maintainer: Varun Sharma

en: antarctica blowing-snow snow-atmosphere-interaction alps mesoscale-modelling

en:
REPRODUCIBILITY_POSTPROCESSING.zip contains data and scripts used to produce all figures from for the associated manuscript submitted for peer review ( see section on Citations below )

The folders stand for the three case studies presented in the manuscript. Two case studies (case Ia and case Ib) are on simulations in Antarctica and one case study
case II is for simulations in the Alps.

The associated data in the form of netcdf files or text files were produced using CRYOWRF v1.0

Apart from reproducibility, the intention of sharing these scripts is also to make it easy for new users to adopt CRYOWRF and be efficient, in particular in processing snowpack outputs.

The scripts were tested on multiple machines (different OSes) with the attached YAML file (wrf_analysis.yml) to setup the conda environment. All scripts were run using spyder as the IDE.

en: REPRODUCIBILITY_SIMULATION.zip contains all the extraneous files required to perform the simulations in associated manuscript (see Citations 3 in README.txt). The purpose of sharing these files apart from purposes of reproducibility is to also serve as templates for users to learn the workflow of CRYOWRF and perform simulations for their own purposes.

en:
This repository contains data required for reproducibility of the results to be published in the associated manuscript.

Apart from reproducibility, the attached datasets also serve as templates for new users to adopt CRYOWRF in their research.

The datasets consist of two folders organized in zip format:

1. REPRODUCIBILITY_SIMULATION:
  Consists of namelists for WPS, WRF and SNOWPACK to reproduce simulations published in the manuscript
  Additional files include datasets (from IMAU-FDM / RACMO, see "credits" below ) as well as helper python scripts to
  produce *.sno files
  which are used as initial conditions for SNOWPACK in CRYOWRF.

2. REPRODUCIBILITY_POSTPROCESSING:
   Includes outputs of CRYOWRF and python scripts used to prepare figures in the manuscript.

Each of the folders have their own readme files for more details.

 Code
citation: Varun Sharma. (2021, July 2). vsharma-next/CRYOWRF: CRYOWRF v1.0 (Version v1.0). Zenodo. http://doi.org/10.5281/zenodo.5060165

location: https://gitlabext.wsl.ch/atmospheric-models/CRYOWRF   (stable releases / institutional repo)
        https://github.com/vsharma-next/CRYOWRF            (dev branches / developer repo)

 Publication
**Introducing CRYOWRF v1.0: Multiscale atmospheric flow simulations with advanced snow cover modelling.**
Varun Sharma, Fraziska Gerber and Michael Lehning, Submitted to Geoscientific Model Development

 Acknowledgements
We thank Peter Kuipers Munneke (P.KuipersMunneke@uu.nl) for preparing and sharing outputs of IMAU-FDM and RACMO used for initial conditions for case Ia. The relevant citations for the methods through which these datasets were generated are:

* Kuipers Munneke, P., S. R. M. Ligtenberg, B. P. Y. Noël, I. M. Howat, J. E. Box, E. Mosley-Thompson, J. R. McConnell, K. Steffen, J. T. Harper, S. B. Das and M. R. van den Broeke. 2015. Elevation change of the Greenland ice sheet due to surface mass balance and firn processes, 1960-2014. The Cryosphere, 9, 2009-2025. doi:10.5194/tc-9-2009-2015

 * Ligtenberg, S. R. M., P. Kuipers Munneke, B. P. Y. Noël, and M. R. van den Broeke. 2018. Brief communication: Improved simulation of the present-day Greenland firn layer (1960-2016). The Cryosphere, 12, doi:10.5194/tc-12-1643-2018

alps

display_name: alps

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

mesoscale-modelling

display_name: mesoscale-modelling

snow-atmosphere-interaction

display_name: snow-atmosphere-interaction

en: Reproducibility Dataset for CRYOWRF v1.0


maintainer: EnviDat Support

en: landuse wrf cryowrf topography antarctica

state: active

type: dataset

en: Documentation

media_type: application/pdf

en: Documentation about how the provided dataset was produced including details to reproduce the dataset.

format: PDF

mimetype: application/pdf

en: Scripts

media_type: application/zip

en: Scripts to run the preprocessing to produce WRF binary tiles from REMA and AntarcticaLC2000 for topography and landuse (see Documentation for procedure).

format: ZIP

mimetype: application/zip

en: WPSinput

en: Input files to run the Weather Research and Forecasting model (WRF) preprocessing system WPS with REMA topography and AntarcticaLC2000 landuse data (see Documentation for details).

en:
Reference Elevation Model of Antarctica (REMA) topography and AntarcticaLC2000 landuse data
are now available as static data input for the Weather Research and Forecasting model (WRF). Topography
and landuse are made available at a spatial resolution of 1 km. This documentation describes the methods
applied to convert REMA and AntarcticaLC2000 to WRF readable format and shows how this improves
the representation of the Antarctic topography and landuse categories over coastal Antarctic regions.

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: REMA topography and AntarcticaLC2000 for WRF


maintainer: Rebecca Mott

en: eddy-covariance-measurements turbulent-sensible-heat-fluxes patchy-snow-covers snow-patch dischmex

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific Inc.) in 3.2 m on a daily basis.

en: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 3.3 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 0.7 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 3.5 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.2 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (DA-600, Kaijo-Denki) in 0.3 m on a daily basis.

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.6 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific Inc.) in 1.7 m on a daily basis.

en: Gletschboden setup

media_type: image/png

en: Background map based on data © 2014/2016 swisstopo (JD100042)

format: PNG

mimetype: image/png

en: Output explanation

format: XLS

en:
This dataset contains eddy-covariance measurements in the ablation period of 2014-2016. Measurements were taken from two turbulence towers over a long-lasting snow patch, which are 5 m apart from each other (2014 and 2015). The turbulence towers were equipped with two YOUNG ultrasonic anemometers mounted 0.7 m (in 2014) and 3.3 m (in 2015) above snow-free ground, two ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) mounted at 2.6 m (in 2014) and 2.2 m (in 2015) above snow-free ground and one anemometer (DA-600, Kaijo Denki) mounted at 0.3 m above snow surface.

The measurement setup changed in 2016 and includes a measurement above the snow-free ground in upwind direction (Swiss coordinates: 790191/176689). The measurement tower is equipped with one ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 3.3 m above the snow-free ground. Additionally, one measurement tower is installed above the long-Lasting snow patch and equipped with the same setup as 2015.

Turbulence data were sampled at a frequency of 20 Hz. The processing of the data to quality controlled fluxes has been done with the Biomicrometeorology flux software (Thomas et al., 2009). The program applies plausibility tests and a despiking test after Vickers and Mahrt (1997) on the measured data. The routine further applies a time-lag correction and considers the deployment (e.g. the sonic azimuth). A frequency response correction (Moore, 1986) is done and a three-dimensional rotation is performed. Finally, quality assurance/quality control (QA/QC) flags after Foken et al., (2004) are issued and fast Fourier transform power and co-spectra are calculated. The change in snow height is considered in the post-processing for every measurement day. The turbulence data were averaged to 30 minute intervals.

dischmex

display_name: dischmex

eddy-covariance-measurements

display_name: eddy-covariance-measurements

patchy-snow-covers

display_name: patchy-snow-covers

snow-patch

display_name: snow-patch

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

en: DISCHMEX - Impact of extreme land-surface heterogeneity on micrometeorology over spring snow-cover


maintainer: Sofia Pagliarin

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

media_type: CSV

format: CSV

en: Information on data sources

media_type: .csv

format: SERVICE

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


en: pattern-formation snow python numerical-model vapor-transport

media_type: ZIP

en:
Data and code v1.0 downloaded from the git.

Running the code requires an installation of FEniCS via docker.

en:
This python code uses the Finite Element library FEniCS (via docker) to solve the one dimensional partial differential equations for heat and mass transfer in snow. The results are written in vtk format.

The dataset contains the code and the output data to reproduce the key Figure 5 from the related publication:

_Schürholt, K., Kowalski, J., Löwe, H.; Elements of future snowpack modeling - Part 1: A physical
instability arising from the non-linear coupling of transport and phase changes, The Cryosphere, 2022_

The code and potential updates can be accessed directly through git via:

https://gitlabext.wsl.ch/snow-physics/snowmodel_fenics

numerical-model

display_name: numerical-model

pattern-formation

display_name: pattern-formation

python

display_name: python

snow

display_name: snow

vapor-transport

display_name: vapor-transport

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: A numerical solver for heat and mass transport in snow based on FEniCS


en: snow-temperature water-front snowmicropen snow-stratigraphy weissfluhjoch ice-layers

en: README

media_type: text/plain

format: TXT

mimetype: text/plain

en: WFJ_ICE_LAYERS dataset

en: The WFJ_ICE_LAYERS dataset contains multi-instrument snowpack measurements at high temporal resolution, which enable to monitor the formation of deep ice layers due to preferential water flow, at the Weissfluhjoch research site, Davos, Switzerland. It covers the winter 2016/2017, with a focus on the early melting season. This dataset includes traditional snowpack profiles (weekly resolution, 15/11/2016-29/05/2017), SnowMicroPen penetration resistance profiles (daily resolution, 01/02/2017-19/04/2017), snow temperatures measured at different heights in the snowpack (half-hourly resolution, 01/03/2017-15/04/2017) and the water front height derived from an upward-looking ground penetrating radar (3-hour resolution, 04/03/2017-08/04/2017). The measurements are complemented by initialization files for SNOWPACK model simulations with the ice reservoir parameterization at Weissfluhjoch for the winter 2016/2017.

ice-layers

display_name: ice-layers

snow-stratigraphy

display_name: snow-stratigraphy

snow-temperature

display_name: snow-temperature

snowmicropen

display_name: snowmicropen

water-front

display_name: water-front

weissfluhjoch

display_name: weissfluhjoch

en: WFJ_ICE_LAYERS: Multi-instrument data for monitoring deep ice layer formation in an alpine snowpack


automatic-detection-of-avalanches

maintainer: Matthias Heck

title_for_slug: automatic-detection-of-avalanches

en: monitoring hidden-markov-model seismic avalanche-activity snow

en: Results and Scripts

en: This zip package contains the classification results, coherence results, reference data set, python scripts used for the classification and the start and end times for the pre-processed continuous seismic data. A further readme file is also include for more detailed information.

en: This dataset contains the results obtained by an automatic classification using hidden Markov models of a continuous seismic dataset. To avoid long computational times, we reduced the seismic data using pre-processing step. The start and end times of the windows used for the classification are also included in this dataset. Furthermore, an avalanche reference data set is included and the python scripts used to perform the processing steps and the classification.

avalanche-activity

display_name: avalanche-activity

hidden-markov-model

display_name: hidden-markov-model

monitoring

display_name: monitoring

seismic

display_name: seismic

en: Automatic detection of avalanches


disdrometer-data-laret

maintainer: Daniel Wolfensberger

title_for_slug: disdrometer-data-laret

en: disdrometer hydrometeors visibility raclets precipitation

en: Disdrometer Data Laret

en: The zip folder contains one netCDF file per day for Laret from February 7 to March 29 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Laret_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

en:
A laser optical disdrometer (Parsivel² , OTT Hydromet) was used to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms.
The dataset contains information on precipitation amount and type for the period of February 7 to March 29 2019 in Laret.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal


maintainer: Leo Gallus Bont

en: seilaplan forest qgis geoprocessing openstreetmap accessible-forest

en: Railways vector data (close to the sample forest range)

en: Forest vector data (for sample forest range)

en: Power lines vector data (close to the area of the sample forest range)

en: Juypter Notebook for Data Preparation

media_type: ipynb

en: DEM (for the area of the sample forest range)

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Preview

en: Digitised sample perimeter

en: Juypter Notebook for Data Preparation (online)

en:
This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps).
The purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin [Seilaplan]( https://doi.org/10.16904/envidat.software.1) for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting.
The vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019.

Additional notes for vector data:
Please note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API - https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any perimeter or area can be digitised freely using the QGIS editing toolbar.

The DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are:

- Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM)
- Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif

This methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed.

Additional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range.

This sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.

accessible-forest

display_name: accessible-forest

forest

display_name: forest

geoprocessing

display_name: geoprocessing

openstreetmap

display_name: openstreetmap

qgis

display_name: qgis

seilaplan

display_name: seilaplan

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: Sample Geodata and Software for Demonstrating Geospatial Preprocessing for Forest Accessibility and Wood Harvesting at FOSS4G2019


maintainer: Anita C. Risch

en: herbivory grassland native-plant weed-management non-native-plant

en: Correction: Data file native and non-native plant interactions in Australian grasslands

media_type: XLSX

en:
taxa tab:	list and overview of all the recorded species

* family:                 family of the plant

* genus:                genus of the plant

* species:                plant species name

* origin:                indicates whether the plant is native to Australia or not (non-native)

* common name:	        common name of the plant species

* functional group:	        functional group of the plant species: forb, graminoid, fern, tree

* functional group detailed:	gives more detail about the type of graminoid and forb: legume, forb (non-leguminous),
                        grass, sedge, rush, fern, tree

* lifeform:                annual or perennial lifeform (species which can have both of these lifeforms where
                        considered as annuals)

plot tab:	list of species found in each plot and their cover (%)

* sampling.session:        provides information about the sampling time:
                        May2020 = data that was collected in May 2020
                        Nov2020 = data that was collected in November 2020

* farm.name:	            name of the farms where the sampling took place:
                        SF = farm of the Southern group
                        NF = farm of the Northern group
                        numbers 1-3 = randomly allocated to the Southern group of farms
                        numbers 4-6 = randomly allocated to the Northern group of farms

* site.type:	                KG: Kangaroo grass dominated site
                        ALG: ALG+KG site (Kangarooo grass and African lovegrass co-dominated site)

* plot.no:                plot number: 9-12

* scientific.name:	        scientific name of the plant species found in a certain plot

* functional group:	        indicates whether the species found is a tree, forb, graminoid or fern

* functional group detailed:	indicates whether the species found is a tree, legume, forb (non-leguminous),
                        grass, sedge, rush, fern

* lifeform:                specifies the lifeform of the species: annual or perennial lifeform
                        (species which can have both of these lifeforms where considered as annuals)

corrections tab:	Detailed description of corrections made in plot.data tab

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

Paper Citation:

_Schlierenzauer, C., Risch, A.C., Schütz, M., Firn, J. 2021. Non-native Eragrostis curvula reduces plant species diversity in pastures of South-eastern Australia even when native Themeda triandra remains co-dominant. Plants 10, 596._

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

Study area
The study was conducted in the lowland grassy woodlands of the Bega Valley Region, which is located in the south-east corner of New South Wales, Australia. Embedded between the Pacific Ocean and the Australian Alps, the lowland grassy woodlands are mostly located on granitic substrates and reach elevations of roughly 500 m above sea level. Typically, these grassy woodlands receive less precipitation (mean annual precipitation between 700-1100 mm) compared to the more elevated areas that surround them (NSW Government - Office of Environment and Heritage 2017).
The vegetation is dominated by an open tree canopy layer consisting of Eucalyptus tereticornis Sm, Angophora floribunda Sm. (Sweet) and a range of other eucalypt species. Sometimes shrub or small trees are also present, whereas grasses and forbs form the ground-cover. In areas without intensive agricultural history, this layer is dominated by perennial, tussock grasses such as Themeda triandra Forssk, Microlaena stipoides R.Br (Weeping Grass), Eragrostis leptostachya Steud. (Paddock Lovegrass) and Echinopogon ovatus P.Beauv (Forest Hedgehog Grass). The remaining inter-tussock spaces are occupied by a diversity of growth-restricted grasses and herbaceous forbs (NSW - Department of Planing, Industries and Environment 2019; NSW Government - Office of Environment and Heritage 2017).
Clearing, pasture sowing, fertilizer application and livestock grazing resulted in a dramatic decrease in the extent of these natural woodlands, with less than five percent within conservation reserves and overall, with only about 20% of their original extent in New South Wales still existing (Tozer et al. 2010). The remaining areas outside of reserves are threatened by altered fire frequencies, habitat clearing, livestock grazing and especially by non-native plant invasion, particularly Eragrostis curvula (Schrad.) Nees. For this reason, the grassy woodlands are listed as an endangered ecological community in the NSW state legislation. Additionally, they are considered as critically endangered by the Commonwealth of Australia (Threatened Species Scientific Committee (TSSC) 2013).

Experimental design and sampling
The study was conducted on six farms and in each of them two sites were chosen, representing a paired design. One of the sites at each farm is dominated by native Themeda triandra, the other one co-dominated by non-native Eragrostis curvula and Themeda triandra. All farms are within a radius of approximately 10 km from the town Candelo. Three of the farms are located North (36°40’ to 36°42’ S and 149°38’ to 149°42’ E) and three of them are located South (36°51’ to 36°49’ S and 149°38’ to 149°42’ E) of Candelo.
Non-native herbivores (mainly cattle, sheep and rabbits) and native herbivorous marsupials (mainly kangaroos, wallabies and wombats) are present in the area of these sites. On each site, data was collected within four plots (each 1 x 1 m) in May and November 2020. All plant species found within a plot were recorded and their relative abundance was estimated.

References
NSW - Department of Planing, Industries and Environment. 2019. “Lowland Grassy Woodland in the South East Corner Bioregion - Endangered Ecological Community Listing.” https://www.environment.nsw.gov.au/topics/animals-and-plants/threatened-species/nsw-threatened-species-scientific-committee/determinations/final-determinations/2004-2007/lowland-grassy-woodland-south-east-corner-bioregion-endangered-ecological-community-l (February 18, 2021).
NSW Government - Office of Environment and Heritage. 2017. “Lowland Grassy Woodland in the South East Corner Bioregion - Profile.” https://www.environment.nsw.gov.au/threatenedSpeciesApp/profile.aspx?id=20070 (January 31, 2021).
Threatened Species Scientific Committee (TSSC). 2013. Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) Conservation Advice for Lowland Grassy Woodland in the South East Corner Bioregion. http://www.environment.gov.au/biodiversity/threatened/communities/pubs/82-conservation-advice.pdf.
Tozer, Mark et al. 2010. “Native Vegetation of Southeast NSW: A Revised Classification and Map for the Coast and Eastern Tablelands.” Cunninghamia : a journal of plant ecology for eastern Australia 11(3): 359–406.

grassland

display_name: grassland

herbivory

display_name: herbivory

native-plant

display_name: native-plant

non-native-plant

display_name: non-native-plant

weed-management

display_name: weed-management

en: Native and no-native plant interactions in Australian grasslands


high-resolution-climate-data-for-europe

title_for_slug: high-resolution-climate-data-for-europe

en: maximum-temperature eur11 air-temperature europe precipitation cordex daily-climate minimum-temperature

en: CHELSA EUR11 Technical Documentation

media_type: PDF

en: As the CHELSA project is continuously expanded, certain new parameters, time scales etc. are not included anymore in the original publication (Karger et al. 2017). We are therefore provide this document as a guideline of the current climatic parameters available and will expand it as new parameters or time periods will become available. Please refer to the version history for changes made in the document.

en: Data Access

media_type: NetCDF

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present downscaled climate data for the CORDEX EUR11 domain at a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperature lapse rates. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height. The resulting data consist of a daily temperature and precipitation timeseries.

The data is distributed under a: Creative Commons: Attribution 4.0 International (CC BY 4.0) license.

air-temperature

display_name: air-temperature

cordex

display_name: cordex

daily-climate

display_name: daily-climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

en: High resolution climate data for Europe


maintainer: Athanasios Nenes

en: cloud-modeling sigma-w supersaturation cloud-droplets raclets wolfgangpass

en: Predicted cloud droplet numbers (kappa=0.1) Davos Wolfgang

media_type: text/csv

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.1 is assumed, which is the lower limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

mimetype: text/csv

en: Predicted cloud droplet numbers (kappa=0.25) Weissfluhjoch

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.25 is assumed, which is the upper limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

en: Cloud droplet properties were predicted between February 24 and March 8 2019 for the measurement site Davos Wolfgang (1630 m a.s.l., LON: 9.853594, LAT: 46.835577). Droplet calculations are carried out with the physically based aerosol activation parameterization of Morales and Nenes (2014), employing the “characteristic velocity” approach of Morales and Nenes (2010). Aerosol size distribution observations required to predict the cloud droplet numbers and maximum in-cloud supersaturation are obtained from a Scanning Mobility Particle Size Spectrometer (SMPS) instrument deployed at Davos Wolfgang (https://www.envidat.ch/dataset/aerosol-data-davos-wolfgang). The required vertical velocity measurements are derived from the wind Doppler Lidar (https://www.envidat.ch/dataset/lidar-wind-profiler-data) deployed at the same station and are extracted from the first bin of the instrument, being 200 m above ground level. The hygroscopic properties of the particles measured at Davos Wolfgang could not be estimated, owing to a lack of concurrent CCN measurements. As a sensitivity test, droplet calculations are performed assuming two different values of the aerosol hygroscopicity parameter, 0.1 and 0.25, based on the analysis carried out for Weissfluhjoch. Additional information can be found in Section 2.3 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

cloud-droplets

display_name: cloud-droplets

cloud-modeling

display_name: cloud-modeling

raclets

display_name: raclets

sigma-w

display_name: sigma-w

supersaturation

display_name: supersaturation

wolfgangpass

display_name: wolfgangpass

en: Predicted cloud droplet numbers Davos Wolfgang


en: europe urban-region spatial-information strategic-plans development-priorities

en: Planning intentios

en:
The present dataset is part of the report titled Gradinaru S.R., Hersperger A.M., Schmid F. (2021). Deriving Planning Intentions from written planning documents. Report on CONCUR Project- From plans to land change: how strategic spatial planning contributes to the development of urban regions.
The data corresponds to the data collected as part of the DPI Method for deriving all PIs contained in a plan (open coding) as detailed in section 4 of the report. The method involved reading the plans to break down of information in meaningful discrete “incidents” or planning intentions. To identify the planning intentions, the starting points were represented by a) the structuring of the plans in chapters and sub chapters and b) the themes that the plans addressed. Thus, the collected information was not grouped according to pre-defined categories of planning intentions, but rather put together as a list of intentions as revealed by each plan. As a result, we provide, for each case study, a document (named [Urban region name] PI as defined in the plan) which contains:
	Date when the information was filled in.
	Name of the urban region and analysed strategic spatial plan .
	A list of all planning intentions contained in a plan, with each PI being addresses as follows:
	Name of PI as it appears in the plan
	Translated name of the PI (i.e. short name for easy understanding of the meaning)
	Explanation regarding the meaning of the PI
	Why the PI is considered a priority for the urban region
	Spatial information on the PI (text and cartographic representations).
In total, 14 documents are available, one for each case study. Documents contain up to 20 pages of information extracted from the plans together with explanations and notes taken during plan reading.

development-priorities

display_name: development-priorities

spatial-information

display_name: spatial-information

strategic-plans

display_name: strategic-plans

urban-region

display_name: urban-region

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: Planning intentions in strategic plans of European urban regions


maintainer: Achille Capelli

en: gnss liquid-water-content snow-water-equivalent swe lwc gps snow

en: Daily data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: GNSS derived SWE, LWC and HS from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-20

en: Webcam images

en: Webcam images showing some typical differences in the snow conditions at the four sites (Küblis, Klosters, Laret and Weissfluhjoch) for two time periods (14-18.3.2019 and 27.1-11.2.2020). Both time periods included a precipitation event with partial rain-on–snow occurring at the lower locations.

en: Snow profiles data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: Daily data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: GNSS derived data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Snow and meteo data from automatic sensors from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: Snow profiles data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: GNSS derived SWE, HS, and LWC for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Snow and meteo data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: Daily observer data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Profile data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Snow profiles data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Snow and meteo data from automatic sensors for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en: Snow and meteo data from automatic sensors for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en: Manual profiles

media_type: .zip

en: Data of the traditional manual profiles for the locations Weissfluhjoch, Klosters and Küblis. For the location of Küblis there are no traditional manual profile data. We provided the data as both PDF and .CAAML format (See https://niviz.org/ or http://caaml.org/Schemas/V5.0/Profiles/SnowProfileIACS/CAAMLv5_SnowProfileIACS.pdf). Moreover, we added LWC and density profiles when available (all locations).

en: Daily observer data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en: GNSS derived SWE, LWC and HS from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-20

en: Daily observer data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en: Daily data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: Daily data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en: This database contains GNSS derived snow water equivalent (SWE), liquid water content (LWC), and snow height (HS) and reference data collected during the two winter 2018-2020 at 4 sites Weissfluhjoch (2540 m asl, 46°49’47’’ N, 9°48’34’’E), Laret (1515 m asl, . 46°50’2’’N, 9°52’17’’E), Klosters (1200 m asl, 46°51’49’’N, 9°53’17’’E), and Küblis (815 m asl, 46°54’48’’N, 9°46’54’’E).

gnss

display_name: gnss

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

lwc

display_name: lwc

snow

display_name: snow

en: Snow water equivalent measurements with low-cost GNSS receivers along a steep elevation gradient in the East-ern Swiss Alps


maintainer: Océane Hames

en: mosaic arctic-sea-ice snow-deposition openfoam snow-transport

en: snowBedFoam 1.0.

en:
OpenFOAM-2.3.0. scripts containing the implemented Eulerian-Lagrangian snow transport model.

The code file provided here is not updated. The most recent version of the script can be found on the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/atmospheric-models/snowbedfoam-v1-0.git

en: MOSAiC Met City preliminary (Level 2) wind data

media_type: zip-compressed folder of csv

en:
Extract from the preliminary MOSAiC atmospheric data (Level 2) for the time period 6th to 13th of November, 2019.
This data was used to set up the fluid forcing parameters in the snowBedFoam simulations on MOSAiC sea ice. It is being published in this repository with the kind permission from Matthew Shupe and his team.
The final processed and quality controlled version of this dataset (Level 3) has not been published yet. A complete reference will be added in this description once it is released.

en: Paper Draft

en: This is the initial draft of the paper where the snowBedFoam 1.0. results are tested against Terrestrial Laser Scan (TLS) measurements of snow dynamics on Arctic sea ice (MOSAiC expedition). It highlights the numerical limitations of our model as well as the measurement uncertainties, which may occur in such extreme environments.

en:
snowBedFoam 1.0. is a snow transport solver implemented in the Computational Fluid Dynamics (CFD) software OpenFOAM. It is adapted from the standard multi-phase flow solver DPMFoam for application in snow-influenced environments.

To simulate aeolian snow transport, snowBedFoam 1.0. handles coupled Eulerian–Lagrangian phases, which involve a finite number of particles (snow) spread in a continuous phase (air). The snow erosion and deposition are modelled through physically-based equations such as the ones employed in the well-established LES-Lagrangian Stochastic Model (Comola and Lehning, 2017 ; Sharma et al., 2018). This modelling approach is computationally intensive and thus adapted to simulate snow movement and distribution on small scale terrain.

snowBedFoam 1.0. was tested against topographical data collected on Arctic sea ice during the MOSAiC expedition (Clemens-Sewall, 2021) . Together with atmospheric data from the MOSAiC Met City (Shupe et al., 2021) used for the fluid forcing, the model was able to accurately simulate the zones of erosion and deposition of snow along a complex ice ridge structure.

The core code of snowBedFoam 1.0. is also accessible on the WSL/SLF GitLab repository (more details in the Resources section).

arctic-sea-ice

display_name: arctic-sea-ice

mosaic

display_name: mosaic

openfoam

display_name: openfoam

snow-deposition

display_name: snow-deposition

snow-transport

display_name: snow-transport

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: snowBedFoam: an OpenFOAM Eulerian-Lagrangian solver for modelling snow transport


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

en: README

media_type: TXT

en: README file giving use metadata.

en: WFJ Snow Profiles 1999-2014

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

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

snow-density

display_name: snow-density

snow-ice-temperature

display_name: snow-ice-temperature

snow-stratigraphy

display_name: snow-stratigraphy

snow-water-equivalent

display_name: snow-water-equivalent

weisfluhjoch

display_name: weisfluhjoch

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


maintainer: Jana von Freyberg

en: stable-water-isotope hydrology stream-water catchment alptal precipitation

en: Data Set Documentation: alptal_Isotopes_daily_2015-2019_v2

media_type: .pdf

en: Documentations contains meta data of the data columns and information about the study catchments.

media_type: .txt

en:
Version 2 of the dataset contains additional information on:
- line-conditioned (lc) excess
- precipitation sample volumes
- isotope data quality

en: Single comma-separated txt-file with daily data of stable water isotopes measured in streamwater and precipitation in the Swiss Alptal catchment and two of its tributaries (Erlenbach and Vogelbach), as well as daily data of key hydrometeorological variables from the Alptal valley

en: This dataset contains four years of daily measurements of the natural isotopic composition (2H, 18O) of precipitation and stream water at the Alp catchment (area 47 km2) in Central Switzerland and two of its tributaries (0.73 km2 and 1.55 km2). In addition, the dataset contains daily measurements of key hydrometeorological variables.

alptal

display_name: alptal

catchment

display_name: catchment

hydrology

display_name: hydrology

precipitation

display_name: precipitation

stable-water-isotope

display_name: stable-water-isotope

stream-water

display_name: stream-water

en: Four years of daily stable water isotope data in stream water and precipitation from three Swiss catchments


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

en: 02. Questionnaire Data

en: 03. Publication Ready Data

en: 01. EDA Processed Data

en: 04. Scripts

en: 05. Visuals

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

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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


en: icecube snow intercomparison microct specific-surface-area

en: Grain survey of snow particles

en: tbd

en: TARTES simulations

en: Jupyter notebook with TARTES simulations.

en: Statistics of samples

en: IceCube and MicroCT data

en: The specific surface area (SSA) of different snow types were measured with the IceCube instrument and the Scanco Medical microCT 40. In addition, the snow particles created during the preparation of IceCube samples were counted. The difference in SSA between these instruments is explained by the formation of the surface particles. A numerical simulation using TARTES simulation support the observations.

icecube

display_name: icecube

intercomparison

display_name: intercomparison

microct

display_name: microct

snow

display_name: snow

specific-surface-area

display_name: specific-surface-area

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


maintainer: Michael Lehning

en: Data Source

media_type: R

en: Coordinates of Grid Points

en: Hourly Gridded Wind Power Time Series

en: Description

media_type: application/pdf

en: Full Data Description

en:
This dataset consist of simulated hourly power production from an Enercon E82 Turbine at 100 m hub-height. It describes the hourly power output a 1MW turbine would produce in each 0.01° grid cell for the years 2016 and 2017.

100 m wind speed data was taken from the COSMO-1 model (Consortium for Small-scale Modeling 2017), which has a 0.01° horizontal resolution. The domain covered is the whole of Switzerland, with the exclusion of lakes. As such, the number of 0.01◦ pixels within Switzerland amounts to 48657.
Conversion to power output was done based on the power curve of the Enercon E82 Turbine. As power output is lower at altitude due to lower air density, we corrected for this effect as described in (Kruyt et al. 2017).

Please cite the following paper in connection with the dataset:

Paper Citation:
 > _Bert Kruyt, Jérôme Dujardin, and Michael Lehning: Improvement of wind power assessment in complex terrain: The case of COSMO-1 in the Swiss Alps, Front. Energy Res., [doi:10.3389/fenrg.2018.00102] (https://doi.org/10.3389/fenrg.2018.00102)_

mountain-wind-potential

display_name: mountain-wind-potential

topography

display_name: topography

wind-energy

display_name: wind-energy

en: Dataset on Cosmo-1 based Energy Potential in Swiss Alps


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

de: orthofoto satellitenbild luftbild luftaufnahme dop

label: Geometadaten Kanton Zürich: GeoLion

label: geocat.ch permalink

spatial: Kanton Zürich

de: Download via GIS-Browser

de: Orthofoto Frühjahr (laubfrei) RGB/Infrarot 2021/22 Neben dem Bezug via GIS-Browser-Bestellung, ist es auch möglich die Daten via direktem File-Download unter dem Verzeichnis maps.zh.ch/download zu beziehen. Hinweise für das Digitalisieren ab Orthofotos: 1. Alle Objekte, die auf dem Boden aufliegen (z.B. Strassen, Wege, Markierungen, Schächte), lassen sich mit einer Präzision von 1-2 Pixeln digitalisieren (±5-10cm). Wird das Orthofoto in der Amtlichen Vermessung eingesetzt, dann dürfen nur nicht exakt definierte Punkte digitalisiert werden. 2. Die Brücken sind zwar im Geländemodell nicht enthalten und würden demnach nicht lagerichtig abgebildet, wurden aber manuell korrigiert und sind damit lagerichtig. 3. Dachflächen sind nicht Teil des Geländemodelles. Deshalb sind Dächer nicht lagerichtig abgebildet. Aufgrund der Schrägsicht im Originalbild, können Dächer den nahen, unterliegenden Boden verdecken. 4. Treppen in Unterführungen sind nicht Teil des Geländemodelles und werden daher nicht lagerichtig abgebildet. 5. Bäume sind im Geländemodell nicht enthalten und deren Lage wird daher im Orthofoto nicht korrekt abgebildet. Dies ist bei der Digitalisierung von Baumwipfeln entsprechend zu berücksichtigen (bei Anwendungen ausserhalb der AV). (mehr Informationen im PDF unter "Datengrundlage")

name:
Amt für Raumentwicklung
             - Geoinformation

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

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

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

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

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

political_level: canton

value: ZH - Geocat Harvester

de: Orthofoto Frühjahr RGB/Infrarot 2021/22


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: CSV

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

de: Energie

en: Energy

it: Energia

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).

political_level: confederation


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).


maintainer: Leonie Schönbeck

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

en: Pfynwald gas exchange

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

en: Methods light response

en: Methods and parameters for light response curves

en: Methods ACi curves

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

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

en: Instrument details

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

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

en: Methods fluorescence

en:
Parameters and methodology for Fluorescence measurements

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

en: Variable names and units

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

en: Methods diurnal measurements

en:
Parameters and methodology for diurnal measurements

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

en: Methods survey

media_type: .csv

en: Parameters and methods for point measurements / survey measurements

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

acclimation

display_name: acclimation

drought

display_name: drought

fluorescence

display_name: fluorescence

gas-exchange

display_name: gas-exchange

photosynthesis

display_name: photosynthesis

pinus-sylvestris

display_name: pinus-sylvestris

vpd

display_name: vpd

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

envidat

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

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

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.

en: 2013-2020 gas exchange at Pfynwald


geography

de: Geographie

en: Geography

territory

de: Raum und Umwelt

en: Territory and environment

fr: corps-executif planification-de-lespace-physique bordure bois planification

de: behorde raumplanung grenze wald planung

spatial: Kanton Bern (erweitert)

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: Thème du cadastre RDPPF L'ordonnance classe les jeux de géodonnées de base cantonales qui relèvent du domaine des plans d'affectation dans le cadastre des restrictions de droit public à la propriété foncière (cadastre RDPPF). Le thème du cadastre RDPPF suivantes se trouve dans le géoproduit NUPLWALD: - Limites forestières statiques (OGéo ID 157). **Le jeu de données est en construction et n'est pas encore disponible pour l'en-semble du canton de Berne.**.

de: ÖREB-Katasterthema Die kantonalen Geobasisdatensätze im Bereich Nutzungsplanung sind gemäss der Verordnung über den Kataster der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREBKV) Bestandteile des ÖREB-Katasters. Folgendes ÖREB-Katasterthema ist in diesem Geoprodukt NUPLWALD enthalten: - Statische Waldgrenzen (GeoIV ID 157). **Der Datensatz befindet sich im Aufbau und ist noch nicht flächendeckend für den ganzen Kanton Bern vorhanden. **

name: Amt für Wald und Naturgefahren - Fachdienste und Ressourcen

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: Limites forestières statiques

de: Statische Waldgrenzen


kommunale-nutzungsplanung

geography

fr: Géographie

fr: Territoire et environnement

title_for_slug: kommunale-nutzungsplanung

fr: protection-de-la-nature corps-executif risque-naturel planification-de-lespace-physique amenagement-du-paysage commune planification-regionale eaux-geographie cadastre amenagement-du-territoire bois polluant-sonore plan planification

de: naturschutz behorde naturgefahr raumplanung landschaftsplanung gemeinde regionalplanung gewasser kataster flachennutzungsplanung wald larmbelastung plan planung

spatial: Kanton Bern

fr: Thème du cadastre RDPPF L'ordonnance classe les jeux de géodonnées de base communales qui relèvent du domaine des plans d'affectation dans le cadastre des restrictions de droit public à la propriété foncière (cadastre RDPPF). Les thèmes du cadastre RDPPF suivantes se trouvent dans le géoproduit NUPLA: - Plans d'affectation communales (OGéo ID 73C), - Degré de sensibilité au bruit (OGéo ID 145), - Distances par rapport à la forêt communales (OGéo ID 159C). Les espaces réservés aux eaux déterminés par les communes se trouvent aussi dans le géoproduit (couches 'UEGEWRF: Espaces réservés aux eaux (surfaces)' et 'UEGEWRL: Espaces réservés aux eaux (lignes)'). **Le jeu de données est en construction et n'est pas encore disponible pour l'ensemble du canton de Berne.**

de: ÖREB-Katasterthema Die kommunalen Geobasisdatensätze im Bereich Nutzungsplanung sind gemäss der Verordnung über den Kataster der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREBKV) Bestandteile des ÖREB-Katasters. Folgende ÖREB-Katasterthemen sind in diesem Geoprodukt NUPLA enthalten: - Kommunale Nutzungsplanung (GeoIV ID 73C), - Lärmempfindlichkeitsstufen (GeoIV ID 145), - Kommunale Wald-Baulinien (GeoIV ID 159C). Enthalten sind auch die von den Gemeinden festgelegten Gewässerräume (Ebenen 'UEGEWRF: Gewässerraumflächen' und 'UEGEWRL: Gewässerraumlinien'). **Der Datensatz befindet sich im Aufbau und ist noch nicht flächendeckend für den ganzen Kanton Bern vorhanden. **

fr: Plans d'affectation communales

de: Kommunale Nutzungsplanung


lebensraum-quellen

title_for_slug: lebensraum-quellen

de: quelle biomonitoring okosystem

fr: État écologique de l'habitat des sources dans le canton de Berne - Résultats de la cartographie d'état selon la méthode bernoise, d'informations supplémentaires et portrait de la source.

de: Ökologischer Zustand des Lebensraumes der Quellen im Kanton Bern - Ergebnisse der Zustandskartierung nach der Berner Methode, weitere Angaben und Standortportrait.

fr: Habitat des sources

de: Lebensraum Quellen


wald-flora-und-fauna-des-kantons-bern

title_for_slug: wald-flora-und-fauna-des-kantons-bern

fr: desserte gibier chasse animal-sauvage gestion-des-forets conseil vegetation comportement-animal routes-forestieres bois trafic-motorise espace-vital gestion-forestiere

de: erschliessung wild jagd wildtier waldbewirtschaftung gutachten vegetation tierverhalten waldstrassen wald motorfahrzeugverkehr lebensraum forstwirtschaft

fr: Service d'image

de: Darstellungsdienst

format: WMS

fr: Le service représente les données de base du canton de Berne selon la géocatégorie G conforme à eCH-0166. Il comprend la carte de base de la desserte des forêts, l'expertise des dégâts du gibier, les grands prédateurs, l'information sur la fôret, le modèle de hauteur de végétation forêt (LIDAR), le plan des routes forestières ainsi que les zones de gestion du gibier.

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie G gemäss eCH-0166 dar. Er enthält die Datensätze Grossraubtiere, Grundlagenkarte Walderschliessung, Vegetationshöhenmodell Wald und Wildschadengutachten, Waldinformation, Waldstrassenplan sowie Wildräume.

fr: Forêt, flore et faune du canton de Berne

de: Wald, Flora und Fauna des Kantons Bern


fr: societe-de-distribution-deau etablissement-humain reseau-routier transport-prive collecte-des-dechets habitation animal-sauvage alimentation-en-eau infrastructure-routiere zone-de-protection-du-paysage concentration-de-peuplement industrie-de-traitement-des-dechets production-denergie parc-naturel-regional peche-a-la-ligne zone-de-developpement zone-de-montagne migration-pendulaire cascade sentier-de-randonnee zone-constructible besoin remise-en-culture paysage transport-de-voyageurs planification-et-developpement-urbain espace-de-loisirs developpement-urbain zone-construite registre-foncier eau-usee decomposition planification-de-lespace-physique degradation-des-ressources-naturelles planification-politique agriculture droit-de-propriete parc-naturel commune trafic planification-regionale eaux-geographie zonage transport-en-commun energie centrale-hydroelectrique epuration-des-eaux-usees energie-eolienne promotion-du-commerce-et-de-lindustrie cadastre incineration-des-dechets amenagement-du-territoire construction-hydraulique amenagement-du-territoire eaux-interieures projet tourisme developpement-durable rotation-des-cultures temps-libre planification itineraire matiere-premiere

de: wasserwerk siedlung strassennetz individualverkehr abfallsammlung wohnung wildtier wasserversorgung verkehrsinfrastruktur landschaftsschutzgebiet siedlungsverdichtung abfallbeseitigungsunternehmen energiegewinnung regionaler-naturpark angeln entwicklungsgebiet bergland pendelverkehr wasserfall wanderweg bauland bedarf rekultivierung landschaft personenverkehr stadtplanung-und--entwicklung erholungsgebiet stadtentwicklung baugebiet grundbuch abwasser abbau raumplanung abbau-von-naturlichen-ressourcen politikplanung landwirtschaft eigentumsordnung naturpark gemeinde verkehr regionalplanung gewasser zoneneinteilung offentlicher-verkehr energie wasserkraftwerk abwasserreinigung windenergie wirtschaftsforderung kataster abfallverbrennung flachennutzungsplanung wasserbau raumordnung-und--planung binnengewasser projekt fremdenverkehr nachhaltige-entwicklung fruchtfolge freizeit planung fahrweg-streckenfuhrung rohstoff

fr: Le service représente les données de base du canton de Berne selon la géocatégorie E conforme à eCH-0166. Il comprend l'aperçu du cadastre des conduites, la carte synoptique des zones 1:25'000, le développement durable dans les communes, les espaces réservés aux eaux approuvés, l'état actuel de la mensuration officielle, le plan cantonal d'aménagement des eaux, le plan sectoriel pour le trafic cycliste (y.c. informations complémentaires), le plan sectoriel itinéraires de randonnée pédestre (y.c. informations complémentaires), le projet cantonal d'aménagement du paysage, la protection des rives et des rivières selon la LRLR, les surfaces d'assolement du canton de Berne, les surfaces des terres cultivables, le système de gestion des zones d'activités, les territoires à habitat dispersé, les thèmes régionaux relatifs à l'urbanisation et au paysage ainsi que l'urbanisation interne. Les plans directeurs des éléments d'énergie, des éléments parcs naturels, des éléments urbanisation, des éléments d'approvisionnement et élimination, des éléments de transport, des éléments de la faune et des mesures régionales sont également inclus.

de: Der Dienst stellt Geobasisdatensätze des Kantons Bern der Geokategorie E gemäss eCH-0166 dar. Er enthält die Datensätze Arbeitszonenbewirtschaftung, Fruchtfolgeflächen, genehmigte Gewässerräume, Grundeigentumskategorien, kantonales Landschaftsentwicklungskonzept, kantonaler Wasserbauplan, Kulturlandflächen, nachhaltige Entwicklung in den Gemeinden, regionale Siedlungs- und Landschaftsthemen, Siedlungsentwicklung nach Innen, Sachplankarte Veloverkehr und Wanderroutennetz (inkl. informativer Inhalte), See- und Flussuferschutz gemäss SFG, Stand der amtlichen Vermessung, Streusiedlungsgebiete, Übersicht Leitungskataster und Übersichtszonenplan 1:25'000. Ausserdem enthalten sind die kantonalen Richtpläne Elemente Energie, Elemente Naturpärke, Elemente Siedlung, Elemente Ver- und Entsorgung, Elemente Verkehr, Elemente Wildtiere sowie regionale Massnahmen.

fr: Développement territorial et cadastre foncier du canton de Berne

de: Raumplanung und Grundstückskataster des Kantons Bern


parzellennummern

geography

de: Geographie

territory

de: Raum und Umwelt

title_for_slug: parzellennummern

de: grundbuch eigentumsordnung kataster

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: Le produit Numéros de parcelles contient les numéros géoréférencés de parcelles (bien-fonds ainsi que les droits distincts et permanents) du canton de Berne. Par le fait que les numéros de parcelles soient connues par leurs coordonnées (y et x), DIPANU permet de rechercher des parcelles dans le canton de Berne.

de: Das Produkt Parzellennummern beinhaltet die georeferenzierten Nummern von Grundstücken (Liegenschaften und Selbstständige, dauernde Rechte) im Kanton Bern. Dadurch, dass die Grundstücknummern mit ihren Koordinaten (y und x) abgelegt sind, dient DIPANU als Suchinstrument von Grundstücken innerhalb des Kantons Bern.

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

fr: Numéros de parcelles

de: Parzellennummern


gruda-av-export

geography

fr: Géographie

territory

fr: Territoire et environnement

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.

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.

fr: GRUDA MO Export

de: GRUDA AV Export


gebaudeadressen

title_for_slug: gebaudeadressen

fr: batiment liste-de-diffusion

de: gebaude adressenliste

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


amtliche-vermessung-vereinfacht

title_for_slug: amtliche-vermessung-vereinfacht

fr: cadastre planification

de: kataster planung

fr: Le géoproduit mensuration officielle simplifiée (MOPUBE) contient les données relatives à la structure de propriété et à l'utilisation du sol dans le canton de Berne. Ces données sont les plus précises disponibles actuellement. Elles se prêtent bien à un fond de plan pour la représentation d'informations thématiques. Le géoproduit mensuration officielle simplifiée est mis à jour chaque semaine ; il n'a pas de portée légale. Il constitue un sous-ensemble des données complètes de la mensuration officielle (MO). Il contient les données géométriques et les attributs des objets décrivant la propriété et l'utilisation du sol. Ces données sont à la base de la plupart des applications SIG. Elles ont été élaguées des informations plus détaillées n'intéressant principalement que les spécialistes de la mensuration cadastrale. Ce jeu de données comprend des extraits des couches d'information suivantes: points fixes, couverture du sol, objets divers, nomenclature, biens-fonds, divisions administratives et techniques de la mensuration officielle. La structure du geoproduit correspond à celle du modèle de données de la Confédération. Il a été toutefois complété avec des exigences cantonales.

de: Das Geoprodukt Amtliche Vermessung vereinfacht (MOPUBE) enthält die genauesten, verfügbaren Daten über Grund und Boden des Kantons Bern. Es eignet sich optimal  insbesondere die Bodenbedeckung und Liegenschaften  als Kartenhintergrund für die Darstellung thematischer Informationen. Das Geoprodukt Amtliche Vermessung vereinfacht wird wöchentlich aktualisiert; es besitzt keine Rechtswirkung. Es enthält eine Teilmenge der Daten der Amtlichen Vermessung (AV), namentlich diejenigen geometrischen und attributiven Daten zu Grund und Boden, die von den meisten GIS-Anwendern benötigt werden. Weitergehende Informationen, die vorwiegend Vermessungsspezialisten interessieren, werden weggelassen. Der Geodatensatz umfasst Auszüge aus den Informationsebenen Fixpunkte, Bodenbedeckung, Einzelobjekte, Nomenklatur, Liegenschaften, administrative und technische Einteilungen der Amtlichen Vermessung. Das Geoprodukt entspricht von der Struktur her dem Datenmodell «MOpublic» des Bundes. Es ist jedoch mit einigen kantonalen Anforderungen ergänzt worden.

fr: Mensuration officielle simplifiée

de: Amtliche Vermessung vereinfacht


stand-der-amtl-vermessung

geography

de: Geographie

title_for_slug: stand-der-amtl-vermessung

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: Etat actuel de la mensuration officielle

de: Stand der amtl. Vermessung


standorte-offentlicher-volksschulen

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

population

fr: Population

de: Bevölkerung

en: Population

it: Popolazione

title_for_slug: standorte-offentlicher-volksschulen

de: schulsozialarbeit tagesschule

fr: Lien vers le téléchargement de données (Zip)

de: Link zum Daten-Download (Zip)

fr: Sites des écoles publiques du canton de Berne avec des détails sur les offres de l'unité scolaire associée.

de: Schulstandorte der Volksschulen des Kantons Bern mit Angabe der Angebote an der zugehörenden Schulorganisationseinheit.

name: Amt für Kindergarten, Volksschule und Beratung

fr: Sites d'écoles publiques de la scolarité obligatoire

de: Standorte öffentlicher Volksschulen


qualitat-der-oberflachengewasser

geography

fr: Géographie

territory

fr: Territoire et environnement

de: Raum und Umwelt

title_for_slug: qualitat-der-oberflachengewasser

fr: analyse-de-leau eau-de-surface qualite-de-leau surveillance-de-leau fond-de-leau eaux-geographie diversite-biologique organisme-aquatique

de: wasseruntersuchung oberflachengewasser wassergute wasseruberwachung gewassersohle gewasser artenvielfalt wasserorganismen

fr: La qualité chimique et biologique de l'eau des ruisseaux, rivières et lacs est contrôlée régulièrement par la Laboratoire de la protection des eaux et du sol (GBL) du canton de Berne. Les résultats des mesures sont exploités et représentés selon les recommandations de la Confédération (système modulaire gradué, SMG).

de: Die chemische und biologische Wasserqualität von Fliessgewässern und Seen wird vom Gewässer- und Bodenschutzlabor des Kantons Bern regelmässig überprüft. Die Resultate werden gemäss Modulstufen-Konzept des Bundes (MSK) ausgewertet und dargestellt.

name: Amt für Wasser und Abfall - Gewässer- und Bodenschutzlabor / Umweltanalytik

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

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: Qualité des cours d'eau

de: Qualität der Oberflächengewässer


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: 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: Cadastre RDPPF du canton de Berne

de: ÖREB-Kataster des Kantons Bern


geography

de: Geographie

fr: bassin-versant precipitation-atmospherique eaux-geographie eaux-souterraines

de: gewassereinzugsgebiet niederschlag gewasser grundwasser

spatial: Schweiz

fr: Le géoproduit 'Réseau cantonal de mesure hydrométrique' comprend les point de mesure cantonaux des eaux de surface, des eaux souterraines, des jauges de dotation pour les prélèvements d'eau et des mesures hydrométriques ponctuelles. Des points de mesure météorologique sont également prévus.

de: Das Geoprodukt 'kantonales hydrometrisches Messstellennetz' umfasst die kantonalen Messstellen der Oberflächengewässer, des Grundwassers, der Pegellatten für Dotierwassermengen bei Wasserentnahmen, sowie punktuell durchgeführte hydrometrische Messungen. Zusätzlich werden auch die meteorologischen Messstellen bereitgestellt.

fr: Réseau cantonal de mesure hydrométrique


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: 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: 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


ubersicht-leitungskataster

fr: Géographie

territory

fr: Territoire et environnement

de: Raum und Umwelt

title_for_slug: ubersicht-leitungskataster

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

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: Aperçu du cadastre des conduites

de: Übersicht Leitungskataster