en: snow first-order-catchment alptal meteorological-data runoff subalpine

en: Daily meteorological and snow data (1968-2019) Alptal

en:
Air temperature, dew point temperature, relative humidity, wind speed, precipitation and global radiation have been measured (since 1981) on a meadow (Erlenhöhe) in the Erlenbach catchment. It is located at 1'220 m a.s.l. with an exposure towards west. In order to assess the spatial variability of precipiation, two additional rain gauges have been running in the Vogelbach and Lümpenenbach catchment, respectively.
For the period before 1981, meteorological variables have been extrapolated from the nearby MeteoSwiss station Einsiedeln (ca. 15 km north) to the WSL station Erlenhöhe using a linear correction factor for air temperature, wind speed and precipitation.
Snow depth has been recorded automatically since 2003.

en: Daily runoff data from three steep torrents in the Alptal (1968-2019)

en: Runoff, water temperature and electrical conductivity have been measured since 1968 at the outlet of three torrential catchments (with an area of approximately 1 km2 each) located in the Alptal valley: Erlenbach, Lümpenenbach and Vogelbach. This data set provides daily mean values; data at 10-min resolution can be provided on request for the period 1984-2020 (contact: alptal@wsl.ch).

en: Manual snow measurements Alptal (1968-2020)

en:
Snow depth, snow density and snow water equivalent have been measured since winter 1968/69 along more than 15 transects distributed across the Alptal valley representing different altitudes, aspects and land use (closed forest and open meadows). Length of the snow courses: 20 to 30 m. The measurement interval has been weekly to monthly.
More details about the locations and methods can be found in Stähli, M.; Gustafsson, D., (2006). Long-term investigations of the snow cover in a subalpine semi-forested catchment. Hydrological Processes, 20, 411-428. doi: 10.1002/hyp.6058.

en:
This data set includes 52 years of hydrometeorological measurements from small (first-order) catchments in the pre-alpine valley Alptal. Here we provide daily mean values; values in sub-daily resolution can be provided on demand.
Runoff has been measured at the outlet of three small (first-order) catchments of approximately 1 km2 area: Erlenbach (two independent runoff measurements), Vogelbach and Lümpenenbach. The catchments are similar with regard to geology (Flysch) and soil conditions (clay soils), but differ in forest coverage (20 to 60%). A detailed description of the catchments can be found at https://www.wsl.ch/alptal .
Runoff in these small catchments is typically very dynamic and can temporally carry large amounts of sediment and large wood. Thus, the accuracy of the measurements at very large flow is limited.
Meteorological variables have been measured on a meadow (Erlenhöhe) located in the Erlenbach catchment at 1220 m a.s.l. using a standard meteorological station (incl. ventilated air temperature and heated rain gauges). In addition, precipitation has also been recorded at two other locations (in the Vogelbach and Lümpenenbach catchments).
Snow measurements have been conducted weekly to monthly since 1968 at more than 15 locations (30-m transects) representing different altitudes, aspects and land uses (meadow, forest). In addition, snow depth has been recorded continuously since 2003 at Erlenhöhe, and for this location we also include a simulation of snow depth and SWE (using the numerical model COUP) that assimilates the manual weekly snow-course measurements. Details on these snow measurements can be found in Stähli, M. and Gustafsson, D. 2006. Hydrol. Proc., 20, 411-428. doi: 10.1002/hyp.6058.

Further information on the methods and sensors can be found at https://www.wsl.ch/alptal .

A first version of this data set (for the period 1968-2017) was uploaded in June 2018 at the occasion of the 50-year anniversary. This original data set was updated in February 2021 (with data from 2018 and 2019), and this data set was used for a longterm trend analysis, submitted for publication in a special issue of Hydrological Processes.

alptal

display_name: alptal

first-order-catchment

display_name: first-order-catchment

meteorological-data

display_name: meteorological-data

runoff

display_name: runoff

subalpine

display_name: subalpine

education

en: Education and science

en: Longterm hydrological observatory Alptal (central Switzerland)


maintainer: EnviDat Support

en: outgoing davos incoming shortwave-radiation longwave-radiation

state: active

type: dataset

en: DATA ACCESS

media_type: SMET

format: SERVICE

en: Metadata

media_type: application/pdf

format: PDF

mimetype: application/pdf

en: Processing doc

en: Parameter file

media_type: text/plain

format: TXT

mimetype: text/plain

en:
Incoming and outgoing shortwave and longwave 2 min radiation measurements in Davos Dorf, CH.

 References
1. Marty, C., Philipona, R., Frohlich, C., Ohmura, A.. Altitude dependence of surface radiation fluxes and cloud forcing in the alps: results from the alpine surface radiation budget network. 2002. Theoretical and Applied Climatology. Volume 72. Issue 3-4. 137-155. http://dx.doi.org/10.1007/s007040200019. 10.1007/s007040200019.
2. Christoph Marty. Surface Radiation, Cloud Forcing and Greenhouse Effect in the Alps. 2000. Institute fuer Klimaforschung ETH. Zuercher Klima-Schriften. Volume 79. http://e-collection.library.ethz.ch/eserv/eth:23491/eth-23491-01.pdf.

davos

display_name: davos

incoming

display_name: incoming

longwave-radiation

display_name: longwave-radiation

outgoing

display_name: outgoing

shortwave-radiation

display_name: shortwave-radiation

fr: Education, science

de: Bildung, Wissenschaft

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: ASRB_DAV: Shortwave and longwave radiation measurements (2 min) in Davos Dorf


en: avalanche-accidents number-of-caught-persons number-of-dead-persons avalanche-accident-statistics avalanche-fatalities

en: Fatal avalanche accidents in Switzerland since 1995-1996

media_type: CSV

format: CSV

mimetype: text/csv

en:
This data collection contains information concerning all accidents by snow avalanches causing at least one fatality in Switzerland. The data set commences on 01/10/1995. After the completion of a hydrological year, the new data is added.

The following information is provided:

 * avalanche identifier
 * date of the accident
 * accuracy of the date in range of days before and after
 * canton
 * name of the locality
 * start zone of the avalanche
  * coordinates (Swiss coordinate system, approximately in middle of start zone)
  * accuracy of the coordinates in meters
 * elevation (in meteres above sea level, app. in middle of start zone)
 * slope aspect (main orientation of start zone)
 * slope inclination (in degree, steepest point within start zone)
 * number of dead persons
 * number of caught persons
 * number of fully buried persons
 * forecasted avalanche danger level
 * activity/location of the accident party at the time of the incident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

number-of-caught-persons

display_name: number-of-caught-persons

number-of-dead-persons

display_name: number-of-dead-persons


en: climate ecological-indicator-values soil grain-size taxonomic-diversity functional-diversity phylogenetic-diversity

en: Data access

media_type: ZIP

format: ZIP

en:
This dataset comprises a large array of ecological data for the European Alps:

  (1) Current soil and climate predictors at various resolutions.
  (2) GBIF observations of the European Alps Flora (~4,000 species).
  (3) Species habitat suitability maps (1,109 species; based on species observations filtered at 40x40-km)
  at various resolutions used in the study to generate (4); except 'expert'...
  (4) Expert, Taxonomic, phylogenetic and functional diversity of the study region at various resolutions
  (from 100-m to 40-km --> 100-m aggregated & mean to km + non-aggregated/predicted) for CLIM,
  SOIL and CLIM-SOIL models.
  (5) Ecological and altitudinal preferences of the European Alps Flora.
  (6) Data outputs of the related published article.
  (7) All scripts used for analyses.
  (8) Additional files used for analyses.
  (9) Improved set of species habitat suitability maps (~2,600 species; based on species observations
  filtered at 1x1-km) and related taxonomic diversity at 100-m resolution (aggregated to km +
  non-aggregated/predicted) for CLIM, SOIL and CLIM-SOIL models ---> not incorporated in the study.

climate

display_name: climate

ecological-indicator-values

display_name: ecological-indicator-values

functional-diversity

display_name: functional-diversity

grain-size

display_name: grain-size

phylogenetic-diversity

display_name: phylogenetic-diversity

soil

display_name: soil

taxonomic-diversity

display_name: taxonomic-diversity

en: Resolution in species distribution models shapes spatial patterns of plant multifaceted diversity


maintainer: Jürg Schweizer

en: avalanche-size danger-level avalanche-forcasting snow-avalanche avalanche-activity

en: Snow avalanche data

media_type: text/csv

en: This data file includes data on the avalanches mapped in the region of Davos.

en: Avalanche activity data

en: This data file includes data on the avalanche activity per day aggregated from the avalanche data.

en: Readme

en: The Readme file contains the description of the two data files.

en:
These data include all avalanches that were mapped in the region of Davos, Switzerland during the winters 1998-1999 to 2018-2019 (21 years), in total 13,918 avalanches, and the corresponding forecast danger level valid on the day of avalanche occurrence, 3533 days and danger ratings in total.

This avalanche activity data set was analysed and results published by Schweizer et al. (2020). They found that the
number of avalanches per day strongly increased with increasing danger level, but avalanche size was poorly related to avalanche danger level.

The data are provided in two files: the first includes the avalanche data (13,918 records); the second includes the avalanche activity per day (3533 records).
Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Schweizer, J., Mitterer, C., Techel, F., Stoffel, A. and Reuter, B., 2020. On the relation between avalanche occurrence and avalanche danger level. The Cryosphere, 14, 737-750, https://doi.org/10.5194/tc-14-737-2020.

avalanche-activity

display_name: avalanche-activity

avalanche-forcasting

display_name: avalanche-forcasting

avalanche-size

display_name: avalanche-size

danger-level

display_name: danger-level

snow-avalanche

display_name: snow-avalanche

education

en: Education and science

en: Snow avalanche data Davos, Switzerland, 1999-2019


backward-trajectories

maintainer: Michael Sprenger

title_for_slug: backward-trajectories

en: alps raclets backward-trajectories lagrangian-analysis cosmo atmospheric-dynamics complex-topopgraphy

en: Backward Trajectories

media_type: application/zip

en: The trajectories are started from surface up to 5000 m altitude, with an equidistant vertical spacing of 200 m, and calculated 120 h backward in time. As long as the trajectories stay in the COSMO1 domain (essentially the Alpine region), as run operationally at MeteoSwiss, the COSMO analysis wind fields are used. When the trajectories leave this domain, they are extended further backward in time based on ECMWF analysis data. The following fields are traced along the trajectories: longitude, latitude, geopotential height, pressure, specific humidity, temperature and surface topography. Furthermore, it is indicated for each trajectory time instance on which model data, COSMO or ECMWF, the trajectory time is based. Finally, the trajectories are started every hour in the specified time period, and positions and fields are available every 10 min. Each day is saved as a separate file. The last 8 digits of the file names indicate the starting date of the trajectories.

mimetype: application/zip

en: Backward trajectories were calculated from two positions: Davos Wolfgang (LON: 9.85361, LAT: 46.83551) and Weissfluhjoch (LON: 9.80646 LAT: 46.83304) for the time period February 2 until March 27 2019 using COSMO or ECMWF, respectively.

alps

display_name: alps

atmospheric-dynamics

display_name: atmospheric-dynamics

backward-trajectories

display_name: backward-trajectories

complex-topopgraphy

display_name: complex-topopgraphy

cosmo

display_name: cosmo

lagrangian-analysis

display_name: lagrangian-analysis

raclets

display_name: raclets

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: Backward  Trajectories


en: cmip5 climate-change orographic-precipitation precipitation-amount air-temperature

en: Download Server

en:
Predicting future climatic conditions at high spatial resolution is essential for many applications in science. Here we present data for monthly time series of precipitation and minimum and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation sums at ~5km spatial resolution globally for the years 1850-2100. We validated the performance of the downscaling algorithm by comparing model output with observed climates for the years 1950-2069.

CHELSA_cmip5_ts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

climate-change

display_name: climate-change

orographic-precipitation

display_name: orographic-precipitation

precipitation-amount

display_name: precipitation-amount

en: High resolution monthly precipitation and temperature timeseries for the period 2006-2100


en: review switzerland manure bioenergy biogas

en: Production de biogaz à partir d’engrais de ferme en Suisse

media_type: PDF

en: L'objectif de ce livre blanc est de fournir aux décideurs, aux administrations et aux parties prenantes les résultats de recherche les plus récents afin de promouvoir l'utilisation optimale de la bioénergie issue des engrais de ferme dans la transition énergétique suisse. A cette fin, les résultats du centre de compétence suisse pour la recherche en bioénergie - SCCER BIOSWEET - sont résumés et présentés dans un contexte plus large. Si rien d'autre n'est mentionné, les résultats se réfèrent à la Suisse et, dans le cas de la matière première, aux potentiels nationaux de biomasse.

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland


maintainer: Jana von Freyberg

en: uncertainties endmember-mixing-models plant-water-uptake review ecohydrology stable-water-isotopes root-zone

en: Data set of MEE-20-04-264 (CSV)

en: Data set of MEE-20-04-264

en: The following two tables contain information about the data sources of the values reported in Table 1 and 2 in the paper “Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources” published in the journal ‘Methods in Ecology and Evolution’.

en: The following two tables contain information about the data sources of the values reported in Table 1 and 2 in the paper “Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources” published in the journal 'Methods in Ecology and Evolution'.

ecohydrology

display_name: ecohydrology

endmember-mixing-models

display_name: endmember-mixing-models

plant-water-uptake

display_name: plant-water-uptake

root-zone

display_name: root-zone

stable-water-isotopes

display_name: stable-water-isotopes

uncertainties

display_name: uncertainties

en: Data set of: Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources


maintainer: Benjamin Reuter

en: snow avalanche-problem-type weissfluhjoch snow-instability avalanche-activity avalanche-danger snowpack snow-cover-modeling crocus avalanche

en: 1999-2017 Avalanche problem types from SNOWPACK

media_type: .csv

en:
Avalanche problem types were derived from snow cover simulations with the model SNOWPACK at the Weissfluhjoch study plot, Davos, CH.
The data cover the winter seasons between 1999-2017 and include the simulated annual frequencies of new snow, wind slab, persistent weak layer, aging-persistent weak layer and wet snow problem types.
The data are shown in Figure 8 in Reuter et al. (2021).

en: 2015-2016 Avalanche problem types from Crocus

en:
Avalanche problem types were derived from a snow cover simulation with the model Crocus for the winter season 2015-2016 at the Weissfluhjoch study plot, Davos, CH.
The data cover the period 01.01.2016-30.04.2016. The binary indicator (0,1) tells whether an avalanche problem type was identified in the snow cover simulation (1) or not (0).
The data are presented in Figure 7 in Reuter et al. (2021).

en: 2015-2016 Avalanche problem types from SNOWPACK

en:
Avalanche problem types were derived from a snow cover simulation with the model SNOWAPCK for the winter season 2015-2016 at the Weissfluhjoch study plot, Davos, CH.
The data cover the period 01.01.2016-30.04.2016. The binary indicator (0,1) tells whether an avalanche problem type was identified in the snow cover simulation (1) or not (0).
The data are presented in Figure 7 in Reuter et al. (2021).

en: 2015-2016 Seismic avalanche acitivity catalogue

en:
Avalanches were indentified in seismic data recorded by two seismic arrays, one deployed at Wannengrat (2,500 m) and another one deployed in the Dischma valley (2,000 m).
The data cover the period from 01.01.2016 - 30.04.2016 and are presented in Figure 7 in Reuter et al. (2021).

en: 1999-2017 Avalanche problem types from Crocus

en:
Avalanche problem types were derived from snow cover simulations with the model Crocus at the Weissfluhjoch study plot, Davos, CH.
The data cover the winter seasons between 1999-2017 and include the simulated annual frequencies of new snow, wind slab, persistent weak layer, aging-persistent weak layer and wet snow problem types.
The data are presented in Figure 8 in Reuter et al. (2021).

en:
Avalanche problem types were derived from snow cover simulations with the models Crocus and SNOWPACK at the Weissfluhjoch study plot, Davos, CH. The data include annual frequencies of avalanche problem types for the seasons 1999-2017 and daily presence of avalanche problem types for the period 01.01.2016 - 30.04.2016.
Avalanche activity was derived from two seismic sensor arrays deployed no further than 15 km from Weissfluhjoch, Davos, CH. The data cover the period 01.01.2016 - 30.04.2016.

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

avalanche-danger

display_name: avalanche-danger

avalanche-problem-type

display_name: avalanche-problem-type

crocus

display_name: crocus

snow

display_name: snow

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability

snowpack

display_name: snowpack

weissfluhjoch

display_name: weissfluhjoch

education

en: Education and science

en: Simulated avalanche problem types and seismic avalanche activity around Weissfluhjoch


en: uas swe snow-depth snow remote-sensing

en: .tfw file

media_type: tfw

en: coordinates for the .tif raster

en: HS map Brämabül, 14. April 2015

media_type: image/tiff

en:
10 cm resolution
15 cm accuracy

format: TIFF

mimetype: image/tiff

en:
This snow depth map was generated 14 January 2015, close to peak of winter accumulation, applying Unmanned Aerial System digital surface models with a spatial resolution of 10 cm. The covered area is 285'000 m2 at the top of Brämabüel, 2490 m a.s.l. covering all expositions. Coordinate system: CH1903LV03.

A detailed description is given here:

Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075-1088, 10.5194/tc-10-1075-2016, 2016.

Abstract:
Detailed information on the spatial and temporal distribution, and variability of snow depth (HS) is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Nowadays, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network is not able to capture the large spatial variability of snow depth in alpine terrain.
Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, such data acquisition is costly, if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand, is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UAS), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Such systems have the advantage that they are comparatively cost-effective and can be applied very flexibly to cover also otherwise inaccessible terrain. In this study we map snow depth at two different locations: a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and b) an exposed location (2500 m a.s.l.) on a peak in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) better than 0.07 to 0.15 m on meadows and rocks and a RMSE better than 0.30 m on sections covered by bushes or tall grass. This new measurement technology opens the door for efficient, flexible, repeatable and cost effective snow depth monitoring for various applications, investigating the worlds cryosphere.

remote-sensing

display_name: remote-sensing

snow-depth

display_name: snow-depth

swe

display_name: swe

uas

display_name: uas

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: UAS based snow depth maps Brämabüel, Davos, CH


maintainer: Leonie Schönbeck

en: vpd fluorescence drought pinus-sylvestris photosynthesis gas-exchange acclimation

en: Methods survey

en: Parameters and methods for point measurements / survey measurements

en: Methods diurnal measurements

en:
Parameters and methodology for diurnal measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Instrument details

en:
Instrument details for all LiCor instruments used during collection of dataset.

Metatdata created following guidelines from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Methods fluorescence

en:
Parameters and methodology for Fluorescence measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Variable names and units

media_type: XLSX

en: Variable names, description and units for the Pfynwald Gas exchange data

format: XLS

en: Pfynwald gas exchange

en:
Full dataset of Pfynwald gas exchange data taken in the period from June 2013 to October 2020.
All metdata can be found in attached documents.
Data uploaded after quality control using guidelines by Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en: Methods light response

en: Methods and parameters for light response curves

en: Methods ACi curves

en:
Parameters and methods for CO2 response curves of Photosynthesis.

Metatdata format by
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds.
All metadata can be found in the attached documents.

acclimation

display_name: acclimation

drought

display_name: drought

fluorescence

display_name: fluorescence

gas-exchange

display_name: gas-exchange

photosynthesis

display_name: photosynthesis

pinus-sylvestris

display_name: pinus-sylvestris

vpd

display_name: vpd

en: 2013-2020 gas exchange at Pfynwald


data-set-on-snow-instability

title_for_slug: data-set-on-snow-instability

en: snow-avalanche weak-layer rutschblock slab snow-stability-evaluation failure-initiation avalanche-forcasting crack-propagation slab-tensile-support propgatoin-saw-test

en: data set on snow instability

en: Read-me file on snow instability data

en:
These data on snow instability include three data subsets that were analyzed and the results published by Reuter and Schweizer (2018) who suggest a novel framework on how to describe snow instability by failure initiation, crack propagation and slab tensile support.

Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Reuter, B. and Schweizer, J., 2018. Describing snow instability by failure initiation, crack propagation and slab tensile support. Geophys. Res. Lett., 45, doi: 10.1029/2018GL078069.

avalanche-forcasting

display_name: avalanche-forcasting

crack-propagation

display_name: crack-propagation

failure-initiation

display_name: failure-initiation

propgatoin-saw-test

display_name: propgatoin-saw-test

rutschblock

display_name: rutschblock

slab

display_name: slab

slab-tensile-support

display_name: slab-tensile-support

snow-avalanche

display_name: snow-avalanche

snow-stability-evaluation

display_name: snow-stability-evaluation

weak-layer

display_name: weak-layer

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Data set on snow instability


en: snowmelt-lysimeter snowpack-outflow stable-water-isotopes snowmelt-rate solutes

en: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution. 10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

en:
This data contain volumes, solutes and isotopes of snowpack outflow measured by a snowmelt lysimeter system at three locations in the southern Alp catchment, situated Central Switzerland. The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.
The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (snowpack outflow volumes) at daily intervals from several sampling locations. Additionally, the data measured by the snowmelt lysimeter system are provided in 10-minute resolution.

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes

stable-water-isotopes

display_name: stable-water-isotopes

en: Daily data of the volumes, solutes and isotopes in snowpack outflow measured at three locations in the southern Alp catchment


maintainer: Henning Löwe

en: snow-mechanics 3d-ct-images unconfined-compression-experiments microstructure discrete-element-modelling spherical-model-snow

en: Data Access

media_type: HTTPS

en: Data Structure (Python Notebook - view online)

media_type: ipynb

en: Data Structure (Python Notebook)

en:
For the investigation of microstructural and mechanical properties of snow unconfined compression experiments and 3D computed tomography (CT) imaging were performed on sintered rounded grain snow and spherical model snow. The spherical model snow was generated to create geometrically simplified, well-defined microstructures for calibration of numerical models, such as discrete element models (DEM) in which the microstructure is represented by spherical particles.
In the experiments, microstructural variation was created by varying the sintering time (contact size) and the density of the ice sphere samples (number of contacts). The 3D CT images allow for a complete reconstruction of the entire experimental sample (cylindrical sample dimension: diameter = 33.6 mm; height = 14 mm).

discrete-element-modelling

display_name: discrete-element-modelling

microstructure

display_name: microstructure

snow-mechanics

display_name: snow-mechanics

spherical-model-snow

display_name: spherical-model-snow

unconfined-compression-experiments

display_name: unconfined-compression-experiments

en: Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples


en: snow-density microstructure antarctica snow-density-profile snowmicropen

en: Python code exported from the Jupyter notebook for processing the SnowMicroPen files

media_type: py

en: Documentation SnowMicroPen measurements

media_type: .zip

en: This *.zip archive contains all available documentation of the SnowMicroPen measurements, including the mapping of the SMP measurements in the terrestrial laser scan field at PEA (see documentation for 20161220) and at the Hammarryggen Ice Rise (see documentation for 20190104 and 20190111).

en: SnowMicroPen pts files and processed txt files

en: Zip archive containing the acquired *.pts files (binary files recorded by the SnowMicroPen), and the converted *.txt files using the SMP.ipynb jupyter notebook (see the python code in the other resources in this dataset)

en: Jupyter notebook for processing the SnowMicroPen files.

en: Manual snow pits and other snow density measurements

media_type: .txt

en: List of SnowMicroPen measurements

en: List of all SnowMicroPen measurements, including date and location, and processing status. This list has been generated by the python code (see other resources in this dataset).

en: SnowMicroPen (SMP) measurements and manual snowpits from Dronning Maud Land, East Antarctica. Measurements were taken in the vicinity of the Belgium Princess Elisabeth Station (PEA), in a transect towards the coast, and on the Lokeryggen and Hammarryggen Ice Rises near the coast. Measurements were taken during 3 individual campaigns in the 2016-2017, 2018-2019 and 2019-2020 field seasons.

antarctica

display_name: antarctica

snow-density

display_name: snow-density

snow-density-profile

display_name: snow-density-profile

snowmicropen

display_name: snowmicropen

en: SnowMicroPen measurements and manual snowpits from Dronning Maud Land, East Antarctica


en: functional-taxonomic-group endemic climate-change-impact madeira-island bryophyte-life-strategy moss biodiversity climate-change lichen-growthform functional-taxonomic-groups elevational-gradient liverwort lichen-growth-form bryophyte lichen photobiont disturbance endemic-species

en: MadCrypto – Bryophyte and macrolichen diversity in laurel forests of Madeira

en:
This dataset includes species lists of bryophytes and macrolichens (presence/absence) sampled on the forest floor and on trees in disturbed and undisturbed plots along elevation gradients in the laurel forests of Madeira island. It also contains species specific information (bryophytes: red list status, endemic status, taxonomic group, life strategy; macrolichens: photobiont type, growth form) as well as plot information (Plot_ID, sampling date, coordinates, elevation a.s.l. (m), disturbance type, sampled host tree species).

The dataset was used for the paper
Boch S, Martins A, Ruas S, Fontinha S, Carvalho P, Reis F, Bergamini A, Sim-Sim M (2019) Bryophyte and macrolichen diversity show contrasting elevation relationships and are negatively affected by disturbances in laurel forests of Madeira island. Journal of Vegetation Science.

en:
This dataset includes species lists of bryophytes and macrolichens (presence/absence) sampled on the forest floor and on trees in disturbed and undisturbed plots along elevation gradients in the laurel forests of Madeira island. It also contains species specific information (bryophytes: red list status, endemic status, taxonomic group, life strategy; macrolichens: photobiont type, growth form) as well as plot information (Plot_ID, sampling date, coordinates, elevation a.s.l. (m), disturbance type, sampled host tree species).

The dataset was used for the paper
Boch S, Martins A, Ruas S, Fontinha S, Carvalho P, Reis F, Bergamini A, Sim-Sim M (2019) Bryophyte and macrolichen diversity show contrasting elevation relationships and are negatively affected by disturbances in laurel forests of Madeira island. Journal of Vegetation Science 30: 1122–1133.

The excel file contains 5 sheets:
1) Plot information
2) Bryophyte data with species specific information, separated per substrate
3) Macrolichen data with species specific information, separated per substrate
4) Bryophyte data with species specific information (plot level data). Species lists of the two substrates were merged; if one substrate in a plot hosted a species identified only to genus level (genus spec.) but the second investigated substrate hosted an identified species of the same genus, we removed the genus spec. entry in the particular plot. The species list of sheet 2 and 4 might therefore differ slightly.
5) Macrolichen data with species specific information (plot level data). Species lists of the two substrates were merged; if one substrate in a plot hosted a species identified only to genus level (genus spec.) but the second investigated substrate hosted an identified species of the same genus, we removed the genus spec. entry in the particular plot. The species list of sheet 3 and 5 might therefore differ slightly.

biodiversity

display_name: biodiversity

bryophyte

display_name: bryophyte

bryophyte-life-strategy

display_name: bryophyte-life-strategy

climate-change

display_name: climate-change

climate-change-impact

display_name: climate-change-impact

disturbance

display_name: disturbance

elevational-gradient

display_name: elevational-gradient

endemic

display_name: endemic

endemic-species

display_name: endemic-species

functional-taxonomic-group

display_name: functional-taxonomic-group

functional-taxonomic-groups

display_name: functional-taxonomic-groups

lichen

display_name: lichen

lichen-growth-form

display_name: lichen-growth-form

lichen-growthform

display_name: lichen-growthform

liverwort

display_name: liverwort

madeira-island

display_name: madeira-island

moss

display_name: moss

photobiont

display_name: photobiont

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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


maintainer: Matthias Haeni

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

en: Site photo of the field station (JUF)

media_type: image/jpeg

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

mimetype: image/jpeg

en: Site aerial photo (Jussy)

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

en: Site photo of the forest station (JUB)

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

en: Data plot of the field station (JUF)

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

en: Data plot of the forest station (JUB)

en: Forest station data (JUB)

en: Data file.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Jussy in Switzerland where one station is located within a natural broad-leaved forest stand (JUB) with sessile oak (_Quercus petrea_; 90 yrs), aspen (_Populus tremula_; 60 yrs) and European hornbeam (_Carpinus betulus_; 60 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, JUF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Jussy is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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


en: urban-compactness forest-gain built-up-classification topography planning-outcome land-use-and-cover-change spatial-modelling urban-sprawl urban-morphology forest-persistence nature-conservation basic-services

media_type: geotiff

en: Native forest cover gains from 2005 to 2015

format: GeoTIFF

en: Increase in waste collection service

en: Topographic Index Position (TPI)

en: infill

en: New built-up pixels classified as infill

en: Descricao dos dados em portiuguês

en: Portugues description

en: Population density per pixel (change per year)

en: isolated

en: New built-up pixels classified as isolated

media_type: SHP

en: Master plan Ihabela (zones)

format: SHP

en: Increase in clean water provision service

en: Ecological-Economic Zoning (EEZ)

en: Permanent housing density increase

en: Increase in sanitation service

en: Native forest cover persistence from 2005 to 2015

en: Urban persistence: Built-up 2005 = Built-up 2015

media_type: .shp

en: Master plan Ubatuba (zones)

en: Variables description

en: Table of content. Variables description, source, and other important information

en:
Basic education in % per census sector (change per
year)

en: Axial

en: New built-up pixels classified as axial

en: slope

en: Slope °

en: Mean income in Reais (R$) per census sector (change per year)

en: Increase in Normalized Difference Vegetation Index

en: Human Development Index (HDI) per municipality (change per year)

en:
The present dataset is part of the published scientific paper entitled “The role of spatial planning in land change: An assessment of urban planning and nature conservation efficiency at the southeastern coast of Brazil” (Pierri Daunt, Inostroza and Hersperger, 2021). In this work, we evaluated the conformance of stated spatial planning goals and the outcomes in terms of urban compactness, basic services and housing provision, and nature conservation for different land-use strategies. We evaluate the 2005 Ecological-Economic Zoning (EEZ) and two municipal master plans from 2006 in a coastal region in São Paulo State, Brazil. We used Partial Least Squares Path Modelling (PLS-PM) to explain the relationship between the plan strategies and land-use change ten years after implementation in terms of urban compactness, basic services and housing increase, and nature conservation.

We acquired the data for the explanatory variables from different sources listed on Table 1. Since the model is spatially explicit, all input data were transformed to a 30 m resolution raster. Regarding the evaluated spatial plans, we acquired the zones limits from the São Paulo State Environmental Planning Division (CPLA-SP), Ilhabela and Ubatuba municipality.

1)	Land use and cover data: Urban persistence, Urban axial, Urban infill, Urban Isolates, Forest cover persistence, Forest cover gain, NDVI increase

We acquired two Landsat Collection 1 Higher-Level Surface Reflectance images distributed by the U.S. Geological Survey (USGS), covering the entire study area (paths 76 and 77, row 220, WRS-2 reference system, https://earthexplorer.usgs.gov/). We classified one image acquired by the Landsat 5 Thematic Mapper (TM) sensor on 2005-05-150, and one image from the Landsat 8 Operational Land Imager (OLI) sensor from 2015-08-15. We collected 100 samples for forest cover, 100 samples for built-up cover and 100 samples for other classes. We then classified these three classes of land cover at each image date using the Support Vector Machine (SVM) supervised algorithm (Hsu et al., 2003), using ENVI 5.0 software.

Land-use and land-cover changes from 2005 to 2015 were quantified using map algebra, by mathematically adding them together in pairs (10*LULC2015 + LULC2005). We reclassified the LULC data into forest gain (conversion of any 2005 LULC to forest cover in 2015); forest persistence (2005 forested pixels that remained forested in 2015); new built-up area (conversion of any 2005 LULC to built-up in 2015); and urban maintenance (2005 built-up pixels that remained built-up in 2015).

To describe the spatial configuration of the urban expansion, we classified the new built-up areas into axial, infill and isolated, following Inostroza et al. (2013) (For details, please refer to Supplementary Material I at the original publication).

The NDVI was obtained from the same source used for the LULC data. With the Google Engine platform, we used an annual average for the best pixels (without clouds) for 2005 and 2015, and we calculated the changes between dates. We used increases of > 0.2 NDVI to represent an improvement in forest quality.

2)	Federal Census data organization: Urban Basic Services and Housing indicator, socioeconomic and population:

The data used to infer the values of basic services provision, socioeconomic and population drivers was derived from the Brazilian National Census data (IBGE, 2000 and 2010). Population density, permanent housing unit density, mean income, basic education, and the percentage of houses receiving waste collection, sanitation and water provision services, called basic services in the context of this study, were calculated per 30 m pixel. The Human Development Index is only available at the municipality level. We attributed the HDI for the vector file with the municipality border, and we rasterized (30 m resolution) this file in QGIS. Annual rates of change were then calculated to allow comparability between LULC periods. To infer the BSH, we used only areas with an increase in permanent housing density and basic services provision (See Supplementary Material I at the original publication).

3)	Topographic drivers

To infer the values of the topographic driver, we used the slope data and the Topographic Index Position (TPI) based on the digital elevation model from SRTM (30 m resolution) produced by ALOS (freely available at eorc.jaxa.jp/ALOS/en/about/about_index.htm), and both variables were considered constant from 2005 to 2015 (See Supplementary Material I at the original publication).

basic-services

display_name: basic-services

en: Spatially explicit data to evaluate spatial planning outcomes in a coastal region in São Paulo State, Brazil


maintainer: Ana Beatriz Pierri Daunt

en: decision-making sense-of-place planning multifunctionality landscape-planning literature-review resilience landscape-perception green-infrastructure landscape-services landscape-ecology socio-ecological-system pdfsearch ecosystem-services

en: 6. Protocol

en: 5. Planning steps.

media_type: CSV

en: 4. Use of any additional concept.

en: 3. Use of any early concept.

en: 2. Frequency of additional concepts.

en: 1. Frequency of early concepts.

en:
Table of content: 1. Frequency of early concepts; 2. Frequency of additional concepts; 3. Use of any early concept; 4. Use of any additional concept, 5. Planning steps; 6. Protocol.

The present dataset is part of the published scientific paper entitled “Landscape ecological concepts in planning: review of recent developments” (Hersperger et al., 2021). The goal of this research was to review recent publications to assess the use of landscape ecological concepts in planning. Specifically, we address the following research questions: Q1. Landscape ecological concepts: What are they? How frequently are they mentioned in current research? Q2. How are landscape ecological concepts integrated in landscape planning?

We analysed all empirical and overview papers that have been published in four key academic journals in the field of landscape ecology and landscape planning in the years 2015–2019 (n = 1918). Four key journals in the field of landscape ecology were selected to conduct the analysis, respectively Landscape Ecology (LE), Landscape Online (LO), Current Landscape Ecology Reports (CLER), and Landscape and Urban Planning (LUP). The title, abstract and keywords of all papers were read in order to identify landscape ecological concepts. Then, all 1918 papers went through a keyword search to identify the use of early and additional concepts. We used the “pdfsearch” package in R programming language and searched for singular and plural forms and different variations of the concepts (see Supplementary material 1, Table A). As a result, we provided four outputs:

  1. Frequency of early concepts. This data provides the total number of times each article used each early concept (Q1). This data was used to produce the Figure 2a at the original publication.

  2. Frequency of additional concepts. This data provides the total number of times each article used each additional concept (Q1). This data was used to produce the Figure 2b at the original publication.

  3. Use of any early concept. This data provides the total number of times each article used any early concept (Q1).
This data was used to produce the Figure 3a at the original publication.

  4. Use of any additional concept. This data provides the total number of times each article used any additional concept (Q1). This data was used to produce the Figure 3b at the original publication.

To address the second question (Q2), the title, abstract and keywords of the papers included in our sample (n=1918 articles) were screened to identify papers that might show how landscape ecological concepts are integrated into planning. We selected 52 empirical papers (see Supplementary material – 4 Integration of landscape ecological concepts into planning), and we provided two outputs:

  5. Planning steps. This data provides the number of times landscape ecological concepts were addressed in each
planning steps in 52 empirical papers analysed in detail (Q2). This data was used to produce the Figure 4 at the
original publication.

  6. Protocol for assessing the integration of landscape ecological concepts into planning. To systematically collect the
data, we used this protocol which addressed the following questions: (a) which type of planning is addressed by the
paper? (b) to which planning level does the paper refer to? (c) which concepts are integrated in any of the planning
steps described above?

decision-making

display_name: decision-making

ecosystem-services

display_name: ecosystem-services

green-infrastructure

display_name: green-infrastructure

landscape-ecology

display_name: landscape-ecology

landscape-perception

display_name: landscape-perception

landscape-planning

display_name: landscape-planning

landscape-services

display_name: landscape-services

literature-review

display_name: literature-review

multifunctionality

display_name: multifunctionality

pdfsearch

display_name: pdfsearch

planning

display_name: planning

resilience

display_name: resilience

sense-of-place

display_name: sense-of-place

socio-ecological-system

display_name: socio-ecological-system

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: The usage of landscape ecological concepts in the planning literature


weissfluhjoch-dataset-for-esm-snowmip

maintainer: Nander Wever

title_for_slug: weissfluhjoch-dataset-for-esm-snowmip

en: esm-snowmip snow-models snow weissfluhjoch snow-depth

en: ini file

en: This ini file is required by data-converter from MeteoIO version 1887 (http://models.slf.ch/p/meteoio/)

en: Conversion script

media_type: text/x-sh

en:
Use this script to convert WFJ_optimaldataset_v6.smet to wfj.smet, the file that is used for the ESM-SnowMIP project. It also requires the file: WFJ_AirPressure_Data.zip

Use: bash create_wfj_dataset.sh > input/wfj.smet

mimetype: text/x-sh

en: Dataset Weissfluhjoch for ESM-SnowMIP

en: This Weissfluhjoch dataset is a processed version of the Weissfluhjoch dataset version 6 from https://doi.org/10.16904/6. This dataset was specially created for the ESM-SnowMIP project. Here it is documented how this dataset has been created.

esm-snowmip

display_name: esm-snowmip

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-models

display_name: snow-models

weissfluhjoch

display_name: weissfluhjoch

en: Weissfluhjoch dataset for ESM-SnowMIP


kof-economic-sentiment-indicator

maintainer: KOF Datenservice

title_for_slug: kof-economic-sentiment-indicator

en: Data description

media_type: text/csv

fr: Description des données

fr: KOF Indice du climat économique

en: KOF Economic Sentiment Indicator

de: KOF Economic Sentiment Indicator

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

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

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

de: Datenbeschreibung

climat-economique

display_name: climat-economique

economic-sentiment

display_name: economic-sentiment

okonomische-stimmung

display_name: okonomische-stimmung

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

kof-konjunkturforschungsstelle

fr: KOF Centre de recherches conjoncturelles

de: KOF Konjunkturforschungsstelle

en: KOF Swiss Economic Institute

it: KOF Centro di ricerca congiunturale

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

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

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

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

value: KOF Harvester


maintainer: James W. Kirchner

en: ecohydrology sap-flow diel-cycle streamflow diurnal-cycle evapotranspiration groundwater snowmelt

en: 30-minute time series

media_type: text/plain

en: 30-minute hydrometeorological and ecohydrological time series.

en: MODIS EVI2 script

en: Google Earth Engine script for computing MODIS two-band enhanced vegetation index (EVI2) values and averaging them over subcatchments.

en: Metadata

media_type: application/pdf

en: Column descriptions for both data files, and map coordinates for all measurement locations.

en: Subcatchment polygons

en: Subcatchment polygons for use in the Google Earth Engine scripts.

en: Daily time series

en: Daily hydrometeorological and ecohydrological time series

en: MODIS NDSI script

en: Google Earth Engine script for computing MODIS normalized difference snow index (NDSI) values and averaging them over subcatchment areas.

en:
Hydrometerological and ecohydrological time series from Sagehen Creek and Independence Creek, Sierra Nevada, USA, illustrating hydrological responses to daily cycles in snowmelt and evapotranspiration forcing.

Data include 30-minute time series of

- weather variables,

- sap flow fluxes,

- groundwater levels (in two riparian transects of shallow groundwater wells),

- and stream stages (at 12 sites spanning a 500-meter elevation gradient),

and daily time series of

- temperature, precipitation, and snow water equivalent at three nearby snow telemetry stations

- diel cycle index values for groundwater levels and stream stages,

- and MODIS normalized difference snow index (NDSI) and enhanced vegetation index (EVI2) values averaged over selected subcatchments.

Google Earth Engine scripts for extracting the MODIS data are also provided.

diel-cycle

display_name: diel-cycle

diurnal-cycle

display_name: diurnal-cycle

ecohydrology

display_name: ecohydrology

evapotranspiration

display_name: evapotranspiration

groundwater

display_name: groundwater

sap-flow

display_name: sap-flow

snowmelt

display_name: snowmelt

streamflow

display_name: streamflow

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Daily cycles in solar flux, snowmelt, transpiration, groundwater, and streamflow at Sagehen and Independence Creeks, Sierra Nevada, USA


globale-konjunkturbarometer

title_for_slug: globale-konjunkturbarometer

fr: Baromètres conjoncturels mondiaux

de: Globale Konjunkturbarometer

en: Global Economic Barometers

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

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

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

en: Data description

economie-mondiale

display_name: economie-mondiale

global-economy

display_name: global-economy

weltwirtschaft

display_name: weltwirtschaft

national-economy

en: National economy

kof-konjunkturforschungsstelle

en: KOF Swiss Economic Institute

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


maintainer: Ionuț Iosifescu Enescu

en: huge map 100GB

en: map 2GB

en: map 0.2GB

en: large map 10GB

en: map 1GB

en: map preview 0.5MB

en: map 0.5GB

en: Bulk Data Access

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

en:
The attached data are some large GIS raster files (GeoTIFFs) made with Natural Earth data. Natural Earth is a free vector and raster map data @ naturalearthdata.com. The data used for creating these large files was the "Cross Blended Hypso with Shaded Relief and Water". Data was concatenated to achieve larger and larger files. Internal pyramids were created, in order that the files can be opened easily in a GIS software such as QGIS or by a (future) GIS data visualisation module integrated in EnviDat.

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis

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: Large GIS raster data derived from Natural Earth Data (Cross Blended Hypso with Shaded Relief and Water)


geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

health

fr: Santé

de: Gesundheit

en: Health

it: Sanità

label: Link zum Geoportal

label: geocat.ch permalink

spatial: Schweiz-BAG-Faeller

fr: Map (Preview) Aperçu map.geo.admin.ch

de: Map (Preview) Vorschau map.geo.admin.ch

en: Map (Preview)  map.geo.admin.ch

it: Map (Preview) Previsione map.geo.admin.ch

fr: Aperçu map.geo.admin.ch

de: Vorschau map.geo.admin.ch

en: Preview map.geo.admin.ch

it: Previsione map.geo.admin.ch

fr: Serveur de téléchargement de geo.admin.ch

de: Download Server von geo.admin.ch

en: Download server from geo.admin.ch

it: Server di download di geo.admin.ch

fr: RESTful API de geo.admin.ch

de: RESTful API von geo.admin.ch

en: RESTful API from geo.admin.ch

it: RESTful API da geo.admin.ch

format: API

fr: La méningo-encéphalite à tiques (FSME) est une infection transmise par les tiques, soumise à l'obligation légale de déclarer. Entre 2012 et 2022, au moins un cas de FSME a été déclaré dans les communes figurant en orange sur la carte.

de: Die Frühsommer-Meningoenzephalitis (FSME) ist eine durch Zecken übertragene Erkrankung, für die eine gesetzlich verankerte Meldepflicht besteht. Diese Karte zeigt in Orange die Gemeinden auf, in denen im Zeitraum 2012-2022 mindestens 1 Fall von FSME gemeldet wurden.

en: Tick-borne encephalitis (TBE) is an infectious viral disease transmitted by ticks, which is subject to a statutory duty to report. This map shows in orange the communes in which at least one case of TBE was reported in the period 2012-2022.

it: La meningoencefalite primaverile-estiva (FSME) è una malattia trasmessa dalle zecche, per la quale è stato sancito per legge l'obbligo di dichiarazione. La presente cartina mostra in arancio i Comuni in cui nel periodo 2012-2022 è stato dichiarato almeno un caso di FSME.

bundesamt-fur-gesundheit-bag

fr: Office fédéral de la santé publique OFSP

de: Bundesamt für Gesundheit BAG

en: Federal Office of Public Health FOPH

it: Ufficio federale della sanità pubblica UFSP

fr: L'Office fédéral de la santé publique (OFSP) fait partie du Département fédéral de l'intérieur. De concert avec les cantons, il assume la responsabilité des domaines touchant à la santé publique ainsi que la mise en œuvre de la politique sanitaire. Autorité à vocation nationale, il représente les intérêts sanitaires de la Suisse dans les organisations internationales et auprès d'autres Etats.

de: Das Bundesamt für Gesundheit (BAG) ist Teil des Eidgenössischen Departements des Innern. Es ist - zusammen mit den Kantonen - verantwortlich für die Gesundheit der Schweizer Bevölkerung und für die Entwicklung der nationalen Gesundheitspolitik. Zudem vertritt das BAG als nationale Behörde die Schweiz in Gesundheitsbelangen in internationalen Organisationen und gegenüber anderen Staaten.

en: The Federal Office of Public Health (FOPH) is part of the Federal Department of Home Affairs. Along with the cantons it is responsible for public health in Switzerland and for developing national health policy. As the national health authority, the FOPH also represents Switzerland's interests in the field of health in international organisations and with respect to other countries.

it: L'Ufficio federale della sanità pubblica (UFSP) è incorporato nel Dipartimento federale dell'interno. Unitamente ai Cantoni, è responsabile della salute della popolazione svizzera e dello sviluppo della politica nazionale in materia di salute. In qualità di autorità nazionale rappresenta inoltre gli interessi della Svizzera in materia di sanità in seno a organizzazioni internazionali e nei rapporti con altri Stati.

political_level: confederation

value: BAG - Geocat Harvester

fr: Lieux déclarés de piqûre pour la méningo-encéphalite à tiques (FSME), Suisse, 2012-2022

de: Gemeldete Stichorte der Frühsommer-Meningoenzephalitis (FSME), Schweiz, 2012-2022

en: Site of tick bite reported for tick-borne encephalitis (TBE), Switzerland, 2012-2022

it: Luoghi in cui sono stati dichiarati casi di meningoencefalite primaverile-estiva (FSME), Svizzera, 2012-2022


maintainer: OGD-Koordinationsstelle St.Gallen

de: real-time api resultate abstimmungen wahlen

de: json

media_type: application/json

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

format: JSON

mimetype: application/json

license: CC BY

de: csv

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

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

abstimmungen

display_name: abstimmungen

api

display_name: api

real-time

display_name: real-time

resultate

display_name: resultate

wahlen

display_name: wahlen

politics

fr: Politique

de: Politik

en: Politics

it: Politica

staatskanzlei-kanton-st-gallen

de: Staatskanzlei Kanton St.Gallen

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

«Wir verbinden und überzeugen. Ihre Staatskanzlei.»

political_level: canton

value: DCAT Staatskanzlei Kanton St.Gallen


kof-business-situation-indicator

title_for_slug: kof-business-situation-indicator

fr: situation-des-affaires suisse

de: schweiz geschaftslageindikator

de: Datenbeschreibung

fr: KOF Indicateur de la situation des affaires

de: KOF Business Situation Indicator

en: KOF Geschäftslageindikator

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

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

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

fr: Description des données

en: Data description

bussiness-situation

display_name: bussiness-situation

economics

display_name: economics

geschaftslageindikator

display_name: geschaftslageindikator

schweiz

display_name: schweiz

situation-des-affaires

display_name: situation-des-affaires

suisse

display_name: suisse

switzerland

display_name: switzerland

national-economy

de: Volkswirtschaft

en: National economy

kof-konjunkturforschungsstelle

de: KOF Konjunkturforschungsstelle

en: KOF Swiss Economic Institute

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

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


kof-konjunkturbarometer

title_for_slug: kof-konjunkturbarometer

fr: conjoncture suisse

de: konjunktur vorlaufindikator schweiz

en: fli switzerland business-cycle leading-indicator

fr: KOF Baromètre conjoncturel

en: KOF Economic Barometer

de: KOF Konjunkturbarometer

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

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

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

business-cycle

display_name: business-cycle

conjoncture

display_name: conjoncture

fli

display_name: fli

konjunktur

display_name: konjunktur

leading-indicator

display_name: leading-indicator

vorlaufindikator

display_name: vorlaufindikator

national-economy

fr: Economie nationale

kof-konjunkturforschungsstelle

fr: KOF Centre de recherches conjoncturelles

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


de: real-time abstimmungen auszahlungen wahlen

de: json

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

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

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

abstimmungen

display_name: abstimmungen

auszahlungen

display_name: auszahlungen


kof-beschaftigungsindikator

title_for_slug: kof-beschaftigungsindikator

fr: emploi marche-de-lemploi

de: arbeitsmarkt beschaftigung

en: labour-market employment

fr: KOF Indicateur de l'emploi

en: KOF Employment Indicator

de: KOF Beschäftigungsindikator

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

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

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

arbeitsmarkt

display_name: arbeitsmarkt

beschaftigung

display_name: beschaftigung

emploi

display_name: emploi

employment

display_name: employment

labour-market

display_name: labour-market

marche-de-lemploi

display_name: marche-de-lemploi

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito


geography

fr: Géographie

de: Geographie

en: Geography

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

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

label: Geometadaten Kanton Zürich: GeoLion

spatial: Kanton Zürich

de: Download via GIS-Browser

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

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

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

fr:
Le département de géomatique est le centre de compétence du system d'information géographique du canton de Zurich.
Nous coordinons l'aquisition des géodonnées d'intérêt commun sur le territoire cantonal et les mettons à disposition des
secteurs public et privé et des particuliers.

en:
The department of geoinformation is the geospatial competency center of the Canton of Zurich.
We coordinate the acquisition of geodata within the cantonal territory and provide public, private, and government sectors with data of outstanding quality.

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

it: La divisione della geoinformazione è il centro d'eccellenza del Cantone di Zurigo per dati georeferenziati. Mettiamo a disposizione dati geografici e informazioni di alta qualità per l'economia, la società e la pubblica amministrazione su tutto il cantone.

value: ZH - Geocat Harvester

de: Kataster der belasteten Standorte (KbS)


de: resultate abstimmungen wahlen

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

de: csv

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

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

resultate

display_name: resultate

wahlen

display_name: wahlen

politics

fr: Politique

de: Politik

en: Politics

staatskanzlei-kanton-st-gallen

de: Staatskanzlei Kanton St.Gallen

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

«Wir verbinden und überzeugen. Ihre Staatskanzlei.»


de: ÖREB - Kataster der belasteten Standorte (KbS)


geography

de: Geographie

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

de: tiefbau strassen verkehr baustellen verkehrsbehinderung

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

name:
Tiefbauamt
             - Stab

de: Baustellen Kantonsstrassen


media_type: WCS

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

format: WCS

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

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WCS Immissionen (Luftqualität)


wfs-warmenutzungsatlas

title_for_slug: wfs-warmenutzungsatlas

media_type: WFS

de: Gebiete der Zulässigkeiten der verschiedenen Wärmenutzungen aus dem Untergrund und des Grundwassers. Tiefenbeschränkungen für Erdwärmesonden. Die Zone A wird im ÖREB geführt, die Zonen B-F sind im Datensatz Wärmenutzung (Vektor) enthalten.

format: WFS

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

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

de: WFS Wärmenutzungsatlas


wms-grundwasserkarte-mittelwasserstand

title_for_slug: wms-grundwasserkarte-mittelwasserstand

media_type: WMS

de: Grundwasserkarte Mittelwasserstand

format: WMS

de: WMS Grundwasserkarte Mittelwasserstand


wfs-denkmalschutzobjekte

title_for_slug: wfs-denkmalschutzobjekte

de: Denkmalschutzobjekte

name:
Amt für Raumentwicklung
               - Kantonale Denkmalpflege

de: WFS Denkmalschutzobjekte


wms-administrative-einteilungen-ogd

title_for_slug: wms-administrative-einteilungen-ogd

de: Administrative Einteilungen

name:
Amt für Raumentwicklung
               - Geoinformation

de: WMS Administrative Einteilungen (OGD)


de: Der WFS Vektor-Übersichtsplan bietet die Möglichkeit das Kartenwerk im Masstab 1:5'000 in vektorieller Form indivuduell zu visualisieren.

de: WFS Vektor-Übersichtsplan


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

name:
Tiefbauamt
               - Stab

de: WMS Baustellen Kantonsstrassen


wms-jagdreviere

title_for_slug: wms-jagdreviere

de: Jagdreviere Kanton Zürich.

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

de: WMS Jagdreviere


de: Hinweiskarte für anthropogene Böden

name:
Amt für Landschaft und Natur
               - Fachstelle Bodenschutz

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WMS Hinweiskarte für anthropogene Böden (OGD)


de: Ambrosia Beobachtungen

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

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

de: WFS Ambrosia Beobachtungen


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

de: WMS Strassenlärm


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

de: WMS Strassennetz: Strassentypisierung nach Richtplan:


de: Waldareal im Kanton Zürich

name:
Amt für Landschaft und Natur
               - Abteilung Wald

de: WFS Waldareal


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

de: WFS Gemeindegrenzen 1:5000


de: Das Tiefbauamt (TBA) betreibt auf den Staatsstrassen des Kantons Zürich Verkehrsmessstellen. Die Daten sind nun auch als Open-Data-WFS verfügbar.

de: WFS Verkehrsmessstellen


de: Klimaanalysekarten aus der Anwendung des Klimamodells FITNAH für das Gebiet des Kantons ZH. Rasterdaten mit 25m x 25m räumlicher Auflösung.

de: WCS Klimamodell ZH: Analysekarten (Raster)


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

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

de: Geoinformation Kanton Zürich

de: WMS Stromnetzgebiete


wms-offentliche-oberflachengewasser

title_for_slug: wms-offentliche-oberflachengewasser

de: Öffentliche Oberflächengewässer, Gewässerraum, Wasserrechte

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

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

de: WMS Öffentliche Oberflächengewässer


de: Gewässerschutzkarte

de: WFS Gewässerschutzkarte


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

de: WMS Ausnahmetransportrouten


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

name:
Amt für Mobilität
               - Mobilitätsentwicklung und -steuerung

de: WMS Tempo30- und Begegnungszonen


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

de: WFS Baustellen Kantonsstrassen


de: WMS Öffentliche Oberflächengewässer, Gewässerraum und Wasserrechte (OGD)


de: Dieser WFS beinhaltet die Streckenaufteilung auf Kantonsstrassen nach den Innerorts- und Ausserortsbereichen. Diese sind durch die Signale Ortsein- und Ortsausfahrt (Sig. 4.28 bis 4.30) definiert. Die zugrundeliegende Geometrie bildet der Geodatensatz Strassennetz Kanton Zürich GDS 102. Publiziert wird ein Auszug aus den Attributen des Geodatenelementes 54.4.

de: WFS Inner-/Ausserorts auf Kantonsstrasse


wms-abflussprozesskarte-ogd

title_for_slug: wms-abflussprozesskarte-ogd

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

de: WMS Abflussprozesskarte (OGD)


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

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WMS Immissionen (Luftqualität)


de: Entwicklung der mittleren Anzahl Anzahl Sommertage, Hitzetage, PET und Tropennächte pro Jahr für vier verschiedene Zeiträume.

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

de: WCS Klimamodell ZH: Szenarienkarten


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

de: WFS Haltestellen des öffentlichen Verkehrs


de: WMS Naturgefahrenkarte - Intensitätskarten Massenbewegungen


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

name:
Amt für Landschaft und Natur
               - Fachstelle Naturschutz

de: WMS Lebensraum- und Vegetationskartierungen


de: Von 1981 bis 2000 wurden laufend Luftaufnahmen über das Gebiet des Kantons Zürich erstellt. Das Amt für Raumentwicklung hat schwarz/weiss – Senkrechtaufnahmen in hoher Auflösung flächendeckend gescannt sowie georeferenziert und stellt diese zur freien Verfügung. Eine erste Auswahl liegt bereits vor. In den nächsten Monaten werden insgesamt 10'000 Aufnahmen platziert sein. Die Luftbilder können entweder mittels den Download-Links in der CSV-Datei heruntergeladen oder via GIS-Browser (http://maps.zh.ch?topic=HistLuftZH) mit dem Luftbild-Viewer - Tool LUBIS angeschaut, vergrössert, gedreht und downgeloadet werden.

de: WMS Luftbilder 1981-2000 (OGD)


wfs-grundwasserkarte-mittelwasserstand

title_for_slug: wfs-grundwasserkarte-mittelwasserstand

de: Grundwasserkarte Mittelwasserstand

de: WFS Grundwasserkarte Mittelwasserstand


wms-waldentwicklungsplan-ogd

title_for_slug: wms-waldentwicklungsplan-ogd

de: Waldentwicklungsplan

de: WMS Waldentwicklungsplan (OGD)


de: Strassenlärm - Emissionen als Web - Feature Service zum automatischen Bezug von Geometrien und Werten.

de: WFS Strassenlärm


wms-amtliche-vermessung-s-w-avwms-ogd

title_for_slug: wms-amtliche-vermessung-s-w-avwms-ogd

de: Die Daten der amtlichen Vermessung (AV) und der daraus erstellte Plan für das Grundbuch (PfdGB) sind die Grundlage für die Aufnahme und Beschreibung der Grundstücke im Grundbuch (Art. 950 ZGB). Zudem sind die AV-Daten die Georeferenzdaten für Bund, Kanton und Gemeinden sowie Wirtschaft, Wissenschaft und Dritten zur Gewinnung von Geoinformationen (Art. 1 VAV). Die Erfassung, Verwaltung und Nachführung der AV-Daten erfolgt dezentral bei den zuständigen Nachführungsstellen pro Gemeinde. Als projektierte Objekte werden in Mutation stehende Grundstücke sowie projektierte Bauten ab Baufreigabe geführt. Ausgeführte Bauten und Anlagen sind innerhalb eines Jahres seit der Bauvollendung in der AV nachzuführen. Nach der Nachführung sind die AV-Daten durch die Nachführungsstellen innerhalb einer Woche an das zentrale Datenportal Kanton Zürich hochzuladen. Inhalt und die Datenstruktur der amtlichen Vermessung (AV) sind im Datenmodell DM01AVZH24 definiert. Der AVWMS basiert auf dem vereinfachten Datenmodell MOpublicZH. Die Informationsebenen von AVWMS (MOpublicZH): - Fixpunkte: Dauerhaft versicherte Referenzpunkte zum Koordinatenbezugsrahmen LV95 - Bodenbedeckung: Gebäude, Strassen, Gewässer, Wald etc. - Einzelobjekte: Gebäudeteile, Mauer, Brücke, Masten etc. - Nomenklatur: Ortsnamen, Flurnamen - Liegenschaften: Grenzpunkte, Grundstücke, selbständige und dauernde Rechte - Rohrleitungen: Hochdruckleitungen für Gas und Öl - Hoheitsgrenzen: Gemeinde-, Bezirks-, Kantons-, Landesgrenzen - Gebäudeadressen: Hausnummer, Strassen, Postleitzahl und Ortschaften Dokumentation https://www.cadastre.ch/de/manual-av/service/mopublic.html

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WMS Amtliche Vermessung s/w (AVWMS) (OGD)


de: WMS der Rasterdarstellung der überkommunalen aktuellen Natur- und Landschaftsschutzverodnungen, SVO

geoinformation-kanton-zuerich

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

de: WMS der überkommunalen Natur- und Landschaftsschutzverodnungen


de: Denkmalschutzobjekte

de: WMS Denkmalschutzobjekte


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

de: WFS Abflussprozesskarte


de: Web Coverage Service des Digitalen Terrainmodells (DTM ZH) und des Digitalen Oberflächenmodells (DOM ZH) des Kanton Zürich.

de: WCS Digitales Terrain- (DTM) und Oberflächenmodell (DOM)


geography

de: Geographie

territory

de: Raum und Umwelt

de: Download via GIS-Browser

de: Der Seebautenkataster ist ein Übersichtsplan der zürcherischen Seen. Er enthält die Bauten und Anlagen der gültigen Konzessionen und Bewilligungen wie auch die Dimensionen der konzedierten Landanlagen.

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

de: Seebautenkataster


wms-gebaudevolumen-im-ha-raster

title_for_slug: wms-gebaudevolumen-im-ha-raster

de: Durchschnittliches Gebäudevolumen pro Hektare. Hektaren mit 3 oder wenigeren Bauten sind aus Gründen des Datenschutzes nicht aufgenommen.

de: WMS Gebäudevolumen im ha-Raster


de: Die Verkehrtechnische Abteilung der Kantonspolizei ist zuständig für die Verkehrsanordnungen im Kantonsgebiet (ohne Städte Zürich und Winterthur) und stellt die Verfügungen sämtlicher Strassensignalisationen/Markierungen aus. Diese Verfügungen bilden die Grundlage zur Nachführung der Höchstgeschwindigkeitssignale in der Strassendatenbank LOGO durch das TBA. Aus diesen Daten werden Abschnitte generiert. Halbjährlich werden die Daten ins SDE und in den GIS-Browser (inkl. WMS/WFS) exportiert. Die Datengrundlage ist das Geodatenelement GIS-ZH Nr. 54.3 (aus Geodatensatz GIS-ZH Nr. 54).

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WFS Signalisierte Geschwindigkeit Kantonsstrassen