tree-ring-laser-ablation-data

maintainer: Paula Ballikaya

title_for_slug: tree-ring-laser-ablation-data

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

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

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: Tree-ring laser ablation data


maintainer: EnviDat Support

en: davos dischma avalanches snow-hydrology photogrammetry snow-depth-distribution

state: active

type: dataset

en: Snowdepth maps

format: GeoTIFF

en:
The available datasets are snow depth maps with a spatial resolution of 0.5 m derived from images of the survey camera Vexcel Ultracam mounted on a piloted airplane. Image acquisition was carried out during the approximately peak of winter (time when the thickest snowpack is expected) in spring. The snow depth maps are calculated by the subtraction of a summer-DTM from the processed winter- DSM of the corresponding date. The summer-DTM used was derived from a point cloud of an airborne laser scanner from 2020.

Due to the occurrence of inaccuracies of the calculated snow depth values caused by the photogrammetric method, we applied different masks to significantly increase the reliability of the snow depth maps. We masked out settled areas, high-frequented streets and technical constructions, pixels with high vegetation (height > 0.5 m) , outliers and unrealistic snow depth values. In addition, we modified the snow depth values of snow-free pixels to 0.
The information on buildings and infrastructure comes from the exactly classified ALS point cloud and the TLM dataset from Swisstopo (https://www.swisstopo.admin.ch/de/geodata/landscape/tlm3d.html#links). High vegetation is also derived from the classification and the calculated object height from the point cloud.
Outliers and unrealistic snow depth values are defined as negative snow depth values and snow depths exceeding 10 m. The classification of each pixel of the corresponding orthophoto into snow-covered or snow-free is based on the application of a threshold of the NDSI or manually determined ratios of the RGB values.

An extensive accuracy assessment proves the high accuracy of the snow depth maps with a root mean square error of 0.25 m for the year 2017 and 0.15 m for the following snow depth maps.

The work is published in:

avalanches

display_name: avalanches

davos

display_name: davos

dischma

display_name: dischma

photogrammetry

display_name: photogrammetry

snow-depth-distribution

display_name: snow-depth-distribution

snow-hydrology

display_name: snow-hydrology

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

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.

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: Snow depth mapping by airplane photogrammetry (2017 -  ongoing)


en: minimum-temperature free-climate-data maximum-temperature timeseries climate-layers air-temperature century precipitation climate

en: Data Access

en: CHELSA Technical Documentation

media_type: application/pdf

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

format: PDF

mimetype: application/pdf

en:
CHELSAcruts is a delta change monthly climate dataset for the years 1901-2016 for mean monthly maximum temperatures, mean monthly minimum temperatures, and monthly precipitation sum. Here we use the delta change method by B-spline interpolation of anomalies (deltas) of the CRU TS 4.01 dataset. Anomalies were interpolated between all CRU TS grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2 (Karger et al. 2017, Scientific Data). This method has the assumption that climate only varies on the scale of the coarser (CRU TS) dataset, and the spatial pattern (from CHELSA) is consistent over time. This is certainly a rather crude assumption, and for time periods for which more accurate data is available CHELSAcruts should be avoided if possible (e.g. use CHELSA V1.2 for 1979-2015). Different to CHELSA V1.2, CHELSAcruts does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages.

CHELSAcruts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

century

display_name: century

climate

display_name: climate

climate-layers

display_name: climate-layers

free-climate-data

display_name: free-climate-data

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation

timeseries

display_name: timeseries

en: CHELSAcruts -  High resolution temperature and precipitation timeseries for the 20th century and beyond


wind-crust-formation-snowmicropen-data

title_for_slug: wind-crust-formation-snowmicropen-data

en: wind-crust wind-packing snow snowmicropen smp

en: Processing scripts

media_type: application/zip

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

format: ZIP

mimetype: application/zip

en: README

media_type: text/plain

en: Describes the dataset in detail

format: TXT

mimetype: text/plain

en: SMP data

en: Links to the dataset

format: SERVICE

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

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

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

This dataset is the basis of the following publication:

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

smp

display_name: smp

snow

display_name: snow

snowmicropen

display_name: snowmicropen

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

en: Wind crust formation: SnowMicroPen data


maintainer: Sebastian Schlögl

en: snow stable-boundary-layer atmospheric-turbulence turbulent-sensible-heat-fluxes atmosphere

en: Turbulence data GR00

en: sensor in 1 m height

en: Turbulence data WFJ11

en: sensor in 2 m height

en: Turbulence data PM07

en: SEE

en: Turbulence data AA00

en: sensor in 25 m height

en: sensor in 0.2 m height

en: NWW

en: Turbulence data WFJ07

en: upper sensor

en: lower sensor

en:
We used five different atmospheric turbulence datasets from four test sites, with these sites showing differences in their topographical characteristics. We chose one typical alpine test site with high topographical complexity (Weissfluhjoch, Davos, Switzerland) and three test sites consisting of one glacier site (Plaine Morte, Crans-Montana, Switzerland) and two polar sites (Greenland and Antarctica) representing a quasi-ideal site with homogeneous surface and quasi infinite fetch in all directions.
The turbulent sensible heat flux was calculated using the eddy-covariance method. Note that the sonic temperature fluctuations have been converted into virtual temperature fluctuations.
Three-dimensional wind velocity and air temperature were processed using a linear detrending (Rannik and Vesala, 1999) and a planar fit approach (Massmann and Lee, 2002) to rotate the coordinate system. Air temperature, relative humidity and air pressure from weather stations were used to calculate air properties, which are required for the data processing. The weather stations are located in the immediate vicinity of the turbulence tower and are affected by the same air masses. Turbulence data were averaged to 30-min intervals, whilst changing to a 15-min time interval marginally affects the heat fluxes at the Weissfluhjoch test site (Mott et al., 2011). Note that we define a negative sensible heat flux as being directed towards the snow surface and a positive sensible heat flux as being directed upwards.
The selected datasets and corresponding test sites are briefly introduced below:

Weissfluhjoch 2007 (WFJ07): A vertical set-up of two three-dimensional ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) was used at the traditional field site Weissfluhjoch (2540 m asl.) to measure three-dimensional wind velocity and air temperature at a frequency of 20 Hz. The sensors were mounted 3 m and 5 m above the ground and provided reliable data for 50 days between 11 February 2007 and 24 April 2007. Further information on the field campaign can be found in Stössel et al. (2010) and Mott et al. (2011).

Weissfluhjoch 2011-13 (WFJ11): Three-dimensional wind velocity and air temperature were recorded at 5 m above the ground at a frequency of 10 Hz with a three-dimensional ultrasonic anemometer (CSAT3). The analysis was conducted for data obtained between February and March in the years 2011-13.

Plaine Morte 2007 (PM07): Two three-dimensional ultrasonic anemometers (CSAT3) were installed on a horizontal boom facing opposite directions (west-north-west vs. east-south-east) at 3.75 m above the ground to measure air temperature and three-dimensional wind velocity at 20 Hz. The data were collected at the almost flat field site on the Plaine Morte glacier (2750 m asl.) near Crans-Montana, Switzerland from February to April 2007. High quality meteorological data were additionally recorded and used to force the model. A detailed description about the set-up at the Plaine Morte glacier can be found in Huwald et al. (2009) and Bou-Zeid et al. (2010).

Greenland 2000 (GR00): High-frequency three-dimensional ultrasonic anemometer measurements (CSAT3) were recorded at 50 Hz at the Summit Camp (72.3 °N, 38.8 °W, 3208 m asl.) located on the northern dome of the Greenland ice sheet. Data were collected at 1 m and 2 m above the snow surface during summer in 2000 and 2001. Additionally, meteorological measurements were obtained for the post processing and used to force the model. More information about the field campaign can be found in Cullen et al. (2007, 2014).

Antarctica 2000 (AA00): A set-up of three vertical three-dimensional ultrasonic anemometers (DA-600, Kaijo Denki) were installed at Mizuho Station (70°42' S, 44°20' E, 2230 m asl.) in Eastern Antarctica at 0.2, 1 and 25 m and recorded turbulence data at a frequency of 100 Hz from October to November 2000. Longwave and shortwave radiation, relative humidity, air and snow surface temperature were additionally measured and used to force the model. More information about the field campaign can be found in Nishimura and Nemoto (2005).

atmosphere

display_name: atmosphere

atmospheric-turbulence

display_name: atmospheric-turbulence

stable-boundary-layer

display_name: stable-boundary-layer

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

educ

en: Education, culture and sport

envidat

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

en: How do stability corrections perform in the stable boundary layer over snow?


maintainer: Leo Gallus Bont

en: qgis accessible-forest geoprocessing openstreetmap forest seilaplan

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

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

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Digitised sample perimeter

en: Juypter Notebook for Data Preparation (online)

en: Forest vector data (for sample forest range)

en: Juypter Notebook for Data Preparation

en: Preview

media_type: image/png

format: PNG

mimetype: image/png

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

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: EnviDat: the Environmental Data Portal

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


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

en: Daily meteorological and snow data (1968-2022) Alptal

en:
Air temperature, dew point temperature, relative humidity, wind speed, precipitation and global radiation have been measured (since 1981) on a meadow (Erlenhöhe) in the Erlenbach catchment. It is located at 1'220 m a.s.l. with an exposure towards west. In order to assess the spatial variability of precipiation, two additional rain gauges have been running in the Vogelbach and Lümpenenbach catchment, respectively.
For the period before 1981, meteorological variables have been extrapolated from the nearby MeteoSwiss station Einsiedeln (ca. 15 km north) to the WSL station Erlenhöhe using a linear correction factor for air temperature, wind speed and precipitation.
Snow depth has been recorded automatically since 2003. Snow water equivalent has been calculated using two numerical models: COUP model (Jansson, 2012) and DeltaSnow model (Winkler et al., 2021)

Jansson, P.-E. (2012). COUP model: model use, calibration, and validation.Transactions of the ASABE, 55(4), 1335–1344.
Winkler, M., et al. (2021): Snow water equivalents exclusively from snow depths and their temporal changes: the Δsnow model, Hydrol. Earth Syst. Sci., 25, 1165-1187, 10.5194/hess-25-1165-861 2021.

format: XLS

en: Manual snow measurements Alptal (1968-2022)

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

en: Daily runoff data from three steep torrents in the Alptal (1968-2022)

en: Runoff, water temperature and electrical conductivity have been measured since 1968 at the outlet of three torrential catchments (with an area of approximately 1 km2 each) located in the Alptal valley: Erlenbach, Lümpenenbach and Vogelbach. This data set provides daily mean values; data at 10-min resolution can be provided on request for the period 1984-2022 (contact: alptal@wsl.ch).

en:
This data set includes 54 years of hydrometeorological measurements from small (first-order) catchments in the pre-alpine valley Alptal. Here we provide daily mean values; values in sub-daily resolution can be provided on demand.
Runoff has been measured at the outlet of three small (first-order) catchments of approximately 1 km2 area: Erlenbach (two independent runoff measurements), Vogelbach and Lümpenenbach. The catchments are similar with regard to geology (Flysch) and soil conditions (clay soils), but differ in forest coverage (20 to 60%). A detailed description of the catchments can be found at https://www.wsl.ch/alptal .
Runoff in these small catchments is typically very dynamic and can temporally carry large amounts of sediment and large wood. Thus, the accuracy of the measurements at very large flow is limited.
Meteorological variables have been measured on a meadow (Erlenhöhe) located in the Erlenbach catchment at 1220 m a.s.l. using a standard meteorological station (incl. ventilated air temperature and heated rain gauges). In addition, precipitation has also been recorded at two other locations (in the Vogelbach and Lümpenenbach catchments).
Snow measurements have been conducted weekly to monthly since 1968 at more than 15 locations (30-m transects) representing different altitudes, aspects and land uses (meadow, forest). In addition, snow depth has been recorded continuously since 2003 at Erlenhöhe, and for this location we also include a simulation of snow depth and SWE (using the numerical models COUP and DeltaSnow) that assimilates the manual weekly snow-course measurements. Details on these snow measurements can be found in Stähli, M. and Gustafsson, D. 2006. Hydrol. Proc., 20, 411-428. doi: 10.1002/hyp.6058.

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

A first version of this data set (for the period 1968-2017) was uploaded in June 2018 at the occasion of the 50-year anniversary. This original data set was updated in February 2021 (with data from 2018 and 2019), and this data set was used for a longterm trend analysis, submitted for publication in a special issue of Hydrological Processes. A second update of the data set (with data from 2020 to 2022) was uploaded in March 2023.

alptal

display_name: alptal

first-order-catchment

display_name: first-order-catchment

meteorological-data

display_name: meteorological-data

runoff

display_name: runoff

subalpine

display_name: subalpine

en: Longterm hydrological observatory Alptal (central Switzerland)


snow-depth-mapping

maintainer: Mauro Marty

title_for_slug: snow-depth-mapping

en: avalanche image-matching dsm snow-hydrology aerial-imagery snow-water-equivalent snow-depth

en: Snow depth map 20140417

en: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.18 m

en: Snow depth map 20150415

en: Snow depth map 20160420

en: Snow depth map 20160309

en: Snow depth map 20120320

en: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en: Snow depth map 20100416

en: Snow depth map 20160126

en:
Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m
Because of very diffuse light conditions at time of image acquisition the quality of the resulting snow depth values are in some regions quite poor.

en: Snow depth map 20130415

en:
The available datasets are snow depth maps with a spatial resolution of 2m generated from image matching of ADS 80/100 data. Image acquisition took place at peak of winter (time when the thickest snowpack is expected). The snow depth maps are the difference of a summer DSM from the winter DSM of the corresponding date . The summer DSM used is a product of image matching of ADS 80 data from summer 2013. In the available products buildings, vegetation and outliers were masked (set to NoData).
For the elimination of buildings the TLM layer (swisstopo) was used, because this layer might not represent exactly the
state of infrastructure at time of image acquisition, it is possible that mainly in dense settlement some buildings were not successfully masked. For the relevant area above treeline the masking of buildings showed good results. Vegetation got masked for a height above ground > 1m and was detected in a combination of summer and winter data sets. As Outliers were considered unrealistic snow depths caused by a failure of the image matching algorithm. Snow depths > 15m and smaller than < -15m were classified as outliers. Negative snow depth were kept, because of an uncertainty in image orientation accuracy. It is expected that in regions with negative snow depth also positive snow depth are underestimated by the same amount, which means that an estimation of snow volume should be carried out summing up the absolute values of snow depth (also the negative ones). For volume estimation in small regions the user has to take into account, that orientation accuracy of the images is roughly around 1-2 GSD (30cm), which propagates directly to the snow depth product. Areas which are not covered by snow got assigned a value of 0 as snow depth.

The work is published in:

Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C., (2015). Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9 (1), 229-243. doi: 10.5194/tc-9-229-2015

aerial-imagery

display_name: aerial-imagery

avalanche

display_name: avalanche

dsm

display_name: dsm

image-matching

display_name: image-matching

snow-depth

display_name: snow-depth

snow-hydrology

display_name: snow-hydrology

snow-water-equivalent

display_name: snow-water-equivalent

educ

en: Education, culture and sport

envidat

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


rorcc

maintainer: Tobias Wechsler

title_for_slug: rorcc

en: run-of-river-power-plants climate-change environmental-flow hydropower design-discharge

en: RoRCC

en:
The dataset “RoRCC” consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
-	metadata on the RoR power plants under consideration
-	annual and seasonal production scenarios differentiated into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)
-	annual and seasonal production loss due to environmental flow requirements
-	annual and seasonal the technical increase potential (via design discharge optimisation)
-	annual and seasonal changes in the hydrological cycle for the three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)

en:
The dataset "RoRCC" consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
1) metadata on the RoR power plants under consideration, 2) annual and seasonal production potential scenarios under into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099), 3) annual and seasonal streamflow scenarios, 4) annual and seasonal production loss due to environmental flow requirements, 5) annual and seasonal the technical increase potential (via design discharge optimisation) and 6) annual and seasonal changes in the hydrological cycle.

climate-change

display_name: climate-change

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants

envidat

en: EnviDat: the Environmental Data Portal


maintainer: Franziska Gerber

en: cosmo-wrf static-data topography landuse cryowrf wrf

en: Static data for WRF - Topography

en: Documentation

en: Documentation of the dataset

en: Static data for WRF - Soiltype top

en: Example namelist.wps to use with the 1s static data

en: Static data for WRF - Soiltype bottom

en:
Example GEOGRID.TBL to use with the 1s static data;
Note about naming:
* 121 -> 1-2-1 topography smoothing applied to dataset
* 1 -> one smoothing cycle applied to the data (needs to be changed depending on the chosen resolution to avoid too steep slope angles)

en: Static data for WRF - Landuse

en: Static input data (topography, landuse and soiltype) for the WRF preprocessing system WPS is provided for Switzerland and its neighboring countries between 45-49 N and 4-12 E. The data is provided at a resolution of 1 s. Topography is based on the Aster dataset, while landuse is extracted from the Corine landuse dataset. Soil type is set to silty clay loam for the entire domain. This static input data is valid for WRF and CRYOWRF.

cosmo-wrf

display_name: cosmo-wrf

cryowrf

display_name: cryowrf

landuse

display_name: landuse

static-data

display_name: static-data

topography

display_name: topography

wrf

display_name: wrf

en: High resolution static data for WRF over Switzerland


en: landscape-services switzerland land-use modeling land-use-change urbanization statistical-model

en: Data for Assessing potential landscape service trade-offs driven by urbanization in Switzerland

en:
The provided folder structure follows the set up of the scripts.
Data is only provided when it has been fully produced by us, otherwise dummies are given.
For data that will be produced by one of the scripts, no dummies are given.
The folders may contain sub-folders, which would be filled if the scripts were all run

 00_Analysis_Data
Data produced throughout the process of the calibration and projection that is later needed for analysis

 01_Raw_Data
Primary data from external sources that were used to compile the rasters and numbers used during the calibration and projection of landscape transitions as well as service calculation

 02_Prepared_Data
Data that will be prepared for further use by scripts are put in here
Additionally it contains the parameter sheets for the transition predictors that we compiled

 03_Model_Data
 Model outputs
Folder were the projection models statistics will be saved
 Models
Folder into which the actual transition models will be saved
 Residuals
Folder into which data on models residuals will be saved for future use

 04_Projected_Data
The output of the projections will be saved into this folder

 05_Service_Data
Any service calculations will be saved in here

 06_Results_Analysis
Any Analysis plots and tables as well as intermediate data will be saved here in the respective sub-folder

en: Scripts for Assessing potential landscape service trade-offs driven by urbanization in Switzerland

en:
Scripts ordered by their main purpose within sequential folders in this ReadMe marked with

Within the folders the capital letters refer to the parallel or sequential use of the scripts; scripts here in ReadMe are marked with

 00_Function Scripts
 Functions.r
Script containing several functions for analyzing statistical models: cohen.kappa, meva.table, D2, max-Tss, plot-TSS

 Service_functions.R
Script containing functions for calculating all services and returning sums (and median for bd and rec) as well as rasters

 01_Data Preparation
 A_AS_raster_preparation.R
Preparation of the land use rasters for the years 1985, 1997, and 2009 based on the original Arealstatistik (AS/ASCH); Assigning our categories and assining new values to all "construction sites" for calibrating the models
For model projection starting point (2009) and for service calculations (all ASCH years) the "other" categories were assigned to the land use categories based on dominant neighbor, so that there were no empty cells
Creation of water & mountainous area raster that stayed stable throughout the projections
Creation of MFH raster (2009), to have as base for all new projection years, as this category never becames any other

 B_Factors_preparation.R
Preparation of the factor rasters that were used to calculate service values per cell (see Table 2): LWfactor, Transportation, Vol, Rivers, Lakes, slope, TWW, Hazard_risk

 B_Predictors_preparation.R
Preparation of the raster of the predictors used for calibrating (ASCH years) and projecting (stable) the transition models that do not depend on the land use categories: Temperature (ASCH years), solar radiation (stable), Public transportation access (stable), Elevation (stable), Workers density (ASCH years), Population change (ASCH transitions)

 B_Regions_preparation.R
Preparation of bioregions as raster to be used to mask asxxxx later to calculated services and land use area just for one region

 C_Pred_proj.R
Projecting the dynamic predictors into the future for projecting the land use transitions with the model: Linear extrapolations for workers densities and population; more detailed extrapolation of temperature (based on data for all stations that matched between the temp table we used for the calibration period and the projections from CS2M, and then making a spatial interpolation for all years based on the interpolation of temperature for all years per station)

 02_Model calibration
 A_Bioreg_pred_corr.R
Calculating correlation between the predictors for each bioregion and land use category, Output are those with too high correlation so that one predictor can be removed from transitions were both predictors occur

 A_trans_numbers_bioreg.R
Calculate transition numbers for each bioregion to decide which transitions to primarily consider

 B_Bioreg_ext_eval.R
Calculating TSS based on the external evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 85-97, evaluation data: 97-09)

 B_Bioreg_int_eval.R
Calculating TSS based on the internal evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 70%, evaluation data: 30%)

 C_Bioreg_TSS_analysis.R
Extracting TSS numbers from internal and external evaluation, calculating mean and median for each transition for each region for each evaluation method and saving as csv per region to be able to select only the transitions with high enough model performance

 D_Bioreg_Models_for_prediction.R
Calibration of the models that were then used to project land use transitions into the future; calibrated separately for each bioregion

 E_Residuals_trans_models.R
Calculation of Moran's I statistics to analyze the residuals of the land use transition models

 03_Projections
 A_Bioreg_Projections_run.R
Master script for: Extrapolaitng into the future with the regional models and then assembling for each time step to calculate new AS predictors; Several Outputs: txt file to test for NAs in Predictors, txt file with random seed number for sampling, txt file with times for calculation steps (check progress of script while running), csv sheet with projected transition frequencies, tif-rasters for every region and time step, pdf with raster plot for every region and time step

 04_Service calculation
 A_Bioreg_as_services.R
Calculate services per bioregion for years 1985, 1997, 2009

 A_Service_calculation_bioregions.R
Extracting service numbers(sums) per bioregions for all projection runs and storing them in a list of matrixes to be available for further plotting; can be run for swiss wide projections or regional ones

 05_Analysis
 A_Bioreg_ASCH_development.R
Extracting the occurrence of each category per region for all runs (first part), then for ASCH years, and then plotting them nicely; only works for regional projections

 A_Bioreg_Predictors_importanceD2.R
Calculating D2 for each transition and each considered predictor from bivariate models to get value of importance

 B_Bioreg_Pred_imp_analysis.R
Using calculated D2 to sort Predictors according to their importance for each transition

 A_Bioreg_Spatial_results_analysis.R
Plotting randomly sampled runs for ASCH and services to analyses their spatial development

 A_Bioreg_Transition_numbers_check_v1.R
Analyzing the frequency for all transitions for all regions and producing the point plots for each transition separately

 A_Bioreg_Transition_numbers_check_v2.R
Analyzing percentage and numbers of all transitions but plotting them per region and originating ASCH category

 B_Transition_Analysis.R
Further Analysis of transition numbers

 A_Service_analysis.R
Plotting of the service development for bioregions in several ways for analyzing

en:
Data and scripts of publication:

Madleina Gerecke, Oskar Hagen, Janine Bolliger, Anna M. Hersperger, Felix Kienast, Bronwyn Price, Loïc Pellissier (2019) Assessing potential landscape service trade-offs driven by urbanization in Switzerland. Palgrave communications.

Contains land use projections for Switzerland and scripts and data for these projections as well as the calculation of landscape services.

Data Folder:
Contains sub-folder with the data necessary for this study (provided were no copyright issues, otherwise placeholders with descriptions), and folders where produced data may be stored

Scripts Folder:
Contains scripts organized into subfolders depending on their purpose

Note: Some abbreviations within the scripts and data are derived from German words and not English.

land-use

display_name: land-use

land-use-change

display_name: land-use-change

landscape-services

display_name: landscape-services

modeling

display_name: modeling

statistical-model

display_name: statistical-model

switzerland

display_name: switzerland

urbanization

display_name: urbanization

educ

en: Education, culture and sport

envidat

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

en: Land use projections and services for Switzerland


maintainer: Ionuț Iosifescu Enescu

en: map 0.2GB

en: map 0.5GB

en: map preview 0.5MB

mimetype: image/jpeg

en: Bulk Data Access

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

en: huge map 100GB

en: map 2GB

en: large map 10GB

en: map 1GB

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: EnviDat: the Environmental Data Portal

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


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

en: Population density per pixel (change per year)

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

en: slope

en: Slope °

en: Native forest cover gains from 2005 to 2015

en: isolated

en: New built-up pixels classified as isolated

en: Master plan Ubatuba (zones)

en: Native forest cover persistence from 2005 to 2015

en: Increase in sanitation service

en: infill

en: New built-up pixels classified as infill

en: Descricao dos dados em portiuguês

en: Portugues description

en: Increase in waste collection service

en: Variables description

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

en: Permanent housing density increase

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

en: Ecological-Economic Zoning (EEZ)

format: SHP

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

en: Master plan Ihabela (zones)

en: Increase in clean water provision service

en: Increase in Normalized Difference Vegetation Index

en: Axial

en: New built-up pixels classified as axial

en: Topographic Index Position (TPI)

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

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

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

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

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

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

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

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

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

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

3)	Topographic drivers

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

basic-services

display_name: basic-services

built-up-classification

display_name: built-up-classification

forest-gain

display_name: forest-gain

forest-persistence

display_name: forest-persistence

land-use-and-cover-change

display_name: land-use-and-cover-change

nature-conservation

display_name: nature-conservation

planning-outcome

display_name: planning-outcome

spatial-modelling

display_name: spatial-modelling

urban-compactness

display_name: urban-compactness

urban-morphology

display_name: urban-morphology

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


en: uav photogrammetry dsm wingtra drone-data

en: Data Access

en:
- DSM 10cm resolution
- Orthomosaic 3cm resolution
- Agisoft Metashape Processing Report
- original RGB images

All generated products are also available as a cloud optimized geotiff.

en: We conducted four drone flights in Davos Wolfgang Arelen, in 2020/21 and 2022 to obtain data for the generation of DSMs and orthomosaics at a high resolution. The data was processed with the Agisoft Metashape Professional Software.

drone-data

display_name: drone-data

dsm

display_name: dsm

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

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: Photogrammetric Drone Data Wolfgang Arelen


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

en: 00. EDA Raw Data

en: 02. Questionnaire Data

en: 05. Visuals

en: 04. Scripts

en: 01. EDA Processed Data

en: 03. Publication Ready Data

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

electrodermal-activity

display_name: electrodermal-activity

landscape

display_name: landscape

place-attachment

display_name: place-attachment

sense-of-place

display_name: sense-of-place

urban-ecology

display_name: urban-ecology

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


fr: kanton flachmoor biotop

de: kanton flachmoor biotop

en: kanton flachmoor biotop

it: kanton flachmoor biotop

label: geocat.ch permalink

fr: WFS-Dienst des Kantons Schwyz

de: WFS-Dienst des Kantons Schwyz

en: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

format: WFS

fr: Rechtsgültige Darstellung aller kantonalen Nutzungspläne im Bereich Natur- und Heimatschutz

spatial: Kanton Schwyz (SZ)

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz

de: Das Amt für Geoinformation verwaltet und veröffentlicht die Geodaten des Kantons Schwyz als OGC-Geodienste und als Datei-Download. Alle aktuell verfügbaren Geodaten, welche dem OGD unterliegen, sind hier aufgeführt.

political_level: canton

value: SZ-Kt Geoinformation - Geocat Harvester

fr: Nutzungsplanung kantonal, Bereich Natur- und Heimatschutz ÖREB


fr: schutzzone grundwasserschutz gewasserschutz grundwasser trinkwasser

format: WMS

fr: Grundwasserschutzzbereiche sind Teil des planerischen Gewässerschutzes. Sie dienen als Grundlage für Schutzmassnahmen dem Schutz vor Beeinträchtigungen des Grundwassers. Sie umfassen Schutzbereiche der unterirdischen sowie oberflächlichen Gewässer, welche der Trinkwasserversorgung dienen.

fr: Gewässerschutzbereich Ao

de: Gewässerschutzbereich Ao

en: Gewässerschutzbereich Ao

it: Gewässerschutzbereich Ao


maintainer: Frank Techel

en: long-term-trends avalanche-accident-statistics avalanche-statistics avalanche-accident avalanche-fatalities

en: Data avalanche fatalities 1969/1970 - 2014/2015

en: The data comprises avalanche fatality data from the Alpine regions in the seven countries Austria, France, Germany, Italy, Liechtenstein, Slovenia, and Switzerland.

en:
During the last 45 years, about 100 people lost their lives in avalanches in the European Alps each year. Avalanche fatalities in settlements and on transportation corridors have considerably decreased since the 1970s. In contrast, the number of avalanche fatalities during recreational activities away from avalanche-secured terrain doubled between the 1960s and 1980s and has remained relatively stable since, despite a continuing strong increase in winter backcountry recreational activities.

Data complementing Figure 2 in:
_"Avalanche fatalities in the European Alps: long-term trends and statistics"_, by Techel, F., Jarry, F., Kronthaler, G., Mitterer, S., Nairz, P., Pavšek, M., Valt, M., and Darms, G.

Data description:
please refer to section 2 (Data and Methods) in the mentioned publication

avalanche-accident

display_name: avalanche-accident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

avalanche-statistics

display_name: avalanche-statistics

long-term-trends

display_name: long-term-trends

en: Avalanche fatalities in the European Alps (1969/1970 - 2014/2015)


en: forest-fire natural-hazards bark-beetles extreme-events protective-effect drought protection-forest compound-events

en: Conclusions and recommendations of the project (in German).

en: Description of the study site, extreme event (trigger event) and informations about the survey.

en: Factsheet summarising the methods used in this project (in German).

en: Factsheet summarising the key results of the study (in German).

en: Case study website

media_type: text/html

en: Page of the case study on the project website. It includes figures fo all questions of the survey and additional synthesis graphs.

format: HTML

en: Factsheet summarising the key results of the study (in Italian).

en: Factsheet summarising the key results of the study (in French).

en:
This file contains the anonymous answers to the survey for the case study in the protective forest, Val Mesolcina, GR, Switzerland within the BAFU Project "Wenn Risiken kumulieren - Analyse und Umgang mit unerwarteten Ereignissen und kombinierten Risiken".
The survey consists of two parts, based on different concepts: "top-down" and "bottom-up". Answers for both concepts are available in two different worksheets within the Excel file.

en:
This dataset contains the results of a case study analysing the potential impacts of a compound meteorological extreme event on the protective forest in the Val Mesolcina. These impacts were assessed in an experts survey. 29 Experts from practice, administration and science estimated the probabilities for a loss of the protective function due to a drought-related compound extreme event based on different hazard scenarios. The experts not only assessed these probabilities but also provided estimates about the reliability of the scenarios, other socio-economic consequences and options for adaptation.
This dataset contains the following information:
- Table with all (anonymised) answers from the survey
- Factsheets summarising the results and methods in German, French and Italian
- A detailed description of the study site and survey instructions
- Link to the project website wit illustrations for each individual question of the survey

bark-beetles

display_name: bark-beetles

compound-events

display_name: compound-events

drought

display_name: drought

extreme-events

display_name: extreme-events

forest-fire

display_name: forest-fire

natural-hazards

display_name: natural-hazards

protection-forest

display_name: protection-forest

protective-effect

display_name: protective-effect

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: Experts survey protective forest and combined extremes in Val Mesolcina


maintainer: Peter Bebi

en: soil-temperature carbon-dioxide vegetation climate-change stillberg experiment

en: Metadata FACE Stillberg Experimental Design

en: Schematic illustration and tabular listing of the FACE experimental design.

en: Metadata FACE Stillberg Data File Description

media_type: text/csv

en: List of descriptions for each of the .csv FACE data files.

format: CSV

en: Project Description FACE Stillberg

en: Link to FACE project description on the WSL website.

en: Data FACE Stillberg

en: Folder in .zip format containing the FACE datasets.

en:
 Background information

High elevation ecosystems are important in research about environmental change because shifts in climate associated with anthropogenic greenhouse gas emissions are predicted to be more pronounced in these areas compared to most other regions of the world. This project involved a Free Air CO2 Enrichment (FACE) and soil warming experiment located in a natural treeline environment near Davos, Switzerland (Stillberg, 2200 m a.s.l.). Elevated atmospheric CO2 concentrations (+200 ppm) were applied from 2001 until 2009, and a soil warming treatment (+4 °C) was applied from 2007 until 2012. The combined CO2 enrichment and warming treatment reflects conditions expected to occur in this region in approximately 2050. A broad range of ecological and biogeochemical research was carried out as part of this environmental change project.

 Experimental design

The experiment consisted of 40 hexagonal 1.1 m² plots, 20 with a *Pinus mugo* ssp. *uncinata* (mountain pine, evergreen) individual in the centre and 20 with a *Larix decidua* (European larch, deciduous) individual in the centre. A dense cover of understorey vegetation surrounded the tree in each plot, including the dominant dwarf shrub species *Vaccinium myrtillus* (bilberry), *Vaccinium gaultherioides* (group *V. uliginosum agg.*, northern bilberry) and *Empetrum nigrum* ssp. *hermaphroditum* (crowberry) plus several herbaceous and non-vascular species.
At the beginning of the experimental period, the 40 plots were assigned to ten groups of four neighbouring plots (two larch and two pine trees per group) in order to facilitate the logistics of CO2 distribution and regulation. Half of these groups were randomly assigned to an elevated CO2 treatment, while the remaining groups served as controls and received no additional CO2. In spring 2007, one plot of each tree species identity was randomly selected from each of the 10 CO2 treatment groups and assigned a soil warming treatment, yielding a balanced design with a replication of five individual plots for each combination of CO2 level, warming treatment and tree species.

 Data description

Soil and air conditions have been monitored closely throughout the study period, with most measurements made during the combined CO2 x warming experiment (2007-2009). The data comprise of air temperature, soil temperature, soil moisture, sapflow, tree diameter and CO2 measurements.

carbon-dioxide

display_name: carbon-dioxide

climate-change

display_name: climate-change

experiment

display_name: experiment

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

vegetation

display_name: vegetation

en: FACE: Stillberg CO2 enrichment and soil warming study


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

en: Site photo of the forest station (SCB)

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

en: Data plot of the field station (SCF)

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

en: Site aerial photo (Schänis)

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

en: Forest station data (SCB)

en: Data file.

en: Site photo of the field station (SCF)

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

en: Further details on the data repository

en: Meta data documentation.

en: Field station data (SCF)

mimetype: text/csv

en: Data plot of the forest station (SCB)

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

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


fr: zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: Nutzungsplanung kommunal Gemeinde Wangen

en: WFS-Dienst des Kantons Schwyz

fr: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Wangen (SZ)


kantonsstrassen

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: kantonsstrassen

label: Web GIS Client des Kanton Uri. Die Daten können direkt via dem Portal in den unterschiedlichsten Datenformaten heruntergeladen werden.

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: Strassen, die sich im Zuständigkeitsbereich des Kantons befinden, inkl. Basisbezugspunkte.

spatial: Canton of Uri (UR)

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

value: Uri-Kt - Geocat Harvester

fr: Kantonsstrassen

de: Kantonsstrassen

en: Kantonsstrassen

it: Kantonsstrassen


envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

fr: couverture-du-sol geodonnees-de-base

de: bodenbedeckung geobasisdaten

en: land-cover official-geodata

it: copertura-del-suolo geodati-di-base

url: https://geo.ur.ch/?layers=Bodenbedeckung Darstellung schwarz weiss

fr: Die Informationsebene Bodenbedeckung ist eine generalisierte und kartografisch bearbeitete Darstellung realer Objekte mit flächiger Ausdehnung (Gebäude, Strassen, Gewässer, Wald...).

fr: Bodenbedeckung Darstellung schwarz weiss (UR)


postleitzahl-ur

title_for_slug: postleitzahl-ur

fr: Postleitzahl aus TOPIC «PLZOrtschaft» der amtlichen Vermessung.

fr: Postleitzahl (UR)

de: Postleitzahl (UR)

en: Postleitzahl (UR)

it: Postleitzahl (UR)


gebaudeadressen-ur

title_for_slug: gebaudeadressen-ur

fr: Die Gebäudeadresse setzt sich zusammen aus einer Ortschaft mit Postleitzahl, einem Lokalisationsnamen (in der Regel Strassennamen) und einer Hausnummer. Zusätzlich werden die Strassenstücke und benannten Gebiete der amtlichen Vermessung dargestellt.

fr: Gebäudeadressen (UR)

de: Gebäudeadressen (UR)

en: Gebäudeadressen (UR)

it: Gebäudeadressen (UR)


liegenschaften-ur

title_for_slug: liegenschaften-ur

fr: terrain geodonnees-de-base

de: grundstuck geobasisdaten

en: site official-geodata

it: fondo geodati-di-base

fr: Die Informationsebene Liegenschaften enthält die Grundstücke gemäss Art. 655 Abs. 2 ZGB: rechtsgültige und projektierte Liegenschaften (Parzellen), selbständige und dauernde Rechte (z.B. Baurecht). Zudem sind ab dem Massstab 1:1'000 auch die Grenzpunkte und Hoheitsgrenzpunkte sichtbar.

fr: Liegenschaften (UR)

de: Liegenschaften (UR)

en: Liegenschaften (UR)

it: Liegenschaften (UR)


regi

fr: Régions et villes

fr: plan-de-situation geodonnees-de-base

de: situationsplan geobasisdaten

en: situation-plan official-geodata

it: piano-di-situazione geodati-di-base

fr: Diverse Ebenen aus der Amtlichen Vermessung bilden den bekannten Grundbuchplan. Den Katasterplan A4/A3 als PDF können sie ebenfalls hier direkt beziehen.

fr: Grundbuchplan Darstellung schwarz-weiss (UR)


planeinteilungen-ur

title_for_slug: planeinteilungen-ur

fr: repartition-du-plan geodonnees-de-base

de: planeinteilung geobasisdaten

en: plan-division official-geodata

it: ripartizione-del-piano geodati-di-base

fr: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

fr: Die Geometrien und Nummern der Planeinteilung des Planes für das Grundbuch.

fr: Planeinteilungen (UR)

de: Planeinteilungen (UR)

en: Planeinteilungen (UR)

it: Planeinteilungen (UR)


administrative-einteilung-ur

envi

fr: Environnement

title_for_slug: administrative-einteilung-ur

fr: Die Toleranzstufen sind ein Teil des Datenmodells DM01 und geben an, wie genau die Objekte der AV aufgenommen sein müssen. In den entsprechenden Verordnungen ist definiert, welche Standardabweichungen für die einzelnen Aufnahmepunkte sicherzustellen sind.

fr: Administrative Einteilung (UR)

de: Administrative Einteilung (UR)

en: Administrative Einteilung (UR)

it: Administrative Einteilung (UR)


nomenklatur-ur

regi

de: Regionen und Städte

title_for_slug: nomenklatur-ur

fr: Flur-, Orts- und Geländenamen (= geografische Namen der amtlichen Vermessung) von geografischen Gebieten, Landschaftsteilen, Flurstücken, topografischen Objekten usw.

fr: Nomenklatur (UR)

de: Nomenklatur (UR)

en: Nomenklatur (UR)

it: Nomenklatur (UR)


hoheitsgrenzen-ur

title_for_slug: hoheitsgrenzen-ur

de: WMS-Dienst des Kanton Uri

fr: Da der Kanton Uri keine Bezirke hat, bestehen die Hoheitsgrenzen ausschliesslich aus den Gemeindegrenzen.

fr: Hoheitsgrenzen (UR)

de: Hoheitsgrenzen (UR)

en: Hoheitsgrenzen (UR)

it: Hoheitsgrenzen (UR)


bodenbedeckung-ur

regi

en: Regions and cities

it: Regioni e città

title_for_slug: bodenbedeckung-ur

fr: couverture-du-sol geodonnees-de-base

de: WFS-Dienst des Kanton Uri

fr: Die Informationsebene Bodenbedeckung ist eine generalisierte und kartografisch bearbeitete Darstellung realer Objekte mit flächiger Ausdehnung (Gebäude, Strassen, Gewässer, Wald...).

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

fr: Bodenbedeckung (UR)

de: Bodenbedeckung (UR)

en: Bodenbedeckung (UR)

it: Bodenbedeckung (UR)


einzelobjekte-ur

regi

fr: Régions et villes

envi

de: Umwelt

title_for_slug: einzelobjekte-ur

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: Die Informationsebene Einzelobjekte umfasst Objekte, die Merkmale der Bodenbedeckung enthalten, welche aufgrund ihrer Eigenschaft oder Ausdehnung aber keine oder unwesentliche flächenmässige Bedeutung haben.

geoinformation-kanton-uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

fr: Einzelobjekte (UR)

de: Einzelobjekte (UR)

en: Einzelobjekte (UR)

it: Einzelobjekte (UR)


egid-und-gebaudenummer

title_for_slug: egid-und-gebaudenummer

fr: WMS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: EGID und Gebäudenummer. Jedes Gebäude hat eine vortlaufende Nummer die gemeindeweise eindeutig ist.

fr: EGID und Gebäudenummer

de: EGID und Gebäudenummer

en: EGID und Gebäudenummer

it: EGID und Gebäudenummer


fixpunkte-ur

envi

en: Environment

it: Ambiente

title_for_slug: fixpunkte-ur

fr: WFS-Dienst des Kanton Uri

fr: Die Fixpunkte bilden die Grundlage aller Daten mit Raumbezug. Darunter fallen beispielsweise die Daten der amtlichen Vermessung, die Landeskartenwerke, Leitungskataster, Daten in geographischen Informationssystemen, Zonenpläne etc. Es werden generell zwei Punktarten unterschieden: die Lagefixpunkte (LFP) und die Höhenfixpunkte (HFP).

fr: Fixpunkte (UR)

de: Fixpunkte (UR)

en: Fixpunkte (UR)

it: Fixpunkte (UR)


grundbuchplan-ur

envi

fr: Environnement

title_for_slug: grundbuchplan-ur

fr: plan-de-situation geodonnees-de-base

fr: Diverse Ebenen aus der Amtlichen Vermessung bilden den bekannten Grundbuchplan. Der Katasterplan A4/A3 als PDF können sie ebenfalls hier direkt beziehen.

fr: Grundbuchplan (UR)

de: Grundbuchplan (UR)

en: Grundbuchplan (UR)

it: Grundbuchplan (UR)


amtliche-vermessung-zg

title_for_slug: amtliche-vermessung-zg

label: ZugMap.ch, der öffentliche Geodaten-Viewer des GIS Kanton Zug

de: geodienste.ch - WFS Amtliche Vermessung

de: geodienste.ch WMS Amtliche Vermessung (MOpublic)

de: Die amtliche Vermessung – ein nationales Produkt – liefert geometrische Daten zum Grundeigentum und ist die Grundlage für viele weitere geografische Informationen und Anwendungen in Wirtschaft, Verwaltung und Privatleben.

spatial: Kanton Zug (ZG)

name: Amt für Grundbuch und Geoinformation des Kantons Zug

gis-kanton-zug

fr: GIS Kanton Zug

de: GIS Kanton Zug

en: GIS Kanton Zug

de:
Die Abteilung Geoinformation ist das kantonale Kompetenzzentrum für Geoinformation im Kanton Zug.
Wir sind eine zukunftsorientierte Dienstleistungseinheit für die Verwaltung, Werke, Bürgerinnen und Bürger, Wirtschaft und Politik. Kantonale und kommunale Amtsstellen erhalten von uns Unterstützung bei Ihren GIS-Projekten.
Wir sorgen für die Einhaltung einheitlicher Standards bei der Erstellung von Datenmodellen und beim Einsatz der benötigten Software. Beim Beschaffen, Verwalten, Visualisieren, Bearbeiten, und Verteilen der Geodaten arbeiten wir eng mit den Fachämtern zusammen.

value: ZG-Kt - Geocat Harvester

de: Amtliche Vermessung ZG


abwasseranlagen-darstellung-eigentum

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

regi

de: Regionen und Städte

title_for_slug: abwasseranlagen-darstellung-eigentum

de: leitungskataster geobasisdaten

en: pipeline-cadastre official-geodata

it: catasto-delle-condotte geodati-di-base

de: WMS-Dienst des Kanton Uri

fr: Dieser Datensatz hat den gleichen Inhalt wie der Datensatz "34-UR_Abwasseranlagen". Die Abwasserleitungen sind gemäss dem Attribut "Eigentum" verschiedenfarbig dargestellt.

fr: Abwasseranlagen Darstellung Eigentum

de: Abwasseranlagen Darstellung Eigentum

en: Abwasseranlagen Darstellung Eigentum

it: Abwasseranlagen Darstellung Eigentum


abwasseranlagen

regi

fr: Régions et villes

envi

de: Umwelt

title_for_slug: abwasseranlagen

de: WFS-Dienst des Kanton Uri

fr: In diesem Datensatz werden alle Leitungen für verschmutztes und nicht verschmutztes Abwasser erfasst (Art. 26. Kantonales Umweltschutzgesetz, KUG). Weiter enthält dieser Datensatz Abwasserreinigungsanlagen, Versickerungsanlagen und Sonderbauwerke.

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

fr: Abwasseranlagen

de: Abwasseranlagen

en: Abwasseranlagen

it: Abwasseranlagen


abwasseranlagen-darstellung-nutzungsart

title_for_slug: abwasseranlagen-darstellung-nutzungsart

fr: WMS-Dienst des Kanton Uri

fr: Dieser Datensatz hat den gleichen Inhalt wie der Datensatz "34-UR_Abwasseranlagen". Die Abwasserleitungen sind gemäss dem Attribut "Nutzungsart" verschiedenfarbig dargestellt.

fr: Abwasseranlagen Darstellung Nutzungsart

de: Abwasseranlagen Darstellung Nutzungsart

en: Abwasseranlagen Darstellung Nutzungsart

it: Abwasseranlagen Darstellung Nutzungsart


maintainer: Standeskanzlei Graubünden

fr: votation federal

de: abstimmung national

it: votazione nazionale

label: Formatbeschreibung

label: Descripziun dal format

label: Description du format

label: Descrizione del formato

media_type: application/json

format: JSON

mimetype: application/json

identifier: json

identifier: csv

rm: Resultats finals da la votaziun federala "Iniziativa dal pievel «Per in’entrada da basa nuncundiziunada»", 5 da zercladur 2016, Graubünden - Grischun - Grigioni, ordinà tenor vischnancas.

fr: Résultats finaux du vote fédéral "Initiative populaire « Pour un revenu de base inconditionnel »", 5 juin 2016, Graubünden - Grischun - Grigioni, répartis par municipalités.

de: Schlussresultate der eidgenössischen Abstimmung "Volksinitiative «Für ein bedingungsloses Grundeinkommen»", 5. Juni 2016, Graubünden - Grischun - Grigioni, aufgeschlüsselt nach Gemeinden.

it: Risultati finali della votazione federale "Iniziativa popolare «Per un reddito di base incondizionato»", 5 giugno 2016, Graubünden - Grischun - Grigioni, suddivisi per municipalit.

abstimmung

display_name: abstimmung

federal

display_name: federal

national

display_name: national

nazionale

display_name: nazionale

plaun-naziunal

display_name: plaun-naziunal

votation

display_name: votation

votazione

display_name: votazione

votaziun

display_name: votaziun

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

standeskanzlei-graubuenden

fr: Chancellerie d’État des Grisons

de: Standeskanzlei Graubünden

en: State Chancellery of Grisons

it: Cancelleria dello Stato dei Grigioni

fr: La Chancellerie d’État fournit des données publiques librement accessibles triées sur le volet, qui proviennent du Parlement, du gouvernement et de l’administration et qui portent notamment sur les votations et les élections.

de: Die Standeskanzlei liefert ausgewählte Open Government Daten aus den Bereichen Parlament, Regierung und Verwaltung, insbesondere zu Abstimmungen und Wahlen.

en: The State Chancellery provides selected open government data from parliament, government and administration, particularly on votes and elections.

it: La Cancelleria fornisce dati selezionati dai settori Parlamento, Governo e Amministrazione, concernenti in particolare votazioni ed elezioni, come Open Government Data.

value: GR-Kt - Standeskanzlei - DCAT Harvester


kataster-der-belasteten-standorte-ur

regi

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

title_for_slug: kataster-der-belasteten-standorte-ur

url: https://geo.ur.ch/?layers=Kataster der belasteten Standorte

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

fr: Der Artikel 32c Abs. 2 USG verpflichtet die Kantone, einen öffentlich zugänglichen Kataster der belasteten Standorte zu erstellen. Die Verordnung vom 26. August 1998 über die Sanierung von belasteten Standorten (Altlasten-Verordnung; AltlV) definiert den Begriff "belasteter Standort" (Ablagerungsstandorte, Betriebsstandorte, Unfallstandorte) und legt die Art und Weise fest, wie diese Kataster erstellt und geführt werden soll und welchen Inhalt er aufzuweisen hat.

fr: Kataster der belasteten Standorte (UR)

de: Kataster der belasteten Standorte (UR)

en: Kataster der belasteten Standorte (UR)

it: Kataster der belasteten Standorte (UR)


fr: nutzungsplanung zonenplan kanton oreb flachennutzungsplan

fr: WFS-Dienst des Kantons Schwyz

de: WFS-Dienst des Kantons Schwyz

en: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

fr: OeREB Nutzungsplanung kantonal Teil Siedlung, Seewen Schwyz, überlagernde Festlegung

fr: OeREB Nutzungsplanung kantonal Teil Siedlung, Seewen Schwyz, linienbezogene Festlegung

fr: OeREB Nutzungsplanung kantonal Teil Siedlung, Seewen Schwyz, Grundnutzung

fr: Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz

de: Das Amt für Geoinformation verwaltet und veröffentlicht die Geodaten des Kantons Schwyz als OGC-Geodienste und als Datei-Download. Alle aktuell verfügbaren Geodaten, welche dem OGD unterliegen, sind hier aufgeführt.

fr: Nutzungsplanung kantonal Teil Siedlung, Gebiet Seewen-Schwyz


pedibus-arret

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

regi

fr: Régions et villes

de: Regionen und Städte

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: pedibus-arret

label: Les services sont exposés au travers de l'API REST d'ArcGIS Server. Interfaces supportées : REST - SOAP - WMS - WFS

label: "Lien vers le géoportail SITG pour prévisualisation de la donnée"

fr: SERVICE DE TELECHARGEMENT

de: SERVICE DE TELECHARGEMENT

en: SERVICE DE TELECHARGEMENT

it: SERVICE DE TELECHARGEMENT

fr: Les données vectorielles sont disponibles sous forme de fichiers.zip, incluant la donnée dans le format choisi, sa fiche de métadonnée (.pdf) ainsi que les conditions générales d'utilisation (.pdf). Sauf exception, les formats suivant sont proposés: SHAPE (ESRI) - Geodatabase-File (ESRI) - GML - KML - CSV

fr: Une ligne Pédibus est un itinéraire d'accès à pied à une école sur lequel les enfants sont encadrés par des parents d'élèves bénévoles pour former un petit bus à pied. Les arrêts des lignes sont marqués au moyen d'un panneau et les horaires sont définis en début d'année scolaire en fonction des besoins des familles. Le trajet jusqu'à l'école se fait ainsi en toute sécurité, le Pédibus permet aux parents de se décharger d'une partie des trajets quotidiens, il est convivial pour les parents et gai pour les enfants et il permet un apprentissage de l'autonomie pour les enfants. Cette couche est complémentaire à la couche des Lignes Pédibus.

spatial: Genève

fr: SITG - Système d'information du territoire à Genève

de: SITG - Genfer Geoinformationssystem

en: SITG - The territorial information system of Geneva

it: SITG - Sistema informativo territoriale di Ginevra

fr: Le Système d’Information du Territoire à Genève (SITG) est un organisme fondé sur un réseau de partenaires publics ayant pour but de coordonner, centraliser et diffuser les géodonnées relatives au territoire genevois, produites dans le cadre de leurs missions.

de: Das Genfer Geoinformationssystem (SITG) ist eine Organisation zur Koordination, Zentralisierung und Bereitstellung sämtlicher Geodaten, die durch verschiedene öffentliche Einrichtungen im Rahmen ihrer Missionen produziert werden.

en: The territorial information system of Geneva (SITG) is an organization based on a network of public partners aiming to coordinate, centralize and distribute the geodata of the territory of Geneva.

it: Il Sistema Informativo Territoriale di Ginevra (SITG) è un'organizzazione basata su una rete di partner pubblici con lo scopo di coordinare, centralizzare e pubblicare i dati spaziale del territorio di Ginevra, prodotti come parte delle loro missioni.

value: SITG - Geocat Harvester

fr: PEDIBUS - ARRET

de: PEDIBUS - ARRET

en: PEDIBUS - ARRET

it: PEDIBUS - ARRET


de: nutzungsplanung zonenplan kanton oreb flachennutzungsplan

fr: OeREB Nutzungsplanung kantonal Teil Siedlung, Brunnen Nord, Grundnutzung

fr: OeREB Nutzungsplanung kantonal Teil Siedlung, Brunnen Nord, überlagernde Festlegung

fr: OeREB Nutzungsplanung kantonal Teil Siedlung, Brunnen Nord, linienbezogene Festlegung

de: Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

fr: Nutzungsplanung kantonal Teil Siedlung, Gebiet Brunnen-Nord


educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

de: Les données vectorielles sont disponibles sous forme de fichiers.zip, incluant la donnée dans le format choisi, sa fiche de métadonnée (.pdf) ainsi que les conditions générales d'utilisation (.pdf). Sauf exception, les formats suivant sont proposés: SHAPE (ESRI) - Geodatabase-File (ESRI) - GML - KML - CSV

fr: AGREGATION DES STATISTIQUES CANTONALES DE LA POPULATION ET DU PARC IMMOBILIER (Information aux secteurs de la ville de Genève) Les informations sur la population proviennent de la statistique cantonale de la population, celles sur les bâtiments et les logements proviennent de la statistique du parc immobilier. La statistique cantonale de la population prend en compte les personnes d'origine suisse et les ressortissants étrangers titulaires d'une autorisation de séjour officielle qui habitent effectivement dans le canton. Elle se fonde sur les informations détenues par l'Office cantonal de la population et des migrations (OCPM). Pour plus d'informations sur les bases méthodologiques de cette statistique: https://statistique.ge.ch/domaines/01/01_01/methodologie.asp La statistique du parc immobilier repose sur le Registre fédéral des bâtiments et des logements (RegBL).Pour des raisons liées au rythme de mise à jour de l'information, il est possible que des bâtiments présents dans le RegBL soient absents du SITG. En effet, le RegBL présente un état en fin de trimestre, alors que les informations du SITG sont actualisées quotidiennement. La date de mise à jour est de 2 mois après la fin d'un trimestre. Pour plus d'informations sur cette statistique: https://statistique.ge.ch/domaines/09/09_02/methodologie.asp#1

fr: AGREGATION STATISTIQUES POPULATION ET PARC IMMOBILIER (Secteurs ville de Genève)


schneeschuhrouten

title_for_slug: schneeschuhrouten

fr: itineraire sport-de-neige

de: route schneesport

en: route snowsport

it: itinerario sport-della-neve

fr: Accès aux données (fr) : téléchargement et services web (Géoportail cantonal)

fr: Datenzugriff (de): Download und Webservices (Kantonales Geoportal)

fr: Itinéraires en raquette

fr: Map (Preview) Visualisation des données

de: Map (Preview) Visualisierung der Daten

en: Map (Preview) Visualization of the data

it: Map (Preview) Visualizzazione dei dati

fr: Visualisation des données

de: Visualisierung der Daten

en: Visualization of the data

it: Visualizzazione dei dati

fr: Les itinéraires en raquette numériques se basent sur les cartes de sports de neige 1:50'000 et la carte nationale au 1:50'000. Ils contiennent des informations spécifiques aux sports de neige en régions alpine et préalpine. Conditions particulières d'utilisation des données relatives aux randonnées en raquettes et à skis: Les itinéraires en raquettes et à ski qui ont été tracés à l'échelle 1:50'000 constituent uniquement des indications générales de direction. Ni le Club Alpin Suisse CAS, ni l'Office fédéral de topographie, ni l'Etat de Fribourg ne garantissent l'exactitude, l'exhaustivité et l'actualité des données relatives aux randonnées. Ils déclinent également toute responsabilité pour d'éventuels accidents survenant suite à l'utilisation d'informations relatives aux randonnées. Il est vivement recommandé de planifier minutieusement ses courses. Vous trouverez une description détaillée des itinéraires dans les guides du CAS.

de: Die digitalen Schneeschuhrouten basieren auf der Schneesportkarte 1:50'000 und auf der Landeskarte 1:50'000. Sie enthalten spezifische Angaben für den Schneesport im alpinen und voralpinen Gebiet der Schweiz. Besondere Nutzungsbedingungen für die Schneeschuh- und Skiroutendaten: Die Ski- und Schneeschuhrouten sind als allgemeine Richtungsangaben zu verstehen, welche im Massstab 1:50‘000 gezeichnet wurden. Für die Richtigkeit, Vollständigkeit und Aktualität der Routenangaben übernehmen weder der Schweizer Alpen-Club SAC noch das Bundesamt für Landestopografie noch noch der Staat Freiburg eine Gewähr. Für allfällige Unfälle, die sich aus der Verwendung der Information aus den Routendaten ereignen, wird jede Haftung abgelehnt. Eine sorgfältige Tourenplanung wird dringend empfohlen. Der detaillierte Routenverlauf ist im entsprechenden SAC-Tourenführer beschrieben.

spatial: Canton de Fribourg (FR)

fr: Geoinformation Canton Fribourg

de: Geoinformation Kanton Freiburg

en: Geoinformation Canton Fribourg

it: Geoinformazione Canton Friburgo

fr: Les géodonnées publiques du Canton Fribourg sont gérées par le Centre de compétence SIT du Service du cadastre et de la géomatique SCG et mises à disposition sous forme de services web et de téléchargement via le géoportail cantonal.

en: The public geodata of the Canton Fribourg are managed by the GIS Competence Center of the Office of Surveying and Geomatics (VGA) and made available via the cantonal geoportal as web services and for download.

de: Die öffentlichen Geodaten des Kantons Freiburg werden durch das GIS-Kompetenzzentrum des Amtes für Vermessung und Geomatik VGA verwaltet und über das kantonale Geoportal als Webservices und zum Download bereitgestellt.

it: I geodati pubblici del Canton Friburgo sono gestiti dal Centro di competenza GIS dell'Ufficio della Misurazione e della Geomatica (SCG) e messi a disposizione tramite il geoportale cantonale come servizi web e per il download.

value: Fribourg-Kt - Geocat Harvester

de: Schneeschuhrouten


agglo-atlas-culturel-transfrontalier

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

regi

fr: Régions et villes

de: Regionen und Städte

title_for_slug: agglo-atlas-culturel-transfrontalier

fr: SERVICE DE TELECHARGEMENT

fr: Les données vectorielles sont disponibles sous forme de fichiers.zip, incluant la donnée dans le format choisi, sa fiche de métadonnée (.pdf) ainsi que les conditions générales d'utilisation (.pdf). Sauf exception, les formats suivant sont proposés: SHAPE (ESRI) - Geodatabase-File (ESRI) - GML - KML - CSV

fr: Principalement destiné aux professionnels de l'aménagement et de la culture, l'atlas culturel transfrontalier recense l'ensemble des lieux culturels de l'agglomération franco-valdo-genevoise, et les présente de manière géo localisée. Les lieux sont classés par type d'usage (diffusion, création, conservation, etc.) ainsi que par domaine d'activité (musique, théâtre, musée etc.). Les lieux d'enseignement (danse, musique, etc.) font également l'objet d'informations spécifiques. Il propose deux types d'entrées : - une représentation de tous les lieux qui programment ou abritent une activité culturelle (y compris les lieux considérés comme amateurs) dans l'agglomération. - une représentation des seuls lieux considérés comme professionnels.

name: Office cantonal de la culture et du sport

fr: SITG - Système d'information du territoire à Genève

fr: Le Système d’Information du Territoire à Genève (SITG) est un organisme fondé sur un réseau de partenaires publics ayant pour but de coordonner, centraliser et diffuser les géodonnées relatives au territoire genevois, produites dans le cadre de leurs missions.

fr: AGGLO - ATLAS CULTUREL TRANSFRONTALIER

de: AGGLO - ATLAS CULTUREL TRANSFRONTALIER

en: AGGLO - ATLAS CULTUREL TRANSFRONTALIER

it: AGGLO - ATLAS CULTUREL TRANSFRONTALIER


educ

fr: Éducation, culture et sport

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

regi

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

de: SERVICE DE TELECHARGEMENT

en: Les données vectorielles sont disponibles sous forme de fichiers.zip, incluant la donnée dans le format choisi, sa fiche de métadonnée (.pdf) ainsi que les conditions générales d'utilisation (.pdf). Sauf exception, les formats suivant sont proposés: SHAPE (ESRI) - Geodatabase-File (ESRI) - GML - KML - CSV

fr: Les points de raccordement matérialisent le raccordement d'un collecteur sur un autre collecteur lorsque celui-ci n'est pas fait au travers d'un ouvrage. Ces objets font également partie du produit "Cadastre du réseau d'assainissement des eaux".

de: SITG - Genfer Geoinformationssystem

fr: RESEAU D'ASSAINISSEMENT DES EAUX - POINT DE RACCORDEMENT


grilles-de-sols-lineaires

soci

en: Population and society

title_for_slug: grilles-de-sols-lineaires

it: Les données vectorielles sont disponibles sous forme de fichiers.zip, incluant la donnée dans le format choisi, sa fiche de métadonnée (.pdf) ainsi que les conditions générales d'utilisation (.pdf). Sauf exception, les formats suivant sont proposés: SHAPE (ESRI) - Geodatabase-File (ESRI) - GML - KML - CSV

fr: Les grilles de sol récoltent les eaux de pluie qui ruissellent sur les surfaces imperméabilisées comme les places de stationnement, les places publiques ou les rampes d'accès de parking.

de: Das Genfer Geoinformationssystem (SITG) ist eine Organisation zur Koordination, Zentralisierung und Bereitstellung sämtlicher Geodaten, die durch verschiedene öffentliche Einrichtungen im Rahmen ihrer Missionen produziert werden.

fr: GRILLES DE SOLS LINEAIRES

de: GRILLES DE SOLS LINEAIRES

en: GRILLES DE SOLS LINEAIRES

it: GRILLES DE SOLS LINEAIRES


soci

it: Popolazione e società

educ

de: Bildung, Kultur und Sport

en: SERVICE DE TELECHARGEMENT

de: Les données vectorielles sont disponibles sous forme de fichiers.zip, incluant la donnée dans le format choisi, sa fiche de métadonnée (.pdf) ainsi que les conditions générales d'utilisation (.pdf). Sauf exception, les formats suivant sont proposés: SHAPE (ESRI) - Geodatabase-File (ESRI) - GML - KML - CSV

fr: Les stations de pompage de la géoschématique de l'assainissement représentent les ouvrages de pompage des eaux. La précision géométrique n'est pas comparable à celle du cadastre du réseau d'assainissement des eaux (CRAE) et l'utilisation de ces plans ne fait pas référence pour déterminer les conditions exactes de raccordement d'une construction existante ou projetée. Ces objets font également partie du produit "Géoschématique de l'assainissement".

fr: GEOSCHEMATIQUE DE L'ASSAINISSEMENT - STATION DE POMPAGE


ouvrages-du-lit-des-cours-deau

soci

fr: Population et société

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

title_for_slug: ouvrages-du-lit-des-cours-deau

it: SERVICE DE TELECHARGEMENT

fr: Cette couche recense les ouvrages situés dans le lit des cours d'eau, tels que cunettes, radiers, rampes, échelles à poissons, etc. Aux informations générales de génie civil s'ajoute une évaluation de l'impact écologique de l'ouvrage sur l'environnement. En général une photo illustre l'ouvrage.

en: SITG - The territorial information system of Geneva

fr: OUVRAGES DU LIT DES COURS D'EAU

de: OUVRAGES DU LIT DES COURS D'EAU

en: OUVRAGES DU LIT DES COURS D'EAU

it: OUVRAGES DU LIT DES COURS D'EAU


rdppf-zones-de-developpements

regi

fr: Régions et villes

title_for_slug: rdppf-zones-de-developpements

fr: SERVICE DE TELECHARGEMENT

fr: Les données vectorielles sont disponibles sous forme de fichiers.zip, incluant la donnée dans le format choisi, sa fiche de métadonnée (.pdf) ainsi que les conditions générales d'utilisation (.pdf). Sauf exception, les formats suivant sont proposés: SHAPE (ESRI) - Geodatabase-File (ESRI) - GML - KML - CSV

fr: Pour déterminer l'affectation du sol sur l'ensemble du territoire cantonal, celui-ci est réparti en zones, dont les périmètres sont fixés par des plans annexés à la loi d'application de la loi fédérale sur l'aménagement du territoire. Il y a trois catégories de zones: - les zones ordinaires - les zones de développement - les zones protégées Les zones de développement sont assimilées à des zones d'affectation différée au sens de l'article 18 al. 2 LAT, qui se superposent à une zone primaire, ditede fond. Ces plans définissent l'affectation générale des terrains englobés dans leur périmètre. Elles peuvent être vouées à des affectations spécifiques qui précisent celles visées aux articles 19 (zone à bâtir ordinaire), 30 (zone de développement industriel et artisanal ou vouée à des activités mixtes) et 30A LaLAT (zone de développement affecté à de l'équipement public) ou au besoin de s'en écarter. L'adoption préalable par le Conseil d'État d'un plan localisé de quartier ou d'un plan directeur, précisant certains éléments de détail, y est en principe nécessaire, de même qu'un contrôle des prix et des plans financiers de l'objet à construire, pour permettre la délivrance d'une autorisation de construire.

it: SITG - Sistema informativo territoriale di Ginevra

en: The territorial information system of Geneva (SITG) is an organization based on a network of public partners aiming to coordinate, centralize and distribute the geodata of the territory of Geneva.

it: Il Sistema Informativo Territoriale di Ginevra (SITG) è un'organizzazione basata su una rete di partner pubblici con lo scopo di coordinare, centralizzare e pubblicare i dati spaziale del territorio di Ginevra, prodotti come parte delle loro missioni.

fr: RDPPF - ZONES DE DEVELOPPEMENTS

de: RDPPF - ZONES DE DEVELOPPEMENTS

en: RDPPF - ZONES DE DEVELOPPEMENTS

it: RDPPF - ZONES DE DEVELOPPEMENTS


points-noirs-sur-le-reseau-routier

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: points-noirs-sur-le-reseau-routier

fr: L'application MISTRA VUGIS de l'Office Fédéral des routes (OFROU) qui est un outil de visualisation et d'analyses géographiques des accidents de la circulation saisis par les policiers met à disposition une procédure de calcul des points noirs. La détermination des points noirs se base sur la norme VSS SNR 641724 qui est en vigueur depuis 2013. Elle se base sur les catégories de gravité de l'accident (morts, blessés graves, blessés légers), sur le nombre d'occurrences sur une période de 3 ans et sur le type de route (autoroute/semi-autoroute, hors localité, en localité). La période de référence des données est: 2020 - 2022

fr: SITG - Système d'information du territoire à Genève

fr: Le Système d’Information du Territoire à Genève (SITG) est un organisme fondé sur un réseau de partenaires publics ayant pour but de coordonner, centraliser et diffuser les géodonnées relatives au territoire genevois, produites dans le cadre de leurs missions.

fr: POINTS NOIRS SUR LE RESEAU ROUTIER

de: POINTS NOIRS SUR LE RESEAU ROUTIER

en: POINTS NOIRS SUR LE RESEAU ROUTIER

it: POINTS NOIRS SUR LE RESEAU ROUTIER


educ

fr: Éducation, culture et sport

en: Education, culture and sport

it: Istruzione, cultura e sport

ener

fr: Énergie

envi

fr: Environnement

fr: Les ouvrages spéciaux de la géoschématique de l'assainissement représentent les principaux ouvrages situés sur le réseau d'assainissement: déversoirs d'orage, trop-plein, répartiteurs de débit, bassins de rétention, etc. La précision géométrique n'est pas comparable à celle du cadastre du réseau d'assainissement des eaux (CRAE) et l'utilisation de ces plans ne fait pas référence pour déterminer les conditions exactes de raccordement d'une construction existante ou projetée. Ces objets font également partie du produit "Géoschématique de l'assainissement".

fr: GEOSCHEMATIQUE DE L'ASSAINISSEMENT - OUVRAGES SPECIAUX


soci

fr: Population et société

fr: Selon la statistique structurelle des entreprises (STATENT), toute personne qui exerce une activité professionnelle indépendante ou salariée et dont le revenu est obligatoirement soumis à une cotisation AVS représente un emploi. Seuls les résultats des secteurs secondaire et tertiaire sont fournis. Les résultats sont arrondis à l'entier. Par conséquent, leur somme peut ne pas correspondre exactement au total ou aux sous-totaux publiés par l'OCSTAT. Pour plus d'informations sur cette statistique: https://statistique.ge.ch/domaines/06/06_02/methodologie.asp

fr: STATISTIQUE STRUCTURELLE DES ENTREPRISES (Information aux secteurs de la ville de Genève)