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: geoprocessing forest openstreetmap accessible-forest qgis seilaplan

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

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

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: 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: 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: 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: 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: 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

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


$oid: OBSOLETE

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

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

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

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).

format: jpeg

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: 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

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.

format: CSV

media_type: text/csv

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: 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.

format: PDF

media_type: application/pdf

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: 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

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


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

en: History of wetlands in Switzerland since 1850

format: ZIP

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

en: Data Broedlin CNP

title_for_slug: data-broedlin-cnp

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.

format: XLS

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:

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 monitoring seismic avalanche machine-learning

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: 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:
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 snowmelt discharge soil-moisture climate-change precipitation

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

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.

media_type: application/zip

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.

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: 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: nitrogen soil co2 picea-abies face forest

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

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: 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: 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: 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: 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

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

face

display_name: face

forest

display_name: forest

picea-abies

display_name: picea-abies


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

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

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.

format: TXT

media_type: text/plain

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: 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.

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.

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.

hydrological-simulations

display_name: hydrological-simulations

low-flow

display_name: low-flow

prevah

display_name: prevah


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-depth snow-water-equivalent avalanche image-matching dsm aerial-imagery snow-hydrology

en: Snow Depth Mapping

title_for_slug: snow-depth-mapping

envi

en: Environment

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 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 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 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 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:

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 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 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 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

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:
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 erosion mars snow

envidat

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

en: EnviDat: the Environmental Data Portal

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

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: 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: 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

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: 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

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow


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

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

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: 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 Neunkirch in Switzerland where one station is located within a natural deciduous forest stand (NEB) with European beech (_Fagus sylvatica_; 160 yrs), sycamore maple (_Acer pseudoplatanus_; 160 yrs) and lime trees (_Tilia sp._; 110 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NEF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Neunkirch is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

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

en:
Resource Title: Data plot of the field station (NEF)
    Size: 313178 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/084cafd7-038f-4922-a36c-af54c00399cb/download/nefplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Site photo of the forest station (NEB)
    Size: 5116944 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/49887857-0fad-44d6-a56c-58e8851a65a8/download/neb.jpg
    Description: Site photo of the forest station from below (viewing upwards the slope).

en:
Resource Title: Forest station data (NEB)
    Size: 10603940 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/0dc8b0c2-02f7-4052-bdfc-ac967a916888/download/nebforest.csv
    Description: Data file.

en:
Resource Title: Site photo of the field station (NEF)
    Size: 1877748 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/f8bb24e8-a6a2-4cf5-bf88-f688b7a4e488/download/nef.jpg
    Description: Site photo of the field station from the side.

en:
Resource Title: Site aerial photo (Neunkirch)
    Size: 8951072 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/68f3a7a3-21b6-45cd-8578-6232edf6d1ef/download/nefront.jpg
    Description: Site aerial photo from both Neunkirch stations. Source: Google. 2016. Site aerial photo from both Neunkirch stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en:
Resource Title: Field station data (NEF)
    Size: 10713187 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/f7dc0cd8-8dd9-49f6-bfee-47d2945a23df/download/neffield.csv
    Description: Data file.

en:
Resource Title: Data plot of the forest station (NEB)
    Size: 229180 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/20934806-9510-4de8-b2a6-acb1f9831de3/resource/64f63815-a1df-4f25-92d3-75e2c19b2abd/download/nebplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

climate-change

display_name: climate-change

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


en: This dataset consists of data related to capillary rise experiments performed with neutron radiography. There are 4 videos of capillary rise experiments as well as the files used to perform the inverse fitting with Hydrus. The videos show the upward flow of water in glass columns filled with sand and snow or sand, gravel, and snow. The videos show the 2D evolution of the unitless optical density with time. The Hydrus files were used to fit the parameter values of the Mualem-van Genuchten model. The experiments were performed at the Paul Scherrer Institute (PSI) in Villigen, Switzerland.

en: snow pore-water soil measurements water transport

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: Capillary rise rise experiments in snow using neutron radiography

en:
Resource Title: Hydrus_inverse_fitting_files.zip
    Size: 749844 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/a4e140c9-e73a-402e-9b59-63b6000d5bb6/download/hydrus_inverse_fitting_files.zip
    Description: The Hydrus files used for the inverse fitting of the hydraulic conductivity.

en:
Resource Title: depricated.txt
    Size: 496 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/74c3db20-eaed-40de-a880-f042010cf6cc/download/readme.txt
    Description: Description of the videos

en:
Resource Title: capillary_rise_experiment_videos.zip
    Size: 10552661 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/4d5ee580-c1b4-49d4-868f-971b8383afa7/download/capillary_rise_experiment_videos.zip
    Description: Videos of the capillary rise experiments

en:
Resource Title: README.txt
    Size: 1089 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/5631a26d-f9f0-4548-9e78-e6eecdffcee5/download/readme.txt
    Description: Descriptions of the nomenclature, Hydrus files, and videos.

measurements

display_name: measurements

pore-water

display_name: pore-water

snow

display_name: snow

soil

display_name: soil

transport

display_name: transport

water

display_name: water


en:
This database contains 1957 distribution maps of species from Fagales and Pinales constructed based on a method integrating polygon mapping and SDMs (Lyu et al., 2022).
To construct the maps, we first collected occurrence data from 48 different sources. According to the number of occurrences after data cleaning, three kinds of maps are constructed: (1) For species with more than 20 occurrences, we performed SDM and polygon mapping described in Lyu et al. (2022) and select the integration of the two layers as the distribution range; (2) For species with more than 4 but less than 20 occurrences, we only use polygon mapping to draw the distribution range; (3) For species with less than 4 occurrences, a 20-km buffer was generated around the occurrences as the distribution range. The maps were manually checked and evaluated (see Note S3 and Table S9 in Lyu et al., 2022 for details).

en: species-distribution-model fagales species-occurrence pinales species-richness species-range-map

en: Species distribution maps of Fagales and Pinales (GDPlants)

envi

en: Environment

en:
Resource Title: Species range maps of species in Fagales and Pinales (with enough occurrences)
    Size: 37517772 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/aee8c2bd-ca0b-4de0-a41f-940dc11984e6/resource/6c946cd2-e08b-44e0-8fda-4ab01b6b43b9/download/species_maps.zip
    Description: species_map.zip includes species 1690 range maps generated based on the integrated method described in Lyu et al., (2022). File names with (polygon) indicate that this map is only generated by polygon mapping, as there are not enough occurrences for SDMs.

en:
Resource Title: Occurrence maps for species of Fagales and Pinales with few records
    Size: 32315283 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/aee8c2bd-ca0b-4de0-a41f-940dc11984e6/resource/9239265c-dba9-413d-9fc6-40beb3cb7368/download/point_buffers.zip
    Description: Point_buffer.zip includes 267 occurrence maps of species that do not have enough occurrence data for polygon mapping.

fagales

display_name: fagales

pinales

display_name: pinales

species-distribution-model

display_name: species-distribution-model

species-occurrence

display_name: species-occurrence

species-range-map

display_name: species-range-map

species-richness

display_name: species-richness


en:
To assess the possible consequences of potential changes in snow accumulation and temperature and their impact on avalanche hazard, we introduce a comprehensive multi-step framework. It includes the analysis of climate change scenarios as well as the modeling of future snow covers and the simulation of avalanches in a case study region in central Switzerland.
Using a downscaling and a quantile mapping approach, we considered the high emission RCP8.5 from the CH2018 Swiss climate change scenarios and simulated a potential snow cover of more than 100 future winters with the snow cover model SNOWPACK. Changing snow accumulation and snow cover temperature was taken into account for two future time frames. The changed parameters were used in the RAMMS::EXTENDED avalanche simulation software on large scale.

en: hazard avalanche-mapping ramms climate-change new-snow avalanche

en: A novel approach for bridging the gap between climate change scenarios and avalanche hazard indication mapping

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

climate-change

display_name: climate-change

hazard

display_name: hazard

new-snow

display_name: new-snow

ramms

display_name: ramms


en:
This dataset includes the FORTRAN code of the FSM2trans model version used in the paper: Quéno et al., Snow redistribution in an intermediate-complexity snow hydrology modelling framework, The Cryosphere, 2024.
The FSM2trans code is derived from the FSM2 model (Essery et al., 2015) and its variant FSM2oshd (Mott et al., 2023). In this model, we implemented and adapted the snowdrift model SnowTran-3D (Liston et al., 2007) and the avalanching model SnowSlide (Bernhardt and Schulz, 2010).
This dataset does not include the processing scripts to prepare meteorological input data for the model, provided as bin files.

en: avalanche snow-modelling snowpack source-code snowdrift

en: FSM2trans code

en:
Resource Title: namelist.zip
    Size: 1490 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/d2398461-752f-4984-a944-2e565ed0c1ce/resource/b59836a9-e725-4276-92d2-d3e17efc0966/download/namelist.zip
    Description:

en:
Resource Title: README.txt
    Size: 957 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d2398461-752f-4984-a944-2e565ed0c1ce/resource/7446d1e9-634a-4da1-b7ef-7ffc28ea61c4/download/readme.txt
    Description:

en:
Resource Title: code.zip
    Size: 90894 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/d2398461-752f-4984-a944-2e565ed0c1ce/resource/2f7b6697-4863-4ab8-8975-11603ba6dd5e/download/code.zip
    Description:

snow-modelling

display_name: snow-modelling

snowdrift

display_name: snowdrift

snowpack

display_name: snowpack

source-code

display_name: source-code


sensitivity-of-modeled-snow-instability

en: We investigated the sensitivity of modeled snow instability to meteorological input data using SNOWPACK. We therefore used input data from the automatic weather station at the Weissfluhjoch field site for the year 2016-2017. We investigated three scenarios and performed 14'000 simulations for each scenario.  The dataset contains extracted output data from modeled SNOWPACK simulations, including setup files to reproduce the simulations. For further information read the README file.

en: numerical-avalanche-forecasting snow-cover-modeling snowpack snow-instability global-sensitivity-analysis

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: Sensitivity of modeled snow instability

title_for_slug: sensitivity-of-modeled-snow-instability

en:
Resource Title: Manually observed snow profiles
    Size: 12725 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/5bd23cea-d4e3-4f87-8b0c-bfa3dc82afec/download/manual_profiles.zip
    Description: Manually observed snow profiles at Weissfluhjoch field site for winter season 2016-2017, including layer depth, hand hardness, grain size and grain shape for each layer.

en:
Resource Title: Case SL
    Size: 277264559 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/7635f568-e96c-4901-a385-c369150aaad6/download/case_sl.zip
    Description: Extracted output data for case SL. Here biases were introduced to meteorological input data during the period of slab formation. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

en:
Resource Title: Case WL
    Size: 342942228 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/84ee8947-54aa-40d6-86bb-b6e0ffc14d25/download/case_wl.zip
    Description: Extracted output data for case ALL. Here biases were introduced to meteorological input data during the period of weak layer formation. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

en:
Resource Title: Reference run
    Size: 9909880 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/7eb0f753-02d2-4592-b822-cf91745ea196/download/reference.zip
    Description: Reference run for the sensitivity analysis at Weissfluhjoch field site for winter season 2016-2017. Meteorological data from the automatic weather stations are used. No biases were introduced to the input data.

en:
Resource Title: Case ALL
    Size: 346790131 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/fd47ae3d-77a9-4f79-8c95-57b11de523bb/download/case_all.zip
    Description: Extracted output data for case ALL. Here biases were introduced to meteorological input data during the whole simulation period. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

global-sensitivity-analysis

display_name: global-sensitivity-analysis

numerical-avalanche-forecasting

display_name: numerical-avalanche-forecasting

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability


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

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

en: Reproducibility dataset for CRYOWRF validation

envi

en: Environment

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

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

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

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

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

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

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

cryowrf

display_name: cryowrf

reproducibility

display_name: reproducibility

surface-mass-balance

display_name: surface-mass-balance


en:
We established our study sites in the cities of Basel, Lugano and Zurich, and their peri-urban forests. We characterised urban tree cover of each city using a rectangular grid with squares of 100x100 m. Within each square, we measured the area covered by urban trees using the European Union's Copernicus Land Monitoring Service information, Urban Atlas Street Tree Layer 2018 [https://doi.org/10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c](https://doi.org/10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c).
Then we assigned each square to four categories of urban tree cover that roughly represented the main types of urban uses:
1) low cover, industrial/commercial areas, 0-20% tree cover;
2) intermediate cover, residential areas, 20-40% tree cover;
3) high cover, urban parks and cemeteries, 40-60% tree cover;
4) peri-urban forests (natural/semi-natural forests), 60-100% tree cover.
-br/--br/-
Our study sites consisted of eight 1.2 km-long transects in each city, equally distributed across the four tree cover categories.  We designed an experimental measurements of bird predation rate on herbivore insect larvae using artificial caterpillars. They mimicked a variety of common, cryptically-coloured herbivorous species, which are usually preyed by birds. We designed caterpillars with green water-resistant modelling clay (Staedtler Noris®), 4-6 cm long and approximately 0.5 cm wide. Caterpillars were threaded to a thin (Ø = 0.6 mm) zinc-plated iron wire and tethered to branches of trees or bushes at a height up to 2 m from the ground. We placed 2-4 caterpillar mimics every 200 m along each transect (five points per transect) or, when not possible due to absence of suitable branches, within 200 m from the point.
In total, we placed 270 caterpillar mimics at 115 points during the late breeding season (June-July 2023). Caterpillar mimics were checked after 10-14 days and replaced with new ones at new locations within 10 m from the previous ones. During each of the two visits, we counted the number of bird predation marks.

en: urban pest-invasion urban-ecology periurban urban-biodiversity biodiversity birds biodiversity-experiment insect-herbivores

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: Urban bird predation on artificial caterpillars

biodiversity

display_name: biodiversity

biodiversity-experiment

display_name: biodiversity-experiment

birds

display_name: birds

insect-herbivores

display_name: insect-herbivores

periurban

display_name: periurban

pest-invasion

display_name: pest-invasion

urban

display_name: urban

urban-biodiversity

display_name: urban-biodiversity

urban-ecology

display_name: urban-ecology


en:
Base data which were used for the methodology projecting future regional snow depths based on temperature scenarios. This study was supported by Seilbahnen Schweiz, Schweiz Tourismus, Seco and Speed2Zero.
The data is split in three folders:
- Literature-Fit dataset
- Literature-Validation dataset
- Projections
The Literature-Fit dataset is the data which was used to retrieve the fit parameters a, Delta b and Delta c, for different elevations and temperature scenarios, which can be found in data/literature_fit/fitfactor.csv. Those fit factors were used to project future snow depths from climatological snow depths. Futhermore, this dataset was used to link decreases in mean snow depths for different seasonal periods to the NDJFMA period (November until April, in total six months), those differences in reduction values can be found in data/literature_fit/difference_decrease_4differentperiods.csv.  The raw reference and future snow depths of different studies and different elevation and temperature scenarios (dt) can be found in data/literature_fit/literature_data/* where each file is named by data_author_station_dt.csv.
The Literature-Validation dataset can be found in data/literature_validation/literature_data.csv contains the reference, RCP scenario, reference period, projected period and corresponding temperature scenarios. Furthermore, it contains region, elevation and relative decreases with corresponding seasonal periods, and the number of days with a certain amount of snow during the reference period and the projected period, if literature reported these values.
The folder projections contains mean snow depths, 5th and 95th percentile snow depth for each day of the year for the reference period and a temperature scenario of +2°C for all four stations Engelberg, Maloja, Saanenmöser and Weissfluhjoch.

en: snow-climatology future snow-depth alps climate-change

en: Literature based approach to estimate future snow

alps

display_name: alps

climate-change

display_name: climate-change

future

display_name: future

snow-climatology

display_name: snow-climatology

snow-depth

display_name: snow-depth


lwf-tea-bag-sites

en:
Decomposition of plant litter is a key process for the transfer of carbon and nutrients in ecosystems. Carbon contained in the decaying biomass is released to the atmosphere as respired CO2, and may contribute to global warming. Litterbag studies have been used to improve our knowledge of the drivers of litter decomposition, but they lack comparability because litter quality is plant species-specific. The use of commercial tea bags as a standard substrate was suggested in order to harmonize studies, where green tea and rooibos represent more labile and more recalcitrant C compounds as surrogates of local litter.
The tea bag approach was implemented on eight sites of the Swiss long-term Forest Ecosystem Research (LWF) network (https://www.wsl.ch/LWF). This allowed us to take advantage from the existing infrastructure and data from a previous litterbag study with local litter. In Beatenberg and Schaenis, additional elevation transects were established (1200-1800 m and 540-1150 m, respectively) to examine particularly the effect of temperature on decomposition. In Pfynwald (https://www.wsl.ch/de/ueber-die-wsl/versuchsanlagen-und-labors/flaechen-im-wald/pfynwald.html) and Salgesch, infrastructure of running projects was used to examine the effect of drought and understory removal, respectively. In Novaggio, tea bags were incubated in summer and winter to study the effect of seasonality particularly precipitation. Tea bags are collected after 3, 12, 24, and 36 months; for the two time-shifted experiments additionally after 6 and 9 months.
The study has two primary objectives. Firstly, it contributes to TeaComposition initiative (http://teacomposition.org/) which aims at investigating long-term litter decomposition and its key drivers at present as well as under different future climate scenarios using a common protocol and standard litter (tea) across nine terrestrial biomes. Secondly, the data are used to further develop decomposition models such as Yasso (http://en.ilmatieteenlaitos.fi/yasso) which is used by several countries, including Switzerland to estimate the annual carbon fluxes in dead wood, litter, and soil for reporting in National Greenhouse Gas Inventories under the United Nations Framework Convention on Climate Change and the Kyoto Protocol.

en: forest verification carbon green-tea roiboos modeling litter tea-bag decomposition

en: LWF-Tea bag sites

title_for_slug: lwf-tea-bag-sites

carbon

display_name: carbon

decomposition

display_name: decomposition

forest

display_name: forest

green-tea

display_name: green-tea

litter

display_name: litter

modeling

display_name: modeling

roiboos

display_name: roiboos

tea-bag

display_name: tea-bag

verification

display_name: verification


en: A Young 81000 sonic anemomenter was deployed at Gotschnagrat (LON: 46.859 LAT: 9.849) to record three components of the wind velocity (u, v, w in [m s&8254; &185;]) and air temperature (Ts in [°C]). The anemomenter was mounted in direction North at a height of 1.5 m above snow surface at the beginning. The time within each data set is given in UTC+1. Instrument specifications can be found [here](http://www.youngusa.com/Manuals/81000-90(I).pdf) .

en: wind-velocity wind-speed raclets wind wind-direction anemometer

en: Snow Drift Station - 3D Ultrasonic

envi

en: Environment

en:
Resource Title: Sonic time
    Size: 513827192 bytes
    Format: application/x-npy
    URL: https://www.envidat.ch/dataset/efa1aa57-2aef-41de-8d36-d5847445a2dc/resource/d345ded1-1574-41f3-ae30-d257dc87b926/download/sonic_time.npy
    Description: The data set contains the time in YYYY-mm-dd HH:MM:SS.sss for the anemometer data. The time is given in UTC+1.

en:
Resource Title: Sonic wind component v
    Size: 513827192 bytes
    Format: application/x-npy
    URL: https://www.envidat.ch/dataset/efa1aa57-2aef-41de-8d36-d5847445a2dc/resource/a485c9f7-72e0-474c-9bc8-3d9aea695a30/download/sonic_v.npy
    Description: The data contains values for v direction of the wind in a sampling frequency of 20 Hz.
Erroneour spikes were filterd in two steps.

1. Define moving window uₓ = u(i-3:i+3)
2. If u(i)-mean(uₓ) > 2*std(uₓ):u(i) = NaN

Frozen detectors resulted in continuous zero values (not filtered).
The wind speed and direction were calculated as follows:

wind speed = sqrt(u² + v²)
wind direction = 180° + (180° / PI)* arctan2 (-u, -v)

en:
Resource Title: Sonic wind component u
    Size: 513827192 bytes
    Format: application/x-npy
    URL: https://www.envidat.ch/dataset/efa1aa57-2aef-41de-8d36-d5847445a2dc/resource/54108b5f-082b-483b-8ac0-a56780e44217/download/sonic_u.npy
    Description: The data contains values for u direction of the wind in a sampling frequency of 20 Hz.
Erroneour spikes were filterd in two steps.

1. Define moving window uₓ = u(i-3:i+3)
2. If u(i)-mean(uₓ) > 2*std(uₓ):u(i) = NaN

Frozen detectors resulted in continuous zero values (not filtered).
The wind speed and direction were calculated as follows:

wind speed = sqrt(u² + v²)
wind direction = 180° + (180° / PI)* arctan2 (-u, -v)

en:
Resource Title: Sonic temperature
    Size: 513827192 bytes
    Format: application/x-npy
    URL: https://www.envidat.ch/dataset/efa1aa57-2aef-41de-8d36-d5847445a2dc/resource/cc5577c8-af52-4af3-a16c-bef536dbe363/download/sonic_ts.npy
    Description: The data set contains values of temperature (°C) measured with the anemometer at a sampling frequency of 20 Hz.

en:
Resource Title: Sonic wind component w
    Size: 513827192 bytes
    Format: application/x-npy
    URL: https://www.envidat.ch/dataset/efa1aa57-2aef-41de-8d36-d5847445a2dc/resource/a0d480eb-e00a-4508-9d76-16da99c61b61/download/sonic_w.npy
    Description: The data contains values for w direction of the wind in a sampling frequency of 20 Hz.
Erroneour spikes were filterd in two steps.

1. Define moving window uₓ = u(i-3:i+3)
2. If u(i)-mean(uₓ) > 2*std(uₓ):u(i) = NaN

Frozen detectors resulted in continuous zero values (not filtered).
The wind speed and direction were calculated as follows:

wind speed = sqrt(u² + v²)
wind direction = 180° + (180° / PI)* arctan2 (-u, -v)

anemometer

display_name: anemometer

raclets

display_name: raclets

wind

display_name: wind

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

wind-velocity

display_name: wind-velocity


en:
Monitoring terrestrial mammals through eDNA in rivers of northern Namibia
In 2022, we collected 20 water samples from 10 stations two rivers of Namibia. Samples were taken from the side of the river. At each station, we performed two filtration replicates using a peristaltic pump to conduct environmental DNA (eDNA) sampling. Each filtration targeted a maximum duration of 30 minutes, during which approximately 30 liters of water were filtered through each capsule. After filtration, the water inside the capsules was removed, and the capsules were filled with 50 ml of conservation buffer for preservation at room temperature. We followed strict contamination control protocols throughout both the fieldwork and laboratory processes, adhering to the guidelines of Valentini et al. (2016). We used eDNA primers targeting bacteria, bivalves, fish, vertebrates (V05) and all Eukaryotes (Euka03). To prevent contamination, each sample was processed using disposable gloves and single-use filtration equipment. The MiSeq Reagent Kit v3 (2x75 bp) (Illumina, San Diego, CA, USA) was used for paired-end sequencing at a theoretical sequencing depth of 200,000 reads per sample.
Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

en: bivalves eukaryotes edna namibia metabarcoding

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: Environmental DNA Freshwater Namibia Namibia 2022

bivalves

display_name: bivalves

edna

display_name: edna

eukaryotes

display_name: eukaryotes

metabarcoding

display_name: metabarcoding

namibia

display_name: namibia


en:
Research question / purpose
Timber is widely used for protection measures in torrent control. However, life span of woody constructions such as timber check dams is limited mainly due to fungal decay. In practice a controversial discussion has been going on if either Norway spruce (Picea abies) or silver fir (Abies alba) is more enduring and if bark removal increases resistance against fungal decay.
Description
This dataset contains monitoring information on a series of 15 timber check dams built in 1996 in Hergiswil, Switzerland. The constructions were alternatively realised with Norway spruce and silver fir, half of them each with remaining and removed bark, respectively. The data includes the identification of decayed zones with a simple practical approach (i.e. measurement of the penetration depth of a slotted screwdriver No. 3) from a total of 12 repeated surveys from 2001 to 2025.
The following information is contained (by column and column title):
•	Identification of decayed zone (column title “Decay_Id”)
•	Year of survey (column title “Year”)
•	Identification of check dam (column title “Check dam”)
•	Degree of decay (column title “Degree of decay”): 2 = reduced wood strength (penetration depth 2-10 mm); 3 = low wood strength (penetration depth - 10 mm)
•	Sectors 1 to 7 of check dams (column title “Sector”)
•	Element of check dam (column title “Element”): LH (longitudinal log, German: “Längsholz”), Z (transverse log, German: “Zange”), FH (infill log, German: “Füllholz”)
Plan of check dams and additional information on monitoring surveys: survey information (PDF)

en: fungal-decay check-dam long-term-behaviour timber-structure torrent-control

en: Long-term behaviour of timber constructions in torrent control

en:
Resource Title: decay_envidat.csv
    Size: 13209 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/25bbe989-95e3-4705-9807-248a0ab14884/resource/7db6f23d-ff20-4991-a626-616e2be7aa65/download/decay_envidat.csv
    Description:

en:
Resource Title: Survey Information.pdf
    Size: 357932 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/25bbe989-95e3-4705-9807-248a0ab14884/resource/37048955-41d9-4145-96cd-90c3edc4c83b/download/survey-information.pdf
    Description:

check-dam

display_name: check-dam

fungal-decay

display_name: fungal-decay

long-term-behaviour

display_name: long-term-behaviour

timber-structure

display_name: timber-structure

torrent-control

display_name: torrent-control


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 Chironico in Switzerland where one station is located within a natural coniferous forest stand (CIB) with Norway spruce (_Picea abies_; 160-180 yrs) and European silver fir (_Abies alba_; 140-160 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CIF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Chironico is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

en: Chironico, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 2000 onwards

en:
Resource Title: Data plot of the field station (CIF)
    Size: 9381698 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/5993f35c-f254-4f4e-b603-82f1999524f4/download/ciffield.csv
    Description: Data file.

en:
Resource Title: Site aerial photo (Chironico)
    Size: 8272921 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/c1beb5d4-0bb5-449c-9d68-428f5d7053dc/download/cifront.jpg
    Description: Site aerial photo from both Chironico stations. Source: Google. 2016. Site aerial photo from both Chironico stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en:
Resource Title: Forest station data (CIB)
    Size: 9148615 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/d2125be5-ab36-4a79-8873-100747c9304a/download/cibforest.csv
    Description: Data file.

en:
Resource Title: Site photo of the forest station (CIB)
    Size: 2398813 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/d06f65e8-1a2a-4fc1-9b01-6f8c5f1854ef/download/cib.jpg
    Description: Site photo of the forest station from below (viewing upwards the slope).

en:
Resource Title: Site photo of the field station (CIF)
    Size: 595220 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/6d4df6e5-55ca-4706-84b8-02095fc7247e/download/cif.jpg
    Description: Site photo of the field station from the side.

en:
Resource Title: Data plot of the forest station (CIB)
    Size: 245044 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/806df5aa-7383-4d16-8318-4c26237ddd03/download/cibplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Data plot of the field station (CIF)
    Size: 298986 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/dbf82da9-d637-4660-ab4c-50943b190dde/download/cifplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

climate-change

display_name: climate-change

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


en:
Predicting future climatic conditions at high spatial resolution is essential for many applications in science. Here we present data for monthly time series of precipitation and minimum and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation sums at ~5km spatial resolution globally for the years 1850-2100. We validated the performance of the downscaling algorithm by comparing model output with observed climates for the years 1950-2069.
CHELSA_cmip5_ts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

en: orographic-precipitation climate-change cmip5 precipitation-amount air-temperature

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: High resolution monthly precipitation and temperature timeseries for the period 2006-2100

envi

en: Environment

air-temperature

display_name: air-temperature

orographic-precipitation

display_name: orographic-precipitation

precipitation-amount

display_name: precipitation-amount


en:
Individual genotypes assessed at six nuclear microsatellite loci (two alleles per locus) for individuals of the butterfly Melanargia galathea (Marbled white) that were collected throughout Switzerland, along the regular grid of the Biodiversity Monitoring (BDM) of Switzerland. For each individual, the sampling site (number) and the genotype are given. Note that due to privacy restrictions, the original geographic coordinates remain disclosed. For original coordinates, data holders should be contacted (Swiss Federal Office for the Environment; Biodiversity Monitoring Switzerland).
The data refer to the following publication: Terzer et al., Distinct spatial patterns of genetic structure and diversity in the butterfly Marbled White (Melanargia galathea) inhabiting fragmented grasslands. Conservation Genetics, https://doi.org/0.1007/s10592-023-01593-4.

en: conservation-genetics monitoring melanargia-galathea genetic-diversity genetic-structure

en: Nuclear microsatellite genotypes of the butterfly Melanargia galathea

conservation-genetics

display_name: conservation-genetics

genetic-diversity

display_name: genetic-diversity

genetic-structure

display_name: genetic-structure

melanargia-galathea

display_name: melanargia-galathea

monitoring

display_name: monitoring


en:
One individual per species, vitality class (low and high) and height class (eight classes: 0–10, 11–20, 21–35, 36–60, 61–90, 91–130, 131–200 and 201–500 cm) was randomly selected and harvested in each of the six plots. This resulted in a sample of 82, 80 and 89 living individuals of A. platanoides, A. pseudoplatanus and F. sylvatica, respectively.
 Additionally stems of dead Acer spp. and F. sylvatica trees that had died within the last three years (2015–2018) were randomly harvested, matching the height classes of the harvested living trees wherever possible. In total, 179 dead young trees (60 A. platanoides, 72 A. pseudoplatanus and 47 F. sylvatica) were collected.
 Variables:
* species_code: a_pla - Acer platanoides, a_pse - Acer pseudoplatanus, f_syl - Fagus sylvatica
* species: as above
* dummy: 0 - living individual, 1 - dead individual
* LAR_cm2_g: leaf area ratio or ratio of leaf area to total plant biomass, [cm2/g]
* tree_age: in years
* avg_ring_micron: average width of the last 5 rings in tree life excluding the last ring
* dry_mass_g: aboveground and belowground biomass
* DLI: direct light index (measured only under living individuals)
* BLI: diffuse light index (measured only under living individuals)
* GLI: global light index

en: acer shade-tolerance lar fagus mortality-rate dominance regeneration

en: Mortality of regeneration: Acer spp. and Fagus sylvatica

en:
Resource Title: Survival_AFT_R_script
    Size: 18015 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/8d9df0cd-f20c-423f-a4ab-71fc213871de/resource/6ff5b7a2-6662-41ab-8c2d-68f688cde189/download/survival_script.r
    Description: The R-script of survival analysis for accelerated failure time model

en:
Resource Title: Mortality of regeneration
    Size: 60209 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8d9df0cd-f20c-423f-a4ab-71fc213871de/resource/37fb69d9-c553-4931-89ba-31857ac15c04/download/imputed.csv
    Description: Acer platanoides, Acer pseudoplatanus and Fagus sylvatica living and dead juveniles (0-500 cm in height) grown in the deep shade of a prime beech-dominated forest.

acer

display_name: acer

dominance

display_name: dominance

fagus

display_name: fagus

lar

display_name: lar

mortality-rate

display_name: mortality-rate

regeneration

display_name: regeneration

shade-tolerance

display_name: shade-tolerance


kamerun-sammlungen-am-mrz

de:
Das Museum Rietberg verfügt seit seiner Gründung über erste Objekte aus Kamerun; im Laufe der Jahre wurde dieser Bestand kontinuierlich erweitert. Im Rahmen eines CAS in Provenienzforschung hat Jonas Lendenmann einen umfassenden Überblick über die Provenienzen dieser Sammlung erarbeitet. Seine Studie bietet nicht nur detaillierte Einblicke in die Herkunft der Objekte, sondern liefert auch wichtige Kontextinformationen zur Sammlungsgeschichte, zu Ausstellungstätigkeiten sowie zu Kooperationen des Museums.
Die vollständige Arbeit steht auf der Webseite des Museum Rietberg zum Download bereit.
Der vorliegende Datensatz basiert auf den von Jonas Lendenmann recherchierten und aufbereiteten Informationen zu den Sammlungsobjekten aus Kamerun.

de: kamerun provenienzforschung sammler github

stadt-zurich

fr: Vous trouverez ici les données de la ville de Zürich. En parallèle, Open Data Zürich a son propre portail Open Data où vous pouvez trouver également des manuels et des documents sur le traitement des données. À de rares exceptions près, toutes les données publiées par Open Data Zürich sont sous une licence «Creative Commons Zero».

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

en: Here you find all publicly available data published by Open Data Zürich. In addition, the city of Zurich runs its own Open Data Portal, where you find manuals and documentation about the handling of datasets. With only a few exceptions, all datasets from Open Data Zürich are licensed under «Creative Commons Zero».

it:
Open Data Zürich propone qui dati pubblici della città di Zurigo, pronti alla libera utilizzazione.
La città di Zurigo dispone parallelamente di un proprio portale Open Data, sul quale sono disponibili anche istruzioni e documentazioni per contestualizzare i datasets.
A parte poche eccezioni tutte le datasets della città di Zurigo hanno una licenza «Creative Commons Zero».

de: Stadt Zürich

en: City of Zurich

fr: Ville de Zurich

it: Cità di Zurigo

political_level: commune

name: Museum Rietberg Zürich, Präsidialdepartement

de: Kamerun Sammlungen am MRZ

title_for_slug: kamerun-sammlungen-am-mrz

value: ZH - DCAT Harvester

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

fr: Éducation, culture et sport

it: Istruzione, cultura e sport

format: JSON

media_type: application/json

github

display_name: github

kamerun

display_name: kamerun

provenienzforschung

display_name: provenienzforschung

sammler

display_name: sammler


brunnenfotos-der-stadt-zurich

de: Dieser Datensatz ergänzt den [Geodatensatz mit den Brunnen der Stadt Zürich](https://data.stadt-zuerich.ch/dataset/geo_brunnen). Er enthält die URLs der öffentlich zugänglichen [Brunnenwebseiten](https://www.stadt-zuerich.ch/de/umwelt-und-energie/wasser/trinkwasser/brunnen.html) sowie der zugehörigen Fotos. Über die Brunnennummer lassen sich diese Informationen mit dem Geodatensatz verknüpfen.

de: bilder brunnen fotos github trinkwasser wasserversorgung

name: Wasserversorgung, Departement der Industriellen Betriebe

de: Brunnenfotos der Stadt Zürich

title_for_slug: brunnenfotos-der-stadt-zurich

heal

de: Gesundheit

en: Health

fr: Santé

it: Salute

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

fr: Gouvernement et secteur public

it: Governo e settore pubblico

bilder

display_name: bilder

brunnen

display_name: brunnen

fotos

display_name: fotos

trinkwasser

display_name: trinkwasser

wasserversorgung

display_name: wasserversorgung


parkflachen

de:
In Basel stehen auf dem Stadtgebiet ungefähr 100'000 öffentliche und private Auto-Parkplätze zur Verfügung. Rund ein Viertel davon befindet sich auf Allmend. Ein Grossteil dieser Parkplätze befinden in der Blauen Zone und stehen hauptsächlich den Anwohnerinnen und Anwohner der Quartiere zur Verfügung. Daneben gibt es weitere Parkplatztypen: Gebührenpflichtige Parkplätze, Parkplätze für Velos und Motorräder, Parkplätze für Cars, usw.
Die unterschiedlichen Bewirtschaftungsarten der Parkplätze haben zum Ziel, dass nebst der Anwohnerschaft auch Besucher, der Detailhandel sowie das Gewerbe von den Parkplätzen profitieren können und der Parksuchverkehr reduziert werden kann. Bei den gebührenpflichtigen Parkplätzen sind die Parkgebühren gebietsabhängig.
Wegen Baustellen, Veranstaltungen oder aus anderen Gründe kann es sein, dass Parkplätze vorübergehend nicht zur Verfügung stehen. Auch ist es möglich, dass gewisse Parkplätze im Rahmen von Umbauprojekten bereits aufgehoben wurden, das Projekt aber noch nicht abgeschlossen und somit auch der Datensatz noch nicht nachgeführt ist.

de: parkieren parkzone parkierung parkplatz parken auto velo fahrrad motorrad

kanton-basel-stadt

fr: Le canton de Bâle-Ville publie des ensembles de données ouvertes (Open Government Data) provenant des offices et services cantonaux. **Open Data Basel-Stadt** est responsable du soutien aux services administratifs qui publient des données.

en: The Canton of Basel-Stadt publishes open government datasets from cantonal offices and departments. **Open Data Basel-Stadt** is responsible for supporting the administrative units that publish data.

de: Der Kanton Basel-Stadt veröffentlicht Open Government-Datensätze von kantonalen Ämtern und Dienststellen. **Open Data Basel-Stadt** ist zuständig für die Unterstützung der datenpublizierenden Verwaltungsstellen.

it: Il Cantone di Basilea-Città pubblica set di dati aperti (Open Government Data) provenienti dagli uffici e dai servizi cantonali. **Open Data Basel-Stadt** è responsabile del supporto agli uffici amministrativi che pubblicano i dati.

de: Kanton Basel-Stadt

en: Canton of Basel-City

fr: Canton de Bâle-Ville

it: Cantone di Basilea-Città

political_level: canton

de: Amt für Mobilität

de: Parkflächen

title_for_slug: parkflachen

value: BS Kanton Stadt - DCAT Harvester

tran

de: Verkehr

en: Transport

fr: Transports

it: Trasporti

de: Parkflächen (csv)

de: csv

de: Parkflächen (json)

de: json

de: Parkflächen (jsonl)

de: jsonl

de: Parkflächen (parquet)

de: parquet

format: PARQUET

de: Parkflächen (rdfxml)

de: rdfxml

format: RDF XML

media_type: application/rdf+xml

de: Parkflächen (jsonld)

de: jsonld

format: JSON-LD

de: Parkflächen (turtle)

de: turtle

format: RDF Turtle

media_type: text/turtle

de: Parkflächen (n3)

de: Parkflächen (xls)

de: xls

auto

display_name: auto

fahrrad

display_name: fahrrad

motorrad

display_name: motorrad

parken

display_name: parken


de:
Ein Vollzeitäquivalent entspricht einem 100%-Arbeitspensum. 2011 bis 2023.

(QUELLE: Bundesamt für Statistik, STATENT)

kanton-zug

de:
Hier veröffentlicht das Team von Open Data Zug von der kantonalen Fachstelle für Daten und Statistik schrittweise offene Behördendaten der kantonalen Verwaltung.

Weitere Informationen unter https://zg.ch/opendata

de: Kanton Zug

en: Canton of Zug

fr: Canton de Zoug

it: Cantone di Zugo

de: Fachstelle für Daten und Statistik des Kantons Zug

de: Zeitliche Entwicklung von Betrieben, Beschäftigten und Vollzeitäquivalenten

value: DCAT Harvester Kt. ZG

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

it: Economia e finanze

de: Zeitliche Entwicklung von Beschäftigten

de: Zeitliche Entwicklung von Betrieben

de: Zeitliche Entwicklung von Vollzeitäquivalenten

wirtschaftsstruktur

display_name: wirtschaftsstruktur


betriebe-nach-wirtschaftssektor

de:
Betriebe nach Wirtschaftssektor im Kanton Zug 2011 bis 2023.

(QUELLE: Bundesamt für Statistik, STATENT)

de: Betriebe nach Wirtschaftssektor

title_for_slug: betriebe-nach-wirtschaftssektor

wirtschaftssektoren

display_name: wirtschaftssektoren


beschaftigte-nach-wirtschaftssektor

de:
Beschäftigte nach Wirtschaftssektor im Kanton Zug 2011 bis 2023.

(QUELLE: Bundesamt für Statistik, STATENT)

de: Beschäftigte nach Wirtschaftssektor

title_for_slug: beschaftigte-nach-wirtschaftssektor


kugel-des-st-galler-globus

de: Zentralbibliothek Zürich

en: Zentralbibliothek Zürich

name: Zentralbibliothek Zürich, Abteilung Karten und Panoramen

de:
Der St. Galler Globus ist ein terrestrischer und himmlischer Globus, der eine Darstellung der Erde und des Himmels auf ein und derselben Kugel vereint. Er stammt aus der zweiten Hälfte des 16. Jahrhunderts und befindet sich heute im Landesmuseum in Zürich. Eine Kopie davon befindet sich in der Stiftsbibliothek St. Gallen.
Dieser Datensatz enthält die digitalen Abbildungen sowohl des Originals als auch der Kopie, die die Grundlage für eine dreidimensionale Rekonstruktion bilden.

en:
The St. Gallen Globe is a terrestrial and celestial globe that contains a representation of the earth and the sky on the same sphere. It dates from the second half of the 16th century and is now in the National Museum in Zurich. A copy can be found in the Abbey Library of St. Gall.
This dataset contains the digital images of both the original and the copy, which form the basis for a 3-Dimensional recreation.

de: 3D-Daten zur Kugel des St. Galler Globus

en: 3D scans of the St. Gallen Globe

de: Die Zentralbibliothek Zürich (ZB) ist als öffentliche Stiftung seit über 100 Jahren die Kantons-, Stadt- und Universitätsbibliothek von Zürich. Mit 6,6 Millionen Objekten (Büchern, Zeitschriften, Handschriften, Bildern, Fotografien, Karten, Mikroformen, Musikalien, Tonträgern, DVDs usw.) und über 200 Mitarbeitenden gehört sie zu den grössten Bibliotheken der Schweiz. Dazu kommt ein breites Angebot an Datenbanken und über 200’000 elektronische Volltexte. Eine halbe Million Menschen pro Jahr besucht die ZB und nutzt ihre vielfältigen Angebote.

fr: Zentralbibliothek Zürich

it: Zentralbibliothek Zürich

title_for_slug: Kugel des St. Galler Globus

educ

de: Bildung, Kultur und Sport

regi

de: Regionen und Städte

en: Regions and cities

fr: Régions et villes

it: Regioni e città

de: Digitale Abbildungen des Originals

en: Digital images of the original

de: Digitale Abbildungen der Replik

en: Digital images of the copy