maintainer: Lyu

en: species-range-map species-distribution-model species-occurrence fagales species-richness pinales

en: Occurrence maps for species of Fagales and Pinales with few records

en: Point_buffer.zip includes 267 occurrence maps of species that do not have enough occurrence data for polygon mapping.

en: Species range maps of species in Fagales and Pinales (with enough occurrences)

en: species_map.zip includes species 1690 range maps generated based on the integrated method described in Lyu et al., (2022). File names with (polygon) indicate that this map is only generated by polygon mapping, as there are not enough occurrences for SDMs.

en:
This database contains 1957 distribution maps of species from Fagales and Pinales constructed based on a method integrating polygon mapping and SDMs (Lyu et al., 2022).
To construct the maps, we first collected occurrence data from 48 different sources. According to the number of occurrences after data cleaning, three kinds of maps are constructed: (1) For species with more than 20 occurrences, we performed SDM and polygon mapping described in Lyu et al. (2022) and select the integration of the two layers as the distribution range; (2) For species with more than 4 but less than 20 occurrences, we only use polygon mapping to draw the distribution range; (3) For species with less than 4 occurrences, a 20-km buffer was generated around the occurrences as the distribution range. The maps were manually checked and evaluated (see Note S3 and Table S9 in Lyu et al., 2022 for details).

fagales

display_name: fagales

pinales

display_name: pinales

species-distribution-model

display_name: species-distribution-model

species-occurrence

display_name: species-occurrence

species-range-map

display_name: species-range-map

species-richness

display_name: species-richness

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: Species distribution maps of Fagales and Pinales (GDPlants)


en: hydrological-response snow-modeling spatial-variability complex-topography snowmelt

state: active

type: dataset

en: Alpine3D output Dischma

media_type: application/zip

format: ZIP

en:
 Abstract
Snow and hydrological modeling in alpine environments remains a challenge because of the complexity of the processes complexity affecting the mass and energy balance. This study examines the influence of snowmelt on the hydrological response of a high-alpine catchment of 43.2 km2 in the Swiss Alps during the water year 2014-2015. Based on recent advances in Alpine3D, we examine how modeled snow distributions, and modeled liquid water transport within the snowpack influence runoff dynamics. By combining these results with multi-scale field data (snow lysimeter data, distributed snow depths and streamflow), we demonstrate the added value of a more realistic representation of snow distribution at the onset of melt season. At the site scale, snowpack runoff is well simulated when the snowpack mass balance errors are corrected (R2 = 0.95 vs. R2 = 0.61). At the sub-basin scale, a more heterogeneous snowpack leads to a more rapid runoff pulse originated in the shallower areas while an extended melting period (by more than a month) is caused by slower snowmelt from deeper areas. This result is a marked improvement over results obtained using a less heterogeneous snow distribution (i.e., traditional precipitation interpolation method). Catchment hydrological response is also improved by the more realistic representation of snowpack heterogeneity (Nash coefficient of 0.85 vs. 0.74), even though the calibration process smoothens out the differences.
The added value of a more complex liquid water transport scheme is obvious at the site scale but decreases at the sub-basin and basin scales. Our results highlight not only the importance but also the difficulty of getting a realistic snowpack distribution even in a well-instrumented area and present a model validation from multi-scale experimental datasets.

complex-topography

display_name: complex-topography

hydrological-response

display_name: hydrological-response

snow-modeling

display_name: snow-modeling

snowmelt

display_name: snowmelt

spatial-variability

display_name: spatial-variability

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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: Influence of slope-scale snowmelt on catchment response simulated with the Alpine3D model


lwf-isone-long-term-research-site

title_for_slug: lwf-isone-long-term-research-site

en: meteorological-data plot swiss-forest-lab lwf meteorological-measurements infrastructure forest

en: Isone Meteorological Data LWF

format: SERVICE

en: LWF plot Isone. Photo: Anne Thimonier Rickenmann, 2011

en:
![alt text](https://www.envidat.ch/dataset/f4b44f60-4eed-471f-a09e-749a0f5f0683/resource/cb8e84ea-ad8b-476e-be32-e02a927d2449/download/lwf_isone.jpg "LWF Isone")

LWF Plot Isone

- Community: Isone / canton TI
- Date of installation: 5 September 1995
- Size of the plot: 2 ha
- Altitude (m): 1181-1259
- Mean slope: 58%
- Geology (in German): Untergrund: Südalpin, präpermisches Grundgebirge, Ceneri Zone; schiefriger Biotitplagioklasgneis - Oberfläche: Quartär; Moräne, Hängeschutt-.
- Provisional soil type (WSL) : Humic Cambisol
- Woodland association after EK72: 4: Luzulo niveae-Fagetum dryopteridetosum
- Main tree species: Fagus sylvatica
- Management system: former coppice
- Silvicultural system: unmanaged
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 37.4 cm
- Number of trees BHD >= 12 cm (2011): 1254
- Maximum tree age: Fagus sylvatica uneven-aged - 70-85-100 yr

More Information: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf/sites/isone.html

forest

display_name: forest

infrastructure

display_name: infrastructure

lwf

display_name: lwf

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

plot

display_name: plot

swiss-forest-lab

display_name: swiss-forest-lab

en: LWF Isone long-term research site


en: spatial-development land-use governance urban-regions strategic-spatial-planning spatial-planning

en: Guiding document for the interview transcripts (Metadata of the written transcripts)

media_type: application/pdf

en: This is a guiding document supporting the dataset Interview guide and transcripts (CONCUR Aim 2 on Governance).

format: PDF

en: This dataset is composed of an interview guide used to conduct 43 in-depth, qualitative, and in-person interviews with planning experts, academics and practitioners, in 14 European urban regions and the corresponding interview transcripts. These interviews were conducted in the selected urban regions between March and September 2016. They were first digitally recorded and later fully transcribed (verbatim).

en: This dataset is composed of an interview guide used to conduct 43 in-depth, qualitative, and in-person interviews with planning experts, academics and practitioners, in 14 European urban regions and the corresponding interview transcripts (verbatim). These interviews were conducted in the selected urban regions between March and September 2016. They were first digitally recorded and later thoroughly transcribed.

governance

display_name: governance

land-use

display_name: land-use

spatial-development

display_name: spatial-development

spatial-planning

display_name: spatial-planning

strategic-spatial-planning

display_name: strategic-spatial-planning

urban-regions

display_name: urban-regions


maintainer: Anita C. Risch

en: soil-chemistry nutrient-network soil mineralization soil-biology grassland global worldwide

en:
site.code: Site code

Continent: Continent

sampleID: Sample ID

nn.latitude: Lattitude

nn.longitude: Longitude

bioclim.T.ann: Mean annual temperature (°C)

bioclim.T.var: Temperature variability (°C)

bioclim.T.q.wet: Temperature of the wettest quarter (°C)

bioclim.T.q.dry: Temperature of the driest quarter (°C)

bioclim.T.q.warm: Temperature of the warmest quarter (°C)

bioclim.P.ann: Mean annual preciptiation (mm)

bioclim.P.q.wet: Precipitation of the wettest quarter (mm)

ch.pH: pH

ch.WSK.vol: Water holding capacity (vol%)

ch.bulkdensity.gcm3: Bulk density (g cm-3)

ch.porespace: Pore space (vol%)

ch.sand.perc: Soil texture: sand (%)

ch.silt.perc: Soil texture: silt (%)

ch.clay.perc: Soil texture: clay (%)

ch.NO3start.mgg: NO3 at the beginning of the incubation (mgkg)

ch.Ntot.perc: Total soil N (%)

ch.Ctot.perc: Total soil C (%)

ch.Corg.perc: Soil organic C (%)

ch.netNminfield.mgkgd: Realised soil net N mineralisation (mg kg-1 d-1)

ch.netNminlab.mgkgd: Potential soil ne N mineralisation (mg kg-1 d-1)

archaea.cpg.log: Ammonia oxidising archaea (archaeal amoA gene copies g-1 soil)

bacteria.cpg.log: Ammonia oxidising bacteria (bacterial amoA gene copies g-1 soil)

micr.biom: Microbial biomass (ug g-1 soil)

ch.CtoN: C to N ratio

ch.netNnitriffield.mgkgd.sqrt: Realised soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniffield.mgkgd.sqrt: Realised soil net ammonification, transformed (mg kg-1 d-1)

ch.netNnitriflab.mgkgd.sqrt: Potential soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniflab.mgkgd.sqrt: Potential soil net ammonifiation, transformed (mg kg-1 d-1)

format: XLS

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

Paper Citation:

Risch, A. C.; Zimmermann, S.; Ochoa-Hueso, R.; Schütz, M.; Frey, B.; Firn, J. L.; Fay, P. A.; Hagedorn, F.; Borer, E. T.; Seabloom, E. W.; et al. Soil net nitrogen mineralisation across global grasslands. Nat. Commun. 2019, 10 (1), 4981 (10 pp.). doi.org/10.1038/s41467-019-12948-2

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

We conducted coordinated measurements of realised and potential soil net Nmin, and assessed water holding capacity, bulk density, C and N content, texture, pH, pore space, microbial biomass, and archaeal (AOA) and bacterial (AOB) ammonia oxidiser abundance using identical materials and methods across 30 grasslands on six continents. The sites covered a globally relevant range of climatic and edaphic conditions. Climate data was obtained from worldclim - Global climate data https://www.worldclim.org/

global

display_name: global

grassland

display_name: grassland

mineralization

display_name: mineralization

nutrient-network

display_name: nutrient-network

soil

display_name: soil

soil-biology

display_name: soil-biology

soil-chemistry

display_name: soil-chemistry

worldwide

display_name: worldwide

envidat

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


maintainer: Michael Lehning

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

en: HS Martell autumn 2015

media_type: text/plain

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

format: TXT

mimetype: text/plain

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: Martell .sno

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

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: Fluela .sno

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

en: HS Fluela spring 2015

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

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

educ

en: Education, culture and sport

en: Snowfarming data set Davos and Martell 2015


maintainer: Adam Winstral

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

en: HS and SWE observations

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

mimetype: application/zip

en: File/data descriptor

en: DEM

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

en: Station forcing data

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

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

jim

display_name: jim

jules-investigation-model

display_name: jules-investigation-model

snow-depth

display_name: snow-depth

snow-simulation

display_name: snow-simulation

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


lwf-celerina-long-term-research-site

title_for_slug: lwf-celerina-long-term-research-site

en: forest swiss-forest-lab meteorological-measurements plot lwf infrastructure meteorological-data

en: Celerina Meteorological Data LWF

en: LWF plot Celerina. Photo: Oliver Schramm, 2011

en:
![alt text](https://www.envidat.ch/dataset/0c244fe7-886a-4a1c-add5-5f706e995a29/resource/28e97caa-65fc-4396-8bca-860721eddfa2/download/lwf_celerina.jpg "LWF Celerina")

LWF Plot Celerina

- Community: Celerina / canton GR
- Date of installation: 3 July 1996
- Size of the plot: 2 ha
- Altitude (m): 1846-1896
- Mean slope: 34%
- Geology (in German): Untergrund: ostalpin; prätriadische Tiefengesteine - Oberfläche: Quartär; karbonatfreie Moräne
- Soil types (WSL): n.d.
- Woodland association after EK72: 59: Larici-Pinetum cembrae
- Main tree species: Pinus cembra
- Management system: high forest
- Silvicultural system: group selection
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 48.6 cm
- Number of trees BHD >= 12 cm (2011): 469
- Maximum tree age: Pinus cembra uneven-aged - 210-250 years

More Information: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf/sites/celerina.html

forest

display_name: forest

infrastructure

display_name: infrastructure

lwf

display_name: lwf

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

plot

display_name: plot

swiss-forest-lab

display_name: swiss-forest-lab

en: LWF Celerina long-term research site


basal-area-of-dead-wood

title_for_slug: basal-area-of-dead-wood

en:
Sum of the stem cross-section areas of all dead trees in a stand at a height of 1.3 m (dbh measurement height).

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

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

altitudinal-vegetation-zone

display_name: altitudinal-vegetation-zone

basal-area-of-dead-wood

display_name: basal-area-of-dead-wood

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

lower-higher-altitudinal-zones

display_name: lower-higher-altitudinal-zones

main-tree-species

display_name: main-tree-species

mechanical-strength-of-wood

display_name: mechanical-strength-of-wood

ownership

display_name: ownership

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

tree-state-standing-lying

display_name: tree-state-standing-lying

educ

en: Education, culture and sport

en: Basal area of dead wood


maintainer: EnviDat Support

en: hazard-mapping snow satellite avalanche natural-hazard

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.

format: SHP

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


rorcc

maintainer: Tobias Wechsler

title_for_slug: rorcc

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

en: RoRCC

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

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

climate-change

display_name: climate-change

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants


en: roads buffer density jupyter gis geospatial

en: Road Density Calculation (Python Notebook) online

en: Road data from OSM for the surroundings of Menzberg, Switzerland

en: Plots

en: Random plot locations

en:
This dataset contains the road and plot data used for the geospatial analysis example showcased in "Fostering Open Science at WSL with the EnviDat Environmental Data Portal", a contribution to the 5th Open Source Geospatial Research and Education Symposium (OGRS), 2018.
The example uses Jupyter Notebook to calculate road densities in the neighbourhood of sample plot locations with Python. Road data were extracted from OpenStreetMap, while the point data (sample plots) were generated manually.

buffer

display_name: buffer

density

display_name: density

geospatial

display_name: geospatial

gis

display_name: gis

jupyter

display_name: jupyter

roads

display_name: roads

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: Dataset for OGRS 2018 publication


maintainer: Rebecca Mott

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

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

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

en: Gletschboden setup

media_type: image/png

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

format: PNG

mimetype: image/png

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

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

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

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

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

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

en: Output explanation

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

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

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

dischmex

display_name: dischmex

eddy-covariance-measurements

display_name: eddy-covariance-measurements

patchy-snow-covers

display_name: patchy-snow-covers

snow-patch

display_name: snow-patch

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

educ

en: Education, culture and sport

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


en: avalanche hazard-mapping impact-pressure modelling ramms release

en: Scenario 300 years with forest

en:
PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

en: Extent of the canton of Grisons

media_type: application/json

format: JSON

en: Scenario 100 years without forest

en: Scenario 300 years without forest

en: Scenario 30 years without forest

en: Scenario 10years with Forest

en: Scenario 100 years with forest

en: Scenario 30 years with forest

en: Scenario 10 years without forest

en:
We developed a workflow to generate Large Scale Hazard Simulations for avalanches based on digital elevation models and information on the protective function of the forest. This datasets contains the potential avalanche release areas (PRA) as polygons, the simulation outputs (maximum pressure, maximum flow velocity and maximum flow height) as .tif rasters and the outlines of the simulated avalanches (polygon) for the entire area of the canton of Grisons (7105 km2). The simulations are performed for the scenarios wit return periods of 10, 30, 100 and 300 years, once with (FOR) and once without (NoFor) taking the effect of the forest into account.

The details can be found in this publication:

Bühler, Y., Bebi, P., Christen, M., Margreth, S., Stoffel, L., Stoffel, A., Marty, C., Schmucki, G., Caviezel, A., Kühne, R., Wohlwend, S., and Bartelt, P.: Automated avalanche hazard indication mapping on state wide scale, Nat. Hazards Earth Syst. Sci. Discuss., 2022, 1-22, 10.5194/nhess-2022-11, 2022.

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

impact-pressure

display_name: impact-pressure

modelling

display_name: modelling

ramms

display_name: ramms

release

display_name: release

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: Large Scale Hazard Indication Simulations for avalanches, canton of Grisons


maintainer: Elisabeth Hafner

en: avalanche hazard-mapping natural-hazard snow satellite

en: SPOT6 Avalanche Outlines 16 January 2019

en: Shapefile of the manually mapped avalanche outlines. Please only use this data together with the example key document provided with this dataset and within the limitations of the dataset described in the publications.

en:
Outlines of 6'041 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 16 January 2019. The dataset was acquired following a period with very high avalanche danger. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping16012019.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.

The data was comprehensivly validated in a subset area in

Hafner, E.D.; Techel, F.; Leinss, S.; Bühler, Y., 2021: Mapping avalanches with satellites - evaluation of performance and completeness. Cryosphere, 15, 2: 983-1004. doi: 10.5194/tc-15-983-2021

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow

educ

en: Education, culture and sport

en: SPOT6 Avalanche outlines 16 January 2019


en: swiss-forest-lab deadwood coarse-woody-debris icp-forests long-term-forest-ecosystem-research

en: Data Request

en:
Assessment of coarse woody debris on LWF plots using full count methods on defined subplots (applying ForestBiota protocoll)

 Purpose:

Assessing the amount of coarse woody debris

 Manual Citation:

 * Franziska Heinrich, 2005: Totholz-Aufnahme mit ForestBIOTA Protokoll. Langfristige Waldökosystem-Forschung LWF. Eidg. Forschungsanstalt WSL, Birmensdorf, 7 S.

 * ForestBiota, 2005. Stand structure assessment including deadwood. EU/ICP Forests Biodiversity Test-Phase (ForestBIOTA). [>>>](http://www.forestbiota.org)

 * Fischer, R., Fischer, R., Seidling, W., Granke, O., Meyer, P., Stofer, S., Travaglini, D., 2007. ForestBIOTA – Testphase zur Erfassung der biologischen Vielfalt. AFZ/Wald 62, 1070.

 Paper Citation:

 * Seidling, W., Travaglini, D., Meyer, P., Waldner, P., Fischer, R., Granke, O., Chirici, G., Corona, P., 2014. Dead wood and stand structure - relationships for forest plots across Europe. IForest - Biogeosciences and Forestry 7, 269-281.

coarse-woody-debris

display_name: coarse-woody-debris

deadwood

display_name: deadwood

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

swiss-forest-lab

display_name: swiss-forest-lab

en: Deadwood survey LWF 2005 - subplot (Forets Biota)


en: rcm cryosphere software toposcale cordex downscaling

en:
Model code and documentation for the downscaling model TopoCLIM which provides methods to downscale climate timeseries from CORDEX RCM data. This scheme specifically addresses the need for hillslope scale atmospheric forcing timeseries for modeling the local impact of regional climate change projections on the land surface in complex terrain. The method has a global scope and is able to generate the full suite of model forcing variables required for hydrological and land surface modeling at hourly timesteps.

A working example is provided in this code archive but for full running of the scheme TopoSCALE is required https://doi.org/10.5194/gmd-7-387-2014 with code available at https://github.com/joelfiddes/tscaleV2. Standard library dependencies are given in the python requirements.txt of the archive with installation instructions in the README.md.

cordex

display_name: cordex

cryosphere

display_name: cryosphere

downscaling

display_name: downscaling

rcm

display_name: rcm

software

display_name: software

toposcale

display_name: toposcale

en: TopoCLIM v1.1 code


en: connectivity multifunctionality green-infrastructure planning-principles strategic-planning

en: Results of the coding on general aspects regarding the strategic plans of urban regions as well as extracts from each plan to justify the coding option – this data was derived from the coding procedure corresponding to items from 5 to 11 of the protocol. The data was discussed qualitatively in the research paper.

en:
The present dataset is part of the published scientific paper Grădinaru, S. R., & Hersperger, A. M. (2019). Green infrastructure in strategic spatial plans: Evidence from European urban regions. Urban forestry & urban greening, 40, 17-28.
The goal of this research was to conduct a comparative analysis of the integration of green infrastructure concept in strategic spatial plans of European Urban regions. Specifically, the paper has the following objectivs: 1) which principles of GI planning are followed in strategic plans of urban regions? 2) can we identify different approaches to GI integration into strategic planning?. The study focues on a sample consisting of 14 case studies spanning 11 countries. We retrieved the strategic plans from the websites of the planning authorities. The list of the reviewed planning documents can be found in Appendix A of the paper. A protocol was developed to perform the content analysis of the strategic plans and gather the data. The detailed list of protocol items can be found in Appendix B of the paper.
The planning documents were read in order to address the protocol items. The answer to the protocol items in each of the first two categories (items 1–11) was documented as text, while the answer for the third category, namely items addressing the planning principles (items 12–36), was coded according to Table 1 of the article. As a result, we provide the folowing outputs:
•	GI_Dataset_1_Items_1-12.xlsx – available on request
o	Results of the coding on general aspects regarding the strategic plans of urban regions as well as extracts from each plan to justify the coding option – this data was derived from the coding procedure coresponding to items from 1 to 12 of the protocol. The data was discussed qualitativly in the research paper.
•	GI_Dataset_2_Items_12-36.csv – freely available
o	Results of the coding on principles of GI planning followed in strategic plans of urban regions– this data was derived from the coding procedure coresponding to items from 12 to 36 of the protocol. The data served as input for the classifications performed through hierarchical cluster analysis. This data is a detailed version of Appendix C in the paper.

connectivity

display_name: connectivity

green-infrastructure

display_name: green-infrastructure

multifunctionality

display_name: multifunctionality

planning-principles

display_name: planning-principles

strategic-planning

display_name: strategic-planning


en: larch-budmoth nitrogen phenol spongy-moth flight-traps nun-moth gypsy-moth

en: Moth monitoring

en: See ReadMe

en: The population dynamics of eruptive moths were monitored with pheromone traps and the composition of the larvae's foodplants were analyzed for water content, nitrogen and total phenolics. Moth catches cover a period of 20 years, leaf analyses 10 years. For Zeiraphera griseana (= Z. diniana) only needle analyses are available. The corresponding data on the moth population dynamics are property of A. Fischlin, ETH Zürich, and will be made available on EnviDat as well.

flight-traps

display_name: flight-traps

gypsy-moth

display_name: gypsy-moth

larch-budmoth

display_name: larch-budmoth

nitrogen

display_name: nitrogen

nun-moth

display_name: nun-moth

phenol

display_name: phenol

spongy-moth

display_name: spongy-moth

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: Monitoring of Lymantria dispar, Lymantria monacha and Zeiraphera griseana and host food quality in the Swiss Alps


en: eddy-covariance-measurements snow-melt atmospheric-turbulence patchy-snow-cover surface-heat-exchange

en: Raw eddy covariance data from tower 2 at 1m height. Instrument is Campell Scientific IRGASON

en: Raw eddy covariance data from tower 2 at 3m height. Instrument is Campell Scientifc CSAT 3

en: IR-data that is visualized in the video

en: Raw eddy covariance data from the short-path ultrasonic ("Kaijo") at 0.3m above the snow

en: Raw eddy covariance data from tower 2 at 2m height. Instrument is Campell Scientifc CSAT 3

en: Data and code for the publication. The data is raw data. Processed data can be obtained upon request.

atmospheric-turbulence

display_name: atmospheric-turbulence

eddy-covariance-measurements

display_name: eddy-covariance-measurements

patchy-snow-cover

display_name: patchy-snow-cover

snow-melt

display_name: snow-melt

surface-heat-exchange

display_name: surface-heat-exchange

educ

en: Education, culture and sport

en: Turbulence in The Strongly Heterogeneous Near-Surface Boundary Layer over Patchy Snow


biomass-of-standing-dead-trees

title_for_slug: biomass-of-standing-dead-trees

en:
Dry weight (mass) of dead, standing trees and shrubs starting at 12 cm dbh. This consists of the tree parts: roots, stemwood and also, depending on the degree of decomposition, the branch coarse wood.

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

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

biogeographical-region

display_name: biogeographical-region

biomass-of-standing-dead-trees

display_name: biomass-of-standing-dead-trees

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

en: Biomass of standing dead trees


en: Request Data

media_type: text/csv

en: This dataset is hosted by IAP and therefore, access to the dataset must be requested to the original data provider.

format: CSV

en: Additional publications

media_type: text/html

format: HTML

en:
The IAP has been monitoring forest health since 1984 on behalf of cantonal forest and environmental offices and in collaboration with the Federal Office for the Environment. In the Intercantonal Forest Observation Program (WDB) project, the health, growth and nutrient supply of beech, spruce and oak in managed forest ecosystems are studied on about 190 forest plots. The plots cover the most important gradients of Swiss forests, such as different climatic conditions in precipitation, temperature, as well as differences in soil and in the input of air pollutants such as nitrogen and ozone. Currently (date 2020) 94 plots with 6268 beech trees, 75 plots with 4547 spruce trees, and 50 plots with 1858 oak trees are surveyed in the Intercantonal WDB. Annual investigations include crown condition and tree loss by mortality, uprooting and stem breakage. Every 4 year stem increment is measured on all 12’673 trees and 8 branches are harvested by helicopter very 4 years and subsequently examined for the following parameters:

- Nutrient analysis in foliage (N, P, K, Ca, Mg, Mn)
- Leaf area and weight
- Shoot growth (retrospective for Norway spruce, beech and oak)
- Discoloration and parasite infestation
- Fructification of beech (retrospectively)

In addition, soil samples for analysing the chemistry of the solid phase are taken every 12 years. Also changes in the ground vegetation is assessed every 12 years. On a subset of the plots soil solution is sampled monthly *[(Soil solution monitoring of the Intercantonal Forest Observation Program)](https://www.envidat.ch/dataset/soil-solution-monitoring-of-the-intercantonal-forest-observation-program)*. In addition, soil water potential and soil moisture are measured in a subset of sites of the Intercantonal Forest Observation Program *[(Soil moisture and soil water potential measurements of the Intercantonal Forest Observation Program)](https://www.envidat.ch/dataset/soil-water-measurements-wdb)*.

These data allow to gain a unique understanding of the main factors influencing the forest and the most important changes, which are very valuable especially in the context of climate change. The insights are of great importance for cantonal and regional forest planning as well as for national and international determinations of critical loads and limits (e.g. CLempN, UNECE CLRTAP).

iap

display_name: iap

long-term-data-sets

display_name: long-term-data-sets

long-term-monitoring

display_name: long-term-monitoring

swiss-forest-lab

display_name: swiss-forest-lab

wdb

display_name: wdb

en: Intercantonal Forest Observation Program – Interkantonale Walddauerbeobachtung (WDB)


en: forcing transport freshwater-flux freezing salinity cryospheric-science sea-ice satellite antartic melting sea-ice-divergence polar southern-ocean physical-oceanography salt sea-ice-volume mass-balance climate-change

en: Data in NetCDF4 CF-1.6 format

en: Link to Related Publication

en: Explanatory Document

en:
This data set provides estimates of annual fresh water fluxes related to sea-ice formation from ocean freezing and snow-ice formation, sea-ice melting, lateral transport of sea ice in the Southern Ocean over the period 1982 to 2008.It is derived from a mass balance calculation of local sea-ice volume change and divergence from satellite data and sea-ice reconstructions. The mass balance is calculated on a daily basis and fluxes are then integrated over the entire year, where a year is defined from March to February of the next year (i.e. from March 1982 to February 2009). This approach combines multiple products of sea-ice concentration (Cavalieri & Parkinson, 2008;Comiso, 1986; Meier et al., 2013), sea-ice thickness (Kurtz & Markus, 2012; Massonnet et al., 2013; Worby et al., 2008), and sea-ice drift (Fowler et al., 2013; Kwok 2005; Schwegmann et al., 2011). For a detailed description of the method see Haumann et al. (2016). The data set is derived to estimate large-scale (regional to basin-scale) fluxes on an annual basis. Our confidence is reduced on a grid cell basis, such as for single coastal polynyas, where the method and underlying data induce large, unknown uncertainties.

_Disclaimer: This data set is free to use for any non-commercial purpose at the risk of the user and the authors do not take any liability on the use of the data set. The authors assembled the data set carefully and assessed accuracy, errors, and uncertainties. Please contact the authors if you find any issues._

Related publication: http://www.nature.com/nature/journal/v537/n7618/full/nature19101.html (doi:10.1038/nature19101)

Disclaimer: This data set is free to use for any non-commercial purpose at the risk of the user and the authors do not take any liability on the use of the data set. The authors assembled the data set carefully and assessed accuracy, errors, and uncertainties. Please contact the authors if you find any issues.

antartic

display_name: antartic

climate-change

display_name: climate-change

cryospheric-science

display_name: cryospheric-science

forcing

display_name: forcing

freezing

display_name: freezing

freshwater-flux

display_name: freshwater-flux

mass-balance

display_name: mass-balance

melting

display_name: melting

physical-oceanography

display_name: physical-oceanography

polar

display_name: polar

salinity

display_name: salinity

salt

display_name: salt

satellite

display_name: satellite

sea-ice

display_name: sea-ice

sea-ice-divergence

display_name: sea-ice-divergence

sea-ice-volume

display_name: sea-ice-volume

southern-ocean

display_name: southern-ocean

transport

display_name: transport

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: Antarctic sea-ice freshwater fluxes associated with freezing, transport, and melting


en: uas snow-depth snow swe remote-sensing

en: HS map Brämabül, 14. April 2015

media_type: image/tiff

en:
10 cm resolution
15 cm accuracy

format: TIFF

mimetype: image/tiff

en: .tfw file

en: coordinates for the .tif raster

en:
This snow depth map was generated 14 January 2015, close to peak of winter accumulation, applying Unmanned Aerial System digital surface models with a spatial resolution of 10 cm. The covered area is 285'000 m2 at the top of Brämabüel, 2490 m a.s.l. covering all expositions. Coordinate system: CH1903LV03.

A detailed description is given here:

Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075-1088, 10.5194/tc-10-1075-2016, 2016.

Abstract:
Detailed information on the spatial and temporal distribution, and variability of snow depth (HS) is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Nowadays, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network is not able to capture the large spatial variability of snow depth in alpine terrain.
Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, such data acquisition is costly, if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand, is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UAS), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Such systems have the advantage that they are comparatively cost-effective and can be applied very flexibly to cover also otherwise inaccessible terrain. In this study we map snow depth at two different locations: a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and b) an exposed location (2500 m a.s.l.) on a peak in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) better than 0.07 to 0.15 m on meadows and rocks and a RMSE better than 0.30 m on sections covered by bushes or tall grass. This new measurement technology opens the door for efficient, flexible, repeatable and cost effective snow depth monitoring for various applications, investigating the worlds cryosphere.

remote-sensing

display_name: remote-sensing

snow

display_name: snow

snow-depth

display_name: snow-depth

swe

display_name: swe

uas

display_name: uas

educ

en: Education, culture and sport

en: UAS based snow depth maps Brämabüel, Davos, CH


causal-effect-of-mfoz

title_for_slug: causal-effect-of-mfoz

en: built-up-land-change causality the-major-function-oriented-zone fujian-province propensity-score-matching selection-bias

en: Data and Stata code for repeating the results

en:
Data.xlsx is the variables of 952 townships
Table 1-2 NN(1-1)_noreplace_caliper(0.01).do is STATA code to produce the results in Table 1 and 2
Figure 5 Distribution of the propensity scores.R is R code rto produce Figure 5
Figure 5 Standard mean difference.R is R code rto produce Figure 5

en:
Title: Closer to causality: How effective is spatial planning in governing built-up land expansion in Fujian Province, China?

Research objective: The Major Function Oriented Zone (MFOZ), the first strategic spatial plan in China, is developed to achieve a coordinated regional development, through spatial regulation and zoning of development. The MFOZ he MFOZ divided land into four major function-oriented zones: The development-optimized zone, the development-prioritised zone, the development-restricted zone, and the development-prohibited zone. We used propensity score marching to evaluate the effect of the MFOZ on built-up land expansion in Fujian Province over three time intervals (2013–2015, 2013–2018 and 2013–2020).

Data: Data.xlsx contains the variables of 954 towns in Fujian Province.
Town_ID is the town unique ID;
County_ID is the county unique ID;
City_ID is the city unique ID;
MFOZ is the the development-prioritised zone and the development-restricted zone (The development-optimized zone and the development-prohibited zone are excluded);
Builtup_13_15 is the built-up land expansion from 2013 to 2015;
Builtup_13_18 is the built-up land expansion from 2013 to 2018;
Builtup_13_20 is the built-up land expansion from 2013 to 2020;
Dis2water is the Euclidean distance from the town to the nearest waterbody;
Slope is the the average slope within the town;
GDP is the average GDP in 2010 within the town;
Pop is the average population in 2010 within the town;
Road is the average population in 2010 within the town;
Dis2city is the Euclidean distance from the town to the nearest prefectural city centre;
Nei_Arable, Nei_Forest, and Nei_Built.up are the area of arable land, forest land, and built-up land neighbouring town i in 2010.

Method: we used the propensity score matching to compare the changes in the amount of built-up land in the towns of the development-prioritised zone with the matched towns of the development-restricted zone. Additionally, we used three evaluation intervals (2013–2015, 2013–2018 and 2013–2020) to evaluate temporal variation in the causal effect of the MFOZ on built-up land expansion.

built-up-land-change

display_name: built-up-land-change

causality

display_name: causality

fujian-province

display_name: fujian-province

propensity-score-matching

display_name: propensity-score-matching

selection-bias

display_name: selection-bias

the-major-function-oriented-zone

display_name: the-major-function-oriented-zone

en: Causal effect of MFOZ


aerosol-data-davos-wolfgang

title_for_slug: aerosol-data-davos-wolfgang

en: aerosol drincz raclets inp particles ice-nucleation

en: APS Dataset Davos Wolfgang

en: The APS file contains aerosol data (total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) for aerodynamic diameters between 0.5 μm and ~20 μm as well as instrument characteristics, in a temporal resolution of 20 seconds, with time in UTC, measured at Davos Wolfgang.

mimetype: application/x-netcdf

en: OPC GT-526S Dataset Davos Wolfgang

en: Particle counts were recorded in six size channels (0.3, 0.5, 0.8, 1.5, 2.5 and 5 μm) in a resolution of 20 seconds (time in UTC) by a particle counter (GT-526S, Met One Instruments, Inc.).

mimetype: text/csv

en: SMPS Dataset Davos Wolfgang

en: The SMPS file contains aerosol data (particle concentration, total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) in a size range between 12 and 460 nm (electrical mobility diameter) as well as instrument characteristics (sample temperature, pressure, relative humidity, mean free path and gas viscosity), in a temporal resolution of 2 minutes, with time in UTC, measured at Davos Wolfgang.

en: OPC-N3 Dataset Davos Wolfgang

en: Particle concentrations in a size range of 0.35 μm to 40 μm were measured with an OPC-N3 (Alphasense, Inc.) in a resolution of 20 seconds (time in UTC). PM₁, PM₂,₅ and PM₁₀ were directly derived.

en: DRINCZ Dataset Davos Wolfgang

en: The DRINCZ file contains information on temperature (in °C) dependent frozen fractions, number of Ice Nuleating Particles (INP, per standard liter) and differential INP concentrations (per standard liter and Kelvin).

en:
Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.

Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0).

Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³).

Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³).

Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

aerosol

display_name: aerosol

drincz

display_name: drincz

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

particles

display_name: particles

raclets

display_name: raclets

en: Aerosol Data Davos Wolfgang


maintainer: Yves Bühler

en: hazard-mapping avalanche snow ramms release hazard-indication-mapping

en: RAMMS simulations NHESS

en: Simulated maximum pressures for the scenarios frequent and extreme taking the forest layer into account

en: Potential Release  Area  NHESS

en: This folder contains the output of the different investigated algorithms plus the reference dataset, used for training and validation.

en:
This dataset contains the output and reference data published in the paper "Automated snow avalanche release area delineation - validation of existing algorithms and proposition of a new object-based approach for large scale hazard indication mapping" Yves Bühler, Daniel von Rickenbach, Andreas Stoffel, Stefan Margreth, Lukas Stoffel, Marc Christen (2018) Natural Hazards And Earth System Sciences.

Abstract:
Snow avalanche hazard is threatening people and infrastructure in all alpine regions with seasonal or permanent snow cover around the globe. Coping with this hazard is a big challenge and during the past centuries, different strategies were developed. Today, in Switzerland, experienced avalanche engineers produce hazard maps with a very high reliability based on avalanche cadastre information, terrain analysis, climatological datasets and numerical modelling of the flow dynamics for selected avalanche tracks that might affect settlements. However, for regions outside the considered settlement areas such area-wide hazard maps are not available mainly because of the too high cost, in Switzerland and in most mountain regions around the world. Therefore, hazard indication maps, even though they are less reliable and less detailed, are often the only spatial planning tool available. To produce meaningful and cost-effective avalanche hazard indication maps over large regions (regional to national scale), automated release area delineation has to be combined with volume estimations and state-of-the-art numerical avalanche simulations.

In this paper we validate existing potential release area (PRA) delineation algorithms, published in peer-reviewed journals, that are based on digital terrain models and their derivatives such as slope angle, aspect, roughness and curvature. For validation, we apply avalanche cadastre data from three different ski resorts in the vicinity of Davos, Switzerland, where experienced ski-patrol staff mapped most avalanches in detail since many years. After calculating the best fit input parameters for every tested algorithm, we compare their performance based on the reference datasets. Because all tested algorithms do not provide meaningful delineation between individual potential release areas (PRA), we propose a new algorithm based on object-based image analysis (OBIA). In combination with an automatic procedure to estimate the average release depth (d0), defining the avalanche release volume, this algorithm enables the numerical simulation of thousands of avalanches over large regions applying the well-established avalanche dynamics model RAMMS. We demonstrate this for the region of Davos for two hazard scenarios, frequent (10 – 30 years return period) and extreme (100 – 300 years return period). This approach opens the door for large scale avalanche hazard indication mapping in all regions where high quality and resolution digital terrain models and snow data are available.

avalanche

display_name: avalanche

hazard-indication-mapping

display_name: hazard-indication-mapping

hazard-mapping

display_name: hazard-mapping

ramms

display_name: ramms

release

display_name: release

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Automated Avalanche Release Area (PRA) Delineation Davos


maintainer: Esther Frei

en: treeline-ecosystems literature-review long-term-experiment stillberg mountain-ecology

en: The Stillberg bibliography (Stillberg_bibliography_v1.zip) comprises a comprehensive list of 276 scientific publications, 91 of them published in peer-reviewed ISI journals (Stillberg_bibliography_data_v1.csv) along with the metadata file (Stillberg_bibliography_metadata_v1.csv). Currently the bibliography comprises literature about the main afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, and the G-TREE experiment, as well as further publications related to the Stillberg research site that have been published until August 2023. The bibliography can be filtered for different categories, e.g., experiment, peer-review, source repository or database, and source title.

en:
 Background information

The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Over almost fifty years, research at the Stillberg site combined long-term monitoring of the large-scale high-elevation afforestation with experimental manipulations simulating global change impacts. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone across different compartments and scales, from individual trees, non-tree vegetation and soils to whole ecosystems, in the context of global change resulting in more than 150 publications.

 Dataset generation

We compiled a comprehensive list of scientific publications covering research at the Stillberg research site by conducting searches in the literature databases Web of Science and Google Scholar, as well as in the Digital Object Repository of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL (DORA). We compiled all publications about the afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, the G-TREE experiment, as well as other studies related to the Stillberg research site.

 Data description

The Stillberg bibliography (Stillberg_bibliography_data_v1.csv) comprises a comprehensive list of 276 scientific publications, 91 of them published in peer-reviewed ISI journals. Currently the bibliography comprises literature about the main afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, and the G-TREE experiment, as well as further publications related to the Stillberg research site that have been published until August 2023. The bibliography can be filtered for different categories, e.g., experiment, peer-review, source repository or database, and source title. The bibliography is described in a metadata file (Stillberg_bibliography_metadata_v1.csv). The bibliography along with the metadata file are provided in a ZIP-folder (Stillberg_bibliography_v1.zip).

literature-review

display_name: literature-review

long-term-experiment

display_name: long-term-experiment

mountain-ecology

display_name: mountain-ecology

stillberg

display_name: stillberg

treeline-ecosystems

display_name: treeline-ecosystems

en: Bibliography of the long-term treeline research site Stillberg, Switzerland


radar-wind-profiler-davos-wolfgang

maintainer: Maxim Hervo

title_for_slug: radar-wind-profiler-davos-wolfgang

en: raclets wind-direction radar wolfgangpass wind-speed

en: Radar Wind Profiler Data

en: A Vaisala Lap3000 was installed at Davos Wolfgang to record wind profiles. The time format is number of days fom January 0, 0000 in UTC with a 10 minute resolution.

en: The RADAR wind profiler from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 2171 m above sea level to 11079 m, with a temporal resolution of 10 minutes.

radar

display_name: radar

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

wolfgangpass

display_name: wolfgangpass

en: RADAR Wind profiler Davos Wolfgang


en: lfi switzerland woody-species sdm mogli

en: Map Access

en: Maps are available as georeferenced rasters on request via login or directly via [Andri Baltensweiler](https://www.wsl.ch/en/employees/baltensw.html).

en: MoGLI Summary

en: A summary of methods and results on the potential distribution maps of woody species in Swiss forests.

en: Tabelle S2

en:
Tabelle S2 zum Artikel: Wüest Karpati et al. (2021) Modellierte Verbreitungskarten der häufigsten Gehölzarten der Schweiz, _Schweizerische Zeitschrift für Forstwesen_ 172:4

Übersicht zu den verwendeten Umweltprädiktoren für diejenigen Arten, welche das Qualitätskriterium zur Publikation nicht erreichten (TSS < 0.5)

en: Tabelle S1

en:
Tabelle S1 zum Artikel: Wüest Karpati et al. (2021) Modellierte Verbreitungskarten der häufigsten Gehölzarten der Schweiz, _Schweizerische Zeitschrift für Forstwesen_ 172:4

Übersicht zu den verwendeten Umweltprädiktoren für alle Arten mit erfülltem Qualitätskriterium (TSS > 0.5).

en: Tabelle S3

en:
Tabelle S3 zum Artikel: Wüest Karpati et al. (2021) Modellierte Verbreitungskarten der häufigsten Gehölzarten der Schweiz, _Schweizerische Zeitschrift für Forstwesen_ 172:4

Liste der verwendeten Umweltprädiktoren für jede der Arten mit erfülltem Qualitätskriterium (TSS > 0.5).

en:
**We used Swiss National Forest Inventory ([NFI](https://www.lfi.ch/index-en.php)) data to model the potential distribution of the most common woody species for the forested area of Switzerland and provide potential distribution maps that fulfill specific quality criteria with regard to predicting performance.**

More details on the methods and results are described in the project summary available [here](https://www.envidat.ch/dataset/07a9c22c-9ec2-4f49-87e2-3b2d73ad81f2/resource/9bfd5308-d9be-4d01-ab78-48d33889e04e/download/mogli_summary.pdf).

**The resulting maps can be viewed in a simple web-GIS application available at:**
[https://www.lfi.ch/produkte/mogli/mogli-en.php](https://www.lfi.ch/produkte/mogli/mogli-en.php)

**Data can be used without restrictions, but the data must be explicitly asked from the contact person of the dataset in order to obtain access.**
This is a requirement to fulfill the needs of reporting towards the funding agencies.

lfi

display_name: lfi

mogli

display_name: mogli

sdm

display_name: sdm

switzerland

display_name: switzerland

woody-species

display_name: woody-species

en: Distribution maps of common woody species for Swiss forests


disdrometer-data-gotschnagrat

title_for_slug: disdrometer-data-gotschnagrat

en: raclets hydrometeors visibility disdrometer precipitation

en: Disdrometer Data Gotschnagrat

en: The zip folder contains one netCDF file per day for Gotschnagrat from February 11 to March 27 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Gotschna_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

en: A laser optical disdrometer (Parsivel² , OTT Hydromet) was deployed at Gotschnagrat (LON: 9.849, LAT: 46.859) to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms. The dataset contains information on precipitation amount and type for the period of February 11 to March 27 2019 at Gotschnagrat.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


en: root-water-uptake plant-available-water-storage-capacity water-balance european-summer-drought physiological-drought

en: available water storage capacity (AWC)

en: Root distribution and root water uptake

en: Root density distribution derived from 44 soil profiles and simulated daily root water uptake (mm) aggregated for deciduous and coniferous trees across Switzerland.

en: measured soil matric potential

en: In daily resolution for a site near Neunkirch and Hohtenn from 2014 to 2018.

en: Soil matric potential (kPa)

en: Mean simulated values for August 2018 with 500m spatial resolution.

en: Soil water pools with soil depth

en: Average plant available - (AWC), gravitational (GWC) and residual (RES) water capacity per soil depth layer of the Swiss forest.

en: monthly covariance measurements

en: Data from Davos and Lägeren from 2013-2019

en: Posterior LWF-Brook90 model parameters

en: Sensitive above and belowground parameters of LWF-Brook90 model are provided for best runs of the calibration against soil matric potential data.

en: Gravitational water capacity (mm)

en: Calculated for 1m soil depth and the potential rooting depth at 500m spatial resolution.

en: water balance fluxes

en: Average yearly simulated water fluxes (mm) for the Swiss forest at 500m spatial resolution.

en: Uncertainties of the available water storage capacity (mm)

en: Calculated for 1m soil depth and the potential rooting depth (mrd).

en: Ratio of actual to potential transpiration

en: Simulated monthly values at 500m spatial resolution.

en:
The Swiss forests' water availability during the 2015 and 2018 droughts was modelled by implementing the mechanistic Soil-Vegetation-Atmosphere-Transport (SVAT) model LWF-Brook90 taking advantage of regionalized depth-resolved soil information and measured soil matric potential and eddy covariance data. Data include
1) csv of soil matrix potential and eddy covariance data, 2) csv of posterior model parameters, 3) geotiffs of plant-available water storage capacity until 1m soil depth and the potential rooting depth, 4) geotiffs of yearly average (2014-2019) of precipitation (P), actual evapotranspiration (ETa), evaporation as the sum of soil, snow and interception evaporation (E), actual transpiration (Ta), runoff (F) and total soil water storage (SWAT), 5) csv of simulated root water uptake aggregated for different soil depths per deciduous and coniferous trees across Switzerland at daily resolution and cumulative root fraction per soil depth for coniferous and deciduous sites, 6) geotiffs of the ratio of actual to potential transpiration (-) as mean of non-drought years 2014, 2016, 2017, 2019 and 2015 and 2018 for the month June, July, August, September and October, 7) geotiff of mean soil matric potential in the rooting zone in August 2018, 8) geotiffs of gravitational water capacity (mm) until 1 m soil depth and the maximum rooting depth (mrd), 9) geotiffs of uncertainties of the available water storage capacity (AWC) until 1m soil depth and the mean maximum rooting depth (mrd), 10) csv of average plant available - (AWC), gravitational (GWC) and residual (RES) water capacity per soil depth layer of the Swiss forest.

european-summer-drought

display_name: european-summer-drought

physiological-drought

display_name: physiological-drought

plant-available-water-storage-capacity

display_name: plant-available-water-storage-capacity

root-water-uptake

display_name: root-water-uptake

water-balance

display_name: water-balance

en: Water availability of Swiss forests during the 2015 and 2018 droughts


length-of-forest-roads

title_for_slug: length-of-forest-roads

en:
The length of forest roads corresponds to the length of the NFI forest roads. This length was calculated according to the method of the specific NFI concerned.

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

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

economic-region

display_name: economic-region

length-of-forest-roads

display_name: length-of-forest-roads

lower-higher-altitudinal-zones

display_name: lower-higher-altitudinal-zones

ownership

display_name: ownership

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Length of forest roads


maintainer: Chunhong Zhao

en: urban-morphology austin landscape land-dynamics land-use

en: Land use dynamics in Austin since 1992

en: The present dataset is part of the published scientific paper Zhao C, Weng Q, Hersperger A M. Characterizing the 3-D urban morphology transformation to understand urban-form dynamics: a case study of Austin, Texas, USA. Landscape and urban planning, 2020, 203:103881. The overall objective of this paper is to understand urban form dynamics in the Austin metropolitan area for the periods 2006–2011 and 2011–2016. The study also aims to understand to what extent the changes in the built environment (in terms of ‘efficient growth’ versus ‘inefficient growth’) from the 1990s to 2016 in the Austin metropolitan area corresponded with ‘compact and efficient growth’ planning policy documents. The UMT distribution can be found in the paper. The area of transitioning UMT was provided in Table 2 and Table 3 can be found in the Appendix of the paper. A protocol was developed to perform the content analysis of the strategic plans and gather the data. The detailed list of protocol items can be found in Appendix B of the paper. This study demonstrates the advantage of applying Lidar data to characterize 3-D urban morphology type (UMT) transition and understand its dynamics, which helps develop a comprehensive understanding of the urbanization process and provides a tool for planning intentions and policies evaluation on urban development over time. The UMT maps can be found in Appendix A of the paper. The Lidar point datasets and the 30 × 30 m National Land Cover Database (NLCD) are the two main data sources of UMT mapping. Lidar datasets were gathered from different projects that had been conducted and collected by state agencies and other organizations between 2007 and 2017. Table A1 in the appendix in the paper shows the accuracies and acquisition parameters of the Lidar projects from 2007 to 2017. Land use/cover dynamics in Austin metropolitan area dataset provides Land use/cover patterns in the years 1992, 2001, 2004, 2006, 2008, 2011, 2013, 2016 with a spatial resolution of 30 meters. Since NLCD 1992 used a different classification system for the urban land classes, we first reclassified the NLCD 1992 using a customized Arcpy package.

austin

display_name: austin

land-dynamics

display_name: land-dynamics

land-use

display_name: land-use

landscape

display_name: landscape

urban-morphology

display_name: urban-morphology

en: Land use/cover dynamics in Austin metropolitan area since 1992


en: plan-evaluation governance landscape-principles green-infrastructure strategic-plan

en: Coding results

en: o	Results of the coding procedure. Data were used to create Figures 2, 3, 4, 5, 6 and to qualitatively present the results in the research paper.

en: o	Detailed description of all the protocol items used to conduct the analysis and the way each question was coded

en:
The present dataset is part of the published scientific paper Hersperger, A.M., Bürgi, M., Wende, W., Bacău, S. and Grădinaru, S.R., 2020. Does landscape play a role in strategic spatial planning of European urban regions?. Landscape and Urban Planning, 194, p.103702.

The goal of this research was to assess the role of landscape in contemporary strategic spatial planning. In order to assess the role of “landscape” in the strategic spatial plans, we focused on how plans took advantage of landscape’s integrative power, how plans are based on knowledge on functioning of landscape systems, and how plans show the contribution of landscapes to human well-being. For each aspect, a number of items (detailed in Table 1 of the paper) were selected to assist the assessment.
This study is based on content analysis of the strategic spatial plans of 18 European urban regions. The strategic spatial plans were retrieved from the planning authorities’ websites. The cases study regions as well as the analyzed strategic spatial plans are presented in Table 2 of the paper.
The authors developed a protocol containing 28 items, out of which 16 were directly derived from information presented in Table 1. As a result, we provide the following outputs:
•	Protocol_items.docx – freely available - Detailed description of all the protocol items used to conduct the analysis.
•	Coding results.xlsx – available on request - Results of the coding procedure. Data were used to create Figures 2, 3, 4, 5, 6 and to qualitatively present the results in the research paper.

governance

display_name: governance

green-infrastructure

display_name: green-infrastructure

landscape-principles

display_name: landscape-principles

plan-evaluation

display_name: plan-evaluation

strategic-plan

display_name: strategic-plan

en: Landscape in contemporary strategic spatial plans of European Urban regions


en: forest-structure snow-energy-balance forest-snow snow-models meteorological-data

en: Site overview

en: Overview of field sites

en: AWS data

en: Model driving data from operational AWS

en: Transect data

en: All meteorological and canopy structure data acquired at cable car transects

en: Point data

en: Wind speed data acquired with the portable meteorological stations

en: Grid data

en: Canopy structure and snow depth data at the grids

en:
This dataset contains datasets of sub-canopy meteorological variables acquired in coniferous forest stands in Switzerland (Davos, Engadine) and Finland (Sodankylä) during the winters 2018 and 2019. The data are presented and used in the publication:
Mazzotti, G., Essery, R., Webster, C., Malle, J., & Jonas T. (2020)
Process-level evaluation of a high-resolution forest snow model using observations from mobile multi-sensor platforms
Water Resources Research, under review

The above publication must be cited when using this dataset, and the user is referred to the publication for additional detail.

Data are grouped into 4 folders:
1) Point data includes wind speed data measured with stationary meteorological stations
2) Transect data includes data of incoming short- and longwave radiation, air and snow surface temperature acquired with an automated calblecar system along within-stand transects
3) Grid data includes data of incoming short- and longwave radiation, air and snow surface temperature acquired on 40x40m gridded plots using a handheld instrument, as well as snow depth data measured at the same grids.

Canopy structure information derived from hemispherical images is included for each all surveyed locations as well, and an overview of the field sites is provided.

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

meteorological-data

display_name: meteorological-data

snow-energy-balance

display_name: snow-energy-balance

snow-models

display_name: snow-models

en: Distributed sub-canopy datasets from mobile multi-sensor platforms (CH / FIN, 2018-2019) for hyper-resolution forest snow model evaluation


en: numerical-avalanche-forecasting avalanche avalanche-danger-level avalanche-forcasting machine-learning

en: This data set includes the meteorological variables (resampled 24-hour averages) and the profile variables extracted from the simulated profiles for each of the weather stations of the IMIS network in Switzerland, and, the danger ratings for dry-snow conditions assigned in the Swiss avalanche bulletin to the location of the weather station.

en: This subset of data includes the meteorological variables (resampled 24-hour averages) and the profile variables extracted from the simulated profiles for each of the weather stations of the IMIS network in Switzerland, and, the quality-controlled danger ratings for dry-snow avalanche conditions forecast in Switzerland.

en: README

en: This read-me file contains the descriptions of the variables

en:
Each set includes the meteorological variables (resampled 24-hour averages) and the profile variables extracted from the simulated profiles for each of the weather stations of the IMIS network in Switzerland, and, the danger ratings for dry-snow conditions assigned to the location of the station. The data set of RF 1 contains the danger ratings published in the official Swiss avalanche bulletin, and the data set of RF 2 is a quality-controlled subset of danger ratings.
These data are the basis of the following publication: Pérez-Guillén, C., Techel, F., Hendrick, M., Volpi, M., van Herwijnen, A., Olevski, T., Obozinski, G., Pérez-Cruz, F., and Schweizer, J.: Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland, Nat. Hazards Earth Syst. Sci., 22, 2031–2056, https://doi.org/10.5194/nhess-22-2031-2022, 2022.

avalanche

display_name: avalanche

avalanche-danger-level

display_name: avalanche-danger-level

avalanche-forcasting

display_name: avalanche-forcasting

machine-learning

display_name: machine-learning

numerical-avalanche-forecasting

display_name: numerical-avalanche-forecasting

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Weather, snowpack and danger ratings data for automated avalanche danger level predictions


en: forest-reserves long-term-monitoring permanent-plot switzerland natural-forest-dynamics

en: Metdata Description

en: This document gives an overview on the forest reserves monitoring network and describes the metadata contained in the file metadata.csv

en: Metadata

en: Metadata Forest Reserves Monitoring

en: Data Access (please log in)

en:
Long term monitoring of natural forests provides insights into ecological processes shaping forests without human intervention. To study natural forest dynamics, the former chair of silviculture at the Swiss Federal Institute of Technology (ETH) initiated a network of forest reserves in the late 1940's.
Since 2006, the monitoring is carried out in a cooperation project of the chair of Forest Ecology at ETH, the Swiss Federal Research Institute for Forest, Snow and Landscape Research (WSL) and the Federal Office for the Environment (FOEN). The project relaunch led to a streamlining of the reserve network, which now contains 33 of the original reserves and 16 new reserves.
The main goal is to evaluate the effectiveness of the federal reserve policy by analysing to what extent forest reserves differ from managed forests in terms of structure, dynamics, and habitat quality.

forest-reserves

display_name: forest-reserves

long-term-monitoring

display_name: long-term-monitoring

natural-forest-dynamics

display_name: natural-forest-dynamics

permanent-plot

display_name: permanent-plot

switzerland

display_name: switzerland

en: Forest Reserves Monitoring in Switzerland


en: water-table landslides soil-moisture-water-content hydrology meadow

en: Data Groundwater level in Soil.xlsx

en: Data Groundwater level in Bedrock.xlsx

en: We drilled six boreholes in two clusters. The boreholes reached a depth between 2 and 9 m below the ground surface. The lower half of boreholes BH1 and BH6 were cored with a 9 cm-diameter rotational diamond drilling head. The other boreholes were drilled destructively with an 11 cm-diameter Mitsubishi hammer system. Boreholes BH1, BH2 and BH5 were equipped with open standpipe piezometers, whereas BH3, BH4 and BH6 were equipped with a special piezometer system composed of an enclosed measuring cell at the bottom of a 1 inch-PVC tube. The free groundwater level in the PVC tube is measured in the standpipe piezometer, but it doesn’t necessarily represent the water table in the soil layer because the pressure sensor is located in the sealed lower part of the piezometer in the enclosed measuring cell and thus is not in contact with the air. This system allows the hydraulic pressure of lithologies with low permeability to be measured directly. Two piezometers were installed in BH6 at different depths. The PVC tubes were slotted at the bottom for 0.5, 1 or 2 meters and the boreholes were sealed carefully with clay pellets above this filter section to avoid by-pass and infiltration from the surface. DCX-22 pressure sensors from Keller AG Winterthur, with integrated data loggers, were installed in each piezometer to measure the relative hydraulic pressure at a 30 minute-intervals from November 2010 to November 2011. The data were corrected for in-situ air-pressure fluctuations.

en: Data Soil water content TDR.xlsm

en: Four test pits were excavated in summer 2010 along the slope to install vertical profiles of Time Domain Reflectometry sensors [Topp et al., 1980] to measure soil water content at depths of 0.25 m, 0.7 m, 1.1 m and 1.5 m. The 15 cm long TDR rods were inserted horizontally into the vertical walls of the pits, and the four pits were carefully refilled with the excavated soil. The water content was recorded from summer 2010 to fall 2011 at 10-minute time intervals using a Campbell TDR 100 system.

en: Data Lateral subsurface water flow.xlsm

en:
Rufiberg is a pre-alpine meadow site in Switzerland where shallow landslides have been observed after past intense rain storms. In order to assess the triggering mechanisms of these landslides, a comprehensive investigation was conducted within the project TRAMM from Nov 2009 to Oct 2012. It included meteorological observations, soil moisture measurements, bedrock groundwater measurements. The Rufiberg is located at the NW side of the Gnipen to the north of the village Arth-Goldau in the Canton of Schwyz. In the summer months, the site is used for pasturing. Usually, from December to March a snow cover is present at the Rufiberg. The site is at an altitude between 1080 – 1180 m asl, is ENE oriented, and has an average slope of 30 -35°. The Subalpine Molasse in the region is inclined with 30 - 35° to SE. In the area of the field site, beds of conglomerate with several m of thickness alter with beds of sandstone and marlstone. A ca. 2 – 5 m thick eluvium/colluvium layer composed of silty and sandy clay covers the bedrock. This site has been chosen because on one hand, during heavy rainfall events, e.g. autumn 2005, numerous landslides occur in the region of the Gnipen and the Rufiberg. On the other hand, the Rufiberg is very appropriate for experiments due its location away from infrastructures and due to its accessibility. The goal of the investigation was to understand the hydrology and hydrogeology of the slope with regard to shallow landslides.

More information: Brönnimann, C., Stähli, M., Schneider, P., Seward, L. and Springman, S.M. 2013. Bedrock exfiltration as a triggering mechanism for shallow landslides. Water Resources Research, 49 (9): 5155–5167. DOI: 10.1002/wrcr.20386.

hydrology

display_name: hydrology

landslides

display_name: landslides

meadow

display_name: meadow

soil-moisture-water-content

display_name: soil-moisture-water-content

water-table

display_name: water-table

en: TRAMM project - experimental hydrological and hydrogeological dataset of a landslide prone hillslope. Rufiberg, Switzerland


digitizing-historical-plague

maintainer: Christian Ginzler

title_for_slug: digitizing-historical-plague

en: bubonic-plague plague-inventory yersinia-pestis historical-plague plague-outbreaks plague-mapping black-death palaeo-epidemiology

en: We present newly digitized data on 6,929 plague outbreaks that occurred between 1347 and 1900 AD across Europe. The data base on an inventory initially published 1976. For georeferencing the information of Tele Atlas 2009 was used. The coordinates are in the reference systems ETRS89 and WGS84.

black-death

display_name: black-death

bubonic-plague

display_name: bubonic-plague

historical-plague

display_name: historical-plague

palaeo-epidemiology

display_name: palaeo-epidemiology

plague-inventory

display_name: plague-inventory

plague-mapping

display_name: plague-mapping

plague-outbreaks

display_name: plague-outbreaks

yersinia-pestis

display_name: yersinia-pestis

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Digitizing historical plague


en: growth assimilation dvm npp forest

en: NPP anomalies

en: Spatially resolved yearly anomalies of NPP simulated by 3-PG model relative to the 1961–1990 period.

en:
Simulated net primary productivity (NPP) anomalies (percent deviation) in 1961-2018 years relative to the 1961–1990 reference period for _Picea abies_ and _Fagus sylvatica_. NPP was simulated for the species' potential distribution range in Switzerland on a 1 × 1 km grid using 3-PG model.
We first assimilated nearly 800 observation years from 271 permanent long-term forest monitoring plots across Switzerland, obtained between 1980 and 2017, into the 3-PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from.
We then estimated the NPP anomalies by first simulating the growth of _P. abies_ and _F. sylvatica_ monocultures with the average climate observed during the 1961–1990 period, until the age of 40 years (spin-up). The stands were simulated starting as 2-year-old plantations with an initial density of 10,000 trees/ha. Thinning was performed at age 20 and 35 to reach a final density of ca. 1,000 trees/ha at age 40. We then simulated 30 years forced by monthly resolved climatic data from either the 1961–1990 (reference, according to MeteoSwiss) or the 1991–2018 period. We neglected the first 40 years of simulations due to high variation in productivity caused by early stage stand development. To study the impact of climate extremes on NPP, we focused on the deviation in NPP (expressed in percentage difference from the reference period) during the 30 year period (age 41–70).

assimilation

display_name: assimilation

dvm

display_name: dvm

forest

display_name: forest

growth

display_name: growth

npp

display_name: npp

en: Net primary productivity (NPP) anomalies simulated by 3-PG model for Switzerland


en: phenology chilling hatch spongy-month budburst

en: Temperature data Spongy moth experiment

en:
4 files with hourly temperature recorded at the height of buds in each of the four temperature treatments:
- Winter6: greenhouse where temperature was kept >6°C over winter
- Winter10: greenhouse where temperature was kept >10°C over winter
- OTC_Ambient: Open Top Chamber at Ambient temperature
- OTC_Warm: Open Top Chamber at +3.5°C warmer temperature

en: 3 R-Scripts used for the analyses of the temperature, phenology and performance/preference tests

en: Phenology and performance/preference tests Data

en:
-"Synchronex_Cuttings_Pheno.txt" provides the budburst date ('Stage 2') of each twig of the six studies species in the four different temperature treatments ("ambient", "a+5"=Ambient +5°C, 'Greenhouse-5'= Greenhouse at temperature >5°C, 'Greenhouse_10' = Greenhouse at temperature >10°C); 'Success' give the percentage of buds within the twig that succeeded to reach at least stage 2 during the experiment.

'Synchronex-Gypsy.txt' provides the number of eggs that have hatched at each monitoring date (Day of the year in columns); "DOY_hatch_1" corresponds to the first DOY when at least one egg has hatched; "Replicate_egg_mass" correspond to the egg mass replicate (1 to 5)

'PerformanceTest_GypsyMoth.txt' provides the biomass in mg of the caterpillars fed with fresh leaves of each tested tree species during one week. "Fresh_alive" is the biomass of only the living caterpillars after 1 week and "Freshpermoth" corresponds the weight per living caterpillar (Fresh alive/Nalive)

'PreferenceTest_All_species.txt' provides the total surface of leaf disc of each tested tree species remaining after exposing 5 caterpillars to these leaves during 24H. "Total_area" is the surface of the disc of each species measured after 24h exposed to the spongy moth first instars. For each species 'control' means the surface of the disc after 24H without any exposure to the larvae. 'EatenPercent correspond to the percentage surface loss compared to the control.

en:
The files correspond to the data and R-script used for the analyses of the following paper "Feasting on the ordinary or starving for the exceptional: phenological synchrony between spongy moth and budburst of European trees in a warmer climate" published in Ecology and Evolution by Vitasse et al. 2023.
There are three zip files corresponding to the Temperature data, phenology/preference/performance tests and R-Scripts for the analyses.

Input data:
'Synchrony_Cuttings_Pheno.txt':

budburst

display_name: budburst

chilling

display_name: chilling

hatch

display_name: hatch

phenology

display_name: phenology

spongy-month

display_name: spongy-month

en: Synchrony between spongy moth hatching and leaf phenology of temperate trees