en:
The data presented here corresponds to the publication "A Close-Ridge Small-Scale Atmospheric Flow Field and its Influence on Snow Accumulation" (Gerber et al., 2017), which investigates an eddy-like structure in the vicinity of the Sattelhorn in the Dischma valley (Davos Switzerland)  and its influence on snow accumulation. The dataset contains:
* Alpine3D: Alpine3D snow depth grids (25 m resolution) for two simulations with and without snow redistribution.
* ARPS: 10 ARPS simulations (25 m horizontal resolution) with different model setups (wind direction, wind speed, stability).
* LiDAR: Processed LiDAR PPI (D2_PPI_1h) and RHI (D2_cross_1h) across the valley with a hourly resolution for the period 27 October 2015 01:00 - 29 October 2015c 21:00 (spatial resolution: 25 m).
* meteostations-dischma: Meteorological station data of two meteorological stations in the Dischma valley with 10 minute resolution for the period 28 October 2015 - 30 October 2015.
* TLS: Snow depth change data (m) between 28 October 2015 and 30 October 2015 based on terrestrial laser scans.
For more details about the simulation and observation data, see Gerber et al., 2017.
Publication: Gerber et al., 2017: A Close-Ridge Small-Scale Atmospheric Flow Field and its Influence on Snow Accumulation, submitted to JGR - Atmospheres.

en: DISCHMEX - Observations and simulations of the close-ridge small-scale atmospheric flow field and snow accumulation at Sattelhorn, Dischma valley, Davos, Switzerland.

en: lee-side-flow-field tls preferential-deposition alpine3d lidar

envidat

en: EnviDat: the Environmental Data Portal

envi

en: Environment

lee-side-flow-field

display_name: lee-side-flow-field

lidar

display_name: lidar

preferential-deposition

display_name: preferential-deposition

tls

display_name: tls


$oid: OBSOLETE

en:
Overview
We present GROUNDEYE, a new model of radiative transfer over mountainous terrain, which considers for the first time the forward scattering properties of snow.
Embedded in the surface process model Alpine3D, the new terrain radiation model GROUNDEYE receives interpolated real weather data with diffuse and direct broadband shortwave radiation for each pixel as well as a spatially variable plane albedo from the module SNOWPACK.
 Format
The GROUNDEYE model is written in c++, as is the entire environment of Alpine3d. The input and output data sets are .xlsx or .txt format, pre- and postprocessing including the generation of all figures is in .R format.
 Structure
In Data_Forward_Scattering.zip you will find all necessary data and model details to
reproduce the results of the JGR publication "How forward-scattering snow and terrain change the Alpine radiation balance with application to solar panels"
 - 	Model Input Data contains the meteorological and topographic input data sets, the BRDF, and preprocessing scripts.
 -  Model Code contains the full model Alpine3d including the radiative transfer module GROUNDEYE.
 -  Model Output Data contains the results of the simulation of terrain irradiance and irradiance of solar panels; hourly resolution, 1. Sptember 2017 - 31. August 2018.
 -  Measurements Solar Testsite contains information and measurements of the solar testsite at the Totalp near Davos, Switzerland.
 -  Postprocessing contains all R-Scripts used for the analysis and
plotting of the corresponding data.
In each of these folders you will find detailed information in
the file 'About this Folder.txt'.

en: Data, Code Link and Metadata on Forward Scattering of Snow at Totalp

en: winter-energy-production shortwave-radiation photovoltaic albedo snow

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

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

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

fr: Environnement

it: Ambiente

format: ZIP

albedo

display_name: albedo

photovoltaic

display_name: photovoltaic

shortwave-radiation

display_name: shortwave-radiation

snow

display_name: snow

winter-energy-production

display_name: winter-energy-production


en:
This work presents the first extensive study of climate change impacts on rivers temperature in Switzerland. Results show that even for low emissions scenarios, water temperature increase will lead to adverse effect for both ecosystems and socioeconomic sectors (such as nuclear plant cooling) throughout the 21st century. For high emissions scenarios, the effect will be worsen. This study also shows that water warming in summer will be more important in Alpine regions than in lowlands.
This material is distributed under CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/legalcode).

en: Dataset for: Future water temperature of rivers in Switzerland under climate change investigated with physics-based models

en: water-temperature climate-change-impact discharge hydrology model

climate-change-impact

display_name: climate-change-impact

discharge

display_name: discharge

hydrology

display_name: hydrology

model

display_name: model

water-temperature

display_name: water-temperature


en:
This is the simulation dataset from _"Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland"_, M. Bavay, T. Grünewald, M. Lehning, Advances in Water Resources 55, 4-16, 2013
A model study on the impact of climate change on snow cover and runoff has been conducted for the Swiss Canton of Graubünden. The model Alpine3D has been forced with the data from 35 Automatic Weather Stations in order to investigate snow and runoff dynamics for the current climate. The data set has then been modified to reflect climate change as predicted for the 2021-2050 and 2070-2095 periods from an ensemble of regional climate models.
The predicted changes in snow cover will be moderate for 2021-2050 and become drastic in the second half of the century. Towards the end of the century the snow cover changes will roughly be equivalent to an elevation shift of 800 m. Seasonal snow water equivalents will decrease by one to two thirds and snow seasons will be shortened by five to nine weeks in 2095.
Small, higher elevation catchments will show more winter runoff, earlier spring melt peaks and reduced summer runoff. Where glacierized areas exist, the transitional increase in glacier melt will initially offset losses from snow melt. Larger catchments, which reach lower elevations will show much smaller changes since they are already dominated by summer precipitation.

en: Alpine3D simulations of future climate scenarios for Graubunden

en: snow graubunden switzerland climate-change alpine3d-simulations

en:
Resource Title: Simulation data
    Size: 0
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.608/clisp_2012/
    Description: Reference data as well as the 2050 and 2099 scenarios for ARPEGE and ETHZ other RCMs available on demand)

en:
Resource Title: Configuration file
    Size: 2807 bytes
    Format: text/x-ini
    URL: https://www.envidat.ch/dataset/8bce53fb-3b5e-49fc-94ae-6331401315de/resource/e03efd3c-5966-491d-9d40-8f5366d9c4b7/download/io.ini
    Description:

climate-change

display_name: climate-change

graubunden

display_name: graubunden

switzerland

display_name: switzerland


en:
In fall 2019, a new set of climate change scenarios has been released for
Switzerland, the CH2018 dataset (www.climate-scenarios.ch). The data are
provided at daily resolution. We produced from the CH2018 dataset a new
set of climate change scenarios temporally downscaled at hourly resolution.
In addition, we extended this dataset integrating the meteorological stations
from the Inter-Cantonal Measurement and Information System (IMIS) network,
an alpine network of automatic meteorological stations operated by the WSL
Institute for Snow and Avalanche Research SLF.
The extension to the IMIS network is obtained using a Quantile Mapping approach
in order to perform a spatial transfer of the CH2018 scenarios from the location
of the  MeteoSwiss stations to the location of the IMIS stations. The temporal
downscaling is performed using an enhanced Delta-Change approach. This approach
is based on objective criteria for assessing the quality of the determined delta
and downscaled time series. In addition, this method also fixes a flaw of common
quantile mapping methods (such as used in the CH2018 dataset for spatial downscaling)
related to the decrease of correlation between different variables. The idea behind
the delta change approach is to take the main seasonal signal (and mean) from
climate change scenarios at daily resolution and to map it to a historical time series
at hourly resolution in order to modify the historical time series. The obtained time
series exhibit the same seasonal signal as the original climate change time series,
while it keeps the sub-daily cycle from the historical time series.
The applied methods (Quantile Mapping and Delta-Change) have limitations in
correctly representing statistically extreme events and changes in the frequency
of discontinuous events such as precipitation. In addition, the sub-daily cycle in
the data is inherited from the historical time series, so there is no information
of the climate change signal in this sub-daily cycle. A careful reading of the paper
accompanying the dataset is necessary to understand the limitations and scope of
application of this new dataset.
This material is distributed under CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/legalcode).

en: Dataset for: Climate change scenarios at hourly time-step over Switzerland from an enhanced temporal downscaling approach

en: delta-change quantile-mapping switzerland meteoswiss temporal-downscaling alpine-regions imis climate-change-scenarios

alpine-regions

display_name: alpine-regions

climate-change-scenarios

display_name: climate-change-scenarios

delta-change

display_name: delta-change

imis

display_name: imis

meteoswiss

display_name: meteoswiss

quantile-mapping

display_name: quantile-mapping

temporal-downscaling

display_name: temporal-downscaling


en:
Acknowledgements: The CORE format was proudly inspired by the Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) format, by considering how to leverage the ability of clients issuing HTTP GET range requests for a time-series of remote sensing and aerial imagery (instead of just one image).
License: The Cloud Optimized Raster Encoding (CORE) specifications are released to the public domain under a Creative Commons 1.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.
-----------------------
Summary:
The Cloud Optimized Raster Encoding (CORE) format is being developed for the efficient storage and management of gridded data by applying video encoding algorithms. It is mainly designed for the exchange and preservation of large time series data in environmental data repositories, while in the same time enabling more efficient workflows on the cloud. It can be applied to any large number of similar (in pixel size and image dimensions) raster data layers. CORE is not designed to replace COG but to work together with COG for a collection of many layers (e.g. by offering a fast preview of layers when switching between layers of a time series).
WARNING: Currently only applicable to RGB/Byte imagery. The final CORE specifications may probably be very different from what is written herein or CORE may not ever become productive due to a myriad of reasons (see also 'Major issues to be solved').
With this early public sharing of the format we explicitly support the Open Science agenda, which implies "shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process" (quote from: European Commission, Directorate General for Research and Innovation, 2016. Open innovation, open science, open to the world).
CORE Specifications:
1) a MP4 or WebM video digital multimedia container format (or any future video container playable as HTML video in major browsers)
2) a free to use or open video compression codec such as H.264, VP9, or AV1 (or any future video codec that is open sourced or free to use for end users)
Note: H.264 is currently recommended because of the wide usage with support in all major browsers, fast encoding due to acceleration in hardware (which is currently not the case for AV1 or VP9) and the fact that MPEG LA has allowed the free use for streaming video that is free to the end users. However, please note that H.264 is restricted by patents and its use in proprietary or commercial software requires the payment of royalties to [MPEG LA](https://www.mpegla.com/programs/avc-h-264/). However, when AV1 matures and accelerated hardware encoding becomes available, AV1 is expected to offer 30% to 50% smaller file size in comparison with H.264, while retaining the [same quality](https://trac.ffmpeg.org/wiki/Encode/AV1).
3) the encoding frame rate should be of one frame per second (fps) with each layer segmented in internal tiles, similar to COG, ordered by the main use case when accessing the data: either layer contiguous or tile contiguous;
Note: The internal tile arrangement should support an easy navigation inside the CORE video format, depending on the use case.
4) a CORE file is optimised for streaming with the moov atom at the beginning of the file (e.g. with -movflags faststart) and optional additional optimisations depending on the codec used (e.g. -tune fastdecode -tune zerolatency for H.264)
5) metadata tags inside the moov atom for describing and using geographic image data (that are preferably compatible with the [OGC GeoTIFF standard](https://www.ogc.org/standards/geotiff) or any future standard accepted by the geospatial community) as well as list of original file names corresponding to each CORE layer
6) it needs to encode similar source rasters (such as time series of rasters with the same extent and resolution, or different tiles of the same product; each input raster should be having the same image and pixel size)
7) it provides a mechanism for addressing and requesting overviews (lower resolution data) for a fast display in web browser depending on the map scale (currently external overviews)
Major issues to be solved:
- Internal overviews (similar to COG), by chaining lower resolution videos in the same MP4 container for fast access to overviews first); Currently, overviews are kept as separate files, as external overviews.
- Metadata encoding (how to best encode spatial extent, layer names, and so on, for each of the layer inside the series, which may have a different geographical extent, etc...; Known issues: adding too many tags with FFmpeg which are not part of the standard MP4 moov atom; metadata tags have a limited string length.
- Applicability beyond RGB/Byte datasets; defining a standard way of converting cell values from Int16/UInt16/UInt32/Int32/Float32/Float64/ data types into multi-band Byte values (and reconstructing them back to the original data type within acceptable thresholds)
Example
Notice: The provided CORE (.mp4) examples contain modified Copernicus Sentinel data [2018-2021].
For generating the CORE examples provided, 50 original Sentinel 2 (S-2) TCI data images from an area located inside Switzerland were downloaded from www.copernicus.eu, and then transformed into CORE format using ffmpeg with H.264 encoding using the [x264 library](https://www.videolan.org/developers/x264.html).
DISCLAIMER: Basic scripts are provided for the Geomatics peer review (in 2021) and kept as additional information for the dataset. Nevertheless, please note that software dependencies and libraries, as well as cloud storage paths, may quickly become deprecated over time (after 2021). For compatibility, stable dependencies and libraries released around 2020 should be used.

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

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: extract_S2A_CORE
    Size: 3147 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/387cd755-33df-4543-ae50-529df462b94f/resource/dec6f9ce-cef3-4da1-97a2-42e2d47315a6/download/extract_s2a_core.sh.zip
    Description: Disclaimer: provided for the Geomatics peer review in 2021 and left as additional information for the dataset. Software dependencies and libraries, as well as cloud storage paths, may change over time (after 2021).

media_type: application/zip

en:
Resource Title: View publication in the Digital Object Repository at WSL (DORA)
    Size: 1 bytes
    Format: No Info
    URL: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A28180
    Description:

en:
Resource Title: reproduce_S2A_CORE
    Size: 4313 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/387cd755-33df-4543-ae50-529df462b94f/resource/5d8926a7-e8b9-4f01-a197-7edd0968e5c8/download/reproduce_s2a_core.zip
    Description: Disclaimer: provided for the Geomatics peer review in 2021 and left as additional information for the dataset. Software dependencies and libraries, as well as cloud storage paths, may change over time (after 2021).

en:
Resource Title: CORE Dataset (80 GB)
    Size: 85899345920 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.230/CORE_S2A/
    Description:

core

display_name: core

geodata

display_name: geodata

gridded-data

display_name: gridded-data

raster

display_name: raster

research-data-management

display_name: research-data-management

time-series

display_name: time-series

video-encoding

display_name: video-encoding


en:
Data of snow and sea ice in the McMurdo Sound, October-December 2022. The data was collected as part of the New Zealand Marsden Fund Research Grant 21-VUW-103 "Can Snow Change the Fate of Antarctic Sea Ice?"
The dataset includes raw data of the manual snow and sea ice measurements from snow pits and ice cores (temperature, density, salinity, dO18), measurements of snow water equivalent (SWE), spatial information of snow height (MagnaProbe) and sea ice thickness (EM-31), AWS (air temperature, wind speed, wind direction, relative humidity, pressure), radiations stations (shortwave, longwave, thermal IR, spectral shortwave), differential GPS data (3 fixed stations on different sea ice thicknesses, + 1 rover station for georeferencing UAV measurements), SIMBA buoy temperature (+heated temperature) data (3 buoys during November, 1 buoy for 15 months),  UAV data: RGB, thermal IR, broadband albedo, spectral albedo, Chlorophyll-a from ice cores (bottom 10 cm), NIR reflectivity data of snow at 850 nm, and 940 nm (snow surface, profile, ice surface), photographs (1. overview of field sites, 2. for Structure from Motion for surface roughness, 3. macrophotos of snow) surface impurity concentrations, microCT data of snow microstructure, Denoth probe (density) and InfraSnow (specific surface area - SSA).
See the README file in each dataset for detailed information.

en: Snow on Antarctic Sea Ice - McMurdo Sound 2022

en: sea-ice polar antarctica spatial-variability drone-data snow

envidat

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

envi

en: Environment

en:
Resource Title: magnaprobe_RAW.zip
    Size: 256517 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/75532410-dca7-49a0-813c-274b2b51fa05/resource/cd15f7d9-c236-43eb-be7c-e4002ac7831e/download/magnaprobe_raw.zip
    Description:

en:
Resource Title: EM31_RAW.zip
    Size: 1942229 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/75532410-dca7-49a0-813c-274b2b51fa05/resource/159f3a6b-658f-4656-81b1-73b48493f232/download/em31_raw.zip
    Description:

en:
Resource Title: manual_ice_thickness_RAW.zip
    Size: 144489 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/75532410-dca7-49a0-813c-274b2b51fa05/resource/1e651935-ae61-4b66-a486-3284fe294595/download/manual_ice_thickness_raw.zip
    Description:

antarctica

display_name: antarctica

drone-data

display_name: drone-data

polar

display_name: polar

sea-ice

display_name: sea-ice

snow

display_name: snow

spatial-variability

display_name: spatial-variability


en:
Overview
The SUNWELL Modelling Environment is a combination of data and code that models electricity production from satellite-derived irradiance data and other spatial data sets for all of Switzerland. This ensemble accompanies the publication "The bright side of PV production in snow-covered mountains", published in the Proceedings of the National Academy of Science and reproduces all results and figures of. Code and resources are in their original form (with documentation). A new version with a more generalized application to PV modelling and with more flexibility in terms of input and output formats will be released in the coming months.
 Format
All code is written and has to be executed in Matlab. The input and output data sets are also in the Matlab-specific .mat format. Whenever publicly available, the original data is provided as geotif, .xlsx or other common format.
This is the case for:
- Digital Elevation Model (InputsFromMatlab/MSG/OriginalData/ASTERDEM),
- Landsurface cover type (InputsFromMatlab/MSG/OriginalData/CORINE),
- Population Density (InputsFromMatlab/MSG/OriginalData/popdensRaster,
- Electricity production from three of our validation sites (/Validation/WSL),
- Measured irradiance for two validation sites (/Validation/ASRB)
The ‘Metadata’ documents in the respective folders provide further information about the data sources and processing. Figures are produced either in .pdf or .png format.
 Structure
The central level of the SUNWELL environment holds the 5 Mains, which run the different modelling aspects of the paper; each code is documented separately. Additional code is located in the ‘DataProcessing’ and the ‘functions’ folder. Functions are called in the different Mains.
‘InputsFromMatlab’ contains the radiation and albedo input data sets in separate subfolders (SIS/SISDIR/ALB). The original data is not publicly available, but can be requested for research purposes free of charge. We provide a processed subset of the data set that was used to run the SUNWELL simulations. The MSG subfolder contains additional spatial input data sets.
‘Outputs’ contains the output files from the different mains (matching names, Main_CHallpixels.m  Prod_CHallpixels)
‘Publication_figures’ contains all individual figures from the PNAS publication, as well as the generating code (/code_plot) and the power point figures (/ppts) that provide the combined final figures.
‘Validation’ contains the data sets used in the model validation:
- Electricity production from three of our validation sites (/WSL),
- Measured irradiance for two validation sites (/ASRB)
Electricity production from a validation site at Lac des Toules in Wallis (/LDT), this data set was provided under an NDA and cannot be made publicly available.
Paper Citation:
 - _Annelen Kahl; Jérôme Dujardin; Michael Lehning (2018). Dataset on PV Production in Snow Covered Mountains. PNAS - Proceedings of the National Academy of Sciences. (in press)_

en: snow reflection irradiance photovoltaic energy albedo mountain

en:
Resource Title: PV Data
    Size: 2654822 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/90e36ede-4301-43f3-b0cb-b524d8c81f6b/resource/a2dd7f4f-b4dd-41c5-8ed9-1968af46bbcf/download/pv_daten_wsl_lehning_wfj_slf_laret_19.03.2018.xlsx
    Description:

format: XLS

en:
Resource Title: Dataset on PV Production in Snow Covered Mountains
    Size: 7462505677 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.47/pv.zip
    Description: __Windows users__ use the 7-zip app to extract the zip-file.

albedo

display_name: albedo

energy

display_name: energy

irradiance

display_name: irradiance

mountain

display_name: mountain

photovoltaic

display_name: photovoltaic

reflection

display_name: reflection


en:
Meteorological station at Gemstock (3021 m asl) in Canton Uri. The station includes in/out LW/SW and a snow height sensor.
Data from this station is managed by the permos.ch project. More information: https://www.permos.ch/permafrost-monitoring/field-sites

en: GEM2: Meteorological and snow station at Gemsstock (3021 m asl), Canton Uri, Switzerland

en: shortwave-radiation meteo-station longwave-radiation gemstock snow-height

envidat

en: EnviDat: the Environmental Data Portal

gemstock

display_name: gemstock

longwave-radiation

display_name: longwave-radiation

meteo-station

display_name: meteo-station

shortwave-radiation

display_name: shortwave-radiation

snow-height

display_name: snow-height


swiss-fluxnet-site-davos

en:
The Swiss FluxNet Site Davos is a managed subalpine evergreen forest, located on the Seehorn mountain near Davos in the Swiss Alps. The site is dominated by Norway spruce. The tower is owned by the Federal Office for the Environment (FOEN).
Ecosystem flux measurements of CO2, H2O (since 1997) as well as CH4 and N2O (since 2016) are performed with the eddy covariance method.
In addition to Swiss FluxNet, the site is part of the National Air Pollution Monitoring Network (NABEL), the Long term Forest Ecosystem Research (LWF), the biological drought and growth indicator network (TreeNet) and of ICOS Switzerland (Integrated Carbon Observation System). Since November 2019, the site is an ICOS Class 1 Ecosystem station.
Measurements
- Ecosystem flux measurements of CO2, H2O vapour (since 1997) as well a CH4 and N2O (since 2016) are performed with the eddy-covariance method. This method is based on measurements of trace gas mixing ratios, using infrared gas analyzers (for CO2, H2O vapor) and laser spectrometers (for CH4 and N2O), combined with wind speed and wind direction measurements, using 3D sonic anemometers. To resolve the short-term turbulent fluctuations in the atmosphere, very fast measurements are needed: we measure at 10-20 Hz, i.e., 10-20 times per second. To assess the energy budget of each ecosystem, also radiation sensors and soil climate profiles are installed at the site.
- Sub-canopy eddy fluxes (CO2, H2O, since 2023 also CH4).
- Continuous profile concentration and forest floor flux measurement of CO2, H2O, CH4, N2O.
- Auxiliary micrometeorology and soil climate measurements.
Data availability
Near real-time flux and meteo data uploaded daily to the ICOS Carbon Portal. Processed flux and meteo data are also available from the European Fluxes Database Cluster and part of Fluxnet2015 dataset.
Data policy
ICOS data license:
[https://www.icos-cp.eu/data-services/about-data-portal/data-license](https://www.icos-cp.eu/data-services/about-data-portal/data-license)
Detailed site info:
[https://www.swissfluxnet.ethz.ch/index.php/sites/ch-dav-davos/site-info-ch-dav/](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-dav-davos/site-info-ch-dav/)

en: Swiss FluxNet Site Davos

en: greenhouse-gas meteorological-measurements flux swiss-fluxnet swiss-forest-lab icos eddy-covariance forest

title_for_slug: swiss-fluxnet-site-davos

en:
Resource Title: Processed data
    Size: 1 bytes
    Format: No Info
    URL: http://www.europe-fluxdata.eu/home/site-details?id=CH-Dav
    Description: Processed flux and meteo data are available from the European Fluxes Database Cluster.

en:
Resource Title: Site description
    Size: 320116 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/861bec26-8e58-4796-802d-6ebad6a3484f/resource/49929929-d5d9-43de-bf2a-298230753b46/download/swissfluxnet_dav_sitedescription.pdf
    Description:

format: PDF

media_type: application/pdf

en:
Resource Title: Data access
    Size: 1024 bytes
    Format: No Info
    URL: https://data.icos-cp.eu/portal/#%7B%22filterCategories%22:%7B%22station%22:%5B%22iES_CH-Dav%22%5D%7D%7D
    Description: The flux and meteo data of the Swiss FluxNet site Davos are openly available. Near real-time flux and meteo data are uploaded daily to the ICOS Carbon Portal.

en:
Resource Title: Fluxnet2015 dataset
    Size: 1024 bytes
    Format: No Info
    URL: https://fluxnet.org/data/fluxnet2015-dataset/
    Description: Processed flux and meteo data are also part of the Fluxnet2015 dataset.

eddy-covariance

display_name: eddy-covariance

flux

display_name: flux

forest

display_name: forest

greenhouse-gas

display_name: greenhouse-gas

icos

display_name: icos

meteorological-measurements

display_name: meteorological-measurements

swiss-fluxnet

display_name: swiss-fluxnet

swiss-forest-lab

display_name: swiss-forest-lab


en:
Dataset
This dataset is based on terrestrial laser scanning (TLS) data acquired during winter 2020/2021 in leaf-off conditions, with a Leica BLK 360 instrument following a tree-centric scanning pattern.
The data was acquired on two sites (47.42°N 8.49°E and 47.504°N, 7.78°E), both of which were managed mixed temperate forest stands.
Individual trees were semi-automatically segmented from the co-registered TLS point clouds.
 Background
Accurate estimates of individual tree volume or biomass within forest inventories are essential for calibration and validation of biomass mapping products based on Earth observation data.
Terrestrial laser scanning (TLS) enables detailed and non-destructive volume estimation of individual trees, with existing approaches ranging from simple geometrical features to virtual 3D reconstruction of entire trees. Validating such approaches with weight measurements is a key step before the integration of TLS or other close-range technologies into operational applications such as forest inventories.
In this study, we firstly evaluate individual tree volume estimation approaches based on 3D reconstruction through quantitative structure models (QSM) against destructive reference data of 60 trees and compare them to operational allometric scaling models (ASM).
Secondly, we determine the explanatory power of TLS-derived geometric parameters regarding total tree, stem, coarse wood and fine branch volume.

en: Individual tree TLS point clouds for tree volume estimation

en: lidar terrestiral-laserscanning biomass tree-volume single-tree forest-inventory

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.

envi

en: Environment

en:
Resource Title: site1_WL_group1
    Size: 112302490 bytes
    Format: application/zip
    URL: https://s3-zh.os.switch.ch/pointclouds/20230516_TLSPointClouds_volumeEstimation/data/site1_WL_group1.zip
    Description: **preview_url**:  https://s3-zh.os.switch.ch/pointclouds/20230516_TLSPointClouds_volumeEstimation/vis/site1_WL_group1/site1_WL_group1.html

en:
Resource Title: Individual tree parameters and volume estimates based on TLS point clouds and allometric models
    Size: 42401 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/c82b9485-0b40-41f4-a798-4e4e725cafdc/resource/450e6bd6-f0c2-4c31-b410-52013c50e988/download/tree_parameters_tls_ad_wl.csv
    Description: "ASM" denotes volume estimates calculated by allometric scaling models (as used in Swiss NFI), based on tree height, DBH and D7.
"QSM" denotes volume estimates derived from TLS point clouds by quantitative structure models (QSM).
The remaining variables are geometrical features directly calculated from single tree TLS point clouds.
For more detailed variable descriptions see related publication.

format: CSV

media_type: text/csv

en:
Resource Title: site2_AD
    Size: 41733325 bytes
    Format: application/zip
    URL: https://s3-zh.os.switch.ch/pointclouds/20230516_TLSPointClouds_volumeEstimation/data/site2_AD.zip
    Description: **preview_url**:  https://s3-zh.os.switch.ch/pointclouds/20230516_TLSPointClouds_volumeEstimation/vis/site2_AD/site2_AD.html

en:
Resource Title: site1_WL_group2
    Size: 32505856 bytes
    Format: application/zip
    URL: https://s3-zh.os.switch.ch/pointclouds/20230516_TLSPointClouds_volumeEstimation/data/site1_WL_group2.zip
    Description: **preview_url**:  https://s3-zh.os.switch.ch/pointclouds/20230516_TLSPointClouds_volumeEstimation/vis/site1_WL_group2/site1_WL_group2.html

biomass

display_name: biomass

forest-inventory

display_name: forest-inventory

lidar

display_name: lidar

single-tree

display_name: single-tree

terrestiral-laserscanning

display_name: terrestiral-laserscanning

tree-volume

display_name: tree-volume


en:
Model code and documentation for the downscaling model TopoCLIM which provides methods to downscale climate timeseries from CORDEX RCM data. This scheme specifically addresses the need for hillslope scale atmospheric forcing timeseries for modeling the local impact of regional climate change projections on the land surface in complex terrain. The method has a global scope and is able to generate the full suite of model forcing variables required for hydrological and land surface modeling at hourly timesteps.
A working example is provided in this code archive but for full running of the scheme TopoSCALE is required https://doi.org/10.5194/gmd-7-387-2014 with code available at https://github.com/joelfiddes/tscaleV2. Standard library dependencies are given in the python requirements.txt of the archive with installation instructions in the README.md.
License GPL v.3

en: TopoCLIM v1.0 code

en: toposcale downscaling cryosphere cordex rcm

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Github link to TopoCLIM project
    Size: 1024 bytes
    Format: No Info
    URL: https://github.com/joelfiddes/topoCLIM
    Description:

en:
Resource Title: TopoCLIM v1.0
    Size: 42233916 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3179f1e2-e7fa-4ab5-8949-3b4805f1ea02/resource/fe44c744-6aae-4e8c-a484-2fba1ea1daaf/download/topoclimv.1.0.zip
    Description: Archive of Github repository as of 10 June 2021 including license and documentation and examples.

cordex

display_name: cordex

cryosphere

display_name: cryosphere

downscaling

display_name: downscaling

rcm

display_name: rcm

toposcale

display_name: toposcale


en:
A spatial dataset and tool to simultaneously assess hydropower potential and ecological potential of the Swiss river network (Version 2016)
 Introduction
The steadily growing demand for energy and the simultaneous pursuit of decarbonisation are increasing interest in the expansion of renewable energies worldwide. In Switzerland, various funding projects have been launched to promote technologies in the field of renewable energies and their application as quickly as possible. With the introduction of a funding instrument in 2009, the number of projects submitted to produce renewable energies increased rapidly. The applications for small hydropower plants (≤ 10 MW) were correspondingly numerous. However, the assessment of the environmental impact and its comparison with hydropower importance is still not standardized.
To provide a basis for decision-making, a methodology was developed to determine the overall hydropower potential of a region. A detailed assessment of each river reach, and the systematic and holistic assessment of small hydropower projects at a regional scale are combined here. The assessment of a river reach is conducted at the river space (i.e., the river and adjacent areas) and at the surrounding landscape level. The HYDROpot_integral methodology was developed as part of Carol Hemund's dissertation (2012) at the University of Bern. It allows the evaluation of river reaches holistically, regarding ecological, social, economic and cultural criteria. As a second part of the overall project, the theoretical hydropower (or hydraulic) potential was calculated for the entire river network, which complemnets the spatial assessment. In particular, it is possible to classify river reaches into those that are more suitable for hydropower production (=”use”) and those that are more suitable for protection.
 Material and method
The HYDROpot_Integral method was developed and tested on the basis of cantonal and national data (Hirschi et al. 2013). The method relies on 73 geodata sets. This holistic assessment is the key element of the entire assessment procedure. Its aim is to quantify the importance of the ecosystem functions in terms of services. The river network (GWN07) is divided into reaches of about 450m and for each reach two study units are defined. The river space (RS) records the ecosystem functions of the water body and the nearby riparian area. The length of the RS is 315 m on average in Switzerland and a maximum of 450 m, whereas the width is based on the FOEN definition (BWG 2001: 18f) and varies between 7-107 m. The surrounding landscape (SLS) is the second survey unit that records the ecosystem functions of the surrounding area over a range of 21 m to 321 m. The SLS is calculated over three times the RS width. The length of the SLS is identical to the length of the RS. The ecosystem functions are divided into three types: regulating (service A), cultural (service B) and provisioning (service C) functions. Accordingly, the assessment of the functions is divided into three parts and three values are assigned to each river reach. The more functions there are and the greater their performance, the higher these values are and the more important the corresponding functions are. Hence, these values quantify the importance of the ecosystem functions and the ecological, cultural and economic ecosystem services of each river reach. The concatenation of ecosystem services results in a value (ABC) that can occur in 125 different versions due to the chosen five-level value scale; i.e. each digit of the three-digit number sequence can be assigned a value between 1 and 5. Each of the 125 combinations, and thus each river reach, has its own characteristics determined by the assessments of the three function types. To record the suitability, the combinations are ranked according to their ecological, cultural and economic ecosystem services. These rules mean that the combination that is most suitable for hydropower production at minimum cost in terms of ecological and cultural ecosystem services and has a high economic potential is ranked first; rank 125 indicates the highest ecological and cultural ecosystem services and the lowest economic services and is therefore most suitable for protection. A river reach that is excluded from hydropower use due to legislation, a so-called priority reach, is given rank 126 from the outset and specially marked. A more detailed description of the methods can be found in Hirschi et al. 2013 [Link]. The dataset presented here presents the latest state of the HYDROpot_integral methodology applied at the national level. Only national data that is easily accessible was used in the preparation of the dataset. The cantonal data, such as renaturation and revitalization, would have to be requested by each canton individually and was excluded here. The nationwide value synthesis was made with R.
A list of data sources can be found here [link to text file]
A list of all parameters can be downloaded here [link to PDF and text files]
 Dataset description
Data is presented as a single shapefile. It contains the river network and all assessment results obtained with HYDROpot_Integral.
 Changes in the methodology compared to the original method (Hirschi et. al 2013)
 * RS_A11 Ecomorphology: recorded for the whole of Switzerland and zero values equated with NA;
individual cantons such as Zug and St. Gallen have no mapped values according to the modular
concept of the federal government, Valais and Graubünden only the main valleys, Ticino and Fribourg not
completely (BAFU 2009).
 * RS_A14 Renaturation and revitalization data: not centrally available at the time of data collection.
centrally available, therefore values in GR were equated with NA.
 * RS_A15 Dilution ratio at wastewater treatment plants (WWTPs) for discharges: Zero values
equal to NA.
 * RS_A20 Water flow: use WASTA (2013) with hydroelectric power plants (- 300 kW) under
Federal control and dams serving hydroelectricity (Dam, as of 2013).
 * RS_C05 Synoptic hazard maps: are cantonally managed at the time of data collection,
Values in GR are marked with a 5 so that the systematics in the decision tree is not affected.
is affected.
 * Water quality (RS_A15, RS_A16, RS_A17, RS_A18, RS_A19): for the evaluation of the function type.
A Nature, it is important whether the median of the five values is less than or equal to 3 in total. This
evaluation is based on the decision tree for evaluating GR (Hirschi et al. 2013:22).
Therefore, an evaluation of the station data is made where critical and possible river segments
with poor quality (median less than 3) exist. Only two longer and one short
sections in Switzerland receive a lower median than 3 for water quality.
 * SLS_B06 Visibility: For 99 percent of the river segments (30,733 of 31,062) in the canton of
Bern (2015 reduced version), the landscape area is considered to be visible. Due to this high number
of sections, a large number of viewpoints in the layer of Swisstopo and
the computation time and computability in ArcGIS, the landscape area is classified as generally viewable
(equal to 1).
16 Method
Additional indicators were added (see Appendix B.2):
 * SLS_A21 Dissection
 * SLS_A22 Forest areas
 * SLS_B03 Hiking trails
 * SLS_B10 Residential and vacation homes
 * SLS_B11 Tourist infrastructure
 * SLS_C01 Landfill
 * SLS_C03 Infrastructure
 * SLS_C05 Industry
 * SLS_C06 Agricultural land
Not to be added, although present to some extent:
 * SLS_B06 Cultural assets of national importance: here, too, the calculability of the visibility analysis is
for the whole of Switzerland is limited
 * SLS_A15 Legally binding protection and land use planning: the individual river sections are not
clearly designated, i.e. no geodata exist
The following data are also not supplemented, as they are cantonal data:
 * SLS_A10 Cantonal nature reserves
 * SLS_A16 Forest reserves
 * SLS_A17 Cantonal inventories and contractually protected areas

en: gis decision-making ecosystem-protection hydropower integral-water-management

en:
Resource Title: Indicators
    Size: 1024 bytes
    Format: text/markdown
    URL: https://gitlabext.wsl.ch/hugpeter/hydropot_on_envidat/-/blob/main/indicators.md
    Description: The indicators capture supporting ecosystem functions.

format: markdown

en:
Resource Title: HYDROpot_integral
    Size: 49929041 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2a65b6d6-7471-417e-a67d-b25707b742dc/resource/cbb99ee8-fddf-4091-a070-2c60228341b4/download/hydropot_on_envidat.zip
    Description:

decision-making

display_name: decision-making

ecosystem-protection

display_name: ecosystem-protection

gis

display_name: gis

hydropower

display_name: hydropower

integral-water-management

display_name: integral-water-management


en:
In order to digitally plan a cable line using the QGIS plugin ‘Seilaplan’, maps with various background information are helpful. In this tutorial we show you how to obtain maps that are helpful for cable line planning, for example a national map of Switzerland at different scales,  the NFI vegetation height model or the NFI forest mix rate. For this we explain what WMS datasets are and how to integrate them into QGIS. No download of large data is needed for this, only a good internet connection. Please note that the tutorial language is German!
Link for the integration of WMS data: https://wms.geo.admin.ch/
Link to the description on the Swisstopo website:
https://www.geo.admin.ch/en/geo-services/geo-services/portrayal-services-web-mapping/web-map-services-wms.html
Link to the Seilaplan website: https://seilaplan.wsl.ch
**************************
Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung sind verschiedene Hintergrundkarten hilfreich. In diesem Tutorialvideo zeigen wir, was WMS Daten sind und wie man diese in QGIS einbinden kann. Dafür müssen die Daten nicht heruntergeladen werden. Es braucht lediglich eine gute Internetverbindung. Für die Seillinienplanung hilfreiche Karten sind bspw. die Landeskarte der Schweiz in verschiedenen Massstäben, das Vegetationshöhenmodell LFI oder der Waldmischungsgrad LFI.
Link zur Einbindung der WMS Daten: https://wms.geo.admin.ch/
Link zur Beschreibung auf der Swisstopo Webseite: https://www.geo.admin.ch/de/geo-dienstleistungen/geodienste/darstellungsdienste-webmapping-webgis-anwendungen/web-map-services-wms.html
Link zur Seilaplan-Website: https://seilaplan.wsl.ch

en: Seilaplan Tutorial: Load WMS layers as background maps

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

en:
Resource Title: WMS-Layer als Hintergrundkarten laden
    Size: 946355714 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/96da5435-fcc6-4a25-ba24-234b90cf3dfb/resource/18d13f78-0149-42bc-b962-fdd7bd972e4d/download/seilaplan_tutorial_4_wms_v2.mp4
    Description:

en:
Resource Title: View video on youtube!
    Size: 1024 bytes
    Format: No Info
    URL: https://youtu.be/6ILeTPlOG6A
    Description:

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

wms-data

display_name: wms-data


en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. As an alternative to using the ‘Swiss Geo Downloader’ plugin, the DTM can be obtained directly from Swisstopo. In this tutorial we explain step by step how to download the necessary DTM from the Swisstopo Website, and how to use it in QGIS for the digital planning of a cable line using the plugin ‘Seilaplan’. Please note that the tutorial language is German!
Link to the elevation model on the swisstopo website: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.htmltechnische_details
Link to the rope map website: https://seilaplan.wsl.ch
********************
Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Als Alternative zum Swiss Geo Downloader erklären wir in diesem Tutorial Schritt für Schritt, wie man das nötige Höhenmodell von der Swisstopo Webseite herunterladen und in QGIS zur Seillinienplanung verwenden kann.
Link zum Höhenmodell auf der swisstopo Webseite: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.htmltechnische_details
Link zur Seilaplan-Website: https://seilaplan.wsl.ch

en: Seilaplan Tutorial: DTM download from swisstopo website

en: swisstopo digital-planning swiss-geodata qgis-plugin seilaplan digital-elevation-model geoinformation-software cable-yarding open-source

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.

envi

en: Environment

en:
Resource Title: Herunterladen des DHM von swisstopo Website
    Size: 246551051 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/ed0aaf2e-e5dc-4149-85f2-3bb848a30ffe/resource/6b58a8ae-fb28-42ac-8bec-5db98e69f17e/download/seilaplan_tutorial_2_website.mp4
    Description:

en:
Resource Title: View video on youtube!
    Size: 1024 bytes
    Format: No Info
    URL: https://youtu.be/jUuxp_Xk64k
    Description:

geoinformation-software

display_name: geoinformation-software

swisstopo

display_name: swisstopo


en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. The plugin ‘Swiss Geo Downloader’, which is available for the open source geoinformation software QGIS, allows freely available Swiss geodata to be downloaded and displayed directly within QGIS. It was developed in 2021 by Patricia Moll in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. In this tutorial we describe how to download the high accuracy elevation model ‘swissALTI3D’ with the help of the ‘Swiss Geo Downloader’ and how to use it for digital planning of a cable line with the plugin ‘Seilaplan’. Please note that the tutorial language is German!
Link to the Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader
Link to Seilaplan website: https://seilaplan.wsl.ch
*********************
Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Das Plugin Swiss Geo Downloader, welches für das Open Source Geoinformationssystem QGIS zur Verfügung steht, ermöglicht frei verfügbare Schweizer Geodaten direkt innerhalb von QGIS herunterzuladen und anzuzeigen. Es wurde 2021 von Patricia Moll in Zusammenarbeit mit der eidgenössischen Forschungsanstalt Wald, Schnee und Landschaft WSL entwickelt. In diesem Tutorial beschreiben wir, wie man mit Hilfe des Swiss Geo Downloaders das hochgenaue Höhenmodell swissALTI3D herunterladen und für die Seillinienplanung mit dem Plugin Seilaplan verwenden kann.
Link zum Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader
Link zur Seilaplan-Webseite: https://seilaplan.wsl.ch

en: Seilaplan Tutorial: DTM download with SwissGeoDownloader

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

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Herunterladen des DHM mit SwissGeoDownloader
    Size: 429428137 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/659dc637-e0ca-4393-9f07-13b04290d6ec/resource/05723528-b1c9-4476-a69b-18327d823588/download/seilaplan_tutorial_1_swissgeodownloader.mp4
    Description:

en:
Resource Title: View video on youtube!
    Size: 1024 bytes
    Format: No Info
    URL: https://youtu.be/u7WRrO3GplI
    Description:

swiss-geo-downloader

display_name: swiss-geo-downloader


en:
Close Range Remote Sensing Benchmark for different LiDAR and photogrammetric Sensors in a mixed temperate forest.
Benchmarks are needed to evaluate the performance of different close-range remote sensing devices and approaches, both in terms of efficiency as well as accuracy. In this study we evaluate the performance of two terrestrial (TLS), one handheld mobile (PLS) and two drone based (UAVLS) laser scanning systems to detect trees and extract the diameter at breast height (DBH) in three plots with a steep gradient in tree and understorey vegetation density. As a novelty, we also tested the acquisition of 3D point-clouds using a low-cost action camera (GoPro) in conjunction with the Structure from Motion (SfM) technique and compared its performance with those of the more costly LiDAR devices.

en: Ramerenwald Close Range Remote Sensing Benchmark

en: 3d-point-cloud terrestrial-laser-scanning structure-from-motion unmanned-aerial-vehicle-laser-scanning forest-inventory lidar terrestrial-photogrammetry mobile-laser-scanning

en:
Resource Title: Ramerenwald_Benchmark_FP05
    Size: 25984552141 bytes
    Format: application/zip
    URL: https://s3-zh.os.switch.ch/pointclouds/20230301_Ramerenwald_Benchmark/data/Ramerenwald_Benchmark_FP05.zip
    Description: **preview_url**: https://pointclouds.s3-website-zh.os.switch.ch/20230301_Ramerenwald_Benchmark/vis/Ramerenwald_Benchmark_FP05/Ramerenwald_Benchmark_FP05.html

en:
Resource Title: Ramerenwald_Benchmark_FP08
    Size: 40694815130 bytes
    Format: application/zip
    URL: https://s3-zh.os.switch.ch/pointclouds/20230301_Ramerenwald_Benchmark/data/Ramerenwald_Benchmark_FP08.zip
    Description: **preview_url**: https://pointclouds.s3-website-zh.os.switch.ch/20230301_Ramerenwald_Benchmark/vis/Ramerenwald_Benchmark_FP08/Ramerenwald_Benchmark_FP08.html

en:
Resource Title: Ramerenwald_Benchmark_FP07
    Size: 40050570035 bytes
    Format: application/zip
    URL: https://s3-zh.os.switch.ch/pointclouds/20230301_Ramerenwald_Benchmark/data/Ramerenwald_Benchmark_FP07.zip
    Description: **preview_url**: https://pointclouds.s3-website-zh.os.switch.ch/20230301_Ramerenwald_Benchmark/vis/Ramerenwald_Benchmark_FP07/Ramerenwald_Benchmark_FP07.html

forest-inventory

display_name: forest-inventory

lidar

display_name: lidar

mobile-laser-scanning

display_name: mobile-laser-scanning

structure-from-motion

display_name: structure-from-motion

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

terrestrial-photogrammetry

display_name: terrestrial-photogrammetry

unmanned-aerial-vehicle-laser-scanning

display_name: unmanned-aerial-vehicle-laser-scanning


seilaplan-tutorial-merge-dtm-tiles

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. In this tutorial video, we show how to merge multiple DTM raster tiles into one file, using the QGIS tool ‘Virtual Raster’. This simplifies the digital planning of a cable line using the QGIS plugin ‘Seilaplan’. Please note that the tutorial language is German!
Link to Seilaplan website: https://seilaplan.wsl.ch
***************************
Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. In diesem Tutorialvideo zeigen wir, wie man mit dem QGIS-Plugin Virtuelles Raster mehrere DHM-Kacheln zu einem einzigen Rasterfile zusammenfügen und abspeichern kann. Für die Seillinienplanung mit Seilaplan muss nun nur noch eine Datei, mein neues virtuelles Raster, ausgewählt werden.
Link zur Seilaplan-Website: https://seilaplan.wsl.ch

en: Seilaplan Tutorial: Merge DTM tiles

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

title_for_slug: seilaplan-tutorial-merge-dtm-tiles

en:
Resource Title: View video on youtube!
    Size: 1024 bytes
    Format: No Info
    URL: https://youtu.be/UcORl_PU3No
    Description:

en:
Resource Title: DHM-Kacheln zusammenfügen
    Size: 292363579 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/15cd0733-843f-4491-9998-f437b4cc1df4/resource/ba9ff01f-f7b8-4b35-957d-ff35889a7979/download/seilaplan_tutorial_3_virtuellesraseter.mp4
    Description:

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geodata-processing

display_name: geodata-processing

raster-processing

display_name: raster-processing


en: We modelled the global distribution of 730 amphibian, 1276 reptile, and 1961 mammal species globally as a function of current climate at a 0.5° spatial resolution using four different predictor groups composed of different combinations of input variables: mean climatic conditions, spatial climatic variability, and temporal (interannual) climatic variability.

en: Global species distributions for mammals, reptiles, and amphibians

en: reptiles mammals random-forests chelsa niche-models range-maps sdm amphibians generalized-additive-models climate-variablity interannual-climate-variability species-distribution-models generalized-linear-models iucn

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.

envi

en: Environment

en:
Resource Title: Reptiles
    Size: 2147483648 bytes
    Format: application/zip
    URL: https://envicloud.os.zhdk.cloud.switch.ch/doi/envidat.354/reptiles.zip
    Description: Species distribution models based on different climate predictor groups

en:
Resource Title:
    Size: 1548568 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/b01e0b24-8806-4cfc-b9eb-550fe29e4a40/download/climate_predictors.zip
    Description: File containing the climate predictors as SAGA grid files (.sgrd)

en:
Resource Title:
    Size: 4848 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/09bc5a49-e1ef-4491-928e-6c4440fad9d1/download/readme.txt
    Description: Readme file containing the file naming convention, file dimensions, and variable names

format: TXT

media_type: text/plain

en:
Resource Title: Mammals
    Size: 3650722202 bytes
    Format: application/zip
    URL: https://envicloud.os.zhdk.cloud.switch.ch/doi/envidat.354/mammals.zip
    Description: Species distribution models based on different climate predictor groups

en:
Resource Title: Amphibians
    Size: 1181116006 bytes
    Format: application/zip
    URL: https://envicloud.os.zhdk.cloud.switch.ch/doi/envidat.354/amphibians.zip
    Description: Species distribution models based on different climate predictor groups

en:
Resource Title: mammals_metadata
    Size: 54466 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/4589c081-818c-4873-8b15-8f399464b434/download/mammals_metadata.txt
    Description: File containing the record dimension, genus, and species of the respective netcdf files

en:
Resource Title: amphibials_metadata
    Size: 18938 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/9bff87c6-e1ce-4553-accb-43af8eaca72e/download/amphibians_metadata.txt
    Description: File containing the record dimension, genus, and species of the respective netcdf files

en:
Resource Title: reptiles_metadata
    Size: 32524 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/fa2b6ee3-5067-4eb4-b8a0-fc1cb256a637/download/reptiles_metadata.txt
    Description: File containing the record dimension, genus, and species of the respective netcdf files

amphibians

display_name: amphibians

chelsa

display_name: chelsa

climate-variablity

display_name: climate-variablity

generalized-additive-models

display_name: generalized-additive-models

generalized-linear-models

display_name: generalized-linear-models

interannual-climate-variability

display_name: interannual-climate-variability

iucn

display_name: iucn

mammals

display_name: mammals

niche-models

display_name: niche-models

random-forests

display_name: random-forests

range-maps

display_name: range-maps

reptiles

display_name: reptiles

sdm

display_name: sdm

species-distribution-models

display_name: species-distribution-models


en:
When snow is compressed with a certain speed, micro-snowquakes are triggered in the porous structure of bonded crystals. The present dataset covers uniaxial compression experiments of snow at different strain rates and concurrent X-ray tomography imaging documenting this feature.
The experiments were conducted in a micro-compression stage operated in the X-ray tomography scanner in the SLF cold laboratory. The dataset comprises the compression force data of 17 compression experiments, the 3D image data from 4 X-ray tomography scans and the results of numerical simulations.

en: Compressive stick slip and snow-micro-quakes

en: snow-mechanics snow compression-experiments microstructure x-ray-tomography

envidat

en: EnviDat: the Environmental Data Portal

compression-experiments

display_name: compression-experiments

microstructure

display_name: microstructure

snow

display_name: snow

snow-mechanics

display_name: snow-mechanics

x-ray-tomography

display_name: x-ray-tomography


en:
For the investigation of microstructural and mechanical properties of snow unconfined compression experiments and 3D computed tomography (CT) imaging were performed on sintered rounded grain snow and spherical model snow. The spherical model snow was generated to create geometrically simplified, well-defined microstructures for calibration of numerical models, such as discrete element models (DEM) in which the microstructure is represented by spherical particles.
In the experiments, microstructural variation was created by varying the sintering time (contact size) and the density of the ice sphere samples (number of contacts). The 3D CT images allow for a complete reconstruction of the entire experimental sample (cylindrical sample dimension: diameter = 33.6 mm; height = 14 mm).

en: Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples

en: microstructure 3d-ct-images discrete-element-modelling unconfined-compression-experiments spherical-model-snow snow-mechanics

en:
Resource Title: Data Structure (Python Notebook)
    Size: 335872 bytes
    Format: application/x-ipynb+json
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.83/3dct/Data_Structure.ipynb
    Description:

en:
Resource Title: Data Access
    Size: 161061273600 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.83/3dct/Data/
    Description:

en:
Resource Title: README.txt
    Size: 1925 bytes
    Format: text/plain
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.83/3dct/readme.txt
    Description:

discrete-element-modelling

display_name: discrete-element-modelling

spherical-model-snow

display_name: spherical-model-snow

unconfined-compression-experiments

display_name: unconfined-compression-experiments


en:
This dataset provides 50 years of seasonal synthetic hourly time series for five meteorological variables: incoming shortwave radiation, total precipitation, relative humidity, 2-meter air temperature and wind speed.
The data are generated from observational records (1990–present) from nine MeteoSwiss stations (ABO, BAS, BER, LUG, PUY, SCU, SIO, STG, WFJ). We use a sampling approach that preserves both the temporal structure and inter-variable dependencies. Specifically, the time series are constructed by drawing 7-day blocks from historical observations, ensuring realistic short-term variability and maintaining the physical coherence between variables.
The synthetic sequences are constrained to follow daily temperature change trajectories corresponding to three future climate scenarios for the period 2040–2070: RCP2.6, RCP8.5 and RCP0: a counterfactual scenario with no long-term warming trend, but with temperature variability consistent with the RCP2.6 one.
The temperature constraints are derived from projections downscaled at the staiton level, available at: https://www.envidat.ch//metadata/climate-change-scenarios-at-hourly-resolution

en: Meteorological Time Series Aligned with Projected Temperature Changes

en: air-temperature precipitation relative-humidity meteo-station time-series wind-speed shortwave-radiation speed2zero climate-change

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.

envi

en: Environment

air-temperature

display_name: air-temperature

climate-change

display_name: climate-change

meteo-station

display_name: meteo-station

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

shortwave-radiation

display_name: shortwave-radiation

time-series

display_name: time-series

wind-speed

display_name: wind-speed


en:
Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings.
FORECOMON 2021 - the 9th forest ecosystem monitoring conference.
7-9 June 2021, WSL, Birmensdorf, Switzerland
The goal of FORECOMON 2021 is to highlight the extensive ICP Forests data series on forest growth, phenology and leaf area index, biodiversity and ground vegetation, foliage and litter fall, ambient air quality, deposition, meteorology, soil and crown condition. We combine novel modeling and assessment approaches and integrate long-term trends to assess air pollution and climate effects on European forests and related ecosystem services. Latest results and conclusions from local scale to European scale studies will be presented and discussed.
Copyright © 2021 by WSL, Birmensdorf
The authors are responsible for the content of their contribution.

en: Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings. FORECOMON 2021 - the 9th forest ecosystem monitoring conference. 7–9 June 2021, Birmensdorf, Switzerland

en: forest long-term-monitoring monitoring air-pollution long-term-forest-ecosystem-research

en:
Resource Title: Deprecated version 1.0
    Size: 2699168 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6c2c3d5b-8b2f-4c7b-b996-46df4ccf2b20/resource/1928196d-5fee-48c1-9b30-66362abf2045/download/icp_abstractband_web.pdf
    Description: First version of the proceedings containing errors. This early version it is kept, for traceability purposes, in conformance with DOI rules.

en:
Resource Title: FORECOMON – Proceedings
    Size: 2920688 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6c2c3d5b-8b2f-4c7b-b996-46df4ccf2b20/resource/ab0b32ad-43fa-41c3-93bd-68b6d6b7e4e7/download/abstractband_a4_forecomon_vrs14.pdf
    Description: Latest version

en:
Resource Title: Link to Proceedings in DORA WSL
    Size: 1 bytes
    Format: No Info
    URL: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A27202
    Description:

air-pollution

display_name: air-pollution

forest

display_name: forest

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

long-term-monitoring

display_name: long-term-monitoring

monitoring

display_name: monitoring


en:
Here debrisInterMixing until version 7 is provided for download. Further versions as well as installation instructions and tutorials and discussion forums (mostly in german) can be acessed at murgang.org (choose "als Gast anmelden" and then scroll to the bottom). The first OpenFoam-compatible Version 2.3.x are available as supplement to v. Boetticher, A., Turowski, J. M., McArdell,W. B., Rickenmann, D., Hürlimann, M., Scheidl, C., and Kirchner, J. W.: DebrisInterMixing-2.3: A Finite Volume solver for three dimensional debris flow simulations based on two calibration parameters. Part two: model validation with experiments. Geoscientific Model Development, 10, 11: 3963-3978. doi: 10.5194/gmd-10-3963-2017.
DebrisInterMixing is a Volume-of-Fluid based Finite Volume code that accounts for shear-thinning sensitive shares of fine sediment suspension together with pressure-sensitive components of the gravel grains within debris flow mixtures. All model properties can be derived from a material sample except for a grid-sensitive calibration parameter.
For more information, please contact albrecht.vonboetticher@wasserbau.ch.
For a recent summary on applications see the DFHM8 contribution at https://www.e3s-conferences.org/articles/e3sconf/abs/2023/52/e3sconf_dfhm82023_02024/e3sconf_dfhm82023_02024.html - DOI: https://doi.org/10.1051/e3sconf/202341502024
UPDATE: DebrisInterMixing for OpenFOAM-7 is available, please contact albrecht.vonboetticher@wasserbau.ch. DebrisInterMixing with OpenFOAM-10 is ready but not yet validated.

en: Three-dimensional debris flow simulation tool debrisInterMixing

en: interfoam finite-volumes natural-hazard debris-flow dberisintermixing murgang hangmuren barrier-impact-simulation shallow-landslide

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Installation Instructions debrisInterMixing4
    Size: 79243 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7fa56c27-61f3-4eaa-b150-b07d561e5c34/resource/7f80b14c-152e-4494-900a-9470e6d13520/download/readme_debrisintermixing4.pdf
    Description: These are the installation instructions for debrisInterMixing4

en:
Resource Title: debrisInterMixing-4
    Size: 4350780 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7fa56c27-61f3-4eaa-b150-b07d561e5c34/resource/e72d9355-3bc9-4fd6-8945-1609f5370d56/download/debrisintermixing4x.zip
    Description: This version of debrisInterMixing is based on OpenFOAM Version 4.x and was tested on Ubuntu 18.04.1 LTS.
Please follow the instructions given in ReadMe_debrisInterMixing4.pdf for installation.

en:
Resource Title: putMyContentInFolderUsername-7.zip
    Size: 3777290 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/7fa56c27-61f3-4eaa-b150-b07d561e5c34/resource/8fa5bf42-7a29-4784-be49-a378b25d213b/download/putmycontentinfolderusername-7.zip
    Description:

en:
Resource Title: ReadMe_debrisInterMixing7.pdf
    Size: 147007 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7fa56c27-61f3-4eaa-b150-b07d561e5c34/resource/89031478-a175-4a3a-8930-935f8db6a7c8/download/readme_debrisintermixing7.pdf
    Description: Please install OpenFOAM 7 on a UBUNTU Linux system following the instructions given in readme_debrisintermixing-7.pdf
After a successful OpenFOAM installation, copy the applications-Folder from putMyContent-.zip into the OpenFOAM-User directory and follow the instructions in readme_debrisintermixing-7.pdf  to install debrisInterMixing 7.

If you use UBUNTU 24-04 you might have troubles getting openmpi, I attached a modifiesd instruction installtionOF7Ubuntu20.04.5LTS.txt for a workaround.

en:
Resource Title: debrisInterMixing-6
    Size: 1760632 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7fa56c27-61f3-4eaa-b150-b07d561e5c34/resource/3fdfc2a4-d1ac-43ba-9397-0e338705a6d3/download/debrisintermixing-6.zip
    Description: debrisInterMixing for OF-Version 6

en:
Resource Title: Installation Instructions for debrisInterMixing-6
    Size: 144462 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7fa56c27-61f3-4eaa-b150-b07d561e5c34/resource/671a3da0-326e-4fcb-8bcb-d2080afa6b27/download/readme_debrisintermixing6.pdf
    Description: These are the installation instructions for debrisInterMixing6

barrier-impact-simulation

display_name: barrier-impact-simulation

dberisintermixing

display_name: dberisintermixing

debris-flow

display_name: debris-flow

finite-volumes

display_name: finite-volumes

hangmuren

display_name: hangmuren

interfoam

display_name: interfoam

murgang

display_name: murgang

natural-hazard

display_name: natural-hazard

shallow-landslide

display_name: shallow-landslide


en:
In 2000, a permanent forest plot of 10 ha has been established in the core zone of the primeval beech forest of Uholka.
 All living and dead trees with a diameter at breast height (DBH) ≥ 60 mm were identified to species, DBH measured, stems tagged and mapped.
Since then, the plot has been remeasured in 2005, 2010, and 2015. In total, 4,820 individual trees were measured with 14,116 individual measurements throughout all four inventories.
In spring 2018, an Airborne Laser Scan was carried out, covering the Uholka‐Shyrokyi Luh forest. This data set allows us to derive a high‐resolution digital elevation model (DEM) of the plot area.
The data set allows for important insights into the development and the spatial and temporal dynamics of primeval beech forests.
The detailed dataset description can be found in Stillhard et. al (2019): https://doi.org/10.1002/ecy.2845

en: Stand inventory data from the 10‐ha forest research plot in Uholka, Ukraine

en: permanent-forest-plot-data carpathian-biosphere-reserve forest-structure stand-inventory-data long-term-data-sets dem forest-dynamics fagus-sylvatica primeval-beech-forest forest

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.

envi

en: Environment

carpathian-biosphere-reserve

display_name: carpathian-biosphere-reserve

dem

display_name: dem

fagus-sylvatica

display_name: fagus-sylvatica

forest-dynamics

display_name: forest-dynamics

forest-structure

display_name: forest-structure

long-term-data-sets

display_name: long-term-data-sets

permanent-forest-plot-data

display_name: permanent-forest-plot-data

primeval-beech-forest

display_name: primeval-beech-forest

stand-inventory-data

display_name: stand-inventory-data


urban-birds-point-counts-data

en:
The study area included the cities of Basel, Lugano and Zurich. The sampling design reflected four main city districts related to four categories of tree cover (Figure 1): 1) industrial/commercial areas, 0-20% tree cover; 2) residential areas, 20-40% tree cover; 3) urban parks and cemeteries, 40-60% tree cover; 4) peri-urban forests (natural/semi-natural forests), 60-100% tree cover. The tree cover gradient was evaluated across a square grid with a square side length of 100 m. For each square, we evaluated the area covered by urban trees using the Urban Atlas Street Tree Layer 2018 (European Union’s Copernicus Land Monitoring Service information, 2021).
In each city, we established eight transects of 1.2 km, two for each tree cover category. Transects crossed contiguous grid squares belonging to the same tree cover categories as much as possible. We performed aural-visual point counts of birds every 200 m along each transect (six points per transect) during the breeding season (April-June 2024) (Bibby et al., 2000). The transects were walked at the time of highest activity of birds, which is from thirty minutes after sunrise until 4 hours later. Each transect was walked twice, 20-60 days apart, to account for imperfect detection of birds and sample completeness (Balestrieri et al., 2017; Kéry et al., 2005).

en: Urban birds point counts data

en: spatially-distributed-sampling environmental-gradients birds urban biodiversity periurban

title_for_slug: urban-birds-point-counts-data

biodiversity

display_name: biodiversity

birds

display_name: birds

environmental-gradients

display_name: environmental-gradients

periurban

display_name: periurban

spatially-distributed-sampling

display_name: spatially-distributed-sampling

urban

display_name: urban


en: This dataset comprises environmental and insect larval data from 24 artificial dendrotelms (water-filled tree holes) created in beech trees (Fagus sylvatica) in six old-growth forest patches connecting two forest nature reserves in the Steigerwald in Germany.

en: trems diversity water-filled-tree-holes forest metacommunity steigerwald insects dendrotelms body-size stepping-stones invertebrates old-growth-islands fagus-sylvatica european-beech germany

en:
Resource Title: Community.xlsx
    Size: 10640 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/19176372-9c60-444d-8281-aebd949d273a/resource/2d154092-cce2-4fa1-9112-61a176ed3777/download/community.xlsx
    Description: Dataset on sampled invertebrate communities

en:
Resource Title: Environmental.csv
    Size: 5547 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/19176372-9c60-444d-8281-aebd949d273a/resource/587806e5-b705-40a8-a9d6-af760617c2de/download/environmental.csv
    Description: Dataset with environmental data

en:
Resource Title: Individuals.xlsx
    Size: 124438 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/19176372-9c60-444d-8281-aebd949d273a/resource/77bf43a7-783d-46bd-8b6c-56595131be9b/download/individuals.xlsx
    Description: Dataset on body-length measures of all sampled individuals

body-size

display_name: body-size

dendrotelms

display_name: dendrotelms

diversity

display_name: diversity

european-beech

display_name: european-beech

forest

display_name: forest

germany

display_name: germany

insects

display_name: insects

invertebrates

display_name: invertebrates

metacommunity

display_name: metacommunity

old-growth-islands

display_name: old-growth-islands

steigerwald

display_name: steigerwald

stepping-stones

display_name: stepping-stones

trems

display_name: trems

water-filled-tree-holes

display_name: water-filled-tree-holes


en:
We established our study sites in the cities of Basel, Lugano and Zurich. We characterised urban tree cover of each city using a rectangular grid with squares of 100x100 m. Within each square, we measured the area covered by urban trees using the European Union's Copernicus Land Monitoring Service information, Urban Atlas Street Tree Layer 2018 [https://doi.org/10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c](https://doi.org/10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c).
Then we assigned each square to three categories of urban tree cover that roughly represented the main types of urban uses:
1) low cover, industrial/commercial areas, 0-20% tree cover;
2) intermediate cover, residential areas, 20-40% tree cover;
3) high cover, urban parks and cemeteries, 40-60% tree cover.
-br/--br/-
We measured bird predation rate on the non-native insect larvae of the horse chestnut leaf miner (HCLM) Cameraria ohridella, an invasive moth that lays eggs and completes its larval and pupal development stages within the leaves of the horse chestnut Aesculus hippocastanus. The larvae feed on leaf fluids and tissue while creating mines within the leaf, which ultimately results in early leaf browning and loss of photosynthetic activity. We collected roughly ten twigs from each tree, including five twigs from the inner and five from the outer crown. Each twig carried 2-4 leaves, for a total of 3408 leaflets. Leaves were stored for ~10 weeks in a refrigerated room at 4 degrees C. We checked all HCLM mines using a stereo microscope and distinguished among open and close mines.
Open mines were further divided based on the opening hole, whether it was a small round exit hole of the larva or the parasitoid, or an irregularly shaped, large bird predation hole.

en: Urban bird predation on horse chestnut leaf miner Cameraria ohridella in three Swiss cities

en: birds biodiversity plant-insect-interaction insect-herbivores urban-ecology urban-biodiversity larvae insects

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Urban_Birds_predation_HCLM.xlsx
    Size: 838701 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/529759b5-c550-42b9-94e1-b982afcebfb9/resource/46ed81e5-5d88-410a-ab27-1e4085783bc1/download/urban_birds_predation_hclm.xlsx
    Description:

en:
Resource Title: Urban_Birds_predation_HCLM.xlsx
    Size: 838540 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/529759b5-c550-42b9-94e1-b982afcebfb9/resource/ed64e814-87d3-4166-bad2-6da29fc75b7a/download/urban_birds_predation_hclm.xlsx
    Description:

biodiversity

display_name: biodiversity

birds

display_name: birds

insect-herbivores

display_name: insect-herbivores

larvae

display_name: larvae

plant-insect-interaction

display_name: plant-insect-interaction

urban-biodiversity

display_name: urban-biodiversity

urban-ecology

display_name: urban-ecology


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

en: Urban bird predation on artificial caterpillars

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

biodiversity-experiment

display_name: biodiversity-experiment

periurban

display_name: periurban

pest-invasion

display_name: pest-invasion

urban

display_name: urban


en:
We captured birds in urban parks and peri-urban forests in the cities of Lugano and Zurich. The urban sites were located in an urban forest (Lugano) and in a cemetery (Zurich), and the bird assemblages were comparable with those of the surrounding forests.
We captured individual birds during sessions lasting multiple days using mist-nets, concentrating the activities within 3-4 hours after sunrise and before sunset. We extracted birds from nets using single-use nitrile gloves and gently wiped their body parts with a dry foam swab MW940 (Medical Wire & Equipment), which was then placed in a screw-capped tube (2 ml), which was previously filled with 1 ml ethanol puriss. (Sigma-Aldrich) under sterile conditions.Then, we marked each bird with an alphanumeric leg band, identified the species, determined the sex and age whenever possible, measured for relevant biometrics (e.g. wing chord), the amount of body fat and pectoral muscle (i.e. body condition), and weighed.
Afterwards, we placed each bird in a disposable paper bag within a cotton bag that ensured respiration and left it for few minutes in a safe and calm place to allow for defecation and the collection of faecal samples. The faecal sample was collected from insectivorous and omnivorous birds, and few granivorous birds that are known to occasionally eat invertebrates, such as the house sparrow Passer domesticus.
After releasing the bird, we stored the faecal sample in a screw-capped tube (2 ml), which was previously filled with 1 ml ethanol puriss. (Sigma-Aldrich) under sterile conditions. We wore single-use nitrile gloves and used sterile toothpicks to collect solid samples. The tubes were initially stored in the refrigerator during the field campaign and no later than seven days after collection at -20°C until prepared for DNA extraction.
DNA extraction and library preparation was performed at WSL Phytopathology facilites, Sequencing was performed at Lausanne Genomic Technologies Facility (University of Lausanne; [https://wp.unil.ch/gtf/](https://wp.unil.ch/gtf/)) on an AVITI benchtop sequencing system (Element Biosciences). Bioinformatics was performed at the Genetic Diversity Center (ETH Zurich) using a custom pipeline.

en: Urban bird capture data with prey species and fungal community

en: urban biodiversity urban-ecology fungal-pathogen urban-biodiversity insects fungi birds

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.

envi

en: Environment

fungal-pathogen

display_name: fungal-pathogen

fungi

display_name: fungi

insects

display_name: insects


en: This dataset contains hydrogen and carbon isotope data from 73 tree and shrub species grown in a common garden (Kannenfeldpark) in Basel, Switzerland. Leaf and twig samples were collected in August 2019. The isotope measurements cover various organic compounds, including sugars, cellulose, and (lignin) methoxy groups, as well as leaf and twig xylem water. Details on sample preparation and isotope analysis are provided in Schuler et al. (2023) for carbohydrates and water, and in Wieland et al. (in review) for methoxy groups.

en: Stable isotope data from 73 tree and shrub species in a common garden in Basel Switzerland

en: methoxy-groups isotopes carbohydrates tree-species common-garden

carbohydrates

display_name: carbohydrates

common-garden

display_name: common-garden

isotopes

display_name: isotopes

methoxy-groups

display_name: methoxy-groups

tree-species

display_name: tree-species


en: The diversity and network complexity of prokaryotic and fungal communities and their relationships with soil multifunctionality (SMF) – an integrative index for C-, N- and P-cycling functions – was investigated along a 3,000-km latitudinal transect across Europe (37° to 62°N), spanning biomes from Mediterranean drylands, temperate to boreal forests.

en: Soil microbial diversity and multifunctionality across European biomes

en: soil-microbiome fungi prokaryotes soil-mulitfunctionality latitudinal-gradient microbial-biodiversity

en:
Resource Title: 16S_Han et al_EUgradient.xlsx
    Size: 1592467 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/81f8917a-95b6-45c3-a6bb-3385eaf8dddf/resource/f90ec77d-30a1-4e2f-a763-688f7f011013/download/16s_han-et-al_eugradient.xlsx
    Description: Diversity of prokaryotes (16S gene sequencing) containing: 1) ASV (Amplicon Sequence Variants) table: abundance of ASV in each sample and 2) Taxonomy table: taxonomic classification of each ASV.

en:
Resource Title: Han_et_al_GCB_2025.xlsx
    Size: 41152 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/81f8917a-95b6-45c3-a6bb-3385eaf8dddf/resource/2df1e8b4-e021-4d64-85b0-ba2c325986f1/download/han_et_al_gcb_2025.xlsx
    Description: Metadata, soil properties and soil microbial functions for each sites across the European gradient.

en:
Resource Title: ITS_Han et al_EUgradient.xlsx
    Size: 1132688 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/81f8917a-95b6-45c3-a6bb-3385eaf8dddf/resource/36dfe0f2-3d72-4ba8-ae37-48185214682a/download/its_han-et-al_eugradient.xlsx
    Description: Diversity of fungi (ITS region sequencing) containing: 1) ASV (Amplicon Sequence Variants) table: abundance of ASV in each sample and 2) Taxonomy table: taxonomic classification of each ASV.

latitudinal-gradient

display_name: latitudinal-gradient

microbial-biodiversity

display_name: microbial-biodiversity

prokaryotes

display_name: prokaryotes

soil-microbiome

display_name: soil-microbiome

soil-mulitfunctionality

display_name: soil-mulitfunctionality


en:
This dataset supports a related publication (Sigmund et al., 2025) and contains
- results of four **large-eddy simulations** (LES) coupled to a Lagrangian model (LM) for snow transport, aiming to reproduce field measurements, especially latent heat fluxes, at the S17 site near Syowa Station, East Antarctica, in conditions of drifting and blowing snow,
- references to the **source code** of the LES-LM model,
- the source code and results of a simple **one-dimensional (1D) model** inspired by the large-scale model CRYOWRF (Sharma et al., 2023), aiming to reproduce the LES-LM results,
- post-processed **measurements** shown in the figures of the related publication,
- **programming code** for post-processing and plotting the results.
The LES-LM simulations solve the Navier-Stokes equations for incompressible flows and advection-diffusion equations for air temperature and specific humidity in a domain of 19.2 x 18.32 x 18.32 m³. In these simulations, the airflow is driven by a prescribed large-scale pressure gradient. We assume that the air density is constant (1.18 kg/m³) and the snow particles have a spherical shape and a density of 918.4 kg/m³. Further methodological details are described in the related publication. The 1D model and post-processing code was created using the R software version 4.3.2 (R Core Team, 2024).
References
- Sharma, V., Gerber, F., & Lehning, M. (2023): Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling. Geosci. Model Dev. 16, 719–749. [https://doi.org/10.5194/gmd-16-719-2023](https://doi.org/10.5194/gmd-16-719-2023)
- Sigmund, A., Melo, D. B., Dujardin, J., Nishimura, K., & Lehning, M. (2025). Parameterizing snow sublimation in conditions of drifting and blowing snow. Journal of Advances in Modeling Earth Systems, 17, e2024MS004332. [https://doi.org/10.1029/2024MS004332](https://doi.org/10.1029/2024MS004332)

en: Modeled and measured fluxes of latent and sensible heat and snow transport at S17 near Syowa in Antarctica

en: snow-sublimation antarctica parameterization blowing-snow drifting-snow turbulence large-eddy-simulation

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: (f) LES-LM_particles_case_2.Rdata
    Size: 1288490189 bytes
    Format: application/x-r-data
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_particles_case_2.Rdata
    Description: Properties of individual drifting and blowing snow particles in the LES-LM simulation of Case 2.

en:
Resource Title: (k) Postprocessing_code.zip
    Size: 417382 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/Postprocessing_code.zip
    Description: R scripts used to post-process the results of the LES-LM model and 1D model and produce the figures.

en:
Resource Title: (c) LES-LM_code_settings.zip
    Size: 38912 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_code_settings.zip
    Description: Simulation-specific settings (part of the LES-LM source code).

en:
Resource Title: (h) LES-LM_particles_case_3b.Rdata
    Size: 2040109466 bytes
    Format: application/x-r-data
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_particles_case_3b.Rdata
    Description: Properties of individual drifting and blowing snow particles in the LES-LM simulation of Case 3b.

en:
Resource Title: (j) Turbulence_measurements_case_1.txt
    Size: 1258291 bytes
    Format: text/plain
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/Turbulence_measurements_case_1.txt
    Description: Post-processed high-frequency measurements used to plot turbulence cospectra (data underlying Figure S2 of the related publication). Further measurements are published in a related dataset (Sigmund et al., 2021).

en:
Resource Title: (e) LES-LM_particles_case_1.Rdata
    Size: 1036936806 bytes
    Format: application/x-r-data
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_particles_case_1.Rdata
    Description: Properties of individual drifting and blowing snow particles in the LES-LM simulation of Case 1.

en:
Resource Title: (d) LES-LM_main_results.zip
    Size: 22963814 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_main_results.zip
    Description: Main results of the LES-LM simulations. We do not provide the complete raw output of the simulations because of the large amount of data. For example, the three-dimensional fields of wind velocity components, air temperature and specific humidity are only provided in horizontally averaged form.

en:
Resource Title: (b) Data_of_figures.zip
    Size: 51098 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/Data_of_figures.zip
    Description: Folder containing the data (csv files) visualized in figures of the related publication. The filenames specify the respective figure(s). However, data shown in Figures S5 and S6 are included in data resource (d).

en:
Resource Title: (a) Readme.pdf
    Size: 418202 bytes
    Format: application/pdf
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/Readme.pdf
    Description: Meta data for the whole dataset including a link to the LES-LM source code.

en:
Resource Title: (g) LES-LM_particles_case_3a.Rdata
    Size: 2147483648 bytes
    Format: application/x-r-data
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_particles_case_3a.Rdata
    Description: Properties of individual drifting and blowing snow particles in the LES-LM simulation of Case 3a.

en:
Resource Title: (i) 1D_model_code.zip
    Size: 29082 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/1D_model_code.zip
    Description: Source code of the 1D model (R scripts).

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

drifting-snow

display_name: drifting-snow

large-eddy-simulation

display_name: large-eddy-simulation

parameterization

display_name: parameterization

snow-sublimation

display_name: snow-sublimation

turbulence

display_name: turbulence


en: The TypoCH scoring system (Eggenberg & Bornand 2023), which is widely used in Switzerland, provides good results as classification method for vegetation types based on Delarze et al. (2015). However, the reference list contained species with no diagnostic value and important character species were missing. We therefore made a first attempt to modify the list based on numerical methods and expert knowledge to improve the classification success, at least for vegetation types of the open land (i.e. grasslands, fens, bogs).

en: Modified TypoCH reference list of diagnostic species for the classification of vegetation types in Switzerland

en: phytosociology vegetation-classification typoch vegetation-type character-species diagnostic-species

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.

envi

en: Environment

en:
Resource Title: TypoCH_modified list.csv
    Size: 496727 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bcf50c9d-3b31-4aa7-a774-57a8f6f60ed7/resource/47adb4a8-f089-4622-b525-6dff0da104d9/download/typoch_modified-list.csv
    Description: The file contains the vegetation types and the modified list of diagnostic species (based on Delarze et al. (2015). The numbers indicate the weight of a species in the particular vegetation type for the calculation of the TypoCH score:
1) accompanying species -> 1 point
2) dominant accompanying species (if >10% cover in the plot) -> 2 points
3) character species -> 4 points
4) dominant character species (if >10% cover in the plot) -> 8 points

en:
Resource Title: How the TypoCH list was modified.pdf
    Size: 77776 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/bcf50c9d-3b31-4aa7-a774-57a8f6f60ed7/resource/aa2096a9-b20b-4ca8-a586-84fea79930e6/download/how-the-typoch-list-was-modified.pdf
    Description: Describes details on the modification procedure to improve the TypoCH reference list.

character-species

display_name: character-species

diagnostic-species

display_name: diagnostic-species

phytosociology

display_name: phytosociology

typoch

display_name: typoch

vegetation-classification

display_name: vegetation-classification

vegetation-type

display_name: vegetation-type