en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Othmarsingen in Switzerland where one station is located within a natural deciduous forest stand (OTB) with European beech (_Fagus sylvatica_; 120-140 yrs) and lime trees (_Tilia sp._; 120-140 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, OTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Othmarsingen is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

en: Othmarsingen, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1996 onwards

envi

en: Environment

en:
Resource Title: Field station data (OTF)
    Size: 11582801 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/5b4e810a-ce77-47dc-9e23-ba691ade9192/download/otffield.csv
    Description: Data file.

en:
Resource Title: Site aerial photo (Othmarsingen)
    Size: 7687492 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/d74e4b24-bd75-4ce2-8bb5-4c04b77d8099/download/otfront.jpg
    Description: Site aerial photo from both Othmarsingen stations. Source: Google. 2016. Site aerial photo from both Othmarsingen stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en:
Resource Title: Forest station data (OTB)
    Size: 10501901 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/f5f71a78-9574-4bcc-a326-4d455b6821a4/download/otbforest.csv
    Description: Data file.

en:
Resource Title: Data plot of the field station (OTF)
    Size: 302026 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/663df714-b0fb-45d3-b83f-3e80755a0a1a/download/otfplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Data plot of the forest station (OTB)
    Size: 255873 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/f01faaab-8cee-4b07-b95c-1498f5b09285/download/otbplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Site photo of the field station (OTF)
    Size: 11868194 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/74f4dcb2-e18d-40bb-bb18-8383f907a285/download/otf.jpg
    Description: Site photo of the field station from below (viewing upwards the slope).

en:
Resource Title: Site photo of the forest station (OTB)
    Size: 319164 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/b1937555-6a89-4452-93f9-3cf418382fb6/download/otb.jpg
    Description: Site photo of the forest station from above (viewing downwards the slope).

long-term

display_name: long-term


$oid: OBSOLETE

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

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

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

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

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

fr: Environnement

it: Ambiente

en:
Resource Title: Dataset with GPS-derived snow cover properties and validation data
    Size: 90714 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/cd57ac77-a276-4783-88c9-f52f51552d2c/resource/01f4a113-7ad0-4993-9efa-f30bbe0f0474/download/gps-derived_snow_properties.csv
    Description: This file includes the data as described in the Read-me file.

format: CSV

media_type: text/csv

en:
Resource Title: Read-me
    Size: 109310 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cd57ac77-a276-4783-88c9-f52f51552d2c/resource/d491aadc-0a43-4caa-8b32-09c988ec4841/download/readme.pdf
    Description: The read-me file contains the description of the data provided.

format: PDF

media_type: application/pdf

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:
This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps).
The purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin [Seilaplan]( https://doi.org/10.16904/envidat.software.1) for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting.
The vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019.
Additional notes for vector data:
Please note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API -  https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any  perimeter or area can be digitised freely using the QGIS editing toolbar.
The DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are:
- Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM)
- Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif
This methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed.
Additional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range.
This sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.

en: forest seilaplan accessible-forest qgis openstreetmap geoprocessing

en: Sample Geodata and Software for Demonstrating Geospatial Preprocessing for Forest Accessibility and Wood Harvesting at FOSS4G2019

en:
Resource Title: Railways vector data (close to the sample forest range)
    Size: 50776 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d28614a0-0825-4040-bc1b-e0455b1e4df6/resource/a787f798-0c3d-4cd3-a9d1-c93f51176465/download/osm_railways_export_25832.zip
    Description: EPSG:25832

format: ZIP

media_type: application/zip

en:
Resource Title: Juypter Notebook for Data Preparation
    Size: 29318 bytes
    Format: application/x-ipynb+json
    URL: https://www.envidat.ch/dataset/d28614a0-0825-4040-bc1b-e0455b1e4df6/resource/e0c2a4f8-ee8e-4ca9-b05f-0adf2401c879/download/data_preparation_foss4g2019.ipynb
    Description:

en:
Resource Title: Power lines vector data (close to the area of the sample forest range)
    Size: 66908 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d28614a0-0825-4040-bc1b-e0455b1e4df6/resource/c567f81c-26c9-4122-8fbd-045c55fb73c0/download/osm_powerlines_export_25832.zip
    Description: EPSG:25832

en:
Resource Title: Digitised sample perimeter
    Size: 2083 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d28614a0-0825-4040-bc1b-e0455b1e4df6/resource/710a065d-d50e-4a3d-a993-2a65197cef7b/download/digitized_sample_perimeter.zip
    Description: EPSG:25832

en:
Resource Title: Juypter Notebook for Data Preparation (online)
    Size: 0
    Format: application/x-ipynb+json
    URL: https://nbviewer.jupyter.org/urls/www.envidat.ch/dataset/d28614a0-0825-4040-bc1b-e0455b1e4df6/resource/e0c2a4f8-ee8e-4ca9-b05f-0adf2401c879/download/data_preparation_foss4g2019.ipynb
    Description:

en:
Resource Title: Preview
    Size: 391085 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/d28614a0-0825-4040-bc1b-e0455b1e4df6/resource/729c975c-df90-4af2-979a-af44069dc02f/download/preview.png
    Description:

format: PNG

media_type: image/png

en:
Resource Title: Forest vector data (for sample forest range)
    Size: 288311 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d28614a0-0825-4040-bc1b-e0455b1e4df6/resource/16db97c5-5546-4f80-9cb9-e562637b589c/download/osm_forest_export_25832.zip
    Description: EPSG:25832

en:
Resource Title: DEM (for the area of the sample forest range)
    Size: 1695063 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d28614a0-0825-4040-bc1b-e0455b1e4df6/resource/1bd80d45-a8fd-44dc-b153-7abfa6345d1c/download/eudem_ogdbayern_25m_25832.tif
    Description: EPSG:25832

format: TIFF

media_type: image/tiff

accessible-forest

display_name: accessible-forest

forest

display_name: forest

geoprocessing

display_name: geoprocessing

openstreetmap

display_name: openstreetmap

qgis

display_name: qgis

seilaplan

display_name: seilaplan


en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Schänis in Switzerland where one station is located within a natural mixed forest stand (SCB) with European beech (_Fagus sylvatica_; 130-150 yrs), European silver fir (_Abies alba_; 130-150 yrs) and European ash (_Fraxinus excelsior_; 130-150 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, SCF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Schänis is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

en: Schänis, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1998 onwards

envi

en: Environment

en:
Resource Title: Data plot of the field station (SCF)
    Size: 304254 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/43a2b0ef-6611-4bf2-9d60-60577413515d/download/scfplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Site aerial photo (Schänis)
    Size: 7026512 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/9a6bd255-998b-44c0-9ab2-cc501f9bb78b/download/scfront.jpg
    Description: Site aerial photo from both Schänis stations. Source: Google. 2016. Site aerial photo from both Schänis stations. Retrieved November 11, 2016, from https://www.google.ch/maps

format: jpeg

en:
Resource Title: Field station data (SCF)
    Size: 10669678 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/9bd7e72f-3b65-4250-9f24-f945c4476a0e/download/scffield.csv
    Description: Data file.

en:
Resource Title: Site photo of the forest station (SCB)
    Size: 388600 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/00b2b4fa-a6b1-40b7-b1b7-f5c35c91b1a2/download/scb.jpg
    Description: Site photo of the forest station from below (viewing upwards the slope).

en:
Resource Title: Data plot of the forest station (SCB)
    Size: 253856 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/7a59ef22-0dea-4b48-b92e-8aaca534665c/download/scbplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Site photo of the field station (SCF)
    Size: 8615493 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/68696b24-8c46-48ad-8bb2-c15468b466ce/download/scf.jpg
    Description: Site photo of the field station from above (viewing downwards the slope).

en:
Resource Title: Forest station data (SCB)
    Size: 10593777 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/f5242372-a0bd-42fa-a3be-038395f57134/download/scbforest.csv
    Description: Data file.

en:
Resource Title: Further details on the data repository
    Size: 17153511 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/ee5c2d0d-e229-42e3-9144-37e92827f614/download/furtherdetailsschanis.pdf
    Description: Meta data documentation.

climate-change

display_name: climate-change

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed


en:
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.

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

envidat

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

en: EnviDat: the Environmental Data Portal

en: History of wetlands in Switzerland since 1850

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


data-broedlin-cnp

en: Mircocosm experiment to identify the individual patterns and controls of C, N, and P mobilization in soils under beech forests. Organic and mineral horizons sampled along a nutrient availability gradient in Germany were exposed to either permanent moist conditions or to dry spells in microcosms and quantified the release of inorganic and organic C, N, and P.

en: stoichiometry phosphorus carbon drying-rewetting soil mineralization forest nitrogen dissolved-organic-matter

en: Data Broedlin CNP

title_for_slug: data-broedlin-cnp

en:
Resource Title: Data Broedlin-CNP
    Size: 1189635 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/9dd9a649-405d-413a-ad44-d859ea084bba/resource/c4fce049-b79d-495f-a44d-94f1d59b913a/download/broedlin_cnp_rawdata.xlsx
    Description:

format: XLS

en:
Resource Title: Data Broedlin-CNP-Release
    Size: 1249259 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/9dd9a649-405d-413a-ad44-d859ea084bba/resource/2ec747a1-3a2b-4743-b89f-db13a372c49f/download/broedlin_et_al_cnp_rawdata_v2.xlsx
    Description: Raw data of C-N-P mobilization experiment from Oi, Oe/Oa, and A horizons of beech forest soils along a nutrient availability gradient.

carbon

display_name: carbon

dissolved-organic-matter

display_name: dissolved-organic-matter

drying-rewetting

display_name: drying-rewetting

forest

display_name: forest

mineralization

display_name: mineralization

nitrogen

display_name: nitrogen

phosphorus

display_name: phosphorus

soil

display_name: soil

stoichiometry

display_name: stoichiometry


automatic-classification-of-avalanches

en: This dataset contains the classification and localization results obtained during the automatic classification of avalanches during the winter season 2017.

en: localization machine-learning avalanche seismic monitoring

en: Automatic Classification of Avalanches

title_for_slug: automatic-classification-of-avalanches

envi

en: Environment

avalanche

display_name: avalanche

localization

display_name: localization

machine-learning

display_name: machine-learning

monitoring

display_name: monitoring

seismic

display_name: seismic


en: Data obtained in the free-air CO2 enrichment (FACE) experiment at Hofstetten, NW Switzerland, between 2009 and 2016. This dataset contains analyses of the soil solution throughout the experiment, especially for nitrate, as well as different analyses done at the end of the experiment: ammonium and nitrate captured by ion-exchange resin bags and extracted from soil cores, gross N mineralisation and nitrification measured by isotope dilution.

en: picea-abies face co2 soil forest nitrogen

en: Nitrogen availability under trees exposed to CO2 enrichment (FACE)

en:
Resource Title: Water analyses
    Size: 65553 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/50749920-cf85-4140-8802-54beffcf490e/download/water-analyses.csv
    Description: Analyses of water, especially soil solution

en:
Resource Title: Gross N mineralisation and nitrification
    Size: 1183 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/f6a9e85f-187b-4a55-9f57-e243d14906ab/download/mineralisation-nitrification.csv
    Description: Gross rates of N mineralisation and nitrification (15N dilution)

en:
Resource Title: Soil C and N
    Size: 1298 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/dc99385c-0ab8-4c7f-88cd-cf53ba0aea41/download/soil-c-n.csv
    Description: Analyses of C, N and their stable isotopes in the soil, and soil pH

en:
Resource Title: Collection points
    Size: 453 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/1e7dfaf0-d504-4bab-ae3b-8f96181b4e84/download/points.csv
    Description: Collection points under the trees

en:
Resource Title: Collection of soil solution
    Size: 33840 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/3cfe06e1-c280-4b18-903a-321ceef6044a/download/soil-solution.csv
    Description: Soil solution collected by suction cups

en:
Resource Title: Resin bags
    Size: 1237 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/594288d3-95ff-4ad6-914e-d3e9c1d0ea42/download/resin-bags.csv
    Description: Ammonium, nitrate and their 15N in resin bags

face

display_name: face

picea-abies

display_name: picea-abies


en:
Daily discharge and the related hydro-meteorological variables precipitation, snowmelt, and soil moisture are provided for current (1981-2017) and for future climate conditions (1981-2100) for 307 medium-sized catchments in Switzerland. The catchments have a median catchment area of 117 km². The 307 catchments together form a set representative of the climatological conditions and runoff characteristics in Switzerland. The four variables were simulated at a daily resolution using the hydrological model PREVAH. PREVAH is a conceptual process-based model that was run in this study in its fully distributed version on a 500 m grid (Viviroli et al. 2009a). For the calibration, runoff time series from 140 mesoscale catchments covering the different runoff regimes were used. The model calibration was conducted over the period 1993-1997. Verification was performed on the period 1983-2005 using (i) volumetric deviation (Viviroli et al. 2007) and (ii) benchmark efficiency (Schäfli et al 2007) as objective functions. The calibration and validation procedures are described in detail in Köplin et al. (2010). The parameters for each model grid cell were derived by regionalizing the parameters obtained for the 140 catchments with a procedure based on ordinary kriging (Viviroli et al. 2009b, Köplin et al. 2010).
The calibrated and validated model was then driven with transient meteorological data (precipitation, temperature, radiation, and wind) representing both reference (1981-2017) and future climate conditions (2018-2099). The data were derived from the CH2018 climate scenarios (NCCS 2018) provided by the Swiss National Centre for Climate Services (NCCS). They were obtained from climate experiments produced with different climate modeling chains, consisting of a global and a regional circulation model each, within EUROCORDEX  for three representative concentration pathways (RCP) emission scenarios. Downscaled output of ten climate model chains derived by quantile mapping were considered. The focus was on the chains of the EUR-11 domain with a horizontal resolution of 0.11 degrees (roughly 12.5 km). The climate model chains (GCM, RCM, RCP, and grid resolution) used are listed below:
- ICHEC-EC-EARTH	DMI-HIRHAM5	2.6	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	4.5	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	8.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	2.6	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	4.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	8.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	4.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	8.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	4.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	8.5	EUR-11
*References*:
-	Köplin, N., D. Viviroli, B. Schädler, and R. Weingartner (2010), _How does climate change affect mesoscale catchments in Switzerland? - A framework for a comprehensive assessment_, Advances in Geosciences, 27, 111-119, doi:10.5194/adgeo-27-111-2010.
-	National Centre for Climate Services (2018), CH2018 - _Climate Scenarios for Switzerland_, Tech. rep., NCCS, Zurich.
-	Schäfli, B., and H. V. Gupta (2007), _Do Nash values have value?_, Hydrological Processes, 21, 2075-2080, doi:10.1002/hyp.6825.
-	Viviroli, D., J. Gurtz, and M. Zappa (2007), _The hydrological modelling system PREVAH.  Part II - Physical model description_, Geographica Bernensia, 40, 1-89.
-	Viviroli, D., M. Zappa, J. Gurtz, and R. Weingartner (2009a), _An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools_, Environmental Modelling & Software, 24, 1209-1222, doi:10.1016/j.envsoft.2009.04.001.
-	Viviroli, D., H. Mittelbach, J. Gurtz, and R. Weingartner (2009b), _Continuous simulation  for flood estimation in ungauged mesoscale catchments of Switzerland-Part II: Parameter regionalisation and flood estimation results_, Journal of Hydrology, 377 (1), 208-225, doi:10.1016/j.jhydrol.2009.08.022.

en: hydrology discharge climate-change snowmelt soil-moisture precipitation

envidat

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

en: EnviDat: the Environmental Data Portal

en: Simulated future discharge and climatological variables for medium-sized catchments in Switzerland

en:
Resource Title: Shapefile of 307 catchments in Switzerland
    Size: 103266 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c1c0a28-a23f-4777-88b2-982841adb9b8/resource/05c1a038-40c2-423a-8ad9-f11b43689cf1/download/catchment_shapes.zip
    Description: Shapefile of the 307 medium-sized catchments in Switzerland. The "gridcode" provides the ID of the catchment used in the datafiles.

en:
Resource Title: Daily simulated data for the reference period
    Size: 31447784 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c1c0a28-a23f-4777-88b2-982841adb9b8/resource/a67b4308-25ca-47ea-9aed-f529b8dc7f4d/download/reference.zip
    Description: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the reference period 1981-2017 in mm.

en:
Resource Title: Daily simulated data for the future period
    Size: 1010416415 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c1c0a28-a23f-4777-88b2-982841adb9b8/resource/be17bcca-3f34-414f-960e-bcbdd855ba81/download/climate_simulations.zip
    Description: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the period 1981-2100 in mm for the 307 catchments.

climate-change

display_name: climate-change

discharge

display_name: discharge

hydrology

display_name: hydrology

precipitation

display_name: precipitation

snowmelt

display_name: snowmelt

soil-moisture

display_name: soil-moisture


en: The dataset provides simulated 1) precipitation, 2) discharge, 3) soil moisture, and 4) low-flow simulations for 307 medium-sized catchments in Switzerland for the period 1981-2018. The data were simulated using the hydrological model PREVAH in its gridded-version. The simulated time series are provided at daily resolution. A detailed description of the modeling approach can be found in Brunner et al. 2019 submitted to NHESS.

en: hydrological-simulations prevah precipitation discharge drought-2018 soil-moisture low-flow

en: Hydro-meteorological simulations for the period 1981-2018 for Switzerland

envi

en: Environment

en:
Resource Title: Soil moisture
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/0ad6127b-f7d6-4356-9ac4-283166385578/download/soil_moisture.txt
    Description: Simulated plant-available soil moisture for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm.

format: TXT

media_type: text/plain

en:
Resource Title: Discharge
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/4c11fec4-0846-48a0-8dfe-9f7f5a4b574f/download/discharge.txt
    Description: Simulated discharge for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm/d.

en:
Resource Title: Shapefile of 307 catchments in Switzerland
    Size: 103266 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/7ebed8a1-98ce-4833-b1dd-64246bd07e5f/download/catchment_shapes.zip
    Description: Shapefile of 307 catchments for which simulations of precipitation, discharge, soil moisture, and low flow are provided. The OBJECTID entry corresponds to the data columns in the textfiles of the simulated data provided.

en:
Resource Title: Precipitation
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/0f551cfd-804d-4f3a-80d9-c33562ea8b45/download/precipitation.txt
    Description: Simulated precipitation for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm/d.

en:
Resource Title: Low-flow storage
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/a1338c95-09df-4bce-8d9c-7b059ae2f6a1/download/low_flow.txt
    Description: Simulated low-flow storage for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm.

hydrological-simulations

display_name: hydrological-simulations

low-flow

display_name: low-flow

prevah

display_name: prevah


en:
The files contain the datasets used to produce Figures 2, 3, and 4 of the manuscript ([doi: 10.1002/2016GL071822](http://dx.doi.org/10.1002/2016GL071822)).
 Manuscript Abstract:
Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

en: model sediment-transport snow mars erosion

en: Energy- and momentum-conserving model of splash entrainment in sand and snow saltation

en:
Resource Title:
    Size: 1434 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/8ab9bafb-62f5-4420-80da-a2a96d22be74/download/figure3a.txt
    Description: Datasets of Figure 3a

en:
Resource Title:
    Size: 2904 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/709f4330-9a35-4685-aac8-347067a5e483/download/figure4b.txt
    Description: Datasets of Figure 4b

en:
Resource Title:
    Size: 3626 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/6ee21796-08ad-4069-a4cb-da6c35ffede7/download/figure4a.txt
    Description: Datasets of Figure 4a

en:
Resource Title:
    Size: 2190 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/82479779-1b20-486f-b4bc-414c6024c25d/download/figure3b.txt
    Description: Datasets of Figure 3b

en:
Resource Title:
    Size: 3587 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/1f30b883-fc62-4bbf-a8f5-88f716008097/download/figure2.txt
    Description: Datasets of Figure 2

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow


snow-depth-mapping

en:
The available datasets are snow depth maps with a spatial resolution of 2m generated from image matching of ADS 80/100 data. Image acquisition took place at peak of winter (time when the thickest snowpack is expected). The snow depth maps are the difference of a summer DSM from the winter DSM of the corresponding date . The summer DSM used is a product of image matching of ADS 80 data from summer 2013. In the available products buildings, vegetation and outliers were masked (set to NoData).
For the elimination of buildings the TLM layer (swisstopo) was used, because this layer might not represent exactly the
state of infrastructure at time of image acquisition, it is possible that mainly in dense settlement some buildings were not successfully masked. For the relevant area above treeline the masking of buildings showed good results. Vegetation got masked for a height above ground - 1m and was detected in a combination of summer and winter data sets. As Outliers were considered unrealistic snow depths caused by a failure of the image matching algorithm. Snow depths - 15m and smaller than - -15m were classified as outliers. Negative snow depth were kept, because of an uncertainty in image orientation accuracy. It is expected that in regions with negative snow depth also positive snow depth are underestimated by the same amount, which means that an estimation of snow volume should be carried out summing up the absolute values of snow depth (also the negative ones). For volume estimation in small regions the user has to take into account, that orientation accuracy of the images is roughly around 1-2 GSD (30cm), which propagates directly to the snow depth product. Areas which are not covered by snow got assigned a value of 0 as snow depth.
The work is published in:
Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C., (2015). Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9 (1), 229-243. doi: 10.5194/tc-9-229-2015

en: snow-water-equivalent snow-depth avalanche image-matching aerial-imagery dsm 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: EnviDat: the Environmental Data Portal

en: Snow Depth Mapping

title_for_slug: snow-depth-mapping

en:
Resource Title: Snow depth map 20160309
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/ceae68a6-28f9-43f4-8ff5-9715588ade57/download/snowmap_20160309_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

en:
Resource Title: Snow depth map 20140417
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/5cf5d3a5-555d-429e-9819-6c93ccce6dfc/download/snowmap_2014_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.18 m

en:
Resource Title: Snow depth map 20100416
    Size: 412324171 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/4ba96052-9e3e-4b7a-9968-2dcc58fc96c0/download/snowmap_2010_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20130415
    Size: 412272526 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/da3ca703-c629-45c0-8dac-e78645b0fa5e/download/snowmap_2013_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20160420
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/bc035833-3193-4394-af92-f8d195d5e034/download/snowmap_20160420_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

en:
Resource Title: Snow depth map 20120320
    Size: 412272526 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/aff41055-8e6e-4287-b52d-2c2fb61633c2/download/snowmap_2012_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20160126
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/9229984f-b417-45e5-8dbe-031f295d0406/download/snowmap_20160126_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m
Because of very diffuse light conditions at time of image acquisition the quality of the resulting snow depth values are in some regions quite poor.

en:
Resource Title: Snow depth map 20150415
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/578e95ce-ffa0-4fc6-8109-d9653b2c622a/download/snowmap_2015_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

en:
Resource Title: Snow depth mapping in high-alpine catchments using digital photogrammetry
    Size: 8122296 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/3b711e29-cea1-48e8-8de6-a008850c4f94/download/snow-depth-mapping-in-high-alpine-catchments.pdf
    Description:

aerial-imagery

display_name: aerial-imagery

avalanche

display_name: avalanche

dsm

display_name: dsm

image-matching

display_name: image-matching

snow-depth

display_name: snow-depth

snow-hydrology

display_name: snow-hydrology

snow-water-equivalent

display_name: snow-water-equivalent


en:
Throughfall, litterflow and soil solution were sampled during one whole year under five Oriental beech trees in a mixed Hyrcanian beech forest. The amounts of Ca2+, Mg2+, K+ and Na+ in these fluxes were calculated based on their concentrations and the sampled volumes, and subsequently compared with the respective fluxes in the rainfall and soil solution of an adjacent forest gap.
In addition six soil profiles, one close to every single tree and one in the forest gap, were analyzed for pH, CaCO3, organic matter and texture.

en: potassium calcium magnesium biogeochemical-cycling fagus-orientalis-lipsky

en: Base cation dynamics in an Oriental beech forest

envi

en: Environment

biogeochemical-cycling

display_name: biogeochemical-cycling

calcium

display_name: calcium

fagus-orientalis-lipsky

display_name: fagus-orientalis-lipsky

magnesium

display_name: magnesium

potassium

display_name: potassium


seilaplan

en:
Cable-based technologies have been a backbone for harvesting on steep slopes. The layout of a single cable road is challenging because one must identify intermediate support locations and heights that guarantee structural safety and operational efficiency while minimizing set-up and dismantling costs. Seilaplan optimizes the layout of a cable road by
Seilaplan stands for Cable Road Layout Planner. Seilaplan is able to calculate the optimal rope line layout (position and height of the supports) between defined start and end coordinates on the basis of a digital elevation model (DEM).
The program is designed for Central European conditions and is designed on the basis of a fixed suspension rope anchored at both ends. For the calculation of the properties of the load path curve an iterative method is used, which was described by Zweifel (1960) and was developed especially for standing skylines. When testing the feasibility of the cable line, care is taken that 1) the maximum permissible stresses in the skyline are not exceeded, 2) there is a minimum distance between the load path and the ground and 3) when using a gravitational system, there is a minimum inclination in the load path. The solution is selected which has a minimum number of supports in the first priority and minimizes the support height in the second priority.
The newly developed method calculates the load path curve and the forces occurring in it more accurately than tools available on the market to date (status 2019) and is able to determine the optimum position and height of the intermediate supports.
The reason for the more accurate results of the new tool is the assumption that the skyline is anchored at both end points. Forest cable yarders used in Europe have a skyline that is fixed at both ends. The behaviour of fixed-anchored suspension ropes is very difficult to describe mathematically and cannot be solved analytically. For this reason, simplified linearized assumptions have so far been used in the forestry sector, which corresponds to the behaviour of a weight-tensioned suspension rope and is known as the Pestal method (1961). Weight-tensioned suspension ropes are used for passenger transport.
For the calculation of the load path curve we use an iterative method, which was described by Zweifel (1960) and developed especially for fixed anchored suspension ropes. This makes mathematics much more demanding, but leads to more accurate and realistic results. Since there are no current models which describe the installation costs with adequate accuracy, the solution sought is the one which has a minimum number of supports in the first priority and minimises the support height in the second priority (Figure 2). The presented method is the first one, which starts from a fixed anchored supporting rope and identifies the mathematically optimal column layout at the same time. In contrast to methods that assume a weight-tensioned suspension rope, this approach achieves more realistic solutions with longer spans and lower support heights, which ultimately leads to lower installation costs. Background information on rope mechanics and calculation methods is documented in Bont and Heinimann (2012).
License: GNU, General Public License, Version 2 or newer.
Literature:
Bont, L., & Heinimann, H. R. (2012). Optimum geometric layout of a single cable road. European journal of forest research, 131(5), 1439-1448.

en: qgis cable-yarding cable-planning python steep-terrain-harvesting catenary-load-path software

en: Seilaplan

title_for_slug: seilaplan

cable-planning

display_name: cable-planning

cable-yarding

display_name: cable-yarding

catenary-load-path

display_name: catenary-load-path

python

display_name: python

qgis

display_name: qgis

software

display_name: software

steep-terrain-harvesting

display_name: steep-terrain-harvesting


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.

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

envidat

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

en: EnviDat: the Environmental Data Portal

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

en:
Resource Title: topsoil.zip
    Size: 8375186227 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.431/topsoil.zip
    Description: 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:
Resource Title: 100cm.zip
    Size: 8235599790 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.431/100cm.zip
    Description: 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:
Resource Title: 5cm.zip
    Size: 8836895212 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.431/5cm.zip
    Description: 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.

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


en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for one meteorological station in Lens in Switzerland which is located within a natural coniferous forest with Scots pine (_Pinus sylvestris_; 150-170 yrs)) as dominant tree species. The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lens is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

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

en:
Resource Title: Forest station data (LEB)
    Size: 9240564 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fea7c28b-0a5b-4f38-b3df-c1ce66c2cf43/resource/21e6ffa5-4cc5-4310-be18-91c2d579163c/download/lebforest.csv
    Description: Data file.

en:
Resource Title: Site photo of the forest station (LEB)
    Size: 382534 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/fea7c28b-0a5b-4f38-b3df-c1ce66c2cf43/resource/15eb26e6-46a4-43e6-8cdb-fd7072968eb3/download/leb.jpg
    Description: Site photo of the forest station from below (viewing upwards the slope)

en:
Resource Title: Data plot of the forest station (LEB)
    Size: 234314 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/fea7c28b-0a5b-4f38-b3df-c1ce66c2cf43/resource/569d951e-97b2-44e0-9ad5-d861994a78eb/download/lebplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed


bats-in-beaver-systems

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

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

en: Bats in beaver systems

title_for_slug: bats-in-beaver-systems

envi

en: Environment

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

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

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

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

format: OCTET

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

beaver

display_name: beaver

castor

display_name: castor

chiroptera

display_name: chiroptera

deadwood

display_name: deadwood

ecosystem-engineer

display_name: ecosystem-engineer

flying-arthropods

display_name: flying-arthropods

habitat-heterogeneity

display_name: habitat-heterogeneity

nature-conservation

display_name: nature-conservation

wetland

display_name: wetland


en:
**Article: "Species Species composition shapes canopy microclimate and foliar traits without modifying photosynthetic thermal acclimation in a beech-oak ecotone"**
Authors: **Janisse Deluigi**, Charlotte Grossiord, Alvaro Poretti, Lorenz Walthert, Christoph Bachofen
The study was conducted along a south-exposed elevational gradient ranging from 770 to 860 m a.s.l. in a central alpine valley (46°10`14``N, 7°10`01``E, Saillon, Switzerland). Along the elevational gradient, we selected three forest stands characterized by high coverage of mature European beech (Fagus sylvatica L.) and downy oak (Quercus pubescens Willd.) trees, with are naturally distributed in three species combinations: one pure beech stand (i.e., at least 80% of the basal area) at 860 m a.s.l. , one mixed beech-oak stand (i.e., similar relative abundances of the two species – at least 40% of the basal area each – and minimal presence of other tree species) at 785 m a.s.l., and one pure oak stand (i.e., at least 80% of the basal area) at 770 m a.s.l. An additional forest clearing of around 0.04 ha next to the pure oak stand was selected as reference for conditions outside the forest  (i.e., clearing or gap). At each forest stand, we selected five healthy, mature, overstory trees per tree species, resulting in a total of 20 individuals (5 individuals x 2 species x 2 mixture combinations, i.e., mixed vs. pure forest stand).
**Dataset 1: Climatic conditions at the study sites**
In 2023 and 2024 we monitored climatic conditions at each forest stand and in the clearing using climatic stations with air temperature, relative humidity and radiation sensors installed at 1.8 m height in a central position relative to the selected trees for each site. The meteo station in the clearing site had additionally a rain gauge and wind sensor.
**Dataset 2: Tree and canopy sizes**
Once in 2023 we measured tree height and diameter at breast height of all selected trees using a vertex hypsometer and a caliper. In August 2023 and 2024 we estimated canopy size measuring the height at which canopy starts (CS), canopy depth (= tree height - CS) and maximum canopy radius as the average of two orthogonal measurements (south and east direction) using a vertex hypsometer. We also estimated canopy total leaf area using species- and site-specific allometric equations from collected branches upscaled to the tree level.
**Dataset 3: Microclimatic conditions measured in tree canopies**
We monitored canopy microclimatic conditions in 2023 and 2024 attaching one air temperature and air humidity sensor (HOBO) on one branch at the top and one branch at the bottom of the south-exposed side of the canopy for each selected tree in June 2023.
**Dataset 4: Physiological traits**
During three field campaigns (June, August, September) per year (2023, 2024) we measured temperature response curves of leaf net photosynthesis and dark respiration. As in-situ measurements were not possible, tree-climbers collected one representative branch at the top and the bottom of the canopy from each selected tree at each site. Estimates of the thermal optimum of photosynthesis (Topt), photosynthetic rate at Topt (Aopt), respiration rate at a standard temperature of 25°C (R25) and thermal sensitivity of respiration (Q10) were extracted from the temperature response curves of photosynthesis and respiration, respectively.
Leaf water potentials at predawn and midday, as well as leaf chlorophyll content, were also measured on the same day for each selected tree at each site.
**Dataset 5: Physiological traits - specific leaf area and leaf size**
In August 2023 and 2024 we collected a random subset of 10 representative fully developed leaves of different sizes from a representative branch harvested at the top and bottom of the canopy of each selected tree to estimate the specific leaf area (SLA) and leaf size (average of the 10 leaves).
**Dataset 6: Soil water potentials**
Hourly soil water potentials and soil temperature were recorded during the two years of measurements (2023, 2024) at each forest site at different soil depths: 20 cm, 80 cm, 140 cm and 200 cm.

en: photosynthesis species-interaction acclimation forest-canopy climate-change respiration

envidat

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

en: EnviDat: the Environmental Data Portal

en: Dataset Article "Species composition shapes canopy microclimate and foliar traits without modifying photosynthetic thermal acclimation in a beech-oak ecotone", Deluigi et al.

envi

en: Environment

en:
Resource Title: 1_Climatic conditions at the study sites Saillon 2023-2024.csv
    Size: 22240297 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/85ccee2d-7e73-40b2-ad63-c6ce1b030e26/download/1_climatic-conditions-at-the-study-sites-saillon-2023-2024.csv
    Description: #Dataset 1: Climatic conditions at the study sites
Datetime = date and time (CEST)
PAR	= photosynthetic photon flux density (µmol m-2 s-1)
RH = air relative humidity (%)
Temp = air temperature (°C)
site = forest site (pure beech, mixture, pure oak) and clearing (gap)
date = date (mm/dd/yyyy)
Precip	= rain precipitation (mm)
Wind = wind speed (m s-2)
Gusts = wind gusts (m s-2)
Direction = direction of the wind (°)
month = month of the year (1:12)
VPD = vapor pressure deficit (kPa)
Time = time of the day (HH:MM:SS)
Year = year of measurement

en:
Resource Title: 2_Tree size and canopy Saillon 2023-2024.csv
    Size: 4465 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/b1b06195-b354-404b-b2e2-c44217446c54/download/2_tree-size-and-canopy-saillon-2023-2024.csv
    Description: #Dataset 2: Tree and canopy sizes
Year = year of measurement
Site = forest site (pure beech, mixture, pure oak)
Species = tree species (B = beech, O = downy oak)
Tree = tree ID within each site (5 trees per site and tree species)
height = tree height (m)
DBH = diameter at breast height (cm)
sapwood_depth = depth of sapwood from tree cores (cm)
sapwood_area = area of sapwood in tree trunks (cm2)
Al_As = ratio between branch total leaf area (Al, cm2) and branch section area (As, cm2) from sampled branches
WT_LA = canopy total leaf area estimated for each tree using allometric equations (m2)
radius_max = average maximum radius of the canopy (m) from two orthogonal measurements
radius_east = radius of the canopy (m) measured direction east
radius_south = radius of the canopy (m) measured direction south
crown_start = height at which the canopy starts (m)
canopy_depth = difference between tree height and height at which the canopy starts (m)
Asymetric = TRUE/FALSE to indicate whether the canopy was asymetric
Direction = direction to which the canopy was asymetric

en:
Resource Title: 5_SLA and leaf size measurements Saillon 2023-2024.csv
    Size: 4444 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/b825d938-273b-43a5-83a8-9d5c89c895e5/download/5_sla-and-leaf-size-measurements-saillon-2023-2024.csv
    Description: #Dataset 5: Physiological traits - specific leaf area and leaf size
Year = year of measurement
Site	= forest site (pure beech, mixture, pure oak)
Species	= tree species (B = beech, O = downy oak)
Tree = tree ID within each site (5 trees per site and tree species)
Canopy_level = canopy level (top, bottom)
SLA	= specific leaf area (cm2 g-1)
leaf_size = leaf area (cm2)

en:
Resource Title: 6_Soil moisture and temperature Saillon 2023-2024.csv
    Size: 16861102 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/305fbfa7-56fa-4f62-88d2-f5b87cb51452/download/6_soil-moisture-and-temperature-saillon-2023-2024.csv
    Description: #Dataset 6: Soil water potentials
Datetime = date and time (CEST)
Site	= forest site (pure beech, mixture, pure oak)
Depth	= soil depth (cm)
WP_corr	 = soil water potential corrected by temperature (MPa)
Temp = soil temperature (°C)
Date = date of measurement (mm/dd/yyyy)
Year = year of measurement

en:
Resource Title: 4_Physiological measurements Saillon 2023-2024.csv
    Size: 46961 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/e9f0e85f-b12b-4b29-a4e3-44600d37c34a/download/4_physiological-measurements-saillon-2023-2024.csv
    Description: #Dataset 4: Physiological traits
Year = year of measurement
Campaign = campaign of measurement (June, August, September)
Site	= forest site (pure beech, mixture, pure oak)
Species	= tree species (B = beech, O = downy oak)
Tree = tree ID within each site (5 trees per site and tree species)
Canopy_level = canopy level (top, bottom)
WP_predawn = leaf water potential at predawn (MPa)
WP_midday = leaf water potential at midday (MPa)
CHL = chlorophyll content (CCI)
Date = date of measurement (mm/dd/yyyy)
Aopt = photosynthetic rate at thermal optimum (µmol m-2 s-1)
sd_err_Aopt = standard error of Aopt estimates from temperature response curves of photosynthesis
b	= curvature coefficient of the temperature response curve of photosynthesis
sd_err_b = standard error of b estimates  from temperature response curves of photosynthesis
Topt = thermal optimum of photosynthesis (°C)
sd_err_Topt = standard error of Topt estimates from temperature response curves of photosynthesis
R25	= respiration rate at a standard temperature of 25°C (µmol m-2 s-1)
sd_err_R25 = standard error of R25 estimates from temperature response curves of dark respiration
Q10	= thermal sensitivity of respiration (i.e., increase in respiration rates for a 10°C increase in measurement temperature)
sd_err_Q10 = standard error of Q10 estimates from temperature response curves of dark respiration
Collection_time = time of the day at which the branch was collected (morning, midday)

en:
Resource Title: 3_Microclimatic measurements day and night Saillon 2023-2024.csv
    Size: 179804 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/69ce25f7-f502-4461-8336-0e0400182d03/download/3_microclimatic-measurements-day-and-night-saillon-2023-2024.csv
    Description: #Dataset 3: Microclimatic conditions measured in tree canopies
Site	= forest site (pure beech, mixture, pure oak)
Species	= tree species (B = beech, O = downy oak)
Tree = tree ID within each site (5 trees per site and tree species)
Time = time of the day (HH:MM:SS)
Tair_top	= air temperature at the top of the canopy (°C)
Tair_low	= air temperature at the bottom of the canopy (°C)
VPD_top = vapor pressure deficit at the top of the canopy (kPa)
VPD_low = vapor pressure deficit at the bottom of the canopy (kPa)
Tair_gap	= air temperature in the clearing (i.e., outside the forest) (°C)
VPD_gap = vapor pressure deficit in the clearing (kPa)
Tair_T_L	= difference in air temperature between the top and bottom of the canopy (°C)
VPD_T_L = difference in vapor pressure deficit between the top and bottom of the canopy (kPa)
Tair_T_gap	 =  difference in air temperature between the top of the canopy and the clearing (°C)
VPD_T_gap = difference in vapor pressure deficit between the top of the canopy and the clearing (kPa)
Tair_L_gap	= difference in air temperature between the bottom of the canopy and the clearing (°C)
VPD_L_gap = difference in vapor pressure deficit between the bottom of the canopy and the clearing (kPa)

acclimation

display_name: acclimation

climate-change

display_name: climate-change

forest-canopy

display_name: forest-canopy

photosynthesis

display_name: photosynthesis

respiration

display_name: respiration

species-interaction

display_name: species-interaction


landesschwerenetz

de: Bundesamt für Landestopografie swisstopo, Vermessung

en: Federal office of topography swisstopo, survey

fr: Office fédéral de topographie, mensuration

it: Ufficio federale di topografia swisstopo, misurazione

de: Aktuell verwendete Basisstationen des Landesschwerenetzes. Diese Stationen werden regelmässig neu vermessen und dienen als Referenzpunkte für gravimetrische Projekte.Das Rückgrat des Netzes bilden die absoluten Schweremessungen. Diese werden verdichtet durch relative Schweremessungen auf Fixpunkten der Landesvermessung.

fr: Stations actuelles du réseau gravimétrique national. Ces stations sont observées régulièrement et servent comme points de référence pour des projets gravimétriques.La base de ce réseau est formée par les stations absolues qui sont densifiées par des mesures relatives sur des points fixes de la mensuration nationale.

it: Stazioni di base della rete gravimetrica nazionale attualmente utilizzate. Queste stazioni vengono regolarmente sottoposte a nuove misurazioni e fungono da punti di riferimento per i progetti gravimetrici. La base della rete è costituita dalle misurazioni gravimetriche assolute. Queste vengono intensificate attraverso misurazioni gravimetriche relative eseguite su punti fissi della misurazione nazionale.

en: Current base stations of the national gravity network. These stations are observed regularly and serve as reference Points for gravimetric projects.The backbone of this network is formed by absolute gravity stations. They are densified by relative measurements on Benchmarks of national Survey.

de: Landesschwerenetz

fr: Réseau gravimétrique national

it: Rete gravimetrica nazionale

en: National Gravity Network

fr: Le centre de compétence de la Confédération suisse pour les informations géographiques, c'est-à-dire pour la description, la représentation et l’archivage de données à référence spatiale.

de: Das Kompetenzzentrum der Schweizerischen Eidgenossenschaft für Geoinformation, d.h. für die Beschreibung, Darstellung und Archivierung von raumbezogenen Geodaten.

en: The centre of competence for the Swiss Confederation responsible for geographical reference data, for instance the description, representation and archiving of geographic spatial data.

it: Il centro d’eccellenza della Confederazione Elvetica per geoinformazione, cioè per la descrizione, rappresentazione e archiviazione dei dati georeferenziati (geodati).

en: Federal Office of Topography swisstopo

fr: Office fédéral de topographie swisstopo

political_level: confederation

de: geocat.ch Permalink

fr: geocat.ch permalien

it: geocat.ch link permanente

en: geocat.ch permalink

spatial: Schweiz (mit grenznahem Ausland)

title_for_slug: landesschwerenetz

value: Swisstopo - Geocat Harvester

regi

de: Regionen und Städte

en: Regions and cities

fr: Régions et villes

it: Regioni e città

de: Vorschau map.geo.admin.ch

en: Preview map.geo.admin.ch

fr: Aperçu map.geo.admin.ch

it: Previsione map.geo.admin.ch

de: Map (Preview) Vorschau map.geo.admin.ch

format: HTML

de: WMS-BGDI Dienst, Layer "Schweregrundnetz"

fr: Service WMS-IFDG, couche "Réseau de base gravimétrique"

it: Servizio WMS-IFDG, strato "Rete gravimetrica di base"

en: WMS-FSDI service, layer "Gravimetric base network"

format: XML

media_type: application/xml

de: RESTful API von geo.admin.ch

fr: RESTful API de geo.admin.ch

it: RESTful API da geo.admin.ch

en: RESTful API from geo.admin.ch

de: Download von data/geo.admin.ch


de:
Diese Dateien helfen dabei die fachlichen (VM-Nummer, TU-Code, Variante/Datum) und die technischen Swiss Journey ID (SJYID) Identifikatoren in Beziehung zueinander zu setzen. Denn die SJYID ist nicht über all diese Werte hinweg eindeutig. Dadurch können Sie bei Bedarf die technischen Identifikatoren anhand der fachlichen Identifikatoren finden oder umgekehrt.

Die neue Version 2 (seit 2025-11-25) präsentiert die Daten neu als syntaktisch korrekte, reguläre CSV-Datei.

Daten für 2025 und älter sind in unserem Datenarchiv zu finden: https://archive.opentransportdata.swiss

en:
This list links business (VM-Number, TU-Code, Variant/Date) and technical Swiss Journey ID (SJYID) identifiers. This means that, if necessary, technical identifiers can be found from business identifiers, or vice versa.

The new version 2 (since 2025-11-25) now presents the data as a syntactically correct, regular CSV file.

Data for 2025 and older can be found in our data archive: https://archive.opentransportdata.swiss

fr:
La liste met en relation les identifiants-métier (No prestation, Code ET, Variante/Date) et identifiants-technique ID des voyage suisse (SJYID). Cela permet, en cas de besoin, de trouver les identifiants techniques à partir des identifiants métier ou inversement.

La nouvelle version 2 (depuis le 25.11.2025), qui présente désormais les données sous la forme d’un fichier CSV régulier et correct d’un point de vue syntaxique.

Les données pour 2025 et antérieures se trouvent dans nos archives de données : https://archive.opentransportdata.swiss

it:
L'elenco collega gli identificatori commerciali (numero di servizio, codice ET, data) e gli identificatori tecnici ID viaggio svizzero (SJYID). Ciò significa che, se necessario, gli identificatori tecnici possono essere trovati dagli identificatori professionali o viceversa.

La nuova versione 2 (dal 2025 novembre 2025) presenta i dati come un regolare file CSV sintatticamente corretto.

I dati del 2025 e precedenti sono disponibili nel nostro archivio dati: https://archive.opentransportdata.swiss

de: Swiss Journey ID (SJYID) 2026 - V2

en: Swiss Journey ID (SJYID) 2026 - V2

fr: Swiss Journey ID (SJYID) 2026 - V2

it: Swiss Journey ID (SJYID) 2026 - V2

oevch

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.

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

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

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.

de: Geschäftsstelle Systemaufgaben Kundeninformation (SBB AG)

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

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

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

de: Cookbook (Documentation)

en: Cookbook (Documentation)

fr: Cookbook (Documentation)

it: Cookbook (Documentation)

spatial: Spatial

value: Opentransportdata - DCAT Harvester

tran

de: Verkehr

en: Transport

fr: Transports

it: Trasporti


de:
Neue Version v2 der Stammdaten und Metadaten vom System atlas (https://atlas.app.sbb.ch), bereitgestellt seit 7. Januar 2026 (atlas-v2).

Dieser Datensatz enthält Informationen zur Barrierefreiheit von Billett- und Informationsschaltern.

en:
New version v2 of the master data and metadata of the atlas system (https://atlas.app.sbb.ch), provided since 7 January 2026 (atlas-v2).

This dataset contains information on the accessibility of ticket and information desks.

fr:
Nouvelle version v2 des données de base et métadonnées du système atlas (https://atlas.app.sbb.ch), mise à disposition depuis le 7 janvier 2026 (atlas-v2).

Ce jeu de données contient des informations sur l'accessibilité des guichets de vente de billets et d'information.

it:
Nuova versione v2 dei dati di base e dei metadati del sistema atlas (https://atlas.app.sbb.ch), forniti dal 7 gennaio 2026 (atlas-v2).

Questo set di dati contiene informazioni sull'accessibilità degli sportelli di biglietteria e informazione.

de: Schalter - Barrierefreiheit (v2)

en: Contact points - Accessibility (v)

fr: Guichets - Accessibilité (v2)

it: Sportelli - Accessibilità (v2)


de:
Neue Version v2 der Stammdaten und Metadaten vom System atlas (https://atlas.app.sbb.ch), bereitgestellt seit 7. Januar 2026 (atlas-v2).

Dieser Datensatz enthält Informationen zur Barrierefreiheit von Parkplätzen.

en:
New version v2 of the master data and metadata of the atlas system (https://atlas.app.sbb.ch), provided since 7 January 2026 (atlas-v2).

This dataset contains information on the accessibility of car parks.

fr:
Nouvelle version v2 des données de base et métadonnées du système atlas (https://atlas.app.sbb.ch), mise à disposition depuis le 7 janvier 2026 (atlas-v2).

Cet jeu de données contient des informations sur l'accessibilité des places de stationnement.

it:
Nuova versione v2 dei dati di base e dei metadati del sistema atlas (https://atlas.app.sbb.ch), forniti dal 7 gennaio 2026 (atlas-v2).

Questo set di dati contiene informazioni sull'accessibilità dei parcheggi.

de: Parkplatz - Barrierefreiheit (v2)

en: Parking lot - Accessibility (v2)

fr: Parking - Accessibilité (v2)

it: Parcheggio - Accessibilità (v2)


de:
OJP ist das API eines Routenplanners. Mit dem API können Trips geplant werden, Fahrten nachverfolgt, Abfahrts- und Ankunftsanzeiger gebaut werden. OJP arbeitet von Koordinate zu Koordinate, Adresse zu Adresse.

Für den Zugriff muss ein API-Key verwendet werden, siehe: https://opentransportdata.swiss/de/howto-access-apis

en:
OJP is the API's Route Planner. The API can be used to plan trips, track journeys, and build departure and arrival indicators. OJP works from coordinate to coordinate, address to address.

An API key must be used for access, see: https://opentransportdata.swiss/en/howto-access-apis

fr:
OJP est le planificateur d'itinéraire de l'API. L'API peut être utilisée pour planifier des voyages, suivre les trajets et créer des indicateurs de départ et d'arrivée. OJP travaille de coordonnée à coordonnée, d'adresse en adresse.

Pour l'accès, une clé API doit être utilisée, voir : https://opentransportdata.swiss/fr/howto-access-apis

it:
OJP è il Route Planner dell'API. L'API può essere utilizzata per pianificare viaggi, tenere traccia dei viaggi e creare indicatori di partenza e arrivo. OJP lavora da coordinata a coordinata, da indirizzo a indirizzo.

Per l'accesso è necessario utilizzare una chiave API, vedi: https://opentransportdata.swiss/it/howto-access-apis

en: ojp api multi-modal-journey inter-modal-journey boarding-and-alighting wheelchair-accessibility service-location delay occupancy car-transport real-time-traffic cost-calculation parking-space on-demand service-areas stop-zone stop-place stop mode-of-transportation service-point freight-point operating-point line partial-line swiss-line-id swiss-business-organisation-id swiss-administration-id timetable journey swiss-journey-id message real-time costs prices departure arrival without-transport-service on-demand-bus train bus bicycle cableways ski-lifts car motorised-private-transport motorist passenger wheelchair-user cyclist mobility-service-provider

de: ojp embag api multi-modales-reisen inter-modales-reisen ein--und-ausstieg dienstleistungsort verspatung belegung autoverlad echtzeitverkehr kostenberechnung parkplatz on-demand bedarfsverkehr bediengebiete haltestellenbereich haltekante haltestelle verkehrsmittel dienststelle bedienpunkt betriebspunkt linie teillinie swiss-line-id swiss-business-organisation-id swiss-administration-id fahrplan fahrt swiss-journey-id hinweis echtzeit kosten preise abfahrt ankunft reise ohne-beforderungsleistung on-demand-bus zug bus fahrrad seilbahn skilift auto motorisierter-individualverkehr automobilist passagier rollstuhlfahrer fahrradfahrer mobilitatsdienstleister rollstuhlzuganglichkeit

it: ojp lmeca api multi-modal-transport inter-modal-transport entrata-e-uscita accessibilita-alle-sedie-a-rotelle posizione-del-servizio ritardo occupazione trasporto-macchina traffico-in-tempo-reale calcolo-dei-costi parcheggio on-demand su-richiesta aree-di-servizio zona-di-fermata bordo-di-fermata fermata mezzo-di-trasporto posto-di-servizio punto-di-servizio punto-operativo linea linea-parziale id-linea-svizzera id-organizzazione-aziendale-svizzera id-amministrazione-svizzera orario viaggio id-viaggio-svizzero indicazione tempo-reale progetto costi prezzi partenza arrivo senza-servizio-di-transporto autobus-a-richiesta treno autobus bicicletta funivie impianti-di-risalita macchina trasporto-privato-motorizzato automobilist passaggero persone-in-sedia-a-rotelle ciclista fornitore-di-servizi-di-mobilita

de: Cookbook

en: Cookbook

fr: Cookbook

it: Cookbook

de: Howto: Access our APIs with API Keys

en: Howto: Access our APIs with API Keys

fr: Howto: Access our APIs with API Keys

it: Howto: Access our APIs with API Keys

spatial: Schweiz

de: Open Journey Planner 2020

en: Open Journey Planner 2020

fr: Open Journey Planner 2020

it: Open Journey Planner 2020

de: Open Journey Planner

en: Open Journey Planner

fr: Open Journey Planner

it: Open Journey Planner

identifier: ojp-api

a-la-demande

display_name: a-la-demande

abfahrt

display_name: abfahrt

accessibilita-alle-sedie-a-rotelle

display_name: accessibilita-alle-sedie-a-rotelle

accessibilite-des-fauteuils-roulants

display_name: accessibilite-des-fauteuils-roulants

ankunft

display_name: ankunft

api

display_name: api

aree-di-servizio

display_name: aree-di-servizio

arrival

display_name: arrival

arrivee

display_name: arrivee

arrivo

display_name: arrivo

auto

display_name: auto

autobus

display_name: autobus

autobus-a-richiesta

display_name: autobus-a-richiesta

automobilist

display_name: automobilist

automobiliste

display_name: automobiliste

autoverlad

display_name: autoverlad

bedarfsverkehr

display_name: bedarfsverkehr

bediengebiete

display_name: bediengebiete

bedienpunkt

display_name: bedienpunkt

belegung

display_name: belegung

betriebspunkt

display_name: betriebspunkt

bicicletta

display_name: bicicletta

bicycle

display_name: bicycle

bicyclette

display_name: bicyclette

bicycliste

display_name: bicycliste

boarding-and-alighting

display_name: boarding-and-alighting


de:
Subset der Tarife im öV Schweiz im OSDM-Format

Wichtig: Die vorhandenen Daten stellen keine hinreichende Bedingung für den Ticket-Verkauf durch Dritte dar.

en:
Subset of fares in Swiss public transport in OSDM format
Important: The existing data do not constitute a sufficient condition for ticket sales by third parties.

fr:
Subset des tarifs des TP suisses au format OSDM.
Important : les données disponibles ne constituent pas une condition suffisante pour la vente de billets par des tiers.

it:
Sottoinsieme delle tariffe dei trasporti pubblici svizzeri in formato OSDM.

Importante: i dati esistenti non costituiscono una condizione sufficiente per la vendita di biglietti da parte di terzi.

en: osdm data cost-calculation cost price fare without-transport-service mobility-service-provider

de: osdm embag daten kostenberechnung kosten preise tarife ohne-beforderungsleistung mobilitatsdienstleister

fr: osdm lmeta donnees calcul-de-couts couts prix tarifs sans-prestation-de-transport prestataire-de-mobilite

it: osdm lmeca dati calcolo-dei-costi costi prezzi tariffe senza-servizio-di-transporto fornitore-di-servizi-di-mobilita

de: Spezifikation: OSDM

en: Spezifikation: OSDM

fr: Spezifikation: OSDM

it: Spezifikation: OSDM

de: (Beta) Open Sales and Distribution Model (OSDM) Offline File

de: OSDM-Offline Schweiz

en: OSDM Offline Switzerland

fr: OSDM Offline Suisse

it: OSDM Offline Svizzera

identifier: osdm-file

calcolo-dei-costi

display_name: calcolo-dei-costi

calcul-de-couts

display_name: calcul-de-couts

cost

display_name: cost

cost-calculation

display_name: cost-calculation

costi

display_name: costi

couts

display_name: couts

data

display_name: data

daten

display_name: daten

dati

display_name: dati

donnees

display_name: donnees

embag

display_name: embag

fare

display_name: fare

fornitore-di-servizi-di-mobilita

display_name: fornitore-di-servizi-di-mobilita

kosten

display_name: kosten

kostenberechnung

display_name: kostenberechnung

lmeca

display_name: lmeca

lmeta

display_name: lmeta

mobilitatsdienstleister

display_name: mobilitatsdienstleister

mobility-service-provider

display_name: mobility-service-provider

ohne-beforderungsleistung

display_name: ohne-beforderungsleistung

osdm

display_name: osdm

preise

display_name: preise

prestataire-de-mobilite

display_name: prestataire-de-mobilite

prezzi

display_name: prezzi

price

display_name: price

prix

display_name: prix

sans-prestation-de-transport

display_name: sans-prestation-de-transport

senza-servizio-di-transporto

display_name: senza-servizio-di-transporto


de:
Neue Version v2 der Stammdaten und Metadaten vom System atlas (https://atlas.app.sbb.ch), bereitgestellt seit 7. Januar 2026 (atlas-v2).

Dieser Datensatz enthält Informationen zur Barrierefreiheit auf Ebene Haltekante.

en:
New version v2 of the master data and metadata of the atlas system (https://atlas.app.sbb.ch), provided since 7 January 2026 (atlas-v2).

This dataset contains information about the accessibility at stop place level.

fr:
Nouvelle version v2 des données de base et métadonnées du système atlas (https://atlas.app.sbb.ch), mise à disposition depuis le 7 janvier 2026 (atlas-v2).

Cet ensemble de données contient des informations sur l'accessibilité au niveau des bordures d'arrêt.

it:
Nuova versione v2 dei dati di base e dei metadati del sistema atlas (https://atlas.app.sbb.ch), forniti dal 7 gennaio 2026 (atlas-v2).

Questo set di dati contiene informazioni sul' accessibilità a livello di bordi di fermata.

de: Haltekanten - Barrierefreiheit (v2)

en: Stop places - Accessibility (v2)

fr: Bordures d'arrêt - Accessibilité (v2)

it: Bordi di fermata - Accessibilità (v2)

oevch

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.

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

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

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.

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)

de: Cookbook (Documentation)