en: avalanche snow hazard-mapping natural-hazard satellite

en: SPOT6 Avalanche outlines 24 January 2018

en: Shapefile of the manually mapped avalanche outlines. Please only use this data together with the example key document provided with this dataset.

en:
Outlines of 18'737 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 24 January 2018. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping.pdf)

The generation of the data is described in:

Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.

Abstract.
Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12’500 km2).

We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18’737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.

This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data is of great value to validate avalanche bulletins, complete existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.

Koordinate System: CH1903+ LV95 LN02

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


maintainer: EnviDat Support

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

state: active

type: dataset

en: Site aerial photo (Lausanne)

media_type: image/jpeg

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

format: SERVICE

mimetype: image/jpeg

en: Field station data (LAF)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Data plot of the field station (LAF)

media_type: application/pdf

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

format: PDF

mimetype: application/pdf

en: Site photo of the field station (LAF)

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

en: Site photo of the forest station (LAB)

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

en: Forest station data (LAB)

en: Data plot of the forest station (LAB)

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 Lausanne in Switzerland where one station is located within a natural mixed forest stand (LAB) with European beech (_Fagus sylvatica_; 160-170 yrs), European silver fir (_Abies alba_; 160-170 yrs) and Norway spruce (_Picea abies_; 160-170 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, LAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lausanne is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

education

fr: Education, science

de: Bildung, Wissenschaft

en: Education and science

it: Formazione e scienza

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

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


causal-effect-of-lup

title_for_slug: causal-effect-of-lup

en: plan-evaluation land-use-change annual-effect land-use-planning psm-did

en: causal-effect-of-lup

media_type: ZIP

en:
Data.dbf contains the varibles of 1662 villages in Zhangzhou Cities
PSM_DID.R can re-produce the results

format: ZIP

en:
Title: Does zoning contain built-up land expansion? Causal evidence from Zhangzhou City, China.

Research objective: Built-up land zoning is an imporatant policy measure of land use planning (LUP) to contain built-up land expansion in China. We used a difference-indifference model with propensity score matching to estimate the average and annual effect of built-up land zoning on built-up land expansion in Zhangzhou City, China between 2010 and 2020.

Data: Data.dbf contains the varibles of 1662 villages in Zhangzhou Cities in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020.
XZQDM2 is villages' unique administrative ID;
Area is the land area of village i;
Dis2water is the Euclidean distance from village i to the nearest waterbody;
Dis2coastl is the Euclidean distance from village i to the nearest coastline;
Dis2city is the the Euclidean distance from village i to the city center;
Dis2county is the the Euclidean distance from village i to the nearest county center;
Elevation is the the average elevation within village i;
Dis2road is the the Euclidean distance from village i to the nearest road;
Nei_Built_ is the the area of built-up land (Nei Built.upit) in the neighboring villages of village i in year t;
Treated is a binary variable, Treated = 1 to the villages that were partially or entirely located inside the development-permitted zones, and Treated = 0 to the villages that were entirely located outside the development-permitted zones;
Intensity is the percentage of land that was assigned to the development-permitted zones in village i;
Year represent the year in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020;
BuLE is the dependent variable, representing built-up land expansion in village i in year t;
Town is town' unique administrative ID.

Method: First, we employed propensity score matching to overcome the selection bias and satisfy the parallel trend
assumption. Second, we built four Difference-in-Difference models to estimate the average and annual effect.

annual-effect

display_name: annual-effect

land-use-change

display_name: land-use-change

land-use-planning

display_name: land-use-planning

plan-evaluation

display_name: plan-evaluation

psm-did

display_name: psm-did

en: Causal effect of LUP


maintainer: Marcia Phillips

en: borehole meteo-station ritigraben permos permafrost

en: DATA ACCESS

media_type: SMET

en: Meterological station at the [Ritigraben permafrost borehole](http://www.envidat.ch/dataset/rit1) (RIT_0102) in canton Valais, Switzerland. The station is located at 2690 m asl on a flat site.

borehole

display_name: borehole

meteo-station

display_name: meteo-station

permafrost

display_name: permafrost

permos

display_name: permos

ritigraben

display_name: ritigraben

en: RIT2: Meteorological station at Ritigraben borehole site


en: landuse cryowrf wrf antarctica topography

en: Documentation

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

en: Scripts

media_type: application/zip

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

mimetype: application/zip

en: WPSinput

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

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

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

en: REMA topography and AntarcticaLC2000 for WRF


maintainer: Albrecht von Boetticher

en: shallow-landslide debris-flow finite-volumes murgang dberisintermixing interfoam natural-hazard hangmuren barrier-impact-simulation

en: These are the installation instructions for debrisInterMixing4

en:
This version of debrisInterMixing is based on OpenFOAM Version 4.x and was tested on Ubuntu 18.04.1 LTS.
Please follow the instructions given in ReadMe_debrisInterMixing4.pdf for installation.

en: debrisInterMixing for OF-Version 6

en: Installation Instructions for debrisInterMixing-6

en:
Here the updated versions of debrisInterMixing are provided for download. The first OpenFoam-compatible Version 2.3.x are available as supplement to v. Boetticher, A., Turowski, J. M., McArdell,W. B., Rickenmann, D., Hürlimann, M., Scheidl, C., and Kirchner, J. W.: DebrisInterMixing-2.3: A Finite Volume solver for three dimensional debris flow simulations based on two calibration parameters. Part two: model validation with experiments. Geoscientific Model Development, 10, 11: 3963-3978. doi: 10.5194/gmd-10-3963-2017.
DebrisInterMixing is a Volume-of-Fluid based Finite Volume code that accounts for shear-thinning sensitive shares of fine sediment suspension together with pressure-sensitive components of the gravel grains within debris flow mixtures. All model properties can be derived from a material sample except for a grid-sensitive calibration parameter.
For more information, please contact albrecht.vonboetticher@wasserbau.ch.

barrier-impact-simulation

display_name: barrier-impact-simulation

dberisintermixing

display_name: dberisintermixing

debris-flow

display_name: debris-flow

finite-volumes

display_name: finite-volumes

hangmuren

display_name: hangmuren

interfoam

display_name: interfoam

murgang

display_name: murgang

natural-hazard

display_name: natural-hazard

shallow-landslide

display_name: shallow-landslide

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Three-dimensional debris flow simulation tool debrisInterMixing


maintainer: Michael Lehning

en: snowpack terrestrial-laser-scanning winter-tourism snow-conservation snow snow-farming

en: HS Fluela spring 2015

media_type: text/plain

en:
Snow depth/ height of snow heap in spring 2015 obtained by terrrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903

format: TXT

mimetype: text/plain

en: Martell .smet

en: Meteodata used as input for SNOWAPCK simulations, orginating from Station Hintermartell.

en: HS Fluela autumn 2015

en:
Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903
Nodata: -9999

en: Fluela .smet

en: Meteodata used as input for SNOWAPCK simulations, orginating from Station Windtunnel and DAV.

en: HS Martell spring 2015

en:
Snow depth/ height of snow heap in spring 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

en: Fluela .sno

media_type: SNO

en: Input snow profile (.sno file) used for SNOWPACK simulations of the Flüela heap

en: HS Martell autumn 2015

en:
Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

en: Martell .sno

en: Input snow profile (.sno file) used for SNOWPACK simulations of the Martell heap

en:
Two data sets obtained for snow farming projects (Fluela, Davos, CH and Martell, IT) in 2015.

The data set contains for each site:

* 10 cm GIS raster of snow depth calculated from terrestrial laserscanning surveys (TLS) in the end of winter season (April/May)

* 10 cm GIS raster of snow depth calculated from TLS in the end of summer season (October)

Input files for SNOWPACK model:

* .sno: snow profile at the end of winter

* .smet: meteorological data measured by weather stations in the area

For more details see Grünewald, T., Lehning, M., and Wolfsperger, F.: Snow farming: Conserving snow over the summer season, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-93, in review, 2017.

snow

display_name: snow

snow-conservation

display_name: snow-conservation

snow-farming

display_name: snow-farming

snowpack

display_name: snowpack

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

winter-tourism

display_name: winter-tourism

en: Snowfarming data set Davos and Martell 2015


maintainer: Axel Volkwein

en: trajectory mass-movements rockfall field-data experiments field-test field-tests natural-hazards experiment

en: Block trajectories recorded from local positioning system

media_type: ascii, tab separated, also as Excel table

en: This file contains more than 80 rockfall trajectories projected onto the terrain, i.e. the positions of the single blocks over time during the single tests that were recorded by the local positioning system with about 10Hz. It contains the detected positions as well as a smoothened path (see Volkwein et al., Geosciences, 2018). The table also contains the derived velocities and accelerations along the slope (attention: these accelerations are the once that occur during an impact).

en: Jumps and impacts

media_type: ascii, tab separated, also as excel table

en: This table contains data of more than 2200 of each jumps and impacts of the test blocks on a grassy slope. It gives there durations in combination with acting accerlartions and the rotational speed of the blocks. The data were retrieved using the block internal accelerometer and rotation sensors. The combination of these data with the measurement from the local positioning system allows the deduction of jump lengths, slope gradient etc.

en: Overview of all tests

en:
This table gives an overview on all tests performed including
- block used
- start & end position
- number of jumps
- etc.
-

en: These data contain the point clouds obtained from laser scanning the test slope and the six test blocks used for the experiments. The coordinates of the slope are given in CH-1903 format. The coordinates of the block point clouds are kept in a lokal x/y/z coordinate system.

en:
In summer 2014, 6 rock blocks between 20 and 80kg have been thrown in total 111 times down a slope at the Swiss Oberalppass close to the village Tschamut. The slope was mainly covered by grass and its lower part was flat and large enough to provide natural runouts of the single trajectories.

An extensive measurement program has been set up to measure the block trajectories: With surveyor's instruments the slope and the six used rock blocks were scanned and the start and end positions of each test were recorded. During the single events two cameras filmed the trajectories. A special sensor device located within the blocks recorded the acting accelerations and rotational speeds over time. Further, the device emitted a Wifi signal that got detected from eight receivers around the slope. Based on this signal the block position has been recorded over time.

The dataset contains all data that were gathered through above field campaign.

experiment

display_name: experiment

experiments

display_name: experiments

field-data

display_name: field-data

field-test

display_name: field-test

field-tests

display_name: field-tests

mass-movements

display_name: mass-movements

natural-hazards

display_name: natural-hazards

rockfall

display_name: rockfall

trajectory

display_name: trajectory

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Repetitive trajectory testing in Tschamut 2014


en: erosion model snow mars sediment-transport

en: Datasets of Figure 2

en: Datasets of Figure 4a

en: Datasets of Figure 4b

en: Datasets of Figure 3a

en: Datasets of Figure 3b

en:
The files contain the datasets used to produce Figures 2, 3, and 4 of the manuscript ([doi: 10.1002/2016GL071822](http://dx.doi.org/10.1002/2016GL071822)).

 Manuscript Abstract:
Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

en: Energy- and momentum-conserving model of splash entrainment in sand and snow saltation


weather-station-klosters

maintainer: Maxime Hervo

title_for_slug: weather-station-klosters

en: wind precipitation klosters raclets temperature weather

en: Weather Station Klosters

en: All in one weather station measuring temperature (°C), humidity (%), wind (m s‾ ¹) and precipitation type. The time format is: number of days from January 0, 0000, UTC.

en: A weather station (Lufft WS600) measured meteorological parameters at Klosters (LON: 9.880413, LAT: 46.869019). Detailed information on the specifications can be found [here](https://www.lufft.com/products/compact-weather-sensors-293/ws600-umb-smart-weather-sensor-1832/productAction/outputAsPdf/).

klosters

display_name: klosters

precipitation

display_name: precipitation

raclets

display_name: raclets

temperature

display_name: temperature

weather

display_name: weather

wind

display_name: wind


en: snowpack failure-layer snow-profiles snow-stratigraphy snow-instability rutschblock snowpack-simulation

en: DAV data set: Properties of observed snow profiles and simulated failure layers

media_type: CSV

en:
For each profile pair from the DAV data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. The content of the columns is explained in Table 1 of the ReadMe file. Only those profile pairs which fulfilled predefined similarity criteria (column
"similarity_obs_sim" = 1) and which belonged to the stability classes "stable" and "unstable" (column "stability_class"
= 0 or 1) were used to train the RF model. Please note that for each of the two snow profiles with RB score 7 (profile
IDs 7228 and 9526), three additional layers were included in this data set to obtain a balanced set of training data (73
unstable and 73 stable profiles).

en: SWISS data set: Properties of observed snow profiles and simulated failure layers

media_type: .csv

en: For each profile pair from the SWISS data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. Please note that only those profile pairs which fulfilled the similarity criteria (column similarity_obs_sim = 1, 121 profiles) were used to validate the RF model. The content of the columns is explained in Table 1 of the ReadMe file.

en: Simulated snow profiles

en: Simulated snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding observed profile in the "observed_profiles" folder. One row corresponds to one simulated snow layer. The content of the columns 1-7 is described in Table 3 of the ReadMe file. The remaining columns (8-31) contain all features that were used in the development of the RF model and are described in Table 1 of the ReadMe file.

en: Observed snow profiles

en: Observed snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding simulated profile in the "simulated_profiles" folder. One row corresponds to one observed snow layer. The content of the columns is described in Table 2 of the ReadMe file.

en: ReadMe

en: ReadMe file explaining data structure and content

en:
This data set includes information on all observed and simulated snow profiles that were used to train and validate the
random forest model described in Mayer et al. (2022). The RF model was trained to assess snow instability from simulated snow stratigraphy. The data set contains observed snow profiles from the region of Davos (DAV subset, 512 profiles) and from all over Switzerland (SWISS subset, 230 profiles). For each observed snow profile, there is a corresponding simulated profile which was obtained using meteorological input data for the numerical snow cover model SNOWPACK. The information on the observed snow profile contains a Rutschblock test result including the depth of the failure interface. As part of the study described in Mayer et al. (2022), each observed snow profile was manually compared to its simulated counterpart and the simulated layer corresponding to the Rutschblock failure layer was identified.

The data are provided in the following form: one file each per observed and simulated snow profile (2x512 files DAV, 2x230 files SWISS), two files (1 file DAV, 1 file SWISS) containing the observed information on snow instability, the allocation between observed and simulated failure layer, and all features extracted from the simulated weak layers that were used to develop the RF model.

failure-layer

display_name: failure-layer

rutschblock

display_name: rutschblock

snow-instability

display_name: snow-instability

snow-profiles

display_name: snow-profiles

snow-stratigraphy

display_name: snow-stratigraphy

snowpack

display_name: snowpack

snowpack-simulation

display_name: snowpack-simulation

en: Observed and simulated snow profile data


maintainer: Peter Bebi

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

en: FACE experimental design

media_type: PNG

format: PNG

en: FACE DATASETS

en: Project description

en:
 Overview
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 than in most other regions of the world. This project involves 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 to 2009, and a soil warming treatment (+4 K) was added in 2007 (ongoing). 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 is carried out as part of this environmental change project.

#Experimental setup
The experiment consists 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 surrounds 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 10 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
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).

carbon-dioxide

display_name: carbon-dioxide

climate-change

display_name: climate-change

experiment

display_name: experiment

soil-temperature

display_name: soil-temperature

vegetation

display_name: vegetation

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: FACE: Stillberg CO2 enrichment and soil warming study


maintainer: Mahdi Jafari

en: numerical-simulation snow-density-profile openfoam vapor-transport convection-in-snow

en: snowpackBuoyantPimpleFoam

en:
This zipped folder includes (1) the source code files, (2) an example case for simulation, and (3) an instruction how to compile and use the new solver.

Note that the most updated version of snowpackBuoyantPimpleFoam can be found in the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/snow-models/snowpackbuoyantpimplefoam

en: snowpackBuoyantPimpleFoam is a two-phase solver implemented to model convection of water vapor with phase change in snowpacks. This new solver is based on the standard solver of buoyantPimpleFoam in the open-source fluid dynamics software, OpenFOAM 5.0 (www.openfoam.org).

convection-in-snow

display_name: convection-in-snow

numerical-simulation

display_name: numerical-simulation

openfoam

display_name: openfoam

snow-density-profile

display_name: snow-density-profile

vapor-transport

display_name: vapor-transport

en: snowpackBuoyantPimpleFoam: an OpenFOAM Eulerian–Eulerian two-phase solver for modelling convection of water vapor in snowpacks


maintainer: Matthias Haeni

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

en: Forest station data (ALB)

en: Data plot of the forest station (ALB)

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

en: Site aerial photo (Alpthal)

en: Site aerial photo from the Alpthal forest station. Source: Google. 2016. Site aerial photo from the Alpthal forest station. Retrieved November 11, 2016, from https://www.google.ch/maps

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for one meteorological station in Alpthal in Switzerland which is located within a natural coniferous forest (ALB) with Norway spruce (_Picea abies_; 180-230 yrs) as dominant tree species. The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Alpthal 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: Alpthal, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


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

en: Site photo of the field station (VSF)

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

en: Field station data (VSF)

en: Data file.

en: Data plot of the forest station (VSB)

en: Site photo of the forest station (VSB)

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

en: Site aerial photo (Visp)

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

en: Data plot of the field station (VSF)

en: Forest station data (VSB)

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 Visp in Switzerland where one station is located within a natural mixed forest stand (VSB) with Scots pine (_Pinus sylvestris_; 40-80 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, VSF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Visp is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

education

en: Education and science

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


maintainer: Christoph Marty

en: Graubunden input

media_type: application/x-tar

en: Grid input data for the 'Graubunden' CH2014 simulation.

mimetype: application/x-tar

en: CH2014 REPORT

en:
CH2014-Impacts: Toward Quantitative Scenarios of Climate Change Impacts in Switzerland

The CH2014-Impacts report presents the results of a concerted effort of 15 Swiss research institutions to describe impacts of climate change in Switzerland quantitatively. This dataset contributes to the Crosphere/Snowcover section.

en: Dataset

en: Datasets are grouped under experiment "Aare" and "Graubunden".Data is also made available in netCDF format. A range of tools are available to [read netCDF](http://www.unidata.ucar.edu/software/netcdf/software.html).

en: Aare input

en: Grid input data for the 'Aare' CH2014 simulation.

en:
 Overview

The CH2014-Impacts initiative is a concerted national effort to describe impacts of climate change in Switzerland quantitatively, drawing on the scientific resources available in Switzerland today. The initiative links the recently developed Swiss Climate Change Scenarios CH2011 with an evolving base of quantitative impact models. The use of a common climate data set across disciplines and research groups sets a high standard of consistency and comparability of results. Impact studies explore the wide range of climatic changes in temperature and precipitation projected in CH2011 for the 21st century, which vary with the assumed global level of greenhouse gases, the time horizon, the underlying climate model, and the geographical region within Switzerland. The differences among climate projections are considered using three greenhouse gas scenarios, three future time periods in the 21st century, and three climate uncertainty levels (Figure 1). Impacts are shown with respect to the reference period 1980-2009 of CH2011, and add to any impacts that have already emerged as a result of earlier climate change.

 Experimental Setup

Future snow cover changes are simulated with the physics-based model Alpine3D (Lehning et al., 2006). It is applied to two regions: The canton of Graubünden and the Aare catchment. These domains are modeled with a Digital Elevation Model (DEM) with a resolution of 200 m × 200 m. This defines the simulation grid that has to be filled with land cover data and downscaled meteorological input data for each cell for the time period of interest at hourly resolution. The reference data set consists of automatic weather station data. All meteorological input parameters are spatially interpolated to the simulation grid. The reference period comprises only thirteen years (1999–2012), because the number of available high elevation weather stations for earlier times is not sufficient to achieve unbiased distribution of the observations with elevation. The model uses projected temperature and precipitation changes for all greenhouse gas scenarios (A1B, A2, and RCP3PD) and CH2011 time periods (2035, 2060, and 2085).

 Data

Snow cover changes are projected to be relatively small in the near term (2035) (Figure 5.1 top), in particular at higher elevations above 2000 m asl. As shown by Bavay et al. (2013) the spread in projected snow cover for this period is greater between different climate model chains (Chapter 3) than between the reference period and the model chain exhibiting the most moderate change. In the 2085 period much larger changes with the potential to fundamentally transform the snow dominated alpine area become apparent (Figure 5.1 bottom). These changes include a shortening of the snow season by 5–9 weeks for the A1B scenario. This is roughly equivalent to an elevation shift of 400–800 m. The slight increase of winter precipitation and therefore snow fall projected in the CH2011 scenarios (with high associated uncertainty) can no longer compensate for the effect of increasing winter temperatures even at high elevations. In terms of Snow Water Equivalents (SWE), the projected reduction is up to two thirds toward the end of the century (2085). A continuous snow cover will be restricted to a shorter time period and/or to regions at increasingly high elevation. In Bern, for example, the number of days per year with at least 5 cm snow depth will decrease by 90% from now 20 days to only 2 days on average.

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent

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: Alpine3D simulations of future climate scenarios CH2014


lidar-davos-wolfgang

maintainer: Patric Seifert

title_for_slug: lidar-davos-wolfgang

en: raclets lidar polly clouds tropos

en: Raman Lidar Davos

en: A portable Raman lidar system (Polly) from Leibnitz Institute for Tropospheric Research (Tropos) was deployed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Please use this [link](http://polly.tropos.de/?p=lidarzeit&Ort=39), to be directly forwarded to the Davos location and select the date of interest from the calendar (bold numbers). The data can be requested directly at the Polly team.

clouds

display_name: clouds

lidar

display_name: lidar

polly

display_name: polly

raclets

display_name: raclets

tropos

display_name: tropos

en: LIDAR Davos Wolfgang


maintainer: Benjamin Reuter

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

en: 2015-2016 Avalanche problem types from Crocus

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

en: 1999-2017 Avalanche problem types from Crocus

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

en: 2015-2016 Avalanche problem types from SNOWPACK

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

en: 1999-2017 Avalanche problem types from SNOWPACK

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

en: 2015-2016 Seismic avalanche acitivity catalogue

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

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

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

avalanche-danger

display_name: avalanche-danger

avalanche-problem-type

display_name: avalanche-problem-type

crocus

display_name: crocus

snow

display_name: snow

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability

snowpack

display_name: snowpack

weissfluhjoch

display_name: weissfluhjoch

education

en: Education and science

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


en: cmip5 precipitation-amount climate-change orographic-precipitation air-temperature

en: Download Server

en:
Predicting future climatic conditions at high spatial resolution is essential for many applications in science. Here we present data for monthly time series of precipitation and minimum and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation sums at ~5km spatial resolution globally for the years 1850-2100. We validated the performance of the downscaling algorithm by comparing model output with observed climates for the years 1950-2069.

CHELSA_cmip5_ts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

climate-change

display_name: climate-change

orographic-precipitation

display_name: orographic-precipitation

precipitation-amount

display_name: precipitation-amount

envidat

en: EnviDat: the Environmental Data Portal

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

en: High resolution monthly precipitation and temperature timeseries for the period 2006-2100


en: soil-mapping switzerland plants soil-moisture ecological-indicator-values soil-ph landolt ecological-maps

en: Predictors

en: Predictors generated and used in Descombes et al. (2020)

en: Description

en: Description of the predictors provided in this dataset

format: XLS

en:
Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we derived environmental data layers by mapping ecological indicator values (EIVs) in space by using a large set of environmental predictors in Switzerland.

This dataset contains the predictors (raster layers) generated and used in the following publication (Descombes et al. 2020). Only predictors for which we have the rights to share them are provided. Other datasets and predictors can be accessed via the original data provider. Details on the predictors and sources are fully described in the publication. The predictors are provided as GeoTIFF files, at 93 m spatial resolution and Mercator projection ("+proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"). The excel file (xlsx) provides a short description of the raster layers.

Paper Citation:

Descombes, P. et al. (2020). Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes. Ecography. (accepted)

ecological-indicator-values

display_name: ecological-indicator-values

ecological-maps

display_name: ecological-maps

landolt

display_name: landolt

plants

display_name: plants

soil-mapping

display_name: soil-mapping

soil-moisture

display_name: soil-moisture

soil-ph

display_name: soil-ph

switzerland

display_name: switzerland


en:
This dataset contains the statistics on the number of avalanche fatalities per **calendar year** in Switzerland. The data collection commences with the beginning of the year 1937. After the completion of a hydrological year, which is the standard way avalanche fatalities are summarized in Switzerland and ends on the 30th of September, the new data is appended to the existing dataset.
If you require annual statistics per hydrological year, please download the data from here: [https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936]

The following information is contained (by column and column title):
 - year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste, away from open and secured ski runs)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)

The definitions for these four categories, as described in the guidelines to the avalanche accident database are:

tour:
activities include back-country ski, snowboard or snow-shoe touring

offpiste:
access from ski area, generally from the top of a skilift with short hiking distances

transportation.corridors (Techel et al., 2016):
people travelling or recreating on open or temporarily closed transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)

buildings (Techel et al., 2016):
people inside or just outside buildings, and workers on high alpine building sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

en: Number of avalanche fatalities per calendar year in Switzerland since 1937


en: longwave-radiation air-temperature precipitation-amount snow-depth shortwave-radiation humidity

en: Latest data from Stillberg climate station

en: This dataset represents the latest data from the Stillberg climate station updated daily. Automated quality control procedures are applied but no manual checks as in the main dataset.

en: DATA ACCESS

en: Meteorological station data 1975-2016. Outlier analysis and general quality control has been carried out. Station was completely renovated in 2007 and instruments changed. A complete air temperature timeseries can be obtained by combining parameters "TA" and "AIR_TEMP_FUEHLER".

en: Site photo 2

media_type: JPEG

en: Overview plot

en: Overview plots of all variables in timeseries.

en: Site photo 1

en: Snow sensor perpendicular to slope.

en: README

media_type: TXT

en: Description of station parameters and history.

en: STB2 CSV

en: Stillberg meteo as CSV (see smet for metadata header)

en: Site photo 3

en: Longterm meteorological and snow station on a steep (c. 40 degrees) North-East exposed slope at 2090 m a.s.l above Davos, Switzerland. Established 1975 and ongoing measurements made, although instruments have changed during this period. The station is located within a experimental plantation that serves as avalanche protection to downslope communities as well as a unique site for treeline dynamics research.

air-temperature

display_name: air-temperature

humidity

display_name: humidity

longwave-radiation

display_name: longwave-radiation

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

en: Long-term meteorological and snow station at 2090 m a.s.l., Stillberg, Davos, Switzerland (1975 - present)


wind-crust-formation-snowmicropen-data

title_for_slug: wind-crust-formation-snowmicropen-data

en: wind-packing smp snow wind-crust snowmicropen

en: SMP data

media_type: Link

en: Links to the dataset

en: Processing scripts

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

en: Describes the dataset in detail

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

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

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

This dataset is the basis of the following publication:

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

smp

display_name: smp

snow

display_name: snow

snowmicropen

display_name: snowmicropen

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

en: Wind crust formation: SnowMicroPen data


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

en: Data plot of the field station (NAF)

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

en: Forest station data (NAB)

en: Data file.

en: Site photo of the forest station (NAB)

media_type: image/jpeg

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

en: Data plot of the forest station (NAB)

en: Field station data (NAF)

en: Site photo of the field station (NAF)

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

en: Site aerial photo (Nationalpark)

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

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Nationalpark in Switzerland where one station is located within a natural coniferous forest stand (NAB) with mountain pine (_Pinus mugo_; 210 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Nationalpark is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


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

en: Site aerial photo (Isone)

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

en: Field station data (ISF)

media_type: text/csv

en: Data plot of the forest station (ISB)

en: Forest station data (ISB)

en: Site photo of the forest station (ISB)

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

en: Data plot of the field station (ISF)

en: Site photo of the field station (ISF)

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

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

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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

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


maintainer: Ana Beatriz Pierri Daunt

en: resilience pdfsearch landscape-services multifunctionality landscape-ecology sense-of-place decision-making socio-ecological-system planning literature-review landscape-planning ecosystem-services green-infrastructure landscape-perception

en: 6. Protocol

media_type: XLSX

en: 2. Frequency of additional concepts.

en: 4. Use of any additional concept.

en: 1. Frequency of early concepts.

en: 3. Use of any early concept.

en: 5. Planning steps.

en:
Table of content: 1. Frequency of early concepts; 2. Frequency of additional concepts; 3. Use of any early concept; 4. Use of any additional concept, 5. Planning steps; 6. Protocol.

The present dataset is part of the published scientific paper entitled “Landscape ecological concepts in planning: review of recent developments” (Hersperger et al., 2021). The goal of this research was to review recent publications to assess the use of landscape ecological concepts in planning. Specifically, we address the following research questions: Q1. Landscape ecological concepts: What are they? How frequently are they mentioned in current research? Q2. How are landscape ecological concepts integrated in landscape planning?

We analysed all empirical and overview papers that have been published in four key academic journals in the field of landscape ecology and landscape planning in the years 2015–2019 (n = 1918). Four key journals in the field of landscape ecology were selected to conduct the analysis, respectively Landscape Ecology (LE), Landscape Online (LO), Current Landscape Ecology Reports (CLER), and Landscape and Urban Planning (LUP). The title, abstract and keywords of all papers were read in order to identify landscape ecological concepts. Then, all 1918 papers went through a keyword search to identify the use of early and additional concepts. We used the “pdfsearch” package in R programming language and searched for singular and plural forms and different variations of the concepts (see Supplementary material 1, Table A). As a result, we provided four outputs:

  1. Frequency of early concepts. This data provides the total number of times each article used each early concept (Q1). This data was used to produce the Figure 2a at the original publication.

  2. Frequency of additional concepts. This data provides the total number of times each article used each additional concept (Q1). This data was used to produce the Figure 2b at the original publication.

  3. Use of any early concept. This data provides the total number of times each article used any early concept (Q1).
This data was used to produce the Figure 3a at the original publication.

  4. Use of any additional concept. This data provides the total number of times each article used any additional concept (Q1). This data was used to produce the Figure 3b at the original publication.

To address the second question (Q2), the title, abstract and keywords of the papers included in our sample (n=1918 articles) were screened to identify papers that might show how landscape ecological concepts are integrated into planning. We selected 52 empirical papers (see Supplementary material – 4 Integration of landscape ecological concepts into planning), and we provided two outputs:

  5. Planning steps. This data provides the number of times landscape ecological concepts were addressed in each
planning steps in 52 empirical papers analysed in detail (Q2). This data was used to produce the Figure 4 at the
original publication.

  6. Protocol for assessing the integration of landscape ecological concepts into planning. To systematically collect the
data, we used this protocol which addressed the following questions: (a) which type of planning is addressed by the
paper? (b) to which planning level does the paper refer to? (c) which concepts are integrated in any of the planning
steps described above?

decision-making

display_name: decision-making

ecosystem-services

display_name: ecosystem-services

green-infrastructure

display_name: green-infrastructure

landscape-ecology

display_name: landscape-ecology

landscape-perception

display_name: landscape-perception

landscape-planning

display_name: landscape-planning

landscape-services

display_name: landscape-services

literature-review

display_name: literature-review

multifunctionality

display_name: multifunctionality

pdfsearch

display_name: pdfsearch

planning

display_name: planning

resilience

display_name: resilience

sense-of-place

display_name: sense-of-place

socio-ecological-system

display_name: socio-ecological-system

en: The usage of landscape ecological concepts in the planning literature


maintainer: Frank Techel

en: avalanche-observations switzerland norway rutschblock-test extended-column-test avalanche-danger

en: ECT data (Norway, Switzerland)

en: avalanche occurrence data (Norway, Sitzerland) - largest avalanche size per day and warning region

en: Rutschblock data (Switzerland)

en: avalanche occurrence data (Norway, Sitzerland) - avalanche sizes per day and warning region

en:
Observational data used to quantitatively describe the key elements describing avalanche danger: snowpack stability, the frequency distribution of snowpack stability, and avalanche size.
The data set consists of
- Rutschblock test results (Switzerland)
- Extended Column Test results (Switzerland, Norway)
- Avalanche occurrence data (Switzerland, Norway).
The data were extracted from the respective operational databases of the national avalanche warning services in Switzerland (WSL Institute for Snow and Avalanche Research SLF Davos, Switzerland) and Norway (The Norwegian Water Resources and Energy Directorate NVE).
For further information regarding the data, please refer to the publication or contact the author.

avalanche-danger

display_name: avalanche-danger

avalanche-observations

display_name: avalanche-observations

extended-column-test

display_name: extended-column-test

norway

display_name: norway

rutschblock-test

display_name: rutschblock-test

switzerland

display_name: switzerland

en: Stability tests, avalanche observations, Switzerland, Norway


en: video-encoding time-series raster research-data-management gridded-data core geodata sentinel-2

media_type: .sh

en:
Shell script to reproduce the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software for working with CORE will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en: CORE Dataset (80 GB)

media_type: CORE

en: View publication in the Digital Object Repository at WSL (DORA)

media_type: HTML

format: HTML

en:
Shell script to extract data from the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en:
DISCLAIMER: CORE is still in development. Interested parties are warmly invited to join common development, to comment, discuss, find bugs, etc.

Acknowledgement: The CORE format was proudly inspired by the Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) format, by considering how to leverage the ability of clients issuing HTTP GET range requests for a time-series of remote sensing and aerial imagery (instead of just one image).

License: The Cloud Optimized Raster Encoding (CORE) specifications are released to the public domain under a Creative Commons 1.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

-----------------------

Summary:
The Cloud Optimized Raster Encoding (CORE) format is being developed for the efficient storage and management of gridded data by applying video encoding algorithms. It is mainly designed for the exchange and preservation of large time series data in environmental data repositories, while in the same time enabling more efficient workflows on the cloud. It can be applied to any large number of similar (in pixel size and image dimensions) raster data layers. CORE is not designed to replace COG but to work together with COG for a collection of many layers (e.g. by offering a fast preview of layers when switching between layers of a time series).

WARNING: Currently only applicable to RGB/Byte imagery. The final CORE specifications may probably be very different from what is written herein or CORE may not ever become productive due to a myriad of reasons (see also 'Major issues to be solved').

With this early public sharing of the format we explicitly support the Open Science agenda, which implies "shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process" (quote from: European Commission, Directorate General for Research and Innovation, 2016. Open innovation, open science, open to the world).

CORE Specifications:

1) a MP4 or WebM video digital multimedia container format (or any future video container playable as HTML video in major browsers)

2) a free to use or open video compression codec such as H.264, VP9, or AV1 (or any future video codec that is open sourced or free to use for end users)

Note: H.264 is currently recommended because of the wide usage with support in all major browsers, fast encoding due to acceleration in hardware (which is currently not the case for AV1 or VP9) and the fact that MPEG LA has allowed the free use for streaming video that is free to the end users. However, please note that H.264 is restricted by patents and its use in proprietary or commercial software requires the payment of royalties to [MPEG LA](https://www.mpegla.com/programs/avc-h-264/). However, when AV1 matures and accelerated hardware encoding becomes available, AV1 is expected to offer 30% to 50% smaller file size in comparison with H.264, while retaining the [same quality](https://trac.ffmpeg.org/wiki/Encode/AV1).

3) the encoding frame rate should be of one frame per second (fps) with each layer segmented in internal tiles, similar to COG, ordered by the main use case when accessing the data: either layer contiguous or tile contiguous;

Note: The internal tile arrangement should support an easy navigation inside the CORE video format, depending on the use case.

4) a CORE file is optimised for streaming with the moov atom at the beginning of the file (e.g. with -movflags faststart) and optional additional optimisations depending on the codec used (e.g. -tune fastdecode -tune zerolatency for H.264)

5) metadata tags inside the moov atom for describing and using geographic image data (that are preferably compatible with the [OGC GeoTIFF standard](https://www.ogc.org/standards/geotiff) or any future standard accepted by the geospatial community) as well as list of original file names corresponding to each CORE layer

6) it needs to encode similar source rasters (such as time series of rasters with the same extent and resolution, or different tiles of the same product; each input raster should be having the same image and pixel size)

7) it provides a mechanism for addressing and requesting overviews (lower resolution data) for a fast display in web browser depending on the map scale (currently external overviews)

Major issues to be solved:

- Internal overviews (similar to COG), by chaining lower resolution videos in the same MP4 container for fast access to overviews first); Currently, overviews are kept as separate files, as external overviews.

- Metadata encoding (how to best encode spatial extent, layer names, and so on, for each of the layer inside the series, which may have a different geographical extent, etc...; Known issues: adding too many tags with FFmpeg which are not part of the standard MP4 moov atom; metadata tags have a limited string length.

- Applicability beyond RGB/Byte datasets; defining a standard way of converting cell values from Int16/UInt16/UInt32/Int32/Float32/Float64/ data types into multi-band Byte values (and reconstructing them back to the original data type within acceptable thresholds)

Example

Notice: The provided CORE (.mp4) examples contain modified Copernicus Sentinel data [2018-2021].

For generating the CORE examples provided, 50 original Sentinel 2 (S-2) TCI data images from an area located inside Switzerland were downloaded from www.copernicus.eu, and then transformed into CORE format using ffmpeg with H.264 encoding using the [x264 library](https://www.videolan.org/developers/x264.html).

For full reproducibility, we provide the original data set and results, as well scripts for data encoding and extraction (see resources).

core

display_name: core

geodata

display_name: geodata

gridded-data

display_name: gridded-data

raster

display_name: raster

research-data-management

display_name: research-data-management

time-series

display_name: time-series

video-encoding

display_name: video-encoding

education

en: Education and science

envidat

en: EnviDat: the Environmental Data Portal

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


culture

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

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

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

energy

fr: Energie

de: Energie

en: Energy

it: Energia

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

fr: alimentation-en-eau eau-potable

de: wasserversorgung trinkwasser

en: water-supply drinking-water

author: Gemeinde Köniz, Dienstzweig Wasserversorgung

label: geocat.ch permalink

spatial: Köniz

de: Shapefile

de: Download der Daten als Shapefile

de: DWG

de: Download der Daten als DWG

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

dienstzweig-geomatik-gemeinde-koeniz

fr: Section de la géomatique Commune de Köniz

de: Dienstzweig Geomatik Gemeinde Köniz

en: Dienstzweig Geomatik Gemeinde Köniz

it: Ufficio della geomatica Comune di Köniz

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

political_level: commune

value: Dienstzweig Geomatik Gemeinde Köniz – Geocat Harvester

de: Trinkwasserqualität Wasserversorgung Köniz Oberbalm


warmeversorungskarte-gemeinde-koniz

title_for_slug: warmeversorungskarte-gemeinde-koniz

de: SHP

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

name: Gemeinde Köniz, Fachstelle Umwelt und Energie

de: Wärmeversorgungskarte Gemeinde Köniz


maintainer: Dirk Nikolaus Karger

en: free-climate-data climate-layers climate-change climatology bioclim precipitation temperature climate

en: CHELSA Technical Documentation

media_type: PDF

en: Technical documentation document including the variable names, units, scaling, offset, and background.

en: CHELSA V1.2 (deprecated)

media_type: geotiff

en: CHELSA Version 1.2 based on ERA-Interim forcings and CMIP5

format: GeoTIFF

en: CHELSA V2.1 (current)

en: CHELSA Version 2.1 based on ERA5 forcings and CMIP6

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled temperature and precipitation to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction.

CHELSA data published in EnviDat includes the deprecated version 1.2 (originally published under 10.5061/dryad.kd1d4). Please use the current 2.1 version.

Paper Citation:
 > _Karger DN. et al. Climatologies at high resolution for the earth’s land surface areas, Scientific Data, 4, 170122 (2017) [doi: 10.1038/sdata.2017.122](https://doi.org/10.1038/sdata.2017.122)._

bioclim

display_name: bioclim

climate

display_name: climate

climate-change

display_name: climate-change

climate-layers

display_name: climate-layers

climatology

display_name: climatology

free-climate-data

display_name: free-climate-data

precipitation

display_name: precipitation

temperature

display_name: temperature

education

de: Bildung, Wissenschaft

envidat

de: EnviDat: das Umwelt-Datenportal

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.


geography

de: Geographie

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

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"

spatial: Genève

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 nouvelle série de couche en lien avec la gestion du trafic est mise à disposition par l'Office cantonal des transports. Cet ensemble de couche sert à la gestion de tous les équipements des carrefours à feux qui régulent le trafic des véhicules privés et des transports collectifs, mais également les piétons et les cyclistes. Quelques chiffres pour illustrer ces données : plus de 9000 boîtes à feux tout confondu pour les voitures, piétons, cyclistes, bus ou trams, 2180 détecteurs (boutons poussoirs piéton / cycliste ou détecteurs vidéo), 3392 mâts pour maintenir le tout ! Sur un total de 359 armoires qui commande 454 carrefours, ainsi que 164 installations avec des feux clignotants pour les piétons. Ces données servent à l'inventaire, à l'entretien et au dépannage de ces équipements. Ils servent également à prévoir et étudier toutes les modifications apportées régulièrement à ces carrefours. Cette couche représente l'appareillage de détection et d'annonce autre que les boucles, tel que les boutons poussoirs piétons, vélos et transports publics. Ces informations sont utiles aux programmes de régulation des carrefours.

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.

political_level: canton

value: SITG - Geocat Harvester

fr: SIGNALISATION LUMINEUSE - DETECTEURS D'ANNONCES


toits-des-batiments

territory

de: Raum und Umwelt

title_for_slug: toits-des-batiments

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: Emprises des toitures des bâtiments hors-sol, permettant la visualisation des formes de toitures et l'orientation des faces de celles-ci. Ces informations proviennent de la numérisation 3D des bâtiments Voir également la classe d'entités CAD_BATIMENTS_HORSOL_TOIT_SP

name: Direction de l'information du territoire

fr: TOITS DES BATIMENTS

de: TOITS DES BATIMENTS

en: TOITS DES BATIMENTS

it: TOITS DES BATIMENTS


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

en: Data plot of the field station (CLF)

media_type: application/pdf

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

en: Site photo of the forest station (CLB)

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

en: Data plot of the forest station (CLB)

en: Data file.

en: Site photo of the field station (CLF)

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

en: Site aerial photo (Celerina)

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

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Celerina in Switzerland where one station is located within a natural coniferous forest stand (CLB) with Swiss pine (_Pinus cembra_; 210-250 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CLF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Celerina 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

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

wind-speed

display_name: wind-speed

education

fr: Education, science

en: Education and science

envidat

fr: EnviDat: le portail de données environnementales

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


culture

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

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

energy

de: Energie

en: Energy

geography

en: Geography

mobility

en: Mobility and Transport

territory

en: Territory and environment

en: 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: Le pourtour des rives du Rhône en 1726-1728 (Billon) et 1837-1840 (Céard) a été tracé sur la base du plan Billon et de la reconstitution des fortifications au milieu du XVIIIe siècle. Il sera peaufiné dans un deuxième temps pour son extension au-delàdes limites de la ville.

name: Service de l'inventaire des monuments d'art et d'histoire

en: SITG - The territorial information system of Geneva

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.

fr: COURS D'EAU CEARD (1837-1840)

de: COURS D'EAU CEARD (1837-1840)

en: COURS D'EAU CEARD (1837-1840)

it: COURS D'EAU CEARD (1837-1840)


en: stable-water-isotopes alptal streamflow groundwater runoff

en: Deuterium streamwater event A

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

en: Deuterium rainfall event C

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

en: Deuterium streamwater extra event

en: Deuterium groundwater and baseflow October 2017

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

Date: Date (year-month-day)
Location: Well number or outlet
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)
riparian: riparian wells (i.e. from the riparian-like cluster as presented in Kiewiet et al. (2019)) are marked a one, all other wells are marked a zero
d.D (per mil): Deuterium composition (per mil)

en: Precipitation and discharge extra event

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

en: Precipitation and discharge event C

en: Deuterium groundwater and baseflow August 2017

en: Precipitation and discharge event B

en: Deuterium rainfall extra event

en: Deuterium groundwater and baseflow October 2016

en: Deuterium rainfall event A

en: Deuterium streamwater event C

en: Precipitation and discharge event A

en: Deuterium streamwater event B

en: Deuterium rainfall event B

en:
This dataset includes discharge and rainfall measurements and deuterium compositions of streamflow, rainfall and groundwater, for four rainfall events and three baseflow snapshot campaigns in the Studibach (Alptal, Switzerland). More specifically, we present the following data:

- Specific discharge at the catchment outlet at 5-minute resolution (mm per hour);
- Rainfall at 5-minute resolution (mm per hour);
- Rainfall deuterium composition (‰);
- Stormflow deuterium composition (‰);
- Groundwater and baseflow deuterium compositions (‰).

For the files containing rainfall and discharge timeseries (QP), and rainfall and streamwater deuterium compositions ("Deuterium_Rainfall" and "Deuterium_Streamwater"), we added the corresponding event identifier (A, B, C or extra) to the file names. For the files containing the groundwater and baseflow deuterium values ("Deuterium_Snapshot") we added the sample collection date to the file name. We included the X and Y coordinates for each data point (coordinate system: CH1903 LV3) as well as the date and time (UTC).

More information on the data collection and preparation can be found in Kiewiet et al. (in review). A detailed description of the baseflow snapshot campaigns can also be found in Kiewiet et al., 2019.

alptal

display_name: alptal

envidat

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

en: Discharge, rainfall, and deuterium compositions of streamwater, rainwater and groundwater, for four rainfall events in the Studibach, Alptal, Switzerland


geography

fr: Géographie

en: Geography

territory

fr: Territoire et environnement

en: Territory and environment

en: 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: ISOLIGNES DE LA CONDUCTIVITE THERMIQUE MOYENNE POUR DES SONDES DE 50 METRES DE PROFONDEUR Les isolignes ont été calculées à partir du modèle numérique représentant les variations de conductivité thermique du sous-sol pour des sondes de 50m de profondeur, avec une équidistance de 0,2 [W/(mK)]. Afin de donner un rendu plus doux les courbes de niveaux ont été retravaillées par le biais d'un lissage qui ne modifie en rien l'information de base. Modèle numérique avec une maille de 5m. Ces indications ont un caractère général et sont insuffisantes au stade d'un projet d'exécution. Elles ne sauraient en aucun cas remplacer la nécessité d'études géotechniques, le cas échéant. De plus, ces données sont à replacer dans un contexte global de planification multi-usages du sous-sol. Ainsi pour tout projet lié au sous-sol, il conviendra de prendre en compte de nombreuses thématiques complémentaires telles que : - la protection des nappes phréatiques (eau potable) - l'utilisation de l'espace (ouvrages, infrastructures et réseaux divers...) - la possibilité d'extraction de matériaux. - le potentiel géothermique. Rapports sur la géothermie genevoise: https://www.ge.ch/publication?titre=g%C3%A9othermie&type=All&dossier=All&organisation=All

en: SITG - The territorial information system of Geneva

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.

fr: ISOLIGNES CONDUCTIVITE THERMIQUE MOYENNE - SONDES 50 M


archivage-des-adresses

title_for_slug: archivage-des-adresses

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: Chaque intervention dans la gestion des adresses par la DMO laisse une trace dans la table CAD_ADRESSE_ARCHIVE. Une radiation d'adresse, une renumérotation d'adresse ou une modification du type de l'adresse restent donc visibles via cette classe d'objet et il est possible de garder la tracabilité de interventions liées à une adresse en tout temps. Les adresses dont la valeur de l'attribut QUOI (type d'intervention) n'est pas radiée se retrouvent dans la classe d'objet des adresses CAD_ADRESSE Les contraintes d'utilisation sont les mêmes que pour la classe d'objet CAD_ADRESSE Dans la description des attributs, les termes ci-dessous sont à traduire comme suit : - ancien correspond à : avant l'intervention sur l'adresse - nouveau correspond à : après l'intervention sur l'adresse.

fr: ARCHIVAGE DES ADRESSES

de: ARCHIVAGE DES ADRESSES

en: ARCHIVAGE DES ADRESSES

it: ARCHIVAGE DES ADRESSES


construction

fr: Construction, logement

de: Bau- und Wohnungswesen

en: Construction and housing

it: Costruzione e abitazione

culture

en: Culture, media, information society, sport

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

energy

fr: Energie

en: Energy

work

fr: Travail, rémunération

de: Arbeit, Erwerb

en: Work and income

it: Lavoro e reddito

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: Produit secondaire Cette couche contient les données de base permettant d'évaluer le potentiel solaire par bâtiment. Ces données portent notamment sur la répartition des surfaces de toitures par tranche d'irradiation et la répartition mensuelle de l'irradiation solaire. Par exemple, si l'usager souhaite évaluer le potentiel solaire (irradiation) sur les parties de toitures dont l'irradiation est supérieur à 1300 kWh/m2/an, il effectuera la somme pondérée suivante: irradiation solaire totale > 1300 kWh/m2/an = AREA_TOIT * (_13_14 * I_13_14 + _14_20* I_14_20) L'élaboration de cette couche s'inscrit dans le cadre du programme INTERREG V France-Suisse et du projet G2 Solaire. Ce dernier permet à la fois de mettre à jour le précédent cadastre solaire genevois de 2016 (sous mandat de l'OCEN - Office cantonal de l'énergie - et des SIG - Services industriels genevois), et de l'étendre sur le reste du Grand Genève incluant le canton de Genève, le District de Nyon et les communes francaises limitrophes des départements de l'Ain et de Haute Savoie. Le cadastre solaire a été calculé sur le Grand Genève en juin 2019 (sur la base des données LIDAR 2017 Genève, 2014 France, 2015 Vaud), puis mis à jour en janvier 2022 uniquement sur le District de Nyon avec les données LIDAR de 2019. Les données calculées ne tiennent pas compte de bâtiments construits après ces dates.

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: POTENTIEL SOLAIRE - DONNES DE BASE PAR BÂTIMENT


descentes-de-toiture

culture

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

title_for_slug: descentes-de-toiture

fr: Les descentes de toiture sont les points d'arrivée au niveau du sol des chenaux qui récoltent les eaux de pluie des toitures.

fr: DESCENTES DE TOITURE

de: DESCENTES DE TOITURE

en: DESCENTES DE TOITURE

it: DESCENTES DE TOITURE


geography

fr: Géographie

mobility

fr: Mobilité et transports

en: Mobility and Transport

territory

fr: Territoire et environnement

fr: Schéma d'agglomération de 3ème génération (2016) Le réseau routier supra-régional (autoroutes et voies express) constitue l'armature principale du réseau routier d'agglomération. Il assure la fonction de liaison rapide au sein de l'agglomération et entre l'agglomération et ses territoires voisins et la fonction d'écoulement des grands volumes de trafic individuel motorisé au sein des aires urbaines d'agglomération centrale et d'agglomération régionale. - Les autoroutes ou voie express existantes correspondent au réseau en service en 2016 - Les autoroutes ou voie express horizon 2030 correspondent au réseau à mettre en service jusqu'à 2030.

fr: AUTOROUTES SCHEMA D'AGGLOMERATION 3

de: AUTOROUTES SCHEMA D'AGGLOMERATION 3

en: AUTOROUTES SCHEMA D'AGGLOMERATION 3

it: AUTOROUTES SCHEMA D'AGGLOMERATION 3


culture

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

geography

de: Geographie

population

fr: Population

de: Bevölkerung

en: Population

it: Popolazione

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: 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)


geography

it: Geografia

mobility

de: Mobilität und Verkehr

territory

it: Territorio e ambiente

de: SERVICE DE TELECHARGEMENT

fr: GRAPHE DE LA MOBILITE - GRAPHE DES VOIES OFFICIELLES : Le graphe de la mobilité est un regroupement des graphes de base, qui sont la forme géométrique des troncons, et des différentes jonctions (carrefours, arrêts, gares, débarcadères) qui sont les points de connexions, de transferts entre les différents graphes. Ces graphes représentent les différentes voies physiques (et non virtuelles, comme une ligne de bus) sur lesquelles les usagers circulent. Cette donnée: - Graphe des voies officielles gmo_graphe_voies_officielles Autres données disponibles : - Graphe routier gmo_graphe_routier - Graphe de la mobilité douce gmo_mobilite_douce - Graphe des accès parkings gmo_acces_parking - Graphe entretien autoroute gmo_entretien_autoroute - Graphe ferroviaire gmo_ferroviaire - Graphe navigable gmo_voie_navigable - Troncons en projet gmo_troncon_projet - Carrefours gmo_carrefour - Quais de gare gmo_quai_gare - Débarcadères gmo_debarcadere - Aéroports gmo_aeroport - Noeuds en projet gmo_noeud_projet