en:
This dataset accompanies the article Factors influencing public support for forest restoration in Europe: Evidence from Sweden and Spain, published in the journal Ecosystems and People. It presents results from a multi-country survey exploring public perceptions of forests and support for forest restoration in Västerbotten County (Sweden) and the Castilla y León autonomous community (Spain).
Between March and September 2024, structured questionnaires were distributed to 3,000 randomly selected households, yielding 241 valid responses after data cleaning (171 from Sweden and 70 from Spain). The dataset includes anonymised survey responses measured on 5-point Likert scales, covering composite indicators for support for forest restoration, perceived forest benefits, and perceived impacts of restoration activities. It also contains socio-demographic information such as age, education level, and years of residence.
Sampling adhered to the EU General Data Protection Regulation (GDPR) and the Swiss Federal Act on Data Protection. Principal Components Analysis (PCA) was used to construct composite indicators, and Generalised Linear Modelling (GLM) was applied to assess how socio-demographic and perceptual factors influence support for restoration.
The dataset provides insights into behavioural, perceptual, and demographic factors that shape public support for forest restoration, contributing to policy discussions, such as the EU Nature Restoration Regulation (2023). A full codebook is included to facilitate reuse.

en: household-surveys socio-demographic-factors sweden spain public-perceptions forest-restoration

envi

en: Environment

en:
Resource Title: Forest_Restoration_Survey_Data_Sweden_Spain_2024.xlsx
    Size: 48735 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/bd1818e7-deef-4ecb-95bf-6d7fb26239e4/resource/a5233576-1b32-495d-a2da-0b7743100d92/download/dataset_sweden_spain.xlsx
    Description: This file contains anonymised survey responses from 241 individuals in Västerbotten County (Sweden) and Castilla y León (Spain), collected between March and September 2024. It includes variables on forest visitation, restoration awareness, perceptions of forest benefits and impacts, and socio-demographic characteristics. The responses are coded numerically and correspond to categories defined in the metadata file. The dataset supports analysis of public support for forest restoration as presented in the associated article.

en:
Resource Title: Forest_Restoration_Survey_Metadata_Sweden_Spain_2024.xlsx
    Size: 15572 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/bd1818e7-deef-4ecb-95bf-6d7fb26239e4/resource/90046645-5c1e-482b-9da2-931fc5da1866/download/metadata_sweden_spain.xlsx
    Description: This metadata file provides detailed documentation for the survey dataset titled "Survey data on public support for forest restoration in Europe based on evidence from Sweden and Spain." It includes:

Variable Map (Variable names and descriptions): Each survey item is listed alongside a clear explanation of its content and purpose.
Labels Map: For categorical variables, response options are defined numerically and labelled (e.g., Likert scale options, age groups, gender).
Derived variables: Several composite indicators have been created from survey responses, including support for restoration, perceived forest benefits, and perceived restoration impacts.
The metadata enables accurate interpretation, reuse, and analysis of the dataset and is formatted in two Excel sheets:

Variable Map – detailing survey question codes and content.
Labels Map – providing categorical response scales for select questions.

forest-restoration

display_name: forest-restoration

household-surveys

display_name: household-surveys

public-perceptions

display_name: public-perceptions

socio-demographic-factors

display_name: socio-demographic-factors

spain

display_name: spain

sweden

display_name: sweden


$oid: OBSOLETE

en: Meteorological data used to run SNOWPACK for 58 catchments in the Swiss Alps. The data consists of a 2 km grid of "virtual meteorological stations" for each catchment. It was used to simulate snow cover processes during rain-on-snow events, therefore meteorological data of each catchment contains at least one rain-on-snow event. Further information can be found in the attached readme.txt and in Würzer & Jonas et al. (2017), currently under review in Hydrological Processes.

en: Meteorological data for investigation of rain-on-snow events in 58 catchments in Switzerland

en: catchment-data snow-hydrology rain-on-snow snowpack meteorological-data

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

fr: Environnement

it: Ambiente

en:
Resource Title:
    Size: 1534677078 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.305/ros_data/ros_data.zip
    Description: The file contains all data needed to run simulations with the snow cover model SNOWPACK.

format: ZIP

media_type: application/zip

en:
Resource Title:
    Size: 768 bytes
    Format: text/plain
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.305/ros_data/readme.txt
    Description: Readme.txt

format: TXT

media_type: text/plain

catchment-data

display_name: catchment-data

meteorological-data

display_name: meteorological-data

rain-on-snow

display_name: rain-on-snow

snow-hydrology

display_name: snow-hydrology

snowpack

display_name: snowpack


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

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

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

format: PDF

media_type: application/pdf

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

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

air-temperature

display_name: air-temperature

glaciers

display_name: glaciers

last-glacial-maximum

display_name: last-glacial-maximum

orography

display_name: orography

paleo-climate

display_name: paleo-climate

precipitation

display_name: precipitation


en:
Outlines of 18'737 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 24 January 2018. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping.pdf)
The generation of the data is described in:
Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.
Abstract.
Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12’500 km2).
We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18’737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.
This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data is of great value to validate avalanche bulletins, complete existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.
Koordinate System: CH1903+ LV95 LN02

en: SPOT6 Avalanche outlines 24 January 2018

en: natural-hazard snow hazard-mapping satellite avalanche

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


en:
**for English see below**
*******************************************************************************
-br/- -/br-
 Datenbeschrieb
-br/- -/br-
Dieser Datensatz enthält die **Umrisse der 11'120 Lawinen** die aus schwarzweiss Luftbildern, welche zwischen dem 25.2.1999 und dem 1.3.1999 aufgenommen wurden, kartiert wurden. Die Lawinenumrisse haben verschiedene Attribute welche im **beigelegten Beispielschlüssel** beschrieben sind (Beispielschluessel_1999_d.pdf).
Es gibt drei Shapefiles:
* **avalanches1999_endversion1.shp**: die kartierten Lawinen (für Attribute siehe Beispielschlüssel!)
* **area_images_1999.shp**: Fläche die durch die Luftbilder abgedeckt wurde
* **clouds_1999.shp**: grobe Umrisse der Wolken in den Bildern
 Bildverfügbarkeit:
Die entzerrten Luftbilder können von der [Swisstopo](https://s.geo.admin.ch/rpq3hufnb588) einzeln über den Downloadlink heruntergeladen werden (herzlichen Dank an Holger Heisig für die Prozessierung und ans BAFU für die Finanzierung der Prozessierung!!). Über "Erweiterte Werkzeuge"/ "Datei importieren" können die Bilder nach hereinziehen des Orthofotolinks direkt im map.geo.admin.ch angezeigt werden.
 Weiterführende Litertaur:
Details zu den Luftbildern und zur Kartierung, sowie eine kleine Analyse und Empfehlungen zur Verwendung der Daten finden sich unter
- Hafner, E., Margreth, S., and Bühler, Y.: Die grossflächigen Lawinenkartierungen 1999, 2018 und 2019: ein Überblick für die Praxis, FAN Agenda, 1/2025, 15 - 21, 2025.
- Dal, F. J., Hafner, E. D., Peters, T., Narnhofer, D., Caye Daudt, R., Heisig, H., & Bühler, Y. (2024). Automated snow avalanche mapping with deep learning in aerial imagery from the extreme avalanche winter of 1999. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1264-1271). Norwegian Geotechnical Institute.
- Hafner, E. D., Techel, F., Heisig, H., Dal, J. F., & Bühler, Y. (2024). Remotely sensed avalanche activity during three extreme avalanche periods in Switzerland. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1222-1229). Norwegian Geotechnical Institute.
*******************************************************************************
-br/- -/br-
 Data description
-br/- -/br-
This dataset contains the **outlines of 11'120 avalanches** mapped from panchromatic aerial imagery taken between February 25, 1999 and March 1, 1999. The avalanche outlines have various attributes which are described in the **attached example key** (ExampleKey_AvalMapping_1999_e.pdf).
There are three shapefiles:
* **avalanches1999_endversion1.shp**: the mapped avalanches (for attributes see example key!)
**area_images_1999.shp**: Area covered by the aerial images
**clouds_1999.shp**: rough outlines of the clouds in the images
 Image availability:
The rectified aerial images can be downloaded individually from [Swisstopo](https://s.geo.admin.ch/bg6beetinfdc) via the download link (many thanks to Holger Heisig for processing and to BAFU for financing the processing!!). The images can be displayed directly in map.geo.admin.ch via “Advanced tools”/“Import file” after dragging in the orthophoto link.
 Further Reading:
Details on the aerial images and mapping, as well as a brief analysis and tips on using the data can be found at
- Hafner, E., Margreth, S., and Bühler, Y.: Die grossflächigen Lawinenkartierungen 1999, 2018 und 2019: ein Überblick für die Praxis, FAN Agenda, 1/2025, 15 - 21, 2025.
- Dal, F. J., Hafner, E. D., Peters, T., Narnhofer, D., Caye Daudt, R., Heisig, H., & Bühler, Y. (2024). Automated snow avalanche mapping with deep learning in aerial imagery from the extreme avalanche winter of 1999. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1264-1271). Norwegian Geotechnical Institute.
- Hafner, E. D., Techel, F., Heisig, H., Dal, J. F., & Bühler, Y. (2024). Remotely sensed avalanche activity during three extreme avalanche periods in Switzerland. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1222-1229). Norwegian Geotechnical Institute.

en: Avalanche outlines February and March 1999 from aerial imagery

en: avalanche-mapping avalanche-activity avalanche remote-sensing aerial-imagery

envi

en: Environment

aerial-imagery

display_name: aerial-imagery

avalanche-activity

display_name: avalanche-activity

avalanche-mapping

display_name: avalanche-mapping

remote-sensing

display_name: remote-sensing


en:
This dataset contains measurements from two debris flows recorded in 2024 at the Illgraben debris-flow observatory in Switzerland. The first debris flow was recorded on 15 June 2024 and the second debris flow was recorden on 21 June 2024.
This dataset contains the following reseach data for both:
a) Cummulative rainfall measured at CD1 in the catchment.
b) Radar-based flow height of debris flows measured at CD28.
Abstract
In recent years, the destructive impact of debris flows in alpine regions has become increasingly evident. Surge waves within debris flows increase peak discharge and magnify the hazard potential. Hence, understanding the dynamic complexity of debris flows is crucial to mitigate their risk. In order to capture the dynamic processes involved in the formation and interaction of surge waves, it is necessary to obtain distributed observations in the spatiotemporal domain. In this study, we present near-torrent distributed seismic measurements to monitor the Illgraben channel located in the Swiss Alps. With 33 nodal sensors, we detected and tracked surge waves along a 2-kilometer torrent section across the Illgraben fan, which allowed us to gain valuable new insights into the spatial scales relevant for surge wave formation and their long-distance propagation characteristics. We observed erosion-deposition waves that emerged out of the muddy flow tail and propagated with constant velocity along the torrent, reaching meter-scale flow heights within only 100s of meters of flow distance which significantly impact the hazard potential of debris flows. Our results provide valuable observations of surge waves from their formation to their annihilation. We can differentiate flow regimes based on their seismic signature and track them along the torrent, thus mapping the debris-flow evolution in time and space. The observations elucidate large-scale debris flow dynamics thus improving our understanding of hazard potential and the effectiveness of structural countermeasures.

en: Debris flow observation at Illgraben 2024: Event Data 15 June / 21 June

en: radar debris-flow rainfall illgraben surge-waves

en:
Resource Title: Radar_Illgraben_CD28_2025-06-21
    Size: 86229 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/052465cb-5c81-4ba5-88be-115a96c27dd1/resource/be56122c-15cb-40e0-8df3-ae54a02861f0/download/radar_illgraben_cd28_2025-06-21.csv
    Description: Radar-based flow height measurement of debris flow at CD28 at Illgraben. Flow height is derived relative to pre-event channel-bed elevation. Sensor location: 46.309677N, 7.633304E

format: CSV

media_type: text/csv

en:
Resource Title: Rainfall_Illgraben_CD1_2025-06-15
    Size: 34923 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/052465cb-5c81-4ba5-88be-115a96c27dd1/resource/26a8197f-a18d-48b7-84fd-ad7453b09781/download/rainfall_illgraben_cd1_2025-06-15.csv
    Description: Cumulative rainfall measured at CD1 in the Illgraben catchment. Sensor location:  46.283287N / 7.619689E

en:
Resource Title: Rainfall_Illgraben_CD1_2025-06-21
    Size: 34812 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/052465cb-5c81-4ba5-88be-115a96c27dd1/resource/f8e3ff62-bdf1-4043-9956-7937c47f2191/download/rainfall_illgraben_cd1_2025-06-21.csv
    Description: Cumulative rainfall measured at CD1 in the Illgraben catchment. Sensor location:  46.283287N / 7.619689E

en:
Resource Title: Radar_Illgraben_CD28_2025-06-15
    Size: 73728 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/052465cb-5c81-4ba5-88be-115a96c27dd1/resource/fb160833-ebd4-4374-96ff-378473c4cebc/download/radar_illgraben_cd28_2025-06-15.csv
    Description: Radar-based flow height measurement of debris flow at CD28 at Illgraben. Flow height is derived relative to pre-event channel-bed elevation. Sensor location: 46.309677N, 7.633304E

debris-flow

display_name: debris-flow

illgraben

display_name: illgraben

radar

display_name: radar

rainfall

display_name: rainfall

surge-waves

display_name: surge-waves


en:
This dataset comprises of a post-processed set of terrestrial laser scans (TLS’s) of Antarctic sea ice obtained during the Sea Ice Physics and Ecosystem Experiment-2 (SIPEX-2, http://seaice.acecrc.org.au/sipex2012/) in September-November 2012. The post-processing steps include the registration of the individual scans into a single 3-dimensional point cloud, the removal of unwanted noise caused by particles in the air (i.e., snow crystals), and the final generation of surface grids based on the cleaned individual point returns. The final product includes the ‘xyz’ coordinates of the individual point measurements, and gridded surfaces covering study areas of 100m x 100 m, and at resolutions of 0.01 m, 0.1 m, 0.25 m, 0.5 m and 1 m for each of the survey dates. Additionally, subgrid statistics that include the mean elevation, standard deviation, minimum and maximum elevations, range, and number of point returns in each gridcell are generated. The final product is provided in space-delimited text files, with the surface grids provided in Digital Terrain Model (DTM) format ready for visualization in any GIS software.
How to cite:
Please also cite the original publication when using this data set.: Trujillo, E., K. Leonard, T. Maksym, and M. Lehning (2016), Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice, J. Geophys. Res. Earth Surf., 121, doi:[10.1002/2016JF003893](https://dx.doi.org/10.1002/2016JF003893).

en: High resolution sea ice surface topography from the SIPEX-2 expedition, East Antarctica, 2012

en: terrestrial-laser-scans tls sea-ice sea-ice-elevation polar

envidat

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

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Post Processed TLS's
    Size: 932144467 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c88b82ed-d54e-43e6-b4e4-7ae1ee06a014/resource/2557ecb5-e65d-4d60-97ce-fd6696ee2d00/download/10-16904-9sipex2dat.zip
    Description: Compressed dat files

en:
Resource Title: Data processing documentation
    Size: 848896 bytes
    Format: application/msword
    URL: https://www.envidat.ch/dataset/c88b82ed-d54e-43e6-b4e4-7ae1ee06a014/resource/bb51210c-6738-41d4-b4a4-31dd08f4725e/download/tlssipex-2metadata.doc
    Description:

format: msword

polar

display_name: polar

sea-ice

display_name: sea-ice

sea-ice-elevation

display_name: sea-ice-elevation

terrestrial-laser-scans

display_name: terrestrial-laser-scans

tls

display_name: tls


en:
This dataset contains stable isotope ratios of oxygen and hydrogen (O-18 and H-2) and electrical conductivity (EC) in overland flow (OF), topsoil interflow (TIF), soil water, groundwater, and rainwater for 12 rainfall events during the snow-free seasons of 2021 and 2022 in the Studibach catchment, Alptal, Switzerland.
Overland flow, topsoil interflow (i.e., lateral flow from the more densely rooted soil layer), soil water, and groundwater were collected at 14 small trenched runoff plots (1 x 3 m) in three subcatchments (C2, C3, C5) of the Studibach catchment. Overland flow was collected from the surface up to 2-5 cm depth and thus includes biomat flow. A trench was used to collect topsoil interflow (up to 60 cm below the surface; see Table 1 in the manuscript for details). Rainwater was collected at two locations in the Studibach catchment (in C3 and C5, respectively). Soil water was collected in between the events from suction lysimeters installed at 12.5 cm and 20 cm below the soil surface in the middle of each plot. Groundwater was collected between events from wells installed near the plots up to the soil-bedrock interface.
The water samples were analysed for the stable isotopes of oxygen and hydrogen (O-18 and H-2) using with a cavity ring-down spectroscope (CRDS; L2140-i or L2130-i, Picarro, Inc., USA) at the Chair of Hydrology at the University of Freiburg, Germany. The isotope ratios are reported in per mil (‰) relative to Vienna Standard Mean Ocean Water.
A more detailed description of the field setup, data collection and preparation can be found in Leuteritz et al. (in press).
The dataset contains in addition to the sample identifier and the site and event identifiers that are used in the publication, also the sample collection date (typically one day after the event) and the coordinates for each plot (coordinate system: WGS84). For the plots for which samples were collected with an automatic sampler (ISCO), the date and time (UTC) of sample collection are given as well.

en: Stable water isotopes and EC in overland flow, topsoil interflow, soil water, groundwater, and rainwater for 12 rainfall events in the Studibach catchment, Alptal, Switzerland

en: plot topsoil-interflow stable-isotopes studibach alptal electrical-conductivity rainfall soil-water overland-flow groundwater

alptal

display_name: alptal

electrical-conductivity

display_name: electrical-conductivity

groundwater

display_name: groundwater

overland-flow

display_name: overland-flow

plot

display_name: plot

soil-water

display_name: soil-water

stable-isotopes

display_name: stable-isotopes

studibach

display_name: studibach

topsoil-interflow

display_name: topsoil-interflow


en:
The attached data are some large GIS raster files (GeoTIFFs) made with Natural Earth data. Natural Earth is a free vector and raster map data @ naturalearthdata.com. The data used for creating these large files was the "Cross Blended Hypso with Shaded Relief and Water". Data was concatenated to achieve larger and larger files. Internal pyramids were created, in order that the files can be opened easily in a GIS software such as QGIS or by a (future) GIS data visualisation module integrated in EnviDat.
Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com

en: Large GIS raster data derived from Natural Earth Data (Cross Blended Hypso with Shaded Relief and Water)

envi

en: Environment

en:
Resource Title: Bulk Data Access
    Size: 111669149696 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.68%2F
    Description: Link to the S3 bucket where all the data resources can be downloaded in bulk

en:
Resource Title: map preview 0.5MB
    Size: 482223 bytes
    Format: image/jpeg
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.68/gisdata/tiny_map_preview.jpg
    Description:

format: jpeg

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis


en:
The following repository contains the data and code to reproduce the figures analyses of the paper "Examining honeybee (Apis mellifera) dominance patterns within urban bee communities worldwide". It contains three datasets and one .R file
---
The data results from a literature review on abundance distribution of urban bee communities worldwide, aiming at obtaining studies reporting total abundances of honeybees and wildbees in a given city, and species abundances of wildbees and honeybees in a given city.
---
1. **Data**:
- *20240308_cities_coords.csv*: the data contains the latitude and longitude of the included cities in the study. It is used for making the world map with the cities.
- *20241201_proportion_HB_WB.csv*: the data contains the total wild bee and honeybee abundances per city/urban aggregation, and the proportions.
- *20241201_rad_bees.csv*: the data contains the species abundances per city/urban aggregation
2. **Script**:
- *HoneybeeDominance_Analyses_Figures.R*: the script to run the analyses and make the plots. Analyses were done in R version 4.2.1, using the packages ggplot2, glmmTMB, multcomp, wesanderson, terra.

en: Data supporting ‘Examining honeybee (Apis mellifera) dominance patterns within urban bee communities worldwide’

en: sads anthophila urban-ecosystems wildbees dominance urban-beekeeping cities honeybees

en:
Resource Title: Dataset proportion honeybees and wild bees
    Size: 14245 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/90c4bffd-bfc1-4100-99f5-a2ad3e9503a8/download/20241201_proportion_hb_wb.csv
    Description: The dataset provide the main features for each included dataset from published and unpublished research works.  Each row represents a dataset, which provides bee community data in one city / urban aggregation. Overall, it contains 68 datasets from 46 cities in 15 countries and five continents. The data is organised in the following columns:
- Article_ID: id used in the study
- DOI: doi of the publication, when available
- Authors
- Year: of publication
- Duration sampling (years)
- Start_sampling: month of the year
- End_sampling: month of the year
- Continent
- Country
- N. cities: number of cities included in the publication
- City
- Sampling type: active, passive or both
- Sampling methodology: within each sampling type.
- Habitats: list of sampling habitats
- N_habitats: number of sampling habitats
- Parks_similar: binnary (1 = yes; 0 = no)
- Agriculture: binnary (1 = yes; 0 = no)
- Private_gardens: binnary (1 = yes; 0 = no)
- Green_roofs: binnary (1 = yes; 0 = no)
- seminatural_natural_wasteland: binnary (1 = yes; 0 = no)
- other_unspecified: binnary (1 = yes; 0 = no)
- Number sites
- Abundance honeybees
- Abundance wild bees
- Total bees
- Proportion honeybees
- Proportion wildbees
- Area:. of the studied city/urban aggregation

en:
Resource Title: Dataset species abundance
    Size: 598032 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/a4e637d3-911b-4806-b0ba-cbbd17a34309/download/20241201_rad_bees.csv
    Description: This data resource provides the individual species abundance per city / urban aggregation. It contains data from 41 datasets from 37 studies collected in 33 cities / urban aggregations. It contains the following columns:
 - Article_ID
- DOI
- Authors
- Year
- Continent
- Country
- City
- Bee genus
- Bee species
- Bee merged
- Bee full
- Abundance
- Bee_ID_per_study: ID for the study

en:
Resource Title: Dataset coordinates study cities
    Size: 2196 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/9a73209e-98c0-4fee-a208-c726bf957efa/download/20240308_cities_coords.csv
    Description: The data contains the latitude and longitude of the studied cities / urban aggregations. It contains the following columns:
- Continent
-Country
- City
- Lat: Latitude
- Lon: Longitude

en:
Resource Title: R script for analyses and plots
    Size: 17744 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/2f39336d-f343-4325-8207-38372826ecf4/download/honeybeedominance_analyses_figures.r
    Description:

format: OCTET

anthophila

display_name: anthophila

cities

display_name: cities

dominance

display_name: dominance

honeybees

display_name: honeybees

sads

display_name: sads

urban-beekeeping

display_name: urban-beekeeping

urban-ecosystems

display_name: urban-ecosystems

wildbees

display_name: wildbees


en:
This dataset contains the data used  and collected to investigate the reliability of avalanche size estimates and avalanche outlines (see related publications). Namely this is
 Avalanche size estimates
* the 10 pictures depicting avalanches
* the survey results from the 170 participants
 Avalanche outlines mapped from oblique photographs
* the pictures of the six avalanches
* the avalanche outlines mapped by the 10 participants
* the reference mapped from the georeferenced photographs
 Avalanche outlines from remotely-sensed imagery
* the orthophotos in the four different resolutions (2m, 1m, 50cm, 25cm)
* the area of interest (AoI) delimiting the research area
* the avalanche mappings in each resolution for all five participants
* the shade masks used to separate illuminated and shaded areas
The acquisition of the orthophotos has been partially supported by the Swiss National Science Foundation (SNF; Grant N°200021_172800).

en: Data reliability study: avalanche size estimates and outlines

en: avalanche remote-sensing avalanche-size-estimation avalanche-mapping reliability

envidat

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

en: EnviDat: the Environmental Data Portal

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

avalanche-size-estimation

display_name: avalanche-size-estimation

reliability

display_name: reliability

remote-sensing

display_name: remote-sensing


en:
Outlines of 6'041 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 16 January 2019. The dataset was acquired following a period with very high avalanche danger. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping16012019.pdf)
The generation of the data is described in:
Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.
The data was comprehensivly validated in a subset area in
Hafner, E.D.; Techel, F.; Leinss, S.; Bühler, Y., 2021: Mapping avalanches with satellites - evaluation of performance and completeness. Cryosphere, 15, 2: 983-1004. doi: 10.5194/tc-15-983-2021

en: SPOT6 Avalanche outlines 16 January 2019

en: hazard-mapping satellite snow avalanche natural-hazard

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


en:
Validation points, validation area, ground truth coverage, SPOT 6 avalanche outlines, Sentinel-1 avalanche outlines, Sentinel-2 avalanche outlines, Davos avalanche mapping (DAvalMap) avalanche outlines as shapefiles and a detailed attribute description (DataDescription_EvalSatMappingMethods.pdf).
Coordinate system: CH1903+_LV95
The generation of this dataset is described in detail in:
Hafner, E. D., Techel, F., Leinss, S., and Bühler, Y.: Mapping avalanches with satellites – evaluation of performance and completeness, The Cryosphere, https://doi.org/10.5194/tc-2020-272, 2021.

en: Satellite avalanche mapping validation data

en: validation snow satellite avalanche avalanche-hazard-mapping

envi

en: Environment

avalanche-hazard-mapping

display_name: avalanche-hazard-mapping

validation

display_name: validation


en: This dataset contains detailed records of pollinator communities and plant reproductive outcomes from an urban garden experiment in Zurich, Switzerland. It includes flower visitation frequency and pollinator species richness for four insect-pollinated plant species observed across 24 home gardens. The dataset spans 167 pollinator taxa, with over 5,700 individuals identified, mostly to species or genus level. It features individual-level trait measurements for pollinators, such as body size and tongue lengths. Measures of pollination success, including seed and fruit set, are provided for each plant species.

en: Comprehensive dataset of pollinator diversity and visitation rates with individual-based traits and pollination success across four urban garden plant species

en: garden-experiment pollinator-experiment green-spaces urban-biodiversity daucus-carota bettergardens better-gardens gardens urban-ecology urbanisation plant-insect-interaction symphytum-officinale raphanus-sativus plant-pollinator-interactions pollination onobrychis-viciifolia zurich

better-gardens

display_name: better-gardens

bettergardens

display_name: bettergardens

daucus-carota

display_name: daucus-carota

garden-experiment

display_name: garden-experiment

gardens

display_name: gardens

green-spaces

display_name: green-spaces

onobrychis-viciifolia

display_name: onobrychis-viciifolia

plant-insect-interaction

display_name: plant-insect-interaction

plant-pollinator-interactions

display_name: plant-pollinator-interactions

pollination

display_name: pollination

pollinator-experiment

display_name: pollinator-experiment

raphanus-sativus

display_name: raphanus-sativus

symphytum-officinale

display_name: symphytum-officinale

urban-biodiversity

display_name: urban-biodiversity

urban-ecology

display_name: urban-ecology

urbanisation

display_name: urbanisation

zurich

display_name: zurich


en:
This data set contains roughly 5600 photographs of plants and plant parts from 153 sites recorded in all major biogeographic regions of Switzerland using smartphone cameras. Image names contain a letter referring to depicted plant parts: b = bark, i = inflorescence, f = infructescense, s = several parts, v = vegetative parts.
Photos are grouped in folders by observation (individual or population), i.e., photos in the same folder are of the same species, observed at the same time and sampling plot. At a higher organisational level, these folders are grouped by sampling plot (usually 3×3 m in open areas and 10×10 m in forests). The main folder contains metadata including taxon name, sampling time and location, as well as the TypoCH habitat type encoded as integers.
This data set accompanies the following publication:
Popp, M. R., Zimmermann, N. E. & Brun, P. Evaluating the use of automated plant identification tools in biodiversity monitoring—a case study in Switzerland. _Ecological Informatics_ **103316** (2025) doi:[10.1016/j.ecoinf.2025.103316](https://doi.org/10.1016/j.ecoinf.2025.103316).

en: Photos of vegetative and reproductive parts of 560 vascular plant species taken in all biogeographic regions of Switzerland

en: species-observations plant-species testing vascular-plants photo

photo

display_name: photo

plant-species

display_name: plant-species

species-observations

display_name: species-observations

testing

display_name: testing

vascular-plants

display_name: vascular-plants


en: Earth’s snow cover is very dynamic on diurnal time scales. The changes to the snow structure during this metamorphism have wide ranging impacts such as on avalanche formation and on the capacity of surface snow to exchange trace gases with the atmosphere. Here, we investigate the influence of dry metamorphism, which involves fluxes of water vapor, on the chemical reactivity of bromide in the snow. For this, the heterogeneous reactive loss of ozone at a concentration of 5-6E12 molecules cm-3 is investigated in artificial, shock-frozen snow samples doped with 6.2 uM sodium bromide and with varying metamorphism history. The oxidation of bromide in snow is one reaction initiating polar bromine releases and ozone depletions.

en: Data set on bromide oxidation by ozone in snow during metamorphism from laboratory study

en: alpine ozone snow arctic reaction heterogeneous interface metamorphism solution laboratory-study chemistry antarctica brine

en:
Resource Title: Readme file
    Size: 503143 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/d41fa166-35e9-430f-b96d-a5862556d9cd/download/edebeli_acp_2019__snowbrmet.pdf
    Description: This file shows data, code, and plots.

en:
Resource Title: Matlab Data
    Size: 1008529 bytes
    Format: application/x-matlab
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/2cbff0e6-bf62-4476-a533-10cb745520ed/download/edebeli_acp_2020__data.mat
    Description: All data as Matlab mat file

en:
Resource Title: Matlab Script to view and plot data
    Size: 9299 bytes
    Format: application/vnd.wolfram.mathematica.package
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/b718b5db-b15c-4f88-95a9-ce649b79308a/download/edebeli_acp_2019__snowbrmet.m
    Description:

alpine

display_name: alpine

antarctica

display_name: antarctica

arctic

display_name: arctic

brine

display_name: brine

chemistry

display_name: chemistry

heterogeneous

display_name: heterogeneous

interface

display_name: interface

laboratory-study

display_name: laboratory-study

metamorphism

display_name: metamorphism

ozone

display_name: ozone

reaction

display_name: reaction

snow

display_name: snow

solution

display_name: solution


hymenoptera

en:
Hymenopteran data from all historic up to the recent projects (29.10.2019) of WSL, collected with various standardized methods in landscapes of different types.
Data are provided on request to contact person against bilateral agreement.

en: Hymenoptera

en: forests urban arthropoda agricultural hymenoptera hautfluger

envidat

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

en: EnviDat: the Environmental Data Portal

title_for_slug: hymenoptera

agricultural

display_name: agricultural

arthropoda

display_name: arthropoda

forests

display_name: forests

hautfluger

display_name: hautfluger

hymenoptera

display_name: hymenoptera

urban

display_name: urban


high-resolution-climate-data-for-europe

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present downscaled climate data for the CORDEX EUR11 domain at a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperature lapse rates. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height. The resulting data consist of a daily temperature and precipitation timeseries.
The data is distributed under a: Creative Commons: Attribution 4.0 International (CC BY 4.0) license.

en: High resolution climate data for Europe

en: europe precipitation maximum-temperature daily-climate air-temperature eur11 minimum-temperature cordex

title_for_slug: high-resolution-climate-data-for-europe

envi

en: Environment

en:
Resource Title: Data Access
    Size: 2199023255552 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav2&prefix=EUR11%2F
    Description:

en:
Resource Title: CHELSA_EUR11 technical documentation
    Size: 713475 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/9e2c4a69-443d-4eb1-b8ab-697fd50bc7d2/resource/bc1df26a-0b8f-4547-872d-f00ed45db554/download/chelsa_eur11_technical_documentation.pdf
    Description: Technical documentation of the data with variable names and methodology.

air-temperature

display_name: air-temperature

cordex

display_name: cordex

daily-climate

display_name: daily-climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation


en:
Important note: From 2025 the NEAD format is being transformed into the interoperable CSV (iCSV) format, a formalized and standardized evolution of the NEAD format. Furthermore, iCSV should be backwards compatible with NEAD. More information on the new iCSV format will be linked here in due time.
Acknowledgement: The NEAD format includes NetCDF metadata and is proudly inspired by both SMET and NetCDF formats. NEAD is designed as a long-term data preservation and exchange format.
The NEAD specifications were presented at the "WMO Data Conference 2020 - Earth System Data Exchange in the 21st Century" (Virtual Conference).
-----------------------
Summary:
The Non-Binary Environmental Data Archive (NEAD) format is being developed as a generic and intuitive format that combines the self-documenting features of NetCDF with human readable and writeable features of CSV. It is designed for exchange and preservation of time series data in environmental data repositories.
License: The NEAD specifications are released to the public domain under a Creative Commons CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

en: Non-Binary Environmental Archive Data (NEAD) format

en: metadata-convention nead csv research-data-management meteorological-data-format

en:
Resource Title: NEAD on GitHub
    Size: 1024 bytes
    Format: No Info
    URL: https://github.com/GEUS-PROMICE/NEAD
    Description:

en:
Resource Title: NEAD syntax v0.1 (EBNF)
    Size: 3383 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d51285c9-953d-42e5-a925-20209cde10e5/resource/bf21243d-cdb9-47a8-a15b-d42efaef5d82/download/ebnf.txt
    Description:

en:
Resource Title: MeteoIO (future reference implementation)
    Size: 1024 bytes
    Format: text/html
    URL: https://www.slf.ch/en/services-and-products/meteoio.html
    Description:

format: HTML

media_type: text/html

en:
Resource Title: PyNEAD (future reference implementation)
    Size: 1024 bytes
    Format: No Info
    URL: https://github.com/GEUS-PROMICE/pyNEAD
    Description:

csv

display_name: csv

metadata-convention

display_name: metadata-convention

meteorological-data-format

display_name: meteorological-data-format

nead

display_name: nead

research-data-management

display_name: research-data-management


en: This dataset contains four years of daily measurements of the natural isotopic composition (2H, 18O) of precipitation and stream water at the Alp catchment (area 47 km2) in Central Switzerland and two of its tributaries (0.73 km2 and 1.55 km2). In addition, the dataset contains daily measurements of key hydrometeorological variables.

en: Four years of daily stable water isotope data in stream water and precipitation from three Swiss catchments

en: alptal hydrology catchment stable-water-isotope stream-water precipitation

en:
Resource Title: Data Set Documentation: alptal_Isotopes_daily_2015-2019_v2
    Size: 158372 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6a2fefc6-ce6d-4eb7-9ea9-c37b64959437/resource/d26ca42e-4cdb-4ef8-bf35-a87d5239757d/download/data-set-documentation_sdata-21-00930.pdf
    Description: Documentations contains meta data of the data columns and information about the study catchments.

en:
Resource Title: Alptal_Isotopes_daily_2015-2019_v2.txt
    Size: 760332 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/6a2fefc6-ce6d-4eb7-9ea9-c37b64959437/resource/7865517d-357b-4e08-8b6a-b405eca4e547/download/alptal_isotopes_daily_2015-2019_v2.txt
    Description: Version 2 of the dataset contains additional information on:
- line-conditioned (lc) excess
- precipitation sample volumes
- isotope data quality

en:
Resource Title: Alptal_Isotopes_daily_2015-2019
    Size: 717293 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/6a2fefc6-ce6d-4eb7-9ea9-c37b64959437/resource/8a06beab-3092-45d3-ad41-a59d79e6cb71/download/alptal_isotopes_daily_2015-2019.txt
    Description: Single comma-separated txt-file with daily data of stable water isotopes measured in streamwater and precipitation in the Swiss Alptal catchment and two of its tributaries (Erlenbach and Vogelbach), as well as daily data of key hydrometeorological variables from the Alptal valley

alptal

display_name: alptal

catchment

display_name: catchment

hydrology

display_name: hydrology

stable-water-isotope

display_name: stable-water-isotope

stream-water

display_name: stream-water


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

en: Reproducibility dataset for CRYOWRF validation

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

envidat

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

en: EnviDat: the Environmental Data Portal

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

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

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

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

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

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

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

cryowrf

display_name: cryowrf

reproducibility

display_name: reproducibility

surface-mass-balance

display_name: surface-mass-balance


mosaic-snow-on-sea-ice-data

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

en: MOSAIC Snow on Sea Ice Data

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

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

envi

en: Environment

en:
Resource Title: SNOWPACK setup for MOSAiC
    Size: 2386070 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.381/snowpack_jgr.zip
    Description:  The zip file contains both input and output data as well as the model configuration as used in the submitted manuscript "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

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

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

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

en:
Resource Title: ALPINE3D setup for MOSAiC
    Size: 9663676416 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.381/a3d_jgr.zip
    Description: The zip file contains a folder structure that must be kept as it is in order to run the simulation in the current configuration.
The setup contains both input and output data as well as the model configuration as used in the submitted manuscript
"Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

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

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

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

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

arctic-sea-ice

display_name: arctic-sea-ice

drifting-and-blowing-snow

display_name: drifting-and-blowing-snow

snow-distribution

display_name: snow-distribution

spatial-variability

display_name: spatial-variability


en:
Silvopastoral systems are highly productive and combine long-term wood production with annual provision of forage for livestock. In the Swiss Jura Mountains these systems are a key component of the landscape. As in other cold biomes, climate change can potentially accelerate landscape change within these historically sustainable systems.
In order to anticipate the evolution of subalpine wooded pasture ecosystems under future climate and land-use changes, this project focused on the interplay between soil, vegetation and climate. It was aimed at providing experimental evidence for chief ecosystem processes, with emphasis on the quality of the ecosystem services provided. The main interest was placed on vegetation turf resistance to climate change along an unwooded – sparsely wooded - densely wooded pasture gradient (land-use intensity), where plant productivity, diversity and succession along with rates of carbon cycling and microbial activity provided measures of ecosystem functioning at both plot and landscape level.
Experimental transplantation of monolith soil turfs to lower altitudes allowed to simulate soil warming and reduced annual precipitation. In order to simulate a year-round warmer and drier climate the natural climate variation along an altitudinal gradient was used as a proxy. The aim was to simulate realistic climate change scenarios for the second half of the 21st century predicted by the IPCC report and downscaled for Switzerland providing regionalized interpolated projections integrating therein trends for temperature increase and precipitation decrease. By using permanent meteorological stations within the network of the Federal Office of Meteorology and Climatology (MeteoSwiss), we obtained high resolution regional data on the variation of mean annual temperature (MAT) and mean annual precipitation (MAP) in relation to altitude in the Swiss Jura Mountains. We observed a general increase of +0.5 K in MAT and a decrease of -20 % MAP for each 100 m decrease in altitude along the SE slope of the Swiss Jura Mountains. These relationships served for the selection of the transplantation sites such that in comparison to a control site at 1350 m a.s.l. (Combe des Amburnex, N 46°54’, E 6°23’) a +2 K MAT and -20 % MAP was achieved at 1010 m a.s.l. (Saint-George, N 46°52’, E 6°26’), a +4 K MAT and -40 % MAP at 570 m a.s.l., (Arboretum d’Aubonne, N 46°51’, E 6°37’), and a +5 K MAT and -50 % MAP at 395 m a.s.l. (Les Bois Chamblard, N 46°47’, E 6°41’). The two stations at 1010 m a.s.l. and 570 m a.s.l. corresponded to the IPCC scenario A1B for a moderate increase in greenhouse gas emissions and to scenario A2 for a high increase in greenhouse gas emissions, respectively. The station at 395 m a.s.l. was chosen to represent an extreme scenario with climate variables lying at the positive tail distribution of model predictions under the A2 scenario.
Soil cores were assembled into rectangular PVC boxes of 60  80 cm2 size and of 35 cm height. All mesocosms were dug down to surface level into previously prepared trenches in the ground thus preventing lateral heat exchange with the atmosphere. Since at each site the mesocosms were placed in a common garden with no light interception, mesocosms with turfs from the two wooded pastures were shaded from direct sun light to simulate the natural light conditions in the corresponding habitats. Each mesocosm was equipped with a drainage system and was connected to a water tank thus representing a zero potential lysimeter collecting soil solution and precipitation/snowmelt runoff. ECH2O EC-TM sensor probes coupled to Em50 data-loggers (Decagon Devices, Inc., USA) recorded soil temperature and volumetric water content in each mesocosm at the top-soil (0 to -3 cm) every minute and data were averaged over one hour intervals. Climate parameters at each transplantation site were monitored continuously throughout the experiment by means of automated weather stations (Sensor Scope Sàrl, Switzerland), measuring rain precipitation (non-heated tipping bucket gauges) and air temperature and humidity 2 m above the ground surface at one minute intervals.
A list of above- and belowground variables were measured to assess the resilience of biogeochemical processes, plant productivity, tree regeneration, and carbon sequestration for each respective land-use practice. Furthermore, the experimental data were used to improve on (parameterization) the existing spatially explicit, dynamic model WoodPaM and refine the modelʼs climatic and land-use variables so that different scenarios of climate change and land use change could be simulated. Natural and management induced disturbance patterns were incorporated into the model.
The data have been made available within the project CCES Mounted. The climate stations Sensorscope are still in use within the project CLIMARBRE (Wald und Klimawandel, WSL/BAFU).
References
1. Puissant, J., Cécillon, L., Mills, R.T.E., Robroek, B.J.M. Gavazov, K., De Danieli, S., Spiegelberger, T., Buttler, A., Brun, J.J. 2015. Seasonal influence of climate manipulation on microbial community structure and function in mountain soils. Soil Biology and Biochemistry 80: 296–305.
2. Mills, R., K. Gavazov, T. Spiegelberger, D. Johnson and A. Buttler 2014. Diminished soil functions occur under simulated climate change in a sup-alpine pasture, but heterotrophic temperature sensitivity indicates microbial resilience. Science of the Total Environment, vol. 473–474(0): 465-472.
3. Gavazov, K., Spiegelberger, T. and Buttler, A. 2014. Transplantation of subalpine wood-pasture turfs along a natural climatic gradient reveals lower resistance of unwooded pastures to climate change compared to wooded ones. Oecologia (174) : 1425-1435.
4. Peringer A., Siehoff S., Chételat J., Spiegelberger T., Buttler A. & Gillet F. 2013. Past and future landscape dynamics in pasture-woodlands of the Swiss Jura Mountains under climate change. Ecology and Society, 18, 3: 11. DOI: 10.5751/ES-05600-180311. [online] URL: http://www.ecologyandsociety.org/vol18/iss3/art11/
5. Gavazov, K. S., A. Peringer, A. Buttler, F. Gillet and T. Spiegelberger. 2013. Dynamics of Forage Production in Pasture-woodlands of the Swiss Jura Mountains under Projected Climate Change Scenarios. Ecology and Society 18 (1): 38. [online] URL: http://www.ecologyandsociety.org/vol18/iss1/art38/

en: Biogeochemical data from a transplantation experiment of monolith soil turfs along an altitudinal gradient to simulate climate change scenarios

en: transplantation-experiment climate-change soil biogeochemisty silvopastoral-systems

biogeochemisty

display_name: biogeochemisty

climate-change

display_name: climate-change

silvopastoral-systems

display_name: silvopastoral-systems

soil

display_name: soil

transplantation-experiment

display_name: transplantation-experiment


en:
The Swiss Landscape Monitoring Program (LABES) records both the physical and the perceived quality of the landscape with about 30 indicators. The surveys of the physical aspects are largely based on evaluations of data available throughout Switzerland from swisstopo and the Federal Statistical Office (FSO). Another significant part of the data comes from a nationwide population survey on landscape perception.
This dataset describes data that have been assembled in the 2020 update of the Swiss Landscape Monitoring Program LABES.

en: LABES 2 Indicators of the Swiss Landscape Monitoring Program

en: landscape landscape-perception landscape-ecology ecosystem-services european-landscape-convention

envidat

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

en:
Resource Title: LABES_36_Zersiedlung
    Size: 318716414 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/4d6c7084-30af-47c7-a5db-8c5fa24fc96a/download/labes_36_zersiedlung.zip
    Description: As a metric for characterising urban sprawl, the measure of urban sprawl (Z or weighted urban permeation WUP) was first propagated by Jaeger et al. (2008). We use this measure here. Urban sprawl is expressed in DSE/m2. The metric was refined within the framework of the National Research Programme 54 "Sustainable settlement and infrastructure development" in the project "Landscape sprawl Switzerland - Quantitative analysis 1935 to 2002 and implications for spatial planning" (Jaeger et al. 2008).

en:
Resource Title: LABES_2a_Nutzungsvielfalt_in_der_LW_Flaeche
    Size: 40224676 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/7d98e337-544b-4a43-bb68-e88b45aa38b6/download/labes_2a_nutzungsvielfalt_in_der_lw_flaeche.zip
    Description: This indicator measures the average number of different uses of agricultural land in Switzerland. It is thus a measure of the diversity of agricultural land. The agricultural structure survey is used to record the diversity of use.

en:
Resource Title: LABES_9_Zerschneidung
    Size: 2873713695 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/49481125-656d-4f80-b637-5e269df54345/download/labes_9_zerschneidung.zip
    Description: Transport infrastructure such as highways, connecting roads and railroads, as well as settlement areas divide a landscape into individual areas separated from each other. To measure the degree of landscape fragmentation, the metric of "effective mesh size" (meff) was used (Jaeger 2000). It expresses the probability that there are no separating elements, such as traffic routes or settlements, between two randomly selected points. The more separating elements cut up the landscape, the lower this probability and the smaller the effective mesh size.

en:
Resource Title: LABES_31a_Gewaesserabschnitte_frei_begehbar
    Size: 650033460 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/5936cb4e-fdb5-42fe-abc8-a2e1b49819db/download/labes_31a_gewaesserabschnitte_frei_begehbar.zip
    Description: Indicator 31a describes the accessibility of water bodies in Switzerland. Water bodies are popular recreational areas. In order to be used by the population, therefore they should be freely accessible.

en:
Resource Title: LABES_17a_Soemmerungsweiden
    Size: 373970 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/58fe447d-badc-4f46-b5ae-4a27e3278ad5/download/labes_17a_soemmerungsweiden.zip
    Description: Summer pastures make up the majority of extensively used agricultural land in Switzerland. Summer pastures are located at altitudes that do not allow intensive use of the land, as is the case in the Central Plateau. Fertiliser use is either non-existent or limited. The indicator helps to measure changes in a basic agricultural use that is very important for the mountain landscape. It is a major determinant of landscape character and biodiversity.

en:
Resource Title: LABES_8_Bauen_ausserhalb_Bauzone_neue_Berechnung
    Size: 552983317 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/6f63c401-4569-416a-835e-bbf92db5c446/download/labes_8_bauen_ausserhalb_bauzone_neue_berechnung.zip
    Description: Indicator 8 quantitatively describes the Euclidean distance from each point of a 12.5x12.5m grid outside the building zone to the nearest building. This is a revision based on a new calculation method.

en:
Resource Title: LABES_3_Flaechenverbrauch_siedlung
    Size: 289613 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/50af6ee4-e060-449a-928b-eaf7d56584d6/download/labes_3_flaechenverbrauch_siedlung.zip
    Description: This indicator quantitatively describes land consumption for settlement and the change in Switzerland's settlement area based on data from Switzerland's land use statistics (Swiss Federal Statistical Office FSO).

en:
Resource Title: LABES_11_Gewaesser
    Size: 87721372 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/3989c431-0da1-4f0f-ae38-0052dd0d5b59/download/labes_11_gewaesser.zip
    Description: Indicator 11a describes the change in the length of watercourses in Switzerland between different points in time. The changes are systematically recorded on the basis of the changes in the national maps 1:25,000, later Vector25 and from about 2012 using TLM3D. With this evaluation protocol (2022), the sampling procedure of "Landschaft unter Druck" is used for the last time. It consists of 152 sampling rectangles in which the changes are recorded and extrapolated to the whole of Switzerland. From TLM3D (2020) onwards, the extrapolation is guaranteed for the entire area of Switzerland.

en:
Resource Title: LABES_NEU_12_Landwirtschaftliche_Intensitaet
    Size: 3136976655 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/2a4fd5bc-9d68-4ba9-8386-2589ff7c280b/download/labes_neu_12_landwirtschaftliche_intensitaet.zip
    Description: This indicator shows the agricultural intensity in Switzerland using satellite data by calculating the NDVI values for each growing season and, in particular, observing the standard deviation of these values over the years. The remote sensing data used to calculate this indicator come from Sentinel-2 MSI and cover the whole of Switzerland. Sentinel-2 is a wide-area, high-resolution, multispectral imaging mission of ESA for monitoring vegetation, soil and water cover. Sentinel-2 Level-1C data were used, which are radiometrically and geometrically corrected top-of-atmosphere products. The corrections include orthorectification and spatial registration on a global reference system (combined UTM projection and WGS84 ellipsoid) with sub-pixel accuracy. Level 1C images are delivered in tiles of 100×100 km. A total of 11 tiles are needed to cover the extent of Switzerland.

en:
Resource Title: LABES_2_Veraenderung_LW_Flaeche
    Size: 1823447 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/1b183a3b-12fb-4449-9f94-6dbdbb27c09c/download/labes_2_veraenderung_lw_flaeche.zip
    Description: Indicator 2 describes the quantitative change in Switzerland's agricultural area excluding summer pastures. It contributes to assessing the basic agricultural use, which is very important for the landscape. This has a significant impact on the character of the landscape and on biodiversity.

en:
Resource Title: LABES_35_ErschliessungFussWanderwege
    Size: 612264376 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/0b03f50f-90db-43ab-9efb-20ab17c7645a/download/labes_35_erschliessungfusswanderwege.zip
    Description: Indicator 35 describes the accessibility with footpaths and hiking trails less than 2m wide. The basis for this is the Topographic Landscape Model (TLM and TLM3D) of the Federal Office of Topography. The data are given in km/km2 and are broken down by land use. The land use categories settlement, forest and open land are extracted from the area statistics of the Federal Statistical Office. Contrary to the initial calculation in 2015, we have abandoned the official attribute "hiking trail", as it has been shown that official "hiking trails" are also routed over longer distances along major roads. The current definition has to do solely with the width of the path (max. width 2m) and not with the official designation. This is closer to the quality of a trail than the official designation "hiking trail".

en:
Resource Title: README_LABES
    Size: 37075 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/57905ae4-1e6f-47e7-b2c9-bea903d73591/download/readme_labes2.pdf
    Description: This is the general readme for all LABES datasets.

en:
Resource Title: Labes_all_social_indicators_23_24_25_27_29_30_NEU16_NEU17_NEU18_NEU20_NEU22_NEU23
    Size: 7262265 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/63db81c2-01b8-4285-b602-5090673d9330/download/labes_all_social_indicators_23_24_25_27_29_30_neu16_neu17_neu18_neu20_neu22_neu23.zip
    Description: The social indicators for LABES were collected with a Swiss-wide representative survey. The first survey was conducted in 2011 (n = 2814 participants), the second in 2020 (n = 2090 participants). The “Auswertungsprotokolle” inform about the results of each indicator in 2020 and compared to the state of 2011.

Indicator list:

Indicator 23 Ortsbindung / place attachment

Indicator 24 Landschaftliche Schönheit / visual landscape quality or beauty

Indicator 25 Besonderheit (Eigenart und Vergangenheitsbezug)/ place identity

Indicator 27 Wahrgenommener Informationsgehalt der Landschaft: Komplexität, Entdeckungspotenzial, Kohärenz, Lesbarkeit / Kaplans’ preference matrix: complexity, mystery, coherence, legibility

Indicator 29 Faszination / soft fascination

Indicator 30 Authentizität /authenticity

Indicator Neu_16 Erholung und Landschaft (Erholungsindex, Zugang, Outdoorsport) / recreation and landscapes (recreationindex, access, outdoor sports)

Indicator Neu_17 Beobachtete Landschaftscharakterisierung / perceived landscape charachterization

Indicator Neu_18 Beobachtete Landschaftsveränderungen / perceived landscape changes

Indicator Neu_20 Wahrgenommene Landschaftsqualität in den Grundnutzungen oder Texturen (Wald, Landwirtschaft, Siedlungsflächen, Gewässer)/ Perceived landscape quality in the different land use areas (forest, agriculture, settlement areas, water bodies)

Indicator Neu_22 Gesamturteil zur wahrgenommenen Landschaftsqualität / overall satisfaction

Indicator Neu_23 Kulturelle Landschafswerte / cultural values and services of the landscape

en:
Resource Title: LABES_NEU_2_Abgeschiedenheit
    Size: 234154689 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/091a8634-f47c-44f0-89f2-122cecf3f12d/download/labes_neu_2_abgeschiedenheit.zip
    Description: Remoteness implies distance from a reference. In the case of an actual journey through a remote landscape, this distance can mean the physical distance from society or from signs of civilisation. In solitude, individuals face the elements of nature and thus move a step away from the backing of security provided by civilised society.
To calculate the remoteness of each grid cell per time period, the "Path Distance" ArcGIS tool is used. This calculates the cost between each grid cell and the settlement areas (pixels with >15 people) as the shortest trajectory. The surface distance is calculated from the horizontal and vertical distance (including the digital elevation model DHM25) and a cost grid, which assigns to each cell the costs incurred when passing through this area. As soon as the trajectory meets (or starts on) a road on which the settlement can be reached, the journey time by public transport or by private means of transport is calculated and the shorter of the two journey times is used.

en:
Resource Title: LABES_15_NaturuberlasseneFlache
    Size: 86402157 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/241e4703-b922-493d-92bb-dba59111c5f6/download/labes_15_naturuberlasseneflache.zip
    Description: Areas left to nature are areas in which natural processes can take place essentially undisturbed and direct human influences determine the (current) development only to a small extent. In such areas, the composition of animal and plant communities differs from that in the cultivated landscape. The areas left to nature in Switzerland can be divided into "wilderness areas" in the forest (forest wilderness), areas left to nature in the high mountains (alpine fallow) and areas along water bodies (floodplains). The areas may or may not be accessible. Of central importance is the intensity of human activities.

en:
Resource Title: LABES_7_Versiegelung
    Size: 83715075 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/c285f76d-d16e-49eb-a894-11d22b91ffe6/download/labes_7_versiegelung.zip
    Description: The degree of imperviousness indicates the sealed surface area as a percentage. The LABES indicator 7 is surveyed with the area statistics Switzerland. The survey interval of the areal statistics is 12 years for the first 3 surveys and 9 years for the fourth survey of the areal statistics; therefore, short-term developments in the change of the sealed surface cannot be recorded.

en:
Resource Title: LABES_NEU_7_Leitungen
    Size: 13553015 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/9abf7e9d-3a4c-4fb1-89e9-9b46f886555e/download/labes_neu_7_leitungen.zip
    Description: This indicator shows the status of transmission lines in Switzerland and analyses the land cover on which these infrastructures are built. Transmission lines are assessed on the basis of TLM data. An extract from TLM_VERSORGUNGSBAUTE (OBJEKTART: Hochspannungsleitungen) is used to calculate the length consumption. In addition, the area statistics layer (NOLC04) is used to differentiate land types into different categories. The total length of transmission lines in Switzerland, in the different biogeographical regions and in the different cantons is calculated by overlay operations for year 2015 and year 2020 (see appendices for further details).

en:
Resource Title: LABES_NEU_14_StaedtischesGruen
    Size: 13710568925 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/17cbc14c-0f93-4757-9bc7-1ea8b3a241e2/download/labes_neu_14_staedtischesgruen.zip
    Description: This indicator shows the state of vegetation within urban areas in Switzerland. On the one hand, the entire vegetation period is considered, taking into account all data from mid-May to mid-September. On the other hand, an additional analysis focuses on the spring period from mid-May to the end of June in order to observe only the growing season, which in the vast majority of cases is not yet affected by drought stress.
The remote sensing data used to calculate this indicator come from Sentinel-2 MSI and cover the whole of Switzerland. Sentinel-2 is a wide-area, high-resolution, multispectral imaging mission of ESA for monitoring vegetation, soil and water cover. Sentinel-2 Level-1C data were used, which are radiometrically and geometrically corrected top-of-atmosphere products. The corrections include orthorectification and spatial registration on a global reference system (combined UTM projection and WGS84 ellipsoid) with sub-pixel accuracy. Level 1C images are delivered in tiles of 100×100 km. A total of 11 tiles are required to cover the extent of Switzerland.

en:
Resource Title: LABES_4_VerkehrFlaecheLaenge
    Size: 586793568 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/b803de8f-9e8f-4e88-87fa-7a5630a7b636/download/labes_4_verkehrflaechelaenge.zip
    Description: Indicator 4 describes the length and area of roads and railroads for the year 2020, as well as the changes between different points in time. The calculation of length and area consumption is based on the Topographic Landscape Model TLM and TLM3D of the Federal Office of Topography. Before 2014, changes were recorded in a sampling procedure based on landscape elements and extrapolated to subspaces and the whole of Switzerland. Since 2015, however, it has been possible to use data directly for the whole of Switzerland.

en:
Resource Title: LABES_NEU_9_Windanlagen
    Size: 31839422 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/8ad25619-6fd6-44eb-8356-128591a07d67/download/labes_neu_9_windanlagen.zip
    Description: This indicator shows the situation of wind energy in Switzerland. Firstly, we locate the current wind turbines and wind farms in Switzerland and compare their location with the wind speed map and the federal government's base map concerning the main wind potential areas. Secondly, we analyse the development of wind energy in Switzerland over the years and the efficiency of such structures.

en:
Resource Title: LABES_1_Wald
    Size: 880214 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/ecac03e4-7b78-4cfd-b8dc-0f901784105f/download/labes_1_wald.zip
    Description: Indicator 1 quantitatively describes the forest area of Switzerland and its change. The required data on forest area are calculated using the area statistics (Swiss Federal Statistical Office, SFSO).

en:
Resource Title: LABES_14_Licht
    Size: 35479307 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/89793b05-e29e-4db1-acf6-44bea2b37965/download/labes_14_licht.zip
    Description: Light emissions in 500m resolution for entire Switzerland for the periode 2014-2020 using VIIRS-VCSML

en:
Resource Title: LABES_32_Anlagefrei
    Size: 245411882 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2b286615-22ad-432c-a63f-b917deac85b1/resource/fd301e2a-b4aa-40da-8268-bfb3f0f7fbd3/download/labes_32_anlagefrei.zip
    Description: For many people, "untouched landscape" is the very essence of nature. There are hardly any places left in Switzerland that have no human influence. But you can find regions where human influence is not so obvious. These are areas where no human buildings and installations can be seen. Areas free of facilities are therefore the most natural areas that can be found in Switzerland.

ecosystem-services

display_name: ecosystem-services

european-landscape-convention

display_name: european-landscape-convention

landscape

display_name: landscape


en:
The dataset Hydro-CH2018 reservoirs provides estimates of current and future water supply, water demand, and storage volumes for 307 medium-sized catchments in Switzerland.
Water supply for current (1981-2010) and future (2070-2099) climate conditions was simulated using the hydrological model PREVAH. For modeling current water supply, observed meteorological time series were used as input, while simulated meteorological time series derived from 39 model chains of the CH2018 initiative were used as an input for simulating future climate conditions.
Water demand was estimated for six categories:
- 1) Drinking water (households and tourism),
- 2) industry (second and third sector),
- 3) artificial snow production,
- 4) agriculture (irrigation and livestock feeding),
- 5) ecology (residual flows), and
- 6) hydropower.
Future estimates consider changes in demand related to population growth and changes in the hydrological conditions.
Storage volumes are provided for natural lakes (storage capacities and usable volumes), artificial reservoirs, reservoirs for artificial snow production, and drinking reservoirs.
A detailed description of the simulation and estimation procedures can be found in
*   Brunner, M.I., Björnsen Gurung, A., Zappa, M., Zekollari, H., Farinotti, D., Stähli, M., 2019. Present and future water scarcity in Switzerland: Potential for alleviation through reservoirs and lakes. Sci. Total Environ. 666, 1033–1047. https://doi.org/10.1016/j.scitotenv.2019.02.169.
This dataset contains the following information:
1.	Shapefile with the 307 medium-sized Swiss catchments.
2.     Textfiles with the water supply simulations for the control run and the 39 climate model chains (one file per chain) at daily resolution for the 307 catchments.
3.	Textfiles with the current and future demand estimates per category at monthly resolution for the 307 catchments.
4.	Textfiles with the storage volumes per category and catchment.

en: Hydro-CH2018 reservoirs

en: water-demand water-scarcity water-supply climate-change reservoirs

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: Water supply
    Size: 1113489603 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3fc83159-6e65-47f9-9fd8-dd60f749fda4/resource/340da6dc-991a-4f2e-9ff1-75b9daea4dcb/download/supply.zip
    Description: Simulated discharge series for a reference period 1981-2010 and till the end of the century. Data are provided for 39 climate model chains and a control run based on the observed meteorology. Data are provided at daily resolution (mm/d).

en:
Resource Title: Water demand (deprecated)
    Size: 920391 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3fc83159-6e65-47f9-9fd8-dd60f749fda4/resource/ab06042e-059a-40b0-b9da-101958dab5e7/download/demand.zip
    Description: Warning: please use the corrected version 2, since this file contains errors for certain categories such as Livestock, Industry or Houshold.

Water demand estimates for the 307 medium-sized catchments for different categories for current and future conditions. One text file is provided per demand category. One column corresponds to one catchment (IDs compare to shapefile), The data are provided at monthly resolution in mm/d and can be converted to volumes by using the catchment area. E.g.
Q[mm/d] * catchment area [m²] /1000 = Q[m³/d]
or to obtain discharge in m³/s
Q[mm/d] * catchment area [m²]/1000/24/3600 = Q [m³/s].
Future irrigation and hydropower water demand are provided per climate model chain.

en:
Resource Title: Water demand version 2 (corrected version)
    Size: 1007064 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3fc83159-6e65-47f9-9fd8-dd60f749fda4/resource/15462633-0157-4027-9f17-1e80ec4c1f92/download/demand.zip
    Description: Water demand estimates for the 307 medium-sized catchments for different categories for current and future conditions. One text file is provided per demand category. One column corresponds to one catchment (IDs compare to shapefile), The data are provided at monthly resolution in mm/d and can be converted to volumes by using the catchment area. E.g.
Q[mm/d] * catchment area [m²] /1000 = Q[m³/d]
or to obtain discharge in m³/s
Q[mm/d] * catchment area [m²]/1000/24/3600 = Q [m³/s].
Future irrigation and hydropower water demand are provided per climate model chain.

en:
Resource Title: Shapefile of 307 catchments in Switzerland
    Size: 100341 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3fc83159-6e65-47f9-9fd8-dd60f749fda4/resource/b30c2b9e-71f9-4798-b841-104a58d79667/download/shapefile_307_regions.zip
    Description: Shapefile of 307 catchments for which estimates of water supply, demand, and reservoir volumes are provided. The OBJECTID entry corresponds to the catchment ID which is used as a reference in the other datasets provided.

en:
Resource Title: Reservoir volumes
    Size: 7781 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3fc83159-6e65-47f9-9fd8-dd60f749fda4/resource/d601bc26-6f1a-46a3-9ccd-603fca11920b/download/reservoirs.zip
    Description: Reservoir volume for the 307 medium-sized catchments for different storage categories: natural lakes, artificial reservoirs, reservoirs for artificial snow production, drinking water reservoirs, and usable volumes of natural lakes.  Unit: Mio m³. One column per catchment (see shapefile).

reservoirs

display_name: reservoirs

water-demand

display_name: water-demand

water-scarcity

display_name: water-scarcity

water-supply

display_name: water-supply


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

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

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

en:
Resource Title: topsoil.zip
    Size: 8375186227 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.431/topsoil.zip
    Description: Predicted microclimate topsoil temperatures at 5 cm below ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en:
Resource Title: 5cm.zip
    Size: 8836895212 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.431/5cm.zip
    Description: Predicted microclimate air temperatures at 5 cm above ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en:
Resource Title: 100cm.zip
    Size: 8235599790 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.431/100cm.zip
    Description: Predicted microclimate air temperatures at 100 cm above ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

biodiversity

display_name: biodiversity

ecology

display_name: ecology

forest

display_name: forest

microclimate

display_name: microclimate

radiation-transfer

display_name: radiation-transfer

statistical-interpolation

display_name: statistical-interpolation


en: Although species range may be obtained using expert maps or modeling methods, expert data is often species-limited and statistical models need more technical expertise as well as many species observations. When unavailable, such information may be extracted from the Global Biodiversity Information facility (GBIF), the largest public data repository inventorying georeferenced species observations worldwide. However, retrieving GBIF records at large scale may be tedious if users are unaware of specific tools and functions that need to be employed. Here we present *gbif.range*, an R library that contains automated methods to generate species range maps from scratch using in-house ecoregions shapefiles and an easy-to-use GBIF download wrapper. Finally, this library also offers a set of additional very useful parameters and functions for large GBIF datasets (generate doi, extract GBIF taxonomy, records filtering...). [gbif.range R project](https://github.com/8Ginette8/gbif.range)

en: gbif.range - An R package to generate species range maps based on ecoregions and a user-friendly GBIF wrapper

en: conservation range-maps gbif species-observations synonyms hard-limit filtering flags accepted-name ecoregions large-scale species-distribution taxonomy landsca r-package occurrence-records

en:
Resource Title: GitHub URL
    Size: 0
    Format: .range
    URL: https://github.com/8Ginette8/gbif.range
    Description:

en:
Resource Title: gbif.range R package version 0.2 (deprecated)
    Size: 75970559 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f5f4a8fd-7172-4db0-9b41-832a94ea9cab/resource/802ecb6b-f4c6-49f8-b25d-093bf1ff9d7c/download/gbif.range_r_package.zip
    Description:

en:
Resource Title: wsl.gbif R package version 0.1 (deprecated)
    Size: 2704605 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f5f4a8fd-7172-4db0-9b41-832a94ea9cab/resource/402acab8-6657-452e-bde3-53b1cbb59dcd/download/wsl.gbif-main-version.2022-10-25.zip
    Description: Test version, not to be used.

en:
Resource Title: gbif.range R package version 1.1 (current)
    Size: 307157973 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f5f4a8fd-7172-4db0-9b41-832a94ea9cab/resource/3290357e-2e2f-4a10-a254-4689b5f91705/download/gbif.range.zip
    Description:

accepted-name

display_name: accepted-name

conservation

display_name: conservation

ecoregions

display_name: ecoregions

filtering

display_name: filtering

flags

display_name: flags

gbif

display_name: gbif

hard-limit

display_name: hard-limit

landsca

display_name: landsca

large-scale

display_name: large-scale

occurrence-records

display_name: occurrence-records

r-package

display_name: r-package

range-maps

display_name: range-maps

species-distribution

display_name: species-distribution

species-observations

display_name: species-observations

synonyms

display_name: synonyms

taxonomy

display_name: taxonomy