en: lake-level-regulation hydrologic-and-hydrodynamic-modelling switzerland perialpine-lakes climate-change

en: Lake outflow scenarios CH2018

en: Lake outflow scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en: Lake characteristics

en: Lake characteristics: stage-area relation for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun, stage-discharge relations for the unregulated Lake Walen and semi-regulated Lake Brienz and, lake level management rules for the two regulated lakes Zurich and Thun.

en: Lake water level scenarios CH2018

en: Lake water level scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en:
The dataset "Lake_climate_change_scenarios_CH2018" provides simulation-based climate change impact scenarios for perialpine lakes in Switzerland. These transient future scenarios were produced by combining the hydrologic model PREVAH with the hydrodynamic model MIKE11 to simulate daily lake water level (Lake_water_level_scenarios_CH2018.xls) and outflow scenarios (Lake_outflow_scenarios_CH2018.xls) from 1981 to 2099, using the Swiss Climate Change Scenarios CH2018. The future scenarios contain a total of 39 model members for three Representative Concentration Pathways, RCP2.6 (concerted mitigation efforts), RCP4.5 (limited climate mitigation) and RCP8.5 (no climate mitigation measures). These scenarios result from the study titled "Lower summer lake levels in regulated perialpine lakes, caused by climate change," authored by Wechsler et al. in 2023.

The dataset emphasizes four specific Swiss lakes, each subject to different degrees of lake level management: an unregulated lake (Lake Walen), a semi-regulated lake (Lake Brienz), and two regulated lakes (Lake Zurich and Lake Thun).

In addition, the file (Lake_characteristics.xlsx) includes data used in the modeling process, encompassing the stage-area relation for the four lakes, stage-discharge relations for the unregulated and semi-regulated lakes, and lake level management rules for the two regulated lakes.

climate-change

display_name: climate-change

hydrologic-and-hydrodynamic-modelling

display_name: hydrologic-and-hydrodynamic-modelling

lake-level-regulation

display_name: lake-level-regulation

perialpine-lakes

display_name: perialpine-lakes

switzerland

display_name: switzerland

en: Lake climate change scenarios CH2018


maintainer: Irene Cordero

en: drought land-use pesticide soil-nutrients soil soil-biodiversity heatwave

state: active

type: dataset

en: All soil data

en: Soil physicochemical characteristics

format: XLS

en:
Soil chemical and biological properties of soils affected by 10 different perturbations related with global change, applied individually or in combination. Greenhouse experiment. Perturbations applied to intact soil cores (15 cm diameter, 15 cm deep) collected in an extensively managed grassland on the WSL grounds in June 2023.
This dataset contains all data on which the publication below was based:
"Fioratti Junod M, Gombeer S, Holmes J, Zimmerman S, Rillig M, Risch AC and Cordero I. Soil functionality declines under multiple superimposed global change perturbations. XXXX "
Please, cite this publication together with the citation of the datafile.
Database includes:
Pot_ID: pot or soil core identifier.
Batch: numeric, 1 or 2.
Enzyme_plate: numeric, from 1 to 6.
Number_of_perturbations: numeric, from 0 to 10.
N_addition: binary. Yes = 1, No = 0.
P_addition: binary. Yes = 1, No = 0.
Defoliation: binary. Yes = 1, No = 0.
Trampling: binary. Yes = 1, No = 0.
Insecticide: binary. Yes = 1, No = 0.
Fungicide: binary. Yes = 1, No = 0.
Herbicide: binary. Yes = 1, No = 0.
Antibiotic: binary. Yes = 1, No = 0.
Drought: binary. Yes = 1, No = 0.
Heat_wave: binary. Yes = 1, No = 0.
Treatment: character. Description of the treatment, 15 levels.
SWC: soil water content. Numeric, unitless.
Green_biomass: green plant biomass. Numeric, g.
Brown_biomass: brown or dead plant biomass. Numeric, g.
Biomass_cut: plant biomass cut during defoliation treatments. Numeric, g.
CO2_flux_light: net CO2 flux under ambient light. Numeric, mg CO2 m-2 h-1.
CO2_flux_dark: ecosystem respiration. Numeric, mg CO2 m-2 h-1.
S: organic matter stabilisation factor (tea bag index). Numeric, unitless.
k: organic matter decomposition rate (tea bag index). Numeric, unitless.
DOC: dissolved organic carbon, mg Kg-1 dry soil.
IC: inorganic carbon, mg Kg-1 dry soil.
Ammonium_KCl: plant available ammonium, mg Kg-1 dry soil.
Nitrate_KCl: plant available nitrate, mg Kg-1 dry soil.
Phosphate: phosphate, mg Kg-1 dry soil.
MBC: microbial biomass carbon, mg Kg-1 dry soil.
MBN: microbial biomass nitrogen, mg Kg-1 dry soil.
PHO: phosphatase activity, nmol h-1 g-1 dry soil.
BG: β-glucosidase, nmol h-1 g-1 dry soil.
XYL: xylosidase, nmol h-1 g-1 dry soil.
CBH: cellobiohydrolase, nmol h-1 g-1 dry soil.
NAG: N-acetylglucosaminidase, nmol h-1 g-1 dry soil.
LAP: leucine aminopeptidase, nmol h-1 g-1 dry soil.
POX: phenoloxidase, nmol h-1 g-1 dry soil.
PER: peroxidase, nmol h-1 g-1 dry soil.
pH: soil pH, unitless
Water_stable_aggregates: water stable aggregates, %
Surface_infiltration_time: water surface infiltration time, s.

drought

display_name: drought

heatwave

display_name: heatwave

land-use

display_name: land-use

pesticide

display_name: pesticide

soil

display_name: soil

soil-biodiversity

display_name: soil-biodiversity

soil-nutrients

display_name: soil-nutrients

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

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: Escalating effects of multiple perturbations on soil functionality


maintainer: EnviDat Support

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

en: Read-me

media_type: text/plain

en: A short description of the data contained in the zipped-file. Recommended for reading before downloading the dataset.

format: TXT

mimetype: text/plain

en: Data files and read-me

media_type: application/zip

en: raw data and micro-CT data available from contacts

format: ZIP

mimetype: application/zip

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

advection

display_name: advection

metamorphism

display_name: metamorphism

snow

display_name: snow

stable-water-isotope

display_name: stable-water-isotope

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


maintainer: Frank Techel

en: avalanche-forecasting avalanche-danger-level avalanche-forecast avalanche-bulletin verification

en: D_QC for forecasting seasons 2020/2021 - 2022/2023.

en: D_QC for forecasting seasons 2001/2002 until 2019/2020.

en: Data for the 2023/2024 forecasting season. It was added on 26 Aug 2024 by F. Techel.

en:
The data set contains the re-analyzed (or quality-checked) regional avalanche danger levels (D_QC) for Switzerland.

D_QC relates to dry-snow avalanche conditions only. Measuring the avalanche danger level D is not possible; forecast, nowcast, and hindcast assessments of D are judgments by humans interpreting data. However, combining several pieces of information indicating the same D, it can be expected that it is more likely that D_QC represents the avalanche conditions well.

For the **forecasting seasons 2001/2002 until 2019/2020**, the approach to obtain D_QC is described in detail in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

For the **forecasting seasons 2020/2021 and later**, D_QC is derived using the following approach:
1. *Combination of forecast (D_forecast) and nowcast (D_nowcast)*: If there was only one assessment available by an observer after a day in the field for a region, and if D_forecast = D_nowcast --> D_QC = D_forecast.
2. *Combination of several nowcast assessments (D_nowcast)*: If two (or more) observers agreed (or majority opinion) in their (independent) assessments of D_nowcast after a day in the field in the same warning region. --> D_QC = D_nowcast.
3. *Hindcast analysis (D_hindcast)*: In Switzerland, avalanche forecasters re-evaluate all situations when D = 4 (high) or D = 5 (very high) were either forecast, should have been forecast, or when forecasters discussed given one of these two levels but had not given them. Generally, two forecasters assess each situation. In these cases, D_QC = D_hindcast. The hindcast analysis, only available since the forecasting season 2020/2021, replaces what was step (2) in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

All other cases - ties in case of (1) or (2), no new information from the warning region in question, or if no D_hindcast was available - are not considered quality-checked, and are, thus, not contained in the data set.

In addition to D_QC, the file contains information on the elevation and aspect, where D_QC likely prevails.
- The indicated elevation is the mean of the respective elevations in (1), (2), or (3). At danger level 1 (low), when no elevation is indicated in the Swiss forecast, a value of 1500 m is set.
- For the four cardinal aspects N, E, S, and W, a value of 1 means that there was agreement that D was reached in this aspect and a value of 0 means that there was agreement that D was not reached in this aspect. Intermediate values correspondingly mark disagreements in the assessments.

avalanche-bulletin

display_name: avalanche-bulletin

avalanche-danger-level

display_name: avalanche-danger-level

avalanche-forecast

display_name: avalanche-forecast

avalanche-forecasting

display_name: avalanche-forecasting

verification

display_name: verification

en: Re-analyzed regional avalanche danger levels in Switzerland


maintainer: Anita C. Risch

en: weed-management herbivory non-native-plant native-plant grassland

en: Data file native and non-native plant interactions in Australian grasslands

en:
taxa tab:	list and overview of all the recorded species

* family:                 family of the plant

* genus:                genus of the plant

* species:                plant species name

* origin:                indicates whether the plant is native to Australia or not (non-native)

* common name:	        common name of the plant species

* functional group:	        functional group of the plant species: forb, graminoid, fern, tree

* functional group detailed:	gives more detail about the type of graminoid and forb: legume, forb (non-leguminous),
                        grass, sedge, rush, fern, tree

* lifeform:                annual or perennial lifeform (species which can have both of these lifeforms where
                        considered as annuals)

plot tab:	list of species found in each plot and their cover (%)

* sampling.session:        provides information about the sampling time:
                        May2020 = data that was collected in May 2020
                        Nov2020 = data that was collected in November 2020

* farm.name:	            name of the farms where the sampling took place:
                        SF = farm of the Southern group
                        NF = farm of the Northern group
                        numbers 1-3 = randomly allocated to the Southern group of farms
                        numbers 4-6 = randomly allocated to the Northern group of farms

* site.type:	                KG: Kangaroo grass dominated site
                        ALG: ALG+KG site (Kangarooo grass and African lovegrass co-dominated site)

* plot.no:                plot number: 9-12

* scientific.name:	        scientific name of the plant species found in a certain plot

* functional group:	        indicates whether the species found is a tree, forb, graminoid or fern

* functional group detailed:	indicates whether the species found is a tree, legume, forb (non-leguminous),
                        grass, sedge, rush, fern

* lifeform:                specifies the lifeform of the species: annual or perennial lifeform
                        (species which can have both of these lifeforms where considered as annuals)

en:
This dataset contains all data, on which the following publication below is based.

Paper Citation:

_Schlierenzauer, C., Risch, A.C., Schütz, M., Firn, J. 2021. Non-native Eragrostis curvula reduces plant species diversity in pastures of South-eastern Australia even when native Themeda triandra remains co-dominant. Plants 10, 596._

Please cite this paper together with the citation for the datafile.

Study area
The study was conducted in the lowland grassy woodlands of the Bega Valley Region, which is located in the south-east corner of New South Wales, Australia. Embedded between the Pacific Ocean and the Australian Alps, the lowland grassy woodlands are mostly located on granitic substrates and reach elevations of roughly 500 m above sea level. Typically, these grassy woodlands receive less precipitation (mean annual precipitation between 700-1100 mm) compared to the more elevated areas that surround them (NSW Government - Office of Environment and Heritage 2017).
The vegetation is dominated by an open tree canopy layer consisting of Eucalyptus tereticornis Sm, Angophora floribunda Sm. (Sweet) and a range of other eucalypt species. Sometimes shrub or small trees are also present, whereas grasses and forbs form the ground-cover. In areas without intensive agricultural history, this layer is dominated by perennial, tussock grasses such as Themeda triandra Forssk, Microlaena stipoides R.Br (Weeping Grass), Eragrostis leptostachya Steud. (Paddock Lovegrass) and Echinopogon ovatus P.Beauv (Forest Hedgehog Grass). The remaining inter-tussock spaces are occupied by a diversity of growth-restricted grasses and herbaceous forbs (NSW - Department of Planing, Industries and Environment 2019; NSW Government - Office of Environment and Heritage 2017).
Clearing, pasture sowing, fertilizer application and livestock grazing resulted in a dramatic decrease in the extent of these natural woodlands, with less than five percent within conservation reserves and overall, with only about 20% of their original extent in New South Wales still existing (Tozer et al. 2010). The remaining areas outside of reserves are threatened by altered fire frequencies, habitat clearing, livestock grazing and especially by non-native plant invasion, particularly Eragrostis curvula (Schrad.) Nees. For this reason, the grassy woodlands are listed as an endangered ecological community in the NSW state legislation. Additionally, they are considered as critically endangered by the Commonwealth of Australia (Threatened Species Scientific Committee (TSSC) 2013).

Experimental design and sampling
The study was conducted on six farms and in each of them two sites were chosen, representing a paired design. One of the sites at each farm is dominated by native Themeda triandra, the other one co-dominated by non-native Eragrostis curvula and Themeda triandra. All farms are within a radius of approximately 10 km from the town Candelo. Three of the farms are located North (36°40’ to 36°42’ S and 149°38’ to 149°42’ E) and three of them are located South (36°51’ to 36°49’ S and 149°38’ to 149°42’ E) of Candelo.
Non-native herbivores (mainly cattle, sheep and rabbits) and native herbivorous marsupials (mainly kangaroos, wallabies and wombats) are present in the area of these sites. On each site, data was collected within four plots (each 1 x 1 m) in May and November 2020. All plant species found within a plot were recorded and their relative abundance was estimated.

References
NSW - Department of Planing, Industries and Environment. 2019. “Lowland Grassy Woodland in the South East Corner Bioregion - Endangered Ecological Community Listing.” https://www.environment.nsw.gov.au/topics/animals-and-plants/threatened-species/nsw-threatened-species-scientific-committee/determinations/final-determinations/2004-2007/lowland-grassy-woodland-south-east-corner-bioregion-endangered-ecological-community-l (February 18, 2021).
NSW Government - Office of Environment and Heritage. 2017. “Lowland Grassy Woodland in the South East Corner Bioregion - Profile.” https://www.environment.nsw.gov.au/threatenedSpeciesApp/profile.aspx?id=20070 (January 31, 2021).
Threatened Species Scientific Committee (TSSC). 2013. Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) Conservation Advice for Lowland Grassy Woodland in the South East Corner Bioregion. http://www.environment.gov.au/biodiversity/threatened/communities/pubs/82-conservation-advice.pdf.
Tozer, Mark et al. 2010. “Native Vegetation of Southeast NSW: A Revised Classification and Map for the Coast and Eastern Tablelands.” Cunninghamia : a journal of plant ecology for eastern Australia 11(3): 359–406.

grassland

display_name: grassland

herbivory

display_name: herbivory

native-plant

display_name: native-plant

non-native-plant

display_name: non-native-plant

weed-management

display_name: weed-management

educ

en: Education, culture and sport

en: Native and no-native plant interactions in Australian grasslands


maintainer: Franziska Gerber

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

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

mimetype: application/x-zip-compressed

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

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

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

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, submitted.

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

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: Reproducibility dataset for CRYOWRF validation


wind-crust-formation-snowmicropen-data

title_for_slug: wind-crust-formation-snowmicropen-data

en: snow snowmicropen wind-crust wind-packing smp

en: Processing scripts

en: Contains the R-scripts used to process the SMPs

en: SMP data

en: README

en: Describes the dataset in detail

en:
This dataset contains the SnowMicroPen (SMP) data from 38 wind tunnel experiments on wind-packing / wind crust formation. These experiments were performed in the winters 2015/16 and 2016/17 and include more than 1000 SMP measurements.

The SMPs are organized per experiment. Each experiment subfolder contains the processed SMP profiles and some additional files.

Please refer to the README for more details on the data. The processing scripts are available for download as well. The scripts are mainly provided as documentation and would need to be adjusted to be used.

This dataset is the basis of the following publication:

Sommer C.G., Lehning M., & Fierz C. (2017). Wind tunnel experiments: Saltation is necessary for wind-packing. Journal of Glaciology, 63(242), 950-958. doi:10.1017/jog.2017.53

smp

display_name: smp

snow

display_name: snow

snowmicropen

display_name: snowmicropen

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

en: Wind crust formation: SnowMicroPen data


maintainer: Irmi Seidl

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

en: Raw data (.csv)

media_type: text/csv

en: Raw data in csv. format. For comprehension of the data and variable structure, please consult the codebook and the modified questionnaire with variable names.

format: CSV

mimetype: text/csv

en: Questionnaire with variable names

media_type: application/pdf

en: Modified questionnaire with variable names for each item. Should be used together with the data files (.csv or .sav) to reconstruct the data and variable structures.

format: PDF

mimetype: application/pdf

en: Raw date (SPSS)

en: Raw data in sav. format (SPSS). For comprehension of the data and variable structure, please consult the modified questionnaire with variable names.

format: SERVICE

en: Codebook

en: Description of variable attributes and valid n

en:
 Topic of Survey
The data at hand on energy cooperatives in Switzerland were collected in 2016 as part of the project "Collective financing of renewable energy projects in Switzerland and Germany" of the National Research Programme 71 "Managing Energy Consumption". The cooperatives were surveyed on their organizational structure, their activities in electricity and heat generation, their finances, the political context and their assessments of the future.

 Survey Method
The survey was targeted at all energy cooperatives in Switzerland (this is the basic population). The Swiss Commercial Register was searched for cooperatives and specific keywords in order to determine this basic population and collect addresses. This search in May 2016 resulted in a total of 304 energy cooperatives, to which a questionnaire was sent in July 2016. A pre-test with 8 persons had been carried out before the questionnaire was sent out. The questionnaire was provided in German and French. It was sent by mail and an attached letter referred to a link for the digital version if preferred. The online version was designed with the software "Sawtooth". After three weeks, a first, and after six weeks a second reminder letter was sent to those cooperatives that had not yet completed the questionnaire. The returned hardcopy questionnaires were manually entered into the database and then combined with the electronic data from the online survey. In the course of the survey, the total population was reduced from 304 to 289: in 4 cases the survey was not deliverable, 4 cooperatives had dissolved, 6 were not actually energy cooperatives, 1 case had recently changed its legal form. With a response rate of 47%, the final data set comprises 136 responses (from 77 digital and 59 hardcopy questionnaires). However, not all 136 of the returned questionnaires were filled out completely. We checked for answers that seemed contradictory or incomprehensible. If an error could be clearly identified and the correct answer derived, the answer was adjusted, otherwise the answer was replaced by "missing data".

 Anonymization
Participating cooperatives have been assured that their information will be kept confidential and will only be made public anonymously. For this reason, the data have been anonymized in in order to prevent any identification of individual cooperatives.

 How to Use the Data
* The data are available in CSV and SPSS (sav.) format.
* A codebook and a modified version of the used questionnaire are provided to illustrate the data and variable structure. In the questionnaire, the variable names are assigned to the corresponding questions. In the codebook, further information on these variables (valid n, answer categories) can be found. This information (of the codebook) is already integrated in the SPSS file.

 Current Embargo on Data
These data are currently under embargo and will only be released when the project is completed (not before 2020).

#Additional Information
* The used questionnaire is provided in German and French.
* Descriptive results of the survey were published in a WSL report: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:18943

community-energy

display_name: community-energy

cooperatives

display_name: cooperatives

energy-cooperatives

display_name: energy-cooperatives

renewable-energy

display_name: renewable-energy

switzerland

display_name: switzerland

educ

en: Education, culture and sport

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


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

en: DATA ACCESS

en:
Meteo data at Gemsstock [Level 2 dataset](http://models.slf.ch/p/dataset-processing/).

fields      = timestamp TSS HS VW DW VW_MAX OSWR ISWR ILWR RECORD AUX_VOLTAGE LOGGER_VOLTAGE LW_SENSOR_TEMP VENTILATION_FLAG OLWR

en:
Meteorological station at Gemstock (3021 m asl) in Canton Uri. The station includes in/out LW/SW and a snow height sensor.

Data from this station is managed by the permos.ch project. More information: https://www.permos.ch/permafrost-monitoring/field-sites

gemstock

display_name: gemstock

longwave-radiation

display_name: longwave-radiation

meteo-station

display_name: meteo-station

shortwave-radiation

display_name: shortwave-radiation

snow-height

display_name: snow-height

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


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

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

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

climate-change

display_name: climate-change

hazard

display_name: hazard

new-snow

display_name: new-snow

ramms

display_name: ramms

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


en: sdms urbanization birds arthropods species-richness-models snails insects diversity urban-ecology spiders species-abundance-distributions

en: abundance and occurrence data of the 1446 species studied, used to investigate species-abundance distributions and species-occurrence distributions

en: contains the raw data to perform the species richness models of all species

en: contains the raw data to perform species distribution models, only for common species

en: contains the raw data to perform the species richness models of the rare species

en: contains the raw data to perform the species richness models of the hypercommon species

en:
Richness, site occurrence and abundance data of bees, beetles, birds, hoverflies, net-wingeds, true bugs, snails, spiders, milipides, wasps collected in the city of Zurich using different sampling techniques, and the environmental variables for each sampling site.
Data are provided on request to contact person against bilateral agreement.

arthropods

display_name: arthropods

birds

display_name: birds

diversity

display_name: diversity

insects

display_name: insects

sdms

display_name: sdms

snails

display_name: snails

species-abundance-distributions

display_name: species-abundance-distributions

species-richness-models

display_name: species-richness-models

spiders

display_name: spiders

urban-ecology

display_name: urban-ecology

urbanization

display_name: urbanization

en: Ecological properties of urban ecosystems. Biodiversity dataset of Zurich


maintainer: Marcus Schaub

en: tree drought dbh diameter-at-breast-height forest scots-pine crown-condition swiss-forest-lab irrigation tree-species lwf

en: Dataset

en: Long-term Irrigation	Experiment Pfynwald homepage

media_type: text/html

format: HTML

mimetype: text/html

en: Site photo 1

en: Site photo 2

en: Shapefile	of measurement location

en: Swiss Forest Health Inventory

en: Site photo 3

en: To study the performance of mature Scots pine (_Pinus sylvestris_ L.) under chronic drought conditions in comparison to their immediate physiological response to drought release, a controlled long-term and large-scale irrigation experiment has been set up in 2003. The experiment is located in a xeric mature Scots pine forest in the Pfynwald (46° 18' N, 7° 36' E, 615 m a.s.l.) in one of the driest inner-Alpine valleys of the European Alps, the Valais (mean annual temperature: 9.2°C, annual precipitation sum: 657 mm, both 1961-1990). Tree age is on average 100 years, the top height is 10.8 m and the stand density is 730 stems ha-1 with a basal area of 27.3 m2 ha-1. The forest is described as _Erico Pinetum sylvestris_ and the soil is a shallow pararendzina characterized by low water retention. The experimental site (1.2 ha; 800 trees) is split up into eight plots of 1'000 m2 each. During April-October, irrigation is applied on four randomly selected plots with sprinklers of 1 m height at night using water from an adjacent water channel. The amount of irrigation corresponds to a supplementary rainfall of 700 mm year-1. Trees in the other four plots grow under naturally dry conditions. Soil moisture has been monitored since the beginning of the project at 3 soil depths (10, 20 and 60 cm). The crown condition of each tree is being assessed each year since 2003. Tree measurement data such as diameter at breast height, tree height, and social status were assessed in 2002, 2009 and 2014. The duration of the irrigation experiment is planned for 20 years.

crown-condition

display_name: crown-condition

dbh

display_name: dbh

diameter-at-breast-height

display_name: diameter-at-breast-height

drought

display_name: drought

forest

display_name: forest

irrigation

display_name: irrigation

lwf

display_name: lwf

scots-pine

display_name: scots-pine

swiss-forest-lab

display_name: swiss-forest-lab

tree

display_name: tree

tree-species

display_name: tree-species

educ

en: Education, culture and sport

en: Tree measurements 2002-2016 from the long-term irrigation experiment Pfynwald, Switzerland


maintainer: Giulia Francesca Azzurra Donati

en: integrated-modelling human-dominated-landscapes ecological-corridors biodiversity circuit-theory urban-spatial-planning

en: Amphibian breeding sites of national importance - cantons of Aargau and Zürich

en: Amphibian breeding sites of national importance (focal nodes) in the cantons of Aargau and Zürich, 30x30 m resolution, binarised ascii format.

en: Binarized "green" and "grey" landcover data (Cantons of Aargau and Zürich)

en: "Green" landcover refers to lawns and vegetated urban surfaces such as, for example private gardens, public parks, cemeteries, green stripes along roadsides, etc. While "grey" landcover refers to impervious grounds such as roads, troittoirs, other impervious. Binarized maps, 30x30m resolution.

en: Amphibian monitoring data

en: Processed amphibian occurrence data (2017-2019) in the cantons of Aargau and Zürich. The dataset includes information for the following species: _Alytes obstetricans_,_Bombina variegata_, _Bufo bufo_, _Hyla arborea_, _Ichtyosaura alpestris_, _Lissotriton helveticus_, _Lissotriton vulgaris_, _Rana temporaria_, _Salamandra salamandra_, and _Triturus cristatus_.

en: Amphibian species specific landscape resistance maps.

en: For each amphibian species we used the weighted average Ensemble model suitability map and converted it to a resistance map using an exponential decay function following (Duflot et al., 2018) using the species-specific mpa threshold previously computed (Preau et al., 2020). The function assigns a resistance value of 1,000 when habitat suitability equals zero, and a value of one when habitat suitability is greater than or equal to the binarization threshold. The exponential shape strengthens the barrier effect of less favorable areas.

en: Amphibian whole life cycle predictors - 10m resolution

en:
Amphibian whole life cycle predictors include 6 variable types:
(1)	Topographic – slope [°]: derived from the Swiss Topographical Landscape model (swissTLM 3D 2015) at 2 m resolution (elevation uncertainty ± 0.5m) and, subsequently, aggregated to a median value;
(2)	Hydrologic: two predictors including nearest distance to water [m] (all water-related objects and rasterized lotic, lentic and reedbeds from the regional cadastral maps – AV: Daten der Amtliche Vermessung) and runoff coefficient [C] (between 0 and 1 relating amount of runoff to amount of precipitation, mapped AV: Daten der Amtliche Vermessung data against literature values for different land covers);
(3)	Edaphic – soil moisture variability (not available): can gathered from the spatial modelling of Ecological Indicator Values in Switzerland (Descombes et al., 2020) and resampled from 100m to 10m;
(4)	Vegetation: we calculated the median and standard deviation of the Normalized Difference Vegetation Index (NDVI) from all available cloud free Sentinel-2 pixels available between April and October for the years 2016 to 2019 (Drusch et al., 2012) and the median vegetation height [m] (not available) can gathered from Ginzler and Hobi (2015);
(5)	Land-use derived: includes three predictors, grassland density [grassland/cell] (not available) - can be gathered from Pazur et al. (2021), total grasslands area evaluated using a spatial weight matrix and a 250m neighborhood radius around each cell; urbanization [buildings/cell] – average building density for a 250m neighborhood around each cell based on the AV: Daten der Amtliche Vermessung ; and traffic intensity [vehicles/day] – average daily vehicle count (Nationales Personenverkehrsmodells);
(6)	Movement-ecology related: includes three predictors of proximity – nearest forest distance [m]; nearest rock-gravel and sandy area (RGS) distance [m] and nearest road distance [m] (considering any road type) – all calculated based on the AV: Daten der Amtliche Vermessung maps.

en: The data includes (1) amphibian occurrence data (2017-2019) for ten species across the cantons of Aargau and Zürich gathered from the Coordination Center for the Protection of Amphibians and Reptiles of Switzerland (http://www.karch.ch), (2) amphibian whole-life cycle environmental predictors (i.e. topographic, hydrologic, edaphic, vegetation, land-use derived, movement-ecology related), and (3) local urban "green" and "grey" landcover data which can be used to identify opportunities for Blue-Green Infrastructure (through green or grey transitions) in support of regional landscape connectivity.

biodiversity

display_name: biodiversity

circuit-theory

display_name: circuit-theory

ecological-corridors

display_name: ecological-corridors

human-dominated-landscapes

display_name: human-dominated-landscapes

integrated-modelling

display_name: integrated-modelling

urban-spatial-planning

display_name: urban-spatial-planning

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: Amphibian and urban-rural landscape data Swiss Lowlands


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

en: Data processing documentation

en: Post Processed TLS's

en: Compressed dat files

en:
This dataset comprises of a post-processed set of terrestrial laser scans (TLS’s) of Antarctic sea ice obtained during the Sea Ice Physics and Ecosystem Experiment-2 (SIPEX-2, http://seaice.acecrc.org.au/sipex2012/) in September-November 2012. The post-processing steps include the registration of the individual scans into a single 3-dimensional point cloud, the removal of unwanted noise caused by particles in the air (i.e., snow crystals), and the final generation of surface grids based on the cleaned individual point returns. The final product includes the ‘xyz’ coordinates of the individual point measurements, and gridded surfaces covering study areas of 100m x 100 m, and at resolutions of 0.01 m, 0.1 m, 0.25 m, 0.5 m and 1 m for each of the survey dates. Additionally, subgrid statistics that include the mean elevation, standard deviation, minimum and maximum elevations, range, and number of point returns in each gridcell are generated. The final product is provided in space-delimited text files, with the surface grids provided in Digital Terrain Model (DTM) format ready for visualization in any GIS software.

How to cite:
Please also cite the original publication when using this data set.: Trujillo, E., K. Leonard, T. Maksym, and M. Lehning (2016), Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice, J. Geophys. Res. Earth Surf., 121, doi:[10.1002/2016JF003893](https://dx.doi.org/10.1002/2016JF003893).

polar

display_name: polar

sea-ice

display_name: sea-ice

sea-ice-elevation

display_name: sea-ice-elevation

terrestrial-laser-scans

display_name: terrestrial-laser-scans

tls

display_name: tls

educ

en: Education, culture and sport

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


root-traits

maintainer: Ivano Brunner

title_for_slug: root-traits

en: ingrowth-cores drought soil-coring belowground-biomass fine-root-traits

en: Root-traits

en:
Fine-root traits of Scots pine in response to enhanced soil water availability deriving from long-term irrigation in the Pfynwald

Data_Fig.1.xlsx
Fine-root biomass of the topsoil (0-10 cm) in the dry and irrigated treatment of the Scots pine forest of the years 2003 to 2016 recorded by soil coring

Data_Tab1+2_2005.xlsx
Fine-root traits from roots of ingrowth cores from 2005 after two years of growth in the dry and irrigated treatment of the Scots pine forest

Data_Tab1+2_2016.xlsx
Fine-root traits from roots of ingrowth cores from 2016 after two years of growth, and from roots of the soil-coring sampling from 2016 in the dry and irrigated treatment of the Scots pine forest

belowground-biomass

display_name: belowground-biomass

drought

display_name: drought

fine-root-traits

display_name: fine-root-traits

ingrowth-cores

display_name: ingrowth-cores

soil-coring

display_name: soil-coring


en: gis buffer jupyter density geospatial roads

en: Plots

en: Random plot locations

en: Road Density Calculation (Python Notebook) online

en: Road data from OSM for the surroundings of Menzberg, Switzerland

en:
This dataset contains the road and plot data used for the geospatial analysis example showcased in "Fostering Open Science at WSL with the EnviDat Environmental Data Portal", a contribution to the 5th Open Source Geospatial Research and Education Symposium (OGRS), 2018.
The example uses Jupyter Notebook to calculate road densities in the neighbourhood of sample plot locations with Python. Road data were extracted from OpenStreetMap, while the point data (sample plots) were generated manually.

buffer

display_name: buffer

density

display_name: density

geospatial

display_name: geospatial

gis

display_name: gis

jupyter

display_name: jupyter

roads

display_name: roads

en: Dataset for OGRS 2018 publication


maintainer: Elisabeth Hafner

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

en: AvalancheReliabilityData

en: The .zip contains all data used to conduct the reliability study as well as the results, a detailed description of the included files is contained in the included pdf. All geospatial data is provided in the Swiss Coordinate System: CH1903+ / LV95 (EPSG 2056). For any use of the data the proper citation provided is obligatory!

en:
This dataset contains the data used and collected to investigate the reliability of avalanche size estimates and avalanche outlines (see related publications). Namely this is

 Avalanche size estimates

* the 10 pictures depicting avalanches
* the survey results from the 170 participants

 Avalanche outlines mapped from oblique photographs
* the pictures of the six avalanches
* the avalanche outlines mapped by the 10 participants
* the reference mapped from the georeferenced photographs

 Avalanche outlines from remotely-sensed imagery
* the orthophotos in the four different resolutions (2m, 1m, 50cm, 25cm)
* the area of interest (AoI) delimiting the research area
* the avalanche mappings in each resolution for all five participants
* the shade masks used to separate illuminated and shaded areas

The acquisition of the orthophotos has been partially supported by the Swiss National Science Foundation (SNF; Grant N°200021_172800).

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

avalanche-size-estimation

display_name: avalanche-size-estimation

reliability

display_name: reliability

remote-sensing

display_name: remote-sensing

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: Data reliability study: avalanche size estimates and outlines


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

en: Dataset

en:
The data presented here corresponds to the publication "A Close-Ridge Small-Scale Atmospheric Flow Field and its Influence on Snow Accumulation" (Gerber et al., 2017), which investigates an eddy-like structure in the vicinity of the Sattelhorn in the Dischma valley (Davos Switzerland) and its influence on snow accumulation. The dataset contains:

* Alpine3D: Alpine3D snow depth grids (25 m resolution) for two simulations with and without snow redistribution.
* ARPS: 10 ARPS simulations (25 m horizontal resolution) with different model setups (wind direction, wind speed, stability).
* LiDAR: Processed LiDAR PPI (D2_PPI_1h) and RHI (D2_cross_1h) across the valley with a hourly resolution for the period 27 October 2015 01:00 - 29 October 2015c 21:00 (spatial resolution: 25 m).
* meteostations-dischma: Meteorological station data of two meteorological stations in the Dischma valley with 10 minute resolution for the period 28 October 2015 - 30 October 2015.
* TLS: Snow depth change data (m) between 28 October 2015 and 30 October 2015 based on terrestrial laser scans.

For more details about the simulation and observation data, see Gerber et al., 2017.

Publication: Gerber et al., 2017: A Close-Ridge Small-Scale Atmospheric Flow Field and its Influence on Snow Accumulation, submitted to JGR - Atmospheres.

lee-side-flow-field

display_name: lee-side-flow-field

lidar

display_name: lidar

preferential-deposition

display_name: preferential-deposition

tls

display_name: tls

educ

en: Education, culture and sport

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


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

en: Site photo of the forest station (LEB)

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

mimetype: image/jpeg

en: Data plot of the forest station (LEB)

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

en: Forest station data (LEB)

en: Data file.

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 one meteorological station in Lens in Switzerland which is located within a natural coniferous forest with Scots pine (_Pinus sylvestris_; 150-170 yrs)) as dominant tree species. The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lens 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: Lens, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: Sektion energieeffizienter Verkehr

title_for_slug: Kennzahlen alternativ angetriebene LNF

de: ogd93-bfe elektromobilitat leichte-nutzfahrzeuge alternative-antriebe lieferwagen elektrische-fahrzeuge hybridfahrzeuge co2

fr: Chiffres clés des véhicules utilitaires légers neufs à propulsion alternative (VUL)

de: Kennzahlen alternativ angetriebene LNF

en: Key figures for alternatively powered LCVs

it: Indicatori VCL a propulsione alternativa

author: Bundesamt für Energie BFE

de: Storymap

fr: Modèles de VUL entièrement électriques (modèles BEV) les plus prisés

de: Beliebteste vollelektrische LNF-Modelle (BEV)

en: Most popular all-electric LCV models (BEV)

it: VCL completamente elettrici più diffusi (modelli BEV)

fr:
L’Office fédéral de l’énergie évalue depuis 2020 les modèles de VUL entièrement électriques (modèles BEV) les plus prisés. Pour l’année 2020, des chiffres trimestriels sont disponibles; à partir de 2021, les valeurs sont disponibles à un rythme mensuel.

La numérotation des cantons est celle de l’OFS.

en:
The Swiss Federal Office of Energy has since 2020 ranked the most popular all-electric LCV models (BEV). Quarterly figures are provided for 2020; from 2021 on, the values are available on a monthly basis.

Numbering of cantons according to FSO

de:
Das Bundesamt für Energie wertet seit 2020 bei den LNF die beliebtesten, vollelektrischen Modellen (BEV) aus. Für das Jahr 2020 sind Quartalszahlen bereitgestellt, ab 2021 sind die Werte in monatlicher Auflösung verfügbar.

Nummerierung der Kantone gemäss BFS

it:
Dal 2020 l'Ufficio federale dell'energia analizza i modelli di VCL completamente elettrici più diffusi. Per il 2020 vengono forniti dati trimestrali, mentre dal 2021 in poi i valori sono disponibili con risoluzione mensile.

Numerazione dei Cantoni secondo UST.

fr: Chiffres clés des VUL à propulsion alternative

fr:
Sur la base des données anonymisées des nouvelles immatriculations publiées par l’OFROU, l’Office fédéral de l’énergie évalue depuis 2020 des chiffres clés importants concernant les voitures de livraison et tracteurs à sellette légers à propulsion alternative (véhicules utilitaires légers, VUL). Sont réputés véhicules à propulsion alternative les véhicules ne disposant pas exclusivement d’un moteur à combustion à essence ou à diesel. Ce jeu de données comprend, outre les statistiques annuelles agrégées, les chiffres trimestriels et mensuels des parts de marché ainsi que des indications sur les différents cantons.

Légende: t1 = émissions moyennes de CO2, t2 = part BEV, t3 = part PHEV essence, t4 = part PHEV diesel, t5 = part hybride essence, t6 = part hybride diesel, t7 = part gaz naturel, t8 = part nouvelles immatriculations, t10 = part hydrogène

La numérotation des cantons est celle de l’OFS.

en:
On the basis of the anonymised data for new registrations published by FEDRO, the Swiss Federal Office of Energy has evaluated since 2020 the key figures for alternatively powered vans and light articulated vehicles (collectively: light commercial vehicles, LCVs). Vehicles are considered to be alternatively powered if they do not have an exclusively petrol or diesel-driven internal combustion engine. In addition to aggregated annual key figures, this data set also contains quarterly and monthly market share figures as well as information regarding the individual cantons.

Key: t1 = CO2 average, t2 = Share of BEVs, t3 = Share of petrol PHEVs, t4 = Share of diesel PHEVs, t5 = Share of hybrid petrol, t6 = Share of hybrid diesel, t7 = Share of natural gas, t8 = Number of new registrations, t10 = Share of hydrogen

Numbering of cantons according to FSO

de:
Auf Basis der vom ASTRA publizierten, anonymisierten Neuzulassungsdaten wertet das Bundesamt für Energie ab 2020 wichtige Kennzahlen zu den alternativ angetriebenen Lieferwagen und leichten Sattelschlepper (Sammelbegriff: leichte Nutzfahrzeuge, LNF) aus. Als alternativ angetrieben gelten Fahrzeuge, bei denen nicht ausschliesslich ein Benzin- oder Diesel-Verbrennungsmotor eingebaut ist. Dieser Datensatz enthält neben aggregierten jährlichen Kennzahlen auch Quartals- und Monatszahlen der Marktanteile sowie Angaben zu den einzelnen Kantonen.

Legende: t1 = CO2 Durchschnitt, t2 = Anteil BEV, t3 = Anteil Benzin PHEV, t4 = Anteil Diesel PHEV, t5 = Anteil Hybrid Benzin, t6 = Anteil Hybrid Diesel, t7 = Anteil Erdgas, t8 = Anzahl Neuzulassungen, t10 = Anteil Wasserstoff

Nummerierung der Kantone gemäss BFS

it:
Sulla base dei dati anonimizzati sulle nuove immatricolazioni pubblicati dall'USTRA, dal 2020 l'Ufficio federale dell'energia analizza importanti indicatori relativi agli autofurgoni e ai trattori a sella leggeri (iperonimo: veicoli commerciali leggeri VCL) a propulsione alternativa. Per veicoli a propulsione alternativa si intendono veicoli sui quali non è installato esclusivamente un motore a combustione a benzina o diesel. Oltre a indicatori annuali aggregati, questo set di dati contiene anche dati trimestrali e mensili relativi alle quote di mercato e indicazioni sui singoli Cantoni.

Legenda: t1 = Emissioni medie di CO2, t2 = Percentuale BEV, t3 = Percentuale PHEV benzina, t4 = Percentuale PHEV diesel, t5 = Percentuale ibride benzina, t6 = Percentuale ibride diesel, t7 = Percentuale gas naturale, t8 = Numero nuove immatricolazioni, t10 = Percentuale idrogeno

Numerazione dei Cantoni secondo UST.

fr: Modèles de VUL hybrides rechargeables (modèles PHEV) les plus prisés

de: Beliebteste Plug-In LNF-Modelle (PHEV)

en: Most popular plug-in models (LCV)

it: VCL plug-in più diffusi (modelli PHEV)

fr:
L’Office fédéral de l’énergie évalue depuis 2020 les modèles de VUL hybrides rechargeables (modèles PHEV) les plus prisés. Pour l’année 2020, des chiffres trimestriels sont disponibles; à partir de 2021, les valeurs sont disponibles à un rythme mensuel.

La numérotation des cantons est celle de l’OFS.

en:
The Swiss Federal Office of Energy has since 2020 ranked the most popular plug-in LCV models (PHEV). Quarterly figures are provided for 2020; from 2021 on, the values are available on a monthly basis.

Numbering of cantons according to FSO

de:
Das Bundesamt für Energie wertet seit 2020 bei den LNF die beliebtesten Plug-In LNF-Modelle (PHEV) aus. Für das Jahr 2020 sind Quartalszahlen bereitgestellt, ab 2021 sind die Werte in monatlicher Auflösung verfügbar.

Nummerierung der Kantone gemäss BFS

it:
Dal 2020 l'Ufficio federale dell'energia analizza i modelli di VCL plug-in più diffusi (modelli PHEV). Per il 2020 vengono forniti dati trimestrali, mentre dal 2021 in poi i valori sono disponibili con risoluzione mensile.

Numerazione dei Cantoni secondo UST.

fr:
Sur la base des données anonymisées des nouvelles immatriculations publiées par l’OFROU, l’Office fédéral de l’énergie évalue depuis 2020 des chiffres clés importants portant sur les voitures de livraison et tracteurs à sellette légers à propulsion alternative (véhicules utilitaires légers, VUL). Sont réputés véhicules à propulsion alternative les véhicules dont la propulsion ne se fait pas exclusivement avec un moteur à combustion à essence ou à diesel. Ce jeu de données comprend, outre les statistiques annuelles agrégées, les chiffres trimestriels et mensuels des parts de marché ainsi que des indications sur les différents cantons. L’OFEN évalue en outre les modèles de VUL entièrement électriques les plus prisés.

Base légale: art. 11 de l’ordonnance sur les exigences relatives à l’efficacité énergétique (OEEE)

en:
On the basis of the anonymised data for new registrations published by FEDRO, the Swiss Federal Office of Energy has since 2020 evaluated key figures for alternatively powered vans and light articulated vehicles (collectively: light commercial vehicles, LCVs). Alternatively powered vehicles are vehicles that are not solely powered by a petrol or diesel internal combustion engine. In addition to aggregated annual key figures, this data set also contains quarterly and monthly market share figures as well as information regarding the individual cantons. Also, the Swiss Federal Office of Energy ranks the most popular all-electric LCV models.

Legal basis: Energy Efficiency Ordinance (EnEO), Art. 11

de:
Auf Basis der vom ASTRA publizierten, anonymisierten Neuzulassungsdaten wertet das Bundesamt für Energie seit 2020 die wichtigsten Kennzahlen zu den alternativ angetriebenen Lieferwagen und leichten Sattelschlepper (Sammelbegriff: leichte Nutzfahrzeuge, LNF) aus. Als alternativ angetrieben gelten Fahrzeuge, die nicht ausschliesslich über einen Benzin- oder Diesel-Verbrennungsmotor angetrieben werden. Dieser Datensatz enthält neben aggregierten jährlichen Kennzahlen auch Quartal- und Monatszahlen der Marktanteile sowie Angaben zu den einzelnen Kantonen. Zudem wertet das Bundesamt für Energie bei den LNF die beliebtesten, vollelektrischen Modellen aus.

Rechtsgrundlage: Energieeffizienzverordnung (EnEV) Art. 11

it:
Sulla base dei dati anonimizzati sulle nuove immatricolazioni pubblicati dall'USTRA, dal 2020 l'Ufficio federale dell'energia analizza importanti indicatori relativi agli autofurgoni e ai trattori a sella leggeri (iperonimo: veicoli commerciali leggeri VCL) a propulsione alternativa. Per veicoli a propulsione alternativa si intendono veicoli che non sono mossi esclusivamente da un motore a combustione a benzina o diesel. Oltre a indicatori annuali aggregati, questo set di dati contiene anche dati trimestrali e mensili relativi alle quote di mercato e indicazioni sui singoli Cantoni. Inoltre l'Ufficio federale dell'energia analizza i modelli di VCL completamente elettrici più diffusi.

Base legale: ordinanza sull’efficienza energetica (OEEne), nello specifico l'articolo 11

alternative-antriebe

display_name: alternative-antriebe

elektrische-fahrzeuge

display_name: elektrische-fahrzeuge

elektromobilitat

display_name: elektromobilitat

hybridfahrzeuge

display_name: hybridfahrzeuge

leichte-nutzfahrzeuge

display_name: leichte-nutzfahrzeuge

lieferwagen

display_name: lieferwagen

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

de: Bundesamt für Energie BFE

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).

political_level: confederation


agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

author: Abteilung Wald

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

it: geocat.ch link permanente

de: AGIS Direktdownload

de: Waldareal

format: WMS

de: Der Datensatz enthält den statischen Wald bzw. das Waldareal gemäss §3 AWaG. Dieses ist Bestandteil der Informationsebene 'Waldgrenzen' des Objektkataloges der amtlichen Vermessung.

de: Abteilung Wald

de: AGIS Service Center Kanton Aargau

de: Das AGIS Service Center unterstützt als kantonale Koordinationsstelle die Bereitstellung von Geoinformationen und Metadaten der kantonalen Verwaltung. Die zuständigen kantonalen Fachstellen stellen die öffentlichen Geodaten des Kantons Aargau mittels der Infrastruktur des AGIS Service Center in der Informatik Aargau als Webservices und zum Download bereit.

political_level: canton

value: Aargau-Kt - Geocat Harvester


waldgrenze

title_for_slug: waldgrenze

de: Waldgrenze

de: Der Datensatz enthält die Abgrenzungen des statischen Wald. Diese sind Bestandteil der Informationsebene 'Waldgrenzen' des Objektkataloges der amtlichen Vermessung.


flughindernisse-kanton-schwyz

title_for_slug: flughindernisse-kanton-schwyz

fr: WFS-Dienst des Kantons Schwyz

de: WFS-Dienst des Kantons Schwyz

en: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

format: WFS

fr: Seillinien (Flughindernisse)

de: Seillinien (Flughindernisse)

en: Seillinien (Flughindernisse)

it: Seillinien (Flughindernisse)

fr: Flughindernisse Kanton Schwyz

de: Flughindernisse Kanton Schwyz

en: Flughindernisse Kanton Schwyz

it: Flughindernisse Kanton Schwyz

fr: Linienförmige Lufthindernisse im Kanton Schwyz mit Maximalhöhen von 25 m über Boden. Es handelt sich vorwiegend um Seilanlagen der Landwirtschaft wie Transport- und Heuseile. Die Daten sollen in erster Linie dazu dienen, die Flugsicherheit bei Helikoptereinsätzen zu erhöhen. Gewähr auf Vollständigkeit und Haftungsansprüche sind ausgeschlossen. Auch bezüglich Genauigkeit erheben wir nicht den Anspruch auf Geometerqualität. Die Nutzung dieser Daten erfolgt auf eigene Verantwortung. Hinweise, die zur Aktuellhaltung dieses Datensatzes beitragen, werden gerne entgegengenommen. Diese Daten ergänzen die Datenbank des Bundesamtes für Zivilluftfahrt BAZL, welches für die - meldepflichtigen - Luftfahrthindernisse über 25 m Höhe zuständig ist.

spatial: Kanton Schwyz (SZ)

fr: SZ Amt für Wald und Natur

de: SZ Amt für Wald und Natur

en: SZ Amt für Wald und Natur

it: SZ Amt für Wald und Natur

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz

de: Das Amt für Geoinformation verwaltet und veröffentlicht die Geodaten des Kantons Schwyz als OGC-Geodienste und als Datei-Download. Alle aktuell verfügbaren Geodaten, welche dem OGD unterliegen, sind hier aufgeführt.

value: SZ-Kt Geoinformation - Geocat Harvester


wms-orthofotos

title_for_slug: wms-orthofotos

author: Kanton Zürich

fr: WMS Orthofotos Kanton Zürich in Echtfarben und als Falschfarbeninfrarot

fr: Kanton Zürich

de: Kanton Zürich

en: Kanton Zürich

it: 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.

value: ZH - Geocat Harvester

fr: WMS Orthofotos

de: WMS Orthofotos

en: WMS Orthofotos

it: WMS Orthofotos


wms-orthofotos-ogd

title_for_slug: wms-orthofotos-ogd

de: geocat.ch Permalink

fr: Orthofotos Kanton Zürich in Echtfarben und als Falschfarbeninfrarot

fr: WMS Orthofotos (OGD)

de: WMS Orthofotos (OGD)

en: WMS Orthofotos (OGD)

it: WMS Orthofotos (OGD)


soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

regi

de: Regionen und Städte

envi

fr: Environnement

de: Umwelt

tran

fr: Transports

de: Verkehr

de: orthofoto satellitenbild luftbild luftaufnahme dop

de: WMS Orthofotos Kanton Zürich in Echtfarben und als Falschfarbeninfrarot

fr: Orthofoto Sommer (belaubt) RGB/Infrarot 2024/25 Neben dem Bezug via GIS-Browser-Bestellung, ist es auch möglich die Daten via direktem File-Download unter dem Verzeichnis maps.zh.ch/download zu beziehen. Hinweise für das Digitalisieren ab Orthofotos: 1. Alle Objekte, die auf dem Boden aufliegen (z.B. Strassen, Wege, Markierungen, Schächte), lassen sich mit einer Präzision von 1-2 Pixeln digitalisieren (±5-10cm). Wird das Orthofoto in der Amtlichen Vermessung eingesetzt, dann dürfen nur nicht exakt definierte Punkte digitalisiert werden. 2. Die Brücken sind zwar im Geländemodell nicht enthalten und würden demnach nicht lagerichtig abgebildet, wurden aber manuell korrigiert und sind damit lagerichtig. 3. Dachflächen sind nicht Teil des Geländemodelles. Deshalb sind Dächer nicht lagerichtig abgebildet. Aufgrund der Schrägsicht im Originalbild, können Dächer den nahen, unterliegenden Boden verdecken. 4. Treppen in Unterführungen sind nicht Teil des Geländemodelles und werden daher nicht lagerichtig abgebildet. 5. Bäume sind im Geländemodell nicht enthalten und deren Lage wird daher im Orthofoto nicht korrekt abgebildet. Dies ist bei der Digitalisierung von Baumwipfeln entsprechend zu berücksichtigen (bei Anwendungen ausserhalb der AV). (mehr Informationen im PDF "Merkblatt zur Nutzung des Orthofotos des Kantons Zürich aus Luftbildern, die 2024 und 2025 erstellt wurden" unter "Datengrundlage").

spatial: Kanton Zürich

fr: Orthofoto Sommer RGB/Infrarot 2024/25

de: Orthofoto Sommer RGB/Infrarot 2024/25

en: Orthofoto Sommer RGB/Infrarot 2024/25

it: Orthofoto Sommer RGB/Infrarot 2024/25


name: Amministrazione federale delle finanze AFF

fr: Comparaison internationale: Dépenses des administrations publiques par fonction (COFOG, codelist)

en: International comparison: Expenditure of general government by function (COFOG, codelist)

de: Internationaler Vergleich: Staatsausgaben nach Aufgabenbereichen (COFOG, codelist)

it: Confronto internazionale: Spesa delle amministrazioni pubbliche per funzione (COFOG, codelist)

fr: Cette liste de codes peut être utilisée comme table d'aide pour les dimensions _country_\__code_ et _cofog_ de l'ensemble de données correspondant (identifiant : resource_cofog_int).

de: Diese codelist kann als Hilfstabelle für die Dimensionen _country_\__code_ und _cofog_ des zugehörigen Datensets (identifier: resource_cofog_int) verwendet werden.

en: This codelist can be used as an auxiliary table for the dimensions _country_\__code_ and _cofog_ of the corresponding dataset (identifier: resource_cofog_int)

it: Questo codelist può essere utilizzata come tabella ausiliaria per le dimensioni _country_\__code_ e _cofog_ del dataset associato (identificatore: resource_cofog_int).

fr: Comparaison internationale: Dépenses des administrations publiques par fonction (COFOG, données)

en: International comparison: Expenditure of general government by function (COFOG, data)

de: Internationaler Vergleich: Staatsausgaben nach Aufgabenbereichen (COFOG, Daten)

it: Confronto internazionale: Spesa delle amministrazioni pubbliche per funzione (COFOG, dati)

fr:
Ce jeu de données contient une comparaison internationale des dépenses des administrations publiques par fonction (COFOG).
Les dimensions suivantes sont disponibles :

* country_code: pays (voir liste de codes)
* cofog: dépense des administrations publiques par fonction (voir liste de codes)
* jahr: année correspondante
* value: valeur correspondante
* unit: unité de la valeur
* source: source

en:
This dataset contains an international comparison of the expenditures of the general government by function (COFOG).
Following dimensions are shown:

* country_code: country (see codelist)
* cofog: expenditure of the general government by function (see codelist)
* jahr: corresponding year
* value: corresponding value
* unit: unit of value
* source: source

de:
Dieses Datenset enthält einen internationalen Vergleich der Staatsausgaben nach Aufgabenbereichen (COFOG).
Folgende Dimensionen sind verfügbar:

* country_code: Land (siehe zugehörige codelist)
* cofog: Staatsausgabe nach Aufgabenbereich (siehe codelist)
* jahr: zeigt das entsprechende Jahr
* value: zeigt den Wert der entsprechenden Position
* unit: zeigt die Einheit des Wertes
* source: Quelle

it:
Questo dataset incluso un confronto internazionale delle spese delle amministrazioni pubbliche per funzione (COFOG).
Sono mostrate le seguenti dimensioni:

* country_code: pasese (vedi codelist)
* cofog: spesa delle amministrazioni pubbliche per funzione(vedi codelist)
* jahr: anno corrispondente
* value: valore corrispondente
* unit: unità di valore
* source: fonte

fr: The expenditure of general government (central government, state government, local government and social security funds) is broken down by function following the functional classification COFOG (Classification of the functions of government) of the United Nations, which allows an international comparison of the results. The "expenditure" concept follows the principles of the National Accounts; it refers to the compensation of employees, the intermediate consumption, the subsidies, the social benefits, the other transfers, the interests paid and the gross investments.

de: Die Ausgaben des Staates (Bund, Kantone, Gemeinden und Öffentliche Sozialversicherungen) sind nach dem Aufgabenbereich ausgewertet. Wir benutzen die funktionelle Klassifikation COFOG (Classification of the functions of government) der Vereinten Nationen, die einen internationalen Vergleich der Ergebnisse erlaubt. Das Konzept der "Ausgaben" folgt dem Prinzip der Volkswirtschaftlichen Gesamtrechnung; es enthält die Arbeitnehmerentgelte, die Vorleistungen, die Subventionen, die Sozialleistungen, die anderen Transfers, die bezahlten Zinsen und die Bruttoinvestitionen gemäss den Definitionen.

it: La spesa delle amministrazioni pubbliche (Confederazione, cantoni, comuni ed enti di previdenza sociale) è ripartita per funzione secondo la classificazione funzionale COFOG (Classification of the functions of government) delle Nazioni Unite, la quale permette di paragonare i risultati a livello internazionale. Il concetto di "spesa" comprende i redditi da lavoro, il consumo intermedio, le sovvenzioni, le prestazioni sociali, altri trasferimenti, gli interessi pagati e gli investimenti lordi conformemente alle definizioni dei Conti nazionali.

eidgenossische-finanzverwaltung-efv

display_name: eidgenossische-finanzverwaltung-efv

federal-finance-administration-ffa

display_name: federal-finance-administration-ffa

spatial: CH

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

fr: Administration fédérale des finances AFF

de: Eidgenössische Finanzverwaltung EFV

en: Federal Finance Administration FFA

eidgenossische-finanzverwaltung-efv

fr: L’Administration fédérale des finances (AFF) est responsable du budget, du plan financier et de l’établissement des comptes. Elle se prononce sur tous les projets des départements susceptibles d’entraîner des dépenses, développe des solutions en matière de politique budgétaire, établit la statistique des finances publiques en Suisse et applique la péréquation financière à l’échelon fédéral. Elle veille en outre à la solvabilité permanente de la Confédération, se procure les fonds nécessaires et se charge des placements sur le marché monétaire et sur le marché des capitaux.

de: Die Eidgenössische Finanzverwaltung (EFV) ist für den Voranschlag, den Finanzplan und die Rechnungslegung verantwortlich, beurteilt die ausgabenwirksamen Vorhaben aller Departemente, entwickelt finanzpolitische Konzepte, ist für die Statistik der öffentlichen Haushalte der Schweiz zuständig und führt den bundesstaatlichen Finanzausgleich. Sie stellt die ständige Zahlungsbereitschaft des Bundes sicher und ist für die Mittelbeschaffung und Anlagen am Geld- und Kapitalmarkt verantwortlich.

en: The Federal Finance Administration (FFA) is responsible for the budget, the financial plan, and accounting; it evaluates the projects of all departments involving expenditures, develops financial policy concepts, is responsible for the statistics on the public budgets of Switzerland, and administers federal fiscal equalisation. It ensures the permanent liquidity of the Federal Government and is responsible for raising funds and investing on the money and capital markets.

it: L'Amministrazione federale delle finanze (AFF) è responsabile per il preventivo, il piano finanziario e la presentazione dei conti della Confederazione, valuta i progetti di tutti i dipartimenti con ripercussioni sulle uscite e sviluppa progetti politico-finanziari. L’AFF è altresì responsabile per la statistica delle amministrazioni pubbliche in Svizzera e gestisce la perequazione finanziaria a livello federale. Essa garantisce in ogni momento la solvibilità della Confederazione e provvede alla raccolta di fondi e agli investimenti nel mercato monetario e dei capitali.

value: DCAT I14Y EFV

fr: Comparaison internationale: Dépenses des administrations publiques par fonction (COFOG)

de: Internationaler Vergleich: Staatsausgaben nach Aufgabenbereichen (COFOG)

en: International comparison: Expenditure of general government by function (COFOG)

it: Confronto internazionale: Spesa delle amministrazioni pubbliche per funzione (COFOG)


fr: Comparaison internationale selon le modèle SFP (codelist)

de: Internationaler Vergleich gemäss GFS-Modell (codelist)

en: International comparison according to the GFS Model (codelist)

it: Confronto internazionale secondo il modello SFP (codelist)

fr: Cette liste de codes peut être utilisée comme table d'aide pour les dimensions _country_\__code_ et _indicator_ de l'ensemble de données correspondant (identifiant : resource_kennz_int).

de: Diese codelist kann als Hilfstabelle für die Dimensionen _country_\__code_ und _indicator_ des zugehörigen Datensets (identifier: resource_kennz_int) verwendet werden.

en: This codelist can be used as an auxiliary table for the dimensions _country_\__code_ and _indicator_ of the corresponding dataset (identifier: resource_kennz_int)

it: Questo codelist può essere utilizzata come tabella ausiliaria per le dimensioni _country_\__code_ e _indicator_ del dataset associato (identificatore: resource_kennz_int).

fr: Comparaison internationale selon le modèle SFP (données)

de: Internationaler Vergleich gemäss GFS-Modell (Daten)

en: International comparison according to the GFS Model (data)

it: Confronto internazionale secondo il modello SFP (dati)

fr:
Ce jeu de données contient une comparaison internationale des principaux indicateurs financiers selon le modèle SFP.
Les dimensions suivantes sont disponibles :

* country_code: pays (voir liste de codes)
* indicator: indicateur financier (voir liste de codes)
* jahr: année correspondante
* value: valeur correspondante
* unit: unité de la valeur
* source: source

en:
This dataset contains an international comparison of the key financial ratios according to the GFS model.
Following dimensions are shown:

* country_code: country (see codelist)
* indicator: financial ratio (see codelist)
* jahr: corresponding year
* value: corresponding value
* unit: unit of value
* source: source

de:
Dieses Datenset enthält einen internationalen Vergleich der wichtigsten Finanzkennzahlen gemäss GFS-Modell.
Folgende Dimensionen sind verfügbar:

* country_code: Land (siehe zugehörige codelist)
* indicator: Finanzkennzahlen  (siehe codelist)
* jahr: zeigt das entsprechende Jahr
* value: zeigt den Wert der entsprechenden Position
* unit: zeigt die Einheit des Wertes
* source: Quelle

it:
Questo dataset incluso un confronto internazionale dei principali indicatori secondo il modello GFS.
Sono mostrate le seguenti dimensioni:

* country_code: pasese (vedi codelist)
* indicator: indicatore (vedi codelist)
* jahr: anno corrispondente
* value: valore corrispondente
* unit: unità di valore
* source: fonte

fr:
Ce jeu de données contient une comparaison internationale des principaux indicateurs financiers selon le modèle SFP.

### Modèle SFP
En respectant le standard de statistique financière du Fonds monétaire international, le __modèle SFP__ assure la __comparabilité internationale__ des données de la statistique financière suisse. Ce standard est décrit dans le Manuel de statistiques de finances publiques (MSFP 2014).

de:
Dieses Datenset enthält einen internationalen Vergleich der wichtigsten Finanzkennzahlen gemäss GFS-Modell.

### GFS Modell
Die __internationale Vergleichbarkeit__ der Schweizer Finanzstatistikdaten wird durch das __GFS-Modell__ sichergestellt, in welchem der finanzstatistische Standard des Internationalen Währungsfonds umgesetzt ist. Dieser Standard wird im Government Finance Statistics Manual GFSM2014 beschrieben.

en:
This dataset contains an international comparison of the key financial ratios according to the GFS model.

### GFS model
__International comparability__ of Swiss financial statistics data is ensured with the __GFS Model__, which applies the financial statistics standard of the International Monetary Fund. This standard is described in the Government Finance Statistics Manual (GFSM 2014).

it:
Questo dataset incluso un confronto internazionale dei principali indicatori secondo il modello GFS.

### Modello GFS
La __comparabilità a livello internazionale__ dei dati svizzeri della statistica finanziaria è garantita dal __modello GFS__, che attua lo standard della statistica finanziaria del Fondo monetario internazionale. Questo standard è descritto nel Government Finance Statistics Manual (GFSM2014).

it: Amministrazione federale delle finanze AFF


fr: Agrégats principaux et prévisions dans les modèles SF et SFP (codelist)

de: Hauptaggregate und Prognosen im FS und GFS-Modell (codelist)

en: Main aggregates and forecasts with FS- and GFS-Model (codelist)

it: Gruppi principali e proiezioni nei modelli SF e GFS (codelist)

fr: Cette liste de codes peut être utilisée comme table d'aide pour les dimensions _hh_ et _variable_ de l'ensemble de données correspondant (identifiant : resource_main).

de: Diese codelist kann als Hilfstabelle für die Dimensionen _hh_ und _variable_ des zugehörigen Datensets (identifier: resource_main) verwendet werden.

en: This codelist can be used as an auxiliary table for the dimensions _hh_ and _variable_ of the corresponding dataset (identifier: resource_main)

it: Questo codelist può essere utilizzata come tabella ausiliaria per le dimensioni _hh_ e _variable_ del dataset associato (identificatore: resource_main).

fr: Agrégats principaux et prévisions dans les modèles SF et SFP (données)

de: Hauptaggregate und Prognosen im FS und GFS-Modell (Daten)

en: Main aggregates and forecasts with FS- and GFS-Model (data)

it: Gruppi principali e proiezioni nei modelli SF e GFS (dati)

fr:
Ce jeu de données présente les agrégats principaux et prévisions dans les modèles SF et SFP .
Les dimensions suivantes sont disponibles :

* hh: unité d'administration publique
* model: modèle considéré
* variable: agrégat
* jahr: année correspondante
* value: valeur correspondante (en millions CHF, pour dim == gfs_quote en % du PIB)

de:
Dieses Datenset zeigt Hauptaggregate und Prognosen im FS und GFS-Modell.
Folgende Dimensionen sind verfügbar:

* hh: zeigt den entsprechenden öffentlichen Haushalt
* model: zeigt das betrachtete Modell
* variable: Aggregat
* jahr: zeigt das entsprechende Jahr
* value: zeigt den Wert der entsprechenden Position (in Millionen CHF, für dim == gfs_quote in % des BIP)

en:
This dataset shows the main aggregates and forecasts with FS- and GFS-Model.
Following dimensions are shown:

* hh: corresponding public household
* model: model used
* variable: aggregate
* jahr: corresponding year
* value: corresponding value (in million CHF, for dim == gfs_quote in % of GDP)

it:
Questo dataset mostra i principali aggregati e le previsioni del modello FS e GFS.
Sono mostrate le seguenti dimensioni:

* hh: unità della pubblica amministrazione
* model: modello considerato
* variable: aggregato
* jahr: anno corrispondente
* value: valore corrispondente (in milioni CHF, per dim == gfs_quote in % del PIL)

fr:
### Modèle SFP
En respectant le standard de statistique financière du Fonds monétaire international, le __modèle SFP__ assure la __comparabilité internationale__ des données de la statistique financière suisse. Ce standard est décrit dans le Manuel de statistiques de finances publiques (MSFP 2014).

### Modèle SF
Reposant sur le Modèle comptable harmonisé pour les cantons et les communes (MCH2) et s'inspirant des normes IPSAS (International Public Sector Accounting Standards), le __modèle SF__ assure la __comparabilité nationale__. Dans la classification par nature, les évaluations standard du modèle SF contiennent le bilan, le compte de résultats et le compte de financement. Dans ce dernier, les recettes et les dépenses sont présentées par fonction.

A partir de l’année comptable 2008, la statistique financière se base sur de nouveaux standards. C’est pourquoi la comparabilité avec les données du modèle national SF d’avant 2008 est limitée.

en:
### GFS model
__International comparability__ of Swiss financial statistics data is ensured with the __GFS Model__, which applies the financial statistics standard of the International Monetary Fund. This standard is described in the Government Finance Statistics Manual (GFSM 2014).

### FS model
__National comparability__ is achieved with the __FS Model__, which is based on the Harmonized Accounting Model for the Cantons and Communes (HAM2) and is thus inspired by the International Public Sector Accounting Standards (IPSAS). Standard evaluations with the FS Model always contain the statement of financial position, statement of financial performance and financing statement in the economic classification. Furthermore, receipts and expenditure are shown by function in the financing statement. In the 2008 fiscal year, the financial statistics were adjusted to new standards. There is therefore limited comparability with the figures prior to 2008 in the national FS Model.

In the 2008 fiscal year, the financial statistics were adjusted to new standards. There is therefore limited comparability with the figures prior to 2008 in the national FS Model.

de:
### GFS Modell
Die __internationale Vergleichbarkeit__ der Schweizer Finanzstatistikdaten wird durch das __GFS-Modell__ sichergestellt, in welchem der finanzstatistische Standard des Internationalen Währungsfonds umgesetzt ist. Dieser Standard wird im Government Finance Statistics Manual GFSM2014 beschrieben.

### FS Modell
Die __nationale Vergleichbarkeit__ wird mit dem __FS-Modell__ sichergestellt, welches auf dem Harmonisierten Rechnungslegungsmodell der Kantone und Gemeinden (HRM2) basiert und sich damit an die International Public Sector Accounting Standards (IPSAS) anlehnt. Die Standardauswertungen im FS-Modell enthalten jeweils in der Artengliederung die Bilanz, die Erfolgsrechnung und die Finanzierungsrechnung. Zusätzlich werden in der Finanzierungsrechnung die Einnahmen und Ausgaben nach Funktionen ausgewiesen.

Mit dem Rechnungsjahr 2008 wurde die Finanzstatistik an neue Standards angepasst. Deshalb ist die Vergleichbarkeit mit den Zahlen vor 2008 im nationalen FS-Modell eingeschränkt.

it:
### Modello GFS
La __comparabilità a livello internazionale__ dei dati svizzeri della statistica finanziaria è garantita dal __modello GFS__, che attua lo standard della statistica finanziaria del Fondo monetario internazionale. Questo standard è descritto nel Government Finance Statistics Manual (GFSM2014).

### Modello SF
La __comparabilità a livello nazionale__ è garantita dal __modello SF__, che si basa sul modello di presentazione dei conti armonizzato dei Cantoni e dei Comuni (MPCA2) e quindi sugli International Public Sector Accounting Standards (IPSAS). Le valutazioni standard nel modello SF contengono nell’articolazione per tipi il bilancio, il conto economico e il conto di finanziamento. Inoltre, nel conto di finanziamento vengono indicate le entrate e le uscite secondo funzioni.

Con l’esercizio 2008 la statistica finanziaria è stata adeguata a nuovi standard. Pertanto, il raffronto con le cifre antecedenti al 2008 nel modello SF nazionale è limitato.


fr: Données détaillée modèle SF: Compte de financement, par groupe par nature et par fonction (données)

de: Detaillierte Daten FS Modell: Finanzierungsrechnung nach Sachgruppen und Funktionen (Daten)

en: Detailed data FS model: Financing statement by nature and function (data)

it: Dati dettagliati modello SF: Conto di finanziamento secondo gruppi di beni e servizi e secondo funzione (dati)

fr:
Ce jeu de données présente le compte de financement, par groupe de natures et par fonction selon le modèle SF.
Les dimensions suivantes sont disponibles :

* arten: classification par nature (voir liste de codes)
* funk: classifcation fonctionnelle (voir liste de codes)
* jahr: année correspondante
* value: valeur correspondante
* hh: unité d'administration publique (voir https://www.efv.admin.ch/dam/efv/de/dokumente/finanzstatistik/daten/readme.xlsx.download.xlsx/readme.xlsx, feuille "file_structure")
* unit: unité de la valeur
* model: modèle considéré

de:
Dieses Datenset zeigt die Finanzierungsrechnung nach Sachgruppen und Funktionen gemäss FS-Modell.
Folgende Dimensionen sind verfügbar:

* arten: ermöglicht Artengliederung (siehe zugehörige codelist)
* funk: ermöglicht funktionale Gliederung (siehe codelist)
* jahr: zeigt das entsprechende Jahr
* value: zeigt den Wert der entsprechenden Position
* hh: zeigt den entsprechenden öffentlichen Haushalt (siehe https://www.efv.admin.ch/dam/efv/de/dokumente/finanzstatistik/daten/readme.xlsx.download.xlsx/readme.xlsx sheet "file_structure")
* unit: zeigt die Einheit des Wertes
* model: zeigt das betrachtete Modell

en:
This dataset shows the financing statement by nature and function according to the FS model.
Following dimensions are shown:

* arten: used to classify by nature (see codelist)
* funk: used to classify by function (see codelist)
* jahr: corresponding year
* value: corresponding value
* hh: corresponding public household (see https://www.efv.admin.ch/dam/efv/de/dokumente/finanzstatistik/daten/readme.xlsx.download.xlsx/readme.xlsx sheet "file_structure")
* unit: unit of value
* model: model used* funk: used to classify by function
* jahr: corresponding year
* value: corresponding value
* hh: corresponding public household (see https://www.efv.admin.ch/dam/efv/de/dokumente/finanzstatistik/daten/readme.xlsx.download.xlsx/readme.xlsx sheet "file structure")
* unit: unit of value
* model: model used

it:
Questo dataset mostra il conto di finanziamento secondo gruppi di beni e servizi in base ai modelli SF.
Sono mostrate le seguenti dimensioni:

* arten: classificazione per gruppi di beni e servizi (vedi codelist)
* funk: classificazione funzionale (vedi codelist)
* jahr: anno corrispondente
* value: valore corrispondente
* hh: unità della pubblica amministrazione (vedere https://www.efv.admin.ch/dam/efv/de/dokumente/finanzstatistik/daten/readme.xlsx.download.xlsx/readme.xlsx, scheda "file_structure")
* unit: unità di valore
* model: modello considerato

fr: Données détaillée modèle SF: Compte de financement, par groupe par nature et par fonction (codelist)

de: Detaillierte Daten FS Modell: Finanzierungsrechnung nach Sachgruppen und Funktionen (codelist)

en: Detailed data FS model: Financing statement by nature and function (codelist)

it: Dati dettagliati modello SF: Conto di finanziamento secondo gruppi di beni e servizi e secondo funzione (codelist)

fr: Cette liste de codes peut être utilisée comme table d'aide pour les dimensions _arten_ et _funk_ de l'ensemble de données correspondant (identifiant : resource_fir_art_funk).

de: Diese codelist kann als Hilfstabelle für die Dimensionen _arten_ und _funk_ des zugehörigen Datensets (identifier: resource_fir_art_funk) verwendet werden.

en: This codelist can be used as an auxiliary table for the dimensions _arten_ and _funk_ of the corresponding dataset (identifier: resource_fir_art_funk)

it: Questo codelist può essere utilizzata come tabella ausiliaria per le dimensioni _arten_ e _funk_ del dataset associato (identificatore: resource_fir_art_funk).

fr:
### Modèle SF
Reposant sur le Modèle comptable harmonisé pour les cantons et les communes (MCH2) et s'inspirant des normes IPSAS (International Public Sector Accounting Standards), le __modèle SF__ assure la __comparabilité nationale__. Dans la classification par nature, les évaluations standard du modèle SF contiennent le bilan, le compte de résultats et le compte de financement. Dans ce dernier, les recettes et les dépenses sont présentées par fonction.

A partir de l’année comptable 2008, la statistique financière se base sur de nouveaux standards. C’est pourquoi la comparabilité avec les données du modèle national SF d’avant 2008 est limitée.

de:
### FS Modell
Die __nationale Vergleichbarkeit__ wird mit dem __FS-Modell__ sichergestellt, welches auf dem Harmonisierten Rechnungslegungsmodell der Kantone und Gemeinden (HRM2) basiert und sich damit an die International Public Sector Accounting Standards (IPSAS) anlehnt. Die Standardauswertungen im FS-Modell enthalten jeweils in der Artengliederung die Bilanz, die Erfolgsrechnung und die Finanzierungsrechnung. Zusätzlich werden in der Finanzierungsrechnung die Einnahmen und Ausgaben nach Funktionen ausgewiesen.

Mit dem Rechnungsjahr 2008 wurde die Finanzstatistik an neue Standards angepasst. Deshalb ist die Vergleichbarkeit mit den Zahlen vor 2008 im nationalen FS-Modell eingeschränkt.

en:
### FS model
__National comparability__ is achieved with the __FS Model__, which is based on the Harmonized Accounting Model for the Cantons and Communes (HAM2) and is thus inspired by the International Public Sector Accounting Standards (IPSAS). Standard evaluations with the FS Model always contain the statement of financial position, statement of financial performance and financing statement in the economic classification. Furthermore, receipts and expenditure are shown by function in the financing statement.

In the 2008 fiscal year, the financial statistics were adjusted to new standards. There is therefore limited comparability with the figures prior to 2008 in the national FS Model.

it:
### Modello SF
La __comparabilità a livello nazionale__ è garantita dal __modello SF__, che si basa sul modello di presentazione dei conti armonizzato dei Cantoni e dei Comuni (MPCA2) e quindi sugli International Public Sector Accounting Standards (IPSAS). Le valutazioni standard nel modello SF contengono nell’articolazione per tipi il bilancio, il conto economico e il conto di finanziamento. Inoltre, nel conto di finanziamento vengono indicate le entrate e le uscite secondo funzioni.

Con l’esercizio 2008 la statistica finanziaria è stata adeguata a nuovi standard. Pertanto, il raffronto con le cifre antecedenti al 2008 nel modello SF nazionale è limitato.


fr: Importants débits de crue en Suisse

de: Grosse Hochwasserabflüsse in der Schweiz

it: Portate di piena elevate

fr: Répertoire des importants débits de crue dans les bassins versants suisses, établi par Scherrer AG sur mandat de l'OFEV. Les données les plus anciennes remontent à 1900, avec des valeurs isolées antérieures.

de: Verzeichnis grosser Hochwasserabflüsse in schweizerischen Einzugsgebieten, zusammengestellt von der Scherrer AG im Auftrag des BAFU. Daten ab 1900, einzelne Werte von früher.

it: Elenco delle portate di piena elevate nei bacini imbriferi svizzeri. Elaborato da Scherrer AG, su mandato dell’UFAM.

format: ODS

high-water

display_name: high-water

hochwasser

display_name: hochwasser

inondations

display_name: inondations

inondazione

display_name: inondazione

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

fr: Office fédéral de l'environnement (OFEV)

en: Federal Office for the Environment (FOEN)

de: Bundesamt für Umwelt (BAFU)

it: Ufficio federale dell'ambiente (UFAM)

bundesamt-fur-umwelt-bafu

fr: Office fédéral de l'environnement OFEV

de: Bundesamt für Umwelt BAFU

en: Federal Office for the Environment FOEN

it: Ufficio federale dell'ambiente UFAM

fr: L’autorité compétente pour les questions environnementales. Il est à ce titre chargé de gérer les ressources naturelles selon les principes du développement durable et de protéger l’homme contre les dangers naturels et l’environnement contre les pollutions.

de: Die Fachbehörde für die Umwelt. Es ist zuständig für die nachhaltige Nutzung der natürlichen Ressourcen sowie für den Schutz des Menschen vor Naturgefahren und den Schutz der Umwelt vor übermässigen Belastungen.

en: The federal environmental authority. It is responsible for ensuring that natural resources are used sustainably, that the public is protected against natural hazards, and that the environment is protected from unacceptable adverse impacts.

it: Il servizio specializzato in materia ambientale, è competente per quanto riguarda l'utilizzazione sostenibile delle risorse naturali, la protezione delle persone dai pericoli naturali e dell'ambiente da un inquinamento eccessivo.

value: DCAT I14Y BAFU


author: BFS/OFS

de: Statistisches Jahrbuch der Schweiz 1926

fr: Annuaire statistique de la Suisse 1926

basas-statisticas-e-survistas

display_name: basas-statisticas-e-survistas

bases-statistiques-et-generalites

display_name: bases-statistiques-et-generalites

grundlagen-und-ubersichten

display_name: grundlagen-und-ubersichten

statistical-basis-and-overviews

display_name: statistical-basis-and-overviews

spatial: Schweiz

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS

de: Bundesamt für Statistik BFS

en: Federal Statistical Office FSO

it: Ufficio federale di statistica UST

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.

en: The FSO is Switzerland's national competence centre for official statistics. It produces and publishes statistical information on the status and development of the population, economy, society, education, research, territory and the environment. This information is used for opinion building among the population and for the planning and management of key policy areas. They make an important contribution to a modern, democratic state.

it: L’UST è il centro di competenza nazionale per la statistica pubblica della Svizzera. Produce e pubblica informazioni statistiche sullo stato e sull'evoluzione della popolazione, dell'economia, della società, della formazione, della ricerca, del territorio e dell'ambiente. Queste informazioni servono alla formazione dell'opinione pubblica nonché alla pianificazione e alla gestione in ambiti politici di centrale importanza. Forniscono un importante contributo per uno Stato moderno e democratico.

value: BFS – DCAT Harvester


fr: Annuaire statistique de la Suisse 1953

de: Statistisches Jahrbuch der Schweiz 1953


de: Bauvorhaben nach Art der Auftraggeber, Art der Bauwerke und Art der Arbeiten, 1995-2012

de: Dieses Dataset präsentiert die jährliche Anzahl der Bauvorhaben nach Kanton und Gemeinde, Art der Auftraggeber (öffentlich, privat), Art der Bauwerke (Hochbau, Tiefbau) und Art der Arbeiten (Neubau, Umbau), 1995 - 2012.

fr: Projets dans la construction par genre de maîtres d'ouvrage, genre d'ouvrage et genre de travaux, 1995-2012

fr: Ce dataset présente les chiffres annuels des projets dans la construction selon le canton et la commune, le genre de maîtres d'ouvrage (publics, privés), le genre d'ouvrage (bâtiment, génie civil) et le genre de travaux (nouvelles constructions, transformations), de 1995 à 2012.

de: JSON-Struktur

fr: Structure JSON

bau--und-wohnungswesen

display_name: bau--und-wohnungswesen

construction-and-housing

display_name: construction-and-housing

construction-et-logement

display_name: construction-et-logement

construcziuns-ed-abitaziuns

display_name: construcziuns-ed-abitaziuns

costruzioni-e-abitazioni

display_name: costruzioni-e-abitazioni

spatial: Kantone

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società