufour created between the years 1834 and 1863.
* Basis 1900/ Basis 1950: The Siegfried maps were updated and published at regular intervals between 1870 and 1949. This long period of time made it possible to reconstruct wetlands for two periods based on the Siegfried Maps: the first edition (hereinafter referred to as "1900") and the last edition ("1950").
* Basis 2010: Map sheets from the National Map from 2006 to 2011 were used for the most recent time period of the reconstruction.
 Location of wetlands due to reconstructions
The reconstruction **must not** be interpreted in the sense of a surface-accurate separation, but shows without claim to location accuracy the approximate extent of the areas that would have corresponded to the mapping criteria for wetlands used in today's topographic maps around 1850, 1900 and 1950. The basics can be found in Stuber & Bürgi 2019, chapter 5.4.

en:
Naturally, large parts of the Swiss Plateau are characterised by wetlands
and meandering rivers. That this is no longer the case today is the result
of centuries of efforts to obtain dry land. But how did this process take
place? What were the relevant actors and what were their motivations? And
what can be said about the ecological consequences of this development?

In a research project on the history of wetlands in Switzerland since 1700,
we conducted (a) a historical analysis of the development of land use in
wetlands and the actors involved, (b) a historical-cartographic
reconstruction of wetland extent since 1850 and (c) an evaluation of
ecological effects of changes in wetlands on various organisms groups.

The series of GIS layers on wetland history stem from the second part of
the project. The area reconstruction is based on digitized and homogenized
signatures from national map series, as they have been available since
about 1850. Details about the digitalization process and the homogenization
procedures applied ("Rekonstruktionen") are included in Stuber & Bürgi
2019.

Book Citation:
 > Stuber M, Bürgi M (2019) Vom «eroberten Land» zum Renaturierungsprojekt. Geschichte der Feuchtgebiete in der Schweiz seit 1700. "Bristol Schriftenreihe", Band 59. Haupt Verlag, Bern, Stuttgart, Wien. 262 Seiten.

ecology

display_name: ecology

environmental---history

display_name: environmental---history

environmental--policy

display_name: environmental--policy

historical-carthography

display_name: historical-carthography

switzerland

display_name: switzerland

wetlands

display_name: wetlands

en: History of wetlands in Switzerland since 1850


regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

fr: gestion-des-ressources-en-eau reseau-de-mesure analyse-de-leau eau-de-surface source cascade eau-substance surveillance-biologique ecosysteme roche qualite-de-leau ressource-en-eau eau-propre-a-la-consommation surveillance-de-leau fond-de-leau extraction-deau eaux-geographie zonage energie percolation diversite-biologique eaux-interieures environnement eaux-souterraines energie-hydraulique organisme-aquatique

de: wasserbewirtschaftung messstellennetz wasseruntersuchung oberflachengewasser quelle wasserfall wasser biomonitoring okosystem fels wassergute wasserressourcen gebrauchswasser wasseruberwachung gewassersohle wasserentnahme gewasser zoneneinteilung energie versickerung artenvielfalt binnengewasser umwelt grundwasser wasserkraft wasserorganismen

label: geocat.ch permalink

state: active

type: dataset

fr: Service de consultation (WMS)

de: Darstellungsdienst (WMS)

format: WMS

fr: Le service représente les données de base du canton de Berne selon la géocatégorie I conforme à eCH-0166. Il comprend les géoproduits suivantes: * Gisements d'eau souterraine en roches meubles * Qualité des cours d'eau * Zones d'infiltration * Prélèvements d’eau dans les eaux de surface * Habitat des sources * Bases de la planification des revitalisations * Planification stratégique des revitalisations * Stratégie d'utilisation de l'eau

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie I gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Grundwasservorkommen in Lockergestein * Qualität der Oberflächengewässer * Versickerungszonen * Wasserentnahmen aus Oberflächengewässern * Lebensraum Quellen * Revitalisierungsplanung Grundlagen * Strategische Revitalisierungsplanung * Wassernutzungsstrategie

format: SERVICE

fr: Office de l'information géographique du canton de Berne

de: Amt für Geoinformation des Kantons Bern

fr: L'Office de la géoinformation est le centre de compétence pour l'information spatiale dans le canton de Berne. Les géodonnées cantonales peuvent être utilisées gratuitement, sous réserve des conditions d'utilisation. Le Géoportail du canton de Berne est le point d'entrée central pour les cartes interactives, les géodonnées et les géoservices de l'administration cantonale.

de: Das Amt für Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Bern. Die kantonalen Geodaten sind unter Einhaltung der Nutzungsbedingungen kostenlos nutzbar. Das Geoportal des Kantons Bern ist der zentrale Einstiegspunkt für interaktive Karten, Geodaten und Geodienste der kantonalen Verwaltung.

political_level: canton

capacity: public

type: organization

approval_status: approved

value: Bern-Kt - Geocat Harvester

fr: Hydrographie 03 (WMS)


maintainer: Leo Gallus Bont

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

en: View video on youtube!

en: Herunterladen des DHM mit SwissGeoDownloader

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

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

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

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

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

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

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

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geo-downloader

display_name: swiss-geo-downloader

swiss-geodata

display_name: swiss-geodata

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

key: guid

key: uri

value: Envidat Harvester

en: Seilaplan Tutorial: DTM download with SwissGeoDownloader


ener

fr: Énergie

de: Energie

en: Energy

it: Energia

de: bauwerk energiespeicherung wasserversorgung energieversorgung erdgas wasser abwasserbeseitigung erdwarme gasversorgung grundwassertrager elektrizitatsversorgung abwasser energie kataster grundwasserentnahme hochspannungsleitung grundwasser grundwasserschutz

fr: Service de téléchargement (WFS)

de: Downloaddienst (WFS)

format: WFS

fr: Le service représente les données de base du canton de Berne selon la géocatégorie Q conforme à eCH-0166. Il comprend les géoproduits suivantes: * Cadastre des zones de desserte * Sondes géothermiques * Conduites de gaz * Procédure de garantie d’implantation des conduites publiques (GICP) * Utilisation des eaux souterraines

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie Q gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Kataster der Netzgebiete * Erdwärmesonden * Gasleitungen * Öffentlich-rechtliche Sicherungen von öffentlichen Leitungen (SöL) * Grundwassernutzung

fr: Approvisionnement, élimination et communication 01 (WFS)

de: Versorgung, Entsorgung und Kommunikation 01 (WFS)


photogrammetric-drone-data-schurlialp

maintainer: Yves Bühler

title_for_slug: photogrammetric-drone-data-schurlialp

en: dsm photogrammetry uav drone-data orthophoto wingtra

en: Data Access

en:
- 10 cm DSM
- 10 cm HS
- 3 cm orthophoto
- original RGB images
- Agisoft Metashape Processing Report

All of the products are also available as a cloud optimized geotiff.

en: The data was collected on 16.04.2021 and on 28.05.2021 with a Wingtra Gen II and a Sony RX1 II RGB sensor to obtain snow depth and distribution data. Following the data collection, the data was processed with Agisoft Metashape. A 10cm DSM, a 10cm snow depth raster, a 3mm orthophoto and the original drone images are available for download.

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

en: Photogrammetric Drone Data Schürlialp


media_type: text/csv

format: CSV

mimetype: text/csv

en:
Attention: this data is not updated after 2022 anymore.
This dataset contains the statistics on the number of avalanche fatalities per **calendar year** in Switzerland. The data collection commences with the beginning of the year 1937. After the completion of a hydrological year, which is the standard way avalanche fatalities are summarized in Switzerland and ends on the 30th of September, the new data is appended to the existing dataset.
If you require annual statistics per hydrological year, please download the data from here: [https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936]
The following information is contained (by column and column title):
 - year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste, away from open and secured ski runs)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)
The definitions for these four categories, as described in the guidelines to the avalanche accident database are:
tour:
activities include back-country ski, snowboard or snow-shoe touring
offpiste:
access from ski area, generally from the top of a skilift with short hiking distances
transportation.corridors (Techel et al., 2016):
people travelling or recreating on open or temporarily closed transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)
buildings (Techel et al., 2016):
people inside or just outside buildings, and workers on high alpine building sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

en: Number of avalanche fatalities per calendar year in Switzerland since 1937


bauinventar

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

regi

en: Regions and cities

title_for_slug: bauinventar

fr: batiment inventaire-environnement monument-historique bien-culturel

de: gebaude inventar baudenkmal kulturgut

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

format: ZIP

fr: Le recensement architectural du canton de Berne décrit et évalue les monuments historiques (objets, ensembles bâtis ou structurés). Il constitue une base solide pour le travail pratique du Service des monuments historiques et pour la recherche scientifique. En publiant le recensement architectural, le Service des monuments historiques fournit aux communes et aux propriétaires, mais aussi à la population, une vue d’ensemble du patrimoine histo-rique du canton. Les données du géoportail sont un extrait actuel et juridiquement non contraignant sur le plan du recensement architectural.. La version légalement valide des recensements architecturaux sont disponibles auprès des communes concernées, dans les préfectures, au Ser-vice des monuments historiques et à l’Office des affaires communales et de l’organisation du territoire. Depuis 2010, toutes les communes du canton ont leur propre recensement. Le recensement architectural des quartiers de la ville de Berne a, quant à lui, été élaboré par le Service des monuments historiques de la ville de Berne. Il est également disponible en ligne (en allemand) : Bauinventar Stadt Bern (https://bauinventar.bern.ch/) Le Service cantonal des monuments historiques révise régulièrement le recensement architectural. Toute modification doit d’abord être mise à l’enquête publique, puis mise en vigueur par une décision de l’Office de la culture du canton de Berne, avant d’être reportée dans le géoportail. Vous trouverez de plus amples informations sur le Service des monuments historiques du canton de Berne ici : Service des monuments historiques (https://www.kultur.bkd.be.ch/fr/start/themen/denkmalpflege.html) et Recensement architectural en ligne (https://www.kultur.bkd.be.ch/fr/start/themen/denkmalpflege/baudenkmaeler-im-kanton-bern/bauinventar/bauinventar-online.html)

de: Das kantonale Bauinventar erfasst, beschreibt und bewertet Baudenkmäler (Einzelobjekte sowie Bau- und Strukturgruppen). Es bildet eine fundierte Grundlage für die praktische Arbeit der Denkmalpflege und für die wissenschaftliche Forschung. Mit dem Bauinventar stellt die Denkmalpflege nicht nur Gemeinden und Grundeigentümerinnen und -eigentümern, sondern auch der breiten Öffentlichkeit eine qualifizierte Gesamtschau des historischen Baubestandes im Kanton zur Verfügung. Die Daten im Geoportal präsentieren einen aktuellen, aber rechtlich nicht verbindlichen Datenauszug aus dem Bauinventar. Die rechtlich verbindliche Ausgabe kann auf den Gemeindeverwaltungen und den Regierungsstatthalterämtern sowie bei der Denkmalpflege und dem Amt für Gemeinden und Raumordnung eingesehen werden. Seit 2010 liegen die Bauinventare für alle Gemeinden des Kantons vor. Die Quartierinventare der Stadt Bern werden durch die städtische Denkmalpflege bearbeitet. Sie sind online zugänglich: Bauinventar Stadt Bern (bauinventar.bern.ch) Das Bauinventar wird durch die kantonale Denkmalpflege regelmässig revidiert. Änderungen müssen zuerst zur öffentlichen Einsichtnahme aufgelegt und per Verfügung durch das kantonale Amt für Kultur in Kraft gesetzt werden, bevor sie im Geoportal abgebildet werden. Weitere Informationen zur Denkmalpflege des Kantons Bern finden Sie hier: Denkmalpflege (https://www.kultur.bkd.be.ch/de/start/themen/denkmalpflege.html) und Bauinventar Online (https://www.kultur.bkd.be.ch/de/start/themen/denkmalpflege/baudenkmaeler-im-kanton-bern/bauinventar/bauinventar-online.html)

spatial: Kanton Bern (erweitert)

fr: Le recensement architectural

de: Bauinventar


maintainer: Chunhong Zhao

en: urban-morphology austin landscape land-use land-dynamics

en: Land use dynamics in Austin since 1992

en: The present dataset is part of the published scientific paper Zhao C, Weng Q, Hersperger A M. Characterizing the 3-D urban morphology transformation to understand urban-form dynamics: a case study of Austin, Texas, USA. Landscape and urban planning, 2020, 203:103881. The overall objective of this paper is to understand urban form dynamics in the Austin metropolitan area for the periods 2006–2011 and 2011–2016. The study also aims to understand to what extent the changes in the built environment (in terms of ‘efficient growth’ versus ‘inefficient growth’) from the 1990s to 2016 in the Austin metropolitan area corresponded with ‘compact and efficient growth’ planning policy documents. The UMT distribution can be found in the paper. The area of transitioning UMT was provided in Table 2 and Table 3 can be found in the Appendix of the paper. A protocol was developed to perform the content analysis of the strategic plans and gather the data. The detailed list of protocol items can be found in Appendix B of the paper. This study demonstrates the advantage of applying Lidar data to characterize 3-D urban morphology type (UMT) transition and understand its dynamics, which helps develop a comprehensive understanding of the urbanization process and provides a tool for planning intentions and policies evaluation on urban development over time. The UMT maps can be found in Appendix A of the paper. The Lidar point datasets and the 30 × 30 m National Land Cover Database (NLCD) are the two main data sources of UMT mapping. Lidar datasets were gathered from different projects that had been conducted and collected by state agencies and other organizations between 2007 and 2017. Table A1 in the appendix in the paper shows the accuracies and acquisition parameters of the Lidar projects from 2007 to 2017. Land use/cover dynamics in Austin metropolitan area dataset provides Land use/cover patterns in the years 1992, 2001, 2004, 2006, 2008, 2011, 2013, 2016 with a spatial resolution of 30 meters. Since NLCD 1992 used a different classification system for the urban land classes, we first reclassified the NLCD 1992 using a customized Arcpy package.

austin

display_name: austin

land-dynamics

display_name: land-dynamics

land-use

display_name: land-use

landscape

display_name: landscape

urban-morphology

display_name: urban-morphology

en: Land use/cover dynamics in Austin metropolitan area since 1992


maintainer: Armin Sigmund

en: antarctica evaporation snow-sublimation lagrangian-analysis backward-trajectories isotopic-distillation stable-water-isotopes

en: Data

en: Modeled data including the data shown in the figures of the related research article

en: Readme

media_type: text/plain

en: Meta data

format: TXT

en: Model code

media_type: application/zip

en: Model Sublimation and Model Air Parcel (python scripts)

en: Python scripts for data visualization

en: Scripts for generating the figures of the related research article and generating the data files (csv) from the model output

en:
 Summary

This data set contains Python programming code and modeled data discussed in a related research article. We developed a simple isotope model to study the drivers of the particularly depleted vapour isotopic composition measured on the ship of the Antarctic Circumnavigation Expedition close to the outlet of the Mertz glacier, East Antarctica, in the 6-day period from 27 January 2017 to 1 February 2017. The model considers the stable water isotopologues H2(16O), H2(18O), and HD(16O). It uses data from the ERA5 reanalysis product with a spatial resolution of 0.25° x 0.25° (Hersbach et al., 2018) and 10-day backward trajectories for the location of the ship, published by Thurnherr et al. (2020a). Our data set includes the model code, Python scripts for visualizing the results, and data produced by the model including the results shown in the figures of the related research article. Here, we summarize the most important model characteristics while further details can be found in the readme.txt file and the related research article including its supporting information.

 Main model characteristics

The modeling approach consists of two steps called *Model Sublimation* and *Model Air Parcel*. The former estimates the isotopic compositions of the snow and sublimation flux across the Antarctic Ice Sheet using an Eulerian frame of reference while the latter models the vapour isotopic composition and specific humidity along air parcel trajectories using a Lagrangian frame of reference. The isotope effects of most phase changes are represented by equilibrium fractionation. Only for ocean evaporation, kinetic fractionation is additionally taken into account (original Craig-Gordon formula). For snow sublimation, two assumptions are tested: *Run E* assumes that sublimation is associated with equilibrium fractionation while *Run N* assumes that sublimation occurs without isotopic fractionation.

 Model Sublimation
Model Sublimation uses a simple one-dimensional mass-balance approach in each grid cell, considering snow accumulation due to snowfall and vapour deposition and snow ablation due to sublimation. The snowpack is represented by 100 layers of equal thickness (e.g., 1 cm) and density (350 kg m-3). The isotopic composition of snowfall is parameterized by generalizing a site-specific, empirical relationship between the daily mean air temperature and snowfall isotopic composition. In the case of vapour deposition, Model Sublimation assumes equilibrium fractionation and estimates the isotopic composition of the atmospheric vapour as the average value for two idealized situations: (i) locally sourced vapour which has the same isotopic composition as the sublimation flux; (ii) non-locally sourced vapour in isotopic equilibrium with snowfall. Model Sublimation is run with a time step of 1 h, independently of Model Air Parcel.

 Model Air Parcel
Every hour, an ensemble of trajectories arrives at different heights in the ABL above the ship. For each of these trajectories, we consider an air parcel with a constant volume of 1 x 1 x 1 m3. The air parcels are initialized at the first suitable time when the trajectories are located in the ABL, either over the ice-free ocean in conditions of evaporation or over snow (Antarctic Ice Sheet or sea ice). Subsequently, the masses of the water isotopologues in the air parcels are simulated with a time step of 3 h, considering vapour uptake or removal due to the moisture flux at the snow or liquid ocean surface (only if the parcel is in the ABL) and cloud/precipitation formation (if the saturation specific humidity is reached). Sea ice is taken into account in a very simplified way. We represent the sea ice by grid cells with a sea-ice cover of more than 90% and assume the isotopic composition of the sublimation flux to be identical to that in the nearest grid cell of the Antarctic Ice Sheet. The isotopic composition of the sublimation flux is taken from Model Sublimation whereas the isotopic composition of the vapour deposition flux (over snow) and condensation flux (over ice-free ocean) is simulated assuming an isotopic equilibrium with the air parcel. Isotope effects of cloud/precipitation formation are represented using the classic Rayleigh distillation model with equilibrium fractionation, where the cloud water is assumed to precipitate immediately after formation.

 References

Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horanyi, A., Munoz Sabater, J.,... others (2018). *ERA5 hourly data on single levels from 1979 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS)*. doi: 10.24381/cds.bd0915c6

Thurnherr, I., Wernli, H., & Aemisegger, F. (2020a). *10-day backward trajectories from ECMWF analysis data along the ship track of the Antarctic Circumnavigation Expedition in austral summer 2016/2017*. Zenodo. doi: 10.5281/zenodo.4031705

antarctica

display_name: antarctica

backward-trajectories

display_name: backward-trajectories

evaporation

display_name: evaporation

isotopic-distillation

display_name: isotopic-distillation

lagrangian-analysis

display_name: lagrangian-analysis

snow-sublimation

display_name: snow-sublimation

stable-water-isotopes

display_name: stable-water-isotopes

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Modeled Isotopic Composition of Water Vapour Along Air Parcel Trajectories in the Antarctic


disdrometer-data-gotschnagrat

title_for_slug: disdrometer-data-gotschnagrat

en: raclets hydrometeors visibility disdrometer precipitation

en: Disdrometer Data Gotschnagrat

en: The zip folder contains one netCDF file per day for Gotschnagrat from February 11 to March 27 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Gotschna_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

mimetype: application/zip

en: A laser optical disdrometer (Parsivel² , OTT Hydromet) was deployed at Gotschnagrat (LON: 9.849, LAT: 46.859) to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms. The dataset contains information on precipitation amount and type for the period of February 11 to March 27 2019 at Gotschnagrat.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility

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: stable-water-isotopes geochemical-solutes spatially-distributed-sampling precipitation stream-water

format: XLS

en: The dataset contains daily measurements of volumes, isotopes and solutes of stream water as well as precipitation measured several locations; meteorological variables are added. Date: 18.07.2019

en:
This dataset contain measurements of solute and stable water isotopes in stream water and precipitation in the Alp catchment and two of its tributaries (between 2015 -2018) . The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l. The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (precipitation rates, discharge) at daily intervals from several sampling locations.
An updated version of the isotope dataset is available here: https://www.doi.org/10.16904/envidat.242

geochemical-solutes

display_name: geochemical-solutes

spatially-distributed-sampling

display_name: spatially-distributed-sampling

stream-water

display_name: stream-water

en: Daily data of solute and stable water isotopes in stream water and precipitation in the Alp catchment, Central Switzerland


dischmex-meteorological-measurements

maintainer: Rebecca Mott

title_for_slug: dischmex-meteorological-measurements

en: dischmex meteorological-data meteo-station meteorological-measurements dischma

en: Meteorological measurements 2016

media_type: application/pdf

en: Location of the meteorological stations

format: PDF

mimetype: application/pdf

en: Meteorological measurements 2014

en: Overview sensors

en: data

en: Meteorological measurement 2014

en: Meteorological measurement 2015

en:
Meteorological measurements recorded in the Dischma valley from 2014-2016. In 2014 and 2015 we used 11 mobile weather stations from sensorscope to record meteorological parameter in the upper Dischma valley in the closer surroundings of the Gletschboden area. The meteorological stations are eqiupped with at least air temperature/humidity, wind velocity and wind direction sensors. Some stations are additionally equipped with precipitation, shortwave radiation and snow surface temperature sensors.
Three transects were installed at different aspects and were equipped with air temperature/humidity and wind sensors. Transect 1 (stations 2-4) provides meteorological Information on an east-north-east facing slope at elevations ranging between 2100 m and 2500 m. Transect 2 (stations 5-7) provides meteorological Information on a south-west slope and transect 3 (stations 8-10) on a north-west slope. Station 1 is fully equipped with meteorological sensors (temperature/humidity, wind, IR, up and downwand shortwave radiation and precipitation).
In 2016, mobile stations from sensorscope were replaced with six permanent meteorological stations. Meteorological stations 1-3 are equipped with an air temperature/humidity sensor, two wind speed sensors, a wind direction sensor and an incoming and outgoing shortwave radiation sensor. Stations 4 and 6 are equipped with an air temperature/humidity sensor and a wind speed/direction sensor. Station 5 is a equipped with an air temperature/humidity sensor, a wind speed/direction sensor, a snow surface temperature sensor, an incoming and outgoing shortwave radiation sensor and an incoming longwave radiation sensor.

dischma

display_name: dischma

dischmex

display_name: dischmex

meteo-station

display_name: meteo-station

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

en: DISCHMEX - Meteorological measurements


disdrometer-data-davos-wolfgang

title_for_slug: disdrometer-data-davos-wolfgang

en: raclets precipitation fall-velocity disdrometer davos

en: Disdrometer Data Davos Wolfgang

en:
The zip folder contains one netCDF file per day for Davos Wolfgang from February 8 to March 19 2019 with a temporal resolution of 30 seconds (time in UTC) and includes:

- characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...)
- precipitation rate
- radar reflectivity
- visibility range
- weather codes
- instrument performance

en: The dataset contains information on precipitation amount and type for Davos Wolfgang (LON: 9.853594, LAT: 46.835577) from February 8 to March 19 2019. It includes: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

davos

display_name: davos

fall-velocity

display_name: fall-velocity

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal


regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

envi

fr: Environnement

de: Umwelt

en: Environment

fr: gibier protection-de-la-nature animal-sauvage monument-naturel flore reserve-naturelle geologie inventaire-environnement protection-des-plantes espace-protege pelouse-seche sanctuaire-faunique botanique

de: wild naturschutz wildtier naturdenkmal flora naturschutzgebiet geologie inventar pflanzenschutz schutzgebiet trockenrasen wildreservat botanik

fr: Service de consultation (WMS)

de: Darstellungsdienst (WMS)

fr: Le service représente les données de base du canton de Berne selon la géocatégorie L conforme à eCH-0166. Il comprend les géoproduits suivantes: * Zones de tranquillité pour la faune sauvage * Zones de protection de la faune sauvage * Plan sectoriel 'Biodiversité' * Objets géologiques protégés * Réserves naturelles * Objets botaniques protégés * Réserves naturelles Pro Natura * Inventaire des prairies et pâturages secs

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie L gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Ruhezonen für Wildtiere * Wildschutzgebiete * Sachplan Biodiversität * Geschützte geologische Objekte * Naturschutzgebiete * Geschützte botanische Objekte * Naturschutzgebiete Pro Natura * Inventar der Trockenwiesen und -weiden

fr: Thèmes de la protection de l’environnement et de la nature 01 (WMS)


en: canopy-height airborne-laser-scanning forest-structure snow-depth snow-distribution

en: Snow depth maps

en: Snow depth maps from two snow-on flights at each of the three field areas Davos (March 20th and 31st 2017), Engadien (March 20th and 31st, 2017) and Grand Mesa (February 8th and 16th, 2017)

en: Readme

mimetype: text/plain

en: Canopy height maps

en: Canopy height maps of each of the three field areas Davos, Engadine and Grand Mesa

en: Terrain elevation maps

en: Digital elevation model computed from snow-off flights for each of the field areas Davos, Engadine and Grand Mesa

en:
This dataset includes snow depth, canopy height and terrain elevation maps of forest stands in the Grisons (CH) and at Grand Mesa (CO,USA) derived from airborne lidar. Data were acquired i) within a pilot mission of NASA's Airborne Snow Observatory in the Swiss Alps in March 2017 and ii) during NASA’s SnowEx campaign at Grand Mesa in February 2017. Snow depth maps are available for two dates separated by approx.1 week, and include an area of ca. 0.5km2 for each of the three sites Davos, Engadine and Grand Mesa.
All data were presented and analyzed in the publication 'Revisiting Snow Cover Variability and Canopy Structure within Forest Stands: Insights from Airborne Lidar Data' (Mazzotti et al., 2019, WRR, doi: 10.1029/2019WR024898). This publication must be cited when using this dataset.

Paper Citation:
 > _Giulia Mazzotti; William Ryan Currier; Jeffrey S. Deems; Justin M. Pflug; Jessica D. Lundquist; Tobias Jonas (2019). Revisiting Snow Cover Variability and Canopy Structure Within Forest Stands: Insights From Airborne Lidar Data. Water Resources Research, 55, 6198– 6216, [doi: 10.1029/2019WR024898](https://doi.org/10.1029/2019WR024898)._

airborne-laser-scanning

display_name: airborne-laser-scanning

canopy-height

display_name: canopy-height

forest-structure

display_name: forest-structure

snow-depth

display_name: snow-depth

snow-distribution

display_name: snow-distribution

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

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: ALS-based snow depth and canopy height maps from flights in 2017 (Grisons, CH and Grand Mesa, CO)


maintainer: Tessa Hegetschweiler

en: teenagers childhood adolescents forest recreational-activities

en: Survey at schools 2017

en: The dataset of the questionnaire survey at schools in SPSS-format.

en: Dataset survey at schools

en: The dataset of the questionnaire survey at schools in excel format.

en: Questionnaire school survey

en: The questionnaire used in the survey at 8 schools aimed at teenagers in German.

en: Dataset comments

en: The codebook to the dataset

en: The data results from a questionnaire survey conducted at 8 schools in the cantons Zurich, Aargau and St. Gallen. Respondents aged 13-22 years. The aim of the survey was to gain insight into teenagers' relationship to the forest, reasons for visiting or not visiting the forest and activities in the forest.

adolescents

display_name: adolescents

childhood

display_name: childhood

forest

display_name: forest

recreational-activities

display_name: recreational-activities

teenagers

display_name: teenagers

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.

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

en: Factors influencing teenagers' forest visit frequency


regi

en: Regions and cities

envi

en: Environment

fr: gibier protection-de-la-nature sauvegarde-de-lenvironnement animal-sauvage paysage bruit-routier vegetation reserve programme-de-conservation-des-especes bruit protection-de-la-foret diversite-biologique protection-des-especes arbre bois inventaire-environnement biotope nettoyage zone-humide tourbiere tourbiere sanctuaire-faunique reserve-forestiere

de: wild naturschutz umweltschutz wildtier landschaft verkehrslarm vegetation reservat artenschutzprogramm larm waldschutz artenvielfalt artenschutz baum wald inventar biotop sanierung feuchtgebiet moor nahrstoff wildreservat waldschutzgebiet

fr: Le service représente les données de base du canton de Berne selon la géocatégorie L conforme à eCH-0166. Il comprend les géoproduits suivantes: * Zones de protection de la faune sauvage en révision * Inventaire des bas-marais * Bruit routier sur les routes cantonales * Promotion de la biodiversité en forêt (y compris réserves forestières) * Végétation des hauts-marais * Inventaire des objets naturels en forêt * Sites marécageux (délimitation détaillée ct.) * Biotopes potentiels * Zones tampon hydrologiques des hauts-marais * Zones-tampons trophiques pour les inventaires naturels nationaux et cantonaux

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie L gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Wildschutzgebiete in Revision * Inventar der Flachmoore * Strassenlärm auf Kantonsstrassen * Biodiversitätsförderung im Wald (inkl. Waldreservate) * Vegetation der Hochmoore * Waldnaturinventar * Bundesinventar der Moorlandschaften (Detail Kt.) * Potentielle Biotope * Hydrologische Hochmoor-Pufferzonen * Nährstoffpufferzonen zu nationalen und kantonalen Naturinventaren

fr: Office de l'information géographique du canton de Berne

fr: L'Office de la géoinformation est le centre de compétence pour l'information spatiale dans le canton de Berne. Les géodonnées cantonales peuvent être utilisées gratuitement, sous réserve des conditions d'utilisation. Le Géoportail du canton de Berne est le point d'entrée central pour les cartes interactives, les géodonnées et les géoservices de l'administration cantonale.

de: Das Amt für Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Bern. Die kantonalen Geodaten sind unter Einhaltung der Nutzungsbedingungen kostenlos nutzbar. Das Geoportal des Kantons Bern ist der zentrale Einstiegspunkt für interaktive Karten, Geodaten und Geodienste der kantonalen Verwaltung.

fr: Thèmes de la protection de l’environnement et de la nature 03 (WMS)


en: meteorological-data mass-flux antarctica drifting-snow terrestrial-laser-scanning snowmicropen

en: Dataset

en: Links to the dataset

en: README

en: Describes the dataset in detail

en:
This dataset contains the data acquired during the expedition to Princess Elisabeth Antarctica Station in December 2016 and January 2017. The dataset consits of meterorological data, drifting snow mass flux data, SnowMicroPen data and Terrestrial Laser Scanning data.

Please refer to the README for more information about the data.

This dataset is the basis of the following publication:

Sommer, C. G., Wever, N., Fierz, C., and Lehning, M.: Wind-packing of snow in Antarctica, The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-36, in review, 2018.

antarctica

display_name: antarctica

drifting-snow

display_name: drifting-snow

mass-flux

display_name: mass-flux

snowmicropen

display_name: snowmicropen

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Expedition to Princess Elisabeth Antarctica Station, 2016/2017


mosaic-snow-on-sea-ice-data

title_for_slug: mosaic-snow-on-sea-ice-data

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

en: ALPINE3D setup for MOSAiC

en:
The zip file contains a folder structure that must be kept as it is in order to run the simulation in the current configuration.
The setup contains both input and output data as well as the model configuration as used in the submitted manuscript
"Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

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

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

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

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

en: SNOWPACK setup for MOSAiC

en:
 The zip file contains both input and output data as well as the model configuration as used in the submitted manuscript "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

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

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

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

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

arctic-sea-ice

display_name: arctic-sea-ice

drifting-and-blowing-snow

display_name: drifting-and-blowing-snow

spatial-variability

display_name: spatial-variability

surface-mass-balance

display_name: surface-mass-balance

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: MOSAIC Snow on Sea Ice Data


maintainer: Fachstelle Open Data Mobilität Schweiz

label: Wichtigste Anpassungen Realisierungsvorgaben 2024 auf einen Blick

label: Terms of use

label: HRDF Realisierungsvorgaben

label: Cookbook Fahrplan 54 2023 (HRDF)

mimetype: ZIP

fr: ATTENTION : Certaines données sont manquantes pour cet ensemble de données. Un nouvel export est disponible sous https://opentransportdata.swiss/de/dataset/timetable-54-2023-hrdf/resource/abc5350e-d9ea-4e22-a217-f7203fe6264c.

de: ACHTUNG: Bei diesem Datensatz fehlen gewisse Daten. Unter https://opentransportdata.swiss/de/dataset/timetable-54-2023-hrdf/resource/abc5350e-d9ea-4e22-a217-f7203fe6264c steht ein neuer Export zur Verfügung.

en: PLEASE NOTE: Certain data is missing from this data set. A new export is available at https://opentransportdata.swiss/de/dataset/timetable-54-2023-hrdf/resource/abc5350e-d9ea-4e22-a217-f7203fe6264c.

it: ATTENZIONE: In questo set di dati mancano alcuni dati. Una nuova esportazione è disponibile su https://opentransportdata.swiss/de/dataset/timetable-54-2023-hrdf/resource/abc5350e-d9ea-4e22-a217-f7203fe6264c.

fr: Attention : cet ensemble de données contient des données avec des coordonnées erronées. Dans l'exportation du 16.03.2023, elles sont correctes.

de: Achtung: In diesem Datensatz sind Daten mit falschen Koordinaten enthalten. Im Export des 16.03.2023 sind sie korrekt.

en: Attention: In this dataset there is data with wrong coordinates. In the export of 16.03.2023 they are correct.

it: Attenzione: questo set di dati contiene dati con coordinate errate. Sono corrette nell'esportazione del 16.03.2023.

fr:
L’horaire comprend les éléments topologiques et temporels fondamentaux permettant la représentation de l’horaire et la fourniture d’informations à ce sujet. L’horaire est fourni au format de données brutes HAFAS (HRDF).

Remarque : Adaptation des directives de réalisation HRDF 2.0.5 : Nouvelle version le 16.01.2024. Pour plus de détails, voir "Autres informations".

Nous mettons à votre disposition un ensemble de données de test avec les nouvelles adaptations: https://opentransportdata.swiss/fr/dataset/testfile-hrdf-rv2-0-5

en:
The timetable contains the essential topological and temporal elements that enable timetable display and information. The timetable is provided in the HAFAS raw data format (HRDF).

Note: Adaptation of realisation specifications HRDF 2.0.5: New release on 16.01.2024. For details see "Further information".

We provide you with a test data set with the new adjustments: https://opentransportdata.swiss/en/dataset/testfile-hrdf-rv2-0-5

de:
Der Fahrplan enthält die grundlegenden topologischen, sowie die zeitlichen Element, die eine Fahrplandarstellung und -auskunft ermöglichen.

Hinweis: Anpassung Realisierungsvorgaben HRDF 2.0.5: Neuer Release am 16.01.2024. Details siehe "Weitere Informationen".

Wir stellen Ihnen einen Testdatensatz mit den neuen Anpassungen zur Verfügung: https://opentransportdata.swiss/de/dataset/testfile-hrdf-rv2-0-5

it:
L’orario contiene l’elemento topologico basilare e anche l’elemento temporale, che consentono la rappresentazione dell’orario e le informazioni sull’orario. L’orario viene messo a disposizione tramite il formato Raw HAFAS (HRDF).

Nota: adattamento delle specifiche di realizzazione HRDF 2.0.5: nuova release il 16.01.2024. Per i dettagli, vedere "Ulteriori informazioni".

Vi forniremo un set di dati di prova con le nuove regolazioni: https://opentransportdata.swiss/it/dataset/testfile-hrdf-rv2-0-5

oevch

fr: Secrétariat des tâches du système d’information à la clientèle (CFF SA)

de: Geschäftsstelle Systemaufgaben Kundeninformation (SBB AG)

en: Business office of Customer Information System Tasks (SBB CFF FFS)

it: Servizio commerciale Attività di sistema Informazione alla clientela (FFS SA)

fr: Le Secrétariat des tâches du système d’information à la clientèle (SKI) publie pour le compte de l’OFT les données de l’ensemble des transports publics de Suisse.

de: Die Geschäftsstelle Systemaufgaben Kundeninformation (SKI) veröffentlicht im Auftrag des BAV die Daten des gesamten öffentlichen Verkehrs der Schweiz

en: Working on behalf of the Swiss Federal Office of Transport (FOT), the Customer Information System Tasks (SKI) business office publishes data on all public transport in Switzerland

it: Il servizio commerciale Attività di sistema Informazione alla clientela (SKI) pubblica, per conto dell’UFT, i dati di tutto il trasporto pubblico in Svizzera.


maintainer: Esther Frei

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

mimetype: application/x-zip-compressed

en:
 Background information

The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Long-term monitoring of the large-scale high-elevation afforestation has generated data about tree growth, survival, and vitality. In addition, detailed characteristics of the microsite conditions of the research were conducted. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone.

 Experiment description

The Stillberg afforestation experiment was established in 1975 by planting 92,000 seedlings of *Larix decidua*, *Pinus cembra* and *Pinus mugo* ssp. *uncinata* in the alpine treeline ecotone. The afforestation site is located on a northeast-facing slope with steep, topographically highly structured terrain and covers elevations from 2075 to 2230 m a.s.l. The afforestation site was divided into 4052 square plots of 3.5 × 3.5 m, arranged in a regular species-alternating pattern over the whole area. Each plot contained 25 trees of one species (1350 plots per species), and the seedlings were systematically planted 70 cm apart. The trees have been monitored since 1975. Specifically, tree mortality was assessed annually from 1975 until 1995 and has been documented every ten years since then, with surveys in 2005 and 2015 (the next survey is due in 2025). Height of the surviving trees was measured in 1975, 1979, 1982, 1985, 1990, 1995, 2005, and 2015. In 1995, 2005, and 2015, drivers of tree vitality were assessed for a subset of trees per plot. Additionally, an extensive set of environmental parameters characterizing microsite conditions of the afforestation area were recorded before and after the planting of the trees.

 Data description

The five datasets from the afforestation experiment comprise ecological and environmental data from the main afforestation experiment in five datasets with accompanying metadata (Stillberg_afforestation_all_metadata.xlsx). All data and metadata files are bundled in a ZIP-file (Stillberg_afforestation_v1.zip). In particular, a first dataset contains environmental data characterising microsite conditions of the 4000 plots with regard to soil, topography, vegetation and microclimatic conditions (Stillberg_afforestation_plot_data_v1.csv; Stillberg_afforestation_plot_metadata_v1.csv. In each plot, the natural tree regeneration was assessed by counting seedings of several tree species in 2005 and 2015 (Stillberg_afforestation_regeneration_data_v1.csv; Stillberg_afforestation_regeneration_metadata_v1.csv). Furthermore, specific information about each of the 92’000 planted trees of the tree species is available (Stillberg_afforestation_tree_parameter_data_v1.csv; Stillberg_afforestation_tree_parameter_metadata_v1.csv). Survival data for each of the 92’000 individual trees can be found in a separate dataset (Stillberg_afforestation_tree_survival_data_v1.csv; Stillberg_afforestation_tree_survival_metadata_v1.csv). Tree growth and vitality parameters are available for all trees from 1995, and for subsets of trees for 2005 and 2015 (Stillberg_afforestation_tree_measurements_data_v1.csv; Stillberg_afforestation_tree_measurements_metadata_v1.csv).

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: Long-term afforestation experiment at the Alpine treeline site Stillberg, Switzerland


agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

regi

fr: Régions et villes

en: Regions and cities

fr: Service de téléchargement (WFS)

de: Downloaddienst (WFS)

fr: Le service représente les données de base du canton de Berne selon la géocatégorie S conforme à eCH-0166. Il comprend les géoproduits suivantes: * Les cultures agricoles (provisoires) * Les cultures agricoles

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie S gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Landwirtschaftliche Kulturen (provisorisch) * Landwirtschaftliche Kulturen

de: Amt für Geoinformation des Kantons Bern


de: Regionen und Städte

envi

fr: Environnement

de: Umwelt

en: Environment

fr: roche eaux-souterraines

de: fels grundwasser

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: Le géoproduit GW25 contient les gisements d’eau souterraine en roches meubles, connus et supposés (classifiés selon l'épaisseur de la nappe et la perméabilité du sous-sol ainsi que divisés en niveaux supérieurs et inférieurs). En plus les directions d'écoulement, les lignes isohypses des nappes et les venues d'eau artésienne en roches meubles sont contenues dans le géoproduit.

de: Das Geoprodukt GW25 beinhaltet bekannte und vermutete Grundwasservorkommen in Lockergesteinen, klassiert nach Mächtigkeit und Durchlässigkeit sowie unterteilt in obere und untere Stockwerke. Zusätzlich sind im Geoprodukt die Grundwasserfliessrichtungen und Isohypsen des Grundwasserspiegels sowie die Arteser enthalten.

spatial: Kanton Bern (reduziert)

fr: Gisements d'eau souterraine en roches meubles

de: Grundwasservorkommen in Lockergestein


en: climate-change biodiversity ecology statistical-interpolation forest microclimate radiation-transfer

en: Predicted microclimate topsoil temperatures at 5 cm below ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en: Predicted microclimate air temperatures at 100 cm above ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en: Predicted microclimate air temperatures at 5 cm above ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en: Climate data matching the scales at which organisms experience climatic conditions are often missing. Yet, such data on microclimatic conditions are required to better understand climate-change impacts on biodiversity and ecosystem functioning. Here we combine a national network of microclimate temperature measurements with a novel radiative transfer model to map monthly minimum, mean and maximum temperatures during the vegetation period at a 10 meter spatial resolution across Switzerland. The temperature measurements took place in 107 sampling plots distributed across different habitat types, with 62 plots in forests, 22 below trees outside forests, and 23 in open grasslands. In each plot we measured temperature in the topsoil (-5cm), as well as in the air at 5cm and 100cm height above ground. Spatial interpolation was achieved by using a hybrid approach based on linear mixed effects models with input from detailed radiation estimates that account for topographic and vegetation shading, as well as other predictor variables related to the macroclimate, topography and vegetation height. Our data reveals strong horizontal and vertical variability in microclimate temperature, particularly for maximum temperatures at 5 cm above the ground and within the topsoil. Compared to macroclimate conditions as measured by weather stations outside forests, diurnal air and topsoil temperature ranges inside forests were reduced by up to 3.0 and 7.8 °C, respectively, while below trees outside forests, e.g. in hedges and below solitary trees, this buffering effect was 1.8 and 7.2 °C. We also found that in open grasslands, maximum temperatures at 5 cm above ground are on average 3.4 °C warmer than that of macroclimate, suggesting that in such habitats heat exposure close to the ground is often underestimated when using macroclimatic data. After accounting for macroclimate effects, microclimate patterns were primarily driven by radiation, with particularly strong effects on maximum temperatures. Results from spatial block cross-validation revealed predictive accuracies as measured by RSME’s ranging from 1.18 to 3.43 °C, with minimum temperatures generally being predicted more accurately than maximum temperatures. The microclimate maps presented here enable a more biologically relevant perspective when analysing climate-species interactions, which is expected to lead to a better understanding of biotic and ecosystem responses to climate and land use change.

biodiversity

display_name: biodiversity

climate-change

display_name: climate-change

ecology

display_name: ecology

forest

display_name: forest

microclimate

display_name: microclimate

radiation-transfer

display_name: radiation-transfer

statistical-interpolation

display_name: statistical-interpolation

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

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.

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

en: Monthly topsoil and near surface microclimate temperature data for Switzerland


politische-grenzen-generalisiert

title_for_slug: politische-grenzen-generalisiert

fr: frontiere-infranationale lac frontiere-nationale limite-administrative commune bordure

de: innerstaatliche-grenze see staatsgrenze verwaltungsgrenze gemeinde grenze

fr: Les limites politiques généralisées contiennent les limites des communes, des arrondissements administratifs et du canton de Berne, basé sur le plan d'ensemble au 1:5'000. Les limites sont généralisées à partir des données originales de 'Limites politiques du canton de Berne'.

de: Die generalisierten politischen Grenzen enthalten die Gemeinde-, Verwaltungskreis- und Kantonsgrenzen des Kantons Bern. Die Grenzen wurden auf der Grundlage des Originaldatensatzes 'Politische Grenzen des Kantons Bern' generalisiert.

fr: Office de l'information géographique du canton de Berne

fr: L'Office de la géoinformation est le centre de compétence pour l'information spatiale dans le canton de Berne. Les géodonnées cantonales peuvent être utilisées gratuitement, sous réserve des conditions d'utilisation. Le Géoportail du canton de Berne est le point d'entrée central pour les cartes interactives, les géodonnées et les géoservices de l'administration cantonale.

de: Das Amt für Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Bern. Die kantonalen Geodaten sind unter Einhaltung der Nutzungsbedingungen kostenlos nutzbar. Das Geoportal des Kantons Bern ist der zentrale Einstiegspunkt für interaktive Karten, Geodaten und Geodienste der kantonalen Verwaltung.


maintainer: Maria Elvira Murazzi

en: forest-trees 13c-labelling uptake polystyrene nanoplastic

en: Nanoplastic in forests experiment

en:
Data embargoed until August 2022, and it will be provided upon request

-  excel file containing: two working sheets (leaf supply and root supply experiment) with a table with the values 13C-nanopolystyrene in the different tissues of the two forest tree species; graph showing the differences between controls and treatments of 13C-nanopolystyrene enrichment for each tissue of each forest tree species; ANOVA table showing significant values after having exposed the tree species to 13C-nanopolystyrene

en:
The fate of plastic in the environment is of global concern, because its production recently has
increased strongly and it accumulates in terrestrial and aquatic ecosystems. Although some knowledge on
its role in aquatic and terrestrial ecosystems was gained in the recent decade, hitherto very little is known
about the impact of micro and nanoplastics in forest ecosystems.

The aim of this pioneering project was to explore if nanoplastics are taken up by forest trees species
through leaves or roots. In greenhouse experiments, we exposed leaves or roots of seedling of two forest
trees species to solutions with highly 13C-labelled polystyrene nanoparticles (13C-nPS, 99 atom%) and
examined if they were incorporated in different above- and belowground tissues.

Treated part of the trees for both species showed significant 13C-enrichment, indicating that trees take up nanoparticles. However, the overall 13C signal strength in tissues that were not exposed to the 13C label remained low (Δδ13C<1‰) and was confined to a few seedlings, leaving it ambiguous whether nanoplastic transport occurs or not.

We acknowledge that the new method developed might be not sensitive enough to unequivocally detect
mechanisms of nanoplastic uptake and transport at environmentally realistic concentrations.

forest-trees

display_name: forest-trees

nanoplastic

display_name: nanoplastic

polystyrene

display_name: polystyrene

uptake

display_name: uptake

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: Nanoplastics in forests: Exploring the effects of nanoplastics on forest soils and tree physiology (NanoPlast)


maintainer: James W. Kirchner

en: snowmelt streamflow evapotranspiration sap-flow diurnal-cycle ecohydrology diel-cycle groundwater

en: Metadata

en: Column descriptions for both data files, and map coordinates for all measurement locations.

en: Subcatchment polygons

en: Subcatchment polygons for use in the Google Earth Engine scripts.

en: MODIS NDSI script

en: Google Earth Engine script for computing MODIS normalized difference snow index (NDSI) values and averaging them over subcatchment areas.

en: MODIS EVI2 script

en: Google Earth Engine script for computing MODIS two-band enhanced vegetation index (EVI2) values and averaging them over subcatchments.

en: Daily time series

en: Daily hydrometeorological and ecohydrological time series

en: 30-minute time series

en: 30-minute hydrometeorological and ecohydrological time series.

en:
Hydrometerological and ecohydrological time series from Sagehen Creek and Independence Creek, Sierra Nevada, USA, illustrating hydrological responses to daily cycles in snowmelt and evapotranspiration forcing.

Data include 30-minute time series of

- weather variables,

- sap flow fluxes,

- groundwater levels (in two riparian transects of shallow groundwater wells),

- and stream stages (at 12 sites spanning a 500-meter elevation gradient),

and daily time series of

- temperature, precipitation, and snow water equivalent at three nearby snow telemetry stations

- diel cycle index values for groundwater levels and stream stages,

- and MODIS normalized difference snow index (NDSI) and enhanced vegetation index (EVI2) values averaged over selected subcatchments.

Google Earth Engine scripts for extracting the MODIS data are also provided.

diel-cycle

display_name: diel-cycle

diurnal-cycle

display_name: diurnal-cycle

ecohydrology

display_name: ecohydrology

evapotranspiration

display_name: evapotranspiration

groundwater

display_name: groundwater

sap-flow

display_name: sap-flow

snowmelt

display_name: snowmelt

streamflow

display_name: streamflow

en: Daily cycles in solar flux, snowmelt, transpiration, groundwater, and streamflow at Sagehen and Independence Creeks, Sierra Nevada, USA


regi

en: Regions and cities

envi

en: Environment

fr: etablissement-humain concentration-de-peuplement lac peche-a-la-ligne zone-de-developpement zone-constructible paysage planification-et-developpement-urbain zone-construite planification-de-lespace-physique commune trafic planification-regionale eaux-geographie promotion-du-commerce-et-de-lindustrie amenagement-du-territoire eaux-interieures transport-maritime planification

de: siedlung siedlungsverdichtung see angeln entwicklungsgebiet bauland landschaft stadtplanung-und--entwicklung baugebiet raumplanung gemeinde verkehr regionalplanung gewasser wirtschaftsforderung flachennutzungsplanung binnengewasser seeverkehr planung

fr: Le service représente les données de base du canton de Berne selon la géocatégorie E conforme à eCH-0166. Il comprend les géoproduits suivantes: * Thèmes régionaux relatifs à l'urbanisation et au paysage (faisant partie des CRTU) * Pôles de développement * Plan sectoriel de la navigation de plaisance * Projet cantonal de développement paysager (PCDP) * Plan d'affectation cantonal - Plans de quartier * Espaces réservés aux eaux approuvés * Urbanisation interne * Système de gestion des zones d'activités * Territoires à habitat dispersé

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie E gemäss eCH-0166 dar. Er enthält die folgenden Geoprodukte: * Regionale Siedlungs- und Landschaftsthemen (Teile der RGSK) * Entwicklungsschwerpunkte * Sachplan Seeverkehr * Kantonales Landschaftsentwicklungskonzept (KLEK) * Kantonale Nutzungsplanung - Überbauungsordnungen * Genehmigte Gewässerräume * Siedlungsentwicklung nach innen * Arbeitszonenbewirtschaftung * Streusiedlungsgebiete

fr: Développement territorial et cadastre foncier 02 (WFS)

de: Raumplanung und Grundstückskataster 02 (WFS)


gefahrenanalyse-der-gemeinden

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

educ

en: Education, culture and sport

regi

fr: Régions et villes

title_for_slug: gefahrenanalyse-der-gemeinden

fr: etude-de-danger evaluation-du-risque

de: gefahrenanalyse risikobewertung

fr: Les données renseignent sur les dangers spécifiques à chaque commune. Elles constituent le fondement de la préparation des organes communaux de protection de la population en matière de catastrophes ou de situations d’urgence.

de: Die Daten geben Auskunft über die für jede Gemeinde spezifische Gefahrensituation. Sie bilden die Basis für die risikobasierte Vorbereitung der kommunalen Organe des Bevölkerungsschutzes im Hinblick auf Katastrophen und Notlagen.

name: Amt für Bevölkerungsschutz, Sport und Militär


maintainer: Yaquan Chang

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

en: Plant range map at Hengduan scale

en: This is the plant range map at the Hengduan mountain scale based on species distribution model, elevation, and county level distribution information

en: HDM heterogeneity scales

en: The Heterogeneity matrics in the Hengduan mountain scale

en: Hengduan plant family richness map

en: This is the family level plant richness map in the Hengduan mountain scale at 1km resoution

en: Eurasia SR and heteorgeneity

en: This table is used for the Eurasia scale analyses, including both family level species richness map and different heterogeneity predictors

en: Eurasia plant family richness map

en: This is the plant family level richness map at the Eurasia scale calculated from https://www.nature.com/articles/s41597-021-00997-6

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

habitat-heterogeneity

display_name: habitat-heterogeneity

hengduan-mountains

display_name: hengduan-mountains

hypervolume

display_name: hypervolume

model-residuals

display_name: model-residuals

phytodiversity

display_name: phytodiversity

envidat

en: EnviDat: the Environmental Data Portal

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

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


en: landscape-evolution madagascar flora endemism geology

en: Escarpment evolution drives the diversification of the Madagascar flora

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

en: Data v1.o

en: used for paper submission only

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

endemism

display_name: endemism

flora

display_name: flora

geology

display_name: geology

landscape-evolution

display_name: landscape-evolution

madagascar

display_name: madagascar


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

en: Data Compilation

en: Compressed TXT files

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

boundary-layer-winds

display_name: boundary-layer-winds

saltation

display_name: saltation

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

vertical-wind-motion

display_name: vertical-wind-motion

educ

en: Education, culture and sport

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


maintainer: Ionut Iosifescu Enescu

en: open-data open-science reproducibility jupyter-notebooks research-data-management hpc open-source

en: Open Science Support @ WSL (Poster)

en:
This poster was originally created for the swissuniversities Open Science Action Plan: Kick-Off Forum, and showed to the audience on 17.10.2019. It illustrates how the environmental data portal EnviDat provides the tools for fostering Open Science and Reproducibility of scientific research at WSL.

Supporting open science is a highly relevant user requirement for EnviDat and for implementing FAIR (Findability, Accessibility, Interoperability and Reusability) principles at dataset level.
EnviDat encourages WSL scientists to complement data publication with a complete description of research methods and the inclusion of the open source software, code or scripts used for processing the dataset or for obtaining the published results. By openly publishing open software (e.g. as Jupyter notebooks) alongside research data sets, researchers can contribute to mitigate reproducibility issues.

EnviDat also promotes and supports, where possible and practical, the publication of software as Jupyter notebooks. Jupyter notebooks provide a solution for improved documentation and interactive execution of open code in a wide range of programming languages (Python, R, Octave/Matlab, Java or Scala). These programming languages are widely used in environmental research at WSL and well supported by the Jupyter-compatible kernels. We have sucessfully interfaced EnviDat-hosted notebooks with the WSL High-Performance Computing (HPC) Linux Cluster through a JupyterHub/JuypterLab beta installation on the HPC cluster implemented in close collaboration with the WSL IT-Services.
For existing software that cannot be easily migrated to Jupyter Notebooks, the Open Science and Reproducibility is assisted by containerisation. We have proven that several Singularity containers can successfully run on WSL's HPC cluster.

Finally, the researchers can upload the data/results complemented by code (e.g. as Jupyter Notebooks, or Singularity containers) and any additional documentation in EnviDat. Consequently, they will receive a DOI for the entire dataset, which they can reference in their science paper in order to publish a more reproducible research.

_License_: This poster 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 this poster in any way you want, for any purposes and without restrictions.

hpc

display_name: hpc

jupyter-notebooks

display_name: jupyter-notebooks

open-data

display_name: open-data

open-science

display_name: open-science

open-source

display_name: open-source

reproducibility

display_name: reproducibility

research-data-management

display_name: research-data-management

en: Open Science Support at the Swiss Federal Research Institute WSL. The EnviDat Concept


en: ice snow antarctica arctic sea-salt-aerosol

en: Code

en: Matlab code to read and plot the data

en: Fig 1F_1

en: Individual data to mean shown in Figure 1F

en: Fig 1F_2

en: Fig 1E

en: Data to Figure 1E

en: Fig 1B

en: Data in Figure 1B

en: Fig 1F

en: Data to Figure 1F

en: Fig 1A

en: Data Figure 1A

en: Fig 1B_1

en: Individual data to mean shown in Figure 1B

en: Table 2

en: This table lists all NEXAFS data files in chronological order with PE carbon to oxygen signal intensity ratios -from which the atomic ratio were calculated in the paper - before ("preCtoO") and after ("postCtoO") each NEXAFS measurement. Also listed is the change in Na ("lossSodi"), O ("lossOxy"), Cl ("lossChlor"), and C ("lossCarb") signal intensity after the NEXAFS measurement compared to prior to the NEXAFS measurement.

en: Fig 1D

en: Data to Figure 1D

en: Fig 1C

en: Data to Figure 1C

en: This table lists all data files in chronological order. "SampleTemp" refers to the reading of the PT-1000 at the side of the sample holder. "cellPressure" is the water vapour pressure during the measurements. From this, in presence of ice, the temperature of the ice sample can be calculated which is given in the column "iceTemp". "dT" is the difference, or temperature offset, between sensor's reading and the ice samples temperature. The offset is due to the sensor being mounted away from the cooled spot of the sample were it experiences heating from warmer parts of the sample holder. The off-set is used to calibrate the temperature sensor and the resulting temperature during the experiments is given in the column "temperature". "relHum" is the relative humidity above (supercooled) liquid and "concBrine" is the concentration of a NaCl solution in mol/l in equilibrium with ice at the experimental temperature. "Area" is the integrated PE signal.

en: Fig 1B_2

en: Read Me

en: Laboratory experiments are presented on the phase change at the surface of sodium chloride – water mixtures at temperatures between 259 K and 240 K. High selectivity to the upper few nanometres of the frozen solution – air interface is achieved by using electron yield near-edge X-ray absorption fine structure (NEXAFS) spectroscopy. We present the NEXAFS spectrum of the hydrohalite.

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: Data set on interfacial supercooling and the precipitation of hydrohalite in frozen NaCl solutions by X-ray absorption spectroscopy


disdrometer-data-laret

maintainer: Daniel Wolfensberger

title_for_slug: disdrometer-data-laret

en: raclets visibility disdrometer precipitation hydrometeors

en: Disdrometer Data Laret

en: The zip folder contains one netCDF file per day for Laret from February 7 to March 29 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Laret_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

en:
A laser optical disdrometer (Parsivel² , OTT Hydromet) was used to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms.
The dataset contains information on precipitation amount and type for the period of February 7 to March 29 2019 in Laret.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility

educ

en: Education, culture and sport

en: EnviDat: the Environmental Data Portal


en: raster sentinel-2 gridded-data research-data-management video-encoding core geodata time-series

en:
Shell script to reproduce the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software for working with CORE will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en: View publication in the Digital Object Repository at WSL (DORA)

media_type: text/html

format: HTML

en:
Shell script to extract data from the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en: CORE Dataset (80 GB)

en:
DISCLAIMER: CORE is still in development. Interested parties are warmly invited to join common development, to comment, discuss, find bugs, etc.

Acknowledgement: The CORE format was proudly inspired by the Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) format, by considering how to leverage the ability of clients issuing HTTP GET range requests for a time-series of remote sensing and aerial imagery (instead of just one image).

License: The Cloud Optimized Raster Encoding (CORE) specifications are released to the public domain under a Creative Commons 1.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

-----------------------

Summary:
The Cloud Optimized Raster Encoding (CORE) format is being developed for the efficient storage and management of gridded data by applying video encoding algorithms. It is mainly designed for the exchange and preservation of large time series data in environmental data repositories, while in the same time enabling more efficient workflows on the cloud. It can be applied to any large number of similar (in pixel size and image dimensions) raster data layers. CORE is not designed to replace COG but to work together with COG for a collection of many layers (e.g. by offering a fast preview of layers when switching between layers of a time series).

WARNING: Currently only applicable to RGB/Byte imagery. The final CORE specifications may probably be very different from what is written herein or CORE may not ever become productive due to a myriad of reasons (see also 'Major issues to be solved').

With this early public sharing of the format we explicitly support the Open Science agenda, which implies "shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process" (quote from: European Commission, Directorate General for Research and Innovation, 2016. Open innovation, open science, open to the world).

CORE Specifications:

1) a MP4 or WebM video digital multimedia container format (or any future video container playable as HTML video in major browsers)

2) a free to use or open video compression codec such as H.264, VP9, or AV1 (or any future video codec that is open sourced or free to use for end users)

Note: H.264 is currently recommended because of the wide usage with support in all major browsers, fast encoding due to acceleration in hardware (which is currently not the case for AV1 or VP9) and the fact that MPEG LA has allowed the free use for streaming video that is free to the end users. However, please note that H.264 is restricted by patents and its use in proprietary or commercial software requires the payment of royalties to [MPEG LA](https://www.mpegla.com/programs/avc-h-264/). However, when AV1 matures and accelerated hardware encoding becomes available, AV1 is expected to offer 30% to 50% smaller file size in comparison with H.264, while retaining the [same quality](https://trac.ffmpeg.org/wiki/Encode/AV1).

3) the encoding frame rate should be of one frame per second (fps) with each layer segmented in internal tiles, similar to COG, ordered by the main use case when accessing the data: either layer contiguous or tile contiguous;

Note: The internal tile arrangement should support an easy navigation inside the CORE video format, depending on the use case.

4) a CORE file is optimised for streaming with the moov atom at the beginning of the file (e.g. with -movflags faststart) and optional additional optimisations depending on the codec used (e.g. -tune fastdecode -tune zerolatency for H.264)

5) metadata tags inside the moov atom for describing and using geographic image data (that are preferably compatible with the [OGC GeoTIFF standard](https://www.ogc.org/standards/geotiff) or any future standard accepted by the geospatial community) as well as list of original file names corresponding to each CORE layer

6) it needs to encode similar source rasters (such as time series of rasters with the same extent and resolution, or different tiles of the same product; each input raster should be having the same image and pixel size)

7) it provides a mechanism for addressing and requesting overviews (lower resolution data) for a fast display in web browser depending on the map scale (currently external overviews)

Major issues to be solved:

- Internal overviews (similar to COG), by chaining lower resolution videos in the same MP4 container for fast access to overviews first); Currently, overviews are kept as separate files, as external overviews.

- Metadata encoding (how to best encode spatial extent, layer names, and so on, for each of the layer inside the series, which may have a different geographical extent, etc...; Known issues: adding too many tags with FFmpeg which are not part of the standard MP4 moov atom; metadata tags have a limited string length.

- Applicability beyond RGB/Byte datasets; defining a standard way of converting cell values from Int16/UInt16/UInt32/Int32/Float32/Float64/ data types into multi-band Byte values (and reconstructing them back to the original data type within acceptable thresholds)

Example

Notice: The provided CORE (.mp4) examples contain modified Copernicus Sentinel data [2018-2021].

For generating the CORE examples provided, 50 original Sentinel 2 (S-2) TCI data images from an area located inside Switzerland were downloaded from www.copernicus.eu, and then transformed into CORE format using ffmpeg with H.264 encoding using the [x264 library](https://www.videolan.org/developers/x264.html).

For full reproducibility, we provide the original data set and results, as well scripts for data encoding and extraction (see resources).

core

display_name: core

geodata

display_name: geodata

gridded-data

display_name: gridded-data

raster

display_name: raster

time-series

display_name: time-series

video-encoding

display_name: video-encoding


maintainer: Franziska Koch

en: snow-depth snow-cover liquid-water-content snow gps

en: Dataset with GPS-derived snow cover properties and validation data

en: This file includes the data as described in the Read-me file.

en: Read-me

en: The read-me file contains the description of the data provided.

en:
This data set includes GPS-derived snow water equivalent (SWE), snow depth (HS) and liquid water content (LWC) data for three entire snow-covered seasons (2015-2016, 2016-2017, 2017-2018) at the study plot Weissfluhjoch 2540 m a.s.l. (Davos, Switzerland). The procedure to derive these snow properties is described in Koch et al. (2019). The novel approach is based on a combination of GPS signal attenuation and time delay.

The dataset also includes corresponding validation data for SWE and HS measured at Weissfluhjoch, and some additional meteorological data used for interpretation of the snow cover evolution.

Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
> Koch, F., Henkel, P., Appel, F., Schmid, L., Bach, H., Lamm, M., Prasch, M., Schweizer, J., and Mauser, W., 2019. Retrieval of snow water equivalent, liquid water content and snow height of dry and wet snow by combining GPS signal attenuation and time delay. Water Resources Research, 55(5), 4465-4487. https://doi.org/10.1029/2018WR024431

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

en: GPS-derived data of SWE, HS and LWC and corresponding validation data


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

en: Snowdepth maps

format: GeoTIFF

en:
The available datasets are snow depth maps with a spatial resolution of 0.5 m derived from images of the survey camera Vexcel Ultracam mounted on a piloted airplane. Image acquisition was carried out during the approximately peak of winter (time when the thickest snowpack is expected) in spring. The snow depth maps are calculated by the subtraction of a summer-DTM from the processed winter- DSM of the corresponding date. The summer-DTM used was derived from a point cloud of an airborne laser scanner from 2020.

Due to the occurrence of inaccuracies of the calculated snow depth values caused by the photogrammetric method, we applied different masks to significantly increase the reliability of the snow depth maps. We masked out settled areas, high-frequented streets and technical constructions, pixels with high vegetation (height > 0.5 m) , outliers and unrealistic snow depth values. In addition, we modified the snow depth values of snow-free pixels to 0.
The information on buildings and infrastructure comes from the exactly classified ALS point cloud and the TLM dataset from Swisstopo (https://www.swisstopo.admin.ch/de/geodata/landscape/tlm3d.html#links). High vegetation is also derived from the classification and the calculated object height from the point cloud.
Outliers and unrealistic snow depth values are defined as negative snow depth values and snow depths exceeding 10 m. The classification of each pixel of the corresponding orthophoto into snow-covered or snow-free is based on the application of a threshold of the NDSI or manually determined ratios of the RGB values.

An extensive accuracy assessment proves the high accuracy of the snow depth maps with a root mean square error of 0.25 m for the year 2017 and 0.15 m for the following snow depth maps.

The work is published in:

avalanches

display_name: avalanches

davos

display_name: davos

dischma

display_name: dischma

photogrammetry

display_name: photogrammetry

snow-depth-distribution

display_name: snow-depth-distribution

snow-hydrology

display_name: snow-hydrology

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


maintainer: Franziska Gerber

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

en: Python scripts to reproduces figures in Gerber et al., 2022, submitted.

en: Processed CRYOWRF output used for the analysis and the figures in the paper.

en: Namelist and input files and information to run the WRF and CRYOWRF simulations used in the paper.

en: Python scripts to reproduces figures in Gerber et al., 2022, revised

en: Processed WRF output (run with Noah-MP land surface model) used for the analysis and the figures in the paper.

en: Static input data from the WRF simulations (used in the python scripts in Scripts_Reproducibility).

en:
This dataset contains data and scripts for "CRYOWRF - a validation and the effect of blowing snow on the Antarctic SMB" (Gerber et al., submitted).

* Simulation_setup: Namelists and input information to run the simulation. Some input files need to be downloaded from Sharma et a., 2021.
* Static_input: Static topography input file of WRF (geo_em.d01).
* WRF_27km_NoahMP: Preprocessed WRF output of the simulation run with the WRF using the surface parameterization Noah-MP to reproduce the figures and results in the paper.
* WRF_27km_CRYOWRF: Preprocessed WRF output of the simulation run with CRYOWRF to reproduce the figures and results in the paper.
* Scripts_Reproducibility: Python scripts to reproduce the figures and results in the paper.

Note:

* To run some of the scripts Atmospheric Weather station data needs to be prepared using Gerber and Lehning, 2022.
* AWS data is not provided and needs to be downloaded from the corresponding databases. Please make sure to comply with the respective terms and conditions.

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

cryowrf

display_name: cryowrf

reproducibility

display_name: reproducibility

surface-mass-balance

display_name: surface-mass-balance

educ

en: Education, culture and sport

en: EnviDat: the Environmental Data Portal

en: Reproducibility dataset for CRYOWRF validation


en: hazard-mapping release avalanche ramms snow hazard-indication-mapping

en: Potential Release  Area  NHESS

en: This folder contains the output of the different investigated algorithms plus the reference dataset, used for training and validation.

en: RAMMS simulations NHESS

en: Simulated maximum pressures for the scenarios frequent and extreme taking the forest layer into account

en:
This dataset contains the output and reference data published in the paper "Automated snow avalanche release area delineation - validation of existing algorithms and proposition of a new object-based approach for large scale hazard indication mapping" Yves Bühler, Daniel von Rickenbach, Andreas Stoffel, Stefan Margreth, Lukas Stoffel, Marc Christen (2018) Natural Hazards And Earth System Sciences.

Abstract:
Snow avalanche hazard is threatening people and infrastructure in all alpine regions with seasonal or permanent snow cover around the globe. Coping with this hazard is a big challenge and during the past centuries, different strategies were developed. Today, in Switzerland, experienced avalanche engineers produce hazard maps with a very high reliability based on avalanche cadastre information, terrain analysis, climatological datasets and numerical modelling of the flow dynamics for selected avalanche tracks that might affect settlements. However, for regions outside the considered settlement areas such area-wide hazard maps are not available mainly because of the too high cost, in Switzerland and in most mountain regions around the world. Therefore, hazard indication maps, even though they are less reliable and less detailed, are often the only spatial planning tool available. To produce meaningful and cost-effective avalanche hazard indication maps over large regions (regional to national scale), automated release area delineation has to be combined with volume estimations and state-of-the-art numerical avalanche simulations.

In this paper we validate existing potential release area (PRA) delineation algorithms, published in peer-reviewed journals, that are based on digital terrain models and their derivatives such as slope angle, aspect, roughness and curvature. For validation, we apply avalanche cadastre data from three different ski resorts in the vicinity of Davos, Switzerland, where experienced ski-patrol staff mapped most avalanches in detail since many years. After calculating the best fit input parameters for every tested algorithm, we compare their performance based on the reference datasets. Because all tested algorithms do not provide meaningful delineation between individual potential release areas (PRA), we propose a new algorithm based on object-based image analysis (OBIA). In combination with an automatic procedure to estimate the average release depth (d0), defining the avalanche release volume, this algorithm enables the numerical simulation of thousands of avalanches over large regions applying the well-established avalanche dynamics model RAMMS. We demonstrate this for the region of Davos for two hazard scenarios, frequent (10 – 30 years return period) and extreme (100 – 300 years return period). This approach opens the door for large scale avalanche hazard indication mapping in all regions where high quality and resolution digital terrain models and snow data are available.

avalanche

display_name: avalanche

hazard-indication-mapping

display_name: hazard-indication-mapping

hazard-mapping

display_name: hazard-mapping

ramms

display_name: ramms

release

display_name: release

en: Automated Avalanche Release Area (PRA) Delineation Davos