maintainer: Anita Risch

en: invertebrates grassland ecosystem-coupling subalpine grazing swiss-national-park ecosystem-functions ecosystem-multifunctionality exclusion vertebrates

en: Datafile

en:
ID: Plot ID composited of Fence & Treatment number (90 plots total)

Grassland: Name of the six subalpine grasslands where the exclosure setups were erected. In large grasslands (GRIM, MING, STAB), we established four hierarchical exclosure setups (two in short- and two in tall-grass vegetation), whereas in the small grasslands (BOTS, DADA, MARG) only one setup was erected per vegetation type. BOTS = Val dal Botsch, GRIM = Grimmels, MING = Val Mingér, STAB = Alp Stabelchod, DADA = Stabelchod da daint, MARG = Margunet

Fence: Number of exclosure setup (1 - 18). Note that uneven numbers (1,3,5,7,9,11,13,15,17) represent setups established on short-grass vegetation, even numbers (2,4,6,8,10,12,14,16,18) setups established in tall-grass vegetation
Vegetation	Vegetation type, 1 = short-grass vegetation, 2 = tall-grass vegetation; (9 replicate fences on each vegetation type)
Treatment	Progressive animal exclusion, numbers indicate which animals had access to the plot: 1 = Large/medium/small mammals, and invertebrates have access ("L/M/S/I"), 2 = Medium/small mammals, and invertebrates have access (“M/S/I”), 3 = Small mammals and invertebrates have access (“S/I”), 4 = Invertebrates have access (“I”), 5 = No animals have access (“None”)

Bulkden:	Fine fraction soil bulk density (g cm-3)

Soil.moist	: Soil moisture (%)

Soil.org.C: Rhizosphere soil C content (%)

pH: Soil pH

Nema.PC1: First principal component (PC1) of principal component analysis (PCA) of the soil nematode community composition

Nema.PC2: Second principal component (PC2) of principal component analysis (PCA) of the soil nematode community composition

Micro.PC1: 	First principal component (PC1) of principal component analysis (PCA) of the soil microbial community composition

Micro.PC2: Second principal component (PC2) of principal component analysis (PCA) of the soil microbial community composition

Abv.Inv.PC1: First principal component (PC1) of principal component analysis (PCA) of the aboveground-dwelling invertebrate community composition

Abv.Inv.PC2: Second principal component (PC2) of principal component analysis (PCA) of the aboveground-dwelling invertebrate community composition

Arthr.PC1: First principal component (PC1) of principal component analysis (PCA) of the soil arthropod community composition

Arthr.PC2: Second principal component (PC2) of principal component analysis (PCA) of the soil arthropod community composition

Plant.PC1: First principal component (PC1) of principal component analysis (PCA) of the plant community composition

Plant.PC2: Second principal component (PC2) of principal component analysis (PCA) of the plant community composition

Root.biomass: Root biomass (g m-2)

Micro.biomass	: Microbial biomass carbon (mg kg-1)

Plant.richness: Plant species richness

Plant.N: Plant tissue nitrogen content (%)

Soil.N.min: Soil net nitrogen mineralisation (kg ha-1 season)

Soil.resp: Soil carbon dioxide emissions (soil respiration; g m-2 h-1)

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

Paper Citation:
 > Risch AC, Ochoa-Hueso R, van der Putten WH, Bump JK, Busse MD, Frey B, Gwiazdowicz DJ, Page-Dumroese DS, Vandegehuchte ML, Zimmermann S, Schütz M. Size-dependent loss of aboveground animals differentially affects grassland ecosystem coupling and functions. 2018. Nature Communications 9: 3684. [doi: 10.1038/s41467-018-06105-4](https://doi.org/10.1038/s41467-018-06105-4).

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

#Methods
Study sites
The experimental exclosure setups were installed within the SNP (IUCN category Ia preserve; Dudley 2008), in south-eastern Switzerland. The park covers 172 km2 of forests and subalpine and alpine grasslands along with scattered rock outcrops and scree slopes. The entire area has been protected from human impact (no hunting, fishing, camping or off-trail hiking) since 1914. Large, fairly homogenous patches of short- and tall-grass vegetation, which originate from different historical management and grazing regimes, cover the park’s subalpine grasslands entirely. Short-grass vegetation developed in areas where cattle used to rest (nutrient input) prior to the park’s foundation (14th century to 1914) (Schütz and others 2003, 2006) and is dominated by lawn grass species such as Festuca rubra L., Briza media L. and Agrostis capillaris L. (Schütz and others 2003, 2006). Today, this vegetation type is intensively grazed by diverse vertebrate and invertebrate communities that inhabit the park and consume up to 60% of the available biomass (Risch and others 2013). Tall-grass vegetation developed where cattle formerly grazed, but did not rest, and is dominated by rather nutrient-poor tussocks of Carex sempervirens Vill. and Nardus stricta L. (Schütz and others 2003, 2006). This vegetation type receives considerably less grazing, with only roughly 20% of the biomass consumed (Risch and others 2013). Consequently, the two vegetation types together represent a long-term trajectory of changes in grazing regimes. Underlying bedrock of all grasslands is dolomite, which renders these grasslands rather poor in nutrients regardless of former and current land-use regimes.
Experimental design
To progressively exclude aboveground vertebrate and invertebrate animals, we established 18 size-selective exclosure setups (nine in short-grass, nine in tall-grass vegetation) distributed over six subalpine grasslands across the SNP (Risch and others 2013, 2015). Elevation differences of exclosure locations did not exceed 350 m (between 1975 and 2300 m a.s.l.). The exclosures were established immediately after snowmelt in spring 2009 and were left in place for five consecutive growing seasons (until end of 2013). They were, however, temporarily dismantled every fall (late October after first snowfall) to protect them from avalanches. They were re-established in the same location every spring immediately after snowmelt. Each size-selective exclosure setup consisted of five plots (2 x 3 m) that progressively excluded aboveground vertebrates and invertebrates from large to small. The plots are labelled according to the guilds that had access to them “L/M/S/I”, “M/S/I”, “S/I”, “I”, “None”; L = large mammals, M = medium mammals, S = small mammals, I = invertebrates, None = no animals had access. As we only had permission to have the experimental setup in place for five consecutive growing seasons, the experiment had to be completely dismantled in the late fall of 2013 and all material removed from the SNP.
Our exclosure design was aimed at excluding mammalian herbivores, but naturally also excluded the few medium and small mammalian predators, as well as the entire aboveground invertebrate food web. A total of 26 large to small mammal species can be found in the SNP, but large apex predators are missing (wolf, bear, lynx) . Reptiles, amphibians and birds are scarce to absent in the subalpine grasslands under study. Only two reptile species occur in the park and they are confined to rocky areas that warm up enough for them to survive. One frog species spawns in an isolated pond far from our grasslands. Only three bird species occasionally feed on the subalpine grasslands. Using game cameras (Moultrie 6MP Game Spy I-60 Infrared Digital Game Camera, Moultrie Feeders, Alabaster, AL, USA), we did observe that the medium- and small-sized mammals (marmot/hares and mice) were not afraid to enter the fences and feed on their designated plots. We never spotted reptiles, amphibians or birds on camera. We distinguished between 59 higher aboveground-dwelling invertebrate taxa that our size-selective exclosures excluded (see also methods for aboveground-dwelling invertebrates below).
The “L/M/S/I” plot (not fenced) was located at least 5 m from the 2.1 m tall and 7 x 9 m large main electrical fence that enclosed the other four plots. The bottom wire of this fence was mounted at 0.5 m height and was not electrified to enable safe access for medium and small mammals, while fencing out the large ones. Within each main fence, we randomly established four 2 x 3 m plots separated by 1-m wide walkways from one another and from the main fence line: 1) the “M/S/I” plots were unfenced, allowing access to all but the large mammals; 2) the “S/I” plots (10 x 10 cm electrical mesh fence) excluded all medium-sized mammals. Note that the bottom 10 cm of this fence remained non-electrified to enable safe access for small mammals; 3) the “I” plots (2 x 2 cm metal mesh fence) excluded all mammals. We double-folded the mesh at the bottom 50 cm to reduce the mesh size to smaller than 1 x 1 cm openings; and 4) the “None” plots were surrounded by a 1 m tall mosquito net (1.5 x 2 mm) to exclude all animals. The top of the plot was covered with a mosquito-meshed wooden frame mounted to the corner posts (roof). We treated these plots a few times with biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) to remove insects that might have entered during data collection or that hatched from the soil, but amounts were negligible and did not impact soil moisture conditions within these plots.
To assess whether the design of the “None” exclosure (mesh and roof) affected the response variables within the plots and, therefore, influenced the results, we established an additional six “micro-climate control” exclosures (one in each of the six grasslands) (Risch and others 2013, 2015). These exclosures were built as the “None” exclosures but were open at the bottom (20 cm) of the 3-m side of the fence facing away from the prevailing wind direction to allow invertebrates to enter. A 20-cm high and 3-m long strip of metal mesh was used to block access to small mammals. Thus, this construction allowed a comparable micro-climate to the “None” plots, but also a comparable feeding pressure by invertebrates to the “I” plots. We compared various properties within these exclosures against one another to assess if our construction altered the conditions in the “None” plots. We showed that differences in plant (e.g., vegetation height, aboveground biomass) and soil properties (e.g., soil temperature, moisture) found between the “I” and the “None” treatments were not due to the construction of the “None” exclosure, but a function of animal exclusions, although the amount of UV light reaching the plant canopy was significantly reduced (Risch and others 2013).
Aboveground invertebrate sampling
Aboveground invertebrates were sampled with two different methods to capture both ground- and plant-dwelling organisms: 1) we randomly placed two pitfall traps (67 mm in diameter, covered with a roof) filled with 20% propylene glycol in one 1 x 1 m subplot of the 2 x 3 m treatment plots in spring 2013 (May) and emptied them every two weeks until late September 2013 (Vandegehuchte and others 2017b, 2018). A pitfall trap consisted of a plastic cylinder (13 cm depth, 6.75 cm diameter). Within each cylinder we placed a 100 ml plastic vial with outer diameter 6.70 cm and on top of the cylinder we placed a plastic funnel to guide the invertebrates into the vials. Each trap was cover with a cone-shaped and transparent plastic roof to protect the trap from rain (Vandegehuchte and others 2017b, 2018). Note that in the “None” plots only one trap was placed as control to check for effectiveness of the exclosure. 2) We vacuumed all invertebrates from a 60 x 60 cm area on another 1 x 1 m subplot with a suction sampler (Vortis, Burkhard manufacturing CO, Ltd., Rickmansworth, Hertfordshire, UK) every month from June to September 2013 (Vandegehuchte and others 2017b, 2018). For this purpose, we quickly placed a square plastic frame (60 x 60 x 40 cm) with a closable mosquito mesh sleeve attached to the top edge into the plot from the outside. The suction sample was then inserted into through the sleeve and operated for 45 s to collect the invertebrates (Vandegehuchte and others 2017b, 2018).
We sorted the ≈100 000 individuals collected with both methods by hand and identified each individual morphologically to the lowest taxonomic level feasible (59 taxa, including orders, suborders, subfamilies, families; phylum for Mollusca). These taxa belonged to the following feeding types: 19 herbivores, 16 detritivores, 9 predators, 8 mixed feeders, 5 omnivores and 2 non-classified feeders (or not feeding as adults) (Vandegehuchte and others 2017b). We summed the numbers from the two pitfall traps and the suction sampling over the course of the 2013 season to represent the aboveground invertebrate abundance and community composition of a plot. Note: we did not specifically attempt to catch flying invertebrates with e.g., sticky traps, thus a few flying insects may have been missed with our vacuum sampling approach.
Sampling of plant properties
The vascular plant species composition was assessed at peak biomass every summer (July) by estimating the frequency of occurrence of each species with the pin count method in each plot (Frank and McNaughton 1990). A total of 172 taxa occurred within our 90 plots and we calculated plant species richness for each plot separately. We used the 2013 data in this study. Plant quality was assessed every year in July and September; here we use plant quality at the end of the experiment (September 2013). Two 10 x 100 cm wide strips of vegetation per plot were clipped, combined, dried at 65°C, and ground (Pulverisette 16, Fritsch, Idar-Oberstein, Germany) to pass through a 0.5 mm sieve. Twenty randomly selected samples across all treatments were analysed for N (Leco TruSpec Analyser, Leco, St. Joseph, Michigan, USA) (Vandegehuchte and others 2015). Nitrogen concentrations of the other samples were then estimated from models established for the experiment and the entire SNP relating Fourier transform-near infrared reflectance (FT-NIR) spectra to the measured values of N using a multi-purpose FT-NIR spectrometer (Bruker Optics, Fällanden, Switzerland) (Vandegehuchte and others 2015). Root biomass was sampled every fall by collecting five 2.2 cm diameter x 10 cm deep soil samples (Giddings Machine Company, Windsor, CO, USA) per plot (450 samples year-1). The samples were dried at 30 °C and roots were sorted from the sample by hand. We sorted each sample for 1 h which allowed to retrieve over 90% of all roots present in the samples (Risch and others 2013). The roots were then dried at 65 °C for 48 and weighed to the nearest mg. We averaged the values per plot and used the 2013 data only in this study.
Sampling of edaphic communities
In 2009, 2010, and 2011 we collected three composited soil samples (5 cm diameter x 10 cm depth; AMS Samplers, American Falls, ID, USA) and assessed bacterial community structure using T-RFLP profiling (Liu and others 1997; Blackwood and others 2003; Hodel and others 2014). We detected a total of 89 operational taxonomic units (OTUs). These values are in accordance with other studies reporting OTU richness (Wirthner and others 2011; Zumsteg and others 2012; Meola and others 2014) using T-RFLP profiling, a method that detects the most abundant, and thus likely, the most relevant, taxa. We averaged the data over the three years of collections for our calculations. Microbial biomass carbon (MBC) was determined with the substrate-induced method (Anderson and Domsch 1978) every fall (September) between 2009 and 2013 by collecting three mineral soil samples (5 cm diameter × 10 cm mineral soil core, AMS Samplers, American Falls, ID, USA). The three samples were combined (90 samples for each sampling year), immediately put on ice, taken to the laboratory, passed through a 2-mm sieve and stored at 4°C. Again, we only used the 2013 data in this study.
Soil samples (5 cm diameter x 10 cm depth) to extract soil arthropods were collected in June, July, and August 2011 with a soil corer lined with a plastic sleeve to ensure an undisturbed sample (total of 270 samples). The plastic line core was immediately sealed on both ends using cling film and put into a cooler. All plots were sampled within three days and the extraction of arthropods started the evening of the sampling day using a high-gradient Tullgren funnel apparatus (Crossley and Blair 1991; Vandegehuchte and others 2015). Samples were kept in the extractor for four days and the soil arthropods were collected in 95% ethanol. All individuals were counted and each individual was identified morphologically to the lowest level feasible [76 taxa, including orders, suborders, subfamilies, families (Protura, Thysanoptera, Aphidina, Psylina, Coleoptera, Brachycera, Nematocera, Auchenorryncha, Heteroptera, Formicidae); sub-phylum for Myriapoda, for Acari and Collembola also including morpho-species). Note that we also included larval stages (nine of the 76 taxa) (Vandegehuchte and others 2015). All data were summed over the season. A detailed species list for mites and collembolans is published (Vandegehuchte and others 2017a) [https://doi.org/10.1371/journal.pone.0118679.s001]. Earthworms are rare in the SNP and therefore were not included. We collected eight random 2.2 cm diameter x 10 cm deep soil cores from each plot in September 2013 to determine the soil nematode community composition. The samples were mixed and the nematodes were extracted from 100 ml of fresh soil using Oostenbrink elutriators (Oostenbrink 1960). All nematodes in a 1 ml of the 10 ml extract were counted, a minimum of 150 individuals sample-1 were identified to genus or family level using (Bongers 1988), the numbers of all nematodes were extrapolated to the entire sample and expressed for a 100 g dry sample. In total we identified 63 genus or family levels (Vandegehuchte and others 2015). The list of all the nematodes found is published (Vandegehuchte and others 2015) [http://www.oikosjournal.org/appendix/oik-03341] or DOI: [doi: 10.1111/oik.03341].
We are aware that sampling soil microbes from 2009 to 2011 and soil arthropods in 2011 was not ideal, but we are positive that this does not bias the results. Most of the parameters measured in our experiment either already showed a treatment response after the first growing season (e.g., plant biomass) or did not respond over the entire time experiment (e.g., microbial biomass C). The microbial community composition (2009 – 2011) was highly influenced by inter-annual differences in temperature and precipitation, but did not differ between treatments or vegetation types (Hodel and others 2014). We therefore felt comfortable using the 2009 through 2011 data for describing the soil microbial community in our experimental treatments. Similarly, we are positive that our soil arthropod data are representative. We did assess soil arthropods in August 2012 and found no differences to the August 2011 data. However, we did not feel comfortable combining the 2011 June, July, August data with only August data for 2012 for our analyses.
Sampling of soil properties
We collected three soil samples (5 cm diameter x 10 cm depth) in each plot in September 2013 after removing the vegetation. First, we collected the top layer of mineral soil rich in organic matter, the surface organic layer or rhizosphere, typically 1 to 3 cm in depth with a soil corer (AMS Samples, American Falls, Idaho, USA). Second, we collected a 10 cm mineral soil core beneath this surface layer. The cores for each layer were composited, dried at 65 °C for 48 h and fine-ground to pass a 0.5 mm screen. We then analysed all samples for total C using a Leco TruSpec Analyser (Leco, St. Joseph, Michigan, USA). Mineral soil pH was measured potentiometrically in 1:2 soil:CaCl2 solution with an equilibration time of 30 min.
Soil net N mineralisation was assessed during the 2013 growing season (Risch and others 2015). For this purpose, we randomly collected a 5 cm diameter x10 cm deep soil sample with a soil corer (AMS Samples, American Falls, Idaho, USA) after clipping the vegetation in June 2013. After weighing and sieving (4 mm mesh) the soil, we extracted a 20 g subsample in 1 mol l-1 KCl for 1.5 h on an end-over-end shaker and thereafter filtered it through ashless folded filter paper (DF 5895 150, ALBET LabScience, Hahnenmühle FineArt GmbH, Dassel, Germany). From these filtrates NO3- concentrations were measured colorimetrically (Norman and Stucki 1981) and NH4+with flow injection analysis (FIAS 300, Perkin Elmer, Waltham Massachusetts, USA) (Risch and others 2015). We dried the rest of the sample 105 °C to constant mass to determine fine,fraction bulk density. A second soil sample was collected within each plot in June 2013 with a corer lined with a 5 x 13 cm aluminium cylinder. The corer was driven 11.5 cm deep into the soil so that the top 1.5 cm of the cylinder remained empty. Into this space we placed a polyester bag (250 µm) filled an ion-exchanger resin to capture the incoming N. The bag was filled with a 1:1 mixture of acidic and alkaline exchanger resin (ion-exchanger I KA/ion exchanger IIIAA, Merck AG, Darmstadt, Germany). We then removed 1.5 cm soil at the bottom of the cylinder and placed a second resin exchanger bag into this space to capture the N leached from the soil column. To assure that the exchange resin was saturated with H+ and Cl- prior to filling the bags, the mixture was stirred with 1.2 ml l-1 HCl for 1 h and then rinsed with demineralized water until the electrical conductivity of the water reached 5 µm cm-1. The cylinder with the resin bags in place was reinserted into the soil with the top flush to the soil surface and incubated for three months. We recollected the cylinders in September 2013. Each resin bag and 20 g of sieved soil (4 mm mesh) from each cylinder were then separately extracted with KCl and NO3- and NH4+ concentrations were measured. Nitrate and NH4+ concentrations of all samples were then converted to a content basis by multiplying their values with fine fraction bulk density. Net N mineralisation was thereafter calculated as the difference between the N content of the samples collected at the end of the three-month incubation (including the N extracted from the bottom resin bag) and the N content at the beginning of the incubation (Risch and others 2015).
Soil CO2 emissions were measured every two weeks between 0900 and 1700 hrs from early May through late September 2013 with a PP-Systems SRC-1 soil respiration chamber (15 cm high, 10 cm diameter; closed circuit) attached to a PP-Systems EGM-4 infrared gas analyser (PP-Systems, Amesbury, MA, USA) on two locations per plot (Risch and others 2013). The chamber was placed on randomly placed, permanently installed PVC collars (10 cm diameter) driven 5 cm into the soil at the beginning of the study (Risch and others 2013). Freshly germinated plants growing within the collars were removed prior to each measurement to avoid measuring plant respiration or photosynthesis. The two measurements collected per plot and sampling date were averaged.
Soil moisture (with time domain reflectometry; Field-Scout TDR-100, Spectrum Technologies, Plainfield, Illionois, USA) and temperature (with a waterproof digital pocket thermometer; Barnstead International, Dubuque, Iowa, USA) were measured at five random locations per plot every two weeks during the growing seasons during the experiment for the 0 to 10 cm depth (Risch and others 2013, 2015). As soil moisture and soil temperature were highly negatively correlated (Risch and others 2013), we only used soil moisture for this study. We used plot-level averages of all values available to capture soil moisture variability during the five years of the experiment. The results remained unchanged when we only used soil moisture from the 2013 growing season.
Numeral calculations and statistical analyses
Ecosystem coupling. We conducted principal component analyses (PCAs; unscaled) at the complete dataset level using the abundances of each taxonomical entity to describe each of the five different communities used in this study: aboveground-dwelling invertebrates, vascular plants, soil microorganisms, soil arthropods and soil nematodes. We retained the first two components (PCA axis 1 and PCA axis 2) of each analysis as we found them to adequately represent the temporal and spatial variability of our 90 treatment plots in previous studies55,67. Together they explained a total of 71.70% of the variation for aboveground invertebrates, 44.36% for plants, 44.85% for soil microorganisms, 61.85% for soil arthropods and 77.19% for soil nematodes. In addition, we used soil pH and soil organic C content as a proxy for soil chemical properties, soil bulk density as a proxy for soil physical properties and soil moisture (negatively correlated with soil temperature) as a proxy for soil micro-climatic conditions for an overall total of fourteen constituents.
We calculated ecosystem coupling9 for each exclosure treatment within each vegetation type (i.e., 2  5 treatment combinations in total) as an integrated measure of pairwise ecological interactions between ecosystem constituents representing ecological communities and the soil abiotic environment. These ecological interactions are defined by non-parametric Spearman rank correlation analyses between two constituents, excluding interactions involving two abiotic constituents (e.g., soil pH vs. soil moisture) and interactions between the first (PC1) and second (PC2) component of each community type, as these are orthogonal by definition. Interactions between abiotic constituents were excluded from the analyses because the focus of our study was on communities and how they interact with one another and their surrounding environment; therefore, including abiotic-abiotic interactions was not of interest here. Given that the effectiveness of our experimental design resulted in that no community composition data of aboveground-dwelling invertebrates was available for the “None” plots (all animals excluded), only thirteen instead of fourteen constituents were included in the ecosystem coupling calculations for this treatment. The complete absence of aboveground invertebrates represents the most extreme case of disturbance between aboveground animal communities and the rest of the ecosystem constituents. This may have resulted in a slight overestimation of ecosystem coupling for these plots.
	Average ecosystem coupling was calculated as follows:
Ecosystem coupling=
where Xi is the absolute Coupling was calculated value of the Spearman’s rho coefficient of the ith correlation for each treatment within each vegetation type (i.e., based on nine replicates each), considering and n is the number of pairwise comparisons considered (n = a total of 80; interactions (56 in the case of the “None” treatment). We considered a total of 40 biotic-biotic interactions (i.e., concerning two community-level principal components such as plants and microbes; 24 in the case of the “None” treatment) and 40 abiotic-biotic (i.e., concerning one community-level principal component and one abiotic factor, e.g., plant community and soil properties; 32 in the case of the “None” treatment).	Coupling was calculated for each treatment within each vegetation type (i.e., based on nine replicates each), considering a total of 80 interactions (56 in the case of the “None” treatment). We considered a total of 40 biotic-biotic interactions (i.e., concerning two community-level principal components such as plants and microbes; 24 in the case of the “None” treatment) and 40 abiotic-biotic (i.e., concerning one community-level principal component and one abiotic factor, e.g., plant community and soil properties; 32 in the case of the “None” treatment).
To establish whether constituents were significantly and positively coupled within treatments (i.e., the average of their correlation coefficients were greater than in a null model where correlation only happens by chance), we calculated one-tailed p-values based on permutation tests with 999 permutations.

We considered six ecosystem functions and process rates commonly used to assess ecosystem functioning (Meyer and others 2015; Manning and others 2018). Plant N content represents a measure of forage quality, while plant richness has been shown to stabilise biomass production, thus allowing the system to respond to changes in herbivory. Soil net N mineralisation, soil respiration, root biomass, and microbial biomass represent fluxes or stocks of energy. For all functions and processes higher values represent higher functioning (Manning and others 2018). All these variables were measured in the last year of the experiment (2013). We then quantified ecosystem multifunctionality using the multiple threshold approach (Byrnes and others 2014; Manning and others 2018), which considers the number of functions that are above a certain threshold, over a series of threshold values (typically 10-99%) that are defined based on the maximum value of each function. We weighted all our functions equally for these calculations (Manning and others 2018). The number of functions in a plot with values higher than a given threshold value for the respective function is summed up. The sum represents ecosystem multifunctionality for that plot. Given that choosing any particular threshold as a measure of ecosystem multifunctionality is arbitrary, we calculated the average of thresholds from 10-90% (in 10% intervals) as a more integrated representation of ecosystem multifunctionality.
We used Pearson correlations to explore the relationships between ecosystem coupling (all interactions, biotic-biotic interactions, abiotic-biotic interactions involving above- and belowground constituents, and all interactions, biotic-biotic interactions, abiotic-biotic interactions involving belowground constituents only) and ecosystem multifunctionality by calculating the slopes of all relationships between ecosystem coupling and multifunctionality for all thresholds between 10 and 99%. We also related ecosystem coupling with the average of multifunctionality at thresholds between 30-80% as explained before and considered this correlation as a robust indication of the type of association between these two variables. In addition, we explored the relationships between ecosystem coupling (all interactions, biotic-biotic interactions, abiotic-biotic interactions involving above- and belowground constituents, and all interactions, biotic-biotic interactions, abiotic-biotic interactions involving belowground constituents only) and individual ecosystem functions. The effects of exclosures and vegetation type on individual functions and multifunctionality were evaluated using linear mixed effects models ('lme' function of the nlme package), with exclosure and vegetation type as fixed effects and fence as a random factor. All statistical analyses and numerical calculations were done in R version 3.4.0 (R Core Team 2016).

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- Risch AC, Haynes AG, Busse MD, Filli F, Schütz M. 2013. The response of soil CO2 fluxes to progressively excluding vertebrate and invertebrate herbivores depends on ecosystem type. Ecosystems 16:1192–202.
- Risch AC, Schütz M, Vandegehuchte ML, Van Der Putten WH, Duyts H, Raschein U, Gwiazdowicz DJ, Busse MD, Page-Dumroese DS, Zimmermann S. 2015. Aboveground vertebrate and invertebrate herbivore impact on net N mineralization in subalpine grasslands. Ecology 96:3312–22.
- Schütz M, Risch AC, Achermann G, Thiel-Egenter C, Page-Dumroese DS, Jurgensen MF, Edwards PJ. 2006. Phosphorus translocation by red deer on a subalpine grassland in the Central European Alps. Ecosystems 9:624–633.
- Schütz M, Risch AC, Leuzinger E, Krüsi BO, Achermann G. 2003. Impact of herbivory by red deer (Cervus elaphus L.) on patterns and processes in subalpine grasslands in the Swiss National Park. For Ecol Manage 181:177–88.
- Vandegehuchte ML, van der Putten WH, Duyts H, Schütz M, Risch AC. 2017a. Aboveground mammal and invertebrate exclusions cause consistent changes in soil food webs of two subalpine grassland types, but mechanisms are system-speciﬁc. Oikos 126:212–23.
- Vandegehuchte ML, Raschein U, Schütz M, Gwiazdowicz DJ, Risch AC. 2015. Indirect short- and long-term effects of aboveground invertebrate and vertebrate herbivores on soil microarthropod communities. PLoS One 10:e0118679.
- Vandegehuchte ML, Schütz M, de Schaetzen F, Risch AC. 2017b. Mammal-induced trophic cascades in invertebrate food webs are modulated by grazing intensity in subalpine grassland. J Anim Ecol 86:1434–46.
- Vandegehuchte ML, Trivellone V, Schütz M, Firn J, de Schaetzen F, Risch AC. 2018. Mammalian herbivores affect leafhoppers associated with specific plant functional types at different timescales. Funct Ecol 32:545–55.
- Wirthner S, Frey B, Busse MD, Schütz M, Risch AC. 2011. Effects of wild boar (Sus scrofa L.) rooting on the bacterial community structure in mixed-hardwood forest soils in Switzerland. Eur J Soil Biol 47:296–302. http://dx.doi.org/10.1016/j.ejsobi.2011.07.003
- Zumsteg A, Luster J, Göransson H, Smittenberg RH, Brunner I, Bernasconi SM, Zeyer J, Frey B. 2012. Bacterial, Archaeal and Fungal Succession in the Forefield of a Receding Glacier. Microb Ecol 63:552–64. https://doi.org/10.1007/s00248-011-9991-8

ecosystem-coupling

display_name: ecosystem-coupling

ecosystem-functions

display_name: ecosystem-functions

ecosystem-multifunctionality

display_name: ecosystem-multifunctionality

exclusion

display_name: exclusion

grassland

display_name: grassland

grazing

display_name: grazing

invertebrates

display_name: invertebrates

subalpine

display_name: subalpine

swiss-national-park

display_name: swiss-national-park

vertebrates

display_name: vertebrates

en: Ecosystem coupling and multifunctionality - exclosure experiment


maintainer: Michael Lehning

en: terrestrial-laser-scanning winter-tourism snow-conservation snow snowpack snow-farming

state: active

type: dataset

en: Fluela .smet

en: Meteodata used as input for SNOWAPCK simulations, orginating from Station Windtunnel and DAV.

format: SERVICE

en: HS Martell spring 2015

media_type: text/plain

en:
Snow depth/ height of snow heap in spring 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

format: TXT

mimetype: text/plain

en: HS Fluela spring 2015

en:
Snow depth/ height of snow heap in spring 2015 obtained by terrrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903

en: Martell .smet

en: Meteodata used as input for SNOWAPCK simulations, orginating from Station Hintermartell.

en: HS Fluela autumn 2015

en:
Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903
Nodata: -9999

en: Martell .sno

en: Input snow profile (.sno file) used for SNOWPACK simulations of the Martell heap

en: HS Martell autumn 2015

en:
Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

en: Fluela .sno

en: Input snow profile (.sno file) used for SNOWPACK simulations of the Flüela heap

en:
Two data sets obtained for snow farming projects (Fluela, Davos, CH and Martell, IT) in 2015.

The data set contains for each site:

* 10 cm GIS raster of snow depth calculated from terrestrial laserscanning surveys (TLS) in the end of winter season (April/May)

* 10 cm GIS raster of snow depth calculated from TLS in the end of summer season (October)

Input files for SNOWPACK model:

* .sno: snow profile at the end of winter

* .smet: meteorological data measured by weather stations in the area

For more details see Grünewald, T., Lehning, M., and Wolfsperger, F.: Snow farming: Conserving snow over the summer season, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-93, in review, 2017.

snow

display_name: snow

snow-conservation

display_name: snow-conservation

snow-farming

display_name: snow-farming

snowpack

display_name: snowpack

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

winter-tourism

display_name: winter-tourism

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Snowfarming data set Davos and Martell 2015


maintainer: EnviDat Support

en: photogrammetry snow-depth-distribution davos snow-hydrology avalanches dischma

en: Snowdepth maps

format: GeoTIFF

en:
The available datasets are snow depth maps with a spatial resolution of 0.5 m derived from images of the survey camera Vexcel Ultracam mounted on a piloted airplane. Image acquisition was carried out during the approximately peak of winter (time when the thickest snowpack is expected) in spring. The snow depth maps are calculated by the subtraction of a summer-DTM from the processed winter- DSM of the corresponding date. The summer-DTM used was derived from a point cloud of an airborne laser scanner from 2020.

Due to the occurrence of inaccuracies of the calculated snow depth values caused by the photogrammetric method, we applied different masks to significantly increase the reliability of the snow depth maps. We masked out settled areas, high-frequented streets and technical constructions, pixels with high vegetation (height > 0.5 m) , outliers and unrealistic snow depth values. In addition, we modified the snow depth values of snow-free pixels to 0.
The information on buildings and infrastructure comes from the exactly classified ALS point cloud and the TLM dataset from Swisstopo (https://www.swisstopo.admin.ch/de/geodata/landscape/tlm3d.html#links). High vegetation is also derived from the classification and the calculated object height from the point cloud.
Outliers and unrealistic snow depth values are defined as negative snow depth values and snow depths exceeding 10 m. The classification of each pixel of the corresponding orthophoto into snow-covered or snow-free is based on the application of a threshold of the NDSI or manually determined ratios of the RGB values.

An extensive accuracy assessment proves the high accuracy of the snow depth maps with a root mean square error of 0.25 m for the year 2017 and 0.15 m for the following snow depth maps.

The work is published in:

avalanches

display_name: avalanches

davos

display_name: davos

dischma

display_name: dischma

photogrammetry

display_name: photogrammetry

snow-depth-distribution

display_name: snow-depth-distribution

snow-hydrology

display_name: snow-hydrology

en: Snow depth mapping by airplane photogrammetry (2017 -  ongoing)


aerosol-data-davos-wolfgang

title_for_slug: aerosol-data-davos-wolfgang

en: drincz ice-nucleation inp aerosol particles raclets

en: APS Dataset Davos Wolfgang

en: The APS file contains aerosol data (total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) for aerodynamic diameters between 0.5 μm and ~20 μm as well as instrument characteristics, in a temporal resolution of 20 seconds, with time in UTC, measured at Davos Wolfgang.

mimetype: application/x-netcdf

en: OPC GT-526S Dataset Davos Wolfgang

media_type: text/csv

en: Particle counts were recorded in six size channels (0.3, 0.5, 0.8, 1.5, 2.5 and 5 μm) in a resolution of 20 seconds (time in UTC) by a particle counter (GT-526S, Met One Instruments, Inc.).

format: CSV

mimetype: text/csv

en: DRINCZ Dataset Davos Wolfgang

en: The DRINCZ file contains information on temperature (in °C) dependent frozen fractions, number of Ice Nuleating Particles (INP, per standard liter) and differential INP concentrations (per standard liter and Kelvin).

en: OPC-N3 Dataset Davos Wolfgang

en: Particle concentrations in a size range of 0.35 μm to 40 μm were measured with an OPC-N3 (Alphasense, Inc.) in a resolution of 20 seconds (time in UTC). PM₁, PM₂,₅ and PM₁₀ were directly derived.

en: SMPS Dataset Davos Wolfgang

en: The SMPS file contains aerosol data (particle concentration, total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) in a size range between 12 and 460 nm (electrical mobility diameter) as well as instrument characteristics (sample temperature, pressure, relative humidity, mean free path and gas viscosity), in a temporal resolution of 2 minutes, with time in UTC, measured at Davos Wolfgang.

en:
Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.

Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0).

Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³).

Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³).

Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

aerosol

display_name: aerosol

drincz

display_name: drincz

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

particles

display_name: particles

raclets

display_name: raclets

en: Aerosol Data Davos Wolfgang


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

en: Data plot of the field station (SCF)

media_type: application/pdf

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

format: PDF

en: Site aerial photo (Schänis)

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

en: Forest station data (SCB)

en: Data file.

en: Site photo of the forest station (SCB)

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

en: Field station data (SCF)

en: Data plot of the forest station (SCB)

en: Further details on the data repository

en: Meta data documentation.

en: Site photo of the field station (SCF)

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

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Schänis in Switzerland where one station is located within a natural mixed forest stand (SCB) with European beech (_Fagus sylvatica_; 130-150 yrs), European silver fir (_Abies alba_; 130-150 yrs) and European ash (_Fraxinus excelsior_; 130-150 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, SCF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Schänis is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Schänis, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1998 onwards


en: snow alpine3d-simulations snow-cover alpine3d snow-hydrology snow-distribution alpine-precipitation

en: ADS datasets and simulation inputs

media_type: application/zip

en: The file contains the ADS datasets of snow depth and input data used for simulations.

format: ZIP

mimetype: application/zip

en:
Dataset (Model input, snow distribution and validation) for the precipitation scaling paper, which should be cited along with the data set citation.

This data is useful for distributed hydrological modelling or other tasks that involve the study of snow distribution and precipitation in the high Alpine.

The format of the data is for Alpine3D (models.slf.ch) model runs but other models could be used, too.

Please cite:

_Vögeli, C., Lehning, M., Wever, N., Bavay M., 2016: Scaling Precipitation Input to Spatially Distributed Hydrological Models by Measured Snow Distribution., Front. Earth Sci. 4: 108. doi: 10.3389/feart.2016.00108._

Dataset is provided as a single zip file.
The archive contains two directories, the valuable distributed snow depth maps for the landscape Davos and the simulation input.
The archive also contains the file: "ReadMeMetadataDataSetPrecipitationScaling" which explains the data structure.

alpine-precipitation

display_name: alpine-precipitation

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-distribution

display_name: snow-distribution

snow-hydrology

display_name: snow-hydrology

en: Precipitation Scaling Data Set (Vögeli et al., Frontiers)


horodateur

maintainer: Service de la mobilité et de l’aménagement des espaces publics Ville de Lausanne, Gestionnaire de la donnée

title_for_slug: horodateur

name: Frédéric Ducry, Responsable de diffusion

label: Métadonnée sur geocat.ch

label: Métadonnée complète sur viageo.ch

fr: Guichet cartographique de Lausanne

fr: Guichet en ligne : Guichet cartographique de Lausanne

fr: Horodateur (CSV)

fr: Télécharger sur viageo.ch

fr: Horodateur (SHP)

format: SHP

fr: Données des horodateurs de la commune de Lausanne. Contient les emplacements géographiques des horodateurs.

spatial: Lausanne

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

lausanne

fr: Ville de Lausanne

fr: Le service de la mobilité et de l’aménagement des espaces publics (MAP) de la Ville de Lausanne publie ses géodonnées sous forme de fichiers à télécharger. Toutes les géodonnées actuellement disponibles et soumises aux conditions générales d'aquisition et d'utilisation des géodonnées de base en libre accès sont listées ici.

political_level: commune

value: Stadt Lausanne - DCAT Harvester

fr: Horodateur


zone-moderee

maintainer: Frédéric Ducry, Responsable de diffusion

title_for_slug: zone-moderee

name: Service de la mobilité et de l’aménagement des espaces publics Ville de Lausanne, Gestionnaire de la donnée

fr: Zone modérée (CSV)

fr: Zone modérée (SHP)

fr:
Données des zones modérées de la commune de Lausanne.
Contient les zones 30, piétonnes, et de rencontres.

fr: Zone modérée


amenagement-cyclable

title_for_slug: amenagement-cyclable

fr: Aménagement cyclable (CSV)

fr: Aménagement cyclable (SHP)

fr:
Données des aménagements cyclables de la commune de Lausanne.
Contient les aménagements, les emplacements en libre-service, les pompes et les parkings pour vélos.

fr: Aménagement cyclable


stationnement

title_for_slug: stationnement

fr: Stationnement (CSV)

fr: Guichet cartographique de Lausanne

fr: Guichet en ligne : Guichet cartographique de Lausanne

fr: Stationnement (SHP)

fr:
Données du stationnement public de la commune de Lausanne.
Contient les places de parcs et les zones macarons.

fr: Stationnement


fr: Réseau routier du 30km/h de nuit (SHP)

fr: Télécharger sur viageo.ch

fr:
Données du réseau routier du 30km/h de nuit de la commune de Lausanne.
Contient les axes des voies de communication, hors zones modérées déjà existantes, impactés par les restrictions nocturne de vitesse.

regi

fr: Régions et villes

tran

fr: Transports

lausanne

fr: Ville de Lausanne

fr: Réseau routier du 30km/h de nuit


mobilier-urbain

title_for_slug: mobilier-urbain

fr: Mobilier urbain (CSV)

fr: Mobilier urbain (SHP)

fr:
Données du mobilier urbain de la commune de Lausanne.
Contient les emplacements géographiques des bancs publics.

fr: Le service de la mobilité et de l’aménagement des espaces publics (MAP) de la Ville de Lausanne publie ses géodonnées sous forme de fichiers à télécharger. Toutes les géodonnées actuellement disponibles et soumises aux conditions générales d'aquisition et d'utilisation des géodonnées de base en libre accès sont listées ici.

fr: Mobilier urbain


marquage-routier

title_for_slug: marquage-routier

fr: Guichet cartographique de Lausanne

fr: Marquage routier (CSV)

fr: Marquage routier (SHP)

fr:
Données du marquage routier de la commune de Lausanne.
Contient le balisage au sol.

fr: Marquage routier


fr: belasteter-standort altstandort grundwasserschutz altlast

label: WebGIS Kanton Schwyz, Thema einblenden

label: geocat.ch permalink

fr: WFS-Dienst des Kantons Schwyz

de: WFS-Dienst des Kantons Schwyz

en: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

format: WFS

fr: Kataster der belasteten Standorte (KbS)

de: Kataster der belasteten Standorte (KbS)

en: Kataster der belasteten Standorte (KbS)

it: Kataster der belasteten Standorte (KbS)

format: WMS

fr: Bei den im Kataster aufgenommen Standorten handelt es sich um Standorte mit begrenzter Ausdehnung, bei denen feststeht oder mit grosser Wahrscheinlichkeit zu erwarten ist, dass sie mit Abfällen belastet sind (Art. 5 Abs. 3 Altlasten-Verordnung). Nicht in den Kataster eingetragen werden (insbesondere über den Luftpfad verursachte) grossflächige diffuse Belastungen sowie Areale mit ausschliesslich belasteter Gebäudesubstanz (z. B. durch Asbest). Beim Kataster der belasteten Standorte handelt es sich um ein dynamisches Arbeitsinstrument, bei dem abhängig von den aktuellen Erkenntnissen Standorte aufgenommen, verändert oder wieder gelöscht werden. Der Kataster gibt somit immer nur den aktuellen Wissensstand wieder, eine Gewähr für die Richtigkeit (z. B. dass ein nicht eingetragenes Grundstück unbelastet ist) besteht nicht. Insbesondere im Rahmen von Bauvorhaben oder Nutzungsänderungen können altlastenrechtliche oder abfallrechtliche Massnahmen notwendig werden. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Kanton Schwyz (SZ)

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz

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

political_level: canton

value: SZ-Kt Geoinformation - Geocat Harvester


en: land-use-transformations land-use-change land-use-simulations digital-zoning-plans spatial-planning

en: Legend simulated maps

en:
Table of Content: 1. General context of the data set "LUSzoning”; 2. Background and aims of the study using the data set LUSzoning; 3. The data set LUSzoning.
1. General context of the data set "LUSzoning".
The data set "LUSzoning" stands for Land-use simulations integrating zoning regulations in Spanish functional urban areas. The data set has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2021. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, digital zoning plans) into quantitative land-change modelling approaches at the urban regional level.
2.	Background and aims of the study using the data set “LUSzoning”.
As part of the CONCUR project, a specific task was to integrate planning spatial policies in land-change modelling. Planning can be implemented in modelling using either hard or gradual restrictions. Different studies have addressed the inclusion of spatial planning policies in land-use change modelling. However, the integration of zoning constraints is generally established as hard or Boolean-based restrictions (e.g., whether urban development is allowed or not), while not accounting for the spatial heterogeneity or gradual characteristics within planning zones (e.g., whether planning regulations allow low, medium or high urban density), though these could improve real patterns simulations in urban areas. We assume Spanish General Zoning plans were suitable to explore the integration of planning into land-change modelling as soft constrains because they define land-use intensities in the buildable zoning areas. In light of the above considerations, the overall aim of the study was to model urban land-use changes using a multi-scenario approach that integrates digitized zoning plans for the Functional Urban Areas (FUAs) of Madrid, Barcelona, Valencia, and Zaragoza. The following specific objectives were addressed: i) to analyse the role of planning by defining three future scenarios that integrate digitized zoning plans and one scenario that assumes almost no planning intervention; ii) to introduce zoning constraints that reflect different degrees of urban densities; iii) to generate a transferable spatially-explicit modelling framework to integrate planning into land-use change simulations.
Four future land-use demands scenarios were defined for the FUAs. Storylines were created considering probable development scenarios related to zoning plans, current Spanish legislation and sustainability goals defined along two axes: a high market-oriented vs. high planning-intervention axis, and an axis of short-term economic growth vs. long-term sustainable growth. The sustainable development scenario (S1) is characterized by low gross floor area (GFA) growth that is limited to areas that are currently under development according to zoning plans. The business-as-usual scenario (S2) is characterized by medium GFA growth in the range of on-going trends. The strong development scenario (S3) is characterized by high GFA growth rates. Growth is restricted to buildable areas without urbanization project designated in zoning plans. The unrestricted development scenario (S4) prioritizes a high degree of market liberalization characterized by high GFA growth that surpasses population demands. S4 follows a rapid economic growth pattern with almost no planning intervention.
3.	 The data set “LUSzoning”.
The dataset includes 16 .asc raster layers providing the simulated land-uses under four defined scenarios for Barcelona, Madrid, Valencia and Zaragoza Functional Urban Areas (FUAs) for 2030. The simulated raster layers were created using CLUMondo simulation framework and have a spatial resolution of 30m. The .asc layers name include the name of the FUA and scenario number. For example, the output from simulating the urban growth for the city of Zaragoza under Scenario 2 is named “Zaragoza_S2.tif”. Furthermore, a .txt file named “Legend.txt” includes the numeric value of the land-use and the category of land-use that represents to interpret the .asc raster layers. The name of the land-use classes is a reclassification of the Urban Atlas 2012 land-use classes within the four Spanish FUAs analyzed.

digital-zoning-plans

display_name: digital-zoning-plans

land-use-change

display_name: land-use-change

land-use-simulations

display_name: land-use-simulations

land-use-transformations

display_name: land-use-transformations

spatial-planning

display_name: spatial-planning

educ

fr: Éducation, culture et sport

envidat

fr: EnviDat: le portail de données environnementales

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: LUSzoning: Land-use simulations integrating zoning regulations in Spanish functional urban areas


fr: Solarkataster

de: Solarkataster

en: Solarkataster

it: Solarkataster

fr: Dieses Projekt stellt einerseits die im Kanton Schwyz eingeführte Pflicht der Eigenstromerzeugung (Photovoltaik) in Form einer Vollzugsfläche dar. Andererseits werden die Globalstrahlungsdaten dargestellt, auf welchen die Berechnung der Vollzugsfläche beruht.


en: griesgletscher orthoimage glacier dem dsm gletscher orthophoto uav sankt-annafirn alps drone findelengletscher

en: Bulk Data Access

en: Link to the S3 bucket where all the data resources can be downloaded in bulk

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 15th of September 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 28th of September 2015.

en: This .pdf contains an orthoimage for each dataset as well as a Table which displays the number of flights made, image acquired, number of GCP set and the total area covered.

mimetype: application/pdf

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 2nd of July 2016.

en: This folder contains all UAV flights paths that we created for the Sankt Annafirn, the Findelengletscher and Griesgletscher. They have been created with the software eMotion2, that was developped for the eBee platform from Sensefly.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 15th of April 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 13th of September 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 30th of August 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 15th of August 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 21th of July 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 22th of September 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 3rd of August 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 15th of July 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 09th of April 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 19th of April 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 26th of September 2015.

en:
 UAV-derived DSMs and orthoimages

Unmanned Aerial Vehicle (UAV) surveys were conducted between 2015 and 2016 on the Sankt Annafirn, Findelen- and Griesgletscher, situated in the Swiss Alps. Three surveys at the Sankt Annafirn allowed for a full glacier coverage, four surveys at Griesgletscher allowed an almost full glacier coverage and seven surveys at Findelengletscher allowed for a partial coverage of the glacier tongue (see individual datasets for exact extent). For each survey, a high resolution orthoimage and a Digital Surface Model (DSM) was created.

 UAV surveys:

Prior flight, Ground Control Points (GCPs) were deployed on the glacier surface and measured with a differential GPS (Trimble R7 or Leica GPS 1200). They allowed precise georeferencing of the UAV-derived datasets. UAV flight plans were planned with the software *eMotion 2* and a SenseFly eBee was used as surveying platform. The images were then processed with the software Agisoft Photoscan Pro 1.1.6 .

The location and dates of each survey can be found in the table together with the number of flights performed (Nflights), the number of acquired images (Nimages), the number of GCPs set (NGCPs) and the surveyed area.

A folder for each dataset is available (see folder name in table), which contains:

- An orthoimage *glacier_date_photoscan_oi_CH1903+_LV95_0.1m.tif*

- A Digital Surface Model *glacier_date_photoscan_dsm_CH1903+_LV95_0.1m.tif*

- The Agisoft Photoscan automatic processing report  *glacier_date_photoscan_report.pdf*

where:

- *glacier* is the name of the surveyed glacier

- *date* is the date of the UAV image acquisition

- *photoscan* is the name of the photogrammetric software

- *oi* or *dsm* the type of dataset

- *CH1903+_LV95* is the coordinate system and datum of the dataset

- *0.1m* is the resolution of the dataset in meter

- *.tif* is the extention of the dataset

Details about the UAV surveys, the image processing and the accuracy of the UAV-derived products can be found in this publication below.

Paper Citation:
 > _Gindraux et al. 2017. Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’Imagery on Glaciers, Remote Sensing, 9, 186, 1-15, [doi: 10.3390/rs9020186](https://doi.org/10.3390/rs9020186)._

The folder UAV_flight_paths.zip contains all UAV flights performed on the Sankt Annafirn, Findelengletscher and Griesgletscher. The flights were planned with the software eMotion2 and have the .afp extention.

alps

display_name: alps

dem

display_name: dem

drone

display_name: drone

dsm

display_name: dsm

findelengletscher

display_name: findelengletscher

glacier

display_name: glacier

gletscher

display_name: gletscher

griesgletscher

display_name: griesgletscher

orthoimage

display_name: orthoimage

orthophoto

display_name: orthophoto

sankt-annafirn

display_name: sankt-annafirn

uav

display_name: uav

educ

en: Education, culture and sport

en: UAV-derived Digital Surface Models and orthoimages for three alpine glaciers


fr: kanton flachmoor biotop

de: kanton flachmoor biotop

en: kanton flachmoor biotop

it: kanton flachmoor biotop

en: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Kantonale Nutzungsplanung: Naturschutzgebiete, linienbezogene Festlegung

fr: ÖREB: Kantonale Nutzungsplanung: Naturschutzgebiete, Grundnutzung

fr: ÖREB: Kantonale Nutzungsplanung: Naturschutzgebiete, überlagernde Festlegung

fr: ÖREB: Kantonale Nutzungsplanung: Naturschutzgebiete, objektbezogene Festlegung

fr: Rechtsgültige Darstellung aller kantonalen Nutzungspläne im Bereich Natur- und Heimatschutz

fr: Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz ÖREB


fr: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Muotathal, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Muotathal

fr: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren.

spatial: Muotathal


fr: zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: WFS-Dienst des Kantons Schwyz

fr: Nutzungsplanung kommunal Gemeinde Lachen

fr: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Lachen


fr: nutzungsplan zonenplan bauzone grundplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Gersau

de: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Gersau


fr: Darstellung der Imkerstände und Sperrkreise bei Tierseuchenausbrüchen der vier Kantone NW, OW, SZ, UR auf dem WebGis des Kantons Schwyz.

fr: Der Veterinärdienst der Urkantone liefert die Grunddaten der Imker an das Amt für Geoinformation. Mit Hilfe der Grunddaten werden in einem ersten Schritt sämtliche erfassten Bienenstände auf dem WebGIS des Kantons Schwyz dargestellt. Bei einem Tierseuchenausbruch meldet der VdU dem Amt für Geoinformationen den betroffenen Stand. Je nach Seuche (Sauerbrut = 1 km, Faulbrut = 2 km) wird der Sperrkreis auf dem WebGIS SZ eingezeichnet. Via Link auf der Homepage des Labors der Urkantone können interessierte, involvierte Imker nachschauen, wo überall Bienenstände sind und welche Gebiete allenfalls wegen einer Tierseuche gesperrt sind.

name: Veterinärdienst der Urkantone (VdU), Laboratorium der Urkantone


fr: nutzungsplanung strasse kanton oreb flachennutzungsplan

fr: OeREB Nutzungsplanung kantonal Teil Strasse, Anschluss Steinerstrasse Schwyz, Grundnutzung

fr: OeREB Nutzungsplanung kantonal Teil Strasse, Anschluss Steinerstrasse Schwyz, linienbezogene Festlegung

fr: OeREB Nutzungsplanung kantonal Teil Strasse, Anschluss Steinerstrasse Schwyz, überlagernde Festlegung

fr: Nutzungsplanung kantonal Teil Strasse. Geobasisdatensatz Nr. 73B gemäss KGeoiV Kanton Schwyz (SRSZ 214.111)

fr: ÖREB Nutzungsplanung kantonal Teil Strasse Anschluss Steinerstrasse Schwyz


fr: bauzone zonenplan grundplan nutzungsplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Muotathal

en: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".


geschwindigkeitsbereiche

title_for_slug: geschwindigkeitsbereiche

fr: erlaubte Geschwindigkeiten auf Kantonsstrassen

fr: Abbildung der Geschwindigkeit auf den Kantonsstrassen des Kantons Schwyz

fr: Geschwindigkeitsbereiche

de: Geschwindigkeitsbereiche

en: Geschwindigkeitsbereiche

it: Geschwindigkeitsbereiche


fr: zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: WFS-Dienst des Kantons Schwyz

fr: Nutzungsplanung kommunal Gemeinde Vorderthal

it: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Vorderthal


fr: zonenplan grundplan bauzone nutzungsplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Freienbach

fr: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Freienbach


fr: oreb zonenplan bauzone grundplan flachennutzung

fr: ÖREB: Nutzungsplanung kommunal, Freienbach, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Freienbach

fr: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren.


fr: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Unteriberg, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Unteriberg

de: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren.

spatial: Unteriberg


de: zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Wangen

spatial: Wangen (SZ)


abfall-und-rohstoffe

title_for_slug: abfall-und-rohstoffe

fr: abbaustelle bausperrgut rohstoffgewinnung biogener-abfall sonderabfall bauabfalle rekultivierung abfallablagerung kompostierbarer-abfall altmetall

fr: Abfall/Rohstoffe: Steinbruch

de: Abfall/Rohstoffe: Steinbruch

en: Abfall/Rohstoffe: Steinbruch

it: Abfall/Rohstoffe: Steinbruch

fr: Abfall/Rohstoffe: Altmetalle

de: Abfall/Rohstoffe: Altmetalle

en: Abfall/Rohstoffe: Altmetalle

it: Abfall/Rohstoffe: Altmetalle

fr: Abfall/Rohstoffe: Grüngut

de: Abfall/Rohstoffe: Grüngut

en: Abfall/Rohstoffe: Grüngut

it: Abfall/Rohstoffe: Grüngut

fr: A011a: Abfall und Rohstoffe

de: A011a: Abfall und Rohstoffe

en: A011a: Abfall und Rohstoffe

it: A011a: Abfall und Rohstoffe

fr: Abfall/Rohstoffe: Deponie Typ B

de: Abfall/Rohstoffe: Deponie Typ B

en: Abfall/Rohstoffe: Deponie Typ B

it: Abfall/Rohstoffe: Deponie Typ B

fr: Abfall/Rohstoffe: Altfahrzeuge

de: Abfall/Rohstoffe: Altfahrzeuge

en: Abfall/Rohstoffe: Altfahrzeuge

it: Abfall/Rohstoffe: Altfahrzeuge

fr: Abfall/Rohstoffe: Sonderabfälle aus Gewerbe

fr: Abfall/Rohstoffe: Kiesgrube, Sandgrube

de: Abfall/Rohstoffe: Kiesgrube, Sandgrube

en: Abfall/Rohstoffe: Kiesgrube, Sandgrube

it: Abfall/Rohstoffe: Kiesgrube, Sandgrube

fr: Abfall/Rohstoffe: Deponie Typ A

de: Abfall/Rohstoffe: Deponie Typ A

en: Abfall/Rohstoffe: Deponie Typ A

it: Abfall/Rohstoffe: Deponie Typ A

fr: Als Ergänzung zu www.abfall.ch werden in der Karte „Abfall und Rohstoffe“ die Abfallanlagen für Bauabfälle und -sperrgut, biogene Abfälle, Altmetalle, gewerbliche Sonderabfälle sowie die Rohstoffgewinnung und Rekultivierungsstellen geografisch dargestellt. Primär soll die Karte einen Überblick über die einzelnen Standorte verschaffen.

fr: Standorte Abfall und Rohstoffe

de: Standorte Abfall und Rohstoffe

en: Standorte Abfall und Rohstoffe

it: Standorte Abfall und Rohstoffe


fr: zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: WFS-Dienst des Kantons Schwyz

de: WFS-Dienst des Kantons Schwyz

fr: Nutzungsplanung kommunal Gemeinde Schübelbach

fr: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Schübelbach

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz


en: zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Arth

de: Nutzungsplanung kommunal Gemeinde Arth

en: Nutzungsplanung kommunal Gemeinde Arth

it: Nutzungsplanung kommunal Gemeinde Arth

spatial: Arth

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


fr: kanton flachmoor oreb nutzungsplanung biotop

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Hopfräben, linienbezogene Festlegung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Hopfräben, Grundnutzung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Hopfräben, objektbezogene Festlegung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Hopfräben, überlagernde Festlegung

fr: Naturschutzgebiet Hopfräben Rechtsgültige Darstellung des kantonalen Nutzungsplanes im Bereich Natur- und Heimatschutz

fr: ÖREB Nutzungsplanung kantonal Bereich Natur- und Heimatschutz Hopfräben


fr: nutzungsplan zonenplan bauzone grundplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Steinen

de: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Steinen


fr: grundplan zonenplan bauzone nutzungsplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Wollerau

spatial: Wollerau


fr: Revitalisierung Gewässer: Ökomorphologische Klassierung

fr: Ökomorphologie Fliessgewässer

de: Ökomorphologie Fliessgewässer

en: Ökomorphologie Fliessgewässer

it: Ökomorphologie Fliessgewässer

fr: A026b: Ökomorphologie

de: A026b: Ökomorphologie

en: A026b: Ökomorphologie

it: A026b: Ökomorphologie

fr: Darstellung des ökomorphologischen Zustandes der Fliessgewässer im Kanton Schwyz (Ökomorphologie, Stufe F). Die strukturelle Beschaffenheit eines Fliessgewässers hat neben der Gewässerqualität massgeblichen Einfluss auf dessen ökologische Funktionsfähigkeit. Die Ökomorphologiekartierung dient daher der Identifizierung strukturell stark beeinträchtiger Gewässerabschnitte und als Planungsgrundlage für zukünftige Revitalisierungen. Andere Datengrundlagen: - Digitales Gewässernetz der Landeskarten 1:25’000 - Primärflächen 1:25’000 - Gemeinde, Bezirks- und Kantonsgrenzen 1:25’000 - Höhenmodell RIMINI (Auflösung 250 m in der Horizontalen) - Digitale Landeskarten 1:25’000 - Digitale Landeskarten 1:100’000 - Fischgewässer-Karte des Kantons Schwyz 2020 wurden die bestehenden Daten auf das neue Refrenz-Fliessgewässernetz des Kanton Schwyz referenziert.


de: kanton flachmoor oreb nutzungsplanung biotop

fr: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Bätzimatt, überlagernde Festlegung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Bätzimatt, linienbezogene Festlegung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Bätzimatt, Grundnutzung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Bätzimatt, objektbezogene Festlegung

fr: Naturschutzgebiet Bätzimatt Rechtsgültige Darstellung des kantonalen Nutzungsplanes im Bereich Natur- und Heimatschutz

fr: ÖREB Nutzungsplanung kantonal Bereich Natur- und Heimatschutz Bätzimatt


fr: kanton flachmoor oreb nutzungsplanung biotop

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Frauenwinkel, überlagernde Festlegung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Frauenwinkel, objektbezogene Festlegung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Frauenwinkel, Grundnutzung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Frauenwinkel, linienbezogene Festlegung

fr: Naturschutzgebiet Frauenwinkel Rechtsgültige Darstellung des kantonalen Nutzungsplanes im Bereich Natur- und Heimatschutz

fr: ÖREB Nutzungsplanung kantonal Bereich Natur- und Heimatschutz Frauenwinkel


en: kanton flachmoor oreb nutzungsplanung biotop

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Schwantenau, objektbezogene Festlegung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Schwantenau, überlagernde Festlegung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Schwantenau, Grundnutzung

fr: OeREB Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz, Schwantenau, linienbezogene Festlegung

fr: Naturschutzgebiet Schwantenau Rechtsgültige Darstellung des kantonalen Nutzungsplanes im Bereich Natur- und Heimatschutz

fr: ÖREB Nutzungsplanung kantonal Bereich Natur- und Heimatschutz Schwantenau


wanderwegsperrungen

title_for_slug: wanderwegsperrungen

fr: wanderweg tourismus-und-freizeit

de: wanderweg tourismus-und-freizeit

en: wanderweg tourismus-und-freizeit

it: wanderweg tourismus-und-freizeit

fr: Wanderwegsperrungen

de: Wanderwegsperrungen

en: Wanderwegsperrungen

it: Wanderwegsperrungen

fr: Auf dem Schwyzer Wanderwegnetz kommt es immer wieder zu kürzeren oder längeren Sperrungen, welche aufgrund von Sanierungen, Holzereiarbeiten, Rutschung oder anderen Naturgefahren notwendig sind. Solche Sperrungen sollen dem Fachbereich Fuss- und Wanderwege gemeldet werden, damit die Sperrungen inklusive Infoblatt auf dem WebGIS publiziert und aktuell gehalten werden können. Damit dies möglich ist, muss auch das Ende jeder Sperrung gemeldet werden.


panoramatafeln

title_for_slug: panoramatafeln

fr: WFS-Dienst des Kantons Schwyz

en: WFS-Dienst des Kantons Schwyz

fr: Panoramatafeln

de: Panoramatafeln

en: Panoramatafeln

it: Panoramatafeln

fr: Der Kanton Schwyz ist zuständig für das Hauptwanderwegnetz und trägt dafür die Kosten für Planung, Bau, rechtliche Sicherung, Unterhalt und Markierung, soweit dafür nicht Dritte zuständig sind. Um die Attraktivität des Hauptwanderwegnetzes zu steigern, wurden an geeigneten Orten zur Erklärung der Bergwelt und Umgebung Panoramatafeln erstellt. Es gibt über den ganzen Kanton verteilt weitere Panoramatafeln, welche auf private Initiative oder von Gemeinden/Koporationen erstellt wurden und von diesen auch unterhalten werden. Diese Panoramatafeln sind in diesem Datensatz jedoch nicht enthalten.


sportanlagen

title_for_slug: sportanlagen

fr: A102a: Sportanlagen

de: A102a: Sportanlagen

en: A102a: Sportanlagen

it: A102a: Sportanlagen

fr: Sportanlagen

de: Sportanlagen

en: Sportanlagen

it: Sportanlagen

fr: Übersicht aller Sportanlagen im Kanton Schwyz. Neben den Koordinaten und dem Typ der Sportanlage ist jeweils auch ein Link zum Betreiber enthalten.


fr: rettungssystem herzkreislaufsystem

de: rettungssystem herzkreislaufsystem

en: rettungssystem herzkreislaufsystem

it: rettungssystem herzkreislaufsystem

fr: AED-Standorte

de: AED-Standorte

en: AED-Standorte

it: AED-Standorte

fr: Diese Datenebene zeigt die AED-Standorte (automatisierter externer Defibrillator) im Kanton Schwyz, die rund um die Uhr zugänglich sind.


fr: zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Morschach

fr: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Morschach


de: zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Sattel

en: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Sattel


ortstafeln

title_for_slug: ortstafeln

fr: Ortstafeln

de: Ortstafeln

en: Ortstafeln

it: Ortstafeln

fr: Abbildung der Ortstafeln auf den Kantonsstrassen des Kantons Schwyz. Die Daten werden bei Bedarf nachgeführt.


flughindernisse-kanton-schwyz

title_for_slug: flughindernisse-kanton-schwyz

de: WFS-Dienst des Kantons Schwyz

fr: Flughindernisse Kanton Schwyz

de: Flughindernisse Kanton Schwyz

en: Flughindernisse Kanton Schwyz

it: Flughindernisse Kanton Schwyz

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


maintainer: Kantonspolizei des Kantons Zürich, Abteilung Kriminalpolizeiliches Datenmanagement

de: gemeinden einbrueche strafbarehandlungen straftaten strafdelikte kriminalitaet

label: Vorbereiteter Code in R oder Python für jedes Dataset mit csv-Datei(en)

de: Anzahl Einbrüche nach Gemeinden und in den Stadtkreisen der Stadt Zürich

de: Das Total Einbrüche beinhaltet alle polizeilich bekannten, vollendeten und versuchten Einbruchs- und Einschleichdiebstähle. Die Bevölkerungszahlen sind der Einwohnerstatistik des Bundes am Ende des Vorjahres entnommen (bis 2010 ESPOP, ab 2011 STATPOP). Damit wird die Häufigkeitszahl berechnet (Anzahl registrierten Straftaten pro 1000 Einwohner).

de: Anzahl der Einbrüche wie sie in der Kriminalstatistik der Kantonspolizei Zürich erfasst werden. Aufgegliedert nach Gemeinden (im Fall der Stadt Zürich nach Stadtkreisen) und ergänzt mit Angaben zur Bevölkerungszahl. Die polizeiliche Kriminalstatistik (PKS) des Kantons Zürich wird jährlich publiziert. Die polizeiliche Kriminalstatistik verzeichnet nur die polizeilich bekannt gewordene Kriminalität - das sogenannte Hellfeld. Sie ist eine Ausgangsstatistik. D.h. die Straftaten erscheinen nicht zum Tatzeitpunkt in der Statistik. Ausschlaggebend für die Zählung in der PKS ist der Zeitpunkt, an dem die Polizei einen ersten Rapport zur Straftat abgeschlossen hat.

einbrueche

display_name: einbrueche

gemeinden

display_name: gemeinden

kriminalitaet

display_name: kriminalitaet

strafbarehandlungen

display_name: strafbarehandlungen

strafdelikte

display_name: strafdelikte

straftaten

display_name: straftaten

just

fr: Justice, système juridique et sécurité publique

de: Justiz, Rechtssystem und öffentliche Sicherheit

en: Justice, legal system and public safety

it: Giustizia, sistema giuridico e sicurezza pubblica

kantonspolizei-kanton-zuerich

de: Kantonspolizei Zürich

de: Im Auftrag der Regierung und damit der Bevölkerung übernimmt die Kantonspolizei Zürich Verantwortung für die Sicherheit im Kanton Zürich, indem sie vorausschauend handelt, entschlossen Hilfe leistet und Straftaten konsequent aufklärt. Dabei folgt sie den Grundsätzen der Verhältnismässigkeit und der Gesetzmässigkeit.

value: ZH-Kt Kantonspolizei - DCAT Harvester

de: Anzahl Einbrüche nach Gemeinden des Kantons Zürich


maintainer: Kantonspolizei des Kantons Zürich, Verkehrstechnische Abteilung

de: verkehrsunfaelle motorfahrzeuge strassenverkehrsunfaelle fahrzeuge sachschaden langsamverkehr motorraeder strassenverkehr

label: Unfallkarte der Schweiz (Geoportal des Bundes)

label: Polizeilich registrierte Verkehrsunfälle auf dem Stadtgebiet Zürich seit 2011 (Dienstabteilung Verkehr, Sicherheitsdepartement Stadt Zürich)

label: Unfalldaten der Schweiz, Statistiken nach Kantonen (Bundesamt für Strassen ASTRA)

de: Zu jedem Strassenverkehrsunfall sind der Unfallort (geokodiert), das Jahr, der Monat, der Wochentag, die Unfallstunde, die Strassenart, der Unfalltyp (ab 1. Juli 2015 inklusive Bagatellunfälle zB. Parkschäden), die Unfallbeteiligung ('Fussgänger', 'Velo (ohne E-Bikes)', 'Motorrad') und die Unfallschwerekategorie verfügbar. Detaillierte Definitionen der Variabeln sind in der Ressource "Minimales Geodatenmodell Strassenverkehrsunfallorte (ASTRA)" dokumentiert.

de: Detaillierte Definitionen der enthaltenen Variabeln.

media_type: application/json

format: JSON

mimetype: application/json

de: Die Verkehrsunfallstatistik des Kantons Zürich (VUSTA) enthält die Strassenverkehrsunfälle mit Personen- und Sachschäden, die durch die Kantonspolizei Zürich, die Dienstabteilung Verkehr der Stadt Zürich sowie die Stadtpolizei Winterthur registriert wurden. Sie wird einmal jährlich aktualisiert, jeweils gegen Ende des ersten Quartals des Folgejahres

fahrzeuge

display_name: fahrzeuge

langsamverkehr

display_name: langsamverkehr

motorfahrzeuge

display_name: motorfahrzeuge

motorraeder

display_name: motorraeder

sachschaden

display_name: sachschaden

strassenverkehr

display_name: strassenverkehr

strassenverkehrsunfaelle

display_name: strassenverkehrsunfaelle

verkehrsunfaelle

display_name: verkehrsunfaelle

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

de: Polizeilich registrierte Verkehrsunfälle im Kanton Zürich seit 2011