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

en: View video on youtube!

en: WMS-Layer als Hintergrundkarten laden

en:
In order to digitally plan a cable line using the QGIS plugin ‘Seilaplan’, maps with various background information are helpful. In this tutorial we show you how to obtain maps that are helpful for cable line planning, for example a national map of Switzerland at different scales, the NFI vegetation height model or the NFI forest mix rate. For this we explain what WMS datasets are and how to integrate them into QGIS. No download of large data is needed for this, only a good internet connection. Please note that the tutorial language is German!

Link for the integration of WMS data: https://wms.geo.admin.ch/

Link to the description on the Swisstopo website:
https://www.geo.admin.ch/en/geo-services/geo-services/portrayal-services-web-mapping/web-map-services-wms.html

Link to the Seilaplan website: https://seilaplan.wsl.ch

**************************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung sind verschiedene Hintergrundkarten hilfreich. In diesem Tutorialvideo zeigen wir, was WMS Daten sind und wie man diese in QGIS einbinden kann. Dafür müssen die Daten nicht heruntergeladen werden. Es braucht lediglich eine gute Internetverbindung. Für die Seillinienplanung hilfreiche Karten sind bspw. die Landeskarte der Schweiz in verschiedenen Massstäben, das Vegetationshöhenmodell LFI oder der Waldmischungsgrad LFI.

Link zur Einbindung der WMS Daten: https://wms.geo.admin.ch/

Link zur Beschreibung auf der Swisstopo Webseite: https://www.geo.admin.ch/de/geo-dienstleistungen/geodienste/darstellungsdienste-webmapping-webgis-anwendungen/web-map-services-wms.html

Link zur Seilaplan-Website: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

wms-data

display_name: wms-data

educ

en: Education, culture and sport

en: EnviDat: the Environmental Data Portal

en: Seilaplan Tutorial: Load WMS layers as background maps


en: water-potential water-use-strategy root-distribution anisohydric stomatal-stringency

state: active

type: dataset

en: The data file contains the data shown in the Figures 2-7 in Walthert et al. (2024).

format: XLS

en:
This dataset represents the data shown in the Figures 2 - 7 of Walthert et al. (2024): Coordination between degree of isohydricity and depth of root water uptake in temperate tree species. Science of the Total Environment (https://doi.org/10.1016/j.scitotenv.2024.174346). A detailed methodical description of the data can be found in the Methods section of the paper.

Abstract
In an increasingly dry environment, it is crucial to understand how tree species use soil water and cope with drought. However, there is still a knowledge gap regarding the relationships between species-specific stomatal behaviour, spatial root distribution, and root water uptake (RWU) dynamics.
Our study aimed to investigate above- and below-ground aspects of water use during soil drying periods in four temperate tree species that differ in stomatal behaviour: two isohydric tracheid-bearing conifers, Scots pine and Norway spruce, and two more anisohydric deciduous species, the diffuse-porous European beech, and the ring-porous Downy oak. From 2015 to 2020, soil-tree-atmosphere-continuum parameters were measured for each species in monospecific forests where trees had no access to groundwater. The hourly time series included data on air temperature, vapour pressure deficit, soil water potential, soil hydraulic conductivity, and RWU to a depth of 2 m. Analysis of drought responses included data on stem radius, leaf water potential, estimated osmotically active compounds, and drought damage.
Our study reveals an inherent coordination between stomatal regulation, fine root distribution and water uptake. Compared to conifers, the more anisohydric water use of oak and beech was associated with less strict stomatal closure, greater investment in deep roots, four times higher maximum RWU, a shift of RWU to deeper soil layers as the topsoil dried, and a more pronounced soil drying below 1 m depth. Soil hydraulic conductivity started to limit RWU when values fell below 10-3 to 10-5 cm/d, depending on the soil. As drought progressed, oak and beech may also have benefited from their leaf osmoregulatory capacity, but at the cost of xylem embolism with around 50% loss of hydraulic conductivity when soil water potential dropped below -1.25 MPa. Consideration of species-specific water use is crucial for forest management and vegetation modelling to improve forest resilience to drought.

anisohydric

display_name: anisohydric

root-distribution

display_name: root-distribution

stomatal-stringency

display_name: stomatal-stringency

water-potential

display_name: water-potential

water-use-strategy

display_name: water-use-strategy

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

it: EnviDat: il portale dei dati ambientali

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.

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Water-use strategies of temperate tree species


maintainer: Achille Capelli

en: gps swe snow-water-equivalent lwc snow gnss liquid-water-content

media_type: text/csv

en: Snow and meteo data from automatic sensors for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

format: CSV

mimetype: text/csv

en: GNSS derived SWE, LWC and HS from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-20

en: Snow profiles data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Snow and meteo data from automatic sensors for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Snow and meteo data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: Snow and meteo data from automatic sensors from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: Webcam images

media_type: application/zip

en: Webcam images showing some typical differences in the snow conditions at the four sites (Küblis, Klosters, Laret and Weissfluhjoch) for two time periods (14-18.3.2019 and 27.1-11.2.2020). Both time periods included a precipitation event with partial rain-on–snow occurring at the lower locations.

format: ZIP

en: Daily data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Manual profiles

en: Data of the traditional manual profiles for the locations Weissfluhjoch, Klosters and Küblis. For the location of Küblis there are no traditional manual profile data. We provided the data as both PDF and .CAAML format (See https://niviz.org/ or http://caaml.org/Schemas/V5.0/Profiles/SnowProfileIACS/CAAMLv5_SnowProfileIACS.pdf). Moreover, we added LWC and density profiles when available (all locations).

format: SERVICE

en: GNSS derived SWE, HS, and LWC for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: GNSS derived SWE, LWC and HS from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-20

en: Daily observer data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: Snow profiles data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: Daily observer data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: Daily data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Daily data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Snow profiles data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: GNSS derived data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Daily observer data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Profile data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Daily data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: This database contains GNSS derived snow water equivalent (SWE), liquid water content (LWC), and snow height (HS) and reference data collected during the two winter 2018-2020 at 4 sites Weissfluhjoch (2540 m asl, 46°49’47’’ N, 9°48’34’’E), Laret (1515 m asl, . 46°50’2’’N, 9°52’17’’E), Klosters (1200 m asl, 46°51’49’’N, 9°53’17’’E), and Küblis (815 m asl, 46°54’48’’N, 9°46’54’’E).

gnss

display_name: gnss

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

lwc

display_name: lwc

snow

display_name: snow

snow-water-equivalent

display_name: snow-water-equivalent

en: Snow water equivalent measurements with low-cost GNSS receivers along a steep elevation gradient in the East-ern Swiss Alps


maintainer: Esther Frei

en: afforestation treeline stillberg long-term-experiment mountain-forest

mimetype: application/x-zip-compressed

en:
 Background information

The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Long-term monitoring of the large-scale high-elevation afforestation has generated data about tree growth, survival, and vitality. In addition, detailed characteristics of the microsite conditions of the research were conducted. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone.

 Experiment description

The Stillberg afforestation experiment was established in 1975 by planting 92,000 seedlings of *Larix decidua*, *Pinus cembra* and *Pinus mugo* ssp. *uncinata* in the alpine treeline ecotone. The afforestation site is located on a northeast-facing slope with steep, topographically highly structured terrain and covers elevations from 2075 to 2230 m a.s.l. The afforestation site was divided into 4052 square plots of 3.5 × 3.5 m, arranged in a regular species-alternating pattern over the whole area. Each plot contained 25 trees of one species (1350 plots per species), and the seedlings were systematically planted 70 cm apart. The trees have been monitored since 1975. Specifically, tree mortality was assessed annually from 1975 until 1995 and has been documented every ten years since then, with surveys in 2005 and 2015 (the next survey is due in 2025). Height of the surviving trees was measured in 1975, 1979, 1982, 1985, 1990, 1995, 2005, and 2015. In 1995, 2005, and 2015, drivers of tree vitality were assessed for a subset of trees per plot. Additionally, an extensive set of environmental parameters characterizing microsite conditions of the afforestation area were recorded before and after the planting of the trees.

 Data description

The five datasets from the afforestation experiment comprise ecological and environmental data from the main afforestation experiment in five datasets with accompanying metadata (Stillberg_afforestation_all_metadata.xlsx). All data and metadata files are bundled in a ZIP-file (Stillberg_afforestation_v1.zip). In particular, a first dataset contains environmental data characterising microsite conditions of the 4000 plots with regard to soil, topography, vegetation and microclimatic conditions (Stillberg_afforestation_plot_data_v1.csv; Stillberg_afforestation_plot_metadata_v1.csv. In each plot, the natural tree regeneration was assessed by counting seedings of several tree species in 2005 and 2015 (Stillberg_afforestation_regeneration_data_v1.csv; Stillberg_afforestation_regeneration_metadata_v1.csv). Furthermore, specific information about each of the 92’000 planted trees of the tree species is available (Stillberg_afforestation_tree_parameter_data_v1.csv; Stillberg_afforestation_tree_parameter_metadata_v1.csv). Survival data for each of the 92’000 individual trees can be found in a separate dataset (Stillberg_afforestation_tree_survival_data_v1.csv; Stillberg_afforestation_tree_survival_metadata_v1.csv). Tree growth and vitality parameters are available for all trees from 1995, and for subsets of trees for 2005 and 2015 (Stillberg_afforestation_tree_measurements_data_v1.csv; Stillberg_afforestation_tree_measurements_metadata_v1.csv).

afforestation

display_name: afforestation

long-term-experiment

display_name: long-term-experiment

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline

display_name: treeline

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: Long-term afforestation experiment at the Alpine treeline site Stillberg, Switzerland


en: network-analysis dendroecology beech tree-ring dendrochronology fagus-sylvatica

en: Model output

en: Output of the Mixed-effects model

format: OCTET

media_type: text/plain

en:
This dataset contains the raw ring-width and climate data (1952-2020) used in the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation".
RW= ring width
Year= Calendar year
CN = core number
ID3= plot identifier
longitude = longitude (°)
latitude = latitude (°)
elevation = elevation (m)
age= estimated age in calendar year
radius= estimated radius in calendar year (mm)
MAT= mean annual temperature (°C)
MAP= mean annual precipitation (mm)
MCWB= mean climatic water balance (P-PET; mm)
amplitude= simple continentality measure (July - January mean maximum temperatures)
MATspline1 and 2, MCWBspline1 and 2, radiusspline4 and 5= natural spline transformed values of MAT, MCWB and radius ns(x,2)
CWD_pMay_Jun= Climatic Water Balance of previous year May to June !!!#please note CWD here is NOT Climatic Water Deficit, this was a labeling error in the creation of the dataset headers
CWD_May_Jun= Climatic Water Balance of current year May to June
Tmax_pMay_Jun= mean monthly maximum temperature of previous year May to June
Tmax_May_Jun= mean monthly maximum temperature of current year May to June
weight = site replication-based weighting input for model
SOM= membership of regional cluster 1-8 based on Supervised Organized Mapping

format: TXT

en:
R code to run the model behind the results of the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation".
Requires beech_rawtrw.txt.

en: This dataset contains the raw ring-width and climate data (1952-2020), as well as the R code to run the model and the model output used in the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation".

beech

display_name: beech

dendrochronology

display_name: dendrochronology

dendroecology

display_name: dendroecology

fagus-sylvatica

display_name: fagus-sylvatica

network-analysis

display_name: network-analysis

tree-ring

display_name: tree-ring

en: European Beech tree-ring dataset 1952-2020


weissfluhjoch-dataset-for-esm-snowmip

maintainer: Nander Wever

title_for_slug: weissfluhjoch-dataset-for-esm-snowmip

en: esm-snowmip snow-models snow-depth snow weissfluhjoch

mimetype: application/zip

en: Conversion script

en:
Use this script to convert WFJ_optimaldataset_v6.smet to wfj.smet, the file that is used for the ESM-SnowMIP project. It also requires the file: WFJ_AirPressure_Data.zip

Use: bash create_wfj_dataset.sh > input/wfj.smet

mimetype: text/x-sh

en: ini file

en: This ini file is required by data-converter from MeteoIO version 1887 (http://models.slf.ch/p/meteoio/)

en: Dataset Weissfluhjoch for ESM-SnowMIP

en: This Weissfluhjoch dataset is a processed version of the Weissfluhjoch dataset version 6 from https://doi.org/10.16904/6. This dataset was specially created for the ESM-SnowMIP project. Here it is documented how this dataset has been created.

esm-snowmip

display_name: esm-snowmip

snow-depth

display_name: snow-depth

snow-models

display_name: snow-models

weissfluhjoch

display_name: weissfluhjoch

en: Weissfluhjoch dataset for ESM-SnowMIP


maintainer: EnviDat Support

en: drone-data dsm photogrammetry uav wingtra

en: Data Access

en:
- DSM 10cm resolution
- Orthomosaic 3cm resolution
- Agisoft Metashape Processing Report
- original RGB images

All generated products are also available as a cloud optimized geotiff.

en: We conducted four drone flights in Davos Wolfgang Arelen, in 2020/21 and 2022 to obtain data for the generation of DSMs and orthomosaics at a high resolution. The data was processed with the Agisoft Metashape Professional Software.

drone-data

display_name: drone-data

dsm

display_name: dsm

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: Photogrammetric Drone Data Wolfgang Arelen


en: post-depositional-processes sublimation weissfluhjoch paleoclimate latent-heat stable-water-isotopes snow natural-tracer

en: Stable water isotopes in vapor

en:
Stable water isotopes in vapor measurements. Processed (calibrated) and raw data for February - June 2017. Raw data for January and February 2020.
For the time in between July 2017 and April 2020, raw vapor isotopic measurements are available, but no calibrations were performed during that time. For data delivery, please contact one of the authors.
This folder also contains the post-processing scripts for stable water isotopes in vapor measurements.

en: Folder containing the scripts and data used in "Surface snow isotopic composition: post-depositional processes in an alpine snowpack" (Sadowski et al., 2022)

en: Details about the different folders

media_type: application/pdf

en:
Details on the data collected during the different field campaigns and available in this dataset.
Information on the sampling procedure of the snow isotopes samples.

format: PDF

en: Stable water isotopes in snow

en: Stable water isotopes in snow measurements

en: Weather

en: Meteorological data, snow height measurement, and SNOWPACK simulations covering the different field campaigns.

en:
Notice: Changes to the dataset are still possible. Please do not use this dataset until the final publication with a DOI. Contact the authors if you have questions about this.

This dataset contains measurements of stable water isotopes in snow and vapor on the Weissfluhjoch from different field campaigns (Winter 2017 (Trachsel, 2019), January 2020, December 2020, and March 2021 (Sadowski et al., 2022).
Snow profiles and surface samples are available at different frequencies for each campaign. Please see "Data_description.pdf" for details.

Scripts and SNOWPACK simulations used in (Trachsel, 2019) and (Sadowski et al., 2022) are also provided.

latent-heat

display_name: latent-heat

natural-tracer

display_name: natural-tracer

paleoclimate

display_name: paleoclimate

post-depositional-processes

display_name: post-depositional-processes

snow

display_name: snow

stable-water-isotopes

display_name: stable-water-isotopes

sublimation

display_name: sublimation

en: Stable Water Isotopes in snow and vapor on the Weissfluhjoch


en: hatch budburst phenology spongy-month chilling

en: Temperature data Spongy moth experiment

en:
4 files with hourly temperature recorded at the height of buds in each of the four temperature treatments:
- Winter6: greenhouse where temperature was kept >6°C over winter
- Winter10: greenhouse where temperature was kept >10°C over winter
- OTC_Ambient: Open Top Chamber at Ambient temperature
- OTC_Warm: Open Top Chamber at +3.5°C warmer temperature

en: 3 R-Scripts used for the analyses of the temperature, phenology and performance/preference tests

en: Phenology and performance/preference tests Data

en:
-"Synchronex_Cuttings_Pheno.txt" provides the budburst date ('Stage 2') of each twig of the six studies species in the four different temperature treatments ("ambient", "a+5"=Ambient +5°C, 'Greenhouse-5'= Greenhouse at temperature >5°C, 'Greenhouse_10' = Greenhouse at temperature >10°C); 'Success' give the percentage of buds within the twig that succeeded to reach at least stage 2 during the experiment.

'Synchronex-Gypsy.txt' provides the number of eggs that have hatched at each monitoring date (Day of the year in columns); "DOY_hatch_1" corresponds to the first DOY when at least one egg has hatched; "Replicate_egg_mass" correspond to the egg mass replicate (1 to 5)

'PerformanceTest_GypsyMoth.txt' provides the biomass in mg of the caterpillars fed with fresh leaves of each tested tree species during one week. "Fresh_alive" is the biomass of only the living caterpillars after 1 week and "Freshpermoth" corresponds the weight per living caterpillar (Fresh alive/Nalive)

'PreferenceTest_All_species.txt' provides the total surface of leaf disc of each tested tree species remaining after exposing 5 caterpillars to these leaves during 24H. "Total_area" is the surface of the disc of each species measured after 24h exposed to the spongy moth first instars. For each species 'control' means the surface of the disc after 24H without any exposure to the larvae. 'EatenPercent correspond to the percentage surface loss compared to the control.

en:
The files correspond to the data and R-script used for the analyses of the following paper "Feasting on the ordinary or starving for the exceptional: phenological synchrony between spongy moth and budburst of European trees in a warmer climate" published in Ecology and Evolution by Vitasse et al. 2023.
There are three zip files corresponding to the Temperature data, phenology/preference/performance tests and R-Scripts for the analyses.

Input data:
'Synchrony_Cuttings_Pheno.txt':

budburst

display_name: budburst

chilling

display_name: chilling

hatch

display_name: hatch

phenology

display_name: phenology

spongy-month

display_name: spongy-month

en: Synchrony between spongy moth hatching and leaf phenology of temperate trees


en: snow metamorphism time-series x-ray-tomography fem microstructure

en: Simulation parameters and outputs for "A rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism"

format: ODS

en:
In the associated study [1], two time-lapse temperature gradient metamorphism series of three-dimensional micro-computed tomography images of snow (obtained by [2]) have been used to model the decrease of specific surface area (SSA) over time based on the pore-scale physics. We conducted finite element simulations of one-way coupled heat and mass diffusion in order to estimation the spatial pattern of water vapor deposition and sublimation, which controls the evolution of the SSA over time. We notably studied the influence of the condensation coefficient, a key but poorly constrained physical parameter.
This dataset provides the parameters used for the mesh generation and the finite element simulations. It also includes the ice fraction, specific surface area per unit volume and surface average of mean curvature and vapor field obtained as outputs from the mesh process and the simulations.
[1]: Braun, A., Fourteau, K., and Löwe, H.: A rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1947, 2023.
[2]: Pinzer, B. R., Schneebeli, M., and Kaempfer, T. U.: Vapor flux and recrystallization during dry snow metamorphism under a steady temperature gradient as observed by time-lapse micro-tomography, The Cryosphere, 6, 1141–1155, https://doi.org/10.5194/tc-6-1141-2012, 2012.

fem

display_name: fem

metamorphism

display_name: metamorphism

microstructure

display_name: microstructure

time-series

display_name: time-series

x-ray-tomography

display_name: x-ray-tomography

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: Simulation parameters and outputs for a rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism


en: modelling machine-learning land-use landscape land-cover landscape-change

en: Compressed (.zip) file containing six georeferenced raster files in the GeoTIFF format with embedded coordinate reference system, and a table (comma separated values, .csv) encoding a colour palette for plotting (HEX colour codes for each class). GeoTIFF file names include the time-step and the RCP (e.g. “LULC_2020_2049_RCP45.tiff”). Each raster file has 3484x2207 square pixels (i.e. 7.7 megapixels) and is projected in the Swiss coordinate system CH1903+/LV95 (EPSG:2056).

en:
Code used to produce the Land-use/land-cover forecasts for Switzerland across the 21st century at 100-m resolution.
The script is based on input data which are not included as they are not freely available, therefore it will not run as it is. These input data are described in the accompanying publication on Data Science access to them can be requested to their owners. Alternatively the code can be modified to run on other data.

en: We present forecasts of land-use/land-cover (LULC) change for Switzerland for three time-steps in the 21st century under the representative concentration pathways 4.5 and 8.5, and at 100-m spatial and 14-class thematic resolution. We modelled the spatial suitability for each LULC class with a neural network (NN) using >200 predictors and accounting for climate and policy changes. We used data augmentation to increase performance for underrepresented classes, resulting in an overall quantity disagreement of 0.053 and allocation disagreement of 0.15, which indicate good model performance. These class-specific spatial suitability maps outputted by the NN were then merged in a single LULC map per time-step using the CLUE-S algorithm, accounting for LULC demand for the future and a set of LULC transition rules. As the first LULC forecast for Switzerland at a thematic resolution comparable to available LULC maps for the past, this product lends itself to applications in land-use planning, resource management, ecological and hydraulic modelling, habitat restoration and conservation.

land-cover

display_name: land-cover

land-use

display_name: land-use

landscape

display_name: landscape

landscape-change

display_name: landscape-change

machine-learning

display_name: machine-learning

modelling

display_name: modelling

en: High resolution land use forecasts for Switzerland in the 21st century


en: taxonomic-diversity land-use-change migclim functional-diversity species-distribution-models conservation plants european-alps beta-diversity zonation global-change phylogenetic-diversity

en: Data Access

format: GeoTIFF

en: Updated SDM outputs

en: Refined scenarios of plants distribution in the European Alps

en:
This repository contains extensive data for the European Alps:
  - Observations of ~3,500 plant species
  - Climate (1-km), soil (100-m) and land cover predictors (1km); current and future scenarios (28 CMIP6-GCMs, 2 land cover change and 3 dispersal scenarios i.e., unlimited, no and realistic vegetation dispersal)
  - Flora migration rates (categorical) and ecological preferences (continuous indicator values)
  - Regional maps of barriers to migration and water bodies at 100-m resolution
  - Sampling effort, distance to roads and cities predictors at 100-m resolution
  - Present and future abundances over the study region at 1-km resolution (~2,000 species)
  - Present and future multifaceted and uniqueness of the European Alps' Flora at 1-km resolution
  - Present and future conservation recommendations at 1-km resolution (26 current and future strategies)
  - Phylogenetic data and functional traits of ~2,000 plants (raw data and classification trees)
  - All scripts, data and plots used for the analyses, including a singularity container (mini-linux) to run them

beta-diversity

display_name: beta-diversity

conservation

display_name: conservation

european-alps

display_name: european-alps

functional-diversity

display_name: functional-diversity

global-change

display_name: global-change

land-use-change

display_name: land-use-change

migclim

display_name: migclim

phylogenetic-diversity

display_name: phylogenetic-diversity

plants

display_name: plants

species-distribution-models

display_name: species-distribution-models

taxonomic-diversity

display_name: taxonomic-diversity

zonation

display_name: zonation

en: Present and future multifaceted plant diversity, uniqueness and conservation in the European Alps


maintainer: Matthias Haeni

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

en: Data plot of the field station (OTF)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

mimetype: application/pdf

en: Field station data (OTF)

en: Data file.

en: Site photo of the field station (OTF)

en: Site photo of the field station from below (viewing upwards the slope).

mimetype: image/jpeg

en: Site aerial photo (Othmarsingen)

en: Site aerial photo from both Othmarsingen stations. Source: Google. 2016. Site aerial photo from both Othmarsingen stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: Data plot of the forest station (OTB)

en: Site photo of the forest station (OTB)

en: Site photo of the forest station from above (viewing downwards the slope).

en: Forest station data (OTB)

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

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


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

en: Sonic temperature

en: The data set contains values of temperature (°C) measured with the anemometer at a sampling frequency of 20 Hz.

en: Sonic wind component u

en:
The data contains values for u direction of the wind in a sampling frequency of 20 Hz.
Erroneour spikes were filterd in two steps.

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

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

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

en: Sonic wind component w

en:
The data contains values for w direction of the wind in a sampling frequency of 20 Hz.
Erroneour spikes were filterd in two steps.

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

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

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

en: Sonic wind component v

en:
The data contains values for v direction of the wind in a sampling frequency of 20 Hz.
Erroneour spikes were filterd in two steps.

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

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

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

en: Sonic time

en: The data set contains the time in YYYY-mm-dd HH:MM:SS.sss for the anemometer data. The time is given in UTC+1.

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

anemometer

display_name: anemometer

raclets

display_name: raclets

wind

display_name: wind

wind-direction

display_name: wind-direction

wind-velocity

display_name: wind-velocity

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: Snow Drift Station - 3D Ultrasonic


maintainer: Frank Techel

en: shapefile observations snow alps avalanches

en: Selected wet snow avalanche activity data Davos, Switzerland (2011-2014)

en: Zip archive with shapefiles for the selected wet snow avalanche polygons, including metadata.

en:
Polygons of wet snow avalanches in the Davos area, as documented by the Swiss avalanche warning service. The georeferenced outlines of the avalanches contain both the release as well as the deposit area, but without separating between both.

The dataset is a subset of the total record of 1615 avalanches classified as wet snow avalanches from October 2011 - September 2014, containing those 255 avalanches exceeding 0.0125 km^2. Every polygon comes with meta data, including the date of occurrence.

This dataset is the underlying dataset to:
Wever, N., Vera Valero, C. and Techel, F. (2018) _Coupled snow cover and avalanche dynamics simulations to evaluate wet snow avalanche activity_. Submitted to J. Geophys. Res., in review.

alps

display_name: alps

avalanches

display_name: avalanches

observations

display_name: observations

shapefile

display_name: shapefile

snow

display_name: snow


maintainer: Marcia Phillips

en: borehole permos permafrost ritigraben meteo-station

en: DATA ACCESS

en: Meterological station at the [Ritigraben permafrost borehole](http://www.envidat.ch/dataset/rit1) (RIT_0102) in canton Valais, Switzerland. The station is located at 2690 m asl on a flat site.

borehole

display_name: borehole

meteo-station

display_name: meteo-station

permafrost

display_name: permafrost

permos

display_name: permos

ritigraben

display_name: ritigraben

en: RIT2: Meteorological station at Ritigraben borehole site


en: functional-taxonomic-group lichen madeira-island photobiont functional-taxonomic-groups elevational-gradient lichen-growthform climate-change biodiversity endemic disturbance liverwort bryophyte-life-strategy climate-change-impact lichen-growth-form moss bryophyte endemic-species

en: MadCrypto – Bryophyte and macrolichen diversity in laurel forests of Madeira

en:
This dataset includes species lists of bryophytes and macrolichens (presence/absence) sampled on the forest floor and on trees in disturbed and undisturbed plots along elevation gradients in the laurel forests of Madeira island. It also contains species specific information (bryophytes: red list status, endemic status, taxonomic group, life strategy; macrolichens: photobiont type, growth form) as well as plot information (Plot_ID, sampling date, coordinates, elevation a.s.l. (m), disturbance type, sampled host tree species).

The dataset was used for the paper
Boch S, Martins A, Ruas S, Fontinha S, Carvalho P, Reis F, Bergamini A, Sim-Sim M (2019) Bryophyte and macrolichen diversity show contrasting elevation relationships and are negatively affected by disturbances in laurel forests of Madeira island. Journal of Vegetation Science.

en:
This dataset includes species lists of bryophytes and macrolichens (presence/absence) sampled on the forest floor and on trees in disturbed and undisturbed plots along elevation gradients in the laurel forests of Madeira island. It also contains species specific information (bryophytes: red list status, endemic status, taxonomic group, life strategy; macrolichens: photobiont type, growth form) as well as plot information (Plot_ID, sampling date, coordinates, elevation a.s.l. (m), disturbance type, sampled host tree species).

The dataset was used for the paper
Boch S, Martins A, Ruas S, Fontinha S, Carvalho P, Reis F, Bergamini A, Sim-Sim M (2019) Bryophyte and macrolichen diversity show contrasting elevation relationships and are negatively affected by disturbances in laurel forests of Madeira island. Journal of Vegetation Science 30: 1122–1133.

The excel file contains 5 sheets:
1) Plot information
2) Bryophyte data with species specific information, separated per substrate
3) Macrolichen data with species specific information, separated per substrate
4) Bryophyte data with species specific information (plot level data). Species lists of the two substrates were merged; if one substrate in a plot hosted a species identified only to genus level (genus spec.) but the second investigated substrate hosted an identified species of the same genus, we removed the genus spec. entry in the particular plot. The species list of sheet 2 and 4 might therefore differ slightly.
5) Macrolichen data with species specific information (plot level data). Species lists of the two substrates were merged; if one substrate in a plot hosted a species identified only to genus level (genus spec.) but the second investigated substrate hosted an identified species of the same genus, we removed the genus spec. entry in the particular plot. The species list of sheet 3 and 5 might therefore differ slightly.

biodiversity

display_name: biodiversity

bryophyte

display_name: bryophyte

bryophyte-life-strategy

display_name: bryophyte-life-strategy

climate-change

display_name: climate-change

climate-change-impact

display_name: climate-change-impact

disturbance

display_name: disturbance

elevational-gradient

display_name: elevational-gradient

endemic

display_name: endemic

endemic-species

display_name: endemic-species

functional-taxonomic-group

display_name: functional-taxonomic-group

functional-taxonomic-groups

display_name: functional-taxonomic-groups

lichen

display_name: lichen

lichen-growth-form

display_name: lichen-growth-form

lichen-growthform

display_name: lichen-growthform

liverwort

display_name: liverwort

madeira-island

display_name: madeira-island

moss

display_name: moss

photobiont

display_name: photobiont


maintainer: Franziska Gerber

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

en: Static input data from the WRF simulations (used in the python scripts in Scripts_Reproducibility).

en: Processed CRYOWRF output used for the analysis and the figures in the paper.

en: Processed WRF output (run with Noah-MP land surface model) used for the analysis and the figures in the paper.

en: Python scripts to reproduces figures in Gerber et al., 2022, revised

en: Python scripts to reproduces figures in Gerber et al., 2022, submitted.

en: Namelist and input files and information to run the WRF and CRYOWRF simulations used in the paper.

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.

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

cryowrf

display_name: cryowrf

reproducibility

display_name: reproducibility

surface-mass-balance

display_name: surface-mass-balance

en: Reproducibility dataset for CRYOWRF validation


en: subalpine snow runoff alptal meteorological-data first-order-catchment

en: Meteorological data Alptal 1968-2023 EnviDat updated

en:
Air temperature, dew point temperature, relative humidity, wind speed, precipitation and global radiation have been measured (since 1981) on a meadow (Erlenhöhe) in the Erlenbach catchment. It is located at 1'220 m a.s.l. with an exposure towards west. In order to assess the spatial variability of precipitation, two additional rain gauges have been running in the Vogelbach and Lümpenenbach catchment, respectively. For the period before 1981, meteorological variables have been extrapolated from the nearby MeteoSwiss station Einsiedeln (ca. 15 km north) to the WSL station Erlenhöhe using a linear correction factor for air temperature, wind speed and precipitation. Snow depth has been recorded automatically since 2003. Snow water equivalent has been calculated using two numerical models: COUP model (Jansson, 2012) and DeltaSnow model (Winkler et al., 2021)

Jansson, P.-E. (2012). COUP model: model use, calibration, and validation.Transactions of the ASABE, 55(4), 1335–1344. Winkler, M., et al. (2021): Snow water equivalents exclusively from snow depths and their temporal changes: the Δsnow model, Hydrol. Earth Syst. Sci., 25, 1165-1187, 10.5194/hess-25-1165-861 2021.

en: Manual snow measurements Alptal (1968-2022)

en:
Snow depth, snow density and snow water equivalent have been measured since winter 1968/69 along more than 15 transects distributed across the Alptal valley representing different altitudes, aspects and land use (closed forest and open meadows). Length of the snow courses: 20 to 30 m. The measurement interval has been weekly to monthly.
More details about the locations and methods can be found in Stähli, M.; Gustafsson, D., (2006). Long-term investigations of the snow cover in a subalpine semi-forested catchment. Hydrological Processes, 20, 411-428. doi: 10.1002/hyp.6058.

en: Daily runoff data from three steep torrents in the Alptal (1968-2022)

en: Runoff, water temperature and electrical conductivity have been measured since 1968 at the outlet of three torrential catchments (with an area of approximately 1 km2 each) located in the Alptal valley: Erlenbach, Lümpenenbach and Vogelbach. This data set provides daily mean values; data at 10-min resolution can be provided on request for the period 1984-2022 (contact: alptal@wsl.ch).

en: Daily meteorological and snow data (1968-2022) Alptal

en:
Air temperature, dew point temperature, relative humidity, wind speed, precipitation and global radiation have been measured (since 1981) on a meadow (Erlenhöhe) in the Erlenbach catchment. It is located at 1'220 m a.s.l. with an exposure towards west. In order to assess the spatial variability of precipiation, two additional rain gauges have been running in the Vogelbach and Lümpenenbach catchment, respectively.
For the period before 1981, meteorological variables have been extrapolated from the nearby MeteoSwiss station Einsiedeln (ca. 15 km north) to the WSL station Erlenhöhe using a linear correction factor for air temperature, wind speed and precipitation.
Snow depth has been recorded automatically since 2003. Snow water equivalent has been calculated using two numerical models: COUP model (Jansson, 2012) and DeltaSnow model (Winkler et al., 2021)

Jansson, P.-E. (2012). COUP model: model use, calibration, and validation.Transactions of the ASABE, 55(4), 1335–1344.
Winkler, M., et al. (2021): Snow water equivalents exclusively from snow depths and their temporal changes: the Δsnow model, Hydrol. Earth Syst. Sci., 25, 1165-1187, 10.5194/hess-25-1165-861 2021.

en: Runoff daily mean Alptal 1968-2023 EnviDat updated

en: Runoff, water temperature and electrical conductivity have been measured since 1968 at the outlet of three torrential catchments (with an area of approximately 1 km2 each) located in the Alptal valley: Erlenbach, Lümpenenbach and Vogelbach. This data set provides daily mean values; data at 10-min resolution can be provided on request for the period 1984-2023 (contact: alptal@wsl.ch).

en: Snow measurements Alptal 1969-2023 EnviDat updated

en:
This data set includes 54 years of hydrometeorological measurements from small (first-order) catchments in the pre-alpine valley Alptal. Here we provide daily mean values; values in sub-daily resolution can be provided on demand.
Runoff has been measured at the outlet of three small (first-order) catchments of approximately 1 km2 area: Erlenbach (two independent runoff measurements), Vogelbach and Lümpenenbach. The catchments are similar with regard to geology (Flysch) and soil conditions (clay soils), but differ in forest coverage (20 to 60%). A detailed description of the catchments can be found at https://www.wsl.ch/alptal .
Runoff in these small catchments is typically very dynamic and can temporally carry large amounts of sediment and large wood. Thus, the accuracy of the measurements at very large flow is limited.
Meteorological variables have been measured on a meadow (Erlenhöhe) located in the Erlenbach catchment at 1220 m a.s.l. using a standard meteorological station (incl. ventilated air temperature and heated rain gauges). In addition, precipitation has also been recorded at two other locations (in the Vogelbach and Lümpenenbach catchments).
Snow measurements have been conducted weekly to monthly since 1968 at more than 15 locations (30-m transects) representing different altitudes, aspects and land uses (meadow, forest). In addition, snow depth has been recorded continuously since 2003 at Erlenhöhe, and for this location we also include a simulation of snow depth and SWE (using the numerical models COUP and DeltaSnow) that assimilates the manual weekly snow-course measurements. Details on these snow measurements can be found in Stähli, M. and Gustafsson, D. 2006. Hydrol. Proc., 20, 411-428. doi: 10.1002/hyp.6058.

Further information on the methods and sensors can be found at https://www.wsl.ch/alptal .

A first version of this data set (for the period 1968-2017) was uploaded in June 2018 at the occasion of the 50-year anniversary. This original data set was updated in February 2021 (with data from 2018 and 2019), and this data set was used for a longterm trend analysis, submitted for publication in a special issue of Hydrological Processes. A second update of the data set (with data from 2020 to 2022) was uploaded in March 2023.

alptal

display_name: alptal

first-order-catchment

display_name: first-order-catchment

meteorological-data

display_name: meteorological-data

runoff

display_name: runoff

snow

display_name: snow

subalpine

display_name: subalpine

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: Longterm hydrological observatory Alptal (central Switzerland)


maintainer: Ana Beatriz Pierri Daunt

en: sense-of-place planning decision-making literature-review landscape-ecology landscape-services landscape-perception green-infrastructure resilience ecosystem-services socio-ecological-system landscape-planning pdfsearch multifunctionality

en: 5. Planning steps.

en: 3. Use of any early concept.

en: 2. Frequency of additional concepts.

en: 6. Protocol

en: 1. Frequency of early concepts.

en: 4. Use of any additional concept.

en:
Table of content: 1. Frequency of early concepts; 2. Frequency of additional concepts; 3. Use of any early concept; 4. Use of any additional concept, 5. Planning steps; 6. Protocol.

The present dataset is part of the published scientific paper entitled “Landscape ecological concepts in planning: review of recent developments” (Hersperger et al., 2021). The goal of this research was to review recent publications to assess the use of landscape ecological concepts in planning. Specifically, we address the following research questions: Q1. Landscape ecological concepts: What are they? How frequently are they mentioned in current research? Q2. How are landscape ecological concepts integrated in landscape planning?

We analysed all empirical and overview papers that have been published in four key academic journals in the field of landscape ecology and landscape planning in the years 2015–2019 (n = 1918). Four key journals in the field of landscape ecology were selected to conduct the analysis, respectively Landscape Ecology (LE), Landscape Online (LO), Current Landscape Ecology Reports (CLER), and Landscape and Urban Planning (LUP). The title, abstract and keywords of all papers were read in order to identify landscape ecological concepts. Then, all 1918 papers went through a keyword search to identify the use of early and additional concepts. We used the “pdfsearch” package in R programming language and searched for singular and plural forms and different variations of the concepts (see Supplementary material 1, Table A). As a result, we provided four outputs:

  1. Frequency of early concepts. This data provides the total number of times each article used each early concept (Q1). This data was used to produce the Figure 2a at the original publication.

  2. Frequency of additional concepts. This data provides the total number of times each article used each additional concept (Q1). This data was used to produce the Figure 2b at the original publication.

  3. Use of any early concept. This data provides the total number of times each article used any early concept (Q1).
This data was used to produce the Figure 3a at the original publication.

  4. Use of any additional concept. This data provides the total number of times each article used any additional concept (Q1). This data was used to produce the Figure 3b at the original publication.

To address the second question (Q2), the title, abstract and keywords of the papers included in our sample (n=1918 articles) were screened to identify papers that might show how landscape ecological concepts are integrated into planning. We selected 52 empirical papers (see Supplementary material – 4 Integration of landscape ecological concepts into planning), and we provided two outputs:

  5. Planning steps. This data provides the number of times landscape ecological concepts were addressed in each
planning steps in 52 empirical papers analysed in detail (Q2). This data was used to produce the Figure 4 at the
original publication.

  6. Protocol for assessing the integration of landscape ecological concepts into planning. To systematically collect the
data, we used this protocol which addressed the following questions: (a) which type of planning is addressed by the
paper? (b) to which planning level does the paper refer to? (c) which concepts are integrated in any of the planning
steps described above?

decision-making

display_name: decision-making

ecosystem-services

display_name: ecosystem-services

green-infrastructure

display_name: green-infrastructure

landscape-ecology

display_name: landscape-ecology

landscape-perception

display_name: landscape-perception

landscape-planning

display_name: landscape-planning

landscape-services

display_name: landscape-services

literature-review

display_name: literature-review

multifunctionality

display_name: multifunctionality

pdfsearch

display_name: pdfsearch

planning

display_name: planning

resilience

display_name: resilience

sense-of-place

display_name: sense-of-place

socio-ecological-system

display_name: socio-ecological-system

en: The usage of landscape ecological concepts in the planning literature


irkis-soil-moisture-measurements-davos

title_for_slug: irkis-soil-moisture-measurements-davos

en: dischma-catchment davos soil-moisture meteorological-measurements meteo-station

en: IRKIS soil moisture data (zip file)

en: Compressed archive (zip) containing soil moisture measurements, as well as meteorological measurements and interpolated meteorological time series.

en:
Meteorological and soil moisture measurements from soil moisture stations installed from October 2010 - October 2013 in the area surrounding Davos, in particular in the Dischma catchment.

There are in total 7 stations: 1202, 1203, 1204, 1205, 222, 333 and SLF2. For each of the stations, there is a:

* vwc_[stn].smet: containing the soil moisture measurements

* station_[stn].smet: in-situ measured meteorlogical parameters. Note, the quality of these measurements for stations 1202, 1203, 1204 and 1205 is very low, with data gaps. Use this data with care. For stations 222, 333 and SLF2, data quality is high and only the default cautiousness should be applied.

* interpolatedmeteo_[stn].smet contains per stations a dataset derived by interpolating from several stations in the Davos area to the stations location. This dataset was generated from the output of the Alpine3D model, of which simulations are presented in the Wever et al. (2017) manuscript.

At the soil moisture measurement sites, Decagon 10HS sensors were installed, at 10, 30, 50, 80 and 120 cm depth. Per depth 2 sensors were installed, labelled A and B in the datafiles. Note that at stations 1203, 1204 and 1205, sensors were only installed at 10, 30 and 50 cm depth.

The files follow the SMET format: https://models.slf.ch/docserver/meteoio/SMET_specifications.pdf and metadata for the stations can be found in the header of the smet files.

Please cite the Wever et al. (2017) reference when using this data in publications.

For a more detailed description, please refer to: Wever, N., Comola, F., Bavay, M., and Lehning, M.: Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment, Hydrol. Earth Syst. Sci., 21, 4053-4071, https://doi.org/10.5194/hess-21-4053-2017, 2017.

davos

display_name: davos

dischma-catchment

display_name: dischma-catchment

meteo-station

display_name: meteo-station

meteorological-measurements

display_name: meteorological-measurements

soil-moisture

display_name: soil-moisture

en: IRKIS Soil moisture measurements Davos


snow-drift-station-flowcapt

maintainer: Benjamin Walter

title_for_slug: snow-drift-station-flowcapt

en: flowcapt snow-blowing snowdrift wind-speed raclets acoustic-mass-flux

en: minimum wind spees

en: The data file contains the minimum wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: avergaged mass flux

en: Average mass flux of 10 min measurement interval. The Cycle duration is 1 min which includes 6 s observation and 54 s stand-by. The time is given in UTC+1.

en: minimum mass flux

en: The data file contains the minimum mass flux of 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: average wind speed

en: The data file contains the average wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: maximum wind speed

en: The data file contains the maximum wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6 s observations and 54 s stand-by. The time is given in UTC+1.

en: maximum mass flux

en: The data file contains the maximum mass flux of 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: The FlowCapt is an ultra-robust instrument measuring solid particle acoustic mass - flux intensities (g m‾ ² s‾ ¹) and wind speeds (m s‾ ¹). It was deployed at Gotschnagrat (LON: 46.859 LAT: 9.849). The vertical tube with a length of 1 m monitors snowdrift and snow-blowing; and is mounted at a height between 0.1 an 1.1 m above snow surface. The time within each data set is given in UTC+1.

acoustic-mass-flux

display_name: acoustic-mass-flux

flowcapt

display_name: flowcapt

raclets

display_name: raclets

snow-blowing

display_name: snow-blowing

snowdrift

display_name: snowdrift

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Snow Drift Station - Flowcapt


en: sentinel-2 raster-processing force remote-sensing time-series switzerland

media_type: image/tiff

format: TIFF

en:
We processed Sentinel-2 image time series from 2017 to 2023 for Switzerland with the Software FORCE (Frantz 2019) on the basis of [Sentinel-2 images](https://envidat.ch/#/metadata/sentinel-2-imagery-of-switzerland). The respective parameter files can be found here: [Github](https://github.com/TLKoch/Sentinel-2_CH). All the image time series consist of several TB and therefore access will be granted upon request.
The available bands (in spatial reference system EPSG 3035) are the following:
Red, Green, Blue, NIR, Red-Edge-1, Red-Edge-2, Red-Edge-3, SWIR-1, SWIR-2
The available indices (in spatial reference system EPSG 3035) are the following:
CCI, CIRE, NDWI/NDMI, NDVI, EVI
Further indices might be provided upon request.

 Processing
On the basis of processed Sentinel-2 images for the 14 Sentinel-2 tiles covering Switzerland (T31TGN, T32TLT, T32TMT, T32UMU, T32TNT, T32TPT, T31TGM, T32TLS, T32TMS, T32TNS, T32TPS, T32TLR, T32TMR, T32TNR), we processed the image time series further with FORCE v. 3.7.8-12.
We generated interpolated Sentinel-2 time series with a 5-day interval, corresponding to the theoretical revisit time of the Sentinel-2 satellites. It's important to note that the 5-day time series consist of interpolated and smoothed composites, not the original images. We used the radial basis convolutional filtering (RBF) available in the FORCE time series analysis (TSA) submodule (Schwieder et al. 2016). The RBF is similar to a spatial moving window average approach over time (Schwieder et al. 2016). We applied kernel width values of 10, 20, 30, and 50 days. We spectrally adjusted all the images to match Sentinel-2A, and we removed curve outliers and pixels that failed the quality checks for clouds and their shadows, snow, saturation, and limited illumination. The processed image time series are available in tiles of 30 by 30 km.

 Example images
Uploaded is an example of the index EVI for one of the generated 30 by 30 km tiles located around the city of Zürich. The values are multiplied by 10.000. The time series spans the month of July from 2018.

force

display_name: force

raster-processing

display_name: raster-processing

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

time-series

display_name: time-series

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: Sentinel-2 time series of Switzerland


veloparkierungsanlagen

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: veloparkierungsanlagen

de: velo parkierung offentlich veloparkierungsanlagen ov haltestelle fahrrad

label: geocat.ch permalink

fr: Der Kanton Zürich hat sich zum Ziel gesetzt, eine attraktive Veloinfrastruktur bereit zu stellen. Dabei spielt die Verfügbarkeit von genügend zweckmässigen öffentlichen Velo-parkierungsanlagen an den wichtigsten ÖV-Haltestellen eine bedeutende Rolle. 2011 wurde eine umfangreiche Erhebung von öffentlich zugänglichen Veloparkierungs-anlagen im Kanton Zürich durchgeführt. 2015 und 2019 wurden Erhebungen der Velo-parkierungsanlagen an ÖV-Haltestellen mit mehr als 500 Quelleinsteigern (gemäss kan-tonalem Gesamtverkehrsmodell GVM) durchgeführt (ohne Anlagen der Stadt Zürich). Die Standortdaten zur Erhebung 2019 finden sich über diesen WFS.

format: WFS

fr: Der Kanton Zürich hat sich zum Ziel gesetzt, eine attraktive Veloinfrastruktur bereit zu stellen. Dabei spielt die Verfügbarkeit von genügend zweckmässigen öffentlichen Velo-parkierungsanlagen an den wichtigsten ÖV-Haltestellen eine bedeutende Rolle. 2011 wurde eine umfangreiche Erhebung von öffentlich zugänglichen Veloparkierungs-anlagen im Kanton Zürich durchgeführt. 2015 und 2019 wurden Erhebungen der Velo-parkierungsanlagen an ÖV-Haltestellen mit mehr als 500 Quelleinsteigern (gemäss kan-tonalem Gesamtverkehrsmodell GVM) durchgeführt (ohne Anlagen der Stadt Zürich). Die Standortdaten zu diesen drei Erhebungen finden sich über diesen WMS.

format: WMS

fr: WFS für Open-Government-Data des Kantons Zürich (OGD ZH WFS)

fr: Der Datensatz "Veloparkierungsanlagen an wichtigen ÖV-Haltestellen im Kanton Zürich" befasst sich mit den Veloparkierungsanlagen an wichtigen ÖV-Haltestellen im Kanton Zürich. Die Veloparkierungsanagen werden alle vier Jahre im Feld erhoben. Die zu untersuchenden ÖV-Haltestellen werden auf der Grundlage von Daten zu Ein- und Ausstiegen festgelegt. Die Anlagen werden innerhalb eines distanzabhängigen Perimeters um die Haltestellen registriert. Bei der Erhebung werden diverse Eigenschaften festgehalten, bspw. zur Anzahl und Qualität der Abstellplätze. Anhand eines Standardsets an ÖV-Haltestellen, die bisher bei allen Durchführungen Teil der Erhebung waren, lassen sich Zeitreihen zur Entwicklung der Veloparkierungsinfrastruktur im Kanton Zürich und anderen Raumeinheiten berechnen.

spatial: Kanton Zürich

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

fr:
Le département de géomatique est le centre de compétence du system d'information géographique du canton de Zurich.
Nous coordinons l'aquisition des géodonnées d'intérêt commun sur le territoire cantonal et les mettons à disposition des
secteurs public et privé et des particuliers.

en:
The department of geoinformation is the geospatial competency center of the Canton of Zurich.
We coordinate the acquisition of geodata within the cantonal territory and provide public, private, and government sectors with data of outstanding quality.

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

it: La divisione della geoinformazione è il centro d'eccellenza del Cantone di Zurigo per dati georeferenziati. Mettiamo a disposizione dati geografici e informazioni di alta qualità per l'economia, la società e la pubblica amministrazione su tutto il cantone.

political_level: canton

value: ZH - Geocat Harvester

fr: Veloparkierungsanlagen

de: Veloparkierungsanlagen

en: Veloparkierungsanlagen

it: Veloparkierungsanlagen


amtliche-vermessung-zg

title_for_slug: amtliche-vermessung-zg

de: geodienste.ch - WFS Amtliche Vermessung

de: Amtliche Vermessung

de: geodienste.ch WMS Amtliche Vermessung (MOpublic)

de: Die amtliche Vermessung – ein nationales Produkt – liefert geometrische Daten zum Grundeigentum und ist die Grundlage für viele weitere geografische Informationen und Anwendungen in Wirtschaft, Verwaltung und Privatleben.

spatial: Kanton Zug (ZG)

name: Amt für Grundbuch und Geoinformation des Kantons Zug

gis-kanton-zug

fr: GIS Kanton Zug

de: GIS Kanton Zug

en: GIS Kanton Zug

de:
Die Abteilung Geoinformation ist das kantonale Kompetenzzentrum für Geoinformation im Kanton Zug.
Wir sind eine zukunftsorientierte Dienstleistungseinheit für die Verwaltung, Werke, Bürgerinnen und Bürger, Wirtschaft und Politik. Kantonale und kommunale Amtsstellen erhalten von uns Unterstützung bei Ihren GIS-Projekten.
Wir sorgen für die Einhaltung einheitlicher Standards bei der Erstellung von Datenmodellen und beim Einsatz der benötigten Software. Beim Beschaffen, Verwalten, Visualisieren, Bearbeiten, und Verteilen der Geodaten arbeiten wir eng mit den Fachämtern zusammen.

value: ZG-Kt - Geocat Harvester

de: Amtliche Vermessung ZG


schwarzplan

title_for_slug: schwarzplan

de: av grundkarte hintergrundkarte

fr: Map (Preview)

de: Map (Preview) Stadtplan

en: Map (Preview)

it: Map (Preview)

de: Link zum Thema im Internet-Stadtplan der Stadt Bern

de: WMS Schwarzplan

de: Web Map Services WMS

de: WMTS Schwarzplan

de: Web Map Tile Services WMTS

format: WMTS

de: Die Gebäudeflächen aus der Bodenbedeckung der Amtlichen Vermessung schwarz eingefärbt bilden eine einfache Grundkarte "Schwarzplan".

spatial: Stadt Bern

geoinformation-der-stadt-bern

fr: L’Office du cadastre de la ville de Berne

de: Geoinformation Stadt Bern

en: The Land Surveying Office of the City of Bern

it: L'ufficio del catasto nella Città di Berna

fr: L’Office du cadastre (Geoinformation Stadt Bern) est l’organisme compétent pour la collecte, l’accès et la diffusion d’informations géographiques dans la ville de Berne.

de: Geoinformation Stadt Bern (ehemals Vermessungsamt) ist die Kompetenzstelle für die Beschaffung, den Zugang und die Verbreitung von Geoinformationen in der Stadt Bern.

en: The Surveying Office (Geoinformation Stadt Bern) is the centre of competence in the City of Bern for the procurement of, access to and dissemination of geographic information.

it: L'ufficio del catasto (Geoinformation Stadt Bern) è il centro di competenza per il reperimento, l'accesso e la diffusione di geoinformazioni nella Città di Berna.

political_level: commune

value: Geoinformation Stadt Bern - Geocat Harvester

de: Schwarzplan


amtliche-vermessung-darstellung-kontur

regi

de: Regionen und Städte

envi

de: Umwelt

title_for_slug: amtliche-vermessung-darstellung-kontur

de: av katasterplan

de: WMS Amtliche_Vermessung_Kontur

de: WMTS Amtliche_Vermessung_Kontur

de: WFS Amtliche_Vermessung_Kontur

de: Web Feature Services WFS

de: Daten der amtlichen Vermessung in schwarz und ohne Flächenfüllungen dargestellt. Kann zur Überlagerung mit flächengefüllten Informationen nützlich sein.

de: Amtliche Vermessung (Darstellung Kontur)


de: Map (Preview) Stadtplan

de: Link zum Thema im Internet-Stadtplan der Stadt Bern

de: WMS Amtliche_Vermessung_fuer_Orthofoto

de: WMTS Amtliche_Vermessung_fuer_Orthofoto

de: WFS Amtliche_Vermessung_fuer_Orthofoto

de: Daten der amtlichen Vermessung in weiss/gelb und ohne Flächenfüllungen dargestellt. Kann zur Überlagerung mit Orthofotos nützlich sein.

de: Amtliche Vermessung (Darstellung für Orthofoto)


stadtplan-darstellung-schwarz-weiss

title_for_slug: stadtplan-darstellung-schwarz-weiss

de: av grundkarte hintergrundkarte

de: WMS Stadtplan_schwarzweiss

de: Web Map Services WMS

de: WMTS Stadtplan_schwarzweiss

de: Web Map Tile Services WMTS

de: WFS Stadtplan_schwarzweiss

de: Schwarz/weisse, einfache Darstellung basierend auf den Daten der amtlichen Vermessung.

geoinformation-der-stadt-bern

de: Geoinformation Stadt Bern

de: Geoinformation Stadt Bern (ehemals Vermessungsamt) ist die Kompetenzstelle für die Beschaffung, den Zugang und die Verbreitung von Geoinformationen in der Stadt Bern.

de: Stadtplan (Darstellung schwarz/weiss)


stadtplan-darstellung-farbig

regi

de: Regionen und Städte

envi

de: Umwelt

title_for_slug: stadtplan-darstellung-farbig

de: Map (Preview) Stadtplan

de: WMS Stadtplan_farbig

de: WMTS Stadtplan_farbig

de: WFS Stadtplan_farbig

de: Web Feature Services WFS

de: Farbige, einfache Darstellung basierend auf den Daten der amtlichen Vermessung.

de: Stadtplan (Darstellung farbig)


de: av katasterplan kreis

de: Link zum Thema im Internet-Stadtplan der Stadt Bern

de: WMS Amtliche_Vermessung_schwarzweiss

de: Web Map Services WMS

de: WMTS Amtliche_Vermessung_schwarzweiss

de: WFS Amtliche_Vermessung_schwarzweiss

de: Plan für das Grundbuch der Stadt Bern in Graustufen mit blau eingefärbten Gewässern.

de: Amtliche Vermessung (Darstellung schwarz/weiss)


amtliche-vermessung-darstellung-farbig

regi

de: Regionen und Städte

title_for_slug: amtliche-vermessung-darstellung-farbig

de: WMS Amtliche_Vermessung_farbig

de: WMTS Amtliche_Vermessung_farbig

de: Web Map Tile Services WMTS

de: WFS Amtliche_Vermessung_farbig

de: Plan für das Grundbuch der Stadt Bern - farbig.

geoinformation-der-stadt-bern

de: Geoinformation Stadt Bern

de: Geoinformation Stadt Bern (ehemals Vermessungsamt) ist die Kompetenzstelle für die Beschaffung, den Zugang und die Verbreitung von Geoinformationen in der Stadt Bern.

de: Amtliche Vermessung (Darstellung farbig)


influenza

maintainer: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

title_for_slug: influenza

label: BAG-OFSP-UFSP-FOPH Website

fr: Virus respiratoire - Sentinella

de: Respiratorische Viren - Sentinella

en: Respiratory viruses - sentinella

it: Virus respiratori - Sentinella

fr: Les données se fondent sur les informations recueillies par le système de déclaration Sentinella. Dans le cadre de ce système, les médecins transmettent des informations sur les premières consultations en raison d’une infection respiratoire aiguë (ARI) ou d’une affection grippale (ILI) dans leurs cabinets ou lors de visites à domicile.

de: Die Daten basieren auf Informationen aus dem Sentinella-Meldesystem. Im Rahmen dieses Meldesystems übermitteln ambulant tätige Ärztinnen und Ärzte Informationen zu Erstkonsultationen aufgrund akuter respiratorischer Infektion (ARI) oder grippeähnlicher Erkrankung (ILI) in Arztpraxen und bei Hausbesuchen.

en: The data are based on information from the Swiss Sentinel Surveillance Network (SSSN, Sentinella) monitoring system. Within the framework of this reporting system, outpatient doctors send information on initial consultations due to acute respiratory infection (ARI) or influenza-like illness (ILI) in medical practices and during home visits.

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Nel quadro di questo sistema di dichiarazione, i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano un’infezione respiratoria acuta (acute respiratory infection, ARI) o una sindrome simil-influenzale (influenza-like illness, ILI).

fr: Influenza - Système de déclaration obligatoire

de: Influenza - Obligatorisches Meldesystem

en: Influenza - mandatory reporting system

it: Influenza - Sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires en Suisse et dans la Principauté de Liechtenstein ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

en: The data are based on information that laboratories have submitted to the FOPH under the mandatory reporting requirement.

de: Die Daten basieren auf Informationen, die Laboratorien dem BAG im Rahmen der Meldepflicht übermittelt haben.

it: I dati si basano su informazioni comunicate dai laboratori in Svizzera e nel Principato del Liechtenstein all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

fr: Virus respiratoire - Monitorage des eaux usées

de: Respiratorische Viren - Abwassermonitoring

en: Respiratory viruses - wastewater monitoring

it: Virus respiratori - Monitoraggio delle acque reflue

fr: Die Daten basieren auf Informationen aus dem nationalen Abwassermonitoring der Schweiz und des Fürstentums Liechtenstein. Dieses Monitoring erfasst seit Januar 2022 die Viruslast von SARS-CoV-2 und seit Juli 2023 die Viruslast von Influenza und RSV in Abwasserproben der teilnehmenden Abwasserreinigungsanlagen (ARA).

fr: Influenza - Sentinella

en: Influenza - sentinella

de: Influenza - Sentinella

it: Influenza - Sentinella

fr: The data are based on information from the Swiss Sentinel Surveillance Network (Sentinella, SSSN) monitoring system. Since 1987, outpatient doctors have been submitting information on initial consultations in medical practices and during home visits for patients with influenza-like illness (ILI).

fr: Données concernant la propagation et l’évolution temporelle des infections grippales et des cas de grippe en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les consultations ambulatoires provenant du système de déclaration Sentinella, sur les cas confirmés en laboratoire provenant du système de déclaration obligatoire et sur la charge virale dans les eaux usées provenant du monitorage des eaux usées.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Influenza Infektionen und Grippe Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu ambulanten Konsultationen aus dem Sentinella-Meldesystem, zu laborbestätigten Fällen aus dem obligatorischen Meldesystem und zur Viruslast im Abwasser aus dem Abwassermonitoring.

en: Data on the spread and development of influenza infections and cases in Switzerland and the Principality of Liechtenstein. You will find data of outpatient consultations from the Sentinella reporting system and of cases from the obligatory reporting systemand of the viral load in wastewater from the wastewater monitoring system,.

it: Dati della diffusione e dell’evoluzione temporale delle infezioni e dei casi di influenza in Svizzera e nel Principato del Liechtenstein. Qui trovate dati delle consultazioni ambulatoriali basate sul sistema di dichiarazione Sentinella, dati dei casi confermati in laboratorio basate sul sistema di dichiarazione obbligatoria e dati della carica virale nelle acque reflue basate sul sistema di monitoraggio delle acque reflue.

bag-grippe-influenza

display_name: bag-grippe-influenza

foph-seasonal-flu-influenza

display_name: foph-seasonal-flu-influenza

ofsp-grippe-saisonniere-influenza

display_name: ofsp-grippe-saisonniere-influenza

ufsp-influenza-stagionale-influenza

display_name: ufsp-influenza-stagionale-influenza

fr: Influenza

de: Influenza

en: Influenza

it: Influenza

heal

de: Gesundheit

abteilung-uebertragbare-krankheiten

fr: Division Maladies transmissibles

de: Abteilung Übertragbare Krankheiten

en: Communicable Diseases Division

it: Divisione Malattie trasmissibili

fr: Les maladies transmissibles constituent une menace pour la santé publique. La division les surveille, publie régulièrement des rapports sur la situation épidémiologique, définit des stratégies de prévention et de contrôle, et les met en œuvre.

en: Communicable diseases pose a risk to public health. The division monitors these diseases, publishing regular reports on the epidemiological situation, laying down and implementing prevention and control strategies.

de: Übertragbare Krankheiten gefährden die öffentliche Gesundheit. Die Abteilung überwacht diese Krankheiten, publiziert regelmässig Berichte zur epidemiologischen Situation, legt Präventions- und Kontrollstrategien fest und setzt sie um.

it: Le malattie trasmissibili mettono in pericolo la salute pubblica. La divisione Malattie trasmissibili le monitora, pubblica regolarmente rapporti sulla situazione epidemiologica, stabilisce strategie di prevenzione e di controllo e le attua.

political_level: confederation


tularamie

title_for_slug: tularamie

name: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

fr: Tularémie - Système de déclaration obligatoire

de: Tularämie - Obligatorisches Meldesystem

en: Tularaemia - mandatory reporting system

it: Tularemia - Sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires, les médecins et les hôpitaux ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

de: Die Daten basieren auf Informationen, die Laboratorien, Ärztinnen und Ärzte sowie Spitäler dem BAG im Rahmen der Meldepflicht übermittelt haben.

en: The data are based on information that laboratories, doctors and hospitals have submitted to the FOPH under the mandatory reporting requirement.

it: I dati si basano su informazioni comunicate dai laboratori, dai medici e dagli ospedali all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

fr: Données concernant la propagation et l’évolution temporelle es cas de tularémie en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Tularämie Infektionen Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu laborbestätigten Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of tularemia infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on  cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di tularemia in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

tularaemia-foph

display_name: tularaemia-foph

tularamie-bag

display_name: tularamie-bag

tularemia-ufsp

display_name: tularemia-ufsp

tularemie-ofsp

display_name: tularemie-ofsp

fr: Tularémie

de: Tularämie

en: Tularemia

it: Tularämie

heal

fr: Santé

en: Health

it: Salute


fr: SARS-CoV-2 (Covid-19) - monitorage des variants dans les eaux usées

de: SARS-CoV-2 (Covid-19) - Virusvarianten im Abwasser

en: SARS-CoV-2 (Covid-19) -  monitoring of variants in wastewater

it: SARS-CoV-2 (Covid-19) - monitoraggio delle varianti nelle acque reflue

fr: Les données se fondent sur les informations issues du monitorage des variants dans les eaux usées de la Suisse. Ce monitorage enregistre la répartition des variants celle du SARS-CoV-2 dans des échantillons des stations d’épuration des eaux usées (STEP) participantes depuis février 2021.

en: The data are based on information from the monitoring programme of variantes in wastewater of Switzerland. This monitoring programme has been recording the distribution of variants of SARS-CoV-2 since February 2021 in wastewater samples from participating wastewater treatment plants (WWTPs).

de: Die Daten basieren auf Informationen aus dem Variantenmonitoring im Abwasser der Schweiz . Dieses Monitoring erfasst seit Februar 2021 die Verteilung der Virusvarianten von SARS-CoV-2 in Abwasserproben der teilnehmenden Abwasserreinigungsanlagen (ARA).

it: I dati pubblicati di seguito si basano sulle informazioni ricavate dalmonitoraggio delle varianti nelle acque reflue della Svizzera. Questo monitoraggio registra la distribuzione delle varianti del SARS-CoV-2 dal febbraio 2021 nei campioni di acque reflue degli impianti di depurazione delle acque reflue (IDA) partecipanti.

fr: Covid-19 - Sentinella

de: Covid-19 - Sentinella

en: Covid-19 - sentinella

it: Covid-19 - Sentinella

fr: Les données se fondent sur les informations recueillies par le système Sentinella. Dans le cadre de ce système de déclaration, les médecins transmettent depuis mars 2020 des informations sur les premières consultations de patients présentant une infection respiratoire aiguë dans leur cabinet ou lors de visites à domicile.

de: Die Daten basieren auf Informationen aus dem Sentinella-Meldesystem. Im Rahmen dieses Meldesystems übermitteln ambulant tätige Ärztinnen und Ärzte seit März 2020 Informationen zu Erstkonsultationen von Patientinnen und Patienten mit akuter respiratorischer Infektion (ARI) in Arztpraxen und bei Hausbesuchen.

en: The data are based on information from the Swiss Sentinel Surveillance Network (SSSN, Sentinella) monitoring system. Since March 2020, the system has been used by doctors working on an outpatient basis to submit information on initial consultations in medical practices and during home visits for patients with acute respiratory infections (ARIs).

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Nel quadro di questo sistema di dichiarazione, dal marzo 2020 i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano un’infezione respiratoria acuta (acute respiratory infection, ARI).

fr: Covid-19 - surveillance génomique

en: Covid-19 - genomic surveillance

de: Covid-19 - Genomische Überwachung

it: Covid-19 - monitoraggio genomico

fr: Les données se fondent sur les informations tirées du Programme national de surveillance génomique du SARS-CoV-2, auquel participent, à l’heure actuelle, des laboratoires des hôpitaux universitaires et de grands hôpitaux régionaux de Suisse, ainsi qu’une plateforme de séquençage.

de: Die Daten basieren auf Informationen aus dem nationalen genomischen SARS-CoV-2 Überwachungsprogramm. An diesem beteiligen sich aktuell Laboratorien der Universitätsspitäler und grösserer Regionalspitäler der Schweiz sowie eine Sequenzierungsplattform.

en: The data are based on information from the national genomic SARS-CoV-2 surveillance programme. Currently participating in the programme are laboratories of the university hospitals and larger regional hospitals in Switzerland, as well as a sequencing platform.

it: I dati si basano sulle informazioni ricavate dal programma nazionale di sorveglianza genomica del SARS-CoV-2, al quale attualmente aderiscono i laboratori degli ospedali universitari e dei maggiori ospedali regionali della Svizzera, nonché una piattaforma di sequenziamento.

fr: Virus respiratoire - Sentinella

fr: Covid-19 - Système de déclaration obligatoire

en: Covid-19 - mandatory reporting system

de: Covid-19 - Obligatorisches Meldesystem

it: Covid-19 - Sistema di dichiarazione obbligatoria

de: Die Daten basieren auf Informationen aus dem nationalen Abwassermonitoring der Schweiz und des Fürstentums Liechtenstein. Dieses Monitoring erfasst seit Januar 2022 die Viruslast von SARS-CoV-2 und seit Juli 2023 die Viruslast von Influenza und RSV in Abwasserproben der teilnehmenden Abwasserreinigungsanlagen (ARA).

fr: Données concernant la propagation et l’évolution temporelle des infections au SARS-CoV-2 et des cas de COVID-19 en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur la charge virale dans les eaux usées provenant du monitorage correspondant, sur les consultations ambulatoires provenant du système de déclaration Sentinella, sur les variantes de virus provenant de la surveillance génomique et sur sur les cas, hospitalisations, décès et tests provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von SARS-CoV-2 Infektionen und Covid-19 Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zur Viruslast im Abwasser aus dem Abwassermonitoring, zu ambulanten Konsultationen aus dem Sentinella-Meldesystem, zu Virusvarianten aus der genomischen Überwachung und zu Fällen, Hospitalisationen, Todesfällen und Tests aus dem obligatorischen Meldesystem.

en: Data on the spread and development of SARS-CoV-2 infections and Covid-19 cases in Switzerland and the Principality of Liechtenstein. You will find data of the viral load in wastewater from the wastewater monitoring system, of outpatient consultations from the Sentinella reporting system, of virus variants from the genomic surveillance system and of cases, hospitalisations, deaths and tests from the obligatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale delle infezioni da SARS-CoV-2 e dei casi di COVID-19 in Svizzera e nel Principato del Liechtenstein. Qui trovate dati della carica virale nelle acque reflue basate sul sistema di monitoraggio delle acque reflue, dati delle consultazioni ambulatoriali basate sul sistema di dichiarazione Sentinella, dati delle varianti del virus basate sul sistema di sorveglianza genomica e dati di casi, ospedalizzazioni, decessi e test basate sul sistema di dichiarazione obbligatoria.

fr: SARS-CoV-2 (Covid-19)

de: SARS-CoV-2 (Covid-19)

en: SARS-CoV-2 (Covid-19)

it: SARS-CoV-2 (Covid-19)


borreliose

title_for_slug: borreliose

fr: Borréliose - Sentinella

de: Borreliose - Sentinella

en: Lyme disease - sentinella

it: Borreliosi - Sentinella

fr: Les données se fondent sur les informations recueillies par le système Sentinella. Depuis 2008, les médecins transmettent des informations sur les premières consultations de patients présentant une maladie de Lyme dans leur cabinet ou lors de visites à domicile.

de: Die Daten basieren auf Informationen aus dem Sentinella-Meldesystem. Seit 2008 übermitteln ambulante Ärztinnen und Ärzte Informationen über Erstkonsultationen in Arztpraxen bei Patientinnen und Patienten mit Lyme Borreliose.

en: The data are based on information from the Swiss Sentinel Surveillance Network (SSSN, Sentinella) monitoring system. Since 2008, outpatient doctors have been submitting information on initial consultations in medical practices for patients with Lyme Disease.

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Dal 2008, i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano una malattia di Lyme.

fr: Données concernant la propagation et l’évolution temporelle des cas de borréliose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés provenant du système de déclaration Sentinella.

en: Data on the spread and development of lyme disease infections and cases in Switzerland and the Principality of Liechtenstein. You will find data from the Sentinella reporting system.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Borreliose Virusinfektionen und Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten aus dem Sentinella-Meldesystem.

it: Dati della diffusione e dell’evoluzione temporale dei casi di borreliosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati basate sul sistema di dichiarazione Sentinella.

borreliose-bag

display_name: borreliose-bag

borreliosemaladie-de-lyme-ofsp

display_name: borreliosemaladie-de-lyme-ofsp

borreliosi-malattia-di-lyme-ufsp

display_name: borreliosi-malattia-di-lyme-ufsp

lyme-disease-foph

display_name: lyme-disease-foph

fr: Borréliose

de: Borreliose

en: Lyme disease

it: Borreliose

heal

de: Gesundheit

abteilung-uebertragbare-krankheiten

fr: Division Maladies transmissibles


fsme

title_for_slug: fsme

fr: FSME - Système de déclaration obligatoire

en: TBE - mandatory reporting system

de: FSME - Obligatorisches Meldesystem

it: FSME - Sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires, les médecins et les hôpitaux ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

de: Die Daten basieren auf Informationen, die Laboratorien, Ärztinnen und Ärzte sowie Spitäler dem BAG im Rahmen der Meldepflicht übermittelt haben.

en: The data are based on information that laboratories, doctors and hospitals have submitted to the FOPH under the mandatory reporting requirement.

it: I dati si basano su informazioni comunicate dai laboratori, dai medici e dagli ospedali all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

fr: Données concernant la propagation et l’évolution temporelle es cas de FSME en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

en: Data on the spread and development of TBE cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

de: Daten zur Verbreitung und zeitlichen Entwicklung von FSME Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

it: Dati della diffusione e dell’evoluzione temporale dei casi di FSME in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

fsme-bag

display_name: fsme-bag

fsme-meningo-encephalite-a-tiques-ofsp

display_name: fsme-meningo-encephalite-a-tiques-ofsp

tbe-foph

display_name: tbe-foph

fr: FSME

de: FSME

en: TBE

it: FSME

abteilung-uebertragbare-krankheiten

de: Abteilung Übertragbare Krankheiten

en: Communicable Diseases Division

it: Divisione Malattie trasmissibili

fr: Les maladies transmissibles constituent une menace pour la santé publique. La division les surveille, publie régulièrement des rapports sur la situation épidémiologique, définit des stratégies de prévention et de contrôle, et les met en œuvre.

en: Communicable diseases pose a risk to public health. The division monitors these diseases, publishing regular reports on the epidemiological situation, laying down and implementing prevention and control strategies.

de: Übertragbare Krankheiten gefährden die öffentliche Gesundheit. Die Abteilung überwacht diese Krankheiten, publiziert regelmässig Berichte zur epidemiologischen Situation, legt Präventions- und Kontrollstrategien fest und setzt sie um.

it: Le malattie trasmissibili mettono in pericolo la salute pubblica. La divisione Malattie trasmissibili le monitora, pubblica regolarmente rapporti sulla situazione epidemiologica, stabilisce strategie di prevenzione e di controllo e le attua.


campylobacteriose

title_for_slug: campylobacteriose

fr: Campylobactériose - système de déclaration obligatoire

de: Campylobacteriose - Obligatorisches Meldesystem

en: Campylobacteriosis - mandatory reporting system

it: Campilobatteriosi - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle es cas de campylobactériose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Campylobacteriose Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of campylobacteriosis infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di campilobatteriosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

campilobatteriosi-ufsp

display_name: campilobatteriosi-ufsp

campylobacteriose-bag

display_name: campylobacteriose-bag

campylobacteriose-ofsp

display_name: campylobacteriose-ofsp

campylobacteriosis-foph

display_name: campylobacteriosis-foph

fr: Campylobactériose

en: Campylobacteriosis

de: Campylobacteriose

it: Campilobatteriosi

heal

fr: Santé

en: Health

it: Salute


shigellose

title_for_slug: shigellose

fr: Shigellose - système de déclaration obligatoire

de: Shigellose - Obligatorisches Meldesystem

en: Shigellosis - mandatory reporting system

it: Shigellosi - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle es cas de shigellose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Shigellose Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of shigellosis infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di shigellosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

shigellose-bag

display_name: shigellose-bag

shigellose-ofsp

display_name: shigellose-ofsp

shigellosi-ufsp

display_name: shigellosi-ufsp

shigellosis-foph

display_name: shigellosis-foph

fr: Shigellose

de: Shigellose

en: Shigellosis

it: Shigellosi