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: qgis forest accessible-forest geoprocessing openstreetmap seilaplan

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

envi

en: Environment

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

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

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

format: PNG

media_type: image/png

en:
Resource Title: 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

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:
This data set includes GPS-derived snow water equivalent (SWE), snow depth (HS) and liquid water content (LWC) data for three entire snow-covered seasons (2015-2016, 2016-2017, 2017-2018) at the study plot Weissfluhjoch 2540 m a.s.l. (Davos, Switzerland). The procedure to derive these snow properties is described in Koch et al. (2019). The novel approach is based on a combination of GPS signal attenuation and time delay.
The dataset also includes corresponding validation data for SWE and HS measured at Weissfluhjoch, and some additional meteorological data used for interpretation of the snow cover evolution.
Please refer to the Read-me file for further details on the data.
These data are the basis of the following publication:
- Koch, F., Henkel, P., Appel, F., Schmid, L., Bach, H., Lamm, M., Prasch, M., Schweizer, J., and Mauser, W., 2019. Retrieval of snow water equivalent, liquid water content and snow height of dry and wet snow by combining GPS signal attenuation and time delay. Water Resources Research, 55(5), 4465-4487. https://doi.org/10.1029/2018WR024431

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

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.

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

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

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

fr: Environnement

it: Ambiente

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

format: CSV

media_type: text/csv

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

format: PDF

media_type: application/pdf

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth


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

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

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.

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

en:
Resource Title: 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).

format: jpeg

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

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

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

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).

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

en: History of wetlands in Switzerland since 1850

envi

en: Environment

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

envidat

en: EnviDat: the Environmental Data Portal

en: Data Broedlin CNP

title_for_slug: data-broedlin-cnp

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

format: XLS

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

carbon

display_name: carbon

dissolved-organic-matter

display_name: dissolved-organic-matter

drying-rewetting

display_name: drying-rewetting

forest

display_name: forest

mineralization

display_name: mineralization

nitrogen

display_name: nitrogen

phosphorus

display_name: phosphorus

soil

display_name: soil

stoichiometry

display_name: stoichiometry


automatic-classification-of-avalanches

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

en: monitoring localization machine-learning seismic avalanche

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: Automatic Classification of Avalanches

title_for_slug: automatic-classification-of-avalanches

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: snowmelt soil-moisture precipitation climate-change hydrology discharge

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

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

media_type: application/zip

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.

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: forest picea-abies soil nitrogen co2 face

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

envi

en: Environment

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

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

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: 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.

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

en:
Resource Title: 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: 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.

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

en: Snow Depth Mapping

title_for_slug: snow-depth-mapping

envi

en: Environment

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

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

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

aerial-imagery

display_name: aerial-imagery

avalanche

display_name: avalanche

dsm

display_name: dsm

image-matching

display_name: image-matching

snow-depth

display_name: snow-depth

snow-hydrology

display_name: snow-hydrology

snow-water-equivalent

display_name: snow-water-equivalent


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

en: model sediment-transport snow erosion mars

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

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

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

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow


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 fagus-orientalis-lipsky potassium biogeochemical-cycling magnesium

en: Base cation dynamics in an Oriental beech forest

envi

en: Environment

biogeochemical-cycling

display_name: biogeochemical-cycling

calcium

display_name: calcium

fagus-orientalis-lipsky

display_name: fagus-orientalis-lipsky

magnesium

display_name: magnesium

potassium

display_name: potassium


seilaplan

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

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

en: Seilaplan

title_for_slug: seilaplan

cable-planning

display_name: cable-planning

cable-yarding

display_name: cable-yarding

catenary-load-path

display_name: catenary-load-path

python

display_name: python

qgis

display_name: qgis

software

display_name: software

steep-terrain-harvesting

display_name: steep-terrain-harvesting


stem-radius-change-data-pfynwald

en:
**Continuously measured stem radius change data (time series) from high-precision point dendrometers (Natkon) mounted on the stems of Pinus sylvestris trees at 1.5 m in the Pfynwald VPDrought experimental area.**
The data originates from the **TreeNet database**. The published data represents the highest quality data following automatic and manual corrections (LM data level).
**The dataset contains the following files:**
- 10-minute resolution time series (.parquet)
- Daily resolution time series (.csv and .parquet)
- Metadata (.csv)
- Readme (.txt)
Main variables are stem radius changes (SRC), tree water deficit (TWD) and radial stem growth (GRO).

**The site area contains the following site_ids (treatments)**
| 86 | Pfynwald-Control
| 89 | Pfynwald-Irr_Stop
| 90 | Pfynwald-Irrigation
| 145 | Pfynwald-Irrigation_VPD
| 146 | Pfynwald-Roof
| 147 | Pfynwald-Roof_VPD
The measurements cover data from 2011 to 2025. All data is in UTC + 1 hour (Central European Time CET, winter time, no DST).

en: drought-legacy forest ecophysiology treenet pinus-sylvestris treewaterdeficit time-series data-publication drought-experiment dendrometer climate-change alps bark-growth drought-stress wood-growth automated-monitoring

en: Stem Radius Change Data Pfynwald

title_for_slug: stem-radius-change-data-pfynwald

en:
Resource Title: Pfynwald_Dendro_2010-2025.zip
    Size: 446097419 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/60f3c95c-fe5d-49f0-89af-f325ef864cf0/resource/aec4c998-c6dd-4000-bd4e-c9bc79fe7b22/download/pfynwald_dendro_2010-2025.zip
    Description:

en:
Resource Title: Pfynwald_README.txt
    Size: 12082 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/60f3c95c-fe5d-49f0-89af-f325ef864cf0/resource/8c24a11c-ecda-404c-9dd4-078629e89559/download/pfynwald_readme.txt
    Description:

alps

display_name: alps

automated-monitoring

display_name: automated-monitoring

bark-growth

display_name: bark-growth

climate-change

display_name: climate-change

data-publication

display_name: data-publication

dendrometer

display_name: dendrometer

drought-experiment

display_name: drought-experiment

drought-legacy

display_name: drought-legacy

drought-stress

display_name: drought-stress

ecophysiology

display_name: ecophysiology

forest

display_name: forest

pinus-sylvestris

display_name: pinus-sylvestris

time-series

display_name: time-series

treenet

display_name: treenet

treewaterdeficit

display_name: treewaterdeficit

wood-growth

display_name: wood-growth


en:
**Continuously measured stem radius change data (time series) from high-precision point dendrometers (Natkon) mounted on the stems of Pinus sylvestris trees at 1.5 m in the Pfynwald VPDrought experimental area.**
The data originates from the TreeNet database. The published data represents the highest quality data following automatic and manual corrections (LM data level).
The dataset contains the following files:
- 10-minute resolution time series (.parquet)
- Daily resolution time series (.parquet)
- Readme (.txt)
Main variables are stem radius changes (SRC), tree water deficit (TWD) and radial stem growth (GRO).
The measurements cover data from 2011 to 2025. All data is in UTC + 1 hour (Central European Time CET, winter time, no DST).

en: stem-growth irrigation twd pfynwald point-dendrometer drought vpd vpdrought pinus-sylvestris

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: Pfynwald VPDrought  experiment stem radius changes (TreeNet)

en:
Resource Title: pfynwald_vpdrought_dendrometer_2025.zip
    Size: 62493309 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/571cf7ad-edda-4e1f-9e9d-45014c39a9e2/resource/cea43ffe-6437-4b0e-8d58-398026cbde41/download/pfynwald_vpdrought_dendrometer_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_dendrometer_2024.zip
    Size: 61781663 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/571cf7ad-edda-4e1f-9e9d-45014c39a9e2/resource/425594e2-7210-49a8-82b7-1bdfc4cbaf33/download/pfynwald_vpdrought_dendrometer_2024.zip
    Description:

drought

display_name: drought

irrigation

display_name: irrigation

pfynwald

display_name: pfynwald

point-dendrometer

display_name: point-dendrometer

stem-growth

display_name: stem-growth

twd

display_name: twd

vpd

display_name: vpd

vpdrought

display_name: vpdrought


en: This dataset includes the diversity of soil prokaryotes, fungi and micro-eukaryotes in unmanaged forest reserves with managed forests across nine locations within Switzerland. Forests have been exploited for resources for centuries, which has caused disturbances, altered community structure, and reduced diversity at different scales. Strict forest reserves, where no forest management is practiced, have been implemented to promote biodiversity, by allowing old trees with microhabitats and high deadwood amounts. However, the effectiveness of forest reserves on soil microbial diversity and functional traits are little known at a national scale in Swiss forests. The associated metadata includes local environmental conditions, such as soil pH, organic C, N, deadwood volume, MAT and MAP, and forest type (coniferous vs deciduous).

en: forest-management soil-biodiversity microeukaryotes prokaryotes fungi

en: Management practices shape soil fungal diversity and functional traits in Swiss forests

en:
Resource Title: Environmental data
    Size: 13926 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/04e9459c-7024-46c3-9c33-a50a33da55b2/resource/c27f01d0-217e-4b50-88c0-70421ec0334f/download/forest-management-soilbd-environmental-data-envidat.csv
    Description: Environmental Data such as soil abiotic properties

en:
Resource Title: Fungi
    Size: 2931315180 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.780%2FForestMan_SoilBD_Fungi%20%28ITS%29%2F
    Description:

en:
Resource Title: Microeukaryotes
    Size: 2512555868 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.780%2FForestMan_SoilBD_Microeukaryotes%20%2818S%29%2F
    Description:

en:
Resource Title: Prokaryotes
    Size: 2738041651 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.780%2FForestMan_SoilBD_Prokaryotes%20%2816S%29%2F
    Description:

forest-management

display_name: forest-management

fungi

display_name: fungi

microeukaryotes

display_name: microeukaryotes

prokaryotes

display_name: prokaryotes

soil-biodiversity

display_name: soil-biodiversity


en:
This dataset contains the results of greenhouse gas emission modeling for the five Swiss Shared Socioeconomic Pathways (SSP-CH) up to the year 2100. Six sector-specific reduced-complexity models were developed specifically for this analysis, enabling the modelling of the SSP-CH storylines. Accordingly, the dataset comprises the outputs of all six models, generated both in the absence of and under the implementation of additional climate policy packages, referred to as Shared Policy Assumptions (SPAs; see related publications).
- Transport model (energy consumption by energy source and transport type/fleet mix)
- Housing model (heating demand and GHG emissions per building category)
- Electricity model (electricity consumption, electricity generation by energy source, installed capacity, district heating)
- Industry model (energy consumption by energy source, subdivided into raw materials/building materials, consumer goods, and processed goods)
- Agriculture model (feed digestion in livestock, manure storage, and nitrogen fertilization)
- Export/Import model (product quantities in import and export, broken down into consumer goods, raw materials/building materials, and processed goods)
- Synthesis model

en: emissions-scenarios greenhousegas-modelling socioeconomic-scenarios national-ssp qualitative-scenarios

en: Results of greenhouse gas modelling of the Swiss Shared Socioeconomic Pathways (SSP-CH)

envi

en: Environment

en:
Resource Title: SSP-CH_GHG_imp_exp_model.xlsx
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    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/c80f618c-fd87-4c43-920e-77c8081ccd5a/download/ssp-ch_ghg_imp_exp_model.xlsx
    Description: SSP-CH GHG modelling resluts of Export/Import model (product quantities in import and export, broken down into consumer goods, raw materials/building materials, and processed goods). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_agriculture_model.xlsx
    Size: 624865 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/b8d73680-8159-46ac-98f6-9d97131f5c2e/download/ssp-ch_ghg_agriculture_model.xlsx
    Description: SSP-CH GHG modelling results of Agriculture model (feed digestion in livestock, manure storage, and nitrogen fertilization). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_Synthesis_model.xlsx
    Size: 386540 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/a1e54990-11c5-43cf-b922-d839925b4078/download/ssp-ch_ghg_synthesis_model.xlsx
    Description: SSP-CH GHG modelling results of Synthesis model. This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_transport_model.xlsx
    Size: 9070182 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/be82872b-5fd7-4498-a4b9-2141dd5eb00f/download/ssp-ch_ghg_transport_model.xlsx
    Description: SSP-CH GHG modelling results of Transport model (energy consumption by energy source and transport type/fleet mix). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_housing_model.xlsx
    Size: 3051356 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/913c1ae0-418b-4f31-8b51-9ef1e364b3fd/download/ssp-ch_ghg_housing_model.xlsx
    Description: SSP-CH GHG modelling results of Housing model (heating demand and GHG emissions per building category). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_industry_model.xlsx
    Size: 465818 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/3e81b975-33bf-4327-bf18-3ae32f36b21d/download/ssp-ch_ghg_industry_model.xlsx
    Description: SSP-CH GHG modelling results of Industry model (energy consumption by energy source, subdivided into raw materials/building materials, consumer goods, and processed goods). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_transport_model.xlsx
    Size: 9070182 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/c147c40f-3431-4847-a954-5a80b6a38cf1/download/ssp-ch_ghg_transport_model.xlsx
    Description: This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_electricity_model.xlsx
    Size: 1195377 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/b543e472-b1c0-488c-8a71-ff09be0d140d/download/ssp-ch_ghg_electricity_model.xlsx
    Description: SSP-CH GHG modelling results of Electricity model (electricity consumption, electricity generation by energy source, installed capacity, district heating). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

emissions-scenarios

display_name: emissions-scenarios

greenhousegas-modelling

display_name: greenhousegas-modelling

national-ssp

display_name: national-ssp

qualitative-scenarios

display_name: qualitative-scenarios

socioeconomic-scenarios

display_name: socioeconomic-scenarios


en: This dataset comprises qualitative data for the development of the five Swiss Shared Socioeconomic Pathways (SSP-CH) up to the year 2100. First, it comprises projections of 22 socioeconomic factors, each represented by four to five factor-specific trajectories that form the basis of the qualitative scenario storylines. Second, it includes an input table providing concise qualitative characterizations of 63 socioeconomic factors across the five SSP-CH scenarios.

en: ssp-storylines scenario-development qualitative-scenarios socioeconomic-scenarios national-ssps

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: Shared Socioeconomic Pathways for Switzerland (SSP-CH): qualitative data for scenario development

en:
Resource Title: Input-table_final_e.xlsx
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    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/3e5310e5-4038-4782-b3c9-b64100709e32/resource/9eef7ee5-8a6d-47c2-9952-447cd39018e4/download/input-table_final_e.xlsx
    Description: SSP-CH Input table: qualitative description of 63 socioeconomic factors in the 5 SSP-CH (english). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Programme. The following individuals participated in the compilation of this data: Gubler, L., Tschumi, P., Pütz, M., Seidl, I.

en:
Resource Title: Input-Tabelle_final_d.xlsx
    Size: 198502 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/3e5310e5-4038-4782-b3c9-b64100709e32/resource/3458c684-6a22-437e-99cf-20c9f494d521/download/input-tabelle_final_d.xlsx
    Description: SSP-CH Input table: qualitative description of 63 socioeconomic factors in the 5 SSP-CH (german). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Programme. The following individuals participated in the compilation of this data: Gubler, L., Tschumi, P., Pütz, M., Seidl, I.

en:
Resource Title: SSP-CH_Faktorprojektionen_d.pdf
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    Format: application/pdf
    URL: https://www.envidat.ch/dataset/3e5310e5-4038-4782-b3c9-b64100709e32/resource/11d2b1ab-8a77-407e-9732-db22a853e03f/download/faktorprojektionen_beschreibung_d.pdf
    Description: SSP-CH factor projections of 20 socioeconomic factors (german). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Programme. The following individuals participated in the compilation of this data: Gubler, L., Tschumi, P., Pütz, M., Seidl, I.

national-ssps

display_name: national-ssps

scenario-development

display_name: scenario-development

ssp-storylines

display_name: ssp-storylines


en:
Starter kit for the TreeMig framework that allows for an easy application of the forest landscape model TreeMig for simulating forest dynamics in space under changing environmental and land use conditions.
The starter kit consists of a set of climate, land-use, topography and soil property input data for Switzerland, a script for installing the framework and running the GUI of the framework with the link to the input data, a tutorial covering a range of simulation examples for Switzerland and a transect through Europe, and an associated example simulation environment containing the model executables and other model inputs.

en: forest species-interaction bioclimatic-variables treemig forest-model r-package land-use species-migration forest-dynamics spatial-modelling gui

en: Starter Kit for the TreeMig framework v1 for easy simulation of spatio-temporal forest dynamics

envi

en: Environment

en:
Resource Title: Description input data
    Size: 263110 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/3db8ca57-2838-4b26-82a9-9770b75b7096/download/readme_descriptioninputdata.pdf
    Description: Details where the input data come from and how they have been processed

en:
Resource Title: TreeMig_Tutorial_2025-05-02.pdf
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    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/a1dec65a-30ba-4688-90ac-50df5db73d4c/download/treemig_tutorial_2025-05-02.pdf
    Description: Tutorial for using the TreeMig framework; updated

en:
Resource Title: TreeMig Simulation Environment and Input Data
    Size: 1602386904 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/c2ae78fd-418a-4cdb-a511-0914eb46224f/download/tmenvandinputdata.zip
    Description: The zip file consists of a R-script to provide the framework, an example simulation environment and a set of input data.
- The R-script installAndRunTreeMigWrapperAndGUI.R installs the R-package, links to the input data and starts the graphical user interface.
- The gridded input datasets in TMInputData are specifically tailored to Switzerland and have the same coordinate reference system and a congruent 200m spatial resolution. They consist of climate, topographic, land use and soil data.  For details see TMInputDataDetails.pdf.
- TMEnvironment is an example simulation environment, i.e. a set of hierarchically structured folders.  For the first example simulation of the tutorial it contains the
   - the TreeMig executables for MacOS, Linux and Windows
   - simulation control files that define the setup and input files of the simulation (in folder C)
   - species parameters (in folder P)
   - bioclimatic data  (in folder E)
   - folder R for results
   - folder Plots for plots of the simulation results.
   - This environment can be also used for the subsequent simulations of the tutorial.
- Some additional R-scripts demonstrate more complex applications described in the tutorial, e.g. coupling to another model.

en:
Resource Title: TreeMig Tutorial
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    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/8e6ac324-ab2b-40bc-a12f-70960c8f4bd1/download/treemig_tutorial.pdf
    Description: Tutorial for using the TreeMig framework

en:
Resource Title: TreeMig_Tutorial_v2024_12_04.pdf
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    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/d4c15251-917c-4102-b172-256fecd39161/download/treemig_tutorial_v2024_12_04.pdf
    Description:

en:
Resource Title: TreeMig_Tutorial_v2024_12.pdf
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    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/5188a2e1-470c-4ed7-83c6-26dc72bd18ab/download/treemig_tutorial_v2024_12.pdf
    Description: Tutorial for using the TreeMig framework; updated

en:
Resource Title: TreeMig Simulation Environment and Input Data
    Size: 1612103870 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/5eef16d1-80af-442b-9da2-f64b4fa94671/download/tmenvandinputdata.zip
    Description: The zip file consists of a R-script to provide the framework, an example simulation environment and a set of input data.
- The R-script installAndRunTreeMigWrapperAndGUI.R installs the R-package, links to the input data and starts the graphical user interface.
- The gridded input datasets in TMInputData are specifically tailored to Switzerland and have the same coordinate reference system and a congruent 200m spatial resolution. They consist of climate, topographic, land use and soil data.  For details see TMInputDataDetails.pdf.
- TMEnvironment is an example simulation environment, i.e. a set of hierarchically structured folders.  For the first example simulation of the tutorial it contains the
   - the TreeMig executables for MacOS, Linux and Windows
   - simulation control files that define the setup and input files of the simulation (in folder C)
   - species parameters (in folder P)
   - bioclimatic data  (in folder E)
   - folder R for results
   - folder Plots for plots of the simulation results.
   - This environment can be also used for the subsequent simulations of the tutorial.
- Some additional R-scripts demonstrate more complex applications described in the tutorial, e.g. coupling to another model.

bioclimatic-variables

display_name: bioclimatic-variables

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-model

display_name: forest-model

gui

display_name: gui

land-use

display_name: land-use

r-package

display_name: r-package

spatial-modelling

display_name: spatial-modelling

species-interaction

display_name: species-interaction

species-migration

display_name: species-migration

treemig

display_name: treemig


en:
Spatio-temporal vegetation models are essential for simulating dynamics and shifts
in species distributions over large areas, particularly under global change. One such
model is the dynamic forest landscape model TreeMig. We have developed a frame-
work that makes the model more user-friendly, improves its functionality, and expands
its possibilities. The framework consists of the improved TreeMig model, the R pack-
age ‘TreeMig-R’ for pre-processing input data, model execution and visualization and a
graphical user interface (GUI) for ease of use. The code of the TreeMig Package and the GUI is stored here.

en: landscape dynamic-modelling forest-model r-package gui

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: Code of TreeMig Package version 1

dynamic-modelling

display_name: dynamic-modelling

landscape

display_name: landscape


en:
We used 1463 observations of early leaf discoloration presence or absence in Switzerland's European beech (*Fagus sylvatica L.*) forests between 2018 and 2023 and interpolated Sentinel-2 vegetation index time series from Koch et al. (2024) to train a support vector classifier of early leaf discoloration. We applied this classifier to the European beech dominated forest area of Switzerland over the same time period to estimate a probability of early leaf discoloration between 0 and 1 (high probability of early leaf discoloration). The maps intentionally exclude legacy effects of drought like crown dieback or mortality which occurred in prior years.
Early leaf discoloration maps are available at the end of every summer month (June, July, August, and September) 2017 to 2023. Additional maps are available every 5-days during the summer months of 2018. Probability of early leaf discoloration at each date is provided as a GeoTIFF file with a scaled value range of 0 to 10,000 such that a probability of 0.9 is represented by a value of 9000 (a high probability of early leaf discoloration). An optimized probability threshold of 0.4 (4000) is recommended for classification into discolored and not discolored pixels. More details on the methods and results can be found in the publication of Bloom et al. (2026).
***These maps represent an interpreted remote sensing product that approximates ground observations of early leaf discoloration across Switzerland's European beech dominated forests.***
Given ongoing efforts to operationalize an early discoloration pipeline, all data is currently available upon reasonable request. An example of the 2018 5-day time series in the Hardwald (Canton Basel-Land) is available for immediate download.

en: sentinel-2 european-beech switzerland early-defoliation drought-2018 early-warning drought forest

envidat

en: EnviDat: the Environmental Data Portal

en: Early leaf discoloration maps for Switzerland's European beech forests

drought

display_name: drought

early-defoliation

display_name: early-defoliation

early-warning

display_name: early-warning

european-beech

display_name: european-beech

switzerland

display_name: switzerland


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

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

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

en:
Resource Title: readme_descriptioninputdata.pdf
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    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/5abbe67b-ab73-413b-bff8-5cccf5347b1c/download/readme_descriptioninputdata.pdf
    Description:

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

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

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

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

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

bioclimatic-variables

display_name: bioclimatic-variables

climate-change

display_name: climate-change

example-applications

display_name: example-applications

forest

display_name: forest

forest-management

display_name: forest-management


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

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

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

envi

en: Environment

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

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

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

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

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

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

acclimation

display_name: acclimation

forest-canopy

display_name: forest-canopy

photosynthesis

display_name: photosynthesis

respiration

display_name: respiration


en: precipitation last-glacial-maximum air-temperature orography glaciers paleo-climate

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: CHELSA-TraCE21k: Downscaled transient temperature and precipitation data since the last glacial maximum

en:
Resource Title: Technical documentation
    Size: 478853 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/c88baa58-dbae-452c-8c2c-343e4c9fb885/resource/613fcb27-3649-4b5f-8880-984403cccd62/download/chelsa-trace21k_technical_documentation.pdf
    Description: Technical documentation containing file metadata and variable descriptions.

en:
Resource Title: Data Access
    Size: 3848290697216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav1%2F&prefix=chelsa_trace%2F
    Description: High resolution, downscaled climate model data are used in a wide variety of applications in environmental sciences. Here we present the CHELSA-TraCE21k downscaling algorithm to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100 year time steps for the last 21,000 years. Paleo orography at high spatial resolution and at each timestep is created by combining high resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases with the interpolation of a dynamic ice sheet model (ICE6G) and a coupling to mean annual temperatures from CCSM3-TraCE21k. Based on the reconstructed paleo orography, mean annual temperature and precipitation was downscaled using the CHELSA V1.2 algorithm.

The data is published under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

glaciers

display_name: glaciers

last-glacial-maximum

display_name: last-glacial-maximum

orography

display_name: orography

paleo-climate

display_name: paleo-climate

precipitation

display_name: precipitation


en:
Topic of Survey
The data at hand on energy cooperatives in Switzerland were collected in 2016 as part of the project "Collective financing of renewable energy projects in Switzerland and Germany" of the National Research Programme 71 "Managing Energy Consumption". The cooperatives were surveyed on their organizational structure, their activities in electricity and heat generation, their finances, the political context and their assessments of the future.
 Survey Method
The survey was targeted at all energy cooperatives in Switzerland (this is the basic population). The Swiss Commercial Register was searched for cooperatives and specific keywords in order to determine this basic population and collect addresses. This search in May 2016 resulted in a total of 304 energy cooperatives, to which a questionnaire was sent in July 2016. A pre-test with 8 persons had been carried out before the questionnaire was sent out. The questionnaire was provided in German and French. It was sent by mail and an attached letter referred to a link for the digital version if preferred. The online version was designed with the software "Sawtooth". After three weeks, a first, and after six weeks a second reminder letter was sent to those cooperatives that had not yet completed the questionnaire. The returned hardcopy questionnaires were manually entered into the database and then combined with the electronic data from the online survey. In the course of the survey, the total population was reduced from 304 to 289: in 4 cases the survey was not deliverable, 4 cooperatives had dissolved, 6 were not actually energy cooperatives, 1 case had recently changed its legal form. With a response rate of 47%, the final data set comprises 136 responses (from 77 digital and 59 hardcopy questionnaires). However, not all 136 of the returned questionnaires were filled out completely. We checked for answers that seemed contradictory or incomprehensible. If an error could be clearly identified and the correct answer derived, the answer was adjusted, otherwise the answer was replaced by "missing data".
 Anonymization
Participating cooperatives have been assured that their information will be kept confidential and will only be made public anonymously. For this reason, the data have been anonymized in in order to prevent any identification of individual cooperatives.
 How to Use the Data
* The data are available in CSV and SPSS (sav.) format.
* A codebook and a modified version of the used questionnaire are provided to illustrate the data and variable structure. In the questionnaire, the variable names are assigned to the corresponding questions. In the codebook, further information on these variables (valid n, answer categories) can be found. This information (of the codebook) is already integrated in the SPSS file.
 Current Embargo on Data
These data are currently under embargo and will only be released when the project is completed (not before 2020).
Additional Information
* The used questionnaire is provided in German and French.
* Descriptive results of the survey were published in a WSL report: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:18943

en: renewable-energy energy-cooperatives cooperatives community-energy switzerland

en: Energy Cooperatives in Switzerland: Survey Results // Energiegenossenschaften in der Schweiz: Befragungsergebnisse

en:
Resource Title: Raw date (SPSS)
    Size: 323839 bytes
    Format: application/x-spss-sav
    URL: https://www.envidat.ch/dataset/ec4125f8-d549-452f-a134-b53439f3b6e5/resource/1319f978-1d65-498c-8bfd-589f1b89e6a7/download/energy-cooperatives-switzerland_data.sav
    Description: Raw data in sav. format (SPSS). For comprehension of the data and variable structure, please consult the modified questionnaire with variable names.

en:
Resource Title: Raw data (.csv)
    Size: 196544 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ec4125f8-d549-452f-a134-b53439f3b6e5/resource/7f6c3275-0b87-410f-882e-4496a5705a08/download/energy-cooperatives-switzerland_data.csv
    Description: Raw data in csv. format. For comprehension of the data and variable structure, please consult the codebook and the modified questionnaire with variable names.

en:
Resource Title: Questionnaire with variable names
    Size: 3397996 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/ec4125f8-d549-452f-a134-b53439f3b6e5/resource/806cb4ee-b4b7-4b77-9bbd-c014ae28bc76/download/energy-cooperatives-switzerland_questionnaire-with-variable-names.pdf
    Description: Modified questionnaire with variable names for each item. Should be used together with the data files (.csv or .sav) to reconstruct the data and variable structures.

en:
Resource Title: Codebook
    Size: 2433879 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/ec4125f8-d549-452f-a134-b53439f3b6e5/resource/30440e19-9f40-4bd5-a779-af1640db1891/download/energy-cooperatives-switzerland_codebook.pdf
    Description: Description of variable attributes and valid n

community-energy

display_name: community-energy

cooperatives

display_name: cooperatives

energy-cooperatives

display_name: energy-cooperatives

renewable-energy

display_name: renewable-energy


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

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

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

envi

en: Environment

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

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

advection

display_name: advection

metamorphism

display_name: metamorphism

snow

display_name: snow

stable-water-isotope

display_name: stable-water-isotope