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

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

envidat

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

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

en:
Resource Title: Meteo_Kueblis
    Size: 674638 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/398c7a10-d1bf-4fd3-b7a9-8175843077d7/download/kub_meteo.csv
    Description: Snow and meteo data from automatic sensors from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en:
Resource Title: Profiles_WFJ
    Size: 2365 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/8a7318b9-571d-4da9-9686-2330bf0f373a/download/wfj_prof.csv
    Description: Snow profiles data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en:
Resource Title: Meteo_Klosters
    Size: 697178 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/0ba3714e-3caa-47d3-8b8c-c235fc57760e/download/klo_meteo.csv
    Description: Snow and meteo data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en:
Resource Title: Manual profiles
    Size: 4065671 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/f7ac1de9-3b24-47fa-9f67-cd6560674a18/download/profiles.zip
    Description: Data of the traditional manual profiles for the locations Weissfluhjoch, Klosters and Küblis. For the location of Küblis there are no traditional manual profile data.  We provided the data as both PDF and .CAAML format (See https://niviz.org/  or http://caaml.org/Schemas/V5.0/Profiles/SnowProfileIACS/CAAMLv5_SnowProfileIACS.pdf). Moreover, we added LWC and density profiles when available (all locations).

en:
Resource Title: day_Laret
    Size: 27183 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/3af4ec59-d2ff-425e-ba49-996cd5a85247/download/lar_day.csv
    Description: Daily data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en:
Resource Title: day_WFJ
    Size: 71919 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/01d5ba5c-4734-43b0-b1cd-68e97e0fd711/download/wfj_day.csv
    Description: Daily data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en:
Resource Title: day_Klosters
    Size: 28691 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/40726e6f-f175-4033-8df7-526e42cdc266/download/klo_day.csv
    Description: Daily data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en:
Resource Title: Obs_Kueblis
    Size: 10744 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/ba8b38d2-fcc3-4345-b763-4b618e49836f/download/kub_obs.csv
    Description: Daily observer data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en:
Resource Title: Prof_Laret
    Size: 3424 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/d18ef060-e61f-4196-82ad-859e3faa1c9b/download/lar_prof.csv
    Description: Profile data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en:
Resource Title: GNSS_kueblis
    Size: 17196 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/973a7cde-cf6e-484e-8da1-a2da1de4fc49/download/kub_gnss.csv
    Description: GNSS derived SWE, LWC and HS from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-20

en:
Resource Title: GNSS_laret
    Size: 15587 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/0a95d946-3fd0-4d83-bfb9-4fdcb210a0d3/download/lar_gnss.csv
    Description: GNSS derived data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en:
Resource Title: Meteo_LAR
    Size: 2994700 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/e582db3a-a0ba-4527-9c2f-ca961562c317/download/lar_meteo.csv
    Description: Snow and meteo data from automatic sensors for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en:
Resource Title: GNSS_WFJ
    Size: 54679 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/f791ca79-0c9a-4055-9989-d5176e222935/download/wfj_gnss.csv
    Description: GNSS derived SWE, HS, and LWC for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en:
Resource Title: Obs_Klosters
    Size: 13499 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/9bb74e8a-d19b-49ca-aecf-feed84c3e324/download/klo_obs.csv
    Description: Daily observer data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en:
Resource Title: day_Kueblis
    Size: 28335 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/df76c91e-b71e-4441-a905-31b32b8782fb/download/kub_day.csv
    Description: Daily data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en:
Resource Title: Profiles_Klosters
    Size: 2530 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/dc102dd3-9d9d-4757-9263-9306c6474b5c/download/klo_prof.csv
    Description: Snow profiles data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en:
Resource Title: GNSS_klosters
    Size: 19682 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/bc65a02c-f311-49c7-9007-a8df51a87610/download/klo_gnss.csv
    Description: GNSS derived SWE, LWC and HS from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-20

en:
Resource Title: Meteo_WFJ
    Size: 2779069 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/be4ca553-12f8-4a2a-94bc-1672dfbac5b9/download/wfj_meteo.csv
    Description: Snow and meteo data from automatic sensors for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en:
Resource Title: Obs_WFJ
    Size: 23691 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/4b796a10-3ab7-42c9-ab1f-3d6218692326/download/wfj_obs.csv
    Description: Daily observer data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en:
Resource Title: Webcam images
    Size: 236611230 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/292ddd39-edd8-4df4-8dc7-f79137c6494d/download/pictures_webcam.zip
    Description: Webcam images showing some typical differences in the snow conditions at the four sites (Küblis, Klosters, Laret and Weissfluhjoch) for two time periods (14-18.3.2019 and 27.1-11.2.2020). Both time periods included a precipitation event with partial rain-on–snow occurring at the lower locations.

en:
Resource Title: Profiles_Kueblis
    Size: 1151 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/e6d6f714-5f1a-4cc9-9ab1-3cf5417073a7/download/kub_prof.csv
    Description: Snow profiles data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

gnss

display_name: gnss

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

lwc

display_name: lwc

snow

display_name: snow


$oid: OBSOLETE

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

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

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

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

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

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

format: PDF

media_type: application/pdf

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

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

alpine

display_name: alpine

antarctica

display_name: antarctica

arctic

display_name: arctic

brine

display_name: brine

chemistry

display_name: chemistry

heterogeneous

display_name: heterogeneous

interface

display_name: interface

laboratory-study

display_name: laboratory-study

metamorphism

display_name: metamorphism

ozone

display_name: ozone

reaction

display_name: reaction

solution

display_name: solution


restoring-grassland-multifunctionality

en:
Please cite this paper together with the citation for the datafile.
Resch, M. C., Schütz, M., Buchmann, N., Frey, B., Graf, U., van der Putten, W. H., Zimmermann, S., Risch, A. C. 2021. Evaluating long-term success in grassland restoration – an ecosystem multifunctionality approach. Ecological Applications 31, e02271.

 Study area
The study was conducted in the Canton of Zurich, Switzerland, in and around two nature reserves Eigental and Altläufe der Glatt (47°27’ to 47°29’ N, 8°37’ to 8°32’ E, 417 to 572 m a.s.l.). All studied grasslands were located with a radius of approximately 4 km. Average monthly temperatures range from 0.7 ± 2.0 °C (January) to 19.0 ± 1.5 °C (July), and monthly precipitation range from 60 ± 42 mm (January) to 118 ± 46 mm (July [maxima]; 1989-2017; MeteoSchweiz 2018). In our study, we focused on semi-dry and semi-wet oligo- to mesotrophic grasslands characterized by high plant species richness and groundwater fluctuations throughout the year (Delarze et al. 2015, see also Resch et al. 2019).
 Experimental design and sampling
A large-scale restoration experiment to expand and reconnect isolated remnants of species-rich grasslands was initiated in the nature reserve Eigental in 1990. Twenty hectares of adjacent intensive grasslands were chosen for restoration. In 1995, three restoration methods of increasing intervention intensities were implemented. The goal of all three methods was to lower the availability of soil nutrients and hence, facilitate ecosystem development towards the targeted nutrient-poor grasslands. These methods were: Harvest only (hay harvest twice a year), Topsoil (removal of the nutrient-rich topsoil), and Topsoil+Propagules (topsoil removal combined with the application of hay from target vegetation). Plant biomass harvest (once a year in late summer/early autumn) commenced in Topsoil and Topsoil+Propagules five years after the soils were removed and is still ongoing today. We measured restoration success by comparing the three restoration methods with intensively managed (Initial) and semi-natural grasslands (Target) 22 years after restoration. Initial grassland sites share the same agricultural history as the restored sites: mowing and subsequent fertilizing (manure) up to five times a year, as well as different tillage regimes (Resch et al. 2019). Target sites were the sites from which hay for seeding the Topsoil+Propagules sites was collected. Soil conditions (i.e., soil types, soil texture) were comparable to those found in the restored grasslands (Resch et al. 2019). Additionally, Target sites were selected to represent a variety of semi-natural grasslands, including semi-dry to semi-wet conditions.  In Target grasslands, biomass is harvested once a year in late summer or early autumn. Eleven 5 m x 5 m (25 m2) plots were randomly established in each of the five treatments (in total 55 plots; for a detailed map see Neff et al. 2020). An additional 2 m x 2 m (4 m2) subplot was randomly established at least 2 m away from each 25 m2 plot for destructive sampling. Data sampling took place between June and September 2017.
Vegetation properties
All plant species were identified within the 25 m2 plots (nomenclature: Lauber and Wagner 1996) in mid-June 2017 (in total 250 species). Vegetation structure and plant biomass were assessed diagonally on a transect of 2 m x 10 cm within the 25 m2 plot in early July 2017. We measured the maximum and mean height of the vegetation at the start, middle and end of the transect and calculated the standard deviation of these measures to describe vegetation structural heterogeneity (Schuldt et al. 2019). Thereafter, biomass was clipped on the entire transect to 1 cm height, sorted into five functional groups (graminoids, forbs, legumes, litter, and woody species), dried at 60 °C for 48 h, and weighed (Meyer et al. 2015).
 Aboveground arthropods
Aboveground arthropods were sampled at two locations in each 25 m2 plot in early July 2017 (see also Neff et al. 2020). Briefly, two cylindrical baskets (50 cm diameter, 67 cm height; woven fabric) were thrown simultaneously from outside the plot into two opposite corners. A closable mosquito mesh sleeve was mounted to the top of the baskets and an integrated metal ring at the bottom was fixed to the ground with metal stakes to assure that insects could not escape. A suction sampler (Vortis, Burkhard Manufacturing Co. Ltd., Hertfordshire, England) was then inserted into one of the baskets through the opening of the sleeve and the plot was “vacuumed" twice for 105 seconds with a 30 seconds break. The collected animals were immediately transferred into 70% ethanol. Arthropods were sorted and assigned to 23 taxonomic groups. Holometabolic larvae were lumped into one category while hemimetabolic larvae were grouped separately from adults in the respective taxonomic rank. We used mean values of individuals per plot for total abundance. Aboveground arthropod richness was defined by the number of different taxa to lowest taxonomic level (in total 23 taxa). All taxa were assigned to one of five trophic levels: 1) primary producers, 2) primary consumers, 3) secondary consumers, 4) tertiary consumers, and 5) quaternary consumers.
 Belowground fauna
Sampling of all belowground fauna took place in mid-July 2017. Earthworms were sampled in two 30 cm x 30 cm x 20 cm soil monoliths at two opposite corners of the 25 m2 plot (opposite to aboveground arthropod sampling). The excavated soil monolith was broken by hand, all earthworms collected and immediately transferred in a 4% formaldehyde solution. Thereafter, earthworm individuals were identified to species level (in total 10 taxa; Christian and Zicsi 1999) and species assigned to three functional groups (Bouché 1977).
To assess soil arthropod communities, we randomly collected one undisturbed soil core (5 cm diameter, 12 cm depth) in each 4 m2 subplot with a slide hammer corer lined with a plastic sleeve (AMS Samplers, American Falls, Idaho, USA). Soil arthropods were extracted using Berlese-Tullgren funnels (3 mm mesh), starting the day of sampling and lasting 14 days. Individuals were stored in 70% ethanol. Soil arthropods were assigned to 41 taxonomic groups and 4 feeding types. Holometabolic and hemimetabolic larvae were treated as previously described for aboveground arthropods. Belowground arthropod richness refers to the 41 taxonomic groups.
For soil nematode sampling, we randomly collected eight soil cores of 2.2 cm diameter (Giddings Machine Company, Windsor, CO, USA) within each 4 m2 subplot to a depth of 12 cm. The eight cores were combined, gently homogenized, placed in coolers, kept at 4 °C and transported to the laboratory at NIOO in Wageningen (NL) within one week after collection. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriator (Oostenbrink 1960) and prepared for morphological identification and quantification as described by Resch et al. (2019). Nematodes were identified to family level (39 taxa) according to Bongers (1988), assigned to 17 functional groups, 5 feeding types and 5 colonizer-persister (C-P) classes (Yeates et al. 1993, Bongers 1990, Resch et al. 2019).
We randomly collected two more soil cores (2.2 cm diameter x 12 cm depth) within each 4 m2 subplot to determine soil microbial communities. Again, the soil cores were combined, homogenized, placed in coolers and transported to the laboratory at WSL in Birmensdorf (Switzerland) where the metagenomic DNA was extracted from 8 g sieved soil (2 mm) using the DNeasy PowerMax Soil Kit (Quiagen, Hilden, NRW, GER) according to the manufacturer`s instructions. PCR amplification of the V3-V4 region of the prokaryotic small-subunit (16S) and the ribosomal internal transcribed spacer region (ITS2) of eukaryotes was performed with 1 ng of template DNA utilizing PCR primers and conditions as previously described (Frey et al., 2016). PCRs were run in triplicates and pooled. The pooled amplicons were sent to the Genome Quebec Innovation Centre (Montreal, QC, Canada) for barcoding using the Fluidigm Access Array technology (Fluidigm) and paired-end sequencing on the Illumina MiSeq v3 platform (Illumina Inc., San Diego, CA, USA). Quality filtering, clustering into operational taxonomic units (OTUs) and taxonomic assignment were performed as described by Frey et al. (2016) and Adamczyk et al. (2019). We used a customised pipeline largely based on UPARSE (Edgar 2013) implemented in USEARCH v. 9.2 (Edgar 2010). After discarding singletons of dereplicated sequences, clustering into OTUs with 97% sequence similarity was performed (Edgar 2013). Quality-filtered reads were mapped on the filtered set of centroid sequences. Taxonomic classification of prokaryotic and fungal sequences was conducted querying against most recent versions of SILVA (v.132, Quast et al. 2013) and UNITE (v.8, Nilsson et al. 2018). Only taxonomic assignments with confidence rankings equal or higher than 0.8 were accepted (assignments below 0.8 set to unclassified). Prokaryotic OTUs assigned to mitochondria or chloroplasts as well as eukaryotic OTUs assigned other than fungi were removed prior to data analysis. In addition, prokaryotic and fungal datasets were filtered to discard singletons and doubletons. Thereafter, OTU abundance matrices were rarefied to the lowest number of sequences per community, to normalize the total number of reads and achieve parity between samples (Prokaryota: 29,843 reads; Fungi: 26,690 reads). Finally, prokaryotic and fungal observed richness (number of OTUs) were estimated (Prokaryota: 14,010 OTUs; Fungi: 5,813 OTUs). For prokaryotes, we distinguished five and for fungi six functional types based on lowest taxonomic resolution (Nguyen et al. 2016, Tedersoo et al. 2014).  Belowground taxon richness was defined by the total number of earthworm, arthropod, nematode, fungi, and prokaryote taxa assigned to lowest taxonomic level. Finally, all belowground taxa were assigned to the same five trophic levels as the aboveground arthropods.
 Soil chemical and physical properties, soil nitrogen mineralization
We randomly collected three 5 cm diameter x 12 cm depth soil samples in each 4 m2 subplot with a slide hammer corer (AMS Samplers, American Falls, Idaho, USA), pooled them and then made two subsamples. One was field-fresh and stored at 3 °C until analysis, the other was dried for 48 h at 60 °C and passed through a 4 mm mesh. From the dried sample, we measured soil pH potentiometrically in 0.01 M CaCl2 (soil:solution ratio=1:2; 30 minutes equilibration time). Total and organic carbon content were measured on fine-ground samples (≤ 0.5 mm) by dry combustion using a CN analyzer NC 2500 (CE Instruments, Wigan, United Kingdom). Inorganic carbon of samples with a pH - 6.5 was removed with acid vapor prior to analysis of organic carbon (Walthert et al. 2010). We calculated total soil carbon (C) storage after correcting its content for soil depth, stone content and density of fine earth (see below). Exchangeable cations were determined on another 5 g dry soil sample with 50 mL unbuffered 1 M NH4Cl solution (soil:solution ratio=1:10, end-over-end shaker for 1.5 hours) and measured by an ICP-OES (Optima 7300 DV, Perkin-Elmer, Waltham, Massachusetts, USA). Thereafter, cation exchange capacity (CEC) was calculated as the sum of exchangeable cations and protons (and expressed as mmolc per 1 kg soil) and used to describe nutrient retention capacity in our plots. Concentrations of exchangeable protons were calculated as the difference between total and Al-induced exchangeable acidity as determined by the KCl-method (Thomas 1982).
Ammonium (NH4+) and nitrate (NO3−) were extracted from a 20 g fresh subsample with 80 mL 1M KCl for 1.5 hours on an end-over-end shaker and filtered through ashless folded filter paper (DF 5895 150, ALBET LabScience, Hahnemühle FineArt GmbH, Dassel, Germany). NH4+ concentrations were determined colorimetrically by automated flow injection analysis (FIAS 300, Perkin-Elmer, Waltham, Massachusetts, USA). NO3− concentrations were measured colorimetrically according to Norman and Stucki (1981). Potential soil net nitrogen (N) mineralization was assessed during an 8-week incubation period under controlled moisture (60% of field capacity), temperature (20 °C) and light conditions (dark) in the laboratory. We weighed duplicate samples of fresh soil equivalent to 8 g dry soil (24 h at 104 °C) into 50 mL Falcon tubes. Soil samples were extracted for NH4+ and NO3− at the beginning and after eight weeks as described above. Soil net N mineralization was calculated as the difference between the inorganic nitrogen (NH4+ and NO3−) before and after the incubation (Hart et al. 1994), corrected for the total incubation time and represented per day values expressed as mg N kg-1 soil d-1.
To assess soil physical properties, we randomly collected one undisturbed soil core per 4 m2 subplot (5 cm diameter, 12 cm depth) in a steel cylinder that fit into the slide hammer (AMS Samplers, American Falls, Idaho, USA). The cylinder was capped in the field to avoid disturbance. We then measured field capacity in the laboratory. For this purpose, the cylinder and soil therein were saturated in a water bath and drained on a sand/silt-bed with a suction corresponding to 60 cm hydrostatic head. The moist soil was dried at 105 °C to constant weight. Field capacity was calculated by dividing the mass of water by the total mass of wet soil contained at 60 cm hydrostatic head and used to describe water holding capacity. Thereafter, samples were passed through a 4 mm mesh. Fine-earth and skeleton fractions were weighed separately to assess bulk soil density (fine-earth plus skeleton), density of fine earth, and proportion of skeleton. Particle density was determined with the pycnometer method (Blake and Hartge 1986), and total porosity and proportion of fine pores were calculated (Danielson and Sutherland 1986). Clay, silt, and sand contents were quantified with the sediment method (Gee and Bauder 1986).
Surface and soil temperature (12 cm depth, water-resistant digital pocket thermometer; IP65, H-B Instrument, Trappe, Pennsylvania, USA) as well as volumetric soil moisture content (12 cm depth, time domain reflectometry; Field-Scout TDR 300, Spectrum Technologies, Aurora, Illinois, USA) were measured at five random locations within the 4 m2 subplots every month from June to September. We calculated the standard deviation of each temperature and moisture measure over four months to describe seasonal variations. Slope inclination was determined at plot-level via GPS measurements (GPS 1200, Leica Geosystem, Heerbrugg, Switzerland) and categorized into slope gradient classes according to FAO standards (1990). Thickness of the topsoil horizon (equivalent to Ah or Aa horizon) was determined at one soil monolith (30 x 30 x 30 cm3) per 4 m2 subplot in cm and rounded to next integer.
 References
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Blake, G.R., and K. H. Hartge. 1986. Particle Density. Pages 377-382 in A. Klute, editor. Methods of soil analysis: Part 1—Physical and mineralogical methods. Soil Science Society of America (SSSA) Inc., Madison.
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Bongers, T. 1990. The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologia 83:14-19.
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Christian, E., and A. Zicsi. 1999. Ein synoptischer Bestimmungsschlüssel der Regenwürmer Österreichs (Oligochaeta: Lumbricidae). Die Bodenkultur 50:121-131.
Danielson, R. E., and P. L. Sutherland. 1986. Porosity. Pages 443-461 in A. Klute, editor. Methods of soil analysis: Part 1—Physical and mineralogical methods. Soil Science Society of America (SSSA) Inc., Madison.
Delarze, R., Y. Gonseth, S. Eggenberg, and M. Vust. 2015. Lebensräume der Schweiz: Ökologie ‐ Gefährdung ‐ Kennarten, Ott Verlag, Bern.
Edgar, R. C. 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461.
Edgar, R. C. 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods 10:996–998.
FAO. 1990. Guidelines for soil description, third ed. Land and Water Development Division at the Food and Agriculture Organization of the United Nations (FAO), Rome.
Frey, B., T. Rime, M. Phillips, B. Stierli, I. Hajdas, F. Widmer, and M. Hartmann. 2016. Microbial diversity in European alpine permafrost and active layers. FEMS Microbiology Ecology 92:fiw018.
Gee, G.W., and J. W. Bauder. 1986. Particle-size analysis. Pages 383-411 in A. Klute, editor. Methods of soil analysis: Part 1—Physical and mineralogical methods. Soil Science Society of America (SSSA) Inc., Madison.
Hart, S. C, J. M. Stark, E. A. Davidson, and M. K. Firestone. 1994. Nitrogen mineralization, immobilization, and nitrification. Pages 985-1016 in R. W. Weaver, S. Angle, P. Bottomley, D. Bezdicek, S. Smith, A. Tabatabai, and A. Wollum, editors. Methods of soil analysis: Part 2—Microbiological and biochemical properties. Soil Science Society of America (SSSA) Inc., Madison.
Lauber, K., Wagner, G., 1996. Flora Helvetica. Flora der Schweiz. Haupt Verlag, Bern.
MeteoSchweiz, 2018. Klimabulletin Jahr 2017. MeteoSchweiz, Zürich.
Meyer, S. T., C. Koch, and W. W. Weisser. 2015. Towards a standardized rapid ecosystem function assessment (REFA). Trends in Ecology and Evolution 30:390-397.
Neff, F., M. C. Resch, A. Marty, J. Rolley, M. Schütz, A. C. Risch, and M. M. Gossner. 2020. Long-term restoration success of insect herbivore communities in semi-natural grasslands – a functional approach. Ecological Applications 0:e02133
Nguyen, N.H., Z. W. Song, S. T. Bates, S. Branco, L. Tedersoo, J. Menke, J. S. Schilling, and P. G. Kennedy. 2016. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecology 20:241–248.
Nilsson, R. H., K.-H. Larsson, A. F. S. Taylor, J. Bengtsson-Palme, T. S. Jeppesen, D. Schigel, P. G. Kennedy, K. Picard, F. O. Glöckner, L. Tedersoo, I. Saar, U. Kõljalg, and K. Abarenkov. 2018. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Research 47:259–264.
Norman, R. J., and J. W. Stucki. 1981. The Determination of Nitrate and Nitrite in Soil Extracts by Ultraviolet Spectrophotometry. Soil Science Society of America Journal 45:347-353.
Oostenbrink, M. 1960. Estimating nematode populations by some selected methods. Pages 81-101 in J. J. Sasser, and W. R. Jenkins, editors. Nematology. Univ. of North Carolina Press, Chapel Hill.
Quast, C., E. Pruesse, P. Yilmaz, J. Gerken, T. Schweer, P. Yarza, J. Peplies, and F. O. Glöckner. 2013. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research 41:590-596.
Resch, M. C., M. Schütz, U. Graf, R. Wagenaar, W.H. van der Putten, and A. C. Risch. 2019. Does topsoil removal in grassland restoration benefit both soil nematode and plant communities? Journal of Applied Ecology 56:1782-1793.
Schuldt, A., A. Ebeling, M. Kunz, M. Staab, C. Guimarães-Steinicke, D. Bachmann, N. Buchmann, W. Durka, A. Fichtner, F. Fornoff, W. Härdtle, L. R. Hertzog, A-N. Klein, C. Roscher, J. Schaller, von G. Oheimb, A. Weigelt, W. Weisser, C.Wirth, J. Zhang, H. Bruelheide, and N. Eisenhauer. 2019. Multiple plant diversity components drive consumer communities across ecosystems. Nature Communications 10:1460.
Tedersoo, L., M. Bahram, S. Põlme, U. Kõljalg, N. S. Yorou, R. Wijesundera, L. Villarreal Ruiz, A. M. Vasco-Palacios, P. Q. Thu, A. Suija, M. E. Smith, C. Sharp, E. Saluveer, A. Saitta, M. Rosas, T. Riit, D. Ratkowsky, K. Pritsch, K. Põldmaa, M. Piepenbring, C. Phosri, M. Peterson, K. Parts, K. Pärtel, E. Otsing, E. Nouhra, A. L. Njouonkou, R. H. Nilsson, L. N. Morgado, J. Mayor, T. W. May, L. Majuakim, D. J. Lodge, S. See Lee, K.-H. Larsson, P. Kohout, K. Hosaka, I. Hiiesalu, T. W. Henkel, H. Harend, L.-D. Guo, A. Greslebin, G. Grelet, J. Geml, G. Gates, W. Dunstan, C. Dunk, R. Frenkhan, L. Dearnaley, A. De Kesel, T. Dang, X. Chen, F. Buegger, F. Q. Brearley, G. Bonito, S. Anslan, S. Abell, and K. Abarenkov. 2014. Global diversity and geography of soil fungi. Science 346:1256688.
Thomas, G.W. 1982. Exchangeable cations. Pages 159-165 in A. L. Page, R. H. Miller, and D. R. Keeney, editors. Methods of Soil Analysis: Part 2—Chemical and microbiological properties. Soil Science Society of America (SSSA) Inc., Madison.
Walthert, L., U. Graf, A. Kammer, J. Luster, D. Pezzotta, S. Zimmermann, and F. Hagedorn. 2010. Determination of organic and inorganic carbon, δ13C, and nitrogen in soils containing carbonates after acid fumigation with HCl. Journal of Plant Nutrition and Soil Sciences 173:207-216.
Yeates, G. W., T. Bongers, R. G. M. de Goede, D. W. Freckman, and S. S. Georgieva. 1993. Feeding habits in soil nematode families and genera – an outline for soil ecologists. Journal of Nematology 25:315-331.

en: bacteria nematodes plants soil-biodiversity fungi biodiversity mineralization grassland ecosystem-multifunctionality restoration

en: Restoring grassland multifunctionality

title_for_slug: restoring-grassland-multifunctionality

en:
Resource Title: Correction_Soil.properties_20210210
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format: XLS

en:
Resource Title: Soil.properties
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    Description:

en:
Resource Title: Functional diversity above_belowground fauna
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    Description:

en:
Resource Title: Richness_fauna.microbes
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en:
Resource Title: Functional.diversity_taxonomic.classification_plants.fauna.microbes
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en:
Resource Title: Correction_Multifunctionality_single.ecosystem.properties.standardized_20210210
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    Description: Please note that EMF, MF.below, MF.abio and Soil.hetero have been corrected.

en:
Resource Title: Vegetation.properties
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en:
Resource Title: Multifunctionality_single.ecosystem.properties.standardized
    Size: 30156 bytes
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    Description:

bacteria

display_name: bacteria

biodiversity

display_name: biodiversity

ecosystem-multifunctionality

display_name: ecosystem-multifunctionality

fungi

display_name: fungi

grassland

display_name: grassland

mineralization

display_name: mineralization

nematodes

display_name: nematodes

plants

display_name: plants

restoration

display_name: restoration

soil-biodiversity

display_name: soil-biodiversity


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

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

envidat

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

en: EnviDat: the Environmental Data Portal

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

alpine-regions

display_name: alpine-regions

climate-change-scenarios

display_name: climate-change-scenarios

delta-change

display_name: delta-change

imis

display_name: imis

meteoswiss

display_name: meteoswiss

quantile-mapping

display_name: quantile-mapping

switzerland

display_name: switzerland

temporal-downscaling

display_name: temporal-downscaling


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

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

en: LABES 2 Indicators of the Swiss Landscape Monitoring Program

envi

en: Environment

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

format: ZIP

media_type: application/zip

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Indicator list:

Indicator 23 Ortsbindung / place attachment

Indicator 24 Landschaftliche Schönheit / visual landscape quality or beauty

Indicator 25 Besonderheit (Eigenart und Vergangenheitsbezug)/ place identity

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

Indicator 29 Faszination / soft fascination

Indicator 30 Authentizität /authenticity

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

Indicator Neu_17 Beobachtete Landschaftscharakterisierung / perceived landscape charachterization

Indicator Neu_18 Beobachtete Landschaftsveränderungen / perceived landscape changes

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

Indicator Neu_22 Gesamturteil zur wahrgenommenen Landschaftsqualität / overall satisfaction

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

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

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

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

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

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

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

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

ecosystem-services

display_name: ecosystem-services

european-landscape-convention

display_name: european-landscape-convention

landscape

display_name: landscape


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

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

envidat

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

en: EnviDat: the Environmental Data Portal

en: Seilaplan Tutorial: Load WMS layers as background maps

envi

en: Environment

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

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

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

wms-data

display_name: wms-data


en:
This dataset contains the output and reference data published in the paper "Automated snow avalanche release area delineation - validation of existing algorithms and proposition of a new object-based approach for large scale hazard indication mapping" Yves Bühler, Daniel von Rickenbach, Andreas Stoffel, Stefan Margreth, Lukas Stoffel, Marc Christen (2018) Natural Hazards And Earth System Sciences.
Abstract:
Snow avalanche hazard is threatening people and infrastructure in all alpine regions with seasonal or permanent snow cover around the globe. Coping with this hazard is a big challenge and during the past centuries, different strategies were developed. Today, in Switzerland, experienced avalanche engineers produce hazard maps with a very high reliability based on avalanche cadastre information, terrain analysis, climatological datasets and numerical modelling of the flow dynamics for selected avalanche tracks that might affect settlements. However, for regions outside the considered settlement areas such area-wide hazard maps are not available mainly because of the too high cost, in Switzerland and in most mountain regions around the world. Therefore, hazard indication maps, even though they are less reliable and less detailed, are often the only spatial planning tool available. To produce meaningful and cost-effective avalanche hazard indication maps over large regions (regional to national scale), automated release area delineation has to be combined with volume estimations and state-of-the-art numerical avalanche simulations.
In this paper we validate existing potential release area (PRA) delineation algorithms, published in peer-reviewed journals, that are based on digital terrain models and their derivatives such as slope angle, aspect, roughness and curvature. For validation, we apply avalanche cadastre data from three different ski resorts in the vicinity of Davos, Switzerland, where experienced ski-patrol staff mapped most avalanches in detail since many years. After calculating the best fit input parameters for every tested algorithm, we compare their performance based on the reference datasets. Because all tested algorithms do not provide meaningful delineation between individual potential release areas (PRA), we propose a new algorithm based on object-based image analysis (OBIA). In combination with an automatic procedure to estimate the average release depth (d0), defining the avalanche release volume, this algorithm enables the numerical simulation of thousands of avalanches over large regions applying the well-established avalanche dynamics model RAMMS. We demonstrate this for the region of Davos for two hazard scenarios, frequent (10 – 30 years return period) and extreme (100 – 300 years return period). This approach opens the door for large scale avalanche hazard indication mapping in all regions where high quality and resolution digital terrain models and snow data are available.

en: hazard-mapping hazard-indication-mapping release snow ramms avalanche

en: Automated Avalanche Release Area (PRA) Delineation Davos

en:
Resource Title: RAMMS simulations NHESS
    Size: 24222947 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/1a8ed871-a483-4900-b528-95e901b3910e/resource/88c5334b-40d3-47df-b8c7-d300ba46d19c/download/ramms_sim.zip
    Description: Simulated maximum pressures for the scenarios frequent and extreme taking the forest layer into account

en:
Resource Title: Potential Release  Area  NHESS
    Size: 4379100 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/1a8ed871-a483-4900-b528-95e901b3910e/resource/b0aeb914-2c95-4db3-a257-3c51ff0b2e97/download/pra_nhess.zip
    Description: This folder contains the output of the different investigated algorithms plus the reference dataset, used for training and validation.

avalanche

display_name: avalanche

hazard-indication-mapping

display_name: hazard-indication-mapping

hazard-mapping

display_name: hazard-mapping

ramms

display_name: ramms

release

display_name: release

snow

display_name: snow


de: Die Daten beinhalten Bereiche mit Gestaltungs-, Erschliessungs- oder Sondernutzungsplanpflicht aus den genehmigten Nutzungsplänen der Gemeinden sowie genehmigte Erschliessungspläne und Gestaltungspläne aus der Sondernutzungsplanung. Sie werden vom Datensatz "Nutzungsplanung: flächenbezogene Überlagerungen" ableitet und beinhalten folgende Werte gemäss Zonensystematik: Sondernutzungsplanpflicht: KTCode 6211, 6212, 6213, 6311 genehmigte Erschliessungspläne: KTCode 6111 genehmigte Gestaltungspläne: KTCode 6112

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

de: AGIS Service Center Kanton Aargau

political_level: canton

de: Abteilung Raumentwicklung

de: geocat.ch Permalink

fr: geocat.ch permalien

it: geocat.ch link permanente

en: geocat.ch permalink

de: Sondernutzungsplanung: genehmigte Erschliessungspläne, Gestaltungspläne und Sondernutzungsplanpflichten (themenspezifischer Auszug aus den Nutzungsplandaten)

de: AGIS Direktdownload

format: OCTET

value: Aargau-Kt - Geocat Harvester


de: Anzahl Personen und Vollzeitäquivalente. Stand: 30. Juni des jeweiligen Jahres.Folgende Mitarbeitendengruppen werden in den Daten nicht berücksichtigt: Regierungsratsmitglieder, Mitglieder des Landrats und Mitarbeitende im Stundenlohn (ausser Reinigungspersonal). Lehrpersonen und anderes Personal an Schulen in kantonaler Trägerschaft sind hingegen enthalten.Bei den besonderen Behörden sind die Mitarbeitenden der Landeskanzlei (inklusive Staatsarchiv), der Finanzkontrolle, der Ombudsstelle und der Aufsichtsstelle Datenschutz enthalten. Die Mitarbeitenden der Staatsanwaltschaft wurden 2010 zu den Gerichten, danach zur Sicherheitsdirektion gerechnet.Personen werden in jeder Organisationseinheit gezählt, in der sie tätig sind. Die Summe der einzelnen Organisationseinheiten ist deshalb grösser als das Total der Kantonsmitarbeitenden. Bei Betrachtung der gesamten Kantonsverwaltung sollte deshalb die Organisationseinheit «Gesamte Kantonsverwaltung» verwendet werden.Der Rückgang von 2015 auf 2016 ist hauptsächlich auf das Konkordat zur interkantonalen Harmonisierung der obligatorischen Schule (HarmoS; Verkürzung der vom Kanton getragenen Sekundarschule von vier auf drei Jahre) zurückzuführen. Die Entwicklung ab dem Jahr 2020 ist hauptsächlich auf Massnahmen im Zusammenhang mit der Covid-19-Pandemie zurückzuführen.

de: vollzeitaquivalent geschlecht alter kantonspersonal

kanton-basel-landschaft

en:
The Canton of Basel-Country publishes open datasets of cantonal offices and agencies.
Further information at https://ogd.bl.ch/

de:
Der Kanton Basel-Landschaft veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.
Weitere Informationen unter https://ogd.bl.ch/

de: Kanton Basel-Landschaft

en: Canton of Basel-Country

fr: Canton de Bâle-Campagne

it: Cantone di Basilea-Campagna

de: kanton-basel-landschaft

value: BL - DCAT

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

fr: Gouvernement et secteur public

it: Governo e settore pubblico

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Altersklasse und Organisationseinheit (seit 2010) (csv)

de: csv

format: CSV

media_type: text/csv

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Altersklasse und Organisationseinheit (seit 2010) (json)

de: json

format: JSON

media_type: application/json

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Altersklasse und Organisationseinheit (seit 2010) (jsonl)

de: jsonl

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Altersklasse und Organisationseinheit (seit 2010) (parquet)

de: parquet

format: PARQUET

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Altersklasse und Organisationseinheit (seit 2010) (rdfxml)

de: rdfxml

format: RDF XML

media_type: application/rdf+xml

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Altersklasse und Organisationseinheit (seit 2010) (jsonld)

de: jsonld

format: JSON-LD

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Altersklasse und Organisationseinheit (seit 2010) (turtle)

de: turtle

format: RDF Turtle

media_type: text/turtle

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Altersklasse und Organisationseinheit (seit 2010) (n3)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Altersklasse und Organisationseinheit (seit 2010) (xls)

de: xls

alter

display_name: alter

geschlecht

display_name: geschlecht

kantonspersonal

display_name: kantonspersonal

vollzeitaquivalent

display_name: vollzeitaquivalent


de: Anzahl Personen und Vollzeitäquivalente. Stand: 30. Juni des jeweiligen Jahres.Folgende Mitarbeitendengruppen werden in den Daten nicht berücksichtigt: Regierungsratsmitglieder, Mitglieder des Landrats und Mitarbeitende im Stundenlohn (ausser Reinigungspersonal). Polizeiaspirant/innen, Praktikant/innen, Volontär/innen und Auszubildende werden ebenfalls nicht berücksichtigt, da Ausbildungsverhältnisse nicht zu den anrechenbaren Dienstjahren für ein Dienstjubiläum gezählt werden. Lehrpersonen und anderes Personal an Schulen in kantonaler Trägerschaft sind hingegen enthalten.Bei den besonderen Behörden sind die Mitarbeitenden der Landeskanzlei (inklusive Staatsarchiv), der Finanzkontrolle, der Ombudsstelle und der Aufsichtsstelle Datenschutz enthalten. Die Mitarbeitenden der Staatsanwaltschaft wurden 2010 zu den Gerichten, danach zur Sicherheitsdirektion gerechnet.Personen werden in jeder Organisationseinheit gezählt, in der sie tätig sind. Die Summe der einzelnen Organisationseinheiten ist deshalb grösser als das Total der Kantonsmitarbeitenden. Bei Betrachtung der gesamten Kantonsverwaltung sollte deshalb die Organisationseinheit «Gesamte Kantonsverwaltung» verwendet werden.Der Rückgang von 2015 auf 2016 ist hauptsächlich auf das Konkordat zur interkantonalen Harmonisierung der obligatorischen Schule (HarmoS; Verkürzung der vom Kanton getragenen Sekundarschule von vier auf drei Jahre) zurückzuführen. Die Entwicklung ab dem Jahr 2020 ist hauptsächlich auf Massnahmen im Zusammenhang mit der Covid-19-Pandemie zurückzuführen.

de: vollzeitaquivalent geschlecht dienstalter kantonspersonal

kanton-basel-landschaft

de:
Der Kanton Basel-Landschaft veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.
Weitere Informationen unter https://ogd.bl.ch/

de: Kanton Basel-Landschaft

de: kanton-basel-landschaft

gove

de: Regierung und öffentlicher Sektor

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Dienstalter und Organisationseinheit (seit 2010) (csv)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Dienstalter und Organisationseinheit (seit 2010) (json)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Dienstalter und Organisationseinheit (seit 2010) (jsonl)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Dienstalter und Organisationseinheit (seit 2010) (parquet)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Dienstalter und Organisationseinheit (seit 2010) (rdfxml)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Dienstalter und Organisationseinheit (seit 2010) (jsonld)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Dienstalter und Organisationseinheit (seit 2010) (turtle)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Dienstalter und Organisationseinheit (seit 2010) (n3)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Dienstalter und Organisationseinheit (seit 2010) (xls)

dienstalter

display_name: dienstalter


de: Anzahl Personen und Vollzeitäquivalente. Stand: 30. Juni des jeweiligen Jahres.Folgende Mitarbeitendengruppen werden in den Daten nicht berücksichtigt: Regierungsratsmitglieder, Mitglieder des Landrats und Mitarbeitende im Stundenlohn (ausser Reinigungspersonal). Lehrpersonen und anderes Personal an Schulen in kantonaler Trägerschaft sind hingegen enthalten.Bei den besonderen Behörden sind die Mitarbeitenden der Landeskanzlei (inklusive Staatsarchiv), der Finanzkontrolle, der Ombudsstelle und der Aufsichtsstelle Datenschutz enthalten. Die Mitarbeitenden der Staatsanwaltschaft wurden 2010 zu den Gerichten, danach zur Sicherheitsdirektion gerechnet.Personen werden in jeder Organisationseinheit gezählt, in der sie tätig sind. Die Summe der einzelnen Organisationseinheiten ist deshalb grösser als das Total der Kantonsmitarbeitenden. Bei Betrachtung der gesamten Kantonsverwaltung sollte deshalb die Organisationseinheit «Gesamte Kantonsverwaltung» verwendet werden.Der Rückgang von 2015 auf 2016 ist hauptsächlich auf das Konkordat zur interkantonalen Harmonisierung der obligatorischen Schule (HarmoS; Verkürzung der vom Kanton getragenen Sekundarschule von vier auf drei Jahre) zurückzuführen. Die Entwicklung ab dem Jahr 2020 ist hauptsächlich auf Massnahmen im Zusammenhang mit der Covid-19-Pandemie zurückzuführen.

de: vollzeitaquivalent geschlecht beschaftigungsgrad kantonspersonal

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Beschäftigungsgrad und Organisationseinheit (seit 2010) (csv)

de: csv

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Beschäftigungsgrad und Organisationseinheit (seit 2010) (json)

de: json

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Beschäftigungsgrad und Organisationseinheit (seit 2010) (jsonl)

de: jsonl

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Beschäftigungsgrad und Organisationseinheit (seit 2010) (parquet)

de: parquet

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Beschäftigungsgrad und Organisationseinheit (seit 2010) (rdfxml)

de: rdfxml

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Beschäftigungsgrad und Organisationseinheit (seit 2010) (jsonld)

de: jsonld

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Beschäftigungsgrad und Organisationseinheit (seit 2010) (turtle)

de: turtle

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Beschäftigungsgrad und Organisationseinheit (seit 2010) (n3)

de: Mitarbeitende der Kantonsverwaltung nach Geschlecht, Beschäftigungsgrad und Organisationseinheit (seit 2010) (xls)

beschaftigungsgrad

display_name: beschaftigungsgrad


de:
Aktuelle Planauflagen von Strassenbauprojekten nach Strassengesetz gemäss § 13 StrG und § 16 und § 17 StrG.

Hinweis: Beinhaltet nicht die Planauflagen gemäss der restlichen Paragraphen. Diese sind auf der Webseite des TAZ zu finden bzw. können beim TAZ angefragt werden.

**Zweck**: Planauflage

de: geodaten geoportal polygondaten stzh vektordaten

stadt-zurich

fr: Vous trouverez ici les données de la ville de Zürich. En parallèle, Open Data Zürich a son propre portail Open Data où vous pouvez trouver également des manuels et des documents sur le traitement des données. À de rares exceptions près, toutes les données publiées par Open Data Zürich sont sous une licence «Creative Commons Zero».

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

en: Here you find all publicly available data published by Open Data Zürich. In addition, the city of Zurich runs its own Open Data Portal, where you find manuals and documentation about the handling of datasets. With only a few exceptions, all datasets from Open Data Zürich are licensed under «Creative Commons Zero».

it:
Open Data Zürich propone qui dati pubblici della città di Zurigo, pronti alla libera utilizzazione.
La città di Zurigo dispone parallelamente di un proprio portale Open Data, sul quale sono disponibili anche istruzioni e documentazioni per contestualizzare i datasets.
A parte poche eccezioni tutte le datasets della città di Zurigo hanno una licenza «Creative Commons Zero».

de: Stadt Zürich

en: City of Zurich

fr: Ville de Zurich

it: Cità di Zurigo

political_level: commune

name: Kommunikation, Tiefbauamt, Tiefbau- und Entsorgungsdepartement

de: Öffentliche Planauflagen von Strassenbauprojekten gemäss § 13 StrG und § 16 und § 17 StrG

value: ZH - DCAT Harvester

regi

de: Regionen und Städte

en: Regions and cities

fr: Régions et villes

it: Regioni e città

format: DXF

format: GPKG

de: Web Feature Service

format: WFS

de: Web Map Service

format: WMS

de: Web Map Tile Service

format: WMTS

geodaten

display_name: geodaten

geoportal

display_name: geoportal

polygondaten

display_name: polygondaten

stzh

display_name: stzh

vektordaten

display_name: vektordaten


de: Dieser Datensatz enthält Informationen zur Zugänglichkeit öffentlicher Gebäude, die von Pro Infirmis erfasst wurden. Abgedeckt werden verschiedene Aspekte der Zugänglichkeit, darunter Rollstuhlgängigkeit, Zugänglichkeit für Menschen mit Seh- oder kognitiver Beeinträchtigung.

de: api barrierefreiheit gebaeude github parkplatz rollstuhl tabelle wc zugaenglichkeit

name: Immobilien Stadt Zürich, Hochbaudepartement

de: Informationen zur Zugänglichkeit öffentlicher Gebäude der Stadt Zürich

heal

de: Gesundheit

en: Health

fr: Santé

it: Salute

gove

de: Regierung und öffentlicher Sektor

api

display_name: api

barrierefreiheit

display_name: barrierefreiheit

gebaeude

display_name: gebaeude

github

display_name: github

parkplatz

display_name: parkplatz

rollstuhl

display_name: rollstuhl

tabelle

display_name: tabelle

wc

display_name: wc

zugaenglichkeit

display_name: zugaenglichkeit


inventar-hauptarchiv-des-stadtarchivs

de: Inventar des Hauptarchivs des Stadtarchivs Zürich. Die Tabelle wird über den [Online-Archivkatalog des Stadtarchivs Zürich](https://amsquery.stadt-zuerich.ch/suchinfo.aspx) erstellt und umfasst den Inhalt des Abschnitt "V. Hauptarchiv". Weitere Informationen und eine Anleitung zur Benutzung der Schnittstelle finden sich [hier](https://opendatazurich.github.io/sar-sru-api/).

de: archiv archivdaten geschichte glam openglam stadtrat

de: Inventar Hauptarchiv des Stadtarchivs

title_for_slug: inventar-hauptarchiv-des-stadtarchivs

archiv

display_name: archiv

archivdaten

display_name: archivdaten

geschichte

display_name: geschichte

glam

display_name: glam

openglam

display_name: openglam

stadtrat

display_name: stadtrat


kamerun-sammlungen-am-mrz

de:
Das Museum Rietberg verfügt seit seiner Gründung über erste Objekte aus Kamerun; im Laufe der Jahre wurde dieser Bestand kontinuierlich erweitert. Im Rahmen eines CAS in Provenienzforschung hat Jonas Lendenmann einen umfassenden Überblick über die Provenienzen dieser Sammlung erarbeitet. Seine Studie bietet nicht nur detaillierte Einblicke in die Herkunft der Objekte, sondern liefert auch wichtige Kontextinformationen zur Sammlungsgeschichte, zu Ausstellungstätigkeiten sowie zu Kooperationen des Museums.
Die vollständige Arbeit steht auf der Webseite des Museum Rietberg zum Download bereit.
Der vorliegende Datensatz basiert auf den von Jonas Lendenmann recherchierten und aufbereiteten Informationen zu den Sammlungsobjekten aus Kamerun.

de: kamerun provenienzforschung sammler github

name: Museum Rietberg Zürich, Präsidialdepartement

de: Kamerun Sammlungen am MRZ

title_for_slug: kamerun-sammlungen-am-mrz

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

fr: Éducation, culture et sport

it: Istruzione, cultura e sport

kamerun

display_name: kamerun

provenienzforschung

display_name: provenienzforschung

sammler

display_name: sammler


brunnenfotos-der-stadt-zurich

de: Dieser Datensatz ergänzt den [Geodatensatz mit den Brunnen der Stadt Zürich](https://data.stadt-zuerich.ch/dataset/geo_brunnen). Er enthält die URLs der öffentlich zugänglichen [Brunnenwebseiten](https://www.stadt-zuerich.ch/de/umwelt-und-energie/wasser/trinkwasser/brunnen.html) sowie der zugehörigen Fotos. Über die Brunnennummer lassen sich diese Informationen mit dem Geodatensatz verknüpfen.

de: bilder brunnen fotos github trinkwasser wasserversorgung

stadt-zurich

de: Open Data Zürich stellt hier offene Daten aus der Stadt Zürich zur freien Nutzung bereit. Die Stadt Zürich verfügt parallel über ein eigenes Open Data Portal, auf dem Sie auch Anleitungen und Dokumentationen zum Umgang mit Datensätzen finden. Mit wenigen Ausnahmen sind alle Datensätze der Stadt Zürich mit «Creative Commons Zero» lizenziert.

de: Stadt Zürich

name: Wasserversorgung, Departement der Industriellen Betriebe

de: Brunnenfotos der Stadt Zürich

title_for_slug: brunnenfotos-der-stadt-zurich

bilder

display_name: bilder

brunnen

display_name: brunnen

fotos

display_name: fotos

trinkwasser

display_name: trinkwasser

wasserversorgung

display_name: wasserversorgung


de:
Anteil (%) der Bevölkerung mit höchster abgeschlossener Ausbildung nach Geschlecht, 2010 bis 2024.

Ständige Wohnbevölkerung ab 25 Jahren. Die Anteile wurden basierend auf einer Stichprobe hochgerechnet.

(QUELLE: Bundesamt für Statistik, Strukturerhebung)

kanton-zug

de:
Hier veröffentlicht das Team von Open Data Zug von der kantonalen Fachstelle für Daten und Statistik schrittweise offene Behördendaten der kantonalen Verwaltung.

Weitere Informationen unter https://zg.ch/opendata

de: Kanton Zug

en: Canton of Zug

fr: Canton de Zoug

it: Cantone di Zugo

de: Fachstelle für Daten und Statistik des Kantons Zug

value: DCAT Harvester Kt. ZG

de: Anteil der Bevölkerung mit höchster abgeschlossener Ausbildung

schulabschlusse

display_name: schulabschlusse


schulerinnen-und-schuler-nach-schulform

de:
Anzahl Schülerinnen und Schüler im Kanton Zug nach Schulform, Schuljahr 2024/2025.

Die Anzahl umfasst die Schülerinnen und Schüler der obligatorischen Schulzeit (ohne Gymnasium) sowie des vorobligatorischen Kindergartenjahrs. Die Schülerinnen und Schüler mit integrativ sonderpädagogischen Massnahmen werden in der Regelschule beschult, jedoch separat ausgewiesen.

(QUELLE: Kanton Zug, Amt für gemeindliche Schulen)

de: kindergarten primarstufe sekundarstufe

de: Schülerinnen und Schüler nach Schulform

title_for_slug: schulerinnen-und-schuler-nach-schulform

kindergarten

display_name: kindergarten

primarstufe

display_name: primarstufe

sekundarstufe

display_name: sekundarstufe


de: A bridge is a structure that crosses a road or an obstacle. A small bridge up to 2 meters is called a passage. Bridges are represented as a complete object consisting of individual bridge construction units. Last Update Jan 2024A bridge is a structure that crosses a road or an obstacle. A small bridge up to 2 meters is called a passage. Bridges are represented as a complete object consisting of individual bridge construction units.

schweizerische-bundesbahnen-sbb

fr:
Les CFF sont l’un des piliers d’une mobilité durable en Suisse. Chaque jour, les CFF acheminent 1,18 million de voyageurs et 210 000 tonnes de marchandises, de manière ponctuelle et respectueuse de l’environnement.

Le chemin de fer crée des liens à travers toute la Suisse, par-delà les frontières linguistiques, culturelles et politiques. Du point de vue économique et social, il contribue ainsi à la qualité de vie et à la compétitivité de notre pays. Mais les CFF ne sont pas qu’une entreprise de chemin de fer moderne et performante. En leur qualité d’employeur, de commanditaire, de propriétaire et de gérant d’immeubles, ils sont responsables de la Suisse, de ses régions et de l’environnement.

de:
Die SBB ist das Rückgrat einer nachhaltigen Mobilität in der Schweiz. Täglich sind 1,18 Millionen Reisende und 210'000 Tonnen Güter mit der SBB sicher, pünktlich und umweltfreundlich unterwegs.

Die Eisenbahn verbindet die Schweiz über alle sprachlichen, kulturellen und politischen Grenzen hinweg und leistet in wirtschaftlicher und gesellschaftlicher Hinsicht einen überaus wertvollen Beitrag an die Lebensqualität und Wettbewerbsfähigkeit unseres Landes. Die SBB ist aber weit mehr als ein modernes und leistungsfähiges Bahnunternehmen. Auch als Arbeits- und Auftraggeberin sowie als Immobilienbesitzerin und ‑bewirtschafterin übernimmt sie Verantwortung für die Schweiz, ihre Regionen und die Umwelt.

en:
SBB is the backbone of sustainable mobility in Switzerland. Every day, it safely transports 1.18 million passengers and 210,000 tonnes of freight on time and in an environmentally friendly manner.

The railway transcends all linguistic, cultural and political boundaries to bring Switzerland together, and in economic and social terms, it makes a vital contribution to the quality of life and competitiveness of our country. However, SBB is much more than just a modern, efficient railway company. As an employer and contractor, a property owner and a real estate manager, SBB takes responsibility for Switzerland, its regions and the environment.

it:
Le FFS assumono la loro responsabilità.

Consigliare ad altri

Condividere

Le FFS sono la colonna portante della mobilità sostenibile in Svizzera. Ogni giorno 1,18 milioni di viaggiatori e quasi 210 000 tonnellate di merci viaggiano con le FFS in modo sicuro, puntuale e rispettoso dell'ambiente.

La ferrovia unisce la Svizzera oltre i confini linguistici, culturali e politici e dal punto di vista economico e sociale assicura un contributo oltremodo prezioso alla qualità di vita e alla competitività del nostro Paese. Le FFS tuttavia sono ben più di un'impresa ferroviaria moderna e altamente performante. Esse assumono la loro responsalibità per la Svizzera, le sue regioni e l'ambiente anche come datore di lavoro, di committenti, così come di proprietarie e amministratrici di fondi e di immobili.

de: Schweizerische Bundesbahnen SBB

en: Swiss Federal Railways SBB

fr: Chemins de fer fédéraux suisses CFF

it: Ferrovie federali svizzere FFS

de: schweizerische-bundesbahnen-sbb

de: Bridges

value: SBB - DCAT Harvester

tran

de: Verkehr

en: Transport

fr: Transports

it: Trasporti

de: Bridges (csv)

de: csv

de: Bridges (json)

de: json

de: Bridges (fgb)

de: fgb

de: Bridges (geojson)

de: geojson

de: Bridges (gpx)

de: gpx

format: GPX

de: Bridges (jsonl)

de: jsonl

de: Bridges (kml)

de: kml

format: KML

de: Bridges (ov2)

format: TXT

media_type: text/plain

de: Bridges (parquet)

de: parquet

de: Bridges (rdfxml)

de: rdfxml

de: Bridges (jsonld)

de: jsonld

de: Bridges (turtle)

de: turtle


nutzungsflachen-inkl-bff-i-ur

de: Der Geobasisdatensatz 153.1 Nutzungsflächen (inkl. Biodiversitätsförderflächen Qualitätsstufe I) beinhaltet die landwirtschaftlich genutzten Flächen gemäss landwirtschaftlicher Begriffsverordnung (LBV), Direktzahlungsverordnung (DZV) und der daraus abgeleiteten Definitionen (inkl. Codierung) der Nutzungen durch den Bund und die Kantone. Die Biodiversitätsförderflächen (BFF) Qualitätsstufe I sind zusätzlich auch noch als separater Layer verfügbar.

geoinformation-kanton-uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

de: Lisag AG, Geoinformation Kanton Uri

de: Amt für Landwirtschaft Kt. Uri

de: geocat.ch Permalink

spatial: Canton of Uri (UR)

de: Nutzungsflächen inkl. BFF I (UR)

title_for_slug: nutzungsflachen-inkl-bff-i-ur

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

fr: Agriculture, pêche, sylviculture et alimentation

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

de: WMS-Dienst des Kanton Uri

format: XML

media_type: application/xml

de: WFS-Dienst des Kanton Uri

value: Uri-Kt - Geocat Harvester


alpen-inkl-weideperimeter

de: In diesem Layer sind die Alpgrenzen und innerhalb dieser die beitragsberechtigten Landwirtschaftsflächen dargestellt. Grundsätzlich basieren die Grenzen und Flächen auf digitalisierten Plan-Einzeichnungen (Massstab 1:5'000) der verschiedenen Allmendaufseher. Bei denjenigen Alpen, wo im Geodatensatz "BFF im Sömmerungsgebiet" beurteilte Flächen vorhanden sind, wurden die Flächen in Feldbegehungen überprüft (sofern die betroffenen Flächen nicht über 2'200 m liegen, bzw. über 2'400 m im Urserental).

de: Alpen inkl. Weideperimeter

title_for_slug: alpen-inkl-weideperimeter


neophyten

de: Standorte von gebietsfremden Pflanzen (Neophyten) im Kanton Uri.

de: invasiv geodaten

de: Amt für Umwelt Kt. Uri

de: Neophyten

title_for_slug: neophyten

envi

de: Umwelt

en: Environment


antennenstandortenbspmobilfunk

de: Zeigt Antennenstandorte mit Angaben zu Betreiber und Mobilfunkstandard. Angezeigt werden Basisstationen für 2G, 3G, 4G und 5G - Mobilkommunikation.

de: gebaude-und-anlagen strahlung telekommunikation ver--und-entsorgung

fr: La géoinformation du canton de Lucerne est responsable de la collecte, du traitement et de la gestion des données à référence spatiale. Elle dirige, coordonne et surveille les travaux de la géoinformation et de la mensuration officielle.

en: Geoinformation of the Canton of Lucerne is responsible for the collection, processing and management of spatial data. It manages, coordinates and monitors the work of geoinformation and of the cadastral surveying.

de: Die Geoinformation des Kantons Luzern ist für die Erhebung, Verarbeitung und Verwaltung von raumbezogenen Daten zuständig. Sie leitet, koordiniert und überwacht die Arbeiten der Geoinformation und der amtlichen Vermessung.

it: La Geoinformation del Cantone di Lucerna è responsabile della raccolta, dell'elaborazione e della gestione dei dati territoriali. Gestisce, coordina e monitora il lavoro della geoinformazione e della misurazione ufficiale.

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

fr: Géoinformation du canton de Lucerne

it: Geoinformazione del Cantone di Lucerna

de: Kanton Luzern, Abteilung Geoinformation

spatial: Kanton Luzern

de: Antennenstandorte Mobilfunk

title_for_slug: antennenstandortenbspmobilfunk

de: Produktansicht Geodatenshop

de: Datenshop

value: LU-Kt - Geocat Harvester


name: Dienststelle für Verkehr und Infrastruktur (vif)

de: Daten für die Webkarte Kantonale Risikoübersicht Naturgefahren. Der berechnete Risikoindex bezeichnet die Wahrscheinlichkeit, dass eine bestimmte Naturgefahr Schäden anrichtet und wird summiert pro Hektare dargestellt.

de: naturgefahren risiken schadenereignis

de: geocat.ch Permalink

en: geocat.ch permalink

de: Konsequenzen: Schutzgüter indexiert pro Hektare nach Nutzungskategorie

regi

de: Regionen und Städte


de: Der Datensatz zeigt Windmessungen am Bahnhofplatz St.Gallen. Die Daten werden stündlich aggregiert.

de: real-time sensor wind offene-sensordaten

stadt-st-gallen

fr: Avec une population de 80 000 habitants, Saint-Gall, huitième ville de Suisse, est la métropole économique, politique, sociale et culturelle de la Suisse orientale. Ses 1400 ans d'histoire se mêlent à la créativité urbaine, à une économie innovante et à un paysage préservé.

en: With a population of 80,000, St.Gallen, Switzerland’s eighth largest city, is the economic, political, social and cultural metropolis of eastern Switzerland. Its 1400 years of history blend with urban creativity, an innovative economy and an unspoilt landscape.

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

it: Con una popolazione di 80.000 abitanti, San Gallo, l'ottava città più grande della Svizzera, è la metropoli economica, politica, sociale e culturale della Svizzera orientale. I suoi 1400 anni di storia si fondono con la creatività urbana, un'economia innovativa e un paesaggio incontaminato.

de: Stadt St.Gallen

en: City of St.Gallen

fr: Ville de Saint-Gall

it: Città di San Gallo

de: stadt-st-gallen

value: DCAT Harvester Stadt St. Gallen

de: Windmessung Bahnhofplatz Stadt St.Gallen (csv)

de: csv

de: Windmessung Bahnhofplatz Stadt St.Gallen (json)

de: json

de: Windmessung Bahnhofplatz Stadt St.Gallen (fgb)

de: fgb

de: Windmessung Bahnhofplatz Stadt St.Gallen (geojson)

de: geojson

de: Windmessung Bahnhofplatz Stadt St.Gallen (gpx)

de: gpx

de: Windmessung Bahnhofplatz Stadt St.Gallen (jsonl)

de: jsonl

de: Windmessung Bahnhofplatz Stadt St.Gallen (kml)

de: kml

de: Windmessung Bahnhofplatz Stadt St.Gallen (ov2)

de: Windmessung Bahnhofplatz Stadt St.Gallen (parquet)

de: parquet

de: Windmessung Bahnhofplatz Stadt St.Gallen (rdfxml)

de: rdfxml

de: Windmessung Bahnhofplatz Stadt St.Gallen (jsonld)

de: jsonld

de: Windmessung Bahnhofplatz Stadt St.Gallen (turtle)

de: turtle

de: Windmessung Bahnhofplatz Stadt St.Gallen (n3)

de: Windmessung Bahnhofplatz Stadt St.Gallen (shp)

de: shp

format: ZIP

de: Windmessung Bahnhofplatz Stadt St.Gallen (xls)

de: xls

format: XLS


luftwerte-in-der-stadt-st-gallen

de: Die Stadt St.Gallen verfügt über Luftsensoren an verschiedenen Standorten der Stadt, welche die Luftfeuchtigkeit und Temperatur messen. Die Daten werden stündlich aggregiert.

de: real-time sensor feuchtigkeit temperatur offene-sensordaten

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

de: Stadt St.Gallen

de: stadt-st-gallen

de: Luftwerte in der Stadt St.Gallen

title_for_slug: luftwerte-in-der-stadt-st-gallen

envi

de: Umwelt

fr: Environnement

it: Ambiente

de: Luftwerte in der Stadt St.Gallen (csv)

de: csv

format: CSV

de: Luftwerte in der Stadt St.Gallen (json)

de: json

de: Luftwerte in der Stadt St.Gallen (fgb)

de: fgb

format: OCTET

de: Luftwerte in der Stadt St.Gallen (geojson)

de: geojson

de: Luftwerte in der Stadt St.Gallen (gpx)

de: gpx

de: Luftwerte in der Stadt St.Gallen (jsonl)

de: jsonl

de: Luftwerte in der Stadt St.Gallen (kml)

de: Luftwerte in der Stadt St.Gallen (ov2)

de: Luftwerte in der Stadt St.Gallen (parquet)

de: Luftwerte in der Stadt St.Gallen (rdfxml)

de: Luftwerte in der Stadt St.Gallen (jsonld)

de: Luftwerte in der Stadt St.Gallen (turtle)

de: Luftwerte in der Stadt St.Gallen (n3)