maintainer: Roksolana Petrovska

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

en: Mortality of regeneration

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

media_type: r script (flat-ascii text)

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

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

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

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

acer

display_name: acer

dominance

display_name: dominance

fagus

display_name: fagus

lar

display_name: lar

mortality-rate

display_name: mortality-rate

regeneration

display_name: regeneration

shade-tolerance

display_name: shade-tolerance

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


maintainer: Rebecca Mott

en: snow-ablation-rates patchy-snow-covers riegl-vz6000 tls terrestrial-laser-scanning

state: active

type: dataset

media_type: application/zip

en: Digital Elevation Modell 2015

format: ZIP

mimetype: application/zip

en: Snowmask 2015

en: Gletschboden test site

media_type: application/pdf

format: PDF

mimetype: application/pdf

en: Digital Elevation Modell 2014

en: Snowmask 2016

en: Digital Elevation Modell 2016

en: Snowmask 2014

en: We recorded snow ablation maps with a terrestrial laser scanner (TLS, Riegl-VZ6000) at the Gletschboden area. The TLS position is located approximately 30 vertical meters above the Gletschboden area at a northerly exposed slope. In total 44 TLS measurement sets have been conducted in three consecutive years 2014-2016 (2014: 13 measurements; 2015: 17 measurements; 2016: 14 measurements). The TLS system has a single-point measurement frequency of 300 kHz and a beam divergence of 0.007°. This set-up allows a horizontal resolution of approximately 0.01 m in 100 m distance to the TLS position. One scan of the Gletschboden area lasts approximately 15 minutes. The travel time from the laser scanner towards the surface is recorded and afterwards converted into a point cloud of distances. 5 reflectors located at the Gletschboden area and in the closer surroundings were additionally scanned during each measurement to transform the point cloud from the scanner own coordinate system into Swiss coordinates. Additionally, orthophotos have been created by using pictures recorded from the TLS in order to provide snow mask maps. Snow and bare ground can be distinguished by the RGB color information of the orthophoto. Cells with blue band information greater than 175 were categorized as snow and all cells with values smaller or equal 175 were categorized as bare ground.

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

tls

display_name: tls

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: DISCHMEX - High-resolution daily snow ablation rates in an Alpine environment


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

en: View video on youtube!

format: SERVICE

en: DHM-Kacheln zusammenfügen

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. In this tutorial video, we show how to merge multiple DTM raster tiles into one file, using the QGIS tool ‘Virtual Raster’. This simplifies the digital planning of a cable line using the QGIS plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to Seilaplan website: https://seilaplan.wsl.ch

***************************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. In diesem Tutorialvideo zeigen wir, wie man mit dem QGIS-Plugin Virtuelles Raster mehrere DHM-Kacheln zu einem einzigen Rasterfile zusammenfügen und abspeichern kann. Für die Seillinienplanung mit Seilaplan muss nun nur noch eine Datei, mein neues virtuelles Raster, ausgewählt werden.

Link zur Seilaplan-Website: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geodata-processing

display_name: geodata-processing

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

raster-processing

display_name: raster-processing

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

en: Seilaplan Tutorial: Merge DTM tiles


maintainer: Loïc Pellissier Pellissier

en: functional-traits community-indices environmental-gradients herbivores-communities elevation plant-herbivore-interactions alps

en: Nematode surveys

media_type: text/plain

en: Surveys of soil nematode along elevation

format: TXT

mimetype: text/plain

en: Study sites

en: Coordinates and elevation of the study sites

en: Vegetion surveys

en: Species inventories of plants

en: Plant traits

en: Plant functional traits (SLA, LDMC, carbon and nitrogen content, punch strenght; averaged by species)

en: Orthoptera traits

en: Orthoptera functional traits (incisive mandibular strength averaged by species)

en: Orthoptera surveys

en: Species inventories of Orthoptera

en: Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017.

alps

display_name: alps

community-indices

display_name: community-indices

elevation

display_name: elevation

environmental-gradients

display_name: environmental-gradients

functional-traits

display_name: functional-traits

herbivores-communities

display_name: herbivores-communities

plant-herbivore-interactions

display_name: plant-herbivore-interactions

en: Above- and below-ground herbivore communities along elevation


maintainer: Sven-Eric Hopf

en: monitoring ash-dieback forest fraxinus iap

en: Monitoring of ash trees as part of the Intercantonal Forest Observation Programme

media_type: .pdf

en: Packgroun information on data for the publication: Spread and Severity of Ash Dieback in Switzerland – Tree Characteristics and Landscape Features Explain Varying Mortality Probability, (Klesse et al. 2021, Front. For. Glob. Change 4:645920., doi: 10.3389/ffgc.2021.645920)

en:
In 2013, the Institute for Applied Plant Biology (IAP) started a monitoring programme to study the development and the spatial variation of the ash dieback disease with the aim to find some partially resistant European ash trees (Fraxinus excelsior).
We collaborate as co-authors for the publication: Spread and Severity of Ash Dieback in Switzerland - Tree Characteristics and Landscape Features Explain Varying Mortality Probability (Klesse et al. 2021 in frontiers)

ash-dieback

display_name: ash-dieback

forest

display_name: forest

fraxinus

display_name: fraxinus

iap

display_name: iap

monitoring

display_name: monitoring

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.


backward-trajectories

maintainer: Michael Sprenger

title_for_slug: backward-trajectories

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

en: Backward Trajectories

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.

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.

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

en: Backward  Trajectories


maintainer: Matthias Haeni

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

en: Field station data (BAF)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Data plot of the field station (BAF)

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

en: Data plot of the forest station (BAB)

en: Site photo of the field station (BAF)

media_type: image/jpeg

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

mimetype: image/jpeg

en: Forest station data (BAB)

en: Site aerial photo (Beatenberg)

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

en: Site photo of the forest station (BAB)

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

en:
High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Beatenberg in Switzerland where one station is located within a natural coniferous forest (BAB) with Norway spruce (_Picea abies_; 190-210 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Beatenberg is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the
Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


biogas-aus-hofdunger-in-der-schweiz

maintainer: EnviDat Support

title_for_slug: biogas-aus-hofdunger-in-der-schweiz

en: biogas manure switzerland bioenergy review

en: Biogas aus Hofdünger in der Schweiz

media_type: PDF

en: Ziel dieses Whitepapers ist es, Entscheidungsträgern, Verwaltungen und Stakeholdern die aktuellsten Forschungsergebnisse zur Verfügung zu stellen, um die optimale Nutzung von Bioenergie aus Hofdünger in der Schweizer Energiewende zu fördern. Zu diesem Zweck werden die Ergebnisse des Schweizer Kompetenzzentrums für Bioenergieforschung - SCCER BIOSWEET - zusammengefasst und in einem breiteren Kontext dargestellt. Wenn nichts anderes erwähnt wird, beziehen sich die Ergebnisse auf die Schweiz und im Falle der Ressourcen auf die heimischen Biomassepotenziale.

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland

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: Franziska Koch

en: snow-cover liquid-water-content snow snow-depth gps

en: Dataset with GPS-derived snow cover properties and validation data

en: This file includes the data as described in the Read-me file.

en: Read-me

en: The read-me file contains the description of the data provided.

en:
This data set includes GPS-derived snow water equivalent (SWE), snow depth (HS) and liquid water content (LWC) data for three entire snow-covered seasons (2015-2016, 2016-2017, 2017-2018) at the study plot Weissfluhjoch 2540 m a.s.l. (Davos, Switzerland). The procedure to derive these snow properties is described in Koch et al. (2019). The novel approach is based on a combination of GPS signal attenuation and time delay.

The dataset also includes corresponding validation data for SWE and HS measured at Weissfluhjoch, and some additional meteorological data used for interpretation of the snow cover evolution.

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

These data are the basis of the following publication:
> Koch, F., Henkel, P., Appel, F., Schmid, L., Bach, H., Lamm, M., Prasch, M., Schweizer, J., and Mauser, W., 2019. Retrieval of snow water equivalent, liquid water content and snow height of dry and wet snow by combining GPS signal attenuation and time delay. Water Resources Research, 55(5), 4465-4487. https://doi.org/10.1029/2018WR024431

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

en: GPS-derived data of SWE, HS and LWC and corresponding validation data


maintainer: Tessa Hegetschweiler

en: recreational-activities teenagers adolescents forest childhood

en: Dataset survey at schools

en: The dataset of the questionnaire survey at schools in excel format.

format: XLS

en: Dataset comments

en: The codebook to the dataset

en: Questionnaire school survey

en: The questionnaire used in the survey at 8 schools aimed at teenagers in German.

en: Survey at schools 2017

en: The dataset of the questionnaire survey at schools in SPSS-format.

en: The data results from a questionnaire survey conducted at 8 schools in the cantons Zurich, Aargau and St. Gallen. Respondents aged 13-22 years. The aim of the survey was to gain insight into teenagers' relationship to the forest, reasons for visiting or not visiting the forest and activities in the forest.

adolescents

display_name: adolescents

childhood

display_name: childhood

forest

display_name: forest

recreational-activities

display_name: recreational-activities

teenagers

display_name: teenagers

en: Factors influencing teenagers' forest visit frequency


maintainer: Jana von Freyberg

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

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

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


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

en: Herunterladen des DHM mit SwissGeoDownloader

en: View video on youtube!

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. The plugin ‘Swiss Geo Downloader’, which is available for the open source geoinformation software QGIS, allows freely available Swiss geodata to be downloaded and displayed directly within QGIS. It was developed in 2021 by Patricia Moll in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. In this tutorial we describe how to download the high accuracy elevation model ‘swissALTI3D’ with the help of the ‘Swiss Geo Downloader’ and how to use it for digital planning of a cable line with the plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to the Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

Link to Seilaplan website: https://seilaplan.wsl.ch

*********************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Das Plugin Swiss Geo Downloader, welches für das Open Source Geoinformationssystem QGIS zur Verfügung steht, ermöglicht frei verfügbare Schweizer Geodaten direkt innerhalb von QGIS herunterzuladen und anzuzeigen. Es wurde 2021 von Patricia Moll in Zusammenarbeit mit der eidgenössischen Forschungsanstalt Wald, Schnee und Landschaft WSL entwickelt. In diesem Tutorial beschreiben wir, wie man mit Hilfe des Swiss Geo Downloaders das hochgenaue Höhenmodell swissALTI3D herunterladen und für die Seillinienplanung mit dem Plugin Seilaplan verwenden kann.

Link zum Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

Link zur Seilaplan-Webseite: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geo-downloader

display_name: swiss-geo-downloader

swiss-geodata

display_name: swiss-geodata

en: Seilaplan Tutorial: DTM download with SwissGeoDownloader


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

en: Data plot of the forest station (LAB)

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

en: Site aerial photo (Lausanne)

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

en: Data plot of the field station (LAF)

en: Site photo of the forest station (LAB)

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

en: Field station data (LAF)

en: Data file.

en: Forest station data (LAB)

en: Site photo of the field station (LAF)

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

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Lausanne in Switzerland where one station is located within a natural mixed forest stand (LAB) with European beech (_Fagus sylvatica_; 160-170 yrs), European silver fir (_Abies alba_; 160-170 yrs) and Norway spruce (_Picea abies_; 160-170 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, LAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lausanne is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


maintainer: Sofia Pagliarin

en: imperviousness soil-sealing barcelona urban-atlas copernicus milan

media_type: CSV

en: Information on data sources

media_type: mpk

en: Shareable project in Esri ArcGIS format including the HRL IMD data in raster format for each of the territorial boundaries as specified in letter a)-h), see Dataset description

media_type: .csv

en:
Dataset description

This dataset is a recalculation of the Copernicus 2015 high resolution layer (HRL) of imperviousness density data (IMD) at different spatial/territorial scales for the case studies of Barcelona and Milan. The selected spatial/territorial scales are the following:

 * a)	Barcelona city boundaries
 * b)	Barcelona metropolitan area, Àrea Metropolitana de Barcelona (AMB)
 * c)	Barcelona greater city (Urban Atlas)
 * d)	Barcelona functional urban area (Urban Atlas)
 * e)	Milan city boundaries
 * f)	Milan metropolitan area, Piano Intercomunale Milanese (PIM)
 * g)	Milan greater city (Urban Atlas)
 * h)	Milan functional urban area (Urban Atlas)

In each of the spatial/territorial scales listed above, the number of 20x20mt cells corresponding to each of the 101 values of imperviousness (0-100% soil sealing: 0% means fully non-sealed area; 100% means fully sealed area) is provided, as well as the converted measure into squared kilometres (km2).

 Dataset composition

The dataset is provided in .csv format and is composed of:

_IMD15_BCN_MI_Sources.csv_: Information on data sources

 _IMD15_BCN.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Barcelona:
 * a)	Barcelona city boundaries (label: bcn_city)
 * b)	Barcelona metropolitan area, Àrea metropolitana de Barcelona (AMB) (label: bcn_amb)
 * c)	Barcelona greater city (Urban Atlas) (label: bcn_grc)
 * d)	Barcelona functional urban area (Urban Atlas) (label: bcn_fua)

 _IMD15_MI.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Milan:
 * e)	Milan city boundaries (label: mi_city)
 * f)	Milan metropolitan area, Piano intercomunale milanese (PIM) (label: mi_pim)
 * g)	Milan greater city (Urban Atlas) (label: mi_grc)
 * h)	Milan functional urban area (Urban Atlas) (label: mi_fua)

_IMD15_BCN_MI.mpk_: the shareable project in Esri ArcGIS format including the HRL IMD data in raster format for each of the territorial boundaries as specified in letter a)-h).

Regarding the territorial scale as per letter f), the list of municipalities included in the Milan metropolitan area in 2016 was provided to me in 2016 from a person working at the PIM.

In the IMD15_BCN.csv and IMD15_MI.csv, the following columns are included:

 * Level: the territorial level as defined above (a)-d) for Barcelona and e)-h) for Milan);
 * Value: the 101 values of imperviousness density expressed as a percentage of soil sealing (0-100%: 0% means fully non-sealed area; 100% means fully sealed area);
 * Count: the number of 20x20mt cells corresponding to a certain percentage of soil sealing or imperviousness;
 * Km2: the conversion of the 20x20mt cells into squared kilometres (km2) to facilitate the use of the dataset.

 Further information on the Dataset

This dataset is the result of a combination between different databases of different types and that have been downloaded from different sources. Below, I describe the main steps in data management that resulted in the production of the dataset in an Esri ArcGIS (ArcMap, Version 10.7) project.

 1. The high resolution layer (HRL) of the imperviousness density data (IMD) for 2015 has been downloaded from the official website of Copernicus. At the time of producing the dataset (April/May 2021), the 2018 version of the IMD HRL database was not yet validated, so the 2015 version was chosen instead. The type of this dataset is raster.

 2. For both Barcelona and Milan, shapefiles of their administrative boundaries have been downloaded from official sources, i.e. the ISTAT (Italian National Statistical Institute) and the ICGC (Catalan Institute for Cartography and Geology). These files have been reprojected to match the IMD HRL projection, i.e. ETRS 1989 LAEA.

 3. Urban Atlas (UA) boundaries for the Greater Cities (GRC) and Functional Urban Areas (FUA) of Barcelona and Milan have been checked and reconstructed in Esri ArcGIS from the administrative boundaries files by using a Eurostat correspondence table. This is because at the time of the dataset creation (April/May 2021), the 2018 Urban Atlas shapefiles for these two cities were not fully updated or validated on the Copernicus Urban Atlas website. Therefore, I had to re-create the GRC and FUA boundaries by using the Eurostat correspondence table as an alternative (but still official) data source. The use of the Eurostat correspondence table with the codes and names of municipalities was also useful to detect discrepancies, basically stemming from changes in municipality names and codes and that created inconsistent spatial features. When detected, these discrepancies have been checked with the ISTAT and ICGC offices in charge of producing Urban Atlas data before the final GRC and FUA boundaries were defined.

Steps 2) and 3) were the most time consuming, because they required other tools to be used in Esri ArcGIS, like spatial joins and geoprocessing tools for shapefiles (in particular dissolve and area re-calculator in editing sessions) for each of the spatial/territorial scales as indicated in letters a)-h).

Once the databases for both Barcelona and Milan as described in points 2) and 3) were ready (uploaded in Esri ArcGIS, reprojected and their correctness checked), they have been ‘crossed’ (i.e. clipped) with the IMD HRL as described in point 1) and a specific raster for each territorial level has been calculated. The procedure in Esri ArcGIS was the following:

 * Clipping: Arctoolbox > Data management tools > Raster > Raster Processing > Clip. The ‘input’ file is the HRL IMD raster file as described in point 1) and the ‘output’ file is each of the spatial/territorial files. The option "Use Input Features for Clipping Geometry (optional)” was selected for each of the clipping.
 * Delete and create raster attribute table: Once the clipping has been done, the raster has to be recalculated first through Arctoolbox > Data management tools > Raster > Raster properties > Delete Raster Attribute Table and then through Arctoolbox > Data management tools > Raster > Raster properties > Build Raster Attribute Table; the "overwrite" option has been selected.

 Other tools used for the raster files in Esri ArcGIS have been the spatial analyst tools (in particular, Zonal > Zonal Statistics). As an additional check, the colour scheme of each of the newly created raster for each of the spatial/territorial attributes as per letters a)-h) above has been changed to check the consistency of its overlay with the original HRL IMD file. However, a perfect match between the shapefiles as per letters a)-h) and the raster files could not be achieved since the raster files are composed of 20x20mt cells.

The newly created attribute tables of each of the raster files have been exported and saved as .txt files. These .txt files have then been copied in the excel corresponding to the final published dataset.

barcelona

display_name: barcelona

copernicus

display_name: copernicus

imperviousness

display_name: imperviousness

milan

display_name: milan

soil-sealing

display_name: soil-sealing

urban-atlas

display_name: urban-atlas

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: Soil sealing Barcelona and Milan different territorial levels


envidat-supports-open-science

maintainer: Ionut Iosifescu Enescu

title_for_slug: envidat-supports-open-science

en: juypter-notebooks research-data-management wsl open-science envidat

en: Article as PDF

en:
The article "EnviDat Supports Open Science" originally appeared in WSLintern No. 3 (2020), page 14-15 and it is republished here with permission from the WSLintern editorial team. It contains guidelines for WSL scientists about the main issues behind Open Science and how to pragmatically approach the complexities of doing Open Science with EnviDat’s support.

License: This article is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

display_name: envidat

juypter-notebooks

display_name: juypter-notebooks

open-science

display_name: open-science

research-data-management

display_name: research-data-management

wsl

display_name: wsl

en: EnviDat Supports Open Science


en: polar terrestrial-laser-scans tls sea-ice sea-ice-elevation

en: Post Processed TLS's

media_type: ZIP

en: Compressed dat files

en: Link to post-processed TLS’s of Antarctic sea ice

en: Data processing documentation

media_type: DOC

en:
This dataset comprises of a post-processed set of terrestrial laser scans (TLS’s) of Antarctic sea ice obtained during the Sea Ice Physics and Ecosystem Experiment-2 (SIPEX-2, http://seaice.acecrc.org.au/sipex2012/) in September-November 2012. The post-processing steps include the registration of the individual scans into a single 3-dimensional point cloud, the removal of unwanted noise caused by particles in the air (i.e., snow crystals), and the final generation of surface grids based on the cleaned individual point returns. The final product includes the ‘xyz’ coordinates of the individual point measurements, and gridded surfaces covering study areas of 100m x 100 m, and at resolutions of 0.01 m, 0.1 m, 0.25 m, 0.5 m and 1 m for each of the survey dates. Additionally, subgrid statistics that include the mean elevation, standard deviation, minimum and maximum elevations, range, and number of point returns in each gridcell are generated. The final product is provided in space-delimited text files, with the surface grids provided in Digital Terrain Model (DTM) format ready for visualization in any GIS software.

How to cite:
Please also cite the original publication when using this data set.: Trujillo, E., K. Leonard, T. Maksym, and M. Lehning (2016), Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice, J. Geophys. Res. Earth Surf., 121, doi:[10.1002/2016JF003893](https://dx.doi.org/10.1002/2016JF003893).

polar

display_name: polar

sea-ice

display_name: sea-ice

sea-ice-elevation

display_name: sea-ice-elevation

terrestrial-laser-scans

display_name: terrestrial-laser-scans

tls

display_name: tls

en: High resolution sea ice surface topography from the SIPEX-2 expedition, East Antarctica, 2012


en: erosion mars sediment-transport model snow

en: Datasets of Figure 3a

en: Datasets of Figure 4b

en: Datasets of Figure 2

en: Datasets of Figure 4a

en: Datasets of Figure 3b

en:
The files contain the datasets used to produce Figures 2, 3, and 4 of the manuscript ([doi: 10.1002/2016GL071822](http://dx.doi.org/10.1002/2016GL071822)).

 Manuscript Abstract:
Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow

en: Energy- and momentum-conserving model of splash entrainment in sand and snow saltation


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

en: Data plot of the field station (SCF)

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

en: Site photo of the field station (SCF)

media_type: JPEG

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

en: Site photo of the forest station (SCB)

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

en: Forest station data (SCB)

en: Data file.

en: Site aerial photo (Schänis)

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

en: Data plot of the forest station (SCB)

en: Further details on the data repository

en: Meta data documentation.

en: Field station data (SCF)

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

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


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

en: Data plot of the forest station (BTB)

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

en: Field station data (BTF)

en: Site aerial photo (Bettlachstock)

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

en: Site photo of the forest station (BTB)

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

en: Data plot of the field station (BTF)

en: Site photo of the field station (BTF)

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

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Bettlachstock in Switzerland where one station is located within a natural mixed forest stand (BTB) with European beech (_Fagus sylvatica_; 170-190 yrs), European silver fir (_Abies alba_; 190 yrs) and Norway spruce (_Picea abies_; 200 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Bettlachstock is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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


aerosol-data-weissfluhjoch

title_for_slug: aerosol-data-weissfluhjoch

en: aerosol linda particles raclets ice-nucleation inp

en: APS Dataset Weissfluhjoch

media_type: application/x-netcdf

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

mimetype: application/x-netcdf

en: SMPS Dataset Weissfluhjoch

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

en: OPC-GT526S Dataset Weissfluhjoch

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

en: OPC-N3 Dataset Weissfluhjoch

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

en: LINDA Dataset Weissfluhjoch

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

en:
Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.

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

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

Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³).

Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

aerosol

display_name: aerosol

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

linda

display_name: linda

particles

display_name: particles

raclets

display_name: raclets

education

en: Education and science

en: Aerosol Data Weissfluhjoch


globale-konjunkturbarometer

maintainer: KOF Datenservice

title_for_slug: globale-konjunkturbarometer

de: Datenbeschreibung

en: Data description

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.

fr: Description des données

economie-mondiale

display_name: economie-mondiale

global-economy

display_name: global-economy

weltwirtschaft

display_name: weltwirtschaft

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

kof-konjunkturforschungsstelle

de: KOF Konjunkturforschungsstelle

en: KOF Swiss Economic Institute

it: KOF Centro di ricerca congiunturale

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

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

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

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

value: KOF Harvester


kof-economic-sentiment-indicator

title_for_slug: kof-economic-sentiment-indicator

fr: KOF Indice du climat économique

de: KOF Economic Sentiment Indicator

en: KOF Economic Sentiment Indicator

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

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

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

climat-economique

display_name: climat-economique

economic-sentiment

display_name: economic-sentiment

okonomische-stimmung

display_name: okonomische-stimmung

kof-konjunkturforschungsstelle

fr: KOF Centre de recherches conjoncturelles


kof-konjunkturbarometer

title_for_slug: kof-konjunkturbarometer

fr: suisse conjoncture

de: vorlaufindikator konjunktur schweiz

en: leading-indicator switzerland business-cycle fli

fr: KOF Baromètre conjoncturel

de: KOF Konjunkturbarometer

en: KOF Economic Barometer

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

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

schweiz

display_name: schweiz

suisse

display_name: suisse

switzerland

display_name: switzerland

vorlaufindikator

display_name: vorlaufindikator


vegetation-height-model-nfi

maintainer: Christian Ginzler

title_for_slug: vegetation-height-model-nfi

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

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

en: 2016 Vegetation Height Model NFI

media_type: geotiff

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

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

format: GeoTIFF

en: Thumbnail

en: 2012 Vegetation Height Model NFI

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

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

en: 2015 Vegetation Height Model NFI

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

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

en: 2019 Vegetation Height Model NFI (current)

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

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

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

Latest version is from 2019.

forest

display_name: forest

photogrammety

display_name: photogrammety

point-cloud

display_name: point-cloud

vegetation-height-model

display_name: vegetation-height-model

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: Vegetation Height Model NFI


data-analysis-toolkits

title_for_slug: data-analysis-toolkits

en: statistics bayesian-inference data-analysis error-propagation uncertainty hypothesis-testing

en: Toolkit 9: Experimentwise error rates and statistical fishing expeditions

en: Statistical fishing expeditions, and how to avoid being misled by them

en: Toolkit 11: serial correlation

en: Tools for detecting and correcting for serial correlation in analyses of time series

en: Toolkit 5: uncertainty analysis and error propagation

en: Gaussian error propagation, monte carlo methods, and first-order, second-moment error propagation

en: Toolkit 1: graphically displaying data distributions

en: Toolkit 2: quantifying data distributions using descriptive statistics

en: Toolkit 4: confidence intervals

en: Toolkit 8: Hodges-Lehmann estimators

en: A quick introduction to Hodges-Lehmann estimators (nonparametric measures of effect size)

en: Toolkit 10: linear regression

en: An overview of the math, logic, and pitfalls of ordinary least-squares linear regression

en: Toolkit 3: tools for transforming data

en: The ladder of powers and a few other cool transformations

en: Toolkit 7: hypothesis testing, significance, and power

en: An overview of basic concepts -- and common pitfalls -- in statistical hypothesis testing, statistical significance, and power analysis

en: toolkit 6: averaging in nonlinear functions

en: The average of a nonlinear function will not equal the function evaluated at its average inputs (the mean of the function will differ from from the function of the mean). This toolkit shows how to estimate that averaging bias.

en: Toolkit 12: weighted averages and their uncertainties

en: There are two different ways to calculate the uncertainty of a weighted average. Software packages often don't tell you which one they are reporting, and the resulting errors can be huge.

en:
These are condensed notes covering selected key points in data analysis and statistics. They were developed by James Kirchner for the course "Analysis of Environmental Data" at Berkeley in the 1990's and 2000's. They are not intended to be comprehensive, and thus are not a substitute for a good textbook or a good education!

License: These notes are released by James Kirchner under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.

bayesian-inference

display_name: bayesian-inference

data-analysis

display_name: data-analysis

error-propagation

display_name: error-propagation

hypothesis-testing

display_name: hypothesis-testing

statistics

display_name: statistics

uncertainty

display_name: uncertainty

education

en: Education and science


kof-business-situation-indicator

title_for_slug: kof-business-situation-indicator

fr: suisse situation-des-affaires

de: geschaftslageindikator schweiz

fr: KOF Indicateur de la situation des affaires

en: KOF Geschäftslageindikator

de: KOF Business Situation Indicator

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.

en: Data description

bussiness-situation

display_name: bussiness-situation

economics

display_name: economics

geschaftslageindikator

display_name: geschaftslageindikator

situation-des-affaires

display_name: situation-des-affaires

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.


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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en: Bulk Data Access

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

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

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

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

- The Agisoft Photoscan automatic processing report

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

en:
 UAV-derived DSMs and orthoimages

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

 UAV surveys:

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

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

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

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

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

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

where:

- *glacier* is the name of the surveyed glacier

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

- *photoscan* is the name of the photogrammetric software

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

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

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

- *.tif* is the extention of the dataset

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

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

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

alps

display_name: alps

dem

display_name: dem

drone

display_name: drone

dsm

display_name: dsm

findelengletscher

display_name: findelengletscher

glacier

display_name: glacier

gletscher

display_name: gletscher

griesgletscher

display_name: griesgletscher

orthoimage

display_name: orthoimage

orthophoto

display_name: orthophoto

sankt-annafirn

display_name: sankt-annafirn

uav

display_name: uav

education

fr: Education, science

de: Bildung, Wissenschaft

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


maintainer: OGD-Koordinationsstelle St.Gallen

de: wahlen abstimmungen real-time auszahlungen

de: csv

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

license: CC BY

de: json

media_type: application/json

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

format: JSON

mimetype: application/json

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

abstimmungen

display_name: abstimmungen

auszahlungen

display_name: auszahlungen

real-time

display_name: real-time

wahlen

display_name: wahlen

politics

fr: Politique

de: Politik

en: Politics

it: Politica

staatskanzlei-kanton-st-gallen

de: Staatskanzlei Kanton St.Gallen

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

«Wir verbinden und überzeugen. Ihre Staatskanzlei.»

political_level: canton

value: DCAT Staatskanzlei Kanton St.Gallen


kof-beschaftigungsindikator

title_for_slug: kof-beschaftigungsindikator

fr: emploi marche-de-lemploi

de: arbeitsmarkt beschaftigung

en: employment labour-market

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.

en: Data description

de: Datenbeschreibung

arbeitsmarkt

display_name: arbeitsmarkt

beschaftigung

display_name: beschaftigung

emploi

display_name: emploi

employment

display_name: employment

labour-market

display_name: labour-market

marche-de-lemploi

display_name: marche-de-lemploi

national-economy

de: Volkswirtschaft

en: National economy

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito

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.


de: wahlen resultate abstimmungen

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

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

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

resultate

display_name: resultate


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


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 real-time api abstimmungen wahlen

de: csv

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

de: json

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

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

api

display_name: api

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.»


geography

de: Geographie

de: ÖREB - Kataster der belasteten Standorte (KbS)


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: WMS

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

format: WMS

name:
Amt für Raumentwicklung
               - Geoinformation

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

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

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


de: WMS der Teilobjektperimeter Lichte Wälder gemäss Aktionsplan

name:
Amt für Landschaft und Natur
               - Fachstelle Naturschutz

de: WMS der Objekte Lichte Wälder


de: Fischereireviere

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

de: WMS Fischereireviere (OGD)


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).

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

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.

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

de: WMS Immissionen (Luftqualität)


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

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


wms-offentliche-oberflachengewasser

title_for_slug: wms-offentliche-oberflachengewasser

de: Öffentliche Oberflächengewässer, Gewässerraum, Wasserrechte

de: WMS Öffentliche Oberflächengewässer


de: Hauptstrassen nach Durchgangs- und Siganlisationsverordnung

name:
Tiefbauamt
               - Stab

de: WMS Strassennetz: Haupt- und Nebenstrassen


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.

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

de: WMS Haltestellen des öffentlichen Verkehrs


de: Vegetationskundliche Kartierung der Wälder im Kanton Zürich

name:
Amt für Landschaft und Natur
               - Abteilung Wald

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 Vegetationskundliche Kartierung der Wälder


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: WFS Wärmenutzungsatlas


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

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


wfs-naturgefahrenkarte

title_for_slug: wfs-naturgefahrenkarte

de: WFS Naturgefahrenkarte


de: WMS Orthofotos Kanton Zürich in Echtfarben und als Falschfarbeninfrarot

de: WMS Orthofotos


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

de: WFS Beleuchtung


de: Naturgefahrenkarte - Wassertiefenkarten - Intensitätsflächen

de: WMS Naturgefahrenkarte - Intensitätsflächen


wms-klimamodell-zh-analysekarten-vektor

title_for_slug: wms-klimamodell-zh-analysekarten-vektor

de: Klimaanalysekarten aus der Anwendung des Klimamodells FITNAH für das Gebiet des Kantons ZH. Punktdaten des Windfeldes (Windrichtung und -geschwindigkeit) über den ganzen Kanton. Räumliche Genauigkeit: 25m.

de: WMS Klimamodell ZH: Analysekarten (Vektor)


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

geoinformation-kanton-zuerich

de: Geoinformation Kanton Zürich

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


de: Gebiete in Objekten von überkommunaler Bedeutung oder Kant. Fördergebieten vor den ökologischen Ausgleich in denen der Kanton Zürich Zusatzbeiträge leistet.

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 kantonalen Fördergebiete für den ökologischen Ausgleich


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

de: WFS Gewässer-Ökomorphologie


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

name:
Amt für Mobilität
               - Mobilitätsentwicklung und -steuerung

de: WFS Tempo30- und Begegnungszonen


de: Risikokarte Naturgefahren mit den Teilen Hochwasser und Massenbewegungen (mit Hangmuren, permanente und spontane Rutschungen und Steinschlag).

de: WMS Risikokarte Naturgefahren


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

de: WMS Lebensraum- und Vegetationskartierungen


de: WMS Naturgefahrenkarte - Intensitätskarten Massenbewegungen


wfs-grundwasserkarte-mittelwasserstand

title_for_slug: wfs-grundwasserkarte-mittelwasserstand

de: Grundwasserkarte Mittelwasserstand

de: WFS Grundwasserkarte Mittelwasserstand