maintainer: Sofia Pagliarin

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

en: Information on data sources

media_type: .csv

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

en:
Dataset description

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

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

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

 Dataset composition

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

_IMD15_BCN_MI_Sources.csv_: Information on data sources

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

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

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

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

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

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

 Further information on the Dataset

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

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

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

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

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

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

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

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

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

barcelona

display_name: barcelona

copernicus

display_name: copernicus

imperviousness

display_name: imperviousness

milan

display_name: milan

soil-sealing

display_name: soil-sealing

urban-atlas

display_name: urban-atlas

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Soil sealing Barcelona and Milan different territorial levels


maintainer: Adam Winstral

en: jim jules-investigation-model snow snow-simulation snow-depth

state: active

type: dataset

media_type: text/plain

en: File/data descriptor

format: TXT

mimetype: text/plain

en: HS and SWE observations

media_type: application/zip

en: Automated (HS) and manual (SWE) data used to evaluate model simulations

format: ZIP

mimetype: application/zip

en: DEM

en: 1-km resolution DEM used for downscaling gridded NWP data to stations and for distributing BDE evaluations at HS-stations to SWE-stations

en: Station forcing data

en: All forcing data need to run JIM at HS and SWE stations. These are data downscaled directly from COSMO NWP data (WY14, WY15) and further enhanced by additional station observations of snow depth (HS) and air temperature (Ta) in WY17. Further information can be found in README file. Note that in WY14 and WY15, shortwave radiation was not split into direct and diffuse (not necessary for JIM) and that the default method in JIM for splitting precipitation phase was used. In WY 17, direct and diffuse were combined as input to JIM and JIM was forced with pre-processed liquid and solid precipitation phases.

en: These data were used to drive and evaluate Jules Investigation Model (JIM) snow simulations. The data provided are the forcing data used for the "deterministic" runs as described in Winstral et al., 2019. The bias-detecting ensemble (Winstral et al., 2019) used observed snow depths (HS) to detect biases in these deterministic simulations related to precipitation and energy inputs to JIM. Simulations that included the BDE evaluations substantially improved JIM simulations.

jim

display_name: jim

jules-investigation-model

display_name: jules-investigation-model

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-simulation

display_name: snow-simulation

education

fr: Education, science

de: Bildung, Wissenschaft

it: Formazione e scienza

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

it: EnviDat: il portale dei dati ambientali

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

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: Meteorological data used to develop and validate the bias-detecting ensemble (BDE)


automatic-classification-of-avalanches

maintainer: Alec van Herwijnen

title_for_slug: automatic-classification-of-avalanches

en: machine-learning monitoring seismic avalanche localization

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

en: Automatic Classification of Avalanches


en: gis hydropower integral-water-management decision-making ecosystem-protection

en: Indicators

media_type: text/markdown

en: The indicators capture supporting ecosystem functions.

media_type: SHP

format: SHP

en:
 A spatial dataset and tool to simultaneously assess hydropower potential and ecological potential of the Swiss river network (Version 2016)

 Introduction
The steadily growing demand for energy and the simultaneous pursuit of decarbonisation are increasing interest in the expansion of renewable energies worldwide. In Switzerland, various funding projects have been launched to promote technologies in the field of renewable energies and their application as quickly as possible. With the introduction of a funding instrument in 2009, the number of projects submitted to produce renewable energies increased rapidly. The applications for small hydropower plants (≤ 10 MW) were correspondingly numerous. However, the assessment of the environmental impact and its comparison with hydropower importance is still not standardized.
To provide a basis for decision-making, a methodology was developed to determine the overall hydropower potential of a region. A detailed assessment of each river reach, and the systematic and holistic assessment of small hydropower projects at a regional scale are combined here. The assessment of a river reach is conducted at the river space (i.e., the river and adjacent areas) and at the surrounding landscape level. The HYDROpot_integral methodology was developed as part of Carol Hemund's dissertation (2012) at the University of Bern. It allows the evaluation of river reaches holistically, regarding ecological, social, economic and cultural criteria. As a second part of the overall project, the theoretical hydropower (or hydraulic) potential was calculated for the entire river network, which complemnets the spatial assessment. In particular, it is possible to classify river reaches into those that are more suitable for hydropower production (=”use”) and those that are more suitable for protection.

 Material and method
The HYDROpot_Integral method was developed and tested on the basis of cantonal and national data (Hirschi et al. 2013). The method relies on 73 geodata sets. This holistic assessment is the key element of the entire assessment procedure. Its aim is to quantify the importance of the ecosystem functions in terms of services. The river network (GWN07) is divided into reaches of about 450m and for each reach two study units are defined. The river space (RS) records the ecosystem functions of the water body and the nearby riparian area. The length of the RS is 315 m on average in Switzerland and a maximum of 450 m, whereas the width is based on the FOEN definition (BWG 2001: 18f) and varies between 7-107 m. The surrounding landscape (SLS) is the second survey unit that records the ecosystem functions of the surrounding area over a range of 21 m to 321 m. The SLS is calculated over three times the RS width. The length of the SLS is identical to the length of the RS. The ecosystem functions are divided into three types: regulating (service A), cultural (service B) and provisioning (service C) functions. Accordingly, the assessment of the functions is divided into three parts and three values are assigned to each river reach. The more functions there are and the greater their performance, the higher these values are and the more important the corresponding functions are. Hence, these values quantify the importance of the ecosystem functions and the ecological, cultural and economic ecosystem services of each river reach. The concatenation of ecosystem services results in a value (ABC) that can occur in 125 different versions due to the chosen five-level value scale; i.e. each digit of the three-digit number sequence can be assigned a value between 1 and 5. Each of the 125 combinations, and thus each river reach, has its own characteristics determined by the assessments of the three function types. To record the suitability, the combinations are ranked according to their ecological, cultural and economic ecosystem services. These rules mean that the combination that is most suitable for hydropower production at minimum cost in terms of ecological and cultural ecosystem services and has a high economic potential is ranked first; rank 125 indicates the highest ecological and cultural ecosystem services and the lowest economic services and is therefore most suitable for protection. A river reach that is excluded from hydropower use due to legislation, a so-called priority reach, is given rank 126 from the outset and specially marked. A more detailed description of the methods can be found in Hirschi et al. 2013 [Link]. The dataset presented here presents the latest state of the HYDROpot_integral methodology applied at the national level. Only national data that is easily accessible was used in the preparation of the dataset. The cantonal data, such as renaturation and revitalization, would have to be requested by each canton individually and was excluded here. The nationwide value synthesis was made with R.
A list of data sources can be found here [link to text file]
A list of all parameters can be downloaded here [link to PDF and text files]

 Dataset description
Data is presented as a single shapefile. It contains the river network and all assessment results obtained with HYDROpot_Integral.

 Changes in the methodology compared to the original method (Hirschi et. al 2013)

 * RS_A11 Ecomorphology: recorded for the whole of Switzerland and zero values equated with NA;
individual cantons such as Zug and St. Gallen have no mapped values according to the modular
concept of the federal government, Valais and Graubünden only the main valleys, Ticino and Fribourg not
completely (BAFU 2009).
 * RS_A14 Renaturation and revitalization data: not centrally available at the time of data collection.
centrally available, therefore values in GR were equated with NA.
 * RS_A15 Dilution ratio at wastewater treatment plants (WWTPs) for discharges: Zero values
equal to NA.
 * RS_A20 Water flow: use WASTA (2013) with hydroelectric power plants (> 300 kW) under
Federal control and dams serving hydroelectricity (Dam, as of 2013).
 * RS_C05 Synoptic hazard maps: are cantonally managed at the time of data collection,
Values in GR are marked with a 5 so that the systematics in the decision tree is not affected.
is affected.
 * Water quality (RS_A15, RS_A16, RS_A17, RS_A18, RS_A19): for the evaluation of the function type.
A Nature, it is important whether the median of the five values is less than or equal to 3 in total. This
evaluation is based on the decision tree for evaluating GR (Hirschi et al. 2013:22).
Therefore, an evaluation of the station data is made where critical and possible river segments
with poor quality (median less than 3) exist. Only two longer and one short
sections in Switzerland receive a lower median than 3 for water quality.
 * SLS_B06 Visibility: For 99 percent of the river segments (30,733 of 31,062) in the canton of
Bern (2015 reduced version), the landscape area is considered to be visible. Due to this high number
of sections, a large number of viewpoints in the layer of Swisstopo and
the computation time and computability in ArcGIS, the landscape area is classified as generally viewable
(equal to 1).
16 Method
Additional indicators were added (see Appendix B.2):
 * SLS_A21 Dissection
 * SLS_A22 Forest areas
 * SLS_B03 Hiking trails
 * SLS_B10 Residential and vacation homes
 * SLS_B11 Tourist infrastructure
 * SLS_C01 Landfill
 * SLS_C03 Infrastructure
 * SLS_C05 Industry
 * SLS_C06 Agricultural land
Not to be added, although present to some extent:
 * SLS_B06 Cultural assets of national importance: here, too, the calculability of the visibility analysis is
for the whole of Switzerland is limited
 * SLS_A15 Legally binding protection and land use planning: the individual river sections are not
clearly designated, i.e. no geodata exist
The following data are also not supplemented, as they are cantonal data:
 * SLS_A10 Cantonal nature reserves
 * SLS_A16 Forest reserves
 * SLS_A17 Cantonal inventories and contractually protected areas

decision-making

display_name: decision-making

ecosystem-protection

display_name: ecosystem-protection

gis

display_name: gis

hydropower

display_name: hydropower

integral-water-management

display_name: integral-water-management

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal


en: aridity ground-temperature frost-change-velocity precipitation sdms soil

media_type: TIFF

en: Mean diurnal range modified from CHELSA

format: TIFF

en: Frost change frequency modified from CHELSA

media_type: tif

en: Precipitation of driest quarter modified from CHELSA

en: Precipitation seasonality from CHELSA

en: Mean annual temperature modified from CHELSA

en: Soil organic carbon content modified from SoilGrids

en: Soil clay content modified from SoilGrids

en: Soil pH modified from SoilGrids

en: The dataset contains seven environmental layers (average annual temperature, aridity [annual precipitation divided by annual potential evapotranspiration], frost change frequency, precipitation in the driest quarter, mean diurnal temperature range, and precipitation seasonality) modified from CHELSA (https://chelsa-climate.org/) and three soil layers (soil organic matter content, pH water, and clay content) modified from SoilGrids (https://soilgrids.org/).

aridity

display_name: aridity

frost-change-velocity

display_name: frost-change-velocity

ground-temperature

display_name: ground-temperature

precipitation

display_name: precipitation

sdms

display_name: sdms

soil

display_name: soil

en: Environmental layers for SDM simulations (GDPlants)


sensitivity-of-modeled-snow-instability

maintainer: Bettina Richter

title_for_slug: sensitivity-of-modeled-snow-instability

en: numerical-avalanche-forecasting global-sensitivity-analysis snowpack snow-instability snow-cover-modeling

en: Manually observed snow profiles

en: Manually observed snow profiles at Weissfluhjoch field site for winter season 2016-2017, including layer depth, hand hardness, grain size and grain shape for each layer.

en: Case WL

en: Extracted output data for case ALL. Here biases were introduced to meteorological input data during the period of weak layer formation. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

en: Case SL

en: Extracted output data for case SL. Here biases were introduced to meteorological input data during the period of slab formation. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

en: Reference run

en: Reference run for the sensitivity analysis at Weissfluhjoch field site for winter season 2016-2017. Meteorological data from the automatic weather stations are used. No biases were introduced to the input data.

en: Case ALL

en: Extracted output data for case ALL. Here biases were introduced to meteorological input data during the whole simulation period. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

en: We investigated the sensitivity of modeled snow instability to meteorological input data using SNOWPACK. We therefore used input data from the automatic weather station at the Weissfluhjoch field site for the year 2016-2017. We investigated three scenarios and performed 14'000 simulations for each scenario. The dataset contains extracted output data from modeled SNOWPACK simulations, including setup files to reproduce the simulations. For further information read the README file.

global-sensitivity-analysis

display_name: global-sensitivity-analysis

numerical-avalanche-forecasting

display_name: numerical-avalanche-forecasting

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability

snowpack

display_name: snowpack

envidat

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

en: Sensitivity of modeled snow instability


maintainer: Jana von Freyberg

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

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

media_type: application/pdf

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’.

format: PDF

mimetype: application/pdf

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

envidat

en: EnviDat: the Environmental Data Portal

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


maintainer: Giulia Francesca Azzurra Donati

en: circuit-theory biodiversity human-dominated-landscapes ecological-corridors urban-spatial-planning integrated-modelling

en: Amphibian whole life cycle predictors - 10m resolution

media_type: zip-compressed folder of ascii files

en:
Amphibian whole life cycle predictors include 6 variable types:
(1)	Topographic – slope [°]: derived from the Swiss Topographical Landscape model (swissTLM 3D 2015) at 2 m resolution (elevation uncertainty ± 0.5m) and, subsequently, aggregated to a median value;
(2)	Hydrologic: two predictors including nearest distance to water [m] (all water-related objects and rasterized lotic, lentic and reedbeds from the regional cadastral maps – AV: Daten der Amtliche Vermessung) and runoff coefficient [C] (between 0 and 1 relating amount of runoff to amount of precipitation, mapped AV: Daten der Amtliche Vermessung data against literature values for different land covers);
(3)	Edaphic – soil moisture variability (not available): can gathered from the spatial modelling of Ecological Indicator Values in Switzerland (Descombes et al., 2020) and resampled from 100m to 10m;
(4)	Vegetation: we calculated the median and standard deviation of the Normalized Difference Vegetation Index (NDVI) from all available cloud free Sentinel-2 pixels available between April and October for the years 2016 to 2019 (Drusch et al., 2012) and the median vegetation height [m] (not available) can gathered from Ginzler and Hobi (2015);
(5)	Land-use derived: includes three predictors, grassland density [grassland/cell] (not available) - can be gathered from Pazur et al. (2021), total grasslands area evaluated using a spatial weight matrix and a 250m neighborhood radius around each cell; urbanization [buildings/cell] – average building density for a 250m neighborhood around each cell based on the AV: Daten der Amtliche Vermessung ; and traffic intensity [vehicles/day] – average daily vehicle count (Nationales Personenverkehrsmodells);
(6)	Movement-ecology related: includes three predictors of proximity – nearest forest distance [m]; nearest rock-gravel and sandy area (RGS) distance [m] and nearest road distance [m] (considering any road type) – all calculated based on the AV: Daten der Amtliche Vermessung maps.

en: Amphibian species specific landscape resistance maps.

en: For each amphibian species we used the weighted average Ensemble model suitability map and converted it to a resistance map using an exponential decay function following (Duflot et al., 2018) using the species-specific mpa threshold previously computed (Preau et al., 2020). The function assigns a resistance value of 1,000 when habitat suitability equals zero, and a value of one when habitat suitability is greater than or equal to the binarization threshold. The exponential shape strengthens the barrier effect of less favorable areas.

en: Amphibian breeding sites of national importance - cantons of Aargau and Zürich

media_type: .asc

en: Amphibian breeding sites of national importance (focal nodes) in the cantons of Aargau and Zürich, 30x30 m resolution, binarised ascii format.

en: Binarized "green" and "grey" landcover data (Cantons of Aargau and Zürich)

en: "Green" landcover refers to lawns and vegetated urban surfaces such as, for example private gardens, public parks, cemeteries, green stripes along roadsides, etc. While "grey" landcover refers to impervious grounds such as roads, troittoirs, other impervious. Binarized maps, 30x30m resolution.

en: Amphibian monitoring data

en: Processed amphibian occurrence data (2017-2019) in the cantons of Aargau and Zürich. The dataset includes information for the following species: _Alytes obstetricans_,_Bombina variegata_, _Bufo bufo_, _Hyla arborea_, _Ichtyosaura alpestris_, _Lissotriton helveticus_, _Lissotriton vulgaris_, _Rana temporaria_, _Salamandra salamandra_, and _Triturus cristatus_.

en: The data includes (1) amphibian occurrence data (2017-2019) for ten species across the cantons of Aargau and Zürich gathered from the Coordination Center for the Protection of Amphibians and Reptiles of Switzerland (http://www.karch.ch), (2) amphibian whole-life cycle environmental predictors (i.e. topographic, hydrologic, edaphic, vegetation, land-use derived, movement-ecology related), and (3) local urban "green" and "grey" landcover data which can be used to identify opportunities for Blue-Green Infrastructure (through green or grey transitions) in support of regional landscape connectivity.

biodiversity

display_name: biodiversity

circuit-theory

display_name: circuit-theory

ecological-corridors

display_name: ecological-corridors

human-dominated-landscapes

display_name: human-dominated-landscapes

integrated-modelling

display_name: integrated-modelling

urban-spatial-planning

display_name: urban-spatial-planning

en: Amphibian and urban-rural landscape data Swiss Lowlands


irkis-soil-moisture-measurements-davos

maintainer: Nander Wever

title_for_slug: irkis-soil-moisture-measurements-davos

en: meteo-station meteorological-measurements soil-moisture davos dischma-catchment

en: IRKIS soil moisture data (zip file)

en: Compressed archive (zip) containing soil moisture measurements, as well as meteorological measurements and interpolated meteorological time series.

en:
Meteorological and soil moisture measurements from soil moisture stations installed from October 2010 - October 2013 in the area surrounding Davos, in particular in the Dischma catchment.

There are in total 7 stations: 1202, 1203, 1204, 1205, 222, 333 and SLF2. For each of the stations, there is a:

* vwc_[stn].smet: containing the soil moisture measurements

* station_[stn].smet: in-situ measured meteorlogical parameters. Note, the quality of these measurements for stations 1202, 1203, 1204 and 1205 is very low, with data gaps. Use this data with care. For stations 222, 333 and SLF2, data quality is high and only the default cautiousness should be applied.

* interpolatedmeteo_[stn].smet contains per stations a dataset derived by interpolating from several stations in the Davos area to the stations location. This dataset was generated from the output of the Alpine3D model, of which simulations are presented in the Wever et al. (2017) manuscript.

At the soil moisture measurement sites, Decagon 10HS sensors were installed, at 10, 30, 50, 80 and 120 cm depth. Per depth 2 sensors were installed, labelled A and B in the datafiles. Note that at stations 1203, 1204 and 1205, sensors were only installed at 10, 30 and 50 cm depth.

The files follow the SMET format: https://models.slf.ch/docserver/meteoio/SMET_specifications.pdf and metadata for the stations can be found in the header of the smet files.

Please cite the Wever et al. (2017) reference when using this data in publications.

For a more detailed description, please refer to: Wever, N., Comola, F., Bavay, M., and Lehning, M.: Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment, Hydrol. Earth Syst. Sci., 21, 4053-4071, https://doi.org/10.5194/hess-21-4053-2017, 2017.

davos

display_name: davos

dischma-catchment

display_name: dischma-catchment

meteo-station

display_name: meteo-station

meteorological-measurements

display_name: meteorological-measurements

soil-moisture

display_name: soil-moisture

envidat

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

en: IRKIS Soil moisture measurements Davos


maintainer: Yohann Chauvier

en: covariate-correction plant-species background-data survey-effort point-process-model environmental-stratification target-group cluster independent-dataset random-stratified-sampling

media_type: ZIP

en: Non-copyright data, scripts, diversity outputs

en:
Aim: While species distribution models (SDMs) are standard tools to predict species distributions, they can suffer from observation and sampling biases, particularly presence-only SDMs that often rely on species observations from non-standardized sampling efforts. To address this issue, sampling background points with a target-group strategy is commonly used, although more robust strategies and refinements could be implemented. Here, we exploited a dataset of plant species from the European Alps to propose and demonstrate efficient ways to correct for observer and sampling bias in presence-only models.

Innovation: Recent methods correct for observer bias by using covariates related to accessibility in model calibrations (classic bias covariate correction, Classic-BCC). However, depending on how species are sampled, accessibility covariates may not sufficiently capture observer bias. Here, we introduced BCCs more directly related to sampling effort, as well as a novel corrective method based on stratified resampling of the observational dataset before model calibration (environmental bias correction, EBC). We compared, individually and jointly, the effect of EBC and different BCC strategies, when modelling the distributions of 1’900 plant species. We evaluated model performance with spatial block split-sampling and independent test data, and assessed the accuracy of plant diversity predictions across the European Alps.

Main conclusions: Implementing EBC with BCC showed best results for every evaluation method. Particularly, adding the observation density of a target group as bias covariate (Target-BCC) displayed most realistic modelled species distributions, with a clear positive correlation (r≃0.5) found between predicted and expert-based species richness. Although EBC must be carefully implemented in a species-specific manner, such limitations may be addressed via automated diagnostics included in a provided R function. Implementing EBC and bias covariate correction together may allow future studies to address efficiently observer bias in presence-only models, and overcome the standard need of an independent test dataset for model evaluation.

background-data

display_name: background-data

cluster

display_name: cluster

covariate-correction

display_name: covariate-correction

environmental-stratification

display_name: environmental-stratification

independent-dataset

display_name: independent-dataset

plant-species

display_name: plant-species

point-process-model

display_name: point-process-model

random-stratified-sampling

display_name: random-stratified-sampling

survey-effort

display_name: survey-effort

target-group

display_name: target-group

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: Novel methods to correct for observer and sampling bias in presence-only species distribution models


en: landscape electrodermal-activity sense-of-place urban-ecology place-attachment

en: 03. Publication Ready Data

en: 01. EDA Processed Data

en: 04. Scripts

en: 05. Visuals

en: 02. Questionnaire Data

en: 00. EDA Raw Data

en: This repository contains data on EDA measurements of visitors with different cultural backgrounds in virtual urban park settings. The parks are a Persian garden (Shiraz, Iran) and a historical park in Zurich, Switzerland. The cultural background of the visitors is Persian and Central European. The repository contains raw data from EDA, processed time series and statistical procedures.

electrodermal-activity

display_name: electrodermal-activity

landscape

display_name: landscape

place-attachment

display_name: place-attachment

sense-of-place

display_name: sense-of-place

urban-ecology

display_name: urban-ecology

en: Electrodermal Activity (EDA) of Bi-cultural Visitors In Virtual Park Settings


en: air-temperature humidity precipitation-amount snow-ice-temperature wind-direction longwave-radiation snow-depth wind-speed shortwave-radiation

en: Version 1

media_type: SMET

en:
Deprecated version. Release notes:

First release of dataset.

en: Version 6

en:
Deprecated version.

Release notes:

- Missing ISWR for 2009-09-30 and 2010-04-30 has been replaced by data from WFJ Gipfel

This dataset is the basis for the Weissfluhjoch dataset in ESM-SnowMIP (doi: http://dx.doi.org/10.16904/16).

en: Undercatch correction

en: This document describes how the undercatch correction for the Weissfluhjoch measurement site was determined.

en: All versions

en: SNOWPACK sno file

en: This sno-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en: Version 5

en:
Deprecated version. Release notes:

Update: using the incoming and outgoing short- and longwave radiation data from the new processing chain from 2010 onwards, filling also data gaps in pre-2010 data.

Update: dataset extended to 2016-10-04T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 7 (current)

en:
Release notes:

Bug fix: in previous versions, snow lysimeter data from September 2010 onwards was erroneously reported for UTC+2, instead of UTC+1 (i.e., reported one hour later than should have been).

Update: dataset extended to 2017-07-11T00:30.

en: SNOWPACK ini file (old syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en: Version 4

en:
Deprecated version. Release notes:

Update: dataset extended to 2016-09-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 3

en:
Deprecated version. Release notes:

Bug fix: in version 2, the undercatch correction was not applied correctly

Bug fix: in version 2, snow lysimeter data was missing for extended periods of time

Update: dataset extended to 2016-01-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 2

en:
Deprecated version. Release notes:

Bug fix: in v1, incoming radiation components were taken from WFJ_Gipfel station, instead of WFJ Versuchsfeld.

en: SNOWPACK ini file (new syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using the new MeteoIO Filter, Generator and Interpolation syntax.

en:
Dataset of meteorological and snowpack measurements from the automatic weather station at Weissfluhjoch, Davos, Switzerland, suitable for driving snowpack models. The dataset contains standard meteorological measurements, and additionally snowpack runoff data from a snow lysimeter. Where possible, data is quality checked and missing data are replaced from backup sensors from the measurement site itself, or (in only a few cases) from the MeteoSwiss weather station at 470 m distance and 150 m above the measurement site.

Publication
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M. Verification of the multi-layer SNOWPACK model with different water transport schemes. 2015. The Cryosphere. Volume 9. 2271-2293. http://dx.doi.org/10.5194/tc-9-2271-2015.

air-temperature

display_name: air-temperature

humidity

display_name: humidity

longwave-radiation

display_name: longwave-radiation

precipitation-amount

display_name: precipitation-amount

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

snow-ice-temperature

display_name: snow-ice-temperature

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

envidat

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

en: WFJ_MOD: Meteorological and snowpack measurements from Weissfluhjoch, Davos, Switzerland


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

en: DHM-Kacheln zusammenfügen

en: View video on youtube!

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

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

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

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

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

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geodata-processing

display_name: geodata-processing

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

raster-processing

display_name: raster-processing

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

education

en: Education and science

en: EnviDat: the Environmental Data Portal

en: Seilaplan Tutorial: Merge DTM tiles


maintainer: Frank Techel

en: european-alps snow avalanche-forecast warning-regions danger-level

en: shape file warning regions Alps

en: Forecast avalanche danger level

media_type: text/csv

en: contains the highest forecast danger level (dangerLevelMax) for each day and warning region

mimetype: text/csv

en:
This dataset contains the data used in the publication by Techel et al., 2018 _Spatial consistency and bias in avalanche forecasts - a case study in the European Alps_ (Nat Haz Earth Syst Sci).
For details on the data please refer to this publication.
The dataset contains the following:
- shape files for the warning regions in the Alps
- highest forecast danger level for each warning region and day

avalanche-forecast

display_name: avalanche-forecast

danger-level

display_name: danger-level

european-alps

display_name: european-alps

snow

display_name: snow

warning-regions

display_name: warning-regions

en: Forecast avalanche danger level European Alps 2011 - 2015


maintainer: EnviDat Support

en: multilocus-genotypes biological-control switzerland population-genetics simple-sequence-repeats trichopria-drosophilae drosophila-suzukii nuclear-microsatellite-markers

en: Table comprising all pertinent information for multiplex PCRs of species-specific nuclear microsatellite makers for Trichopria drosophilae, comprising all 21 newly developed markers, details on full sequences with GenBank accession numbers, primer sequences (including labeling and pig-tails), and repeat motives. PCRs with respective annealing temperatures (AnnealingTemp) refer to Type-It Multiplex PCR Kit (Qiagen, Hilden, Germany).

en: Multilocus genotypes (biallelic coding for 21 nuclear microsatellites) of Trichopria drosophilae described in Gugerli et al. Agrarforschung Schweiz 2019. Missing data denoted as '999'. Population codes (PopNo) are the following: 1, Vezia; 3, Contone ; 5, Davesco; 6, Corteglia; 7, Mezzana; 8, Stabio; 9, Gordola; 10, Sementina; 12, Brusata di Novazzano; 14, Monteggio; 16, Giubiasco; 17, ComoBP; 18, VD; 19, Weil_D; 20, Dossenheim; 21, BioPlanet_Como. Coordinates (CoordCH_E, CoordCH_N) refer to the Swiss coordinates system CH1903.

en:
 Nuclear microsatellite markers and genotype data for _Trichopria ddrosophilae_

This data set comprises (i) the characteristics of a set of 21 species-specific nuclear microsatellites for PCR amplification in _Trichopria drosophilae_ (ii) and genotype data for samples collected in southern Switzerland (Canton of Ticino), with few reference samples from Canton of Vaud, southern Germany, and northern Italy (lab-reared population).
Markers were developed by Ecogenics GmbH, Balgach (Switzerland), using MiSeq Nano 2x250 v2 format (on a mix of 10 individuals). Multiplex PCR assays for multilocus genotyping were established by Ecological Genetics (WSL Birmensdorf), and population genetic analyses are found in Gugerli et al., Agrarforschung Schweiz 2019.

biological-control

display_name: biological-control

drosophila-suzukii

display_name: drosophila-suzukii

multilocus-genotypes

display_name: multilocus-genotypes

nuclear-microsatellite-markers

display_name: nuclear-microsatellite-markers

population-genetics

display_name: population-genetics

simple-sequence-repeats

display_name: simple-sequence-repeats

switzerland

display_name: switzerland

trichopria-drosophilae

display_name: trichopria-drosophilae

en: Nuclear microsatellite markers for Trichopria drosophilae, parasitoid wasp on Drosophila suzukii


wind-crust-formation-snowmicropen-data

title_for_slug: wind-crust-formation-snowmicropen-data

en: wind-crust wind-packing smp snow snowmicropen

en: Processing scripts

en: Contains the R-scripts used to process the SMPs

en: SMP data

media_type: Link

en: Links to the dataset

en: README

en: Describes the dataset in detail

en:
This dataset contains the SnowMicroPen (SMP) data from 38 wind tunnel experiments on wind-packing / wind crust formation. These experiments were performed in the winters 2015/16 and 2016/17 and include more than 1000 SMP measurements.

The SMPs are organized per experiment. Each experiment subfolder contains the processed SMP profiles and some additional files.

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

This dataset is the basis of the following publication:

Sommer C.G., Lehning M., & Fierz C. (2017). Wind tunnel experiments: Saltation is necessary for wind-packing. Journal of Glaciology, 63(242), 950-958. doi:10.1017/jog.2017.53

smp

display_name: smp

snowmicropen

display_name: snowmicropen

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

envidat

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

en: Wind crust formation: SnowMicroPen data


maintainer: Loïc Pellissier Pellissier

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

en: Vegetion surveys

en: Species inventories of plants

en: Study sites

en: Coordinates and elevation of the study sites

en: Orthoptera traits

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

en: Plant traits

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

en: Orthoptera surveys

en: Species inventories of Orthoptera

en: Nematode surveys

en: Surveys of soil nematode along elevation

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

alps

display_name: alps

community-indices

display_name: community-indices

elevation

display_name: elevation

environmental-gradients

display_name: environmental-gradients

functional-traits

display_name: functional-traits

herbivores-communities

display_name: herbivores-communities

plant-herbivore-interactions

display_name: plant-herbivore-interactions

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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


maintainer: Fachstelle für OGD Basel-Stadt

de: csv

de: Wahl eines Mitglieds des Gerichts für fürsorgerische Unterbringungen (csv)

license: CC BY 3.0 CH

de: json

media_type: application/json

de: Wahl eines Mitglieds des Gerichts für fürsorgerische Unterbringungen (json)

format: JSON

mimetype: application/json

de: Dieser Datensatz zeigt die Resultate des 1. Wahlgangs der Wahl eines Mitglieds des Gerichts für fürsorgerische Unterbringung vom 9. Mai 2021.

legislation

fr: Législation

de: Gesetzgebung

en: Legislation

it: Legislazione

politics

fr: Politique

de: Politik

en: Politics

it: Politica

kanton-basel-stadt

fr: Canton de Bâle-Ville

de: Kanton Basel-Stadt

en: Canton of Basel-City

it: Cantone di Basilea-Città

de: Der Kanton Basel-Stadt veröffentlicht nach und nach Open Government-Datensätze von kantonalen Ämtern und Dienststellen. Die kantonale Fachstelle für Open Government Data ist als Koordinationsorgan zuständig für die Unterstützung der datenpublizierenden Verwaltungsstellen.

political_level: canton

value: BS Kanton Stadt - DCAT Harvester


maintainer: Jonas Stillhard

en: primeval-beech-forest carpathian-biosphere-reserve forest-structure long-term-data-sets forest forest-dynamics dem permanent-forest-plot-data fagus-sylvatica stand-inventory-data

en: Dataset

en: Data description

en: Available online on publishers website

en:
In 2000, a permanent forest plot of 10 ha has been established in the core zone of the primeval beech forest of Uholka.
 All living and dead trees with a diameter at breast height (DBH) ≥ 60 mm were identified to species, DBH measured, stems tagged and mapped.
Since then, the plot has been remeasured in 2005, 2010, and 2015. In total, 4,820 individual trees were measured with 14,116 individual measurements throughout all four inventories.
In spring 2018, an Airborne Laser Scan was carried out, covering the Uholka‐Shyrokyi Luh forest. This data set allows us to derive a high‐resolution digital elevation model (DEM) of the plot area.
The data set allows for important insights into the development and the spatial and temporal dynamics of primeval beech forests.

carpathian-biosphere-reserve

display_name: carpathian-biosphere-reserve

dem

display_name: dem

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-structure

display_name: forest-structure

long-term-data-sets

display_name: long-term-data-sets

permanent-forest-plot-data

display_name: permanent-forest-plot-data

primeval-beech-forest

display_name: primeval-beech-forest

stand-inventory-data

display_name: stand-inventory-data

envidat

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

en: Stand inventory data from the 10‐ha forest research plot in Uholka, Ukraine


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

fr: service-geologique-national geologie

de: landesgeologie geologie

en: swiss-geological-survey geology

it: servizio-geologico-nazionale geologia

label: geocat.ch permalink

spatial: Jura (JU)

fr: Accès aux données / fichiers de téléchargement

protocol: OGC:service WMS

fr: Carte fixant les limites d'utilisation de la chaleur du sol et les conditions d'implantation des forages pour les sondes géothermiques verticales. La carte est établie sur la base des connaissances actuelles des conditions géologiques et hydrogéologiques cantonales. Elle intègre les restrictions liées à la protection des eaux souterraines (Loi fédérale du 24 janvier 1991 sur la protection des eaux souterraines – LEaux RS814.20). Les secteurs en glissements de terrains permanents et spontanés sont également considérés. Remarque : Dans les secteurs "A évaluer (prendre contact avec ENV)", la dérogation ne peut être délivrée que sur la base d'un préavis de l'Office de l'environnement (ENV) ou d'une note technique justifiant l'absence de risques hydrogéologiques et fixant la profondeur maximale des forages. Cette carte ne dispense pas les requérants d'une demande d'autorisation auprès des autorités compétentes. Elle ne tient pas compte de la localisation des sites pollués et des infrastructures souterraines.

canton-du-jura

fr: Canton du Jura

de: Kanton Jura

en: Canton of Jura

it: Canton Giura

fr: Le canton du Jura publie sur Open Data Swiss différents types de données de l'administration cantonale qui répondent au principe de l'Open Government Data.

en: The canton of Jura publishes on Open Data Swiss various types of data of the cantonal administration that meets the principle of Open Government Data.

de: Der Kanton Jura veröffentlicht auf Open Data Swiss verschiedene Arten von Daten der kantonalen Verwaltung, die dem Prinzip von Open Government Data entsprechen.

it: Il Cantone del Giura pubblica su Open Data Swiss vari tipi di dati dell'amministrazione cantonale che soddisfano il principio degli Open Government Data.

value: JU-Kt - Geocat Harvester

fr: Géothermie_Limitation des forages pour sondes géothermiques


de: ortsplanung landesentwicklung

en: local-planning land-development

fr: L'inventaire rend compte du site construit à protéger, c'est-à-dire de l'image actuelle du tissu à protéger, ainsi que des environnements qui présentent une importance pour leur sauvegarde. L'inventaire ordonne le tissu à protéger en composante du site construit, suivant les trois critères de la méthode d'inventaire : le périmètre construit, l'ensemble construit et l'élément individuel. Pour le périmètre construit, il s'agit de la plus grande extension d'un site construit pouvant être perçue comme entité pour ses caractéristiques historico-architecturales et spatiales, ainsi que pour sa spécificité régionale. L'ensemble construit s'applique à une partie du site construit pouvant être perçue comme entité, non seulement pour ses caractéristiques historico-architecturales et spatiales, ainsi que pour sa spécificité régionale mais aussi pour ses contrastes prononcés. Pour terminer, l'élément individuel est la plus petite composante possible du site construit, revêtant une signification prépondérante pour son image. L'inventaire englobe des environnements qui sont indispensables à la sauvegarde du tissu à protéger et qui, de ce fait, sont des parties intégrantes du site construit à protéger. Enfin, l'inventaire des sites construits à protéger en Suisse (ISOS) fournit également des perturbations, lesquelles indiquent des préjudices graves et des menaces qui mettent en péril le site construit. La saisie numérique a été effectuée sur la base des cartes papier de l'ISOS, établies au début des années 1990. En 2011, le Département fédéral de l'intérieur, par l'Office fédéral de la culture, a publié une actualisation de l'ISOS en format analogique concernant uniquement les sites construits d'importance nationale, en deux tomes (A-D et E-Z). La saisie des périmètres ISOS a été actualisée sur cette base en novembre 2011, en supprimant les anciennes données pour les sites construits d'importance nationale. Seules les données analogiques publiées par la Confédération font foi pour ce qui est de l'effet juridique, de l'exactitude et de l'actualité. Pour les sites construits d'importance cantonale ou locale, aucune modification n'a été effectuée, les anciennes cartes demeurant valables.

fr: Inventaire des sites construits à protéger (basé sur l'ISOS)


construction

fr: Construction, logement

de: Bau- und Wohnungswesen

en: Construction and housing

it: Costruzione e abitazione

fr: affectation-de-base infrastructure

de: grundnutzung infrastruktur

en: basic-assignment infrastructure

it: utilizzazione-di-base infrastrutture

fr: Cadastre des risques d'accidents majeurs : installation soumise à l'OPAM et périmètre de consultation associé, selon l'art. 11a, al. 2 OPAM (RS 814.012)

fr: Cadastre des risques selon l’ordonnance sur les accidents majeurs (CARAM entreprises)


agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

en: Agriculture, forestry

it: Agricoltura, selvicoltura

fr: prairie-forestiere foret

de: waldwiese forst

en: forest-meadow forest

it: prato-boschivo foresta

fr: Surfaces de soins aux jeunes peuplements forestiers exécutées dès 2008 sous forme de polygones et de points pour les plantations d'îlots et haute tiges en pâturage boisé. La couche recense les soins réalisés par les propriétaires et annoncés par les gardes forestiers de triage et annoncés pour un subventionnement. Les surfaces sont différenciées selon l'année de décompte et le type d'intervention (rajeunissement, fourré, perchis). En pâturages boisées, les mesures subventionnées incluent également la plantation de hautes-tiges et d'îlots.

fr: Soins aux jeunes peuplements en forêt et dans les pâturages boisés


kantone-lfi

geography

fr: Géographie

territory

fr: Territoire et environnement

title_for_slug: kantone-lfi

label: Link zur Detailbeschreibung der Daten

label: Link zum Fachportal

label: Linked Data Service (using SPARQL)

spatial: Schweiz

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

de: DE#WMTS-BGDI Dienst

format: WMTS

format: WMS

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

de: Linked Data

format: RDF XML

fr: Avec les géométries de l'ensemble de données, la Suisse est divisée en cantons ; dont Bâle-Ville et Bâle-Campagne sont considéré comme une seule entité.

de: Die Schweiz wird mit den im Datensatz vorliegenden Geometrien in die Kantone aufgeteilt, Basel-Stadt und Basel-Landschaft werden als Einheit betrachtet.

en: According to the geometry of the data set, Switzerland is divided into cantons. Basel Stadt and Basel-Landschaft are considered as a single unit.

it: Con le geometrie presenti nel set di dati, la Svizzera viene suddivisa in i cantoni: Basilea Città e Basilea Campagna sono considerati come un'unica unità.

bundesamt-fur-umwelt-bafu

fr: Office fédéral de l'environnement OFEV

de: Bundesamt für Umwelt BAFU

en: Federal Office for the Environment FOEN

it: Ufficio federale dell'ambiente UFAM

fr: L’autorité compétente pour les questions environnementales. Il est à ce titre chargé de gérer les ressources naturelles selon les principes du développement durable et de protéger l’homme contre les dangers naturels et l’environnement contre les pollutions.

de: Die Fachbehörde für die Umwelt. Es ist zuständig für die nachhaltige Nutzung der natürlichen Ressourcen sowie für den Schutz des Menschen vor Naturgefahren und den Schutz der Umwelt vor übermässigen Belastungen.

en: The federal environmental authority. It is responsible for ensuring that natural resources are used sustainably, that the public is protected against natural hazards, and that the environment is protected from unacceptable adverse impacts.

it: Il servizio specializzato in materia ambientale, è competente per quanto riguarda l'utilizzazione sostenibile delle risorse naturali, la protezione delle persone dai pericoli naturali e dell'ambiente da un inquinamento eccessivo.

political_level: confederation

value: BAFU - Geocat Harvester

fr: Cantons IFN

de: Kantone LFI

en: Cantons NFI

it: Cantoni IFN


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

en: Descricao dos dados em portiuguês

media_type: PDF

en: Portugues description

media_type: geotiff

en: Increase in sanitation service

format: GeoTIFF

en: Axial

en: New built-up pixels classified as axial

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

en: Variables description

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

en: slope

en: Slope °

en: Master plan Ihabela (zones)

en: isolated

en: New built-up pixels classified as isolated

en: Ecological-Economic Zoning (EEZ)

en: Population density per pixel (change per year)

en: Increase in Normalized Difference Vegetation Index

en: Native forest cover persistence from 2005 to 2015

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

en: Increase in clean water provision service

en: infill

en: New built-up pixels classified as infill

en: Topographic Index Position (TPI)

media_type: .shp

en: Master plan Ubatuba (zones)

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

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

en: Native forest cover gains from 2005 to 2015

en: Permanent housing density increase

en: Increase in waste collection service

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

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

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

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

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

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

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

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

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

3)	Topographic drivers

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

basic-services

display_name: basic-services

envidat

fr: EnviDat: le portail de données environnementales

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

en: 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.

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


agriculture

en: Agriculture, forestry

geography

de: Geographie

en: Geography

it: Geografia

territory

de: Raum und Umwelt

en: Territory and environment

en: forest-meadow forest

fr: Accès aux données / fichiers de téléchargement

fr: Réserves naturelles et zones de protection paysagère du canton du Jura faisant l'objet d'un arrêté les mettant sous la protection de l'Etat. L'Office de l'environnement travaille actuellement sur la mise à jour des arrêtés de protection et des périmètres de certaines réserves naturelles et zones de protection paysagère. Dans la même démarche, les biotopes marécageux (bas-marais / haut-marais) ne bénéficiant pas encore d'un statut de protection au niveau cantonal seront classés en tant que réserve naturelle.

canton-du-jura

fr: Canton du Jura

de: Kanton Jura

en: Canton of Jura

fr: Le canton du Jura publie sur Open Data Swiss différents types de données de l'administration cantonale qui répondent au principe de l'Open Government Data.

en: The canton of Jura publishes on Open Data Swiss various types of data of the cantonal administration that meets the principle of Open Government Data.

fr: Réserves naturelles et zones de protection paysagère cantonales


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

territory

it: Territorio e ambiente

fr: reseau-electrique energie

de: stromnetz energie

en: power-grid energy

it: rete-elettrica energia

fr: La stratégie de protection et d’utilisation en matière de force hydraulique a pour but d’identifier les tronçons de cours d’eau du canton du Jura sur lesquels il est possible de développer l’exploitation hydroélectrique. Durant le développement de la stratégie, plusieurs jeux de données ont été mis au point et font chacun l'objet d'une annexe au rapport explicatif et d'un modèle de géodonnées minimal : - Installations de force hydraulique en service - Installations de force hydraulique hors service - Intérêt d'utilisation des cours d'eau jurassiens - Intérêt écologique des cours d'eau jurassiens - Possibilités d'exploitation des cours d'eau jurassiens

de: Der Kanton Jura veröffentlicht auf Open Data Swiss verschiedene Arten von Daten der kantonalen Verwaltung, die dem Prinzip von Open Government Data entsprechen.

fr: Stratégie de protection et d’utilisation en matière de force hydraulique


agriculture

fr: Agriculture, sylviculture

de: Land- und Forstwirtschaft

geography

fr: Géographie

fr: Territoire et environnement

fr: prairie-forestiere foret

de: waldwiese forst

fr: Les zones alluviales sont des tronçons de cours d'eau présentant une morphologie intacte dont les abords sont régulièrement inondés et dont la dynamique alluviale (dépôt et retrait des matériaux solides) génère une forte biodiversité. Cette donnée a été mise à jour en 2018 par le canton et transmise à l'OFEV qui doit encore l'intégrer dans son infrastructure.

canton-du-jura

it: Canton Giura

it: Il Cantone del Giura pubblica su Open Data Swiss vari tipi di dati dell'amministrazione cantonale che soddisfano il principio degli Open Government Data.

fr: Inventaire des zones alluviales d'importance nationale, délimitation cantonale


fr: eaux eaux-geographie

de: gewasser gewasser

en: waters water-geographic

it: acque acque-geografia

fr: Le "plan PGEE", respectivement les bassins versants, indique pour chaque parcelle raccordée ou raccordable au réseau d'assainissement le système d'évacuation (unitaire ou séparatif) et le mode d'évacuation des eaux pluviales préconisé (infiltration totale/partielle/nulle, rétention, rejet au cours d'eau). Ces données sont utilisées dans le cadre de plan spécial d'équipements et de permis de construire. L'ensemble du plans PGEE forme une couche correspondant au "périmètre des égoûts publics".

fr: PGEE_Système et mode d'évacuation planifié des eaux (Plan PGEE) et périmètre des égoûts


agriculture

it: Agricoltura, selvicoltura

it: prato-boschivo foresta

fr: Accès aux données / fichiers de téléchargement

fr: Les prairies et pâturages secs doivent leur existence à l’agriculture. Ils sont en effet le résultat de plusieurs siècles d’exploitation extensive et d’agriculture traditionnelle. Depuis la fin du 19e siècle, les prairies et pâturages secs ont régressé de près de 90 %. Parallèlement, les espèces qu’ils abritent depuis toujours subissent de plus en plus de pression : presque 40 % de toutes les espèces végétales et 50 % de toutes les espèces animales qui sont tributaires des terrains secs figurent sur les listes rouges nationales. Les objets inventoriés sont classés selon leur importance (nationale, régionale, locale) conformément aux dispositions de l'article 10 de la Loi sur la protection de la nature et du paysage (RCJU 451).

fr: Canton du Jura

fr: Inventaire des prairies et pâturages secs d'importance régionale et locale


ubersicht-leitungskataster

title_for_slug: ubersicht-leitungskataster

spatial: Kanton Bern

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: La vue d'ensemble du cadastre des conduites donne des informations concernant la disponibilité digitale des fluides eaux usées, gaz, eau, chauffage à distance, électricité, communication et des autres fluides, ainsi que l'adresse de contact du service de gestion des données pour obtenir un extrait du cadastre de conduites.

de: Die Übersicht zum Leitungskataster gibt Informationen zum Stand der digitalen Verfügbarkeit der Lage der Medien Abwasser, Gas, Wasser, Fernwärme, Elektrizität, Kommunikation und den weiteren Medien sowie die Kontaktadresse der Datenverwaltungsstelle zum Bezug des Leitungskatasters.

fr: Office de l'information géographique du canton de Berne

de: Amt für Geoinformation des Kantons Bern

fr: L'Office de la géoinformation est le centre de compétence pour l'information spatiale dans le canton de Berne. Les géodonnées cantonales peuvent être utilisées gratuitement, sous réserve des conditions d'utilisation. Le Géoportail du canton de Berne est le point d'entrée central pour les cartes interactives, les géodonnées et les géoservices de l'administration cantonale.

de: Das Amt für Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Bern. Die kantonalen Geodaten sind unter Einhaltung der Nutzungsbedingungen kostenlos nutzbar. Das Geoportal des Kantons Bern ist der zentrale Einstiegspunkt für interaktive Karten, Geodaten und Geodienste der kantonalen Verwaltung.

value: Bern-Kt - Geocat Harvester

fr: Aperçu du cadastre des conduites

de: Übersicht Leitungskataster


maintainer: Bundesamt für Energie BFE

fr: Contenu des bassins d'accumulation, dimanche 24:00 heures, bulletin hebdomadaire

it: Grado di riempimento dei bacini di accumulazione, domenica alle ore 24, rapporto settimanale livello di accumulazione

author: Bundesamt für Energie BFE

media_type: SERVICE

fr:
Ce relevé, élaboré chaque dimanche à 24h00, recense le contenu (en GWh et en %) des bassins d'accumulation suisses dans 4 régions différentes.
Le taux de remplissage des bassins d'accumulation est relevé dans le cadre de la Statistique de l'électricité, qui fait partie de la statistique publique de la Suisse (base légale: LSF).

de: Der Füllungsgrad der Speicherseen, Sonntag 24h, Wochenbericht Speicherinhalt gibt Auskunft über den Speicherinhalt der Schweizer Speicherseen für vier Regionen in GWh und als Füllgrad in % jeweils am Sonntag 24h auf wöchentlicher Basis. Der Füllungsgrad der Speicherseen wird im Rahmen der Elektrizitätsstatistik erhoben, welche Teil der öffentlichen Statistik der Schweiz ist (gesetzliche Grundlage: BStatG).

statistical-basis

fr: Bases statistiques

de: Statistische Grundlagen

en: Statistical basis

it: Basi statistiche

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

energy

fr: Energie

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).


gruda-av-export

geography

fr: Géographie

de: Geographie

territory

fr: Territoire et environnement

de: Raum und Umwelt

title_for_slug: gruda-av-export

fr: batiment registre-foncier droit-de-propriete cadastre nomenclature

de: gebaude grundbuch eigentumsordnung kataster nomenklatur

fr: Export des données sur les biens-fonds, les bâtiments, désignation de la situation et la couverture du sol de la banque de données des biens-fonds GRUDA-MO. L'export correspond au modèle de données du téléchargement de données issues de GRUDA-MO La correspondance des attributs du modèle de données au géoproduit est décrite dans le fichier [GRUDAEXP_Attribute.pdf](<https://geofiles.be.ch/geoportal/pub/lpi/GRUDAEXP_Attribute.pdf>).

de: Daten-Export zu Grundstücken, Gebäuden, Lagebezeichnung und Bodenbedeckung aus der Grundstückdatenbank GRUDA-AV. Der Export entspricht dem Datenmodell des Datenablads aus GRUDA-AV Die Zuordnung der Attribute des Datenmodells zum Geoprodukt ist in der Datei [GRUDAEXP_Attribute.pdf](<https://geofiles.be.ch/geoportal/pub/lpi/GRUDAEXP_Attribute.pdf>) beschrieben.

fr: GRUDA MO Export

de: GRUDA AV Export


title_for_slug: Schweizerische Elektrizitätsstatistik: Schweizerische Elektrizitätsbilanz - Monatswerte

fr: ogd35-bfe electricite production importation exportation consommation

de: ogd35-bfe elektrizitat produktion import export verbrauch

en: ogd35-bfe electricity production import export

it: ogd35-bfe elettricita produzione importazione esportazione consumo

fr: Statistique suisse de l'électricité: bilan mensuel suisse de l'électricité

it: Statistica svizzera dell'elettricità: bilancio svizzero dell'elettricità - valori mensili

fr: Cette statistique recense sur une base mensuelle la production, l'importation, l'exportation et la consommation d'électricité en Suisse. Elle présente la production des centrales hydrauliques, des centrales nucléaires, des centrales thermiques classiques et renouvelables. Elle indique la consommation des installations de pompage d'accumulation et les pertes en ligne. Elle est établie dans le cadre de la Statistique de l'électricité, qui fait partie de la statistique publique de la Suisse (base légale: LSF).

de: Die Schweizerische Elektrizitätsbilanz - Monatswerte gibt Auskunft über Produktion, Import / Export und Verbrauch von Elektrizität in der Schweiz auf monatlicher Basis. Bei der Produktion werden Wasserkraftwerke, Kernkraftwerke, konventionell-thermische und erneuerbare Kraftwerke unterschieden. Der Verbrauch der Speicherpumpen und die Leitungsverluste werden ausgewiesen. Die monatliche Elektrizitätsbilanz wird im Rahmen der Elektrizitätsstatistik erstellt, welche Teil der öffentlichen Statistik der Schweiz ist (gesetzliche Grundlage: BStatG).

energy

de: Energie


stand-der-amtl-vermessung

geography

it: Geografia

title_for_slug: stand-der-amtl-vermessung

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: Sur la base du fichier cantonal Limites communale 1:5'000, les données relatives aux périmètres approuvé et en les périmètres en cours de la mensuration officielle du canton de Berne, depuis lintroduction du CC en 1910, ont été saisies dans un même fichier AMO. Le fichier AMO montre létat actuel de la mensuration officielle dans le canton de Berne et permet den exploiter les données.

de: Im Datensatz AMO sind auf der Grundlage des Kantonsdatensatzes Gemeindegrenzen 1:5'000 für den Kanton Bern die anerkannten Bearbeitungsperimeter und die sich in Bearbeitung befindenden Bearbeitungsperimeter der amtlichen Vermessung erfasst, welche nach Einführung des ZGB im Jahr 1910 bearbeitet wurden resp. bearbeitet werden. Der Datensatz AMO zeigt den heutigen Stand der amtlichen Vermessung im Kanton Bern.

fr: Office de l'information géographique du canton de Berne

fr: L'Office de la géoinformation est le centre de compétence pour l'information spatiale dans le canton de Berne. Les géodonnées cantonales peuvent être utilisées gratuitement, sous réserve des conditions d'utilisation. Le Géoportail du canton de Berne est le point d'entrée central pour les cartes interactives, les géodonnées et les géoservices de l'administration cantonale.

fr: Etat actuel de la mensuration officielle

de: Stand der amtl. Vermessung


title_for_slug: Solarenergiepotenziale der Schweizer Gemeinden

de: energie energiewirtschaft photovoltaik solar solarenergie solarthermie sonne sonnendach ogd52-bfe

fr: Potentiel d'énergie solaire des communes suisses

en: Solar energy potential of Swiss municipalities

it: Potenziale di energia solare dei comuni svizzeri

format: XLS

fr:
L’application interactive www.toitsolaire.ch fournit des informations sur l’aptitude des toitures des bâtiments à exploiter l’énergie solaire. Il renseigne de manière simple sur les quantités d’électricité et de chaleur qui pourraient être produites sur le toit d’un bâtiment.
Sur la base du potentiel solaire des toits des différents bâtiments, l’OFEN calcule le potentiel global des communes pour la production d’électricité et de chaleur. Deux scénarios ont été imaginés: dans le premier, tous les toits sont exploités uniquement pour produire de l’électricité; dans le second, seules les parties les plus appropriées des toitures sont utilisés pour la production de chaleur et le reste est utilisé pour produire de l’électricité.

en:
Die interaktive Anwendung www.sonnendach.ch informiert über die Eignung von Hausdächern für die Solarenergienutzung. Auf einfache Weise wird vermittelt, wieviel Solarstrom oder Solarwärme mit einem Hausdach produziert werden könnte.
Für die Gemeinden berechnet das Bundesamt für Energie BFE auf der Grundlage der Solarpotenziale der einzelnen Hausdächer, wie gross die Potenziale für Solarstrom und Solarwärme für das gesamte Gemeindegebiet sind. Zwei Szenarien werden berechnet: Im ersten Szenario werden alle Dächer nur für Solarstrom verwendet. Im zweiten Szenario wird pro Haus das beste Dachstück für Solarwärme und der Rest für Solarstrom verwendet.

it:
L'applicazione interattiva www.tettosolare.ch informa circa l’adeguatezza dei tetti delle case per lo sfruttamento
dell'energia solare fornendo, in modo semplice, dati sulla quantità di energia elettrica o termica
che un determinato tetto potrebbe produrre.
L'Ufficio federale dell'energia (UFE), basandosi sul potenziale solare dei singoli tetti di un Comune,
calcola l'entità del potenziale di produzione di energia elettrica e termica del territorio comunale. Vengono
calcolati due possibili scenari: nel primo scenario tutti i tetti vengono utilizzati per la sola produzione
di energia elettrica, mentre nel secondo la superficie migliore di tetto di ogni casa viene utilizzata
per la produzione di energia termica e le restanti superfici esclusivamente per la produzione di energia elettrica.

energie

display_name: energie

energiewirtschaft

display_name: energiewirtschaft

photovoltaik

display_name: photovoltaik

solar

display_name: solar

solarenergie

display_name: solarenergie

solarthermie

display_name: solarthermie

sonne

display_name: sonne

sonnendach

display_name: sonnendach

administration

fr: Administration

de: Verwaltung

en: Administration

it: Amministrazione

statistical-basis

fr: Bases statistiques

construction

fr: Construction, logement

de: Bau- und Wohnungswesen

en: Construction and housing

it: Costruzione e abitazione

culture

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

de: Kultur, Medien, Informationsgesellschaft, Sport

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

national-economy

fr: Economie nationale

politics

fr: Politique

de: Politik

en: Politics

it: Politica


tracer-verbindungslinien

geography

fr: Géographie

en: Geography

territory

fr: Territoire et environnement

en: Territory and environment

it: Territorio e ambiente

title_for_slug: tracer-verbindungslinien

fr: traceur geologie

de: tracer geologie

spatial: Kanton Bern (erweitert)

fr: Dans le service de documentation géologique du canton de Berne sont rassemblées les informations provenant d'études géologiques, hydrogéologiques et géophysiques. Sont également disponibles les résultats d' essais de traçage dans le mileu karstique et les aquifères en roches meubles. Les lignes représentées dans le géoproduit TRALIN indiquent les liaisons entre les points d'injection et les points d'apparition du traçeur démontrées avec certitude.

de: Bei der geologischen Dokumentationsstelle des Kantons Bern werden Informationen aus geologischen, hydrogeologischen und geophysikalischen Untersuchungen zusammengetragen. Darin enthalten sind auch verschiedene Markierversuche im Karst- und Lockergesteinsgrundwasser. Die im Geoprodukt TRALIN dargestellten Linien markieren die gesicherten Verbindungen zwischen Tracereingabestellen und Tracernachweisstellen.

de: Amt für Geoinformation des Kantons Bern

de: Das Amt für Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Bern. Die kantonalen Geodaten sind unter Einhaltung der Nutzungsbedingungen kostenlos nutzbar. Das Geoportal des Kantons Bern ist der zentrale Einstiegspunkt für interaktive Karten, Geodaten und Geodienste der kantonalen Verwaltung.

fr: Ligne de connexion du traceur

de: Tracer Verbindungslinien


fr: pathologie-vegetale alimentation-en-eau utilisation-du-sol exploitation-agricole carte maladie-animale planification-de-lespace-physique vegetation agriculture diversite-biologique cadastre pepiniere abeille arbre-fruitier protection-des-plantes espace-protege vignobles

de: pflanzenkrankheit wasserversorgung bodennutzung landwirtschaftliche-nutzung karte tierkrankheit raumplanung vegetation landwirtschaft artenvielfalt kataster baumschule biene obstbaum pflanzenschutz schutzgebiet reben

fr: Service d'image

de: Darstellungsdienst

fr: Le service représente les données de base du canton de Berne selon la géocatégorie S conforme à eCH-0166. Il comprend actuellement la carte d'aptitude agricole, les cultures agricoles (y compris provisoires), le feu bactérien - objets protégés, les plantes problématiques, les projets mise en réseau selon OQE, les ruchers, les vignobles et les zones d'interdiction et périmètre de protection des stations de fécondation.

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie S gemäss eCH-0166 dar. Er enthält aktuell die Datensätze Bienenstände, Bienensperrgebiete und Schutzzonen für Belegstationen, Feuerbrand-Schutzobjekte, Landwirtschaftliche Eignungskarte, Landwirtschaftliche Kulturen (inkl. provisorischer), Problempflanzen, Reben sowie Vernetzungsprojekte nach OeQV.

fr: Thèmes agricoles du canton de Berne

de: Landwirtschaftsthemen des Kantons Bern


fr: identification-du-lieu-sig batiment liste-de-diffusion point distribution-spatiale altitude nomenclature geographie

de: ortsbestimmung gebaude adressenliste punkt raumliche-verteilung hohe nomenklatur geographie

fr: Le service représente les données de base du canton de Berne selon la géocatégorie B conforme à eCH-0166. Il comprend les adresses des bâtiments, le canton dans votre région, les localités (pour la recherche de localité), les points fixes planimétriques et altimétriques 1 / 2 ainsi que la répartition des plans de nomenclature.

de: Der Dienst stellt Grundlagedaten des Kantons Bern entsprechend der Geokategorie B gemäss eCH-0166 dar. Er enthält die Datensätze Der Kanton in Ihrer Region, Gebäudeadressen, Lage- und Höhenfixpunkte der Kategorien 1 und 2, Ortschaften (für Suche von Ortschaften) und Planeinteilung Nomenklatur.

fr: Office de l'information géographique du canton de Berne

fr: L'Office de la géoinformation est le centre de compétence pour l'information spatiale dans le canton de Berne. Les géodonnées cantonales peuvent être utilisées gratuitement, sous réserve des conditions d'utilisation. Le Géoportail du canton de Berne est le point d'entrée central pour les cartes interactives, les géodonnées et les géoservices de l'administration cantonale.

fr: Localisation et systèmes de référence du canton de Berne

de: Ortsangaben und Referenzsysteme des Kantons Bern


fr: maillage carte registre-foncier laser droit-de-propriete systeme-de-coordonnees cadastre fond-de-plan

de: gitternetz karte grundbuch laser eigentumsordnung koordinatensystem kataster kartenhintergrund

fr: Le service représente les données de base du canton de Berne selon la géocatégorie A conforme à eCH-0166. Il comprend les numéros de parcelles, le plan d’ensemble 1:5'000 (UP5), le réseau kilométrique et la vue d'ensemble des survols LIDAR.

de: Der Dienst stellt Grundlagedaten des Kantons Bern entsprechend der Geokategorie A gemäss eCH-0166 dar. Er enthält das Kilometernetz, die Parzellennummern, die Übersicht der LIDAR-Befliegungen sowie den Übersichtsplan 1:5'000 (UP5).

fr: Cartes de référence, couverture du sol et images aériennes du canton de Berne

de: Basiskarten, Bodenbedeckung und Bilddaten des Kantons Bern


gebaudeadressen

geography

fr: Géographie

de: Geographie

territory

de: Raum und Umwelt

title_for_slug: gebaudeadressen

fr: batiment liste-de-diffusion

de: gebaude adressenliste

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: Le fichier GEBADR contient les adresses postales des bâtiments, adresses spatialisées et enregistrées dans la base de données de la mensuration officielle. Il contient aussi les bâtiments souterrains. En règle générale, une adresse de bâtiment se compose des éléments suivants : un nom de rue, ou de place, ou un lieu dénommé; un numéro de maison; le numéro postal d'acheminement (NPA) et la localité. Les bâtiments annexes (garages, remises, etc.) ne possèdent pas tous un numéro de maison ; ils sont désignés par la mention « nn » (qui veut dire non numéroté). L'objectif à moyen terme est d'attribuer aussi à ces bâtiments annexes un numéro de maison univoque. Cette désignation se fera en collaboration avec les communes bernoises.

de: Der Datensatz GEBADR enthält die postalischen Gebäudeadressen aller ober- und unterirdischen Gebäude, welche in der amtlichen Vermessung erfasst sind. Eine Gebäudeadresse setzt sich im Normalfall aus folgenden Elementen zusammen: Strassenname (oder Platz, benanntes Gebiet), Hausnummer, Postleitzahl und Ortschaft. Nebengebäude (z.B. Garagen, Ökonomiegebäude) verfügen teilweise nicht über eine eigene Hausnummer und sind deshalb mit der Bezeichnung 'nn' (= nicht nummeriert) bezeichnet. Es wird angestrebt, in Zusammenarbeit mit den bernischen Gemeinden künftig auch diese bisher nicht nummerierten Gebäude mit einer eindeutigen Hausnummer zu kennzeichnen.

fr: Adresses des bâtiments

de: Gebäudeadressen


fr: sauvegarde-de-lenvironnement affaissement-du-sol type-de-sol eboulement decharge zone-a-risque relief prevention-des-incendies-de-foret traceur gaz-naturel risque-naturel eau-substance radon roche ecoulement-des-crues avalanche atmosphere-du-sol protection-contre-les-crues sol service-dincendie incendie-de-foret decomposition tassement transport sciences-naturelles degat-des-eaux geologie inondation structure-regionale protection-de-la-foret processus-geomorphologique cadastre index geomorphologie prevention-des-avalanches bois protection-de-la-montagne crue danger eaux-souterraines mesure-de-protection avalanche gestion-forestiere erosion

de: umweltschutz bodensenkung bodenart erdrutsch deponie gefahrenzone relief waldbrandverhutung tracer erdgas naturgefahr wasser radon fels hochwasserabfluss lawine bodenluft hochwasserschutz boden feuerwehr waldbrand abbau bodensetzung transport naturwissenschaft wasserschaden geologie uberschwemmung raumstruktur waldschutz geomorphologischer-prozess kataster index geomorphologie lawinenschutz wald bergschutz hochwasser gefahren grundwasser schutzmassnahme schneerutsch forstwirtschaft erosion

fr: Le service représente les données de base du canton de Berne selon la géocatégorie F conforme à eCH-0166. Il comprend actuellement le cadastre des événements liés aux dangers naturels, la carte des gisements de matières premières EDT, la carte indicative des forêts protectrices, la carte du toit du rocher, les cartes et les indices des dangers naturels, les concentrations de radon à l'intérieur des bâtiments, les constructions paravalanches, les données relatives à des points au sol, les géotopes d'importance régionale, l'indication de sols anthropiques, les lignes de connexion du traceur, les sites définis pour les panneaux d'interdiction de faire du feu, les sondages géologiques ainsi que la typologie des ensembles naturels.

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie F gemäss eCH-0166 dar. Er enthält aktuell die Bodenpunktdaten, die Felsreliefkarte, Feuerverbotsschilder-Standorte (Waldbrandmanagement), die geologische Rohstoffkarte ADT, die geologischen Sondierungen, die Geotope von regionaler Bedeutung, die Hinweise auf anthropogene Böden, die Lawinenverbauungen, den Naturgefahren-Hinweiskataster, die Naturgefahrenkarten und -hinweise, die Naturraumgliederung, die Radonkonzentrationen in Innenräumen, die Schutzwaldhinweiskarte sowie die Tracer-Verbindungslinien.

de: Amt für Geoinformation des Kantons Bern

de: Das Amt für Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Bern. Die kantonalen Geodaten sind unter Einhaltung der Nutzungsbedingungen kostenlos nutzbar. Das Geoportal des Kantons Bern ist der zentrale Einstiegspunkt für interaktive Karten, Geodaten und Geodienste der kantonalen Verwaltung.

fr: Géologie, sols et dangers naturels du canton de Berne

de: Geologie, Böden und naturbedingte Risiken des Kantons Bern


de: naturschutz altlast flughafen naturdenkmal verkehrsinfrastruktur naturgefahr luftverkehr schadstoffbelastung raumplanung flora naturschutzgebiet landschaftsplanung regionalplanung geologie gewasser zivilluftverkehr offentlicher-verkehr luftsicherheit kataster flachennutzungsplanung grenze wald inventar pflanzenschutz grundwasserschutz larmbelastung abfall botanik gewasserschutz planung

fr: Service d'image

de: Darstellungsdienst

fr: Le service offre des informations sur les thèmes du Cadastre des restrictions de droit public à la propriété (cadastre RDPPF). Le cadastre RDPPF dresse l’inventaire des principales restrictions applicables aux parcelles conformément aux dispositions légales ainsi qu’aux actes édictés par les autorités (p. ex. zones à bâtir).

de: Der Dienst stellt die Themen des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB-Kataster) dar. Der ÖREB-Kataster führt die wichtigsten Beschränkungen auf, die aufgrund gesetzlicher Bestimmungen und behördlicher Erlasse auf ein Grundstück wirken (z.B. Bauzonen).

fr: Cadastre RDPPF du canton de Berne

de: ÖREB-Kataster des Kantons Bern