maintainer: Christian G. Sommer

en: wind-tunnel kinect wind-crust wind-packing snow

en: README

en: Describes the dataset in detail

en: Processing scripts

en: Contains the Matlab- and R-scripts used to process the Kinect data

en: Kinect data

en: Links to the dataset

en:
This data sets contains the Microsoft Kinect data from 15 wind tunnel experiments on wind-packing / wind crust formation. These experiments were performed in the winter 2016/17. The Kinect measures distributed snow depth.

The Kinect data is organized per experiment. Each experiment subfolder contains the processed Kinect depth images and some additional files.

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

This dataset is the basis of the following publication:

Sommer C.G., Lehning M. & Fierz C. (2018). Wind Tunnel Experiments: Influence of Erosion and Deposition on Wind-Packing of New Snow. Front. Earth Sci. 6:4. doi: 10.3389/feart.2018.00004

kinect

display_name: kinect

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

wind-tunnel

display_name: wind-tunnel

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: Wind crust formation: Microsoft Kinect data


maintainer: EnviDat Support

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

state: active

type: dataset

en: Dataset V1

en: This dataset is outdated and has been replaced with an updated version (see description).

format: GDB

en: Documentation

en: This data documentation is outdated and has been replaced with an updated version (see description).

format: SERVICE

mimetype: application/msword

en: Site photo

en: This site photo is outdated and has been replaced with an updated version (see description).

en:
 Important
This EnviDat entry is outdated. The most recent, usable version of the data can be found under the new EnviDat entry "Long-term afforestation experiment at the Alpine treeline site Stillberg, Switzerland." The entry can be found under this link <https://www.envidat.ch/dataset/afforestation-stillberg> and with this DOI 10.16904/envidat.397.

afforestation

display_name: afforestation

long-term-experiment

display_name: long-term-experiment

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline

display_name: treeline

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

it: Istruzione, cultura e sport

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

it: EnviDat: il portale dei dati ambientali

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

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: Long-term treeline research dataset at Stillberg, Davos


en: snow monitoring avalanche low-cost lidar wind-drifted-snow

media_type: application/zip

format: ZIP

en:
We developed a monitoring system using low-cost lidar (Livox Avia) and optical sensors, to measure snow depth variations in an avalanche release area at a high spatiotemporal scale (centimeter to low decimeter spatial resolution and hourly temporal resolution). A detailed description of the setup and a first data analysis is published in:
[Ruttner-Jansen, P., Voordendag, A., Hartmann, T., Glaus, J., Wieser, A., & Bühler, Y. (2024). Monitoring snow depth variations in an avalanche release area using low cost lidar and optical sensors. EGUsphere, 2024, 1-20.](https://egusphere.copernicus.org/preprints/2024/egusphere-2024-744/)
This dataset contains hourly 3D lidar data of the snow surface at the test site Braemabuel in Davos, Switzerland from the winter season 2023-2024 (23.11.2023 - 14.04.2024). Braema1 is installed at 2191 m a.s.l. in the slope, looking up into the avalache release area, and Braema2 is installed at 2255 m a.s.l at the ridge, looking down. Both scans together cover an area of about 15000 m².
The data is in format ".las" and contains the points in XYZ [m], in the scanner own coordinate system
- scalar fields: intensity, return number, timestamp, tag, label
-- tag: binary code from Livox (see [Livox Avia Manual](https://terra-1-g.djicdn.com/65c028cd298f4669a7f0e40e50ba1131/Download/Avia/Livox%20Avia%20User%20Manual%20202204.pdf))
-- label: marking outliers (filtered by distance and SOR to get snow particles in the air)

avalanche

display_name: avalanche

lidar

display_name: lidar

low-cost

display_name: low-cost

monitoring

display_name: monitoring

snow

display_name: snow

wind-drifted-snow

display_name: wind-drifted-snow

en: Snow depth mapping by lidar station Braemabuel


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

en: Site photo of the forest station (VOB)

en: Site photo of the forest station from the side.

mimetype: image/jpeg

en: Field station data (VOF)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Data plot of the field station (VOF)

media_type: application/pdf

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

format: PDF

mimetype: application/pdf

en: Forest station data (VOB)

en: Data plot of the forest station (VOB)

en: Site photo of the field station (VOF)

en: Site photo of the field stationfrom the side.

en: Site aerial photo (Vordemwald)

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

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 Vordemwald in Switzerland where one station is located within a natural mixed forest stand (VOB) with European silver fir (_Abies alba_; 110 yrs) and oak trees (_Quercus sp._; 190-210 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, VOF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Vordemwald is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


maintainer: Esther R. Frei

en: g-tree seedling-recruitment stillberg forest swiss-alps picea-abies larix-decidua treeline climate-change

media_type: text/plain

en: climate data G-TREE experiment, Davos, Switzerland

format: TXT

mimetype: text/plain

en:
 Background information
Climate change-induced range expansion of treeline populations depends on their successful recruitment, which requires dispersal of viable seeds followed by successful establishment of individual propagules. The Global Treeline Range Expansion Experiment (G-TREE) is a global initiative involving researchers from Europe, North America, Australia and New Zealand (Brown et al., 2013). At 15 alpine and Arctic treeline sites worldwide the mechanisms determining the elevational and latitudinal distribution of tree populations are studied using a standardized experimental approach. In summer 2013, a multifactorial seedling recruitment experiment has been established at the Stillberg ecological treeline research site. The aim of this experiment, is to quantify the effect of multiple abiotic and biotic drivers on emergence, survival, and growth of *Larix decidua* and *Picea abies* seedlings in replicated plots along an elevation gradient with three sites below (1930 m a.s.l.), at (2090 m a.s.l.), and above treeline (2410 m a.s.l.; Frei et al., 2018). All plots have been surveyed annually to count seedlings and to measure their total height. Additional environmental factors, such as soil temperature, have been recorded.

 Experimental design
The Stillberg research area is located in the Eastern Swiss Alps near Davos, Switzerland. The site has been used for several long-term monitoring as well as experimental studies for the last four decades. Our G-TREE experiment consists of a lowest site located in a subalpine Larch-Spruce forest (*Larici-Picetum*) dominated by *Larix decidua* and *Picea abies* (1930 m a.s.l.), a transition zone site dominated by alpine shrubs (2100 m a.s.l.), and an uppermost site in an alpine meadow with some dwarf shrubs (2390 m a.s.l.). The three experimental sites were set up following the standard protocol of the global G-TREE initiative (Brown et al., 2013). In a split-plot design, 20 plots (224 cm × 45 cm) were established at each site, which were randomly assigned to the 2 × 2 treatment combinations of the main factors seeding and scarification (i.e. seeding and scarification, seeding only, scarification only, and full control), resulting in five replications per main treatment combination. Each plot was divided into 16 split-plots (22.5 cm × 28 cm), to which treatment combinations of four additional two-level factors species (larch and spruce), provenance (low- and high-elevation), herbivore exclosure (with and without exclosure), and seeding year (2013, 2014) were randomly assigned, which resulted in a total of 960 split-plots (Details see Frei et al. 2018).

 Data description
All plots have been surveyed annually to count seedlings and to measure their total height. Seedling height was assessed with a hand ruler as the total length from the original emerging point to the apical meristem (Details see Frei et al. 2018). Additionally, soil temperature at each site, has been continuously recorded since 2013. Here, we present data from eight years (2013–2021).

forest

display_name: forest

g-tree

display_name: g-tree

larix-decidua

display_name: larix-decidua

picea-abies

display_name: picea-abies

seedling-recruitment

display_name: seedling-recruitment

stillberg

display_name: stillberg

swiss-alps

display_name: swiss-alps

treeline

display_name: treeline

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: G-TREE: Global Treeline Range Expansion Experiment Davos, Switzerland


en: strategic-projects land-use-transformations spatial-planning strategic-spatial-planning land-use-change urban-transformations europe large-scale-urban-development-projects

en: QCA R script large-scale urban development projects Europe

en:
For the set up of this R script, we used the “QCA” (Duşa, 2019) and “SetMethods” (Oana and Schneider, 2018) R packages.

The following further resources were also used:
Dusa, A. (2019). QCA with R: A comprehensive resource. Springer: Berlin.
Schneider, C. Q., & Wagemann, C. (2012). Set-theoretic methods for the social sciences. A guide to qualitative comparative analysis. Cambridge: Cambridge University Press.
Thomann, E., Oana, I.-E., & Wittwer, S. (2018). Performing fuzzy- and crisp set QCA with R. A user-oriented beginner's guide. Retrieved from http://www.evathomann.com/links/qca-r-manual

en: QCA data set large-scale urban development projects

en: Please refer to the sections: 3. The data set lsUDPs: 3.1 Selection of cases and data collection; 3.2 Data management and operationalization in the Metadata for further details on this resource.

en:
Table of Content: 1. General context of the data set "lsUDPs" ; 2. Background and aims of the study using the data set lsUDPs; 3. The data set lsUDPs: 3.1 Selection of cases and data collection; 3.2 Data management and operationalisation

1. General context of the data set "lsUDPs"
The data set "lsUDPs" 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 2016-2020. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, strategic spatial plans) into quantitative land-change modelling approaches at the urban regional level. The first stage (2016-2017) of the CONCUR project focussed on 21 urban regions in Western Europe. The urban regions were selected through a multi-stage strategy for empirical research (see Hersperger, A. M., Grădinaru, S., Oliveira, E., Pagliarin, S., & Palka, G. (2019). Understanding strategic spatial planning to effectively guide development of urban regions. Cities, 94, 96–105. https://doi.org/10.1016/j.cities.2019.05.032 ).

2. Background and aims of the study using the data set lsUDPs
As part of the CONCUR project, a specific task was to examine the relationship between strategic spatial plans and the formulation and implementation (i.e. urban land change) of large-scale urban development projects in Western Europe.
Strategic urban projects are typically large-scale, prominent urban transformations implemented locally with the aim to stimulate urban growth, for instance in the form of urban renewals of deprived neighborhoods, waterfront renewals and transport infrastructures. While strategic urban projects are referred to in the literature with multiple terms, in the CONCOR project we call them large-scale urban development projects (lsUDPs).
Previous studies acknowledged both local and supra-local (or structural) factors impacting the context-specific implementation of lsUDPs. Local governance factors, such as institutional capacity, coordination among public and private actors and political leadership, intertwine with supra-local conditions, such as state re-scaling processes and devolution of state competencies in spatial planning, de-industrialisation and increasing social inequality. Hence, in implementing lsUDPs, multi-scalar factors act in combination.
Because the formulation and implementation of lsUDPs require multi-scalar coordination among coalitions of public and private actors over an extended period of time, they are generally linked to strategic spatial plans (SSPs). Strategic spatial plans convey collective visions and horizons of action negotiated among public and private actors at the local and/or regional level to steer future urban development, and can contain legally binding dispositions, but also indicative guidelines.
The key question remains as to what extent large-scale urban development projects and strategic spatial plans can be regarded as aligned. By alignment, or “concordance”, we mean that strategic projects are formulated and implemented as part of the strategic planning process (“high concordance”), or that the strategic role of projects is reconfirmed in (subsequent) strategic plans (“moderate concordance”). Lack of concordance is found when lsUDPs have been limitedly (or not at all) acknowledged in strategic spatial plans.
We assume that certain local and supra-local factors, characterising the development of the projects, foster (but not strictly “cause”) the degree of alignment between lsUPDs and SSPs. In this study, we empirically examine how, and to what extent, the concordance between 38 European large-scale urban development projects and strategic plans (outcome: CONCOR) has been enabled by five multi-scalar factors (or conditions): (i) the role of the national state (STATE), (ii) the role of (inter)national private actors (PRIVATE), (iii) the occurrence of supra-regional external events (EVENTS), (iv) the degree of transport connectivity (TRANSP), and (v) local resistance from civil society (RESIST). We adopted a (multi-data) case-based qualitative strategy for empirical research and applied the formalised procedure of within- and cross-case comparison offered by fuzzy-set Qualitative Comparative Analysis appropriate for the goal of this study. Based on set theory, QCA formally integrates contextual sensitivity to case specificities (within-case knowledge) with systematic comparative analysis (across-case knowledge).
The research question the data set has been created to reply to is the following: which conditions, and combinations of conditions, enable the concordance between large-scale urban development projects and strategic spatial plans?
The conditions (“independent variables”) considered are. STATE: the set of large-scale urban projects characterized by a high degree of state intervention and support in their formulation and implementation, PRIVATE: the set of large-scale urban projects characterized by a high degree of involvement of (inter)national private actors in their formulation and implementation, EVENTS: the set of large-scale strategic projects whose formulation and implementation have been strongly affected by unforeseen international events and/or global trends, TRANSP: the set of large-scale strategic projects with a high degree of road and/or transit connectivity, and RESIST: set of large-scale strategic projects whose realization has been characterized by resistances that have substantially delayed or modified the project implementation.
The outcome (“dependent variable”) under analysis is CONCOR: the set of large-scale urban projects having a high degree of concordance/alignment/integration with strategic spatial plans

3. The data set lsUDPs

   3.1 Selection of cases and data collection
To generate the current data set on large-scale urban development projects in European urban regions (data set "lsUDPs"), we identified 35 large-scale urban development projects in a sample of the 21 Western urban regions considered in the CONCUR project (see supra, Hersperger et al. 2019): Amsterdam, Barcelona, Copenhagen, Hamburg, Lyon, Manchester, Milan, Stockholm, Stuttgart. The criteria we followed to identify the 35 large-scale urban development projects are: geographical location, size (large-scale), site (located either in the city core or in the larger urban region) and urban function (e.g. housing, transportation infrastructures, service and knowledge economic functions). Employing these criteria facilitated the selection of diverse large-scale urban development projects while still ensuring sufficient comparability.
In 2016, we performed 47 in-depth interviews with experts in urban and regional planning and large-scale strategic projects and infrastructure (i.e. academics and practitioners) about the formulation, implementation and development (1990s–2010s) of each project in each of the 9 selected urban regions. On average, each interviewee answered questions on 3.1 large-scale urban development projects. Three cases were subdivided into two cases because a clear differentiation between specific implementation stages was identified by the interviewees (expansion of the Barcelona airport, cases “bcn_airport80-90” and “bcn_airport00-16”; realisation of Lyon Part-Dieu, cases “lyo_partdieu70-90” and “lyo_partdieu00-16”; MediaCityUK, cases “man_salfordquays80-00” and “man_mediacityuk00-16”). Therefore, from the initial 35 cases, the final number of analysed cases in the lsUDPs dataset is 38.

    3.2 The data set lsUDPs: Data management and operationalisation
Interviews were fully transcribed and analysed through MAXQDA (version 12.3, VERBI GmbH, Berlin, Germany), and intercoder agreement was evaluated on a sample of nine interviews. We also compiled “synthetic case descriptions” (SCD) for each case (totalling more than 160 SCDs) to spot potential inconsistencies among interviewees’ accounts and to facilitate completion of the “calibration table” for each case (see below). An online expert survey distributed to the interviewees (response rate 78%) helped systematise the information collected during the interviews. We also consulted both academic and gray literature on the case studies to check for possible ambiguity and inconsistencies in the interview data, and to solve discrepancies between our assigned set membership scores and questionnaire values. Site visits were also carried out to retrieve additional information on the selected cases.
For each case (i.e. each of the 38 selected large-scale urban development projects), we operationalised each condition (i.e. STATE, PRIVATE, EVENTS, TRANSP, RESIST) and the outcome (CONCOR) in terms of sets, for subsequent application of Qualitative Comparative Analysis. This process is called “calibration”; we used a number of indicators for each condition to qualitatively assess each large-scale project across the conditions. The case-based qualitative assessment was then transformed into fuzzy-set membership values. Fuzzy-set membership values range from 0 to 1, and should be conceived as “fundamentally interpretative tools” that “operationalize theoretical concepts in a way that enhances the dialogue between ideas and evidence” (Ragin 2000:162, in “Fuzzy-set Social Science”. Chicago: University Press). We employed a four-value fuzzy-set scale (0, 0.33, 0.67, 1) to “quantify” into set membership scores the individual histories of cases retrieved from interview data. Only the condition TRANSP was calibrated as a crisp-set (0, 1).
The translation of qualitative case-based information into numerical fuzzy-set membership values was iteratively performed by populating a calibration table following standard practices recently emerged in QCA when dealing with qualitative (interview) data.

europe

display_name: europe

land-use-change

display_name: land-use-change

land-use-transformations

display_name: land-use-transformations

large-scale-urban-development-projects

display_name: large-scale-urban-development-projects

spatial-planning

display_name: spatial-planning

strategic-projects

display_name: strategic-projects

strategic-spatial-planning

display_name: strategic-spatial-planning

urban-transformations

display_name: urban-transformations

en: lsUDPS Large-scale urban development projects in European urban regions


en: outdoor-lighting artificial-lighting alan ecosystem-services sustainability

en: Raw data for flying insects and ground-dwelling arthropod combined analysis

en: R code for PERMANOVA Analysis of flight-active insects.

format: OCTET

en: Raw data for flying insects analysis

en: Raw data for ground-dwelling arthropod NMDS analysis

en: Raw data Moran's I test

en: R code of flight-active and ground-dwelling arthropod combined analysis.

en: Raw data for flying insects NMDS analysis

en: Raw data for ground-dwelling arthropod analysis

en: R code of ground-dwelling arthropod analysis.

en: R code of flight-active insects analysis.

en: R code for NMDS of flight-active insects

en: R code for NMDS of ground-dwelling arthropods

en: R code for PERMANOVA Analysis of ground-dwelling arthropods.

en: Raw data and R Code to do all the analysis performed for the paper "Advancing sustainable LED solutions to mitigate light-pollution impacts on arthropods". Including data for both flight-active insects and ground-dwelling arthropods combined (PT_TRF_all.csv), flight-active insects alone (ALANeX_PT_all_clean_control.csv) and ground-dwelling insects alone (ALANeX_TRF_all_clean_control.csv). For the NMDS analysis, there is a data set for the flight-active insects (ALANeX_PT_NMDS.csv) and the ground-dwelling arthropods (ALANeX_TRF_NMDS.csv). For the Morans I use the 'ALANeX_MoransI.csv' dataset.

alan

display_name: alan

artificial-lighting

display_name: artificial-lighting

ecosystem-services

display_name: ecosystem-services

outdoor-lighting

display_name: outdoor-lighting

sustainability

display_name: sustainability


mountain-permafrost-hydrology

maintainer: Jeannette Noetzli

title_for_slug: mountain-permafrost-hydrology

en: monitoring-techniques ice-rich-permafrost mass-movements climate-change-impacts permafrost-degradation mountain-permafrost-hydrology

en: Synthesis report chapter of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN)

en: This report was prepared as one of the synthesis report chapters of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN). In earlier reports such as the CH2014-IMPACTS report (CH-Impacts 2014), the topic of mountain permafrost hydrology was not addressed. Here, we provide a baseline of the available knowledge of mountain permafrost in the Swiss Alps for future reference. We compile an overview of the current understanding of mountain permafrost in the Swiss Alps, its distribution and characteristics, observed and projected changes, and expected impacts on slope stability, infrastructure and hydrological aspects. We also briefly describe the measurement techniques and modelling approaches applied. The chapter closes with a summary of the most important open research questions. The literature cited mainly includes studies on mountain permafrost published in scientific journals and assessments of long-term observation data. We focus on permafrost hydrology interactions wherever information is available. However, systematic studies on permafrost hydrology in mountain areas are still limited.

climate-change-impacts

display_name: climate-change-impacts

ice-rich-permafrost

display_name: ice-rich-permafrost

mass-movements

display_name: mass-movements

monitoring-techniques

display_name: monitoring-techniques

mountain-permafrost-hydrology

display_name: mountain-permafrost-hydrology

permafrost-degradation

display_name: permafrost-degradation

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: Mountain Permafrost Hydrology


maintainer: Felix Gugerli

en: genetic-diversity conservation-genetics genetic-structure monitoring melanargia-galathea

en:
Individual genotypes assessed at six nuclear microsatellite loci (two alleles per locus) for individuals of the butterfly Melanargia galathea (Marbled white) that were collected throughout Switzerland, along the regular grid of the Biodiversity Monitoring (BDM) of Switzerland. For each individual, the sampling site (number) and the genotype are given. Note that due to privacy restrictions, the original geographic coordinates remain disclosed. For original coordinates, data holders should be contacted (Swiss Federal Office for the Environment; Biodiversity Monitoring Switzerland).
The data refer to the following publication: Terzer et al., Distinct spatial patterns of genetic structure and diversity in the butterfly Marbled White (Melanargia galathea) inhabiting fragmented grasslands. Conservation Genetics, https://doi.org/0.1007/s10592-023-01593-4.

conservation-genetics

display_name: conservation-genetics

genetic-diversity

display_name: genetic-diversity

genetic-structure

display_name: genetic-structure

melanargia-galathea

display_name: melanargia-galathea

monitoring

display_name: monitoring

en: Nuclear microsatellite genotypes of the butterfly Melanargia galathea


maintainer: Merin Reji Chacko

en: switzerland vertebrates vascular-plants food-webs metaweb invertebarates trophic-networks

en: trophiCH

en: We provide seven datasets: 1) the metaweb, 2) the taxa checklist, 3) the data source meta-dataset, 4) the list of generalist basal and predator families and polylectic species with citations and 5) a dataset with citations for the inferences of missing predators, 6) a dataset with citations for the parallel inference of diets from similar species and 7) a list of other existing metawebs. The empirical dataset is 00_empirical_metaweb.csv. To reproduce the final metaweb (01_final_metaweb.csv), start the R Project file: trophich.Rproj. We provide five scripts, accompanying functions, and the raw data required to run these scripts to reproduce the taxonomic expansion and validation of the datasets. In the first script (01_inferring_interactions.R), we infer interactions using genus and family level interactions and for basal feeding groups (see Methods: Taxonomic expansion). In the second script (02_inferring_interactions_special_cases.R), we infer further interactions for a few special cases with detailed explanations. In the third script (03_metaweb_comparisons.Rmd), we provide the statistical comparisons between our metaweb and other empirical metawebs as an R Markdown document. We additionally provide a a Python Jupyter Notebook document, outlining the error validation of the data extraction process (04_error_validation.ipynb and an accompanying .html file). Finally, we provide a script to reproduce figure 1 from the data paper (05_metaweb_summary_figure_1.R).

en:
Environmental pressures on species can cascade within food webs and even extend beyond individual ecosystems to interconnected systems at large spatial scales. To facilitate the exploration of these dynamics, we construct a data-based national trophic meta-food web (henceforth metaweb), that includes well-documented vertebrates, invertebrates, and vascular plants within Switzerland's national boundaries, and compiles 160 years of ecological knowledge. We additionally use a combination of taxonomic and geographic information to infer further species-level interactions. Our comprehensive dataset catalogues 1,112,073 trophic interactions involving 23,151 species and 125 feeding guilds (e.g. detritivores, fungivores, etc). While explorations of large-scale food webs in space and time have often relied on modelling approaches due to limited data availability, this empirically based metaweb paves the way for data-driven large-scale studies of real-world food webs. By integrating the metaweb with knowledge of local species assemblages, future studies can gain insights into the impact of global change drivers, including climate change and land-use intensification, on food web structures across spatial scales.

**Please note that this dataset is under embargo until publication of the paper.**

food-webs

display_name: food-webs

invertebarates

display_name: invertebarates

metaweb

display_name: metaweb

switzerland

display_name: switzerland

trophic-networks

display_name: trophic-networks

vascular-plants

display_name: vascular-plants

vertebrates

display_name: vertebrates

en: trophiCH v1 - a food web for Switzerland


maintainer: Roman Zweifel

en: automated-monitoring eddy-covariance dendrometer icos carbon-cycle twd dbh icp-forests climate-growth seehornwald treenet forest-monitoring stem-growth biomass co2 ecophysiology eddy-covariance-measurements forest-ecosystems forest-function davos forest-characteristics forest-canopy climate-change metadata forest-biomass carbon-storage water-relations carbon-sequestration forest-dynamics tree-stem ecosystem-functioning open-data forest atmospheric-conditions subalpine sap-flow carbon-dioxide flux picea-abies ilter forest-area lwf

en: Collection of files with information about the research site Seehornwald Davos CH-DAV

en: Readme

en: Readme file contains the list of material that comes with the download

en: Site description of the Seehornwald Davos (CH-DAV) research site. The material provided offers information on the biomass and growth of trees in CH-DAV, including supporting materials such as maps, geolocations and analyses. CH-DAV is part of networks such as ICOS, LWF, TreeNet, ICPForests and is dedicated to forest monitoring and research.

atmospheric-conditions

display_name: atmospheric-conditions

automated-monitoring

display_name: automated-monitoring

biomass

display_name: biomass

carbon-cycle

display_name: carbon-cycle

carbon-dioxide

display_name: carbon-dioxide

carbon-sequestration

display_name: carbon-sequestration

carbon-storage

display_name: carbon-storage

climate-change

display_name: climate-change

climate-growth

display_name: climate-growth

davos

display_name: davos

dbh

display_name: dbh

dendrometer

display_name: dendrometer

ecophysiology

display_name: ecophysiology

ecosystem-functioning

display_name: ecosystem-functioning

eddy-covariance

display_name: eddy-covariance

eddy-covariance-measurements

display_name: eddy-covariance-measurements

flux

display_name: flux

forest

display_name: forest

forest-area

display_name: forest-area

forest-biomass

display_name: forest-biomass

forest-canopy

display_name: forest-canopy

forest-characteristics

display_name: forest-characteristics

forest-dynamics

display_name: forest-dynamics

forest-ecosystems

display_name: forest-ecosystems

forest-function

display_name: forest-function

forest-monitoring

display_name: forest-monitoring

icos

display_name: icos

icp-forests

display_name: icp-forests

ilter

display_name: ilter

lwf

display_name: lwf

metadata

display_name: metadata

open-data

display_name: open-data

picea-abies

display_name: picea-abies

sap-flow

display_name: sap-flow

seehornwald

display_name: seehornwald

stem-growth

display_name: stem-growth

subalpine

display_name: subalpine

tree-stem

display_name: tree-stem

treenet

display_name: treenet

twd

display_name: twd

water-relations

display_name: water-relations

en: Site description Davos Seehornwald CH-DAV


vegetation-height-model-nfi

maintainer: Christian Ginzler

title_for_slug: vegetation-height-model-nfi

en: photogrammety forest 3d point-cloud vegetation-height-model

en: Thumbnail

en: 2012 Vegetation Height Model NFI

en:
Data 'Vegetation Height Model NFI 2012' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2007 to 2012.

format: GeoTIFF

en: 2016 Vegetation Height Model NFI

en:
Data 'Vegetation Height Model NFI 2016' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2011 to 2016.

en: 2019 Vegetation Height Model NFI (current)

en:
Data 'Vegetation Height Model NFI 2019' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2013 to 2019.

en: 2015 Vegetation Height Model NFI

en:
Data 'Vegetation Height Model NFI 2015' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2010 to 2015.

en: Countrywide Stereo-Image Matching for Updating Digital Surface Models in the Framework of the Swiss National Forest Inventory

en:
A national vegetation height model was calculated for Switzerland using digital aerial images.
We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution
(1 × 1 m and 0.5 x 0.5 m). The DSM was then normalized to obtain the actual
vegetation heights using a digital terrain model (DTM)
based on laser data with the buildings masked out, and to
produce a vegetation height model (VHM). Such a model
will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very
high level of detail. For covering the whole of Switzerland,
we use summer aerial images from six years.

Latest version is from 2019.

forest

display_name: forest

photogrammety

display_name: photogrammety

point-cloud

display_name: point-cloud

vegetation-height-model

display_name: vegetation-height-model

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Vegetation Height Model NFI


snow-drift-station-flowcapt

maintainer: Benjamin Walter

title_for_slug: snow-drift-station-flowcapt

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

en: minimum wind spees

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

format: XLS

en: minimum mass flux

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

en: avergaged mass flux

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

en: maximum mass flux

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

en: maximum wind speed

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

en: average wind speed

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

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

acoustic-mass-flux

display_name: acoustic-mass-flux

flowcapt

display_name: flowcapt

raclets

display_name: raclets

snow-blowing

display_name: snow-blowing

snowdrift

display_name: snowdrift

wind-speed

display_name: wind-speed

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 Drift Station - Flowcapt


en: urbanization urban-ecology cities life-history-traits cavity-nesting natural-enemies richness bees performance-traits hymenoptera hymennoptera wasps

en: Taxonomic metrics on the natural enemies

en: It contains the species richness and the abundance of natural enemies per site.

en: Predictors of the study

en: Information on the study sites

en: For each site, the IDs, city, coordinates, structure where the trapnest was attached and height is provided

en: Performance traits and life-history traits

en:
It contains the data of two performance traits (survival and parasitism) and two life-history traits (sex ratio and number of offspring per nest for the hosts) at the nest level.

We assessed performance traits, i.e. survival and parasitism, at the individual cell level. Specifically, for each cell within a nest, we noted whether the cell was alive or dead (survival), and whether it had a parasite or not (parasitism). Further, we calculated the parasitism rate as the number of cells with a parasite divided by the total number of cells. Concerning life-history traits, we calculated the total number of brood cells per nest as the total number of brood cells within a single nest, regardless of whether the larvae were dead, alive or parasitized. Finally, we used the probability that a femalehost emerged from a given cell as a proxy for the sex ratio. To do so, we first identified the sex of the individual hosts. Then, we noted it in a binary way to indicate whether the host was a female or not. We could identify the sex of all hatched hosts. Further, because CNBW first lay females and then males, on some occasions we could also identify the host sex in dead and parasitized cells, that is, when we had already identified the sex of the preceding and the following cells.

en: Taxonomic metrics on CNBW

en:
The data contains at the site level the species richness of cavity-nesting bees and wasps. It also contains site level estimates of the life-history traits and the performance traits.

We calculated species richness, abundance, and number of nests of the hatched hosts separately for bees and wasps. We calculated the abundance of hatched hosts as the number of brood cells where an individual emerged, i.e. the total number of brood cells minus the number of parasitized cells and the number of cells with no emergence for reasons other than parasitism.

City codes: An =Antwerp, Pa = Paris; Po = Poznan; Ta =Tartu; Zu= Zurich

en:
 Background
Urban ecosystems are associated with socio-ecological conditions that can filter and promote taxa. However, the strength of the effect of ecological filtering on biodiversity could vary among biotic and abiotic factors. Here, we provide the data used to investigate the effects of habitat amount, temperature, and host-enemy biotic interactions in shaping communities of cavity-nesting bees and wasps (CNBW) and their natural enemies. To do so, we installed trap-nests in 80 sites distributed along urban intensity gradients in 5 European cities (Antwerp, Paris, Poznan, Tartu and Zurich). We quantified the species richness and abundance of CNBW hosts and their natural enemies, as well as two performance traits (survival and parasitism) and two life-history traits (sex ratio and number of offspring per nest for the hosts).
The dataset contains:
* The taxonomic metrics on CNBW
* The taxonomic metrics on the natural enemies from CNBW
* The life-history traits and performance traits

bees

display_name: bees

cavity-nesting

display_name: cavity-nesting

cities

display_name: cities

hymennoptera

display_name: hymennoptera

hymenoptera

display_name: hymenoptera

life-history-traits

display_name: life-history-traits

natural-enemies

display_name: natural-enemies

performance-traits

display_name: performance-traits

richness

display_name: richness

urban-ecology

display_name: urban-ecology

urbanization

display_name: urbanization

wasps

display_name: wasps

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Community structure, life-history traits and performance traits of urban cavity-nesting bees annd wasps


maintainer: Yaquan Chang

en: phytodiversity hypervolume habitat-heterogeneity hengduan-mountains model-residuals

en: Eurasia plant family richness map

en: This is the plant family level richness map at the Eurasia scale calculated from https://www.nature.com/articles/s41597-021-00997-6

mimetype: application/zip

en: Hengduan plant family richness map

en: This is the family level plant richness map in the Hengduan mountain scale at 1km resoution

en: Plant range map at Hengduan scale

en: This is the plant range map at the Hengduan mountain scale based on species distribution model, elevation, and county level distribution information

en: Eurasia SR and heteorgeneity

en: This table is used for the Eurasia scale analyses, including both family level species richness map and different heterogeneity predictors

en: HDM heterogeneity scales

en: The Heterogeneity matrics in the Hengduan mountain scale

en: This research data is used to re includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions. This research data includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions.

habitat-heterogeneity

display_name: habitat-heterogeneity

hengduan-mountains

display_name: hengduan-mountains

hypervolume

display_name: hypervolume

model-residuals

display_name: model-residuals

phytodiversity

display_name: phytodiversity

en: Phytodiversity is associated with habitat heterogeneity from Eurasia to Hengduan


maintainer: Frank Techel

en: alps shapefile observations snow avalanches

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

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

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

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

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

alps

display_name: alps

avalanches

display_name: avalanches

observations

display_name: observations

shapefile

display_name: shapefile

snow

display_name: snow

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.


maintainer: Christian Rixen

en: treeline stillberg tree-rings fertilization dwarf-shrubs nitrogen-isotope

en: Data Nutrient Addition Stillberg

en: This link leads to the figshare repository, which contains all nutrient addition data.

en: Metadata Nutrient Addition Stillberg Experimental Design

media_type: image/png

en: Nutrient addition map of the study area with the investigated plots. Each circle (study block) contains one control plot and two plots that received NPK fertilizer corresponding to 15 (NPK15) or 30 (NPK30) kg N ha-1 a-1. Contour lines specify the elevation (m a.s.l.) in steps of 10 m.

format: PNG

en: Project Description Nutrient Addition Stillberg

media_type: text/html

en: Link to Nutrient Addition project description on the WSL website (in German).

format: HTML

en:
 Background information

The availability of nitrogen (N) and phosphorus (P) is considered to be a major factor limiting growth and productivity in terrestrial ecosystems globally. This project aimed to determine whether the growth stimulation documented in previous short‐term fertilisation trials persisted in a longer‐term study (12 years) in the treeline ecotone, and whether possible negative effects of nutrient addition offset the benefits of any growth stimulation.
Over the course of the 12 study years, NPK fertiliser corresponding to 15 or 30 kg N ha−1 a−1 was added annually to plots containing 30‐year‐old *Larix decidua* or 32‐year-old *Pinus uncinata* individuals with an understorey of mainly ericaceous dwarf shrubs. To quantify growth, annual shoot increments of trees and dwarf shrubs as well as radial growth increments of trees were measured. Nutrient concentrations in the soil were also measured and the foliar nutritional status of trees and dwarf shrubs was assessed.

 Experimental design

Over an elevation gradient of 140 m across the treeline afforestation site Stillberg, 22 locations were chosen that covered the whole range of microenvironmental conditions (*see* Nutrient addition experimental design.png). Half of the blocks included European larch (*L. decidua*) and the other half included mountain pine (*P. uncinata*). Within each block, three plantation quadrats were randomly selected as experimental plots and each plot was assigned to a control (no fertilisation) or to one of two fertiliser dose treatments (15 kg and 30 kg N ha−1 a−1). Treatments were assigned randomly but confined so that the location of fertilised plots within a block was not directly above control plots to avoid nutrient input from drainage. For details about the experiment, *see* Möhl et al (2019).

 Data description

The available datasets contain climate variables (2004-2016), nutrient isotope measurements (2010 & 2016), shrub growth measurements (2004-2016), soil parameter measurements and annual ring and shoot measurements (2004-2016). All data can be found here:
<https://figshare.com/articles/dataset/Twelve_years_of_low_nutrient_input_stimulates_growth_of_trees_and_dwarf_shrubs_in_the_treeline_ecotone/7025858>

dwarf-shrubs

display_name: dwarf-shrubs

fertilization

display_name: fertilization

nitrogen-isotope

display_name: nitrogen-isotope

stillberg

display_name: stillberg

tree-rings

display_name: tree-rings

treeline

display_name: treeline

educ

en: Education, culture and sport

en: EnviDat: the Environmental Data Portal

en: Nutrient addition experiment at the Alpine treeline site Stillberg, Switzerland


maintainer: Elisabeth Hafner

en: hazard-mapping snow satellite natural-hazard avalanche

en: SPOT6 Avalanche Outlines 16 January 2019

en: Shapefile of the manually mapped avalanche outlines. Please only use this data together with the example key document provided with this dataset and within the limitations of the dataset described in the publications.

format: SHP

en:
Outlines of 6'041 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 16 January 2019. The dataset was acquired following a period with very high avalanche danger. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping16012019.pdf)

The generation of the data is described in:

Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.

The data was comprehensivly validated in a subset area in

Hafner, E.D.; Techel, F.; Leinss, S.; Bühler, Y., 2021: Mapping avalanches with satellites - evaluation of performance and completeness. Cryosphere, 15, 2: 983-1004. doi: 10.5194/tc-15-983-2021

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

en: SPOT6 Avalanche outlines 16 January 2019


maintainer: Frank Hagedorn

en: soil-nutrients climate-change biomass-dynamics plant-traits treeline-ecosystems plant-community

en: Data on soils, tree biomass, plant nutrients, rock mineralogy, climate of treeline ecosystems in Khibiny mountains, Kola Penninsula, Russia

en: Data on soil nutrients and charcteristics, tree and understory biomass, foliage nutrients, mineralogy, soil temperature and moisture along an elevation gradient from boreal forest to mountain tundra in teh Khibiny mountains (Kola Penninsula, Russia). Samples were taken along two gradients at 7 elevation level either under tree canopy (tree) and in open areas (open).

biomass-dynamics

display_name: biomass-dynamics

climate-change

display_name: climate-change

plant-community

display_name: plant-community

plant-traits

display_name: plant-traits

soil-nutrients

display_name: soil-nutrients

treeline-ecosystems

display_name: treeline-ecosystems

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.


maintainer: Justine Berg

en: dischma fsm2 fsm2trans snow-hydrology snowpack hicar

en: Input data April 2017 HICAR 100m resolution

en: Input data April 2017 COSD

en:
snowheight output of validation days (LiDAR days) for all simulation runs
- 20.03.2027
- 31.03.2017
- 17.05.2017

en: Input data March 2017 HICAR 100m resolution

en: Input data June 2017 HICAR 100m resolution

en: Input data January 2017 COSD

en: Input data June 2017 HICAR 250m resolution

en: Input data March 2017 HICAR 50m resolution

en: Input data December 2016 HICAR 50m resolution

en: Input data July 2017 HICAR 250m resolution

en: Input data october 2016 HICAR 50m resolution

en: input data january 2016 COSD

en: Available input files for running with FSM2trans

en: Input data June 2017 COSD

en: Input data May 2017 HICAR 250m resolution

en: Input data November 2016 HICAR 50m resolution

en: Input data November 2016 HICAR 250m resolution

en: Input data March 2017 HICAR 250m resolution

en: Input data March 2017 COSD

en: input data october 2016 COSD

en: Input data February 2017 HICAR 50m resolution

en: Input data January 2017 HICAR 100m resolution

en: Input data october 2016 HICAR 100m resolution

en: Input data June 2017 HICAR 50m resolution

en: Input data november 2016 HICAR 100m resolution

en:
time series of daily averages of the whole domain for each simulation run
- rainfall
- snowfall
- runoff
- snowmelt
- temperature

en: Input data July 2017 HICAR 50m resolution

en: Input data May 2017 COSD

en: Input data July 2017 COSD

en: Input data December 2016 HICAR 250m resolution

en: Input data February 2017 HICAR 250m resolution

en: Input data May 2017 HICAR 100m resolution

en: Input data April 2017 HICAR 250m resolution

en: Input data January 2017 HICAR 50m resolution

en: Input data April 2017 HICAR 50m resolution

en: Input data February 2017 HICAR 100m resolution

en: Input data July 2017 HICAR 100m resolution

en: Input data January 2017 HICAR 250m resolution

en: Input data December 2016 HICAR 100m resolution

en: Input data May 2017 HICAR 50m resolution

en: Input data October 2016 HICAR 250m resolution

en:
 DESCRIPTION
The dataset is used to run snowpack simulations with various forcing data at different resolutions with the Flexible Snow Model (FSM2oshd). A dynamical downscaling model (HICAR) and a semi-statistical downscaling approach (COSD) are used to downscale COSMO data to resolutions of 250 m, 100 m and 50 m. Simulations are run with the operational snow cover model and a model extension including wind- and gravity-induced snow redistribution (FSM2trans).
 Input Data
This paragraph describes the input data used to run simulations with FSM2trans
 HICAR
The HICAR input data is created by the High-resolution Intermediate Complexity Atmospheric Research model. The input data is available for different resolutions (250m, 100m and 50m) for a domain covering complex terrain in the Swiss Alps (Dischma)
 COSD
The COSD data was statistically downscaled within the OSHD framework to different resolutions (250m, 100m, 50m) for a domain covering complex terrain in the Swiss Alps (Dischma)
 Simulation files
For the Simulations, a landuse file and a namelist file with the parametrizations need to be supplied to the model
 simulation output
This simulation output that is used for the analysis of the study is provided.

en: FSM2trans snowpack simulations with HICAR input


maintainer: Daniel Scherrer

en: ground-vegetation climate-change forest-management forest air-pollution fagus-sylvatica

en: Taxa Data

en: This table contains information about the individual taxa found in the historic and current vegetation relevés in Scherrer et al. 2024.

en: Site Information

en: This table contains information about the 254 forest sites used in the publication of Scherrer et al. 2024.

en: This dataset comprised 254 historical (1937 – 1948) and resurveyed (2019 – 2022) vegetation relevés of beech-dominated forests sites in the Swiss Jura mountains. The data contains species lists as well as site information.

air-pollution

display_name: air-pollution

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

forest-management

display_name: forest-management

ground-vegetation

display_name: ground-vegetation

educ

en: Education, culture and sport

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: Resurveyed vegetation releves of beech forests in the Swiss Jura Mountains


present-weather-sensor-klosters

maintainer: Maxime Hervo

title_for_slug: present-weather-sensor-klosters

en: weather precipitation raclets sensor visibility

en: Present Weather Sensor Klosters

en: Present Weather sensor measuring visibility and weather type installed at Klosters.

en: A present weather sensor (Vaisala PWD22) was deployed in Klosters (LON: 9.880413, LAT: 46.869019) for weather observation, combining the functions of a forwardscatter visibility meter and a present weather sensor. Besides measuring ambient light, it detects the intensity as well as the amount of both liquid and solid precipitation. More information can be found in the [User's Manual](ftp://ftp.cmdl.noaa.gov/aerosol/doc/manuals/PWD22_Manual.pdf).

precipitation

display_name: precipitation

raclets

display_name: raclets

sensor

display_name: sensor

visibility

display_name: visibility

weather

display_name: weather


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

en: AvalancheReliabilityData

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

mimetype: application/x-zip-compressed

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

 Avalanche size estimates

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

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

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

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

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

avalanche-size-estimation

display_name: avalanche-size-estimation

reliability

display_name: reliability

remote-sensing

display_name: remote-sensing

en: Data reliability study: avalanche size estimates and outlines


data-interactive-avalanche-segmentation

maintainer: Elisabeth D. Hafner

title_for_slug: data-interactive-avalanche-segmentation

en: interactive avalanche snow deep-learning segmentation

en:
Images and corresponding avalanche annotations used for interactive avalanche segmentation:
SLF train, vali and test
WebNew
GroundPic
UserPic
UIBK dataset: List of images used
Pictures are from SLF (mostly from the Dischma Cams) if not otherwise indicated. If used, the data needs to be properly cited!

deep-learning

display_name: deep-learning

interactive

display_name: interactive

segmentation

display_name: segmentation

snow

display_name: snow

en: Data interactive avalanche segmentation


maintainer: Mahdi Jafari

en: snow-density-profile numerical-simulation openfoam convection-in-snow vapor-transport

en: snowpackBuoyantPimpleFoam

en:
This zipped folder includes (1) the source code files, (2) an example case for simulation, and (3) an instruction how to compile and use the new solver.

Note that the most updated version of snowpackBuoyantPimpleFoam can be found in the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/snow-models/snowpackbuoyantpimplefoam

en: snowpackBuoyantPimpleFoam is a two-phase solver implemented to model convection of water vapor with phase change in snowpacks. This new solver is based on the standard solver of buoyantPimpleFoam in the open-source fluid dynamics software, OpenFOAM 5.0 (www.openfoam.org).

convection-in-snow

display_name: convection-in-snow

numerical-simulation

display_name: numerical-simulation

openfoam

display_name: openfoam

snow-density-profile

display_name: snow-density-profile

vapor-transport

display_name: vapor-transport

en: snowpackBuoyantPimpleFoam: an OpenFOAM Eulerian–Eulerian two-phase solver for modelling convection of water vapor in snowpacks


maintainer: Thomas Wohlgemuth

en: biogeography pairwise-stand-comparisons forest-management soil-impacts biodiversity

en: Baseline data

en: headers

en: Description of headers for data_wohlgemuth_etal_Neobiota_2022

en: references

en: Bibliography of all references cited in data_wohlgemuth_etal_Neobiota_2022.

en: Compiled data on the impacts of seven important NNTs (Acacia dealbata, Ailanthus altissima, Eucalyptus globulus, Prunus serotina, Pseudotsuga menziesii, Quercus rubra, Robinia pseudoacacia) on physical and chemical soil and biodiversity in Europe, and summarise commonalities and differences. A total of 107 publications considered, studies referred to biodiversity attributes and soil properties: 2804 lines and 30 rows.

biodiversity

display_name: biodiversity

biogeography

display_name: biogeography

forest-management

display_name: forest-management

pairwise-stand-comparisons

display_name: pairwise-stand-comparisons

soil-impacts

display_name: soil-impacts

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: Impact of non-native tree species in Europe on soil properties and biodiversity: a review


maintainer: EnviDat Support

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

en: Site photo of the forest station (SCB)

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

en: Forest station data (SCB)

en: Data file.

en: Site photo of the field station (SCF)

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

en: Data plot of the field station (SCF)

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

en: Field station data (SCF)

en: Further details on the data repository

en: Meta data documentation.

en: Data plot of the forest station (SCB)

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: 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

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


en: sea-salt-aerosol snow arctic antarctica ice

en: Fig 1B_2

en: Individual data to mean shown in Figure 1B

en: Table 2

en: This table lists all NEXAFS data files in chronological order with PE carbon to oxygen signal intensity ratios -from which the atomic ratio were calculated in the paper - before ("preCtoO") and after ("postCtoO") each NEXAFS measurement. Also listed is the change in Na ("lossSodi"), O ("lossOxy"), Cl ("lossChlor"), and C ("lossCarb") signal intensity after the NEXAFS measurement compared to prior to the NEXAFS measurement.

en: Read Me

en: Description of the data tables

en: Fig 1F_2

en: Individual data to mean shown in Figure 1F

en: Fig 1C

en: Data to Figure 1C

en: Fig 1D

en: Data to Figure 1D

en: Fig 1F_1

en: Fig 1B

en: Data in Figure 1B

en: Fig 1A

en: Data Figure 1A

en: Fig 1E

en: Data to Figure 1E

en: Code

en: Matlab code to read and plot the data

en: Fib 1B_3

en: Fig 1B_1

en: Fig 1F

en: This table lists all data files in chronological order. "SampleTemp" refers to the reading of the PT-1000 at the side of the sample holder. "cellPressure" is the water vapour pressure during the measurements. From this, in presence of ice, the temperature of the ice sample can be calculated which is given in the column "iceTemp". "dT" is the difference, or temperature offset, between sensor's reading and the ice samples temperature. The offset is due to the sensor being mounted away from the cooled spot of the sample were it experiences heating from warmer parts of the sample holder. The off-set is used to calibrate the temperature sensor and the resulting temperature during the experiments is given in the column "temperature". "relHum" is the relative humidity above (supercooled) liquid and "concBrine" is the concentration of a NaCl solution in mol/l in equilibrium with ice at the experimental temperature. "Area" is the integrated PE signal.

en: Laboratory experiments are presented on the phase change at the surface of sodium chloride – water mixtures at temperatures between 259 K and 240 K. High selectivity to the upper few nanometres of the frozen solution – air interface is achieved by using electron yield near-edge X-ray absorption fine structure (NEXAFS) spectroscopy. We present the NEXAFS spectrum of the hydrohalite.

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: Data set on interfacial supercooling and the precipitation of hydrohalite in frozen NaCl solutions by X-ray absorption spectroscopy


author: BFS/OFS

fr: Annuaire statistique de la Suisse 1939

mimetype: text/html

de: Statistisches Jahrbuch der Schweiz 1939

basas-statisticas-e-survistas

display_name: basas-statisticas-e-survistas

bases-statistiques-et-generalites

display_name: bases-statistiques-et-generalites

grundlagen-und-ubersichten

display_name: grundlagen-und-ubersichten

statistical-basis-and-overviews

display_name: statistical-basis-and-overviews

spatial: Schweiz

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS

de: Bundesamt für Statistik BFS

en: Federal Statistical Office FSO

it: Ufficio federale di statistica UST

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

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

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

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

political_level: confederation

value: BFS – DCAT Harvester


de: Statistisches Jahrbuch der Schweiz 1935

fr: Annuaire statistique de la Suisse 1935


fr: Annuaire statistique de la Suisse 1906

de: Statistisches Jahrbuch der Schweiz 1906


de: Statistisches Jahrbuch der Schweiz 1919

fr: Annuaire statistique de la Suisse 1919


fr: Annuaire statistique de la Suisse 1964

de: Statistisches Jahrbuch der Schweiz 1964


de: Statistisches Jahrbuch der Schweiz 1979

fr: Annuaire statistique de la Suisse 1979


fr: Annuaire statistique de la Suisse 1996

de: Statistisches Jahrbuch der Schweiz 1996


quartiergestaltungsplane-differenz-ur

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: quartiergestaltungsplane-differenz-ur

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

it: geocat.ch link permanente

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

format: WMS

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

format: WFS

fr: Sondernutzungspläne regeln die Überbaubarkeit von Teilgebieten der Gemeinde. Sie ergänzen oder verfeinern die nutzungsplanerische Grundordnung (Art. 46 PBG). Der Quartiergestaltungsplan bezweckt eine besonders gute Gesamtüberbauung, namentlich in architektonischer und städtebaulicher Hinsicht. Zusätzlich zu den Elementen des Quartierplans regelt er die Lage, Stellung, Grösse und Gestaltung der Bauten und Anlagen sowie die Art und das Mass ihrer Nutzung, die Grenz- und Gebäudeabstände sowie die Grünflächen und Spielplätze (Art. 52 PBG).

spatial: Canton of Uri (UR)

fr: Amt für Raumentwicklung Kt. Uri

de: Amt für Raumentwicklung Kt. Uri

en: Amt für Raumentwicklung Kt. Uri

it: Amt für Raumentwicklung Kt. Uri

geoinformation-kanton-uri

de: Lisag AG, 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.

political_level: canton

value: Uri-Kt - Geocat Harvester

fr: Quartiergestaltungspläne Differenz (UR)

de: Quartiergestaltungspläne Differenz (UR)

en: Quartiergestaltungspläne Differenz (UR)

it: Quartiergestaltungspläne Differenz (UR)


quartierplane-differenz-ur

title_for_slug: quartierplane-differenz-ur

fr: plan-de-quartier geodonnees-de-base

de: quartierplan geobasisdaten

en: quarter-map official-geodata

it: piano-di-quartiere geodati-di-base

fr: Sondernutzungspläne regeln die Überbaubarkeit von Teilgebieten der Gemeinde. Sie ergänzen oder verfeinern die nutzungsplanerische Grundordnung (Art. 46 PBG). Der Quartierplan ordnet die Überbauung eines genau bezeichneten Gemeindeteils, der sich zur gesamthaften Erschliessung eignet. Er regelt die Erschliessung dieses Gebietes, indem er Strassen, Wege, Abstellflächen, Versorgungsleitungen und dergleichen sowie die entsprechenden Baulinien festlegt.

fr: Quartierpläne Differenz (UR)

de: Quartierpläne Differenz (UR)

en: Quartierpläne Differenz (UR)

it: Quartierpläne Differenz (UR)


tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

de: netzstruktur offentlicher-verkehr schienenverkehr schifffahrt verkehr

author: Kanton Luzern, Abteilung Geoinformation

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: Zeigt Haltestellen des öffentlichen Verkehrs, sowie Bahnstrecken, Schiffs- und Buslinien.

spatial: Kanton Luzern

de: Kanton Luzern, Abteilung Geoinformation

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

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.

value: LU-Kt - Geocat Harvester

de: Öffentlicher Verkehr: Haltestellen und Liniennetze Bahn, Bus und Schiff


blockmodelle-gebaude

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

regi

de: Regionen und Städte

title_for_slug: blockmodelle-gebaude

de: amtliche-vermessungav gebaude-und-anlagen oberflachenmodell 3d

de: geocat.ch Permalink

de: Relative Gebäudehöhe [m] der AV Gebäudegrundrisse des Kantons Luzern, berechnet aus der Höhendifferenz des digitalen Oberflächenmodells (DOM) und dem digitalen Terrainmodell (DTM), aus dem LiDAR-Flug 2024.

de: Blockmodelle Gebäude


nutzungsplanung-planungszonen

envi

de: Umwelt

title_for_slug: nutzungsplanung-planungszonen

de: bewilligungen eigentumsbeschrankungoreb nutzungsplanung raumplanung zonenplan

de: Mit Planungszonen wird sichergestellt, dass in den betroffenen Gebieten nur Vorhaben zulässig sind, die der geplanten künftigen Nutzung nicht widersprechen.

de: Nutzungsplanung: Planungszonen


maintainer: OGD-Koordinationsstelle St.Gallen

de: entsorgung fullstand sensor offene-sensordaten

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (ov2)

de: jsonl

media_type: application/json

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (jsonl)

format: JSON

de: parquet

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (parquet)

format: PARQUET

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (n3)

de: csv

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (csv)

de: shp

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (shp)

de: rdfxml

media_type: application/rdf+xml

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (rdfxml)

format: RDF XML

de: fgb

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (fgb)

de: json

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (json)

de: geojson

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (geojson)

de: gpx

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (gpx)

format: GPX

de: kml

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (kml)

format: KML

de: xls

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (xls)

de: turtle

media_type: text/turtle

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (turtle)

format: RDF Turtle

de: jsonld

de: Füllstandsensoren Glassammelstellen (Grünglas) Stadt St.Gallen (jsonld)

format: JSON-LD

de: Die Stadt St.Gallen verfügt über Sensoren in verschiedenen Glassammelstellen der Stadt, welche den Füllstand der Container messen. Dieser Datensatz zeigt die Messwerte der Grünglas-Sammelstellen stündlich aggregiert.

entsorgung

display_name: entsorgung

fullstand

display_name: fullstand

offene-sensordaten

display_name: offene-sensordaten

sensor

display_name: sensor

stadt-st-gallen

fr: Ville de Saint-Gall

de: Stadt St.Gallen

en: City of St.Gallen

it: Città di San Gallo

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.

political_level: commune


de: energy-hackdays sektor material umweltbelastung entsorgung co2

author: stadt-st-gallen

de: json

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (json)

de: csv

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (csv)

format: CSV

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (n3)

de: rdfxml

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (rdfxml)

de: parquet

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (parquet)

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (turtle)

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (jsonld)

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (xls)

de: jsonl

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (jsonl)

de: Der Datensatz zeigt die Material- und Energieflüsse der Entsorgungswege der Schweiz aus dem MatCH Synthesebericht der Eidgenössische Materialprüfungs- und Forschungsanstalt (EMPA), in dem u.a. die Umweltbelastung (Tonnen & CO2) der Wirtschaftssektoren berechnet wird.Der Datensatz wurde aus dem Synthesebericht 2018 erstellt und für die [Energy Hackdays 2021](https://energydatahackdays.ch/#c2391_self) aufbereitet. Daraus entstand eine Anwendung zum Thema "Klimaneutrale Städte". Mehr Infos dazu: [https://hack.opendata.ch/project/745](https://energydatahackdays.ch/#c2391_self)Mehr Infos zum Projekt MatCH und zu den verschiedenen Berichten finden Sie unter folgenden Ressourcen:[MatCH Projekt Informationen](https://www.empa.ch/web/s506/care-project-match)[Bericht - Synthesis: The Swiss Economy](https://www.empa.ch/documents/56122/728861/MatCH_Synthese_Bericht/22c48930-bc8e-4ebc-b899-6e189be39667)[Bericht - Building sector](https://www.empa.ch/documents/56122/728861/MatCH_Bericht_Bau_v8_161017.pdf/3a733b91-ab69-43cd-ad81-2b6817716eff) [Bericht - Mobility sector](https://www.empa.ch/documents/56122/728861/MatCH_Mobilitaet_Bericht_170913.pdf/96d1cb72-fdf1-4f0a-af24-214d5e0a452a)[Bericht - Production and consumption sector](https://www.empa.ch/documents/56122/728861/MatCH_ProduktionKonsum_Bericht_181024.pdf/ef576a3a-fcfa-4f58-9b21-1f05ff82efbd)

energy-hackdays

display_name: energy-hackdays

material

display_name: material

sektor

display_name: sektor

umweltbelastung

display_name: umweltbelastung

soci

de: Bevölkerung und Gesellschaft

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

envi

de: Umwelt

tran

de: Verkehr

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze


stadtarchiv-st-gallen

title_for_slug: stadtarchiv-st-gallen

de: geschichte historisch archiv

de: xls

de: Stadtarchiv St.Gallen (xls)

de: turtle

de: Stadtarchiv St.Gallen (turtle)

de: csv

de: Stadtarchiv St.Gallen (csv)

de: Stadtarchiv St.Gallen (rdfxml)

de: Stadtarchiv St.Gallen (n3)

de: Stadtarchiv St.Gallen (jsonl)

de: Stadtarchiv St.Gallen (parquet)

de: json

de: Stadtarchiv St.Gallen (json)

de: jsonld

de: Stadtarchiv St.Gallen (jsonld)

de: Im Stadtarchiv der Politischen Gemeinde St.Gallen finden Sie das Archivgut der Stadtverwaltung St.Gallen sowie der mit der Stadt fusionierten Gemeinden Tablat und Straubenzell. Daneben liegen im Stadtarchiv u.a. der historische Nachlass mehrerer Schulgemeinden, Karten, Pläne, Fotografien sowie zahlreiche Archive privater Herkunft.Hier finden sie den Link zum Findbuch des Stadtarchivs: [https://www.stadtarchiv-st.gallen.findbuch.net/php/main.php?be_kurz=414453#33](https://www.stadtarchiv-st.gallen.findbuch.net/php/main.php?be_kurz=414453#33)[](https://www.stadtarchiv-st.gallen.findbuch.net/php/main.php?be_kurz=414453#33)Eine Übersicht über sämtliche Bestände, sowie den Archivführer finden Sie unter: [https://www.stadt.sg.ch/home/freizeit-tourismus/stgallen-entdecken/geschichte/stadtarchiv.html](https://www.stadt.sg.ch/home/freizeit-tourismus/stgallen-entdecken/geschichte/stadtarchiv.html)[](https://www.stadt.sg.ch/home/freizeit-tourismus/stgallen-entdecken/geschichte/stadtarchiv.html)Das Stadtarchiv der Politischen Gemeinde St.Gallen umfasst Archivgut von der Helvetischen Revolution (1798) bis heute. Eine erste Übersicht über die Bestände gibt Ihnen unser [Archivführer](https://www.stadtarchiv-st.gallen.findbuch.net/home/Archivfuehrer%20-%20Auszug.pdf).Wenn Sie sich für die Geschichte der Reichsstadt St.Gallen (Mittelalter bis 1798) interessieren, wenden Sie sich bitte an das [Stadtarchiv der Ortsbürgergemeinde](http://www.stadtarchiv.ch/) St.Gallen.AnschriftStadtarchiv St.GallenNotkerstrasse 22CH-9000 St.GallenTelefon ++41 (0)71 224 62 23Fax ++41 (0)71 244 07 45Email [stadtarchiv@stadt.sg.ch](mailto:stadtarchiv@stadt.sg.ch)ÖffnungszeitenMontag bis Donnerstag, ausgenommen Fest- und Feiertage09:00 bis 12:00 und 14:00 bis 17:00[Webseite des Stadtarchivs St. Gallen](http://www.stadt.sg.ch/home/freizeit-tourismus/stgallen-entdecken/geschichte/stadtarchiv.html)[Webseite des Stadtarchivs der Ortsbürgergemeinde St. Gallen](http://www.stadtarchiv.ch/)Bei jedem Zugriff auf unsere Webseite wird die anonymisierte IP-Adresse, Datum und Uhrzeit, URL der besuchten Seite, Statuscode des Webservers, übertragene Datenmenge in Bytes und der verwendete Webbrowser (User-Agent) in einer Protokolldatei gespeichert.Diese Daten sind nicht personenbezogen und lassen keine Identifizierung der Internetbesucherinnen und -besucher zu. Sie werden ausschließlich zum Zweck der Datensicherheit, zur Fehleranalyse und zur statistischen Auswertung (Anzahl der Zugriffe pro Monat) verwendet und nicht an Dritte weitergegeben. Die Protokolldaten werden nach sechs Monaten gelöscht.

archiv

display_name: archiv

geschichte

display_name: geschichte

historisch

display_name: historisch

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

stadt-st-gallen

de: Stadt St.Gallen

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.

value: DCAT Harvester Stadt St. Gallen

de: Stadtarchiv St.Gallen


jahresziele-stadt-st-gallen

title_for_slug: jahresziele-stadt-st-gallen

de: dienststellen vision-2030 stadtrat stadtparlament

de: rdfxml

de: Jahresziele Stadt St.Gallen (rdfxml)

de: turtle

de: Jahresziele Stadt St.Gallen (turtle)

de: jsonl

de: Jahresziele Stadt St.Gallen (jsonl)

de: Jahresziele Stadt St.Gallen (csv)

de: Jahresziele Stadt St.Gallen (n3)

de: Jahresziele Stadt St.Gallen (jsonld)

de: xls

de: Jahresziele Stadt St.Gallen (xls)

de: Jahresziele Stadt St.Gallen (json)

de: parquet

de: Jahresziele Stadt St.Gallen (parquet)

de: Der Stadtrat der Stadt St.Gallen bestimmt und veröffentlicht Legislatur- und Jahresziele, welche den Handlungsfeldern der Vision 2030 zugeordnet werden. Diese Ziele werden jeweils am Ende des Jahres, bzw. der Legislatur bewertet und im Geschäftsbericht der Stadt St.Gallen veröffentlicht. Der Datensatz zeigt die Jahresziele und die jeweilige Bewertung bei abgeschlossenen Jahren.Mehr Informationen und die jeweiligen PDF-Dokumente finden Sie hier:[Stadtrat: Vision 2030 und Legislaturziele](https://www.stadt.sg.ch/home/verwaltung-politik/demokratie-politik/stadtrat.html)[Geschäftsbericht: Legislatur- und Jahresziele, inkl. Bewertung](https://www.stadt.sg.ch/home/verwaltung-politik/demokratie-politik/geschaeftsbericht.html)

dienststellen

display_name: dienststellen

stadtparlament

display_name: stadtparlament

stadtrat

display_name: stadtrat

de: Jahresziele Stadt St.Gallen


hundekotbehalter

title_for_slug: hundekotbehalter

de: Hundekotbehälter Stadt St.Gallen (turtle)

de: jsonld

de: Hundekotbehälter Stadt St.Gallen (jsonld)

de: Hundekotbehälter Stadt St.Gallen (xls)

de: Hundekotbehälter Stadt St.Gallen (ov2)

format: TXT

de: fgb

de: Hundekotbehälter Stadt St.Gallen (fgb)

de: Hundekotbehälter Stadt St.Gallen (rdfxml)

de: gpx

de: Hundekotbehälter Stadt St.Gallen (gpx)

de: Hundekotbehälter Stadt St.Gallen (n3)

de: shp

de: Hundekotbehälter Stadt St.Gallen (shp)

format: ZIP

de: Hundekotbehälter Stadt St.Gallen (jsonl)

de: json

de: Hundekotbehälter Stadt St.Gallen (json)

de: geojson

de: Hundekotbehälter Stadt St.Gallen (geojson)

de: csv

de: Hundekotbehälter Stadt St.Gallen (csv)

de: Hundekotbehälter Stadt St.Gallen (parquet)

de: kml

de: Hundekotbehälter Stadt St.Gallen (kml)

de: Standorte der Hundekotbehälter

robidog

display_name: robidog

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

stadt-st-gallen

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.


heizgradtage-st-galler-stadtwerke

title_for_slug: heizgradtage-st-galler-stadtwerke

de: heizung klima temperatur gas

de: jsonld

de: Heizgradtage St.Galler Stadtwerke (jsonld)

de: Heizgradtage St.Galler Stadtwerke (csv)

de: Heizgradtage St.Galler Stadtwerke (n3)

de: rdfxml

de: Heizgradtage St.Galler Stadtwerke (rdfxml)

de: parquet

de: Heizgradtage St.Galler Stadtwerke (parquet)

de: jsonl

de: Heizgradtage St.Galler Stadtwerke (jsonl)

de: Heizgradtage St.Galler Stadtwerke (json)

de: xls

de: Heizgradtage St.Galler Stadtwerke (xls)

de: turtle

de: Heizgradtage St.Galler Stadtwerke (turtle)

de: Die Heizgradtage (HGT) gestatten Rückschlüsse auf den klimabedingten Heizenergieverbrauch und dienen der Kontrolle der Heizanlage. Dazu wird an jedem Heiztag - einem Tag mit einer Tagesmitteltemperatur kleiner oder gleich 16 Grad Celsius - erhoben, um wie viel die gemessene Aussenlufttemperatur von der angestrebten Innenlufttemperatur von 20 Grad Celsius abweicht.Die monatlichen Heizgradtage sind die Summe der Differenzen zwischen Aussenlufttemperatur und angestrebter Innenlufttemperatur für alle Heiztage des Monats.Werden die Heizgradtage zur Splittung der Nebenkosten verwendet ist zu bedenken, dass der Warmwasserbedarf nicht über denselben Verteilschlüssel abgerechnet werden kann. Der Warmwasserbedarf ist nicht abhängig von den Heizgradtagen und in deren Betrachtung nicht enthalten.

gas

display_name: gas

heizung

display_name: heizung

klima

display_name: klima

temperatur

display_name: temperatur

ener

de: Energie

stadt-st-gallen

de: Stadt St.Gallen

de: Heizgradtage St.Galler Stadtwerke


de: voc feuchtigkeit offene-sensordaten real-time sensor co2 temperatur

de: json

de: CO2 Sensoren in den Innenräumen der Stadtverwaltung St.Gallen (json)

de: CO2 Sensoren in den Innenräumen der Stadtverwaltung St.Gallen (rdfxml)

de: CO2 Sensoren in den Innenräumen der Stadtverwaltung St.Gallen (parquet)

de: csv

de: CO2 Sensoren in den Innenräumen der Stadtverwaltung St.Gallen (csv)

de: jsonld

de: CO2 Sensoren in den Innenräumen der Stadtverwaltung St.Gallen (jsonld)

de: CO2 Sensoren in den Innenräumen der Stadtverwaltung St.Gallen (n3)

de: CO2 Sensoren in den Innenräumen der Stadtverwaltung St.Gallen (turtle)

de: CO2 Sensoren in den Innenräumen der Stadtverwaltung St.Gallen (xls)

de: CO2 Sensoren in den Innenräumen der Stadtverwaltung St.Gallen (jsonl)

de: Die Stadt St.Gallen verfügt über CO2 Sensoren in einigen Innenräumen und Sitzungszimmern der Stadtverwaltung. Dieser Datensatz zeigt die Messwerte dieser Sensoren stündlich aggregiert. Abhängig vom Sensor werden auch noch weitere Werte wie Luftdruck und Anzahl flüchtige organische Stoffe in der Luft angezeigt.

feuchtigkeit

display_name: feuchtigkeit

offene-sensordaten

display_name: offene-sensordaten

real-time

display_name: real-time

voc

display_name: voc

envi

de: Umwelt

stadt-st-gallen

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: medienmitteilung real-time newsfeed news

de: xls

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (xls)

de: turtle

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (turtle)

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (json)

de: rdfxml

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (rdfxml)

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (jsonld)

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (n3)

de: jsonl

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (jsonl)

de: parquet

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (parquet)

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (csv)

de: Der Datensatz bildet eine Schnittstelle zum Newsfeed der Medienmitteilungen der Stadtverwaltung. Der Link zum Newsfeed befindet sich unter "Referenzen"

medienmitteilung

display_name: medienmitteilung

news

display_name: news

newsfeed

display_name: newsfeed

educ

de: Bildung, Kultur und Sport

de: Stadt St.Gallen