maintainer: Felix Neff

en: grassland insects diversity topsoil-removal functional-diversity long-term-experiment functional-traits restoration

en: Insect abundance

en:
Abundance of adult insects recorded in the samplings on all experimental sites

- **Plot**: ID of Plot
- **Treatment**: Experimental treatment
- **Species**: Insect species name (following [Fauna Europaea](https://fauna-eu.org))
- **Author**: Author and year of species' description (following [Fauna Europaea](https://fauna-eu.org))
- **Group**: Insect group as used in the analyses
- **Number_Adults**: Number of adult individuals recorded
- **Herbivore**: Logical indicating whether the species is feeding as a herbivore (*TRUE*) or not (*FALSE*)

en: Plot information

en:
Information on the experimental plots.

- **Plot**: ID of Plot
- **Treatment**: Experimental treatment
- **Landuse_history**: recent agricultural use for Initial; agricultural use before restoration for all restored sites
- **Last_tilled**: Last time the site was tilled
- **Intensity**: Frequency and intensity of mowing and manuring (*intensity1*: mowing once and no manure, i*ntensity2*: 2-3 times mowing and no manure, *intensity3*: 2-3 times mowing and manuring, *intensity4*: 4-5 times mowing and manuring)
- **Slope**: slope gradient according to classes defined by FAO (1990)
- **X**: X coordinate of the plot (CH1903)
- **Y**: Y coordinate of the plot (CH1903)
- **Cluster**: Spatial cluster of the plot

en: Insect traits

en:
Functional traits of all herbivorous insect species sampled in the study.

- **Species**: Insect species name (following [Fauna Europaea](https://fauna-eu.org))
- **Author**: Author and year of species' description (following [Fauna Europaea](https://fauna-eu.org))
- **Group**: Insect group as used in the analyses
- **Body volume**: Body volume determined by body length, body width and body height (in mm$^3$)
- **Body_shape**: Ratio of body length to body width
- **Hind_femur_shape**: Ratio of hind-femur length to hind-femur width
- **Hind_front_leg_ratio**: Ratio of front-leg length to hind-leg length (leg length = femur length + tibia length)
- **Wing_length_rel**: Ratio of wing length to body length
- **Leg_length_rel**: Ratio of front-leg length to body length (leg length = femur length + tibia length)
- **Antenna_length_rel**: Ratio antenna length to body length
- **Eye_width_rel**: Ratio of eye width to head width (Auchenorrhyncha, Heteroptera) / to head height (Orthoptera)
- **Feeding_specialization**: Insect specialization on food source (*m*: monophagous, *o*: oligophagous, *p*: polyphagous)
- **Feeding_tissue**: Feeding tissue used for feeding (*c*: chewers, *x*: xylem, *p*: phloem, *m*: mesophyll, *m-p/r*: mesophyll as well as phloem and/or reproductive organs, *r*: reproductive organs, *se*: ripe seeds)
- **Hibernation**: Hibernation stage (*e*: egg, *e/n*: egg and nymph, *n*: nymph, *a*: adult)
- **Generations**: Number of generations per year (*1.5* stands for *1-2* generations per year)
- **Moisture_pref_mean**: mean of preferred habitat moistures (*1*: xerophilous, *2*: moderately xerophilous, *3*: moderately mesohygrophilous, *4*: mesohygrophilous, *5*: moderately hygrophilous, *6*: hygrophilous, *7*: moderately hydrophilous, *8*: hydrophilous)
- **Moisture_pref_range**: range of preferred habitat moistures (indicating degree of specialization)

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

**Paper Citation**:

Neff, F., Resch, M. C., Marty, A., Rolley, J. D., Schütz, M., Risch, A. C, Gossner, M. M. 2020. Long-term restoration success of insect herbivore communities in semi-natural grasslands: a functional approach. Ecological Applications, 30, e02133. [10.1002/eap.2133](https://doi.org/10.1002/eap.2133)

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

 Methods

 Study site
The study area is situated within and nearby to Eigental nature reserve (47°27’36” to 47°29’06” N, 8°37’12” to 8°37’44” E, 461 to 507 m a.s.l.) in the vicinity of Zurich airport (Canton Zurich, Switzerland). Mean annual precipitation and temperature is 903 ± 136 mm and 9.14°C ± 0.50°C (mean ± SD for 2007-2017 (*MeteoSchweiz 2018*)). In 1967, the Eigental nature reserve was established to protect small and isolated remnants of species-rich, semi-natural grasslands (roughly 12 ha), which were embedded in an otherwise intensively managed landscape. It is characterized by oligo- to mesotrophic Molinion (semi-wet, matrix species *Molinia caerulea*) and Mesobromion (semi-dry, matrix species *Bromus erectus*) meadows (*Delarze et al. 2015*), reflecting small-scale habitat heterogeneity, mainly due to site-specific groundwater levels and slope inclination. As in most Central European grasslands, management is necessary to prevent shrub and tree invasions as well as to secure low levels of available soil nutrients and thus to maintain these species-rich habitats ([*Poschlod and WallisDeVries 2002*](https://doi.org/10.1016/S0006-3207(01)00201-4)).
In 1990, the government of the Canton Zurich decided to enlarge the Eigental nature reserve as a counter measure against degradation and biodiversity loss in semi-natural grasslands due to overutilization and the excessive input of nutrients (mostly nitrogen). Eleven patches of adjacent intensively managed grassland (in total roughly 20 ha) were targeted to be transformed into semi-natural grasslands. As a first restoration measure, fertilization was ceased, and biomass harvested three times to remove excessive soil nutrients from the original system and thus benefit plant species with low competitive ability on the long run. In 1995, the restoration efforts were increased and a large-scale experiment comprising three restoration measures with increasing intervention intensities was implemented:

- **Harvest only**: Initial restoration measures were continued with mowing and removing of the aboveground biomass two times a year (early summer and autumn).
- **Topsoil**: Removal of topsoil, depending on the thickness of the A horizon the upper 10 to 20 cm, in four randomly selected areas within the eleven patches in late autumn 1995. The size of the restoration area depended on individual patch size (2700 to 7000 m2).
- **Topsoil + Propagules**: Plant propagules were added on half of the area where topsoil was removed via application of fresh, seed-containing hay and hand-collected propagules of target species originating from semi-dry and semi-wet species-rich grasslands with local and regional provenance (within radius of 7 to 30 km) (1995, 1996, 1997).

Management of *Topsoil* and *Topsoil + Propagules* started five years after treatment implementation and included yearly mowing and removing of aboveground biomass (late summer or early autumn). The experiment was complemented with intensively managed grassland sites that share the same agricultural history as the restored sites (**Initial**; swards dominated by *Lolium perenne*, *L. multiflorum* and *Trifolium repens*): mowing and subsequent fertilizing (manure) up to five times a year, as well as different tillage regimes. Finally, sites were selected in target semi-dry and semi-wet grasslands (**Target**) located within the Eigental nature reserve and another nature reserve nearby (Altläufe der Glatt; 47°28’29” to 47°27’41” N, 8°31’56” to 8°32’26” E, 418 to 420 m a.s.l.). The selected target sites are mown and aboveground biomass removed once a year in late summer or early autumn. For each of the five treatments, we selected eleven plots (5 m × 5 m) spread across the sites. Altogether, the experiment included 55 plots.

 Arthropod sampling
Aboveground arthropods were sampled using suction sampling on four consecutive days in early July 2017 before the grasslands were mown. Arthropods were sampled in two locations on each 5 m × 5 m plot, once in the south-western and once in the north-eastern corner to account for possible spatial heterogeneity within the plots. Arthropods were sorted to order or lower taxonomic levels and individuals were identified to species level. We focused on three groups (Hemiptera: Auchenorrhyncha, Hemiptera: Heteroptera, Orthoptera),

 Functional traits
We used two sets of functional traits in this study.

**Morphometric traits**:
Body volume, body shape, hind femur shape, hind/front leg ratio, wing length, leg length, antenna length and eye width. We used trait measurements from [*Simons et al. (2016)*](http://dx.doi.org/10.1890/15-0616.1) and [*Neff et al. (2019)*](https://doi.org/10.1007/s10980-019-00872-1) and complemented them with measurements on study specimens. These measurements were conducted using a high-resolution measuring stereo microscope (Leica DVM6, Leica Microsystems) including automated high-resolution photo stacking with the software Leica Application Suite X (LAS X, © 2018 Leica Microsystems CMS GmbH) and Leica Map Premium (Leica Microsystems, © 1996-2017 Digital Surf) at WSL Birmensdorf. The eight morphometric traits were calculated from direct measurements of body parts on specimens of all sampled species. From each species, we measured at least one female and one male specimen. Additionally, for species that show wing dimorphism, we included the different wing morphs and weighted them by their prevalence reported in literature. For few species, of which not all wing morphs were available for measurements (10 cases), we estimated relative wing length from congeneric species or from the literature.

**Life-history traits**
Based on an existing data set collected by [*Gossner et al. (2015)*](http://dx.doi.org/10.1890/14-2159.1). We included traits describing different life-history characteristics of herbivore insect species, namely: feeding specialization, feeding tissue, hibernation stage and number of generations per year, which are related to insect species’ vulnerability to changes in plant community composition, microhabitat use and disturbance tolerance. To represent potential changes in habitat moisture with abandonment of intensive land use (e.g., change in ground-water level), we also included two traits related to preferred habitat moisture of the study species: moisture preference, describing species’ optimum habitat moisture, and moisture range, which describes the species’ range of preferable moisture conditions.

 References

Delarze, R., Y. Gonseth, S. Eggenberg, and M. Vust. 2015. Lebensräume der Schweiz: Ökologie - Gefährdung - Kennarten. 3rd ed. Ott, Bern.

Gossner, M. M., N. K. Simons, R. Achtziger, T. Blick, W. H. O. Dorow, F. Dziock, F. Köhler, W. Rabitsch, and W. W. Weisser. 2015. A summary of eight traits of Coleoptera, Hemiptera, Orthoptera and Araneae, occurring in grasslands in Germany. Scientific Data 2:150013.

MeteoSchweiz. 2018. Klimabulletin Jahr 2017. MeteoSchweiz, Zürich.

Neff, F., N. Blüthgen, M. N. Chisté, N. K. Simons, J. Steckel, W. W. Weisser, C. Westphal, L. Pellissier, and M. M. Gossner. 2019. Cross-scale effects of land use on the functional composition of herbivorous insect communities. Landscape Ecology 34:2001–2015.

Poschlod, P., and M. F. WallisDeVries. 2002. The historical and socioeconomic perspective of calcareous grasslands—lessons from the distant and recent past. Biological Conservation 104:361–376.

Simons, N. K., W. W. Weisser, and M. M. Gossner. 2016. Multi-taxa approach shows consistent shifts in arthropod functional traits along grassland land-use intensity gradient. Ecology 97:754–764.

diversity

display_name: diversity

functional-diversity

display_name: functional-diversity

functional-traits

display_name: functional-traits

grassland

display_name: grassland

insects

display_name: insects

long-term-experiment

display_name: long-term-experiment

restoration

display_name: restoration

topsoil-removal

display_name: topsoil-removal

en: Grassland restoration: insects and insect traits


maintainer: EnviDat Support

en: pattern-formation numerical-model snow vapor-transport python

state: active

type: dataset

media_type: ZIP

en:
Data and code v1.0 downloaded from the git.

Running the code requires an installation of FEniCS via docker.

format: ZIP

en:
This python code uses the Finite Element library FEniCS (via docker) to solve the one dimensional partial differential equations for heat and mass transfer in snow. The results are written in vtk format.

The dataset contains the code and the output data to reproduce the key Figure 5 from the related publication:

_Schürholt, K., Kowalski, J., Löwe, H.; Elements of future snowpack modeling - Part 1: A physical
instability arising from the non-linear coupling of transport and phase changes, The Cryosphere, 2022_

The code and potential updates can be accessed directly through git via:

https://gitlabext.wsl.ch/snow-physics/snowmodel_fenics

numerical-model

display_name: numerical-model

pattern-formation

display_name: pattern-formation

python

display_name: python

snow

display_name: snow

vapor-transport

display_name: vapor-transport

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

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: A numerical solver for heat and mass transport in snow based on FEniCS


maintainer: Leo Gallus Bont

en: qgis geoprocessing openstreetmap accessible-forest seilaplan forest

en: DEM (for the area of the sample forest range)

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Juypter Notebook for Data Preparation (online)

media_type: ipynb

format: SERVICE

en: Digitised sample perimeter

media_type: application/zip

mimetype: application/zip

en: Juypter Notebook for Data Preparation

en: Power lines vector data (close to the area of the sample forest range)

en: Preview

media_type: image/png

format: PNG

mimetype: image/png

en: Railways vector data (close to the sample forest range)

en: Forest vector data (for sample forest range)

en:
This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps).
The purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin [Seilaplan]( https://doi.org/10.16904/envidat.software.1) for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting.
The vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019.

Additional notes for vector data:
Please note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API - https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any perimeter or area can be digitised freely using the QGIS editing toolbar.

The DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are:

- Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM)
- Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif

This methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed.

Additional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range.

This sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.

accessible-forest

display_name: accessible-forest

forest

display_name: forest

geoprocessing

display_name: geoprocessing

openstreetmap

display_name: openstreetmap

qgis

display_name: qgis

seilaplan

display_name: seilaplan

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


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

en: gbif.range R package version 0.2 (current)

en: wsl.gbif R package version 0.1 (deprecated)

en: Test version, not to be used.

en: GitHub URL

media_type: R

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

accepted-name

display_name: accepted-name

conservation

display_name: conservation

ecoregions

display_name: ecoregions

filtering

display_name: filtering

flags

display_name: flags

gbif

display_name: gbif

hard-limit

display_name: hard-limit

landsca

display_name: landsca

large-scale

display_name: large-scale

occurrence-records

display_name: occurrence-records

r-package

display_name: r-package

range-maps

display_name: range-maps

species-distribution

display_name: species-distribution

species-observations

display_name: species-observations

synonyms

display_name: synonyms

taxonomy

display_name: taxonomy

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


en: groundwater switzerland studibach alptal time-series

media_type: text/plain

en:
Groundwater time series of the monitoring network in the Studibach (C7) catchment, Alptal, Switzerland published in
Rinderer M., van Meerveld I, McGlynn B. (2019): From points to patterns – Assessing runoff source area dynamics and hydrological connectivity using time series clustering. Water Resources Research, doi: 2018WR023886R

format: TXT

mimetype: text/plain

en: Groundwater time series between 2010 and 2014 of the distributed monitoring system in the Studibach (C7), Alptal, Switzerland. Data published in Rinderer M., van Meerveld I, McGlynn B. (2019): From points to patterns – Assessing runoff source area dynamics and hydrological connectivity using time series clustering. Water Resources Research, doi: 2018WR023886R

alptal

display_name: alptal

groundwater

display_name: groundwater

studibach

display_name: studibach

switzerland

display_name: switzerland

time-series

display_name: time-series

education

en: Education and science

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: Groundwater time series Studibach (Rinderer et al., 2019, WRR)


maintainer: Roksolana Petrovska

en: acer mortality-rate regeneration shade-tolerance fagus dominance lar

en: Mortality of regeneration

media_type: CSV

en: Acer platanoides, Acer pseudoplatanus and Fagus sylvatica living and dead juveniles (0-500 cm in height) grown in the deep shade of a prime beech-dominated forest.

format: CSV

media_type: r script (flat-ascii text)

en: The R-script of survival analysis for accelerated failure time model

en:
 One individual per species, vitality class (low and high) and height class (eight classes: 0–10, 11–20, 21–35, 36–60, 61–90, 91–130, 131–200 and 201–500 cm) was randomly selected and harvested in each of the six plots. This resulted in a sample of 82, 80 and 89 living individuals of A. platanoides, A. pseudoplatanus and F. sylvatica, respectively.

 Additionally stems of dead Acer spp. and F. sylvatica trees that had died within the last three years (2015–2018) were randomly harvested, matching the height classes of the harvested living trees wherever possible. In total, 179 dead young trees (60 A. platanoides, 72 A. pseudoplatanus and 47 F. sylvatica) were collected.

 Variables:
* species_code: a_pla - Acer platanoides, a_pse - Acer pseudoplatanus, f_syl - Fagus sylvatica
* species: as above
* dummy: 0 - living individual, 1 - dead individual
* LAR_cm2_g: leaf area ratio or ratio of leaf area to total plant biomass, [cm2/g]
* tree_age: in years
* avg_ring_micron: average width of the last 5 rings in tree life excluding the last ring
* dry_mass_g: aboveground and belowground biomass
* DLI: direct light index (measured only under living individuals)
* BLI: diffuse light index (measured only under living individuals)
* GLI: global light index

acer

display_name: acer

dominance

display_name: dominance

fagus

display_name: fagus

lar

display_name: lar

mortality-rate

display_name: mortality-rate

regeneration

display_name: regeneration

shade-tolerance

display_name: shade-tolerance

en: Mortality of regeneration: Acer spp. and Fagus sylvatica


maintainer: Adam Winstral

en: snow-depth snow-simulation jim snow jules-investigation-model

en: HS and SWE observations

en: Automated (HS) and manual (SWE) data used to evaluate model simulations

en: File/data descriptor

en: DEM

en: 1-km resolution DEM used for downscaling gridded NWP data to stations and for distributing BDE evaluations at HS-stations to SWE-stations

en: Station forcing data

en: All forcing data need to run JIM at HS and SWE stations. These are data downscaled directly from COSMO NWP data (WY14, WY15) and further enhanced by additional station observations of snow depth (HS) and air temperature (Ta) in WY17. Further information can be found in README file. Note that in WY14 and WY15, shortwave radiation was not split into direct and diffuse (not necessary for JIM) and that the default method in JIM for splitting precipitation phase was used. In WY 17, direct and diffuse were combined as input to JIM and JIM was forced with pre-processed liquid and solid precipitation phases.

en: These data were used to drive and evaluate Jules Investigation Model (JIM) snow simulations. The data provided are the forcing data used for the "deterministic" runs as described in Winstral et al., 2019. The bias-detecting ensemble (Winstral et al., 2019) used observed snow depths (HS) to detect biases in these deterministic simulations related to precipitation and energy inputs to JIM. Simulations that included the BDE evaluations substantially improved JIM simulations.

jim

display_name: jim

jules-investigation-model

display_name: jules-investigation-model

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-simulation

display_name: snow-simulation

en: Meteorological data used to develop and validate the bias-detecting ensemble (BDE)


en: landscape-planning land-change urban-landscape concur urban-planning

media_type: .pdf

en:
Book of abstracts from the virtual conference "From Plans to Land Change: Dynamics of Urban Regions"

Cities and urban regions are among the most dynamic land-use systems in the world, with dramatic consequences for the provision of ecosystem services and the livelihood of people. Planning is a multifaceted activity with extensive experience in the management of these urbanization processes. However, our understanding of planning’s contribution to shaping urban land use, form and structure is still incomplete, with serious consequences for the efficacy of urban planning and land change models.

This international conference aims to bring together the community of scholars working on planning evaluation and urban modelling. The participants are offered the opportunity to present their current research and to discuss how theoretical developments, data sources, comparative studies and modelling approaches might advance the field.

The conference was financially supported by the CONCUR project and sustained by Swiss Federal Research Institute WSL.

concur

display_name: concur

land-change

display_name: land-change

landscape-planning

display_name: landscape-planning

urban-landscape

display_name: urban-landscape

urban-planning

display_name: urban-planning

education

en: Education and science

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: From Plans to Land Change: Dynamics of Urban Regions. Book of Abstracts


maintainer: Frank Techel

en: warning-regions danger-level snow european-alps avalanche-forecast

en: shape file warning regions Alps

en: Forecast avalanche danger level

media_type: text/csv

en: contains the highest forecast danger level (dangerLevelMax) for each day and warning region

mimetype: text/csv

en:
This dataset contains the data used in the publication by Techel et al., 2018 _Spatial consistency and bias in avalanche forecasts - a case study in the European Alps_ (Nat Haz Earth Syst Sci).
For details on the data please refer to this publication.
The dataset contains the following:
- shape files for the warning regions in the Alps
- highest forecast danger level for each warning region and day

avalanche-forecast

display_name: avalanche-forecast

danger-level

display_name: danger-level

european-alps

display_name: european-alps

warning-regions

display_name: warning-regions

en: Forecast avalanche danger level European Alps 2011 - 2015


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

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

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


maintainer: Anita C. Risch

en: grassland nitrification climate mineralization nutrient-network fertilization nitrogen herbivore soil ammonification global-change

en: Risch et al. 2020 - Raw data for publication "Global impacts of fertilization and herbivore removal on soil net nitrogen mineralization are modulated by local climate and soil properties"

en:
we assessed how the removal of mammalian herbivores (Fence) and fertilization with growth-limiting nutrients (N, P, K, plus nine essential macro- and micronutrients; NPK) individually, and in combination (NPK+Fence), affected potential and realized soil net Nmin across 22 natural and semi-natural grasslands on five continents. Our sites spanned a comprehensive range of climatic and edaphic conditions found across the grassland biome. We focused on grasslands, because they cover 40-50% of the ice-free land surface and provide vital ecosystem functions and services. They are particularly important for forage production and C sequestration. Worldwide, grasslands store approximately 20-30% of the Earth’s terrestrial C, most of it in the soil (Schimel, 1995; White et al., 2000).

Study sites and experimental design
The 22 sites contributing to this project are part of the Nutrient Network Global Research Cooperative (NutNet, https://nutnet.umn.edu/). Mean annual temperature across our 22 sites ranged from -4 to 22°C, mean annual precipitation from 252 to 1,592 mm, and elevations from 6 to 4,261 m above sea level (Fig. 1, Supplementary Table S1). Soil organic C varied from 0.8 to 7.8%, soil total N from 0.1 to 0.6%, and the soil C:N ratio from 9.1 to 21.5. Soil clay content spanned from 3.0 to 35%, and soil pH from 3.4 to 7.6 (Supplementary Table S2). Thus, the sites covered a wide range of environments in which grasslands occur (Fig. 1, Supplementary Table S1 & S2).
At each site, the effects of nutrient addition and herbivore removal were tested via a randomized-block design (Borer et al., 2014; Supplementary Fig. S1a). Three replicate blocks with 10 treatment plots each were established at each site, with the exception of the site at bldr.us, where only two blocks were established (Supplementary Fig. S1a). The 10 plots were randomly assigned to a nutrient or fencing treatment, but only a subset of four plots was used in the current study, each with a different treatment (see below; Supplementary Fig. S1a). All plots were 5 x 5 m and divided into four 2.5 x 2.5 m subplots (Supplementary Fig. S1b). Each subplot was further divided into four 1 x 1 m square sampling plots, one of which was set aside for soil sampling (Borer et al., 2014; Supplementary Fig. S1b). Plots were separated by at least 1 m wide walkways.
In this study, we collected data from the following four treatments: (i) untreated control plots (Control), (ii) herbivore removal plots (Fence), (iii) plots fertilized with N, P, K, plus nine essential macro and micronutrients (NPK), and (iv) plots with simultaneous fertilizer addition and herbivore removal (NPK+Fence; Supplementary Fig. S1a). The number of years of treatment differed among sites (2 – 9 years since start of treatment; Supplementary Table S1). For the nutrient additions, all sites applied 10 g N m-2 yr-1 as time-release urea; 10 g P m-2 yr-1 as triple-super phosphate; 10 g K m-2 yr-1 as potassium sulfate. A micro-nutrient mix (Fe, S, Mg, Mn, Cu, Zn, B, Mo, Ca) was applied at 100 g m-2 together with K in the first year of treatments but not thereafter.
The vertebrate herbivore removal treatment (Fence) was established by fencing two plots, one control and one NPK plot, within each of the blocks (Supplementary Fig. S1a). We designed the fences so that they would effectively exclude aboveground mammalian herbivores with a body mass of over 50 g (Borer et al., 2014). At the majority of sites, the height of the fences was 180 cm, and the fence design included wire mesh (1 cm holes) on the first 90 cm along with a 30 cm outward-facing flange stapled to the ground to exclude burrowing animals; climbing and subterranean animals may potentially still access these plots (Borer et al., 2014). For slight modifications in fence design at a few sites see Supplementary Table S3. While most sites only had native herbivores, a few sites (4) were also grazed by domestic animals (Supplementary Table S1).
Potential and realized soil net N mineralization, ammonification, nitrification and other soil properties
Each site participating in the study received a package containing identical material from the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) to be used for sampling and on-site N incubations. For the field incubation, we followed the protocol by Risch et al. (2015, 2019). Briefly, we drove a 5 x 15 cm (diameter x depth) steel cylinder 13.5 cm deep into the soil after clipping the vegetation at randomized locations in each plot. The top 1.5 cm of the cylinder remained empty to capture incoming N from run-off or deposition with a polyester mesh bag (mesh-size 250 µm) filled with 13.2 ± 0.9 g of acidic and alkaline exchanger resin (1:1 mixture; ion-exchanger I KA/ion-exchanger III AA, Merck AG, Darmstadt). The bag was fixed in place with a metal Seeger ring (Bruetsch-Rüegger Holding, Urdorf, Switzerland). We then removed 1.5 cm soil at the bottom of the cylinder and placed another resin bag to capture N leached from the soil column. The exchange resin was saturated with H+ and Cl- prior to filling the bags by stirring the mixture in 1.2M HCl for 1 h and then rinsing it with demineralized water until the electrical conductivity of the water reached 5 μS/cm. The cylinders were then re-inserted into the cored hole, level with the soil surface, and incubated for an average of 42 days (range 40 to 57days). The individual site coordinators chose the timing of incubation to start approximately six weeks prior to peak plant biomass production. All incubations were completed between February 2015 and January 2016 accounting for differences in growing season between northern and southern hemispheres. At the end of the incubation, the cylinders were re-collected and immediately shipped to WSL in an insulated box together with cold packs to halt further mineralization. Gloves were worn at all times to avoid contamination of the samples. Upon arrival at WSL, we extracted the resin bags and a 20 g subsample of sieved soil (4 mm) separately in a 100 ml PE-bottle with 80 ml 1 M KCl for 1.5 h on an end-over-end shaker and filtered through ashless folded filter paper (DF 5895 150, ALBET LabScience). We measured NO3- (colorimetrically; Norman & Stucki, 1981) and NH4+concentrations (flow injection analysis; FIAS 300, Perkin Elmer) on these filtrates.
At the start of the field incubation, we additionally collected two soil cores of 5 x 12 cm (diameter x depth) in each sampling plot and composited them to measure potential soil net Nmin, soil chemical and biological properties (see below). We also collected an additional sample (5 x 12 cm) to assess soil physical properties, which remained within the steel cylinder. Both ends were tightly closed with plastic caps. Cores were carefully packed to avoid further disturbance, and together with the composited soil samples, were shipped to the laboratory at WSL within a few days after collection.
From the composited samples, we extracted an equivalent of 20 g dry soil with KCl, as described above, and measured NO3- and NH4+concentrations. Realized soil net Nmin was then calculated as the difference between the inorganic N content of samples collected at the end of the incubation (plus N extracted from the bottom resin bag) and the N content at the beginning of the incubation; values were scaled to represent daily mineralization rates (mg N kg-1soil d-1; Risch et al., 2015). Realized soil net Nmin values represent an average period of 42 days prior to peak biomass, typically the highest period of biological activity, and not the entire year (Risch et al., 2019).
A second subsample of the composited sample was used to determine potential soil net Nmin in the laboratory (Risch et al., 2019). Briefly, we weighed duplicate samples (8 g dry soil) into 50-ml Falcon tubes. Soil moisture was brought to 60% of the field capacity of each plot, the Falcon tubes tightly closed and then incubated at 20°C for 42 days in a dark room. Every week the Falcon tubes were opened and ventilated. At the end of the incubation, the soil samples were extracted the same way as described above and NO3- and NH4+ was determined. Potential soil net Nmin was calculated as the difference between the N content before and after the incubation and scaled to represent daily values (mg N kg-1soil d-1). Using our NO3- and NH4+ measures we also calculated potential and realized soil net nitrification and soil net ammonification to be able to better understand the drivers of fertilization and herbivore removal effects on potential and realized soil net Nmin.
A third subsample of the composite soil sample was sieved (2 mm mesh) and microbial biomass (μg Cmic g-1 soil dry weight) was estimated by measuring the maximal respiratory response to the addition of glucose solution (4 mg glucose per g soil dry weight dissolved in distilled water; substrate-induced respiration method) on approximately 5.5 g of soil (Anderson & Domsch, 1978). The rest of the composited sample was dried at 65°C for 48 h, ground and sieved (2 mm mesh) to assess a series of soil chemical properties (Risch et al., 2019). We measured the percentage of clay as an indicator of soil texture (Gee & Bauder, 1986; Risch et al., 2019).
Statistical analyses
Potential and realized soil net Nmin were square root transformed to account for a highly skewed data distribution (yt = sign(y)*sqrt|y|; negative values in the data set impeded log transformation). To assess treatment effects on potential and realized soil net Nmin, we used linear mixed effects models (LMMs) fitted by maximum likelihood using the lme function from the nlme package (version 3.131.1; Pinheiro et al., 2016), R version 3.6.1; R Foundation for Statistical Computing. Treatment (Control, Fence, NPK, NPK+Fence) was a fixed factor, with site and block as random factors, where block was nested within site. We also tested for effects of time since start of treatments in preliminary analyses by adding total treatment years as an additional fixed factor. We did not find a significant effect of years of treatment, and thus dropped this variable from the models. The LMMs were corrected using varIdent if the homogeneity of variance criterion was not met (Pinheiro et al., 2016). To visualize our results, we calculated treatment effects using Cohens’ d statistic (Cohen, 1977; Koricheva et al., 2013). Note that calculating response ratios (or log response ratios) was not possible with our data, as we have both negative and positive values. We also fitted LMMs for potential and realized soil net ammonification and nitrification to gain more insight into how global change affects the processes underpinning potential and realized soil net Nmin. We also sqrt-transformed (see above) these dependent variables. Treatment was included as a fixed factor with random factors as described above. In addition, we assessed how potential and realized soil net Nmin were related to potential and realized soil net ammonification and nitrification, respectively. For this, we calculated site averages for each treatment separately. We then ran LMMs, with potential and realized soil net Nmin as the dependent variable, potential and realized soil net ammonification/nitrification as the independent ones. Site was included as a random factor.
Based on our previous work (Risch et al., 2019) and the existing literature (Schimel & Bennett, 2004; Liu et al., 2017), we developed a priori causal conceptual models of relationships among treatments, environmental drivers, and potential and realized soil net Nmin (Supplementary Fig. S2) to test with structural equation modelling (SEM) using a d-sep approach (Shipley, 2009; Lefcheck, 2016). The variables included in the model were long-term climatic conditions, specifically, site-level mean annual precipitation (MAP) and temperature of the wettest quarter (T.q.wet), plot-level soil texture (clay content) and soil microbial biomass. Mean annual precipitation and T.q.wet were obtained from WorldClim (Hijmans et al., 2005) (http://www.worldclim.org/) and together with the experimental treatments were predicted to directly affect soil properties and soil net Nmin (Supplementary Fig. S2). Soil clay content was, in turn, predicted to affect microbial biomass and soil net Nmin. Because we determined microbial biomass prior to incubating the samples in the laboratory or field, we assumed that the abundance of these microbes would be responsible for N process rates and not vice versa (Supplementary Fig. S2). We tested our conceptual model (Supplementary Fig. S2) using the piecewiseSEM package (version 2.0.2; Lefcheck, 2016) in R 3.4.0, in which a structured set of linear models are fitted individually. This approach allowed us to account for the nested experimental design, and overcome some of the limitations of standard structural equation models, such as small sample sizes (Shipley, 2009; Lefcheck, 2016). We used the lme function of the nlme package to model response variables, including site as a random factor. Good fit of the SEM was assumed when Fisher’s C values were non-significant (p > 0.05). For all significant interactions between covariates and experimental treatments detected in the SEMs, we calculated treatment effect sizes, i.e. the differences in potential or realized soil net Nmin between Control and treatments (Fence, NPK, NPK+Fence) and plotted these values against the climate or soil covariates. Finally, we fitted LMMs for the soil variables included in our SEMs, with treatment as the fixed factor, and with site and block as random factors, where block was nested within site.

format: XLS

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

Paper Citation:

Risch Anita C., Zimmermann, Stefan, Moser, Barbara, Schütz, Martin, Hagedorn, Frank, Firn, Jennifer, Fay, Philip A., Adler, Peter B., Biederman, Lori A., Blair, John M., Borer, Elizabeth T., Broadbent, Arthur A.D., Brown, Cynthia S., Cadotte, Marc W., Caldeira, Maria C., Davies, Kendi F., di Virgilio, Augustina, Eisenhauer, Nico, Eskelinen, Anu, Knops, Johannes M.H., MacDougall, Andrew S., McCulley, Rebecca L., Melbourne, Brett A., Moore, Joslin L., Power, Sally A., Prober, Suzanne M., Seabloom, Eric W., Siebert, Julia, Silveira, Maria L. , Speziale, Karina L., Stevens, Carly J., Tognetti, Pedro M., Virtanen, Risto, Yahdjian, Laura, Ochoa-Hueso, Raul (accepted). Global impacts of fertilization and herbivore removal on soil net nitrogen mineralization are modulated by local climate and soil properties. Global Change Biology

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

We assessed how the removal of mammalian herbivores (Fence) and fertilization with growth-limiting nutrients (N, P, K, plus nine essential macro- and micronutrients; NPK) individually, and in combination (NPK+Fence), affected potential and realized soil net Nmin across 22 natural and semi-natural grasslands on five continents. Our sites spanned a comprehensive range of climatic and edaphic conditions found across the grassland biome. We focused on grasslands, because they cover 40-50% of the ice-free land surface and provide vital ecosystem functions and services. They are particularly important for forage production and C sequestration. Worldwide, grasslands store approximately 20-30% of the Earth’s terrestrial C, most of it in the soil (Schimel, 1995; White et al., 2000).

ammonification

display_name: ammonification

climate

display_name: climate

fertilization

display_name: fertilization

global-change

display_name: global-change

grassland

display_name: grassland

herbivore

display_name: herbivore

mineralization

display_name: mineralization

nitrification

display_name: nitrification

nitrogen

display_name: nitrogen

nutrient-network

display_name: nutrient-network

soil

display_name: soil

en: Anthropogenic change and soil net N mineralization


staatsquote-des-kantons-zurich

title_for_slug: staatsquote-des-kantons-zurich

name: Finanzverwaltung des Kantons Zürich, Steuerung Finanzhaushalt

label: Regierungsratsbeschluss Nr. 373/2022

label: Geschäftsbericht & Rechnung (Teil III: Finanzbericht)

de: Staatsquote des Kantons Zürich ab 2008

de: Variabeln: 'gesamtausgaben' und 'bruttoinlandprodukt' in Tausend CHF.

de: Die Staatsquote entspricht den «konsolidierten Gesamtausgaben» in Prozent des kantonalen Bruttoinlandprodukts (BIP). Die «konsolidierten Gesamtausgaben» umfassen die Ausgaben (Aufwand ohne Abschreibungen, Einlagen in Bestandeskonti von Fonds im Eigen- und Fremdkapital, durchlaufende Beiträge und interne Verrechnungen) plus Bruttoinvestitionen. Die konsolidierten Gesamtausgaben werden durch die Eidgenössischen Finanzverwaltung (EFV) berechnet. Das BIP des Kantons Zürich wird vom Bundesamt für Statistik (BFS) berechnet. Beide Wirtschaftsindikatoren werden mit einer zeitlichen Verzögerung von zwei Jahren veröffentlicht. Vorliegend wird die Staatsquote des Kantons ohne Gemeinden ausgewiesen. Für die interkantonale Vergleichbarkeit müsste die Staatsquote des Kantons und seiner Gemeinden betrachtet werden, aufgrund der je nach Kanton unterschiedlichen Aufgabenteilungen zwischen Kanton und Gemeinden.

finanzkennzahlen

display_name: finanzkennzahlen

oeffentlichefinanzen

display_name: oeffentlichefinanzen

staatsfinanzen

display_name: staatsfinanzen

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

finanzverwaltung-kanton-zuerich

de: Finanzverwaltung Kanton Zürich

de: Der Kanton Zürich hat, nach dem Bund, den zweitgrössten öffentlichen Haushalt der Schweiz. Die Finanzverwaltung ist verantwortlich für die Planung, Führung und Überwachung dieses Finanzhaushalts. Sie erstellt das Budget und den Jahresabschluss der kantonalen Verwaltung und publiziert den Geschäftsbericht. Zudem übernimmt sie das operative Rechnungswesen und sichert mit der Tresorie die Zahlungsbereitschaft des Kantons. Die Finanzverwaltung bildet die finanzielle Schnittstelle zum Bund und den anderen Kantonen, beispielsweise für den nationalen Finanzausgleich.

political_level: canton

value: ZH-Kt Finanzverwaltung - DCAT Harvester

de: Staatsquote des Kantons Zürich


maintainer: Robert Pazúr

en: vegetation-indices cropland grassland switzerland sentinel-2 machine-learning habitat remote-sensing agriculture phenology

en: Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.6  (v1.0)

media_type: TIFF

en:
!!! Please check out the newer version in the repository !!!
Mask of unsealed surfaces of Switzerland based on 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.6

en: (current version) Cropland and grassland map of Switzerland (v.1.5)

media_type: geotiff

format: GeoTIFF

en: Cropland and grassland map of Switzerland  (v.1.0)

en: !!! Please check out the newer version in this repository !!! (1) cropland; (2) grassland; other LC classes are masked out from the map

en: GEE (Google Earth Engine) script (JavaScript) to derived the output map  (v1.0)

media_type: JS

en: !!! Please check out the newer version in the repository !!! The code used in Google Earth Engine to derive the cropland, grassland and shrubland map of Switzerland

en: (current version) Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.7 (v1.5)

en: (current version) Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.6 (v1.5)

en: Assuming that sealed surfaces have little or no phenological response we calculated a mask of unsealed surfaces based on the 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.6.

en: Cropland, grassland, and shrubland map of Switzerland (v1.0)

en: !!! Please check out the newer version in this repository !!! (1) cropland; (2) grassland; (3) shrubland; other LC classes are masked out from the map

en: Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.7 (v1.0)

en: !!! Please check out the newer version in this repository !!! Assuming that sealed surfaces have little or no phenological response we calculated a mask of unsealed surfaces based on the 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.7.

en: (current version) Cropland, grassland, and shrubland map of Switzerland (v.1.5)

en: GEE (Google Earth Engine) script (JavaScript) to derived the output map  (v1.5)

en: The code used in Google Earth Engine to derive the cropland, grassland and shrubland map of Switzerland. Compare to the previous version the newer version includes the shadow masking procedure which might be important in the mountainous areas.

en: We developed a map of cropland and grassland allocation for Switzerland based on several indices dominantly derived from Sentinel-2 satellite imagery captured over multiple growing seasons. The classification model was trained based on parcel-based data derived from landholder reporting. The mapping was conducted on Google Earth Engine platform using random forest classifier. Areas of high vegetation, shrubland, sealed surface and non-vegetated areas were masked out from the country-wide map. The resulting map has high accuracy in lowlands as well as mountainous areas.

agriculture

display_name: agriculture

cropland

display_name: cropland

habitat

display_name: habitat

machine-learning

display_name: machine-learning

phenology

display_name: phenology

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

vegetation-indices

display_name: vegetation-indices

education

en: Education and science

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: Cropland and grassland map of Switzerland based on Sentinel-2 data


schwermetallbelastung-des-bodens

title_for_slug: schwermetallbelastung-des-bodens

media_type: text/html

format: HTML

mimetype: text/html

fr: SPARQL Endpoint avec présélection du graphe

en: SPARQL Endpoint with graph preselection

de: SPARQL Endpoint mit Vorauswahl des Graph

media_type: application/sparql-query

format: SPARQL

mimetype: application/sparql-query

fr: Les données mesurées sont des moyennes des concentrations de métaux lourds relevées sur les 20 cm supérieurs du sol sur 100 sites d'observation à long terme de l'Observatoire national des sols (NABO).

de: Bei den Messdaten handelt es sich um Erhebungsmittelwerte von Schwermetallkonzentrationen in den obersten 20 cm des Bodens von rund 100 Dauerbeobachtungsstandorten der Nationalen Bodenbeobachtung NABO.

en: The measurement data are the surveyed mean values of heavy metal concentrations recorded in the top 20 cm of the soil in around 100 permanent monitoring sites operated by the Swiss National Soil Monitoring Network (NABO).

it: I dati misurati sono valori medi delle concentrazioni di metalli pesanti rilevate nei 20 cm dello strato superiore del suolo presso circa 100 siti di osservazione a lungo termine dell'Osservatorio nazionale dei suoli (NABO).

agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

en: Agriculture, forestry

it: Agricoltura, selvicoltura

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

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.

political_level: confederation

value: LINDAS DCAT Harvester BAFU

fr: Pollution du sol par les métaux lourds

de: Schwermetallbelastung des Bodens

en: Heavy Metal Soil Contamination

it: Carico di metalli pesanti nel suolo


en: meteorological-data antarctica turbulence blowing-snow micro-rain-radar mass-flux large-eddy-simulations drifting-snow eddy-covariance-measurements

en: Measurement data from snow particle counter at MRR site

media_type: zip-compressed folder of csv

en: Near-surface observations of drifting snow from a Snow Particle Counter (SPC) installed at the location of the Micro Rain Radar.

en: Simulation data for a situation with significant snow transport

en: Data from two LES-LSM simulations called Drift_1 and Drift_2, which reproduce the conditions observed at the S17 site on 11th January 2019, 00:40 to 00:50 UTC.

media_type: zip-compressed folder of text files (f90)

en: Source code of the large-eddy simulations coupled with a Lagrangian stochastic model (LES-LSM), available on GitLab.

en: Simulation data for a situation with negligible snow transport

en: Results from two LES-LSM simulations called NoDrift_1 and NoDrift_2, which reproduce the conditions observed at the S17 site on 12th January 2019, 05:40 to 05:50 UTC.

en: Measurement data from Micro Rain Radar (MRR)

media_type: NetCDF

en: Remote sensing data of blowing snow from a Micro Rain Radar (MRR).

en: Measurement data from micro-meteorological station

media_type: zip-compressed folder of ASCII files

en: Automatic in-situ measurements of micro-meteorology and snow transport

en: Readme

media_type: TXT

en: Meta data

en:
This dataset contains measurement and simulation data. The measurements characterize the standard meteorology, turbulence, and snow transport at the S17 site near Syowa Station in East Antarctica during an expedition in austral summer 2018/2019. Large-eddy simulations with sublimating particles provide additional insight into the latent and sensible heat exchange between snow and air in two example situations observed at the S17 site.

A part of the measurement data was recorded by an automatic measurement station from 10th January 2019 to 26th January 2019. This measurement station was equipped with standard meteorological sensors, a three-dimensional ultrasonic anemometer, an open-path infrared gas analyzer, a snow particle counter, an infrared radiometer for measurements of the surface temperature, and a sonic ranging sensor measuring changes in snow surface elevation.

At a horizontal distance of approximately 500 m, a Micro Rain Radar (MRR) was installed in a tilted configuration with an elevation angle of 7° for remote sensing of blowing snow between 25th December 2018 and 24th January 2019. In addition, near-surface in-situ measurements of snow transport were performed at the location of the MRR by deploying a snow particle counter from 27th December 2018 to 24th January 2019.

The simulations cover a 18 x 18 x 6 m³ domain and reproduce the steady-state conditions during a 10-min interval with significant snow transport and another 10-min interval with negligible snow transport. We provide the model source code and the post-processed simulation data, i.e., horizontally averaged quantities as a function of height and time.

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

drifting-snow

display_name: drifting-snow

eddy-covariance-measurements

display_name: eddy-covariance-measurements

large-eddy-simulations

display_name: large-eddy-simulations

mass-flux

display_name: mass-flux

meteorological-data

display_name: meteorological-data

micro-rain-radar

display_name: micro-rain-radar

turbulence

display_name: turbulence

education

de: Bildung, Wissenschaft

en: Meteorology and snow transport at S17 near Syowa, Antarctica, in austral summer 2018/2019


maintainer: Matthias Haeni

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

en: Site photo of the forest station (CLB)

media_type: image/jpeg

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

mimetype: image/jpeg

en: Data plot of the field station (CLF)

en: Data file.

en: Site aerial photo (Celerina)

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

en: Data plot of the forest station (CLB)

media_type: application/pdf

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

format: PDF

mimetype: application/pdf

en: Site photo of the field station (CLF)

en: Site phote of the field station from the side.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Celerina in Switzerland where one station is located within a natural coniferous forest stand (CLB) with Swiss pine (_Pinus cembra_; 210-250 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CLF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Celerina 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: Education and science

envidat

de: EnviDat: das Umwelt-Datenportal

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: Celerina, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


fr: transit trafic accord-sur-les-transports-terrestres air pollution-atmospherique

de: luftbelastung transitverkehr verkehr luft landverkehrsabkommen

en: SPARQL Endpoint with graph preselection

fr: Le projet "Suivi des mesures d’accompagnement Environnement" (SMA-E) mesure la pollution atmosphérique et sonore le long des axes de transit A2 et A13. Il doit permettre d'évaluer l'impact environnemental du trafic de marchandises sur les axes nord-sud. Dans le domaine de l'environnement, cette mesure permet de contrôler la mise en œuvre de la loi sur le transfert du trafic et l'efficacité des mesures d'accompagnement dans le cadre de la politique de transfert de la Confédération.

en: The project "Monitoring flankierende Massnahmen Umwelt" (MFM-U) measures air and noise pollution along the A2 and A13 transit axes. This is intended to show the environmental impact of freight traffic on the north-south axes. In this way, the implementation of the Transfer of Traffic Act and the effectiveness of the accompanying measures within the framework of the federal government's transfer policy are examined in the area of the environment.

de: Das Projekt "Monitoring flankierende Massnahmen Umwelt" (MFM-U) misst die Luft- und Lärmbelastung entlang der Transitachsen A2 und A13. Damit soll die Umweltbelastung des Güterverkehrs auf den Nord-Süd-Achsen aufgezeigt werden. Damit wird im Bereich Umwelt die Umsetzung des Verlagerungsgesetzes und die Wirksamkeit der flankierenden Massnahmen im Rahmen der Verlagerungspolitik des Bundes überprüft.

it: Il progetto "Monitoraggio delle misure di accompagnamento” (MMA-A) misura l'inquinamento atmosferico e acustico lungo gli assi di transito A2 e A13. L'obiettivo è quello di quantificare l'impatto ambientale del traffico merci sugli assi nord-sud, per verificare l’efficacia ambientale dell'attuazione della legge sul trasferimento del traffico e delle misure di accompagnamento nell'ambito della politica di trasferimento della Confederazione.

accord-sur-les-transports-terrestres

display_name: accord-sur-les-transports-terrestres

air

display_name: air

landverkehrsabkommen

display_name: landverkehrsabkommen

luft

display_name: luft

luftbelastung

display_name: luftbelastung

pollution-atmospherique

display_name: pollution-atmospherique

trafic

display_name: trafic

transit

display_name: transit

transitverkehr

display_name: transitverkehr

verkehr

display_name: verkehr

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

territory

en: Territory and environment

bundesamt-fur-umwelt-bafu

en: Federal Office for the Environment FOEN

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.

fr: Pollution atmosphérique  le long de l'A2 et de l'A13 - Moyennes annuelles - NO et NO2

de: Luftbelastung entlang der A2 und der A13 - Jahresmittelwerte - NO und NO2

en: Air pollution along the A2 and A13 - annual averages - NO and NO2

it: Inquinamento atmosferico lungo la A2 e la A13 - Medie annuali - NO e NO2


qualitat-der-badegewasser

title_for_slug: qualitat-der-badegewasser

name: Païvi Rinta, Sektion Hydr. Grundlagen Gewässerzustand

fr: Les relevés de la qualité des eaux de baignade permettent d’évaluer la qualité hygiénique des eaux à l’aide des indicateurs que sont E. coli et les entérocoques intestinaux. Les informations fournies servent à déterminer l’efficacité des mesures de protection des eaux, notamment si les stations d’épuration remplissent leur fonction.

en: The assessment of bathing waters is made on the basis of hygienic quality using E.coli and intestinal enterococci. They provide indications on the effectiveness of water protection measures and in particular the extent to which waste water treatment plants are fulfilling their function.

de: Die Erhebungen zur Badegewässerqualität beurteilen die hygienische Qualität der Gewässer anhand der E.Coli und intestinalen Enterokokken. Sie geben Hinweise darauf, wie gut Gewässerschutzmassnahmen greifen, und insbesondere wieweit die Abwasserreinigungsanlagen ihre Funktion erfüllen.

it: I rilevamenti per la determinazione della qualità delle acque di balneazione valutano la qualità igienica delle acque in base all’E. coli e agli enterococchi intestinali. Forniscono informazioni sull’incisività delle misure di protezione delle acque, in particolare sull’efficienza degli impianti di depurazione delle acque di scarico.

fr: Qualité des eaux de baignade

de: Qualität der Badegewässer

en: Bathing water quality

it: Qualità delle acque di balneazione


fr: Pourcentage de la population, des appartements et des bâtiments exposés au bruit de la circulation routière, ferroviaire et aérienne de jour et de nuit. Les données sont issues d'une modélisation effectuée à l'échelle nationale utilisant le modèle sonBASE.

de: Anteil der Bevölkerung, Wohnungen und Gebäude, die tagsüber und nachts durch Straßen-, Schienen- und Fluglärmbelastung ausgesetzt sind. Die Daten basieren auf flächendeckenden Modellberechnungen (sonBASE).

en: Percentage of the population, flats and buildings exposed to road, rail and air traffic noise during the day and night. The data is based on area-wide model calculations (sonBASE).

it: Percentuale della popolazione, degli appartamenti e degli edifici esposti al rumore del traffico stradale, ferroviario e aereo diurno e notturno. I dati sono derivati da un esercizio di modellazione nazionale utilizzando il modello sonBASE.

air-traffic-noise

display_name: air-traffic-noise

bruit-du-trafic-aerien

display_name: bruit-du-trafic-aerien

bruit-du-trafic-ferroviaire

display_name: bruit-du-trafic-ferroviaire

bruit-du-trafic-routier

display_name: bruit-du-trafic-routier

eisenbahnlarm

display_name: eisenbahnlarm

fluglarm

display_name: fluglarm

rail-traffic-noise

display_name: rail-traffic-noise

road-traffic-noise

display_name: road-traffic-noise

rumore-del-traffico-aero

display_name: rumore-del-traffico-aero

rumore-del-traffico-ferroviaro

display_name: rumore-del-traffico-ferroviaro

rumore-del-traffico-stradale

display_name: rumore-del-traffico-stradale

strassenverkehrslarm

display_name: strassenverkehrslarm

health

fr: Santé

de: Gesundheit

en: Health

it: Sanità

fr: Exposition au bruit du trafic

de: Lärmbelastung durch Verkehr

en: Traffic noise pollution

it: Esposizione al rumore del traffico


kof-beschaftigungsindikator

maintainer: KOF Datenservice

title_for_slug: kof-beschaftigungsindikator

fr: marche-de-lemploi emploi

de: arbeitsmarkt beschaftigung

en: employment labour-market

fr: KOF Indicateur de l'emploi

de: KOF Beschäftigungsindikator

en: KOF Employment Indicator

fr: Le KOF indicateur de l’emploi est calculé à partir des enquêtes conjoncturelles trimestrielles du KOF. Dans le cadre de ses enquêtes, le KOF interroge des entreprises privées de Suisse sur leur appréciation du nombre actuel de leurs salariés et sur leur intention de modifier ses effectifs dans les trois mois qui suivent.

de: Der KOF Beschäftigungsindikator wird aus den vierteljährlichen Konjunkturumfragen der KOF berechnet. Im Rahmen dieser Umfragen befragt die KOF privatwirtschaftliche Unternehmen in der Schweiz, wie sie ihren gegenwärtigen Bestand an Beschäftigten beurteilen und ob sie diesen in den nächsten drei Monaten verändern wollen.

en: The KOF Employment Indicator is calculated on the basis of the quarterly KOF Business Tendency Surveys. As part of these surveys, the KOF asks private businesses in Switzerland how they consider their current staffing levels to be and whether they intend to change them over the coming three months.

en: Data description

de: Datenbeschreibung

fr: Description des données

arbeitsmarkt

display_name: arbeitsmarkt

beschaftigung

display_name: beschaftigung

emploi

display_name: emploi

employment

display_name: employment

labour-market

display_name: labour-market

marche-de-lemploi

display_name: marche-de-lemploi

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito

kof-konjunkturforschungsstelle

fr: KOF Centre de recherches conjoncturelles

de: KOF Konjunkturforschungsstelle

en: KOF Swiss Economic Institute

it: KOF Centro di ricerca congiunturale

fr: Le KOF, Centre de recherches conjoncturelles, fournit des informations tangibles dans le domaine de la recherche économique et conjoncturelle. Il établit une multitude de prévisions et d’indicateurs utiles à l’observation de la conjoncture. Sa base de données, issue d’enquêtes menées auprès des entreprises, est unique en Suisse. Ces données permettent au KOF de générer divers indicateurs (baromètre, indicateur de l’emploi, indicateur bancaire), qui reflètent le climat de l’économie suisse. Les résultats de ces enquêtes sont évalués chaque trimestre et communiqués au public, tout comme les prévisions conjoncturelles. Le KOF analyse également l’activité d’innovation des entreprises suisses, effectue des études sur les dépenses de santé et commente les derniers développements de l’économie. Il participe aussi (en collaboration avec le centre Ifo de Munich) à l’élaboration des prévisions conjoncturelles allemandes (« Gemeinschaftsdiagnose »), lesquelles servent de base au gouvernement allemand en ce qui concerne l’évolution future de l’économie.

en: KOF delivers profund insight into the field of Economic Research. Next to conducting surveys in all branches of the Swiss economy, it also creates forecasts and indicators for business cycle analysis. KOF's data pool of business surveys is unique in Switzerland. KOF uses these data sets to mirror the economic situations and moods of Swiss companies through the generation of indicators. The KOF Economic Barometer, KOF Employment Indicator, KOF Business Situation, etc., are crucial for assessing economic developments in Switzerland. Many of these surveys are carried out monthly and results are evaluated quarterly to be presented to the public. KOF also analyzes the innovation of Swiss companies, provides studies on health issues and comments on current economic developments. KOF is also (together with the Ifo Institute in Munich) involved in the joint economic forecast in Germany, which is used by the German Government as a directional measure of future economic development.

de: Das KOF Institut liefert fundierte Informationen im Bereich der Wirtschafts- und Konjunkturforschung. Sie erstellt eine Vielzahl von Prognosen und Indikatoren zur Konjunkturbeobachtung. Ihr Datenpool aus Unternehmensbefragungen ist einmalig in der Schweiz. Aus diesen Daten generiert die KOF verschiedene Indikatoren (KOF Konjunkturbarometer, KOF Beschäftigungsindikator, KOF Geschäftslageindikator, u.a.), die ein Stimmungsbild der Schweizer Wirtschaft wiedergeben. Ihre Umfrageresultate wertet sie vierteljährlich aus und stellt sie der Öffentlichkeit vor, ebenso ihre Konjunkturprognosen. Sie analysiert aber auch die Innovationstätigkeit Schweizer Unternehmen, liefert Studien zum Arbeitsmarkt, den Gesundheitsausgaben und kommentiert aktuelle wirtschaftliche Entwicklungen. So ist die KOF auch (zusammen mit dem ifo Institut in München) an der Gemeinschaftsdiagnose in Deutschland beteiligt, die der deutschen Regierung als Richtmass für die zukünftige wirtschaftliche Entwicklung dient.

it: l KOF fornisce informazioni approfondite in materia di ricerca economica e congiunturale, producendo svariati indicatori e previsioni per il monitoraggio congiunturale. Il pool di dati derivante da indagini tra le aziende è unico in Svizzera. A partire da questi dati, il KOF genera diversi indicatori (barometro congiunturale, indicatore di occupazione, situazione commerciale, e così via) che riflettono la realtà dell'economia svizzera. Valuta trimestralmente i risultati delle indagini e li presenta al pubblico, unitamente alle previsioni congiunturali. Ma il KOF analizza anche l'attività di innovazione delle imprese svizzere, svolge studi sulla spesa sanitaria o commenta gli ultimi sviluppi economici. Il KOF, inoltre (insieme all'Istituto ifo di Monaco di Baviera) partecipa alla previsione congiunta in Germania, che il governo tedesco utilizza come riferimento per gli sviluppi economici futuri.

value: KOF Harvester


kof-business-situation-indicator

title_for_slug: kof-business-situation-indicator

fr: situation-des-affaires suisse

de: geschaftslageindikator schweiz

fr: KOF Indicateur de la situation des affaires

de: KOF Business Situation Indicator

en: KOF Geschäftslageindikator

fr: The KOF Business Situation Indicator is based on over 4,500 Swiss enterprise respondents. Each month, a survey is conducted among companies active in industry, retail, construction, project engineering as well as financial and insurance services. Companies in hotel and catering, wholesale and other services are interviewed in the first month of every quarter.

de: Die KOF Geschäftslage basiert auf mehr als 4500 Meldungen von Unternehmen in der Schweiz. Monatlich werden Unternehmen in den Wirtschaftsbereichen Industrie, Detailhandel, Baugewerbe, Projektierung sowie Finanz- und Versicherungsdienstleistungen befragt. Unternehmen im Gastgewerbe, im Grosshandel und in den übrigen Dienstleistungen werden vierteljährlich, jeweils im ersten Monat eines Quartals, befragt.

en: L’indicateur de la situation des affaires du KOF se fonde sur plus de 4500 informations d’entreprises de Suisse. Chaque mois, les entreprises des secteurs de l’industrie, du commerce de détail, du bâtiment, des bureaux d’études et des services financiers et assurantiels sont interrogées. Les entreprises de l’hôtellerie, du commerce de gros et des autres services font l’objet d’une enquête trimestrielle, à chaque fois le premier mois d’un nouveau trimestre.

bussiness-situation

display_name: bussiness-situation

economics

display_name: economics

geschaftslageindikator

display_name: geschaftslageindikator

schweiz

display_name: schweiz

situation-des-affaires

display_name: situation-des-affaires

suisse

display_name: suisse

switzerland

display_name: switzerland

national-economy

it: Economia


kof-economic-sentiment-indicator

title_for_slug: kof-economic-sentiment-indicator

fr: KOF Indice du climat économique

en: KOF Economic Sentiment Indicator

de: KOF Economic Sentiment Indicator

fr: Le KOF Indice du climat économique pour la Suisse (KOF Economic Sentiment Indicator) se base sur les résultats d’enquêtes conjoncturelles du KOF et de celle menées auprès des consommateurs par le Secrétariat d’État à l’économie (SECO). La méthode de calcul des indices pour la Suisse s’appuie sur la méthodologie de la Commission européenne. La Commission européenne calcule de cette manière les indices pour tous les pays membres de l’UE ainsi que pour différents agrégats, tels que l’UE dans son ensemble ou la zone euro.

de: Der KOF Economic Sentiment Indicator für die Schweiz basiert auf den Konjunkturumfragen der KOF und der Konsumentenbefragung des Staatssekretariats für Wirtschaft (SECO). Die Berechnungsmethode der Indikatoren für die Schweiz lehnt sich an die Methodik der EU-Kommission an. Die EU-Kommission berechnet auf diese Weise Indikatoren für alle Mitgliedsländer der EU sowie für verschiedene Aggregate, etwa der EU insgesamt oder den Euro-Raum.

en: The KOF Economic Sentiment Indicator for Switzerland is based on the results of the KOF Business Tendency Surveys and the Consumer Confidence Survey conducted by the State Secretariat for Economic Affairs (SECO). The calculation method used for the Swiss indicators follows the method employed by the EU Commission to calculate indicators for all EU member states as well as various aggregates, for instance total EU or Euro area.

climat-economique

display_name: climat-economique

economic-sentiment

display_name: economic-sentiment

okonomische-stimmung

display_name: okonomische-stimmung


kof-konjunkturbarometer

title_for_slug: kof-konjunkturbarometer

fr: conjoncture suisse

de: schweiz konjunktur vorlaufindikator

en: business-cycle leading-indicator switzerland fli

fr: KOF Baromètre conjoncturel

de: KOF Konjunkturbarometer

en: KOF Economic Barometer

fr: Depuis les années 70, le KOF publie un indicateur phare pour l’économie suisse, le baromètre conjoncturel, lequel prévoit l’évolution de la conjoncture suisse dans un avenir proche. La méthode de calcul a été révisée en 1998 puis en 2006. La dernière révision a eu lieu en 2014.

de: Seit den 1970er Jahren veröffentlicht die KOF einen vorlaufenden Sammelindikator, das Konjunkturbarometer, welches anzeigt, wie sich die Schweizer Konjunktur in der nahen Zukunft entwickeln dürfte. Die Methodik wurde 1998 revidiert, dann nochmals 2006. Die letzte umfassende Revision erfolgte im Jahr 2014.

en: Since the 1970s, the KOF Swiss Economic Institute is publishing a leading composite indicator, the KOF Economic Barometer, predicting how the Swiss economy should perform in the near future. The methodology was overhauled in 1998 and again in 2006. The last thorough revision was conducted in 2014.

business-cycle

display_name: business-cycle

conjoncture

display_name: conjoncture

fli

display_name: fli

konjunktur

display_name: konjunktur

leading-indicator

display_name: leading-indicator

vorlaufindikator

display_name: vorlaufindikator


globale-konjunkturbarometer

title_for_slug: globale-konjunkturbarometer

fr: Baromètres conjoncturels mondiaux

en: Global Economic Barometers

de: Globale Konjunkturbarometer

fr: Les Baromètres conjoncturels mondiaux sont un système d’indicateurs destiné à l’analyse en temps réel de l’évolution conjoncturelle mondiale. Il s’agit d’un projet de coopération du KOF Centre de recherches conjoncturelles de l’ETH Zürich et de la Fundação Getúlio Vargas (FGV) de Rio de Janeiro (Brésil). Le système comprend deux sous- indicateurs : un indicateur coïncident et un indicateur avancé.

en: The Global Economic Barometers are a system of indicators that enables a timely analysis of global economic development. They represent a collaboration between the KOF Swiss Economic Institute and Fundação Getúlio Vargas (FGV) based in Rio de Janeiro, Brazil. The system consists of two indicators: a coincident indicator and a leading indicator.

de: Die globalen Konjunkturbarometer sind ein Indikatorensystem für die zeitnahe Analyse der globalen Konjunkturentwicklung. Sie sind ein Kooperationsprojekt der KOF Konjunkturforschungsstelle der ETH Zürich und der Fundação Getúlio Vargas (FGV) in Rio de Janeiro, Brasilien. Das System besteht aus zwei Teilindikatoren: einem Koinzidenz- und einem Frühindikator.

economie-mondiale

display_name: economie-mondiale

global-economy

display_name: global-economy

weltwirtschaft

display_name: weltwirtschaft


maintainer: OGD-Koordinationsstelle St.Gallen

de: wahlen auszahlungen real-time abstimmungen

de: csv

de: Aktuelle Wahl- bzw. Abstimmungsresultate Kanton St.Gallen (csv)

license: CC BY

de: json

media_type: application/json

de: Aktuelle Wahl- bzw. Abstimmungsresultate Kanton St.Gallen (json)

format: JSON

mimetype: application/json

de: Der Datensatz bildet eine Schnittstelle zu wab.sg.ch und liefert während des Wahl- oder Abstimmungssonntags die Auszählungen der Wahl- und Abstimmungsresultate des Kantons St.Gallen in Echtzeit. Der Datensatz wird alle 15 Minuten aktualisiert.Anmerkung: Zwischen Wahlen und Abstimmungen kann es sein, dass die Schnittstelle keine Daten liefert, da die neuen Wahlen und Abstimmungen bereits aufgeschaltet werden.

abstimmungen

display_name: abstimmungen

auszahlungen

display_name: auszahlungen

real-time

display_name: real-time

wahlen

display_name: wahlen

politics

fr: Politique

de: Politik

en: Politics

it: Politica

staatskanzlei-kanton-st-gallen

de: Staatskanzlei Kanton St.Gallen

de:
Die Staatskanzlei ist als Stabsstelle von Kantonsrat und Regierung die zentrale Schaltstelle in der kantonalen Staatsverwaltung. Die Staatskanzlei nimmt vielfältige Unterstützungs- und Koordinationsaufgaben wahr und verbindet die verschiedenen Akteure miteinander. Ob beratend, koordinierend oder federführend in gewissen Sachbereichen, die Staatskanzlei muss in ihrer Rolle immer durch Qualität, Verlässlichkeit und dienstleistungsorientierte Zusammenarbeit überzeugen. Dies bringt die Vision der Staatskanzlei auf den Punkt:

«Wir verbinden und überzeugen. Ihre Staatskanzlei.»

value: DCAT Staatskanzlei Kanton St.Gallen


de: wahlen resultate api abstimmungen real-time

de: Schnittstelle zum Portal "Wahlen & Abstimmungen" des Kantons St.Gallen (wab.sg.ch) (json)

de: Schnittstelle zum Portal "Wahlen & Abstimmungen" des Kantons St.Gallen (wab.sg.ch) (csv)

de: Das Portal "Wahlen & Abstimmungen" des Kantons St.Gallen (wab.sg.ch) bietet eine Schnittstelle an, um auf die verfügbaren Abstimmungs- und Wahlresultate zugreifen zu können. Damit kann das gesamte Archiv oder auch die aktuellen Abstimmungs- oder Wahlresultate in Echtzeit abgefragt und genutzt werden.Unter folgendem Link ist die Nutzung der API-Schnittstelle ausführlich erklärt:https://github.com/OneGov/onegov-cloud/blob/master/docs/api/election_day/open_data_de.md

api

display_name: api

resultate

display_name: resultate


geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

de: kataster-der-belasteten-standorte kbs ablagerungsstandort betriebsstandort unfallstandort altlastenkataster verdachtsflachenkataster altlast

label: Geometadaten Kanton Zürich: GeoLion

label: geocat.ch permalink

spatial: Kanton Zürich

de: Download via GIS-Browser

de: Der Kataster der belasteten Standorte (KbS) zeigt Standorte, bei denen feststeht oder mit grosser Wahrscheinlichkeit zu erwarten ist, dass sie mit Abfällen belastet sind (Art. 32c Abs. 2 des Umweltschutzgesetzes und Art.5 und 6 der Altlasten-Verordnung). Es wird zwischen Ablagerungsstandorten (Deponien, Schüttungen, etc), Betriebsstandorten und Unfallstandorten unterschieden.

name:
Amt für Abfall, Wasser, Energie und Luft
             - Abteilung Abfallwirtschaft und Betriebe

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

de: ÖREB - Kataster der belasteten Standorte (KbS)


de: resultate wahlen abstimmungen

de: csv

de: Wahlen und Abstimmungen Kanton St.Gallen (csv)

de: json

de: Wahlen und Abstimmungen Kanton St.Gallen (json)

de: Wahl- und Abstimmungsresultate in den Jahren 2002-2022 aus dem Archiv des Portals wab.sg.ch des Kantons St.Gallen.


de: Kataster der belasteten Standorte (KbS)


mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

de: tiefbau strassen verkehr baustellen verkehrsbehinderung

de: Die vier Strassenregionen des Tiefbauamtes aktualisieren laufend die Informationen über bestehende und zukünftige Baustellen.

name:
Tiefbauamt
             - Stab

de: Baustellen Kantonsstrassen


media_type: WMS

de: Hinweiskarte für anthropogene Böden

format: WMS

name:
Amt für Landschaft und Natur
               - Fachstelle Bodenschutz

de: WMS Hinweiskarte für anthropogene Böden (OGD)


media_type: WFS

de: Ambrosia Beobachtungen

format: WFS

name:
Amt für Abfall, Wasser, Energie und Luft
               - Abteilung Abfallwirtschaft und Betriebe

de: WFS Ambrosia Beobachtungen


de: Enthält alle flächigen Lebensraum- und pflanzensoziologischen Vegetationskartierungen. Die Geodaten dieses Dienstes sind enthalten im WFS der kantonalen Naturschutzthemen

name:
Amt für Landschaft und Natur
               - Fachstelle Naturschutz

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

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.

de: WMS Lebensraum- und Vegetationskartierungen


de: NO2-, PM10-, PM2.5- und Russ (BC)-Immissionen im Kanton Zürich für die Zeitstände 2015, 2020 und 2030. Es handelt sich dabei um Jahresmittelwerte in 20m x 20m räumlicher Auflösung.

name:
Amt für Abfall, Wasser, Energie und Luft
               - Abteilung Luft, Klima und Strahlung

de: WMS Immissionen (Luftqualität)


de: Dieser WMS beinhaltet die Standorte der Kandelaber im Kanton Zürich entlang Kantonsstrassen, kantonalen Hochleistungsstrassen (inkl. Rampen) und der Glattalbahn mit Informationen zu Status Bauart und Kandelabernummer.

name:
Tiefbauamt
               - Stab

de: WMS Beleuchtung


de: Grundwasserkarte Hochwasserstand

name:
Amt für Abfall, Wasser, Energie und Luft
               - Abteilung Gewässerschutz

de: WMS Grundwasserkarte Hochwasserstand


de: Die Abflussprozesskarte zeigt die Flächen der dominanten Abflussprozesse, hortonscher Oberflächenabfluss, Sättigungsoberflächenabfluss, laterale unterirdische Entwässerung, Drainagen und Tiefenversickerung. In einem zweiten Layer sind Flächen dargestellt, die bei intensiven Starkniederschlägen zu schnellem Oberflächenabfluss neigen (potentielle HOF-Flächen).

name:
Amt für Abfall, Wasser, Energie und Luft
               - Abteilung Wasserbau

de: WMS Abflussprozesskarte


de: Naturgefahrenkarte - Wassertiefenkarten - Intensitätsflächen

de: WMS Naturgefahrenkarte - Intensitätsflächen


de: Wild-Karte oder Topographische Karte des Kantons Zürich 1:25000

name:
Amt für Raumentwicklung
               - Geoinformation

de: WMS Historische Karte J. Wild (~1850)


wfs-grundwasserkarte-hochwasserstand

title_for_slug: wfs-grundwasserkarte-hochwasserstand

de: WFS Grundwasserkarte Hochwasserstand


de: Hauptstrassen nach Durchgangs- und Siganlisationsverordnung

de: WMS Strassennetz: Haupt- und Nebenstrassen


wms-oberflachenabfluss-ogd

title_for_slug: wms-oberflachenabfluss-ogd

de: Oberflächenabfluss

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

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.

de: WMS Oberflächenabfluss (OGD)


de: Die Haltestellen des öffentlichen Verkehrs wurden im Laufe des Jahres 1997 in Zusammenarbeit mit dem ZVV, dem Tiefbauamt, den regionalen Verkehrsbetrieben, der Post und dem GIS-Zentrum erfasst. Die laufende Aktualisierung geschieht durch die VBZ.

de: WMS Haltestellen des öffentlichen Verkehrs


de: Das Strassenenetz visualisiert nach Strassentypisierung Richtplan: Hochleistungsstrassen, Hauptverkehrsstrassen und Regionale Verbindungsstrassen und die wichtigsten geplanten Strassen.

de: WMS Strassennetz: Strassentypisierung nach Richtplan:


gewasser-okomorphologie

title_for_slug: gewasser-okomorphologie

de: Mit dem Bau von Siedlungen und Verkehrswegen sowie der Intensivierung der Landwirtschaft wurde der Raum der Fliessgewässer in den vergangenen Jahrzehnten zunehmend eingeengt. Umfangreiche bauliche Massnahmen veränderten den natürlichen Lauf der Bäche, um Infrastruktur und landwirtschaftliche Kulturen vor Schäden durch Hochwasser zu schützen. Diese Verbauungen beeinträchtigen vielerorts die ökologische Funktionsfähigkeit der Gewässer. Damit ein Gewässer seine Funktion als Lebensraum erfüllen kann, braucht es nicht nur eine gute Wasserqualität, sondern auch naturnahe morphologische und hydrologische Bedingungen. Die flächendeckende Ersterhebung der Daten fand zwischen 1997 und 1999 statt. 2005 wurde eine Teilrevision von rund 500 km gemacht. Zwischen 2009 und 2012 wurde für rund 1500 km eine Neuerhebung im Feld durchgeführt. Für die übrigen rund 2200 km wurden die Daten der Ersterhebung auf das aktuelle Gewässernetz übertragen. Im Zuge der Umstellung des Gewässernetzes auf Daten der amtlichen Vermessung wurden 2014 auch die Ökomorphologiedaten auf die amtlichen Vermessungsdaten übertragen. Ab 2015 werden die Daten laufend nachgeführt. Im Jahr 2019 wurden zusätzlich zu den Fliessgewässern auch die Seeufer bzgl. der Ökomorphologie erhoben und beurteilt.

de: Gewässer-Ökomorphologie (OGD)


de: Dieser Datensatz enthält die durch die KaPo verfügten Tempo30- und Begegnungszonen im Kanton Zürich, ausgenommen die Städte Zürich und Winterthur. Die Karte sagt nichts darüber aus, wann und ob die Verkehrsanordnung umgesetzt wurde.

name:
Amt für Mobilität
               - Mobilitätsentwicklung und -steuerung

de: WFS Tempo30- und Begegnungszonen


wfs-klimamodell-zh-planhinweiskarten

title_for_slug: wfs-klimamodell-zh-planhinweiskarten

de: Die Planhinweiskarten (PHK) stellen die planerische Inwertsetzung der im Projekt erzeugten Modelldaten/Klimaanalysekarten dar. Sie sind die zentrale Basis für Entscheidungsprozesse rund um die klimagerechte räumliche Entwicklung.

de: WFS Klimamodell ZH: Planhinweiskarten


de: Gemeindegrenzen in Übersichtsplangenauigkeit. Es stehen drei Datensätze zur Verfügung: Gemeinden: Offizieller Verlauf der Gemeindegrenzen, d.h. die Grenze der Stadt Zürich verläuft durch den Zürichsee, die Grenzen der übrigen Zürichsee- und der Greifenseegemeinden verlaufen entlang der Seeufer. Gemeinde-, Bezirks- und Kantonsgrenzen: Anhand dieser Linienversion können für kartografische Zwecke Gemeinde-, Bezirks- und Kantonsgrenzen sowie Grenzen auf Seeflächen unterschieden werden. Gemeinden mit Berücksichtigung von Seen: In dieser Variante sind Zürich-, Greifen-, Pfäffiker-, Chatzen- und Türlersee voll ausgespart.

de: WFS Gemeindegrenzen 1:5000


de: Im WMS werden die Ausnahmetransportrouten des Kantons Zürich dargestellt. Es werden die Routen, die Werke und allfällige Einschränkungen dargestellt. Das TBA pflegt im Auftrag des AFV die Daten der kantonalen Ausnahmetransportrouten. Es wird zwischen Typ 1 und Typ 2 unterschieden. Kennzahlen Ausnahmetransportrouten Typ 1: - Lichte Höhe min. 5.20 m - Lichte Breite min. 7.50 m - Totalgew. max. 480 t - Achslast max. 30 t Kennzahlen Ausnahmetransportrouten Typ 2: - Lichte Höhe min. 4.80 m - Lichte Breite min 6.50 m - Totalgew. max. 240 t - Achslast max. 20 t Die Attribute der Ausnahmetransportrouten werden auf dem Datensatz des Strassennetzes gepflegt.

de: WMS Ausnahmetransportrouten


de: Orthofoto 1981

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WMS Orthofoto 1981 (OGD)


wms-jagdreviere

title_for_slug: wms-jagdreviere

de: Jagdreviere Kanton Zürich.

name:
Amt für Landschaft und Natur
               - Fischerei- und Jagdverwaltung

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.

de: WMS Jagdreviere


de: Höhendaten, abgeleitet von LiDAR-Daten (2017 Bund, 2014 ZH): Digitales Terrainmodell (DTM) Relief (Terrainschummerung/Hillshade) des Digitalen Terrainmodells (DTM Relief) Digitales Oberflächenmodell (DOM) Relief (Oberflächenschummerung/Hillshade) des Digitalen Oberflächenmodells (DOM Relief) Isohypsen 1m Isohypsen 5m Isohypsen 10m Für die aktuellste Version der genannten Layer bleibt der Layer-Name konstant: dom, dtm, dtm_relief, dom_relief, hoehenlinien1, hoehenlinien5, hoehenlinien10 Zusätzlich zur aktuellsten Version sind für DOM, DTM, DOM Relief und DTM Relief die älteren Versionen als Layer verfügbar. Im Moment ist die aktuellste Version aus dem Jahr 2017/2018 (Befliegung Bund), die ältere Version aus dem Jahr 2014 (Befliegung Kanton Zürich).

de: WMS Höhendaten, abgeleitet von LiDAR-Daten (OGD)


de: Tagesaktuelle Baustellen auf dem Kantonsstrassennetz. Die vier Unterhaltregionen des Tiefbauamtes aktualisieren laufend die Informationen über bestehende und zukünftige Baustellen. Die Kommunikationsabteilung der Baudirektion des Kantons Zürich ist Ansprechpartner bei Fragen zu den Baustellen (http://www.bd.zh.ch/internet/baudirektion/de/service/nav/service/medien.html).

de: WMS Baustellen Kantonsstrassen


de: Waldareal im Kanton Zürich

name:
Amt für Landschaft und Natur
               - Abteilung Wald

de: WFS Waldareal


de: Naturgefahrenkarte - Wassertiefenkarten - Wassrtiefenflächen

de: WMS Naturgefahrenkarte - Wassertiefenflächen


de: Gewässerschutzkarte

de: WFS Gewässerschutzkarte


wms-offentliche-oberflachengewasser

title_for_slug: wms-offentliche-oberflachengewasser

de: Öffentliche Oberflächengewässer, Gewässerraum, Wasserrechte

de: WMS Öffentliche Oberflächengewässer


de: Web Map Service Strassenlärm-Emissionen zur Darstellung der Lärmquellen.

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WMS Strassenlärm


wms-zustandigkeiten-abteilung-wasserbau

title_for_slug: wms-zustandigkeiten-abteilung-wasserbau

de: Zuständigkeiten der Abteilung Wasserbau, Sektionen 'Gewässerunterhalt', 'Beratung und Bewilligung' (Wasserbauanliegen, Erstberatung und Baugesuche), Planung' (Gewässerraumfestlegung und raumplanerische Geschäfte) und 'Gewässernutzung' (Bewilligungen Stehgewässer).

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.

de: WMS Zuständigkeiten Abteilung Wasserbau


de: Dieser Datensatz enthält die durch die KaPo verfügten Tempo30- und Begegnungszonen im Kanton Zürich, ausgenommen die Städte Zürich und Winterthur. Die Karte sagt nichts darüber aus, wann und ob die Verkehrsanordnung umgesetzt wurde.

de: WMS Tempo30- und Begegnungszonen


de: WMS der Teilobjektperimeter Lichte Wälder gemäss Aktionsplan

de: WMS der Objekte Lichte Wälder


de: Stromnetzgebiete der Netzbetreiber im Kanton Zürich. Flächendeckende Zuteilung, wo möglich parzellenscharf.

name:
Amt für Abfall, Wasser, Energie und Luft
               - Abteilung Energie

de: WMS Stromnetzgebiete