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

en: QCA data set large-scale urban development projects

media_type: TXT

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

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

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

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

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

1. General context of the data set "lsUDPs"
The data set "lsUDPs" has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2020. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, strategic spatial plans) into quantitative land-change modelling approaches at the urban regional level. The first stage (2016-2017) of the CONCUR project focussed on 21 urban regions in Western Europe. The urban regions were selected through a multi-stage strategy for empirical research (see Hersperger, A. M., Grădinaru, S., Oliveira, E., Pagliarin, S., & Palka, G. (2019). Understanding strategic spatial planning to effectively guide development of urban regions. Cities, 94, 96–105. https://doi.org/10.1016/j.cities.2019.05.032 ).

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

3. The data set lsUDPs

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

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

europe

display_name: europe

land-use-change

display_name: land-use-change

land-use-transformations

display_name: land-use-transformations

large-scale-urban-development-projects

display_name: large-scale-urban-development-projects

spatial-planning

display_name: spatial-planning

strategic-projects

display_name: strategic-projects

strategic-spatial-planning

display_name: strategic-spatial-planning

urban-transformations

display_name: urban-transformations

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


automatic-classification-of-avalanches

maintainer: Alec van Herwijnen

title_for_slug: automatic-classification-of-avalanches

en: localization machine-learning monitoring avalanche seismic

state: active

type: dataset

media_type: application/x-tar

en:
This tar file contains classification results for two seismic geophone arrays deployed above Davos, Switzerland. The of the first array located at the Dischma Valley was used to automatically identify all seismic events produced by avalanches, whereas the classification perfomed at the second array located at the Wannengrat field site was used to identify airplanes and earthquakes.
Furthermore, this tar file also contains the median back-azimuth of all classified events at the Dischma field site.

format: SERVICE

mimetype: application/x-tar

en: This dataset contains the classification and localization results obtained during the automatic classification of avalanches during the winter season 2017.

avalanche

display_name: avalanche

localization

display_name: localization

machine-learning

display_name: machine-learning

monitoring

display_name: monitoring

seismic

display_name: seismic

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: Automatic Classification of Avalanches


data-broedlin-cnp

maintainer: EnviDat Support

title_for_slug: data-broedlin-cnp

en: carbon phosphorus nitrogen forest stoichiometry dissolved-organic-matter drying-rewetting soil mineralization

en: Data Broedlin-CNP-Release

en: Raw data of C-N-P mobilization experiment from Oi, Oe/Oa, and A horizons of beech forest soils along a nutrient availability gradient.

format: XLS

en: Data Broedlin-CNP

en: Mircocosm experiment to identify the individual patterns and controls of C, N, and P mobilization in soils under beech forests. Organic and mineral horizons sampled along a nutrient availability gradient in Germany were exposed to either permanent moist conditions or to dry spells in microcosms and quantified the release of inorganic and organic C, N, and P.

carbon

display_name: carbon

dissolved-organic-matter

display_name: dissolved-organic-matter

drying-rewetting

display_name: drying-rewetting

forest

display_name: forest

mineralization

display_name: mineralization

nitrogen

display_name: nitrogen

phosphorus

display_name: phosphorus

soil

display_name: soil

stoichiometry

display_name: stoichiometry

en: Data Broedlin CNP


en: snow-ice-temperature snow-water-equivalent weisfluhjoch snow-stratigraphy snow-density

en: README

en: README file giving use metadata.

format: TXT

en: WFJ Snow Profiles 1999-2014

media_type: application/zip

en:
Biweekly manual snow profiles from Weissfluhjoch, Davos, Switzerland.
Version: 2015-09-14T16:25

format: ZIP

mimetype: application/zip

en: Dataset of manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland. Typical snow profile measurements and observations are included (temperature, density, grain size, grain type, hardness, wetness), following the guidelines of the The International Classification for Seasonal Snow on the Ground (ICSSG) [Fierz, C., Armstrong, R.L., Durand, Y., Etchevers, P., Greene, E., McClung, D.M., Nishimura, K., Satyawali, P.K. and Sokratov, S.A. 2009. The International Classification for Seasonal Snow on the Ground. IHP-VII Technical Documents in Hydrology N°83, IACS Contribution N°1, UNESCO-IHP, Paris].

snow-density

display_name: snow-density

snow-ice-temperature

display_name: snow-ice-temperature

snow-stratigraphy

display_name: snow-stratigraphy

snow-water-equivalent

display_name: snow-water-equivalent

weisfluhjoch

display_name: weisfluhjoch

en: Manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland


snow-drift-station-flowcapt

maintainer: Benjamin Walter

title_for_slug: snow-drift-station-flowcapt

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

en: minimum wind spees

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

en: maximum wind speed

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

en: maximum mass flux

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

en: minimum mass flux

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

en: avergaged mass flux

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

en: average wind speed

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

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

acoustic-mass-flux

display_name: acoustic-mass-flux

flowcapt

display_name: flowcapt

raclets

display_name: raclets

snow-blowing

display_name: snow-blowing

snowdrift

display_name: snowdrift

wind-speed

display_name: wind-speed

education

en: Education and science

en: Snow Drift Station - Flowcapt


dischmex-meteorological-measurements

maintainer: Rebecca Mott

title_for_slug: dischmex-meteorological-measurements

en: meteorological-measurements meteo-station dischmex meteorological-data dischma

en: Meteorological measurements 2014

media_type: application/pdf

en: Location of the meteorological stations

format: PDF

mimetype: application/pdf

en: Meteorological measurement 2014

en: data

en: Overview sensors

en: Meteorological measurements 2016

en: Meteorological measurement 2015

en:
Meteorological measurements recorded in the Dischma valley from 2014-2016. In 2014 and 2015 we used 11 mobile weather stations from sensorscope to record meteorological parameter in the upper Dischma valley in the closer surroundings of the Gletschboden area. The meteorological stations are eqiupped with at least air temperature/humidity, wind velocity and wind direction sensors. Some stations are additionally equipped with precipitation, shortwave radiation and snow surface temperature sensors.
Three transects were installed at different aspects and were equipped with air temperature/humidity and wind sensors. Transect 1 (stations 2-4) provides meteorological Information on an east-north-east facing slope at elevations ranging between 2100 m and 2500 m. Transect 2 (stations 5-7) provides meteorological Information on a south-west slope and transect 3 (stations 8-10) on a north-west slope. Station 1 is fully equipped with meteorological sensors (temperature/humidity, wind, IR, up and downwand shortwave radiation and precipitation).
In 2016, mobile stations from sensorscope were replaced with six permanent meteorological stations. Meteorological stations 1-3 are equipped with an air temperature/humidity sensor, two wind speed sensors, a wind direction sensor and an incoming and outgoing shortwave radiation sensor. Stations 4 and 6 are equipped with an air temperature/humidity sensor and a wind speed/direction sensor. Station 5 is a equipped with an air temperature/humidity sensor, a wind speed/direction sensor, a snow surface temperature sensor, an incoming and outgoing shortwave radiation sensor and an incoming longwave radiation sensor.

dischma

display_name: dischma

dischmex

display_name: dischmex

meteo-station

display_name: meteo-station

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

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: DISCHMEX - Meteorological measurements


maintainer: Elisabeth Hafner

en: avalanche-hazard-mapping snow validation avalanche satellite

en: Satellite Avalanche Mapping Validation data and data description

media_type: ZIP

en: 14 shapefiles to be used only together with the data description also provided as a pdf.

en:
Validation points, validation area, ground truth coverage, SPOT 6 avalanche outlines, Sentinel-1 avalanche outlines, Sentinel-2 avalanche outlines, Davos avalanche mapping (DAvalMap) avalanche outlines as shapefiles and a detailed attribute description (DataDescription_EvalSatMappingMethods.pdf).

Coordinate system: CH1903+_LV95

The generation of this dataset is described in detail in:

Hafner, E. D., Techel, F., Leinss, S., and Bühler, Y.: Mapping avalanches with satellites – evaluation of performance and completeness, The Cryosphere, https://doi.org/10.5194/tc-2020-272, 2021.

avalanche

display_name: avalanche

avalanche-hazard-mapping

display_name: avalanche-hazard-mapping

satellite

display_name: satellite

snow

display_name: snow

validation

display_name: validation

en: Satellite avalanche mapping validation data


maintainer: Jana von Freyberg

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

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

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

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

media_type: CSV

format: CSV

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

ecohydrology

display_name: ecohydrology

endmember-mixing-models

display_name: endmember-mixing-models

plant-water-uptake

display_name: plant-water-uptake

review

display_name: review

root-zone

display_name: root-zone

stable-water-isotopes

display_name: stable-water-isotopes

uncertainties

display_name: uncertainties

education

en: Education and science

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


en: snow-profile snow-water-equivalent snow snow-height gcos

en: DATA ACCESS

en: STATION METADATA

media_type: text/plain

mimetype: text/plain

en: Snowprofile from 11 observer sites in Switzerland compiled for the Global Climate Observing System (GCOS). Height of snow (cm) and snow water equivalent (mm) are recorded every 2 weeks since the 1947 (depending on station). Attached metadata file gives details of each station.

gcos

display_name: gcos

snow-height

display_name: snow-height

snow-profile

display_name: snow-profile

snow-water-equivalent

display_name: snow-water-equivalent

en: GCOS SWE data from 11 stations in Switzerland


en: weissfluhjoch outgoing incoming longwave-radiation shortwave-radiation

en: Metadata

en: Processing doc

en: Parameter file

en:
Corrected incoming and outgoing shortwave and longwave 2 min radiation measurements at the Weissfluhjoch summit, Davos, CH.

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

incoming

display_name: incoming

longwave-radiation

display_name: longwave-radiation

outgoing

display_name: outgoing

shortwave-radiation

display_name: shortwave-radiation

weissfluhjoch

display_name: weissfluhjoch

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: ASRB_WFJ: Shortwave and longwave radiation measurements (2 min) at the Weissfluhjoch research site, Davos


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

en: Manual snow measurements Alptal (1968-2020)

media_type: XLSX

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

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

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

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

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

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

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

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

alptal

display_name: alptal

first-order-catchment

display_name: first-order-catchment

meteorological-data

display_name: meteorological-data

runoff

display_name: runoff

snow

display_name: snow

subalpine

display_name: subalpine

en: Longterm hydrological observatory Alptal (central Switzerland)


maintainer: M. Carol Resch

en: diversity nematodes vegetation long-term-experiment grassland restoration topsoil-removal

en: Plant community composition (plant species)

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

column 3-252: Plant abundance per species (in total 252 plant species) expressed as cover percentage estimation according to van der Maarel (vdM 1979; 7 classes: 1-7); nomenclature according to Lauber & Wagner (1996)

en: Nematode families

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

column 3-41: Nematode abundance (individuals per 100g dry soil) per family; nomenclature according to Bongers 1988

en: Nemadotes and vegetation

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

X: X-Coordinate

Y: Y-Coordinate

Ri.veg: Total number of plant species

Div.veg: Shannon diversity of plant species

Ri.nem: Total number of nematode families

Div.nem: Shannon diversity of nematode families

abund: Total nematode abundance (individuals per 100g dry soil)

MI: Maturity index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

PPI: Plant parasite index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

PPI.MI: Plant parasite to Maturity index according to Bongers, van der Meulen, & Korthals 1997; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

CI: Channel index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

EI: Enrichment index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

SI: Structure index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

He.a: Herbivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.ecto.a: Herbivorous ectoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.endo.a: Herbivorous endoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ba.a: Bacterivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Fu.a: Fungivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.a: Omnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ca.a: Carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.Ca.a	Sum of omnivorous and carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014
CP1.a: C-P (colonizer-persister) class 1 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to enrichment indicators according to Ferris, Bongers, & de Goede 2001

CP2.a: C-P (colonizer-persister) class 2 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to stress indicators according to Ferris, Bongers, & de Goede 2001

CP3.a: C-P (colonizer-persister) class 3 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP4.a: C-P (colonizer-persister) class 4 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP5.a: C-P (colonizer-persister) class 5 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP3-5.a: Sum of C-P3, C-P4 and C-P5 nematode abundance (individuals per 100g dry soil) equivalent to structure indicators according to Ferris, Bongers, & de Goede 2001

protect.sp.pro: plant species categorized into species of concern based on their red list status in Switzerland as well as their protection status in Switzerland and the Canton Zurich (Moser, Gygax, Bäumler, Wyler, & Palese, 2002)

tar.sp: Number of target species (all species recorded in the eleven target plots plus propagules of species applied by hand, resulting in a total of 143 species)

Indi.moist: Plant indicator values for soil moisture according to Landolt et al. 2010

Indi.nutri: Plant indicator values for soil nutrients according to Landolt et al. 2010

Management: level of mowing and manuring frequency (35-40 kg N ha-1 application-1); intensity1 = mowing once and no manure; intensity2 = 2-3 times mowing and no manure; intensity3 = 2-3 times mowing and manuring; intensity4 = 4-5 times mowing and manuring

Tillage: last time of tillage

Land.use.history: for Initial plots = recent agricultural use; for all restored sites = agricultural use before restoration
Mowing	earliest date of biomass harvesting (excluding “Initial”) based on contracts between farmers and the Nature Protection Agency of Zurich

Soil.type: based on soil mapping survey 1991 (before restoration)

Soil.texture: determined by the sediment method (Gee & Bauder 1986) and classified into soil textural classes according to FAO (1990)

pH: soil pH (CaCl2)

Slope: slope gradient classes according to FAO (1990; %)

en: Nematode feeding types

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

He.ecto.a: Herbivorous ectoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.endo.a: Herbivorous endoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ba.a: Bacterivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Fu.a: Fungivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.a: Omnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ca.a: Carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

en: Nematode colonizer-persister classes

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

CP1.a: C-P (colonizer-persister) class 1 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to enrichment indicators according to Ferris, Bongers, & de Goede 2001
CP2.a: C-P (colonizer-persister) class 2 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to stress indicators according to Ferris, Bongers, & de Goede 2001
CP3.a: C-P (colonizer-persister) class 3 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990
CP4.a: C-P (colonizer-persister) class 4 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990
CP5.a: C-P (colonizer-persister) class 5 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

en: Coordinates of one research plot were wrong. This was corrected in the current version of the file.

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

Paper Citation:
 > Resch, M.C., Schütz, M., Graf, U., Wagenaar, R., van der Putten, W.H., Risch, A.C. 2019. Does topsoil removal in grassland restoration benefit both soil nematode and plant communities? Journal of Applied Ecology 56: 1782-1793.

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

 Methods
 Study area and experimental settings
The study was conducted in a nature reserve (Eigental: 47° 27’ to 47° 29’ N, 8° 37’ E, 461 to 507 m a.s.l.) that is located on the Swiss Central plateau close to Zurich airport (Canton Zurich, Switzerland). The mean annual temperature in this area ranges from 8.9 to 10.6 °C, mean annual precipitation from 910 to 1260 mm [10-year average (2007-2017); MeteoSchweiz, 2018]. The main soil types are calcaric to gleyic Cambisol and Gleysols. The reserve was established in 1967 to protect small remnants of oligotrophic semi-natural grasslands (roughly 12 ha). The plant community can be characterized as Molinion and Mesobromion (semi-wet to semi-dry), depending on the site-specific groundwater level and slope inclination (Delarze, Gonseth, Eggenberg, & Vust, 2015). These remnants represent species-rich islands in an otherwise intensively managed agricultural landscape. Semi-natural grasslands covered an area of 60,000 ha in the Canton Zurich in 1939, however, by 2005 only roughly 600 ha remained (Baudirektion Kanton Zürich, 2007). In 1990, the government of Canton Zurich decided to enlarge the nature reserve Eigental. The goal was to incorporate eleven patches of 20 ha adjacent intensively farmed land and transform these patches into semi-natural grasslands. The patches had a different agricultural history, ranging from permanent (no tillage for >50 years) to temporary grassland (as part of crop rotation; last tillage <5 years). On all freshly integrated patches fertilization was stopped in 1992 and from then on biomass was harvested three times a year and removed. After 5 years without noticeable effects on vegetation composition, the Nature Conservation Agency of Canton Zurich decided to increase the restoration efforts. In 1995, a large-scale experiment was initialized to evaluate if certain treatments can facilitate restoration within a reasonable timeframe of 5 to 10 years after treatment implementation.
The three restoration treatments used were:
i. “Harvest only”: Plots are being mowed two to three times a year and the biomass is removed.
ii. “Topsoil”: Topsoil was removed to a depth of 10 to 20 cm, depending on the depth of the O and A horizon, in four randomly selected areas within each of the eleven patches in late autumn 1995. The size of each topsoil removal area depended on individual patch size and was between 2700 and 7000 m2.
iii. “Topsoil+Propagules”: Propagules from target vegetation were added on half of the area where topsoil was removed, using fresh, seed-containing hay originating from a mixture of semi-dry to semi-wet species-rich grasslands of local provenance (within a radius of 7 km). Hay applications were conducted twice in 1995 and 1996. Repeated applications were chosen to account for the low quantity of available plant material per transfer, since area ratio between receptor and donor sites was roughly 1:1. In addition, hand-collected propagules from 15 selected target species of regional provenance (within a radius of 30 km) were equally applied in 1996 and 1997.
“Topsoil” and “Topsoil+Propagules” plots are mowed once a year, and the biomass is removed. Mowing on these plots started five years after the treatment was implemented.
Eleven permanent plots of 5 m x 5 m were randomly established in each treatment to monitor the vegetation development. The experiment was complemented with 11 control plots that represent the initial state of intensively managed grasslands, further referred to as “Initial”, and 11 control plots that represent the targeted state of donor sites for “Topsoil+Propagules”, further referred to as “Target”. Consequently, the experiment consists of 55 plots (5 treatments x 11 replicates). Management of intensively used grasslands includes mowing and fertilizing (manure) between two to five times a year, as well as different tillage regimes (no tillage for >50 years; last time of tillage <5 years).

 Nematode and plant sampling
Soil nematodes were sampled in 2 m x 2 m plots, randomly established at least 2 m away from the vegetation plots. We collected eight soil cores with a 2.2 cm diameter soil core sampler (Giddings Machine Company, Windsor, CO, USA) to a depth of 12 cm (representing the majority of the plant rooting system) in each plot at the beginning of July 2017. The eight cores within each replicate plot were combined, gently homogenized, placed in coolers and transported to the laboratory of NIOO in Wageningen, the Netherlands, within one week. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriator (Oostenbrink, 1960) and concentrated, resulting in 6 mL nematode solution. The nematode solution was subdivided into three subsamples, two for morphological identification and quantification, and one for molecular work (not used in this study). For morphological identification and quantification, nematodes were heat-killed at 90 °C and fixed in 4 % formaldehyde solution (final volume 10 mL per subsample). All nematodes in 1 mL of formaldehyde solution were counted, and a minimum of 150 individuals per 1 mL sample (or all if less nematodes were present) were identified to family level using Bongers (1988). We then extrapolated the numbers of each nematode taxa identified to the entire sample and expressed them per 100 g dry soil for further analyses.
We calculated number of nematode taxa and Shannon diversity and assessed nematode community composition. In addition, we classified the nematode taxa into feeding types (herbivores, bacterivores, fungivores, omni-carnivores), structural and functional guilds (Table S4). Structural guilds assign nematode taxa according to life-history traits into five colonizer-persister (C-P) classes, ranging from one (early colonizers of new resources) to five (persisters in undisturbed habitats; Bongers 1990). C-P classes can be categorized as indicators for nutrient-enriched (C-P1), stressed (C-P2) and structured (C-P3 + C-P4 + C-P5) soil conditions (Ferris, Bongers, & de Goede, 2001). Functional guilds assign nematode taxa according to their C-P classification combined with their feeding habits (Ferris, Bongers, & de Goede, 2001). Based on the structural and functional guild classification we calculated five additional indices to assess soil nutrient status, disturbance and food web characteristics using NINJA (Sieriebriennikov, Ferris, & de Goede, 2014). 1) The Maturity index indicates the degree of different environmental perturbations (e.g., tillage, nutrient enrichment, pollution) and is used to monitor colonization and subsequent succession after disturbances (Bongers, 1990). 2) The ratio between the Plant Parasite (C-P of herbivorous nematodes only) to Maturity index is used to monitor the recovery of disturbed habitats incorporating information of life-history traits for all feeding types (Bongers, van der Meulen, & Korthals, 1997). 3) The Enrichment index indicates nutrient-enriched soils and agricultural management practices (Ferris, Bongers, & de Goede, 2001). 4) The Structure index provides information about the succession stage of the soil food web and therefore correlates with the degree of maturity of an ecosystem (Ferris, Bongers, & de Goede, 2001). 5) The Channel index provides information about the predominant decomposition pathways, where higher values stand for a higher proportion of energy transformed through the slow fungal decomposition channel (Ferris, Bongers, & de Goede, 2001). In addition, the Structure and Enrichment indices can be displayed in a biplot where nematode assemblages are plotted along a structure (x-axis) and enrichment (y-axis) trajectory (increasing index values). Each biplot quadrat reflects different levels of disturbance, soil nutrient pools and decomposition pathways (Ferris, Bongers, & de Goede, 2001).
The plant surveys were conducted on the 25 m2 permanent plots in June 2017. Plant species cover was visually assessed according to the semi-quantitative cover-abundance scale of Braun-Blanquet (1964; nomenclature: Lauber & Wagner, 1996). We calculated number of species and Shannon diversity, and assessed plant community composition. We also counted the number of target species (all species recorded in the eleven target plots plus propagules of species applied by hand, resulting in a total of 143 species) and categorized plant species into species of concern based on their red list status in Switzerland as well as their protection status in Switzerland and the Canton Zurich (Moser, Gygax, Bäumler, Wyler, & Palese, 2002). Furthermore, we calculated indicator values for soil moisture and soil nutrients for each species according to Landolt et al. (2010).

 References
Baudirektion Kanton Zürich (2007). 10 Jahre Naturschutz-Gesamtkonzept für den Kanton Zürich 1995-2005 – Stand der Umsetzung. Zürich: Baudirektion Kanton Zürich.
Bongers, T. (1988). De nematoden van Nederland. Utrecht: Stichting Uitgeverij Koninklijke Nederlandse Natuurhistorische Vereniging.
Bongers, T. (1990). The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologia, 83, 14-19. doi:10.1007/BF00324627
Bongers, T., van der Meulen, H., & Korthals, G. (1997). Inverse relationship between the nematode maturity index and plant parasite index under enriched nutrient conditions. Applied Soil Ecology, 6, 195-199. doi:10.1016/S0929-1393(96)00136-9
Braun-Blanquet, J. (1964). Pflanzensoziologie, Grundzüge der Vegetationskunde (3rd ed.). Wien: Springer.
Delarze, R., Gonseth, Y., Eggenberg, S., & Vust, M. (2015). Lebensräume der Schweiz: Ökologie - Gefährdung - Kennarten (3rd ed.). Bern: Ott.
Ferris, H., Bongers, T., & de Goede, R.G.M. (2001). A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Applied Soil Ecology, 18, 13-29. doi:10.1016/S0929-1393(01)00152-4
Landolt, E., Bäumler, B., Erhardt, A., Hegg, O., Klötzli, F., Lämmler, W., … Wohlgemuth, T. (2010). Flora indicativa. Ecological indicator values and biological attributes of the Flora of Switzerland and the Alps (2nd ed.). Bern: Haupt.
Lauber, K., & Wagner, G. (1996). Flora Helvetica. Flora der Schweiz. Bern: Haupt.
MeteoSchweiz (2018). Klimabulletin Jahr 2017, Zürich: MeteoSchweiz.
Moser, D., Gygax, A., Bäumler, B., Wyler, N., & Palese, R. (2002) Rote Liste der gefährteten Farn- und Blütenpflanzen der Schweiz. Bern: BUWAL.
Oostenbrink, M. (1960). Estimating nematode populations by some selected methods. In N.J. Sasser & W.R. Jenkins (Eds.), Nematology (pp. 85-101). Chapel Hill: University of North Carolina Press.
Sieriebriennikov, B., Ferris, H., & de Goede, R.G.M (2014). NINJA: An automated calculation system for nematode-based biological monitoring. European Journal of Soil Biology, 61, 90-93. doi:10.1016/j.ejsobi.2014.02.004

diversity

display_name: diversity

grassland

display_name: grassland

long-term-experiment

display_name: long-term-experiment

nematodes

display_name: nematodes

restoration

display_name: restoration

topsoil-removal

display_name: topsoil-removal

vegetation

display_name: vegetation

education

en: Education and science

en: Grassland restoration: nematodes and plant communities


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

en: Data processing documentation

media_type: DOC

en: Post Processed TLS's

en: Compressed dat files

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

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

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


maintainer: Sofia Pagliarin

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

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: Information on data sources

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

en: Soil sealing Barcelona and Milan different territorial levels


globale-konjunkturbarometer

maintainer: KOF Datenservice

title_for_slug: globale-konjunkturbarometer

fr: Baromètres conjoncturels mondiaux

de: Globale Konjunkturbarometer

en: Global Economic Barometers

media_type: text/csv

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.

mimetype: text/csv

fr: Description des données

en: Data description

de: Datenbeschreibung

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.

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

de: 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.

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: conjoncture suisse

de: schweiz konjunktur vorlaufindikator

en: switzerland fli leading-indicator business-cycle

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.

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.

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.

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


kof-beschaftigungsindikator

title_for_slug: kof-beschaftigungsindikator

fr: emploi marche-de-lemploi

de: beschaftigung arbeitsmarkt

en: labour-market employment

fr: KOF Indicateur de l'emploi

en: KOF Employment Indicator

de: KOF Beschäftigungsindikator

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

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: 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.

arbeitsmarkt

display_name: arbeitsmarkt

beschaftigung

display_name: beschaftigung

emploi

display_name: emploi

employment

display_name: employment

labour-market

display_name: labour-market

marche-de-lemploi

display_name: marche-de-lemploi

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito


warmeversorungskarte-gemeinde-koniz

culture

fr: Culture, médias, société de l'information, sport

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

it: Cultura, media, società dell'informazione, sport

energy

fr: Energie

de: Energie

en: Energy

it: Energia

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

title_for_slug: warmeversorungskarte-gemeinde-koniz

label: geocat.ch permalink

spatial: Köniz

de: DWG

de: Download der Daten als DWG

de: SHP

de: Download der Daten als Shapefile

de: Die Wärmeversorgungskarte zeigt für jede Liegenschaft auf, welcher erneuerbare Energieträger bei einem Heizungsersatz oder einer neuen Heizung eingesetzt werden kann. Berücksichtigt werden dabei diverse Themen wie z.B. vorhandene Wärmeverbünde, die Nutzbarkeit des Grundwassers oder geplante neue Wärmeverbünde. Die Priorisierung eines Energieträgers erfolgt nach der Prioritätenordnung der Kantonalen Energieversordnung (KEnV). Die Karte wird laufend mit den neuesten Erkenntnissen ergänzt. Dazu gehören neben aktuellen Wärmeverbundprojekten oder Grundwasserstudien auch die Resultate der sogenannten «Wärmeversorgungsplanungen». Sie zeigen den Weg zu einer CO2-freien Wärmeversorgung in den dichten Siedlungsgebieten Niederwangen, Köniz-Liebefeld und Wabern auf. Es werden nur beheizte Gebäude innerhalb der Bauzone berücksichtigt.

name: Gemeinde Köniz, Fachstelle Umwelt und Energie

dienstzweig-geomatik-gemeinde-koeniz

fr: Section de la géomatique Commune de Köniz

de: Dienstzweig Geomatik Gemeinde Köniz

en: Dienstzweig Geomatik Gemeinde Köniz

it: Ufficio della geomatica Comune di Köniz

de: Der Dienstzweig Geomatik ist in Zusammenarbeit mit den Fachabteilungen für die Bewirtschaftung und Publikation der Geodaten sowie in Zusammenarbeit mit dem Informatikdienst für die GIS-Infrastruktur der Gemeinde Köniz zuständig. Hinzu kommen Aufgaben im Bereich Leitungskataster und die Integration der Daten der amtlichen Vermessung ins GIS der Gemeinde. Die Geodaten der Gemeinde Köniz welche den Prinzipien der Open Government Data Strategie entsprechen, werden vom Dienstzweig Geomatik Schritt für Schritt auf opendata.swiss zur Verfügung gestellt.

political_level: commune

value: Dienstzweig Geomatik Gemeinde Köniz – Geocat Harvester

de: Wärmeversorgungskarte Gemeinde Köniz


label: Geometadaten Kanton Zürich: GeoLion

media_type: WCS

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

format: WCS

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

geoinformation-kanton-zuerich

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.

political_level: canton

value: ZH - Geocat Harvester

de: WCS Immissionen (Luftqualität)


health

fr: Santé

de: Gesundheit

en: Health

it: Sanità

label: Link zum Geoportal

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


culture

de: Kultur, Medien, Informationsgesellschaft, Sport

energy

de: Energie

geography

de: Geographie

territory

de: Raum und Umwelt

fr: alimentation-en-eau eau-potable

de: wasserversorgung trinkwasser

en: water-supply drinking-water

author: Gemeinde Köniz, Dienstzweig Wasserversorgung

de: Shapefile

de: Download der Daten als Shapefile

de: DWG

de: Download der Daten als DWG

de: Der Layer «Trinkwasserqualität Wasserversorgung Köniz-Oberbalm» ist Teil der PubliMap der Gemeinde Köniz unter map.koeniz.ch. Über einen Klick auf die Gebäudefläche gelangen die Nutzenden in ein Popup-Fenster. Neben allgemeinen Informationen sehen die Nutzenden welchem der 6 Versorgungsbereiche (5 Köniz plus 1 Oberbalm) die Liegenschaft angehört. Sie gelangen via Web-Link auf die Webseite der Gemeinde Köniz, auf welcher u.a. die Trinkwasserqualitätswerte Wasserhärte, Nitratgehalt, Calciumgehalt publiziert werden. Die Nachführung der Daten erfolgt laufend.

de: Trinkwasserqualität Wasserversorgung Köniz Oberbalm


maintainer: OGD-Koordinationsstelle St.Gallen

de: wahlen abstimmungen resultate

de: csv

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

license: CC BY

de: json

media_type: application/json

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

format: JSON

mimetype: application/json

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

abstimmungen

display_name: abstimmungen

resultate

display_name: resultate

wahlen

display_name: wahlen

politics

fr: Politique

de: Politik

en: Politics

it: Politica

staatskanzlei-kanton-st-gallen

de: Staatskanzlei Kanton St.Gallen

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

«Wir verbinden und überzeugen. Ihre Staatskanzlei.»

value: DCAT Staatskanzlei Kanton St.Gallen


kof-business-situation-indicator

title_for_slug: kof-business-situation-indicator

fr: situation-des-affaires suisse

de: schweiz geschaftslageindikator

en: Data description

fr: Description des données

de: Datenbeschreibung

fr: KOF Indicateur de la situation des affaires

de: KOF Business Situation Indicator

en: KOF Geschäftslageindikator

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

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

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

bussiness-situation

display_name: bussiness-situation

economics

display_name: economics

geschaftslageindikator

display_name: geschaftslageindikator

situation-des-affaires

display_name: situation-des-affaires

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

kof-konjunkturforschungsstelle

fr: KOF Centre de recherches conjoncturelles

de: KOF Konjunkturforschungsstelle

en: KOF Swiss Economic Institute

it: KOF Centro di ricerca congiunturale

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

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

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

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


de: wahlen real-time auszahlungen abstimmungen

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

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

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

auszahlungen

display_name: auszahlungen

real-time

display_name: real-time


de: real-time wahlen abstimmungen api resultate

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


de: Web Coverage Service (WCS) Modellierte Potenziale für naturnahe Lebensräume

name:
Amt für Landschaft und Natur
               - Fachstelle Naturschutz

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

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.

de: WCS Modellierte Potenziale für naturnahe Lebensräume (OGD)


media_type: WFS

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

format: WFS

name:
Amt für Raumentwicklung
               - Geoinformation

de: WFS Vektor-Übersichtsplan


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 AVWFS (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: WFS Amtliche Vermessung (AVWFS)


de: Allgemeiner WFS für Open-Government-Data des Kantons Zürich (OGD ZH WFS)


de: Strassennetzdatensatz des kantonalen Tiefbauamtes. Der WFS besteht aus den Layern Haupt- und Nebenstrassen, Strassenachsen, Kilometrierungspunkten und Routen.

name:
Tiefbauamt
               - Stab

de: WFS Strassennetz


de: Der WCS Vegetationshöhe beschreibt die Höhe der Vegetation (Bäume, Büsche, etc.) im Kanton Zürich. Symbology: Stretched, 3-50, Color Ramp, Apply Gamma Stretch 3-50

name:
Amt für Landschaft und Natur
               - Abteilung Wald

de: WCS Vegetationshöhe