maintainer: Michael Lehning

en: Description

en: Full Data Description

mimetype: application/pdf

en: Data Source

en: Coordinates of Grid Points

en: Hourly Gridded Wind Power Time Series

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


soil-respiration-exclosure-experiment

maintainer: EnviDat Support

title_for_slug: soil-respiration-exclosure-experiment

en: grazing grassland soil-respiration subalpine ungulates

state: active

type: dataset

en: Soil respiration Switzerland

en:
ID: Fence number

Year	:Year of sampling

mean.CO2: soil respiration measured with PP-systems SRC-1 soil respriation chamber attached to a EGM-4 infrared gas analyser; units CO2 g m-2 h-1

Grassland: Grasslands where fences were errected. Note that on large grasslands (STAB, GRIM, MING) 2 pairs of fences were errected (2 in short, 2 in tall-grass vegetation), on small grasslands (DADA, MARG, BOTS) only one pair of fences was errected (1 short-grass; one-tallgrass vegetation)

Fence: Fence number; un-even numbers on short-grass vegetation (1,3,5,7,9,11,13,15,17), even numbers on tall-grass vegetation (2,4,6,8,10,12,14,16,18)

Vegetation:	1 = shortgrass vegetation, 2 = tall-grass vegetation (9 replicate fences on each vegetation type)

Treatment	: 1 = all herbivores grazing, 2 = large ungulates (red deer, chamois) excluded

format: XLS

en:
Location of data collection
The Swiss National Park (SNP) is located in the southeastern part of Switzerland, and covers an area of 170 km2, 50 km2 of which is forested, 33 km2 is occupied by alpine and 3 km2 by subalpine grasslands. Elevations range from 1350 to 3170 m a.s.l., and mean annual precipitation and temperature are 871 mm and 0.6°C measured at the Park’s weather station in Buffalora (1980 m a.s.l.) between 1960 and 2009 (MeteoSchweiz 2011). Founded in 1914, the SNP received minimal human disturbance for almost 100 years (no hunting, fishing, or camping, visitors are not allowed to leave the trails). Large (> 1 ha) homogeneous patches of short- and tall-grass vegetation characterize the subalpine grasslands. The average vegetation height of short-grass vegetation is 2 to 5 cm. Red fescue (Festuca rubra L.), quaking grass (Briza media L.) and common bent grass (Agrostis tenuis Sipthrob) are the predominating plant species in this vegetation type. Tussocks of evergreen sedge (Carex sempervirens Vill.) and mat grass (Nardus stricta L.) are predominant in the tall-grass vegetation, which averages 20 cm in vegetation height (Schütz and others 2006). Short-grass vegetation developed in areas where cattle and sheep rested (high nutrient input) during agricultural land-use (from 14th century until 1914); tall-grass vegetation developed in areas where cattle and sheep used to graze, but did not rest (Schütz and others 2003, 2006). Herbivores were shown to consume > 60% of the biomass in short-grass compared to < 20% in tall-grass vegetation (Schütz and others 2006). The herbivore community present in the SNP can be divided into four groups based on body size/weight: large [red deer (Cervus elaphus L.) and chamois (Rupricapra rupricapra L.); 30 - 150 kg], medium [marmot (Marmota marmota L.) and snow hare (Lepus timidus L.); 3 – 6 kg], and small vertebrate herbivores (small rodents: e.g. Clethrionomys spp., Microtus spp., Apodemus spp.; 30 – 100 g) as well as invertebrates (e.g. grasshoppers, caterpillars, cicadas, < 5 g).

Experimental design
We selected 18 subalpine grassland sites (9 short-grass, 9 tall-grass vegetation). The sites were spread across the entire park on dolomite parent material at altitudes of 1975 to 2300 meters. At each site we established an exclosure network (fences) in spring 2009 (early June), immediately after snowmelt. Each exclosure network consisted of a total of five 2 × 3 m sized plots that progressively excluded the different herbivores listed above (further labeled according to the herbivore guilds that had access to the respective plots “All”, “Marmot/Mice/Invertebrates”, “Mice/Invertebrates”, “Invertebrates”, “None”). The “All” treatment was thus accessible to all herbivores, was not fenced and was located at least 5 m away from a 2.1 m tall and 7 × 9 m main fence that enclosed the other four treatments. This fence was constructed of 10 × 10 cm wooden posts and electrical equestrian tape (AGRARO ECO, Landi, Bern, Switzerland; 20 mm width) mounted at 0.7 m, 0.95 m, 1.2 m, 1.5 m and 2.1 m above the ground that were connected to a solar charged battery (AGRARO Sunpower S250, Landi, Bern, Switzerland). We also mounted non-electrically charged equestrian tape at 0.5 m to help exclude deer and chamois, yet allow marmots and hares to enter safely. Within each main fenced area we randomly established four 2 × 3 m plots: (1) The “Marmot/Mice/Invertebrates” plot remained unfenced, thus, with the exception of red deer and chamois, all herbivores were able to access the plot, (2) The “Mice/Invertebrates” plot consisted of a 90 cm high electric sheep fence (AGRARO Weidezaunnetz ECO, Landi, Bern, Switzerland; mesh size 10 × 10 cm) connected to the solar panel and excluded all medium sized mammals (marmots, hares), but provided access for small mammals and invertebrates, (3) The “Invertebrates” plot provided access for invertebrates only and was surrounded by 1 m high metal mesh (Hortima AG, Hausen, Schweiz; mesh size 2 × 2 cm), (4) The “None” plot was surrounded by a 1 m tall mosquito net (Sala Ferramenta AG, Biasca, Switzerland; mesh size 1.5 × 2 mm) to exclude all herbivores. This plot was covered with a roof constructed of a wooden frame lined with mosquito mesh that was mounted on the wooden corner posts. We also treated this plot with a biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) when needed to remove insects that might have entered during data collection or that hatched from the soil.

!!! The here published data set only contains data for “All”, and “Marmot/Mice/Invertebrates” (= ungulates excluded) plots !!!

Data collection
In-situ soil CO2 emissions were measured with a PP-Systems SRC-1 soil respiration chamber (closed circuit) attached to a PP-Systems EGM-4 infrared gas analyzer (PP-Systems, Amesbury, MA, USA) on two randomly selected locations on one subplot within each of the 90 plots. For each measurement the soil chamber (15 cm high; 10 cm diameter) was placed on a permanently installed PVC collar (10 cm diameter) driven five centimeters into the soil at the beginning of the study (June 2009). The measurements were conducted between 0900 and 1700 hours every two weeks from early to early September 2009, 2010, 2011 and 2013. Freshly germinated plants growing within the PVC collars were removed prior to each measurement to avoid measuring plant respiration/photosynthesis. The two measurements collected per plot every two weeks were averaged.

Please acknowledge the funding of the study: funded by the Swiss National Science Foundation, SNF grant-no 31003A_122009/1 to Anita C. Risch, Martin Schütz and Flurin Filli

grassland

display_name: grassland

grazing

display_name: grazing

soil-respiration

display_name: soil-respiration

subalpine

display_name: subalpine

ungulates

display_name: ungulates

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

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: Soil respiration - exclosure experiment


en: whole-tree-volume branchwood allometric nfi model stemwood

en: Datasets for deriving functions for the stem- and branchwood volume in the Swiss National Forest Inventory

media_type: application/pdf

en: Documentation of the data and review in 2022.

format: PDF

en: linked data set with stem and branchwood data

en: Dataset comprising all measured variables in order to easily derive complete above-ground tree wood volume based on 38’841 trees including 14’038 trees with measured branchwood data.

format: SERVICE

en:
In the Swiss National Forest Inventory (NFI) the volume of the stem and of large (≥ 7cm in diameter) and small branches is estimated based on allometric functions. These functions were developed based on data collected within the permanent plot network of the Experimental Forest Management (EFM) sites at WSL (David I. Forrester; Hubert Schmid; Jens Nitzsche (2021). The Experimental Forest Management network. EnviDat. doi: 10.16904/envidat.213). The data were converted to digital format in two separate steps in the mid-1970s for stemwood and the mid-1980s for branchwood.
The dataset on stemwood volume contains 38’864 single tree data for the mean crosswise diameter at two meter sections along the stem plus an additional measurements at 1.3 m (i.e. DBH) where the diameter is greater than or equal to 7 cm (i.e. threshold of merchantable wood) and the lengths of the stem from the base to the threshold of merchantable wood and to the tree top. The measurements were collected on 768 EFM sites in the period 1888 to 1974. The dataset on branchwood is based on a subset of the stemwood data and contains in the raw format information on 14'712 single trees. It includes aggregated data from the stemwood dataset, i.e. the DBH, the stem-diameter at 7 m from the base, and the tree height from the base to the top, as well as the measured volume of large and small branches.
In 2022, the metadata of both datasets were checked, values were examined for plausibility and duplicated entries. Duplicates were removed as far as possible and the branchwood volume data were appended to the stemwood dataset to obtain a final, single file with matching single tree data. Following this evaluation the final dataset consisted of a total of 38’841 trees including 14’038 trees with measured branchwood data.

allometric

display_name: allometric

branchwood

display_name: branchwood

model

display_name: model

nfi

display_name: nfi

stemwood

display_name: stemwood

whole-tree-volume

display_name: whole-tree-volume


maintainer: Matthias Haeni

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

en: Forest station data (OTB)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Field station data (OTF)

en: Site photo of the field station (OTF)

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

mimetype: image/jpeg

en: Site aerial photo (Othmarsingen)

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

en: Site photo of the forest station (OTB)

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

en: Data plot of the field station (OTF)

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

en: Data plot of the forest station (OTB)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Othmarsingen in Switzerland where one station is located within a natural deciduous forest stand (OTB) with European beech (_Fagus sylvatica_; 120-140 yrs) and lime trees (_Tilia sp._; 120-140 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, OTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Othmarsingen is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


maintainer: Dirk Nikolaus Karger

en: reptiles generalized-linear-models sdm random-forests range-maps mammals iucn chelsa interannual-climate-variability niche-models generalized-additive-models amphibians climate-variablity species-distribution-models

en: File containing the record dimension, genus, and species of the respective netcdf files

en: Mammals

media_type: application/zip

en: Species distribution models based on different climate predictor groups

format: ZIP

en: Reptiles

media_type: text/plain

en: Readme file containing the file naming convention, file dimensions, and variable names

format: TXT

en: File containing the climate predictors as SAGA grid files (.sgrd)

en: Amphibians

en: We modelled the global distribution of 730 amphibian, 1276 reptile, and 1961 mammal species globally as a function of current climate at a 0.5° spatial resolution using four different predictor groups composed of different combinations of input variables: mean climatic conditions, spatial climatic variability, and temporal (interannual) climatic variability.

amphibians

display_name: amphibians

chelsa

display_name: chelsa

climate-variablity

display_name: climate-variablity

generalized-additive-models

display_name: generalized-additive-models

generalized-linear-models

display_name: generalized-linear-models

interannual-climate-variability

display_name: interannual-climate-variability

iucn

display_name: iucn

mammals

display_name: mammals

niche-models

display_name: niche-models

random-forests

display_name: random-forests

range-maps

display_name: range-maps

reptiles

display_name: reptiles

sdm

display_name: sdm

species-distribution-models

display_name: species-distribution-models

educ

en: Education, culture and sport

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: Global species distributions for mammals, reptiles, and amphibians


en: snow-cover-fraction snow-melt snow-water-equivalent snow-climatology operational-snow-hydrological-service

en: Data package

en: This dataset comprises the climatology on gridded data of snow water equivalent and snow melt runoff spanning 1998-2022, with a spatial resolution of 1 km and daily temporal resolution. This data was produced with the conceptual OSHD model (Temperature Index Model).

operational-snow-hydrological-service

display_name: operational-snow-hydrological-service

snow-climatology

display_name: snow-climatology

snow-cover-fraction

display_name: snow-cover-fraction

snow-melt

display_name: snow-melt

snow-water-equivalent

display_name: snow-water-equivalent

en: Climatological snow data since 1998, OSHD


tree-ring-laser-ablation-data

maintainer: Paula Ballikaya

title_for_slug: tree-ring-laser-ablation-data

en: air-pollution dendrochemistry dendrochronology tree-rings laser-ablation

en: Laser ablation data

en:
This dataset contains the values of several chemical elements (Mg, Al, Si, S, K, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, Tl, Pb, Bi) measured in the latewood of tree rings of Mongolian oak from Harbin, China, at a 5-year resolution. Due to the lack of a suitable reference material for wood, absolute concentration was not calculated, and the ratio between the chemical element and 13C was taken as proxy for the element signal.

In Harbin, one of the largest cities and most important industrial centers in northeastern China, air quality monitoring systems were built only by the end of 2015 to meet the national requirements. Thus, dendrochemical analyses could be used as a tool to complement for the lack of air quality data over longer periods of time, allowing for the reconstruction of the temporal trend of trace metals. Our main scopes were to: (a) assess the chemical composition of Quercus mongolica Fisch. ex Ledeb. tree rings from Harbin using a recently developed system of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), (b) identify the main chemical elements which
derived from air pollution and may be used as indicators over the period 1965–2020 in Harbin, while excluding those that were controlled by physiological processes in the tree, and (c) reconstruct the history of pollution in Harbin by comparing the tree-ring chemical composition of recent decades with that of previous decades, in trees growing in the highly polluted city of Harbin and in trees growing in a control site 90 km away from major pollution sources.

Briefly, the temporal trend of some elements was influenced by physiological factors, by environmental factors such as pollution, or influenced by both. Mg, K, Zn, Cu, Ni, Pb, As, Sr and Tl showed changes in pollution levels over time.

air-pollution

display_name: air-pollution

dendrochemistry

display_name: dendrochemistry

dendrochronology

display_name: dendrochronology

laser-ablation

display_name: laser-ablation

tree-rings

display_name: tree-rings

en: Tree-ring laser ablation data


maintainer: Leo Gallus Bont

en: openstreetmap qgis geoprocessing forest seilaplan accessible-forest

en: Juypter Notebook for Data Preparation

en: Preview

media_type: image/png

format: PNG

mimetype: image/png

en: Forest vector data (for sample forest range)

mimetype: application/zip

en: Juypter Notebook for Data Preparation (online)

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

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

en: Digitised sample perimeter

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

media_type: image/tiff

format: TIFF

mimetype: image/tiff

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

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


maintainer: Ueli Reber

en: environmental--policy policy-documents bgb switzerland text-corpus biodiversity policy-analysis

en: Replication files

en:
 Introduction

The ZIP file contains all data and code to replicate the analyses reported in the following paper.

Reber, U., Fischer, M., Ingold, K., Kienast, F., Hersperger, A. M., Grütter, R., & Benz, R. (2022). Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics. *Policy Sciences*. [https://doi.org/10.1007/s11077-022-09456-4](https://doi.org/10.1007/s11077-022-09456-4)

If you use any of the material included in this repository, please refer to the paper. If you use (parts of) the text corpus, please also refer to the sources used for its compilation listed below. The content of the texts may not be changed.

 Data folder

The data folder contains the following files.

* _corpus.parquet_: Text corpus of Swiss policy documents
* _dict_de.csv_: Biodiversity dictionary (German)
* _dict_fr.csv_: Biodiversity dictionary (French)
* _dict_it.csv_: Biodiversity dictionary (Italian)
* _topic_labels.csv_: labels/codes for policy sectors
* _topics.csv_: labels/codes for policy sectors

The corpus and the dictionary were compiled by the authors specifically for this project. The labels/codes for policy sectors are based on the [coding scheme](http://ws-old.parlament.ch/affairs/topics) of the Swiss Parliament.

 Text corpus

The text corpus consists of 439,984 Swiss policy documents in German, French, and Italian from 1999 to 2018. The corpus was compiled from the following source between 2020-10-01 and 2021-01-31.

* Transcripts and parliamentary businesses (e.g. questions, motions, parliamentary initiatives) via the [Web Services (WS)](https://www.parlament.ch/de/%C3%BCber-das-parlament/fakten-und-zahlen/open-data-web-services) provided by the Swiss Parliament
* The official compilation of federal legislation ("Amtliche Sammlung", AS) via [opendata.swiss](https://opendata.swiss/de/dataset/official-compilation-of-federal-legislation-bs-as-1947-2018) provided by the Swiss Federal Archives (SFA)
* The federal gazette ("Bundesblatt") via [fedlex.admin.ch](https://www.fedlex.admin.ch/de/fga/index)
* Decisions of federal courts via [entscheidsuche.ch (ES)](https://entscheidsuche.ch/)

The corpus is stored in a single data frame to use with R saved as [PARQUET](https://parquet.apache.org/) file (corpus.parquet). The data frame has the following structure.

* _text_id_: Unique identifier for each text (source information as prefix, e.g. "t_")
* _doc_type_: Document type (see coding scheme below)
* _branch_: Government branche (1 legislative, 2 executive, 3 judicative)
* _stage_: Stage of policy process (1 drafting, 2 introduction, 3 interpretation)
* _year_: Year of publication
* _topic_: Policy sector (coding scheme in separate file in data folder)
* _lang_: Language (de, fr, it)
* _text_: Text

The following list contains the coding scheme for the doc_type variable.

* 101: Federal gazette // Draft for public consultation ("Vernehmlassungsverfahren")
* 102: Federal gazette // Explanation of draft for parliament ("Botschaft")
* 103: Federal gazette // Strategy, action plan
* 104: Federal gazette // Federal council decree ("Bundesratsbeschluss")
* 105: Federal gazette // (Simple) Federal decree ("(Einfacher) Bundesbeschluss")
* 106: Federal gazette // General decree ("Allgemeinverfügung")
* 107: Federal gazette // Treaty ("Übereinkommen")
* 108: Federal gazette // Treaty ("Abkommen")
* 109: Federal gazette // Draft for parliament ("Entwurf")
* 110: Federal gazette // Report ("Bericht")
* 111: Federal gazette // Report of parliamentary comission ("Bericht")
* 112: Federal gazette // Report of federal council ("Bericht")
* 201: Parl. businesses // Submitted text
* 202: Parl. businesses // Reason text
* 203: Parl. businesses // Federal council response
* 204: Parl. businesses // Initial situation
* 205: Parl. businesses // Proceedings
* 301: Parl. transcripts // Speech of MP
* 302: Parl. transcripts // Speech of federal council
* 401: Federal legislation // Legal text of the official compilation (law, ordinances, etc.)
* 501: Court decisions // Federal Supreme Court
* 502: Court decisions // Federal Criminal Court
* 503: Court decisions // Federal Administrative Court

 Code folder

The code folder contains all R code for the analyses. The files are numbered chronologically.

* _1_classifier_training.R_: Training of classifiers for classification of policy sectors
* _2_classifier_application.R_: Classification of documents in corpus
* _3_dictionary_application.R_: Biodiversity indexing of documents in corpus
* _4_stm_truncation.R_: Truncation of indexed documents to keep only relevant parts
* _5_stm_translation.R_: Translation of FR and IT documents to DE
* _6_stm_model.R_: Preprocesssing and structural topic model
* _7_plots.R_: Plots and numbers as included in the paper

The code/functions folder contains custom functions used in the scripts, e.g. to support topic model interpretation.

Package versions and setup details are noted in the code files.

 Contact

Please direct any questions to Ueli Reber (ueli.reber@eawag.ch).

bgb

display_name: bgb

biodiversity

display_name: biodiversity

environmental--policy

display_name: environmental--policy

policy-analysis

display_name: policy-analysis

policy-documents

display_name: policy-documents

switzerland

display_name: switzerland

text-corpus

display_name: text-corpus

educ

en: Education, culture and sport

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: Replication files for "Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics"


maintainer: Marcus Schaub

en: lwf drought crown-condition tree irrigation forest dbh swiss-forest-lab tree-species diameter-at-breast-height scots-pine

en: Site photo 1

en: Shapefile	of measurement location

en: Long-term Irrigation	Experiment Pfynwald homepage

media_type: text/html

format: HTML

mimetype: text/html

en: Dataset

en: Site photo 3

en: Swiss Forest Health Inventory

en: Site photo 2

en: To study the performance of mature Scots pine (_Pinus sylvestris_ L.) under chronic drought conditions in comparison to their immediate physiological response to drought release, a controlled long-term and large-scale irrigation experiment has been set up in 2003. The experiment is located in a xeric mature Scots pine forest in the Pfynwald (46° 18' N, 7° 36' E, 615 m a.s.l.) in one of the driest inner-Alpine valleys of the European Alps, the Valais (mean annual temperature: 9.2°C, annual precipitation sum: 657 mm, both 1961-1990). Tree age is on average 100 years, the top height is 10.8 m and the stand density is 730 stems ha-1 with a basal area of 27.3 m2 ha-1. The forest is described as _Erico Pinetum sylvestris_ and the soil is a shallow pararendzina characterized by low water retention. The experimental site (1.2 ha; 800 trees) is split up into eight plots of 1'000 m2 each. During April-October, irrigation is applied on four randomly selected plots with sprinklers of 1 m height at night using water from an adjacent water channel. The amount of irrigation corresponds to a supplementary rainfall of 700 mm year-1. Trees in the other four plots grow under naturally dry conditions. Soil moisture has been monitored since the beginning of the project at 3 soil depths (10, 20 and 60 cm). The crown condition of each tree is being assessed each year since 2003. Tree measurement data such as diameter at breast height, tree height, and social status were assessed in 2002, 2009 and 2014. The duration of the irrigation experiment is planned for 20 years.

crown-condition

display_name: crown-condition

dbh

display_name: dbh

diameter-at-breast-height

display_name: diameter-at-breast-height

drought

display_name: drought

irrigation

display_name: irrigation

lwf

display_name: lwf

scots-pine

display_name: scots-pine

swiss-forest-lab

display_name: swiss-forest-lab

tree

display_name: tree

tree-species

display_name: tree-species

en: Tree measurements 2002-2016 from the long-term irrigation experiment Pfynwald, Switzerland


en: defense-chemistry cross-resistance ash-dieback fraxinus intraspecific-variation invasive-species emerald-ash-borer

en: Raw data-Publication cross-resistance in ash-New Phytologist

en:
What are the research data files about: Raw data on perfomance (dry weight, development and mortality) of emerald ash borer larvae used in published bioassays. Raw data on ash dieback leasion lenghts. Raw data on untargeted and targeted specialized ash metabolites.
Which methods were used: Bioassays in greenhouses and climate chambers to collect data on emerald ash borer and ash dieback perfomance. Phytochemical analyses on ash phloem for quantifiying specialized metabolites
When and where was the data created / extracted: Summer 2020-2021

en:
 What are the research data files about: Raw data on perfomance (dry weight, development and mortality) of emerald ash borer larvae used in published bioassays. Raw data on ash dieback leasion lenghts. Raw data on untargeted and targeted specialized ash metabolites.

Which methods were used: Bioassays in greenhouses and climate chambers to collect data on emerald ash borer and ash dieback perfomance. Phytochemical analyses on ash phloem for quantifiying specialized metabolites.

When and where was the data created / extracted: Summer 2020-2021

ash-dieback

display_name: ash-dieback

cross-resistance

display_name: cross-resistance

defense-chemistry

display_name: defense-chemistry

emerald-ash-borer

display_name: emerald-ash-borer

fraxinus

display_name: fraxinus

intraspecific-variation

display_name: intraspecific-variation

invasive-species

display_name: invasive-species

en: Raw data-Publication cross-resistance in ash - New Phytologist


maintainer: Paraskevi Georgakaki

en: ice-crystal-number-concentration ice-water-content wrf jungfraujoch swiss-alps blowing-snow secondary-ice-production liquid-water-content

en: Observational data

en:
The .zip file contains 6 .csv files including all microphysical measurements taken at the Jungfraujoch station during the two periods of interest:

* 25-28 January 2014 : northwesterly-winds (NW)
* 29 January - 1 February 2014 : southeasterly-winds (SE)

The total Ice Crystal Number Concentration (ICNC; reported in L⁻¹) is measured by the two-dimensional stereo hydrometeor spectrometer (2D-S; Lawson et al., 2006) over the size range 10-1280 μm. The total ice water content (IWC; reported in gm⁻³) is also derived by the 2D-S data using the Brown and Francis (1995) mass-diameter relationship. Finally, the quantification of the liquid water content (LWC; reported in gm⁻³) is based on the liquid droplet size distribution data derived from a DMT cloud droplet probe (CDP; Lance et al., 2010) over the size range 2-50 μm. The frequency of the measurements in the .csv files is 30 min, to match the output frequency of the model. Datetime is also reported in the files (DD/MM/YYYY h:mm) in UTC.

Acknowledgment: Collection and pre-processing of the microphysical measurements has been performed by Gary Lloyd (gary.lloyd@manchester.ac.uk). More details about the instrumentation during the CLACE2014 campaign can be found in Lloyd et al. (2015).

en: WRF outputs

en:
The .zip file contains all the NetCDF outputs produced by the mesoscale Weather Research and Forecasting (WRF) model (version: 4.0.1). Two case studies were simulated in this study, between 25-28 January 2014 (00:00 UTC) and 29 January - 1 February 2014 (00:00 UTC), respectively. The former is denoted as "NW" and the latter as "SE", owing to the prevailing wind conditions at the Jungfraujoch (JFJ) station.

The outputs come from the innermost domain of the simulations with a spatial resolution of 1 km and are extracted from the nearest to JFJ model grid point (46.55°N 7.98°E). The dimensions of each model variable is [145,100], which corresponds to time and height, respectively. The frequency of the outputs is 30 min. Note that the first 24 hours of each simulation (i.e., the first 48 outputs) were considered spin up time.

The following sets of sensitivity simulations were presented in this study:

* CNTRL_NW.nc, CNTRL_SE.nc : Sensitivity simulations performed with the default version of WRF
* DS_PHILL_NW.nc, DS_PHILL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Phillips et al. (2018)
* DS_SULL_NW.nc, DS_SULL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Sullivan et al. (2018)
* PHILL_NW.nc, PHILL_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Phillips et al. (2017)
* TAKAH_NW.nc, TAKAH_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Sullivan et al. (2018) based on Takahashi et al. (1995)
* TAKAHrim_NW.nc, TAKAHrim_SE.nc : Same set-up as before but applied only to collisions between rimed ice particles
* BIPS_Xk0_DY_NW.nc, BIPS_Xk0_DY_SE.nc : Sensitivity simulations including a source of Xk0 (either 10.0 or 100.0 L⁻¹) ice crystals with sizes of DY (either 10 or 100 μm) in the first atmospheric level of the model
* BIPS100_PHILL_NW.nc, BIPS100_PHILL_SE.nc : Sensitivity simulations where the combined effect of blowing snow and ice-ice collisional break-up is examined

en:
This repository contains all WRF model outputs and observational data sets used for the paper:
Georgakaki, P., Sotiropoulou, G., Vignon, É., Billault-Roux, A.-C., Berne, A., and Nenes, A.: Secondary ice production processes in wintertime alpine mixed-phase clouds, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-760, in review, 2021.

blowing-snow

display_name: blowing-snow

ice-crystal-number-concentration

display_name: ice-crystal-number-concentration

ice-water-content

display_name: ice-water-content

jungfraujoch

display_name: jungfraujoch

liquid-water-content

display_name: liquid-water-content

secondary-ice-production

display_name: secondary-ice-production

swiss-alps

display_name: swiss-alps

wrf

display_name: wrf

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Data for the publication "Secondary ice production processes in wintertime alpine mixed-phase clouds"


photogrammetric-drone-data-gruenbodeli

title_for_slug: photogrammetric-drone-data-gruenbodeli

en: wingtra photogrammetry drone-data orthophoto dsm snow-depth-mapping uav

en: Data Access

en:
- ortho (3 cm/25 mm resolution)
- DSM (10 cm resolution)
- HS (10 cm resolution)
- RGB images
- Agisoft Metashape Project Report

All products are also available as a cloud optimized geotiff.

en:
We conducted various drone flights at Grüenbödeli near Davos with the Sony RX1R II mounted on a Wingtra drone during 2020/21/22. The data was processed with the Agisoft Metashape Professional Software.
The following products are available for download:
- DSM 10cm resolution
- Orthomosaic 3cm/25mm resolution
- Snow Raster 10cm resolution
- original RGB images

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

snow-depth-mapping

display_name: snow-depth-mapping

uav

display_name: uav

wingtra

display_name: wingtra

en: Photogrammetric Drone Data Grüenbödeli


maintainer: Marco Moretti

en: zurich resource-availability bettergardens beekeeping gardens urban-biodiversity honeybees pollinator-experiment urbanization urban-ecosystems city4bees wild-bees

en:
The data contains the following columns:

  SiteID: numeric, the identity of the garden where the bee was sampled.
  Taxonname: character, species name
  Lecty: numeric discreet, a mesure of specialisation degree. Levels: 1 = monolectic; 2=oliolectic; 3=polilectic
  Pheno.start= numeric discreet, the starting week of the flying activity.
  Pheno.end= numeric discreet, the ending week of the flying activity.
  Pheno.duration=numeric discreet, Pheno.end - Pheno.start
  Daytime.activity = numeric continuous, individual-level measure of the day hour when the bee was sampled
  ITD = numeric continuous, individual-level measure of the InterTegular Distance, a metric of mobility in mm.
  Rel.tongue.length =numeric continuous, individual-level measure of the relative tongue length (Tongue length / ITD), a metric of specilaisation degree, in mm.

en: Metadata for the predictors and response dataset

en: Response and predictors used for the SEMs

en: Metadata for the predictor and response dataset

en:
Mean, standard deviation , minimum and maximum values of six functional traits. The data has the following structure:
- Bee_species: bee scientific name
- mean_trait: mean value
- sd_trait: standard deviation
_min_trait: minimum value
- max_trait: maximum value
- trait: the six traits used. ITD = Intertegular distance (mm); Pheno.duration = duration of the phenology; Pheno.start = start of the phenology; Pheno.end = end of the phenology; Rel.tongue.length= relative tongue length (mm); Daytime.activity = daily activity (h)
DistNichePart: functional dissimilarity in a multidimentional trait space defined by five traits between wild bee individuals of a wild bee species and the honeybee individuals. Values are at the species level.

en:
Cities are socio-ecological systems that filter and select species, thus establishing unique species assemblages and biotic interactions. Urban ecosystems can host richer wild bee communities than highly intensified agricultural areas, specifically in resource-rich urban green spaces such as allotment and family gardens. At the same time, urban beekeeping has boomed in many European cities, raising concerns that the fast addition of a large number of managed bees could deplete the existing floral resources, triggering competition between wild bees and honeybees. The data has been used to investigated the interplay between resource availability and the number of honeybees at local and landscape scales and how this relationship influences wild bee diversity.

This dataset contains the raw and processed data supporting the findings from the paper: "Low resource availability drives feeding niche partitioning between wild bees and honeybees in a European city".

The data contains:
1. Bee trait measurements at the species and individual-level of five functional traits.
2. The values of the feeding niche partitioning (functional dissimilarity to honeybees)
3. The predictors of resource availability and beekeeping intensity at local and landscape scales used in the modelling of the paper for the 23 experimental sites.

beekeeping

display_name: beekeeping

bettergardens

display_name: bettergardens

gardens

display_name: gardens

honeybees

display_name: honeybees

pollinator-experiment

display_name: pollinator-experiment

resource-availability

display_name: resource-availability

urban-biodiversity

display_name: urban-biodiversity

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wild-bees

display_name: wild-bees

zurich

display_name: zurich

en: Niche partitioning between wild bees and honeybees


en: frost-risk tree-phenology climate-warming climatic-water-balance swiss-forest-lab extreme-climatic-events dendrochronology

en: Tree ring width Picea abies Switzerland

en: Tree ring width Larix decidua Switzerland

en: Climate data of the corresponding sites

en: Climate data at daily resolution using DAYMET 100m resolution of the corresponding sites

en: Tree ring width Fagus sylvatica Switzerland

en: Tree ring width Quercus petraea/robur Switzerland

en: Tree rings width Abies alba Switzerland

en:
Raw tree ring data and climate used in the following paper:
Vitasse Y, Bottero A, Cailleret M et al. (2019) Contrasting resistance and resilience to extreme drought and late spring frost in five major European tree species. Glob Chang Biol, 25, 3781-3792.

climate-warming

display_name: climate-warming

climatic-water-balance

display_name: climatic-water-balance

dendrochronology

display_name: dendrochronology

extreme-climatic-events

display_name: extreme-climatic-events

frost-risk

display_name: frost-risk

swiss-forest-lab

display_name: swiss-forest-lab

tree-phenology

display_name: tree-phenology

educ

en: Education, culture and sport

en: Tree rings and climate data of four tree species in Switzerland


en: forest remote-sensing lebensraumkarte milieux-naturels shrub-forest typoch habitat wetlands ensemble-modelling modelling grassland random-forest lebensraum

en: The Habitat Map of Switzerland AG v1 20220316, Canton Aargau, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Aargau, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland ZH v1 20220316, Canton Zurich, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Zurich, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland BS v1 20220316, Canton Basel-Stadt, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Basel-Stadt, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland UR v1 20220316, Canton Uri, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Uri, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland BE v1 20220316, Canton Bern, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Bern, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland TG v1 20220316, Canton Thurgau, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Thurgau, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland VS v1 20220316, Canton Valais, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Valais, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland LU v1 20220316, Canton Lucerne, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Lucerne, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland SH v1 20220316, Canton Schaffhausen, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Schaffhausen, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland SO v1 20220316, Canton Solothurn, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Solothurn, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland BL v1 20220316, Canton Basel-Landschaft, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Basel-Landschaft, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland SG v1 20220316, Canton St Gallen, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton St Gallen, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland NW v1 20220316, Canton Nidwalden, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Nidwalden, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland ZG v1 20220316, Canton Zug, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Zug, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland OW v1 20220316, Canton Obwalden, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to the borders of canton Obwalden, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert)

en: The Habitat Map of Switzerland SZ v1 20220316, Canton Schwyz, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Schwyz, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland FR v1 20220316, Canton Fribourg, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Fribourg, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland GL v1 20220316, Canton Glarus, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Glarus, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland VD v1 20220316, Canton Vaud, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Vaud, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland TI v1 20220316, Canton Ticino, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Ticino, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland CH v1 20220316, file geodatabase

en:
The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert).
V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland GE v1 20220316, Canton Geneva, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Geneva, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland JU v1 20220316, Canton Jura, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Jura, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland GR v1 20220316, Canton Grisons, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Grisons, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland NE v1 20220316, Canton Neuchatel, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Neuchatel, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland AR v1 20220316, Canton Appenzell Ausserrhoden , file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Appenzell Ausserrhoden, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: The Habitat Map of Switzerland AI v1 20220316, Canton  Appenzell Innerrhoden, file geodatabase (zipped)

en: The Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only. Available here is the dataset clipped to a 2km buffer around the borders of canton Appenzell Innerrhoden, as a zipped folder containing a file geodatabase (.gdb, ArcGIS), the data description document (pdf) and symbology layer (lyr, lyrx, qlr) for the legend as the data appears on the WSL's virtual data centre (https://vdc.wsl.ch/vdc_expert). V1 20220316 has been improved (from V1 20211118) to repair geometry errors, and simplify geometry to reduce data size

en: Data Description

en: Metadata document describing the methodology used to develop the dataset

en:
Lebensraumkarte der Schweiz/La carte des milieux naturels de Suisse
The FOEN funded project ‘Developing a Habitat Map of Switzerland’ conducted at the WSL, has produced a map of Swiss habitats according to the TypoCH classification (Delarze et al. 2015) wall-to-wall across the whole of Switzerland, to at least the classification’s 2nd level of detail (where possible to the 3rd level of detail). The implementation of the Habitat Map of Switzerland is a vector data set, where each polygon of the dataset is classified to one habitat type only.
Habitats are mapped through a variety of approaches that can be grouped as either:
1: Derived from the existing Swiss-wide high quality landcover mapping from Swisstopo’s Topographical Landscape Model (TLM), 2: Modelled within the project using Random Forest or Ensemble Modelling techniques to model the spatial distribution of individual habitat types, 3: Combining existing species distribution models to determine habitat types, or 4: Classification with relatively simple rule-sets based on auxiliary spatial datasets, i.e. vegetation height models, the digital terrain model, the normalised difference vegetation index (NDVI) derived from aerial imagery and/or time-series of growing season Sentinel-2 satellite imagery. Further detail on the methodology can be found within the README document.

ensemble-modelling

display_name: ensemble-modelling

forest

display_name: forest

grassland

display_name: grassland

habitat

display_name: habitat

lebensraum

display_name: lebensraum

lebensraumkarte

display_name: lebensraumkarte

milieux-naturels

display_name: milieux-naturels

modelling

display_name: modelling

random-forest

display_name: random-forest

remote-sensing

display_name: remote-sensing

shrub-forest

display_name: shrub-forest

typoch

display_name: typoch

wetlands

display_name: wetlands

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: southern-switzerland spei dendroecology drought-stress grapevine-yellows

en: Dataset 1

en: Sample identification, symptomatology (symptomatic vs. asymptomatic), coordinates (CH1903), phloem disarrangement class, drought-sensitivity, slope sector.

en: Dataset 2. Ring width.

en:
Ring width measured with cellSens from slides.
Measures expressed as [μm] and arranged per ID (see dataset 1) and year.

en:
Dataset collected from dendroecological study on trunks of grapevines ('Chardonnay' cv.) infected by the "Flavescence dorée" phytoplasma (FDp) in Origlio (southern Switzerland) in 2019-2020. Ring widths were measured with cellSens (Olympus Corporation). Calculations and analysis were conducted within R.
The Flavescence dorée phytoplasma (FDp) causes a severe grapevine (Vitis vinifera) disease. Anatomical modification due to FDp infections are known to occur but research so far focused on stems and leaf tissues and, in particular, on their phloem structure. In this paper, we applied dendrochronological techniques on wood rings and analysed the anatomical structures of the trunk of the susceptible grapevine cultivar ‘Chardonnay’ in order to verify their response to FDp infections.
In this study, we tested the impact of FDp and drought stress on xylem ring width and also described phloem anomalies inside the trunk of grapevines. We concluded that drought and FDp infection both have a significant effect on ring width reductions and that FDp supersedes the effect of drought conditions (calculated after the SPEI index) in infected specimens.

dendroecology

display_name: dendroecology

drought-stress

display_name: drought-stress

grapevine-yellows

display_name: grapevine-yellows

southern-switzerland

display_name: southern-switzerland

spei

display_name: spei

educ

en: Education, culture and sport

en: Impact of the “Flavescence dorée” phytoplasma on xylem growth and phloem anomalies in trunks of ‘Chardonnay’ grapevines (Vitis vinifera)


maintainer: Ionuț Iosifescu Enescu

en: Bulk Data Access

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

en: map preview 0.5MB

en: map 0.2GB

en: huge map 100GB

en: map 1GB

en: map 0.5GB

en: map 2GB

en: large map 10GB

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

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

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis

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


maintainer: Esther R. Frei

en: stillberg treeline g-tree larix-decidua climate-change forest picea-abies seedling-recruitment swiss-alps

en: GTREE Website

en: climate data G-TREE experiment, Davos, Switzerland

mimetype: text/plain

en:
 Background information
Climate change-induced range expansion of treeline populations depends on their successful recruitment, which requires dispersal of viable seeds followed by successful establishment of individual propagules. The Global Treeline Range Expansion Experiment (G-TREE) is a global initiative involving researchers from Europe, North America, Australia and New Zealand (Brown et al., 2013). At 15 alpine and Arctic treeline sites worldwide the mechanisms determining the elevational and latitudinal distribution of tree populations are studied using a standardized experimental approach. In summer 2013, a multifactorial seedling recruitment experiment has been established at the Stillberg ecological treeline research site. The aim of this experiment, is to quantify the effect of multiple abiotic and biotic drivers on emergence, survival, and growth of *Larix decidua* and *Picea abies* seedlings in replicated plots along an elevation gradient with three sites below (1930 m a.s.l.), at (2090 m a.s.l.), and above treeline (2410 m a.s.l.; Frei et al., 2018). All plots have been surveyed annually to count seedlings and to measure their total height. Additional environmental factors, such as soil temperature, have been recorded.

 Experimental design
The Stillberg research area is located in the Eastern Swiss Alps near Davos, Switzerland. The site has been used for several long-term monitoring as well as experimental studies for the last four decades. Our G-TREE experiment consists of a lowest site located in a subalpine Larch-Spruce forest (*Larici-Picetum*) dominated by *Larix decidua* and *Picea abies* (1930 m a.s.l.), a transition zone site dominated by alpine shrubs (2100 m a.s.l.), and an uppermost site in an alpine meadow with some dwarf shrubs (2390 m a.s.l.). The three experimental sites were set up following the standard protocol of the global G-TREE initiative (Brown et al., 2013). In a split-plot design, 20 plots (224 cm × 45 cm) were established at each site, which were randomly assigned to the 2 × 2 treatment combinations of the main factors seeding and scarification (i.e. seeding and scarification, seeding only, scarification only, and full control), resulting in five replications per main treatment combination. Each plot was divided into 16 split-plots (22.5 cm × 28 cm), to which treatment combinations of four additional two-level factors species (larch and spruce), provenance (low- and high-elevation), herbivore exclosure (with and without exclosure), and seeding year (2013, 2014) were randomly assigned, which resulted in a total of 960 split-plots (Details see Frei et al. 2018).

 Data description
All plots have been surveyed annually to count seedlings and to measure their total height. Seedling height was assessed with a hand ruler as the total length from the original emerging point to the apical meristem (Details see Frei et al. 2018). Additionally, soil temperature at each site, has been continuously recorded since 2013. Here, we present data from eight years (2013–2021).

climate-change

display_name: climate-change

forest

display_name: forest

g-tree

display_name: g-tree

larix-decidua

display_name: larix-decidua

picea-abies

display_name: picea-abies

seedling-recruitment

display_name: seedling-recruitment

stillberg

display_name: stillberg

swiss-alps

display_name: swiss-alps

treeline

display_name: treeline

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: G-TREE: Global Treeline Range Expansion Experiment Davos, Switzerland


en: long-term-monitoring ozone long-term-forest-ecosystem-research wdb swiss-forest-lab

en: Data request

en: In order to quantify effects of ozone on Swiss forest ozone flux calculations are needed. Currently 5 stations are operated to measure the ozone load on forests. These data form the basis for ozone flux calculations. The ozone flux calculation is carried out with the DO3SE model (Büker et al. 2012). This can then be used for epidemiological evaluations for the Swiss forest (Thomas et al. 2005, Braun et al. 2014, Braun et al. 2017, Braun et al. 2020, Braun et al. 2021, Braun et al. 2022).

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

long-term-monitoring

display_name: long-term-monitoring

ozone

display_name: ozone

swiss-forest-lab

display_name: swiss-forest-lab

wdb

display_name: wdb

educ

en: Education, culture and sport

en: Ozone measurement and analysis in the Intercantonal Forest Observation Program


swiss-municipal-spatial-planning-survey

title_for_slug: swiss-municipal-spatial-planning-survey

en: urban-sprawl densification policy-analysis settlement-development spatial-planning

en: Municipal Planning Survey

en: german

en: Municipal Planning Survey Data for SPSS

en: SPSS

en: francais

en: Glossary

en: Municipal Planning Survey Data for Stata

en: STATA 13

en: Survey of spatial planning instruments and the organization of land use planning in Swiss municipalities. In 2014, the survey was sent to all Swiss municipalities in letter and online form. The response rate of 69% (i.e. 1619 of 2352 municipalities at this time) results in a representative sample of Swiss municipalities. The survey contains questions on the implementation of 20 specific planning instruments and the decade they had been implemented at first, as well as details on the local planning regimes.

densification

display_name: densification

policy-analysis

display_name: policy-analysis

settlement-development

display_name: settlement-development

spatial-planning

display_name: spatial-planning

urban-sprawl

display_name: urban-sprawl

en: Swiss Municipal Spatial Planning Survey


en:
Number of stems of dead trees and shrubs (standing and lying) starting at 12 cm recorded according to the NFI1 method. In NFI1 only those dead trees were recorded whose wood could still be exploited. In addition, lying green trees were classified in NFI1 as deadwood.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

main-tree-species

display_name: main-tree-species

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

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: Stem number of dead wood NFI1


weather-station-davos-wolfgang

maintainer: Jörg Wieder

title_for_slug: weather-station-davos-wolfgang

en: pressure temperature weather relative-humidity raclets

en: Weather Station Davos Wolfgang

en: The data file contains date and time (YYYY-MM-DD hh:mm:ss) in UTC, temperature (°C), relative humidity (%), pressure (hPa) at 10 m above ground and above sea level. The data was averaged over 10 minutes.

en: The dataset contains weather parameters measured at Davos Wolfgang (LON: 9.853594, LAT: 46.835577).

pressure

display_name: pressure

raclets

display_name: raclets

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

weather

display_name: weather

educ

en: Education, culture and sport


en: swisstopo qgis-plugin seilaplan swiss-geodata cable-yarding digital-elevation-model geoinformation-software open-source digital-planning

en: View video on youtube!

en: Herunterladen des DHM von swisstopo Website

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. As an alternative to using the ‘Swiss Geo Downloader’ plugin, the DTM can be obtained directly from Swisstopo. In this tutorial we explain step by step how to download the necessary DTM from the Swisstopo Website, and how to use it in QGIS for the digital planning of a cable line using the plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to the elevation model on the swisstopo website: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.html#technische_details

Link to the rope map website: https://seilaplan.wsl.ch

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

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Als Alternative zum Swiss Geo Downloader erklären wir in diesem Tutorial Schritt für Schritt, wie man das nötige Höhenmodell von der Swisstopo Webseite herunterladen und in QGIS zur Seillinienplanung verwenden kann.

Link zum Höhenmodell auf der swisstopo Webseite: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.html#technische_details

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

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-software

display_name: geoinformation-software

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

swisstopo

display_name: swisstopo

en: Seilaplan Tutorial: DTM download from swisstopo website


maintainer: Benjamin Reuter

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

en: 2015-2016 Avalanche problem types from SNOWPACK

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

en: 1999-2017 Avalanche problem types from SNOWPACK

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

en: 1999-2017 Avalanche problem types from Crocus

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

en: 2015-2016 Avalanche problem types from Crocus

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

en: 2015-2016 Seismic avalanche acitivity catalogue

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

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

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

avalanche-danger

display_name: avalanche-danger

avalanche-problem-type

display_name: avalanche-problem-type

crocus

display_name: crocus

snow

display_name: snow

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability

snowpack

display_name: snowpack

weissfluhjoch

display_name: weissfluhjoch

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


manual-measuring-network

title_for_slug: manual-measuring-network

en: snow-height measurement manual-measurements snow new-snow

en: manual measurements detailed metadata

en: data downloadable over API and File Download

en: manual measurements - live data download

media_type: application/json

en: download manual measurement data via API

format: JSON

en: manual measurements - download historical data

en: For all data older than 7 days

en:
The SLF avalanche warning service operates an extensive network of manual measuring sites. The sites are distributed throughout the Swiss Alps and predominantly situated in intermediate altitude zones, between 1000 and 2000 m. Some of the measurement series already span very long periods and are therefore highly valued; the data are also used for climatological and hydrological purposes.

The measuring sites are in fixed locations, which are flat and wind-protected. The observers who perform the measurements are trained and paid by the SLF. Data is collected, as far as possible, from the beginning of November until the end of April and after that until half of the measuring site is snow-free. On some measuring sites event-based measurements are also collected during the summer months. If possible, measurements take place between 7 and 7.30 am local time.

The following variables are measured at all measuring sites:

- snow depth and 24-hour new snow

at numerous sites this additional variable is measured:

- water equivalent of 24-hour new snow (height of the water column in millimeters, if the new snow sample is melted, without changing the base area)

When using the data, please consider and adhere to the associated [Terms of Use](https://www.slf.ch/en/services-and-products/data-and-monitoring/slf-data-service.html).

To download live data use our [API](https://measurement-api.slf.ch).

To download data older than 7 days use our [File Download](https://measurement-data.slf.ch).

manual-measurements

display_name: manual-measurements

measurement

display_name: measurement

new-snow

display_name: new-snow

snow-height

display_name: snow-height

educ

en: Education, culture and sport

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: Manual measuring network


number-of-forest-edges

title_for_slug: number-of-forest-edges

en:
Number of forest edges according to the NFI definition.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

altitudinal-vegetation-zone

display_name: altitudinal-vegetation-zone

biogeographical-region

display_name: biogeographical-region

boundary-of-forest-edge

display_name: boundary-of-forest-edge

density-of-forest-edge

display_name: density-of-forest-edge

economic-region

display_name: economic-region

ecotone-value

display_name: ecotone-value

number-of-forest-edges

display_name: number-of-forest-edges

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

shape-of-forest-edge

display_name: shape-of-forest-edge

state-of-forest-edge

display_name: state-of-forest-edge

structural-diversity-of-the-forest-edge

display_name: structural-diversity-of-the-forest-edge

structure-of-forest-edge

display_name: structure-of-forest-edge

surroundings-of-forest-edge

display_name: surroundings-of-forest-edge

width-of-herbaceous-fringe

display_name: width-of-herbaceous-fringe

width-of-shelter-belt

display_name: width-of-shelter-belt

width-of-shrub-belt

display_name: width-of-shrub-belt

en: Number of forest edges


en: topography landuse wrf antarctica cryowrf

en: Documentation

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

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: Scripts

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

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.

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

en: REMA topography and AntarcticaLC2000 for WRF


maintainer: Mathias Bavay

en: wind-speed air-pressure precipitation-sum air-temperature dew-point-temperature treeline snow-depth soil-temperature relative-humidity wind-direction stillberg shortwave-radiation

en: The Davos Stillberg meteorological data (Stillberg_meteo_v1.1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

en: The Davos Stillberg meteorological data (Stillberg_meteo_v1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

en:
 Background information
The Stillberg ecological treeline research site is located in the transition zone between the relatively humid climate of the Northern Alps and the continental climate of the Central Alps. In 1975, 92,000 seedlings of the high-elevation conifer species *Larix decidua* Mill. (European larch), *Pinus cembra* L. (Cembran pine), and *Pinus mugo* ssp. *uncinata* (DC.) Domin (mountain pine) were systematically planted across an area of 5 hectares along an elevation gradient of about 150 metres, with the aim to develop ecologically, technically, and economically sustainable afforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Alongside the ecological long-term monitoring of the afforestation, several meteorological stations have recorded local meteorological conditions at the Stillberg research site. Here, we provide the Davos Stillberg meteorological timeseries of five stations from 1975 (01-01-1975), the year of the afforestation establishment, until the end of the year 2022 (31-12-2022).

 Station description
The five meteorological stations were all installed at the same location (46°46′25.015″N 9°52′01.792″E) at 2090 m a.s.l., in the lower part of the afforestation area. In general, the five stations were operated sequentially (Stillberg_meteo_metadata_stations_v1.csv). However, there are some overlapping time periods when more than one station was operated in parallel. The stations have recorded environmental parameters, such as air and soil temperature, dew point temperature, air pressure, relative humidity, wind direction and velocity, radiation, precipitation, and snow depth (Stillberg_meteo_metadata_parameters_v1.csv). The meteorological measurements were recorded hourly from 1975 until 1996 and have been recorded in 10-minute intervals since 1997.

 Data description
We processed the Davos Stillberg meteorological timeseries with the MeteoIO meteorological data pre-processing library (Bavay & Egger, 2014). Data files are provided for each station and quality level separately and named according to the station (see ‘Stillberg_meteo_metadata_stations_v1.csv’). From the raw data in their original formats, we generated three data quality levels: raw standardized (folder ‘raw_standardized’), edited (folder ‘raw_edited’) and filtered (folder ‘filtered’). The processing level is indicated in the headers of the data files. The whole processing protocol is described in a set of human-readable configuration files that are used by MeteoIO to generate the required data quality levels. This improves long-term reproducibility (Bavay et al., 2022), as the data could be regenerated in the future, even using a completely different software, to account for additional data points or to introduce new data corrections. The first quality level (raw standardized) is generated by parsing the original data files and interpreting them in order to convert all data points to a common format and meteorological parameter naming scheme, while excluding unreadable or duplicated data lines. The generated data files are derivatives of CSV files, with a standardised header that contains the metadata that are necessary to interpret and use the data (use metadata) and to populate a data index (search metadata). The latter is a textual implementation of the Attribute Convention for Data Discovery (ACDD) metadata standard (Attribute Convention for Data Discovery 1-3, 2022). The second quality level (edited) builds on the raw data by performing low-level data editing, such as removing some data periods that are known to be unusable (often based on maintenance records or anecdotal evidence) or applying undocumented calibration factors (for example, when there seems to be an obvious offset on a measured parameter for a period between two documented maintenance operations). The third quality level is generated by applying statistical filters on the data (per station and per meteorological parameter) to exclude presumably wrong values. We did not perform gap filling, as no single strategy could be relied upon that would work best for all possible data usage scenarios.

air-pressure

display_name: air-pressure

air-temperature

display_name: air-temperature

dew-point-temperature

display_name: dew-point-temperature

precipitation-sum

display_name: precipitation-sum

relative-humidity

display_name: relative-humidity

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

treeline

display_name: treeline

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

en: Long-term meteorological station Stillberg, Davos, Switzerland at 2090 m a.s.l.


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

en: Data plot of the field station (ISF)

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

en: Site photo of the field station (ISF)

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

en: Data plot of the forest station (ISB)

en: Site photo of the forest station (ISB)

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

en: Forest station data (ISB)

en: Data file.

en: Field station data (ISF)

en: Site aerial photo (Isone)

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

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Isone in Switzerland where one station is located within a natural broad-leaved forest stand (ISB) with European beech (_Fagus sylvatica_; 70-100 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, ISF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Isone is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

educ

en: Education, culture and sport

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