en:
The present dataset is part of the published scientific paper entitled “The role of spatial planning in land change: An assessment of urban planning and nature conservation efficiency at the southeastern coast of Brazil” (Pierri Daunt, Inostroza and Hersperger, 2021). In this work, we evaluated the conformance of stated spatial planning goals and the outcomes in terms of urban compactness, basic services and housing provision, and nature conservation for different land-use strategies. We evaluate the 2005 Ecological-Economic Zoning (EEZ) and two municipal master plans from 2006 in a coastal region in São Paulo State, Brazil. We used Partial Least Squares Path Modelling (PLS-PM) to explain the relationship between the plan strategies and land-use change ten years after implementation in terms of urban compactness, basic services and housing increase, and nature conservation.
We acquired the data for the explanatory variables from different sources listed on Table 1. Since the model is spatially explicit, all input data were transformed to a 30 m resolution raster. Regarding the evaluated spatial plans, we acquired the zones limits from the São Paulo State Environmental Planning Division (CPLA-SP), Ilhabela and Ubatuba municipality.
1)	Land use and cover data: Urban persistence, Urban axial, Urban infill, Urban Isolates, Forest cover persistence, Forest cover gain, NDVI increase
We acquired two Landsat Collection 1 Higher-Level Surface Reflectance images distributed by the U.S. Geological Survey (USGS), covering the entire study area (paths 76 and 77, row 220, WRS-2 reference system, https://earthexplorer.usgs.gov/). We classified one image acquired by the Landsat 5 Thematic Mapper (TM) sensor on 2005-05-150, and one image from the Landsat 8 Operational Land Imager (OLI) sensor from 2015-08-15. We collected 100 samples for forest cover, 100 samples for built-up cover and 100 samples for other classes. We then classified these three classes of land cover at each image date using the Support Vector Machine (SVM) supervised algorithm (Hsu et al., 2003), using ENVI 5.0 software.
Land-use and land-cover changes from 2005 to 2015 were quantified using map algebra, by mathematically adding them together in pairs (10*LULC2015 + LULC2005). We reclassified the LULC data into forest gain (conversion of any 2005 LULC to forest cover in 2015); forest persistence (2005 forested pixels that remained forested in 2015); new built-up area (conversion of any 2005 LULC to built-up in 2015); and urban maintenance (2005 built-up pixels that remained built-up in 2015).
To describe the spatial configuration of the urban expansion, we classified the new built-up areas into axial, infill and isolated, following Inostroza et al. (2013) (For details, please refer to Supplementary Material I at the original publication).
The NDVI was obtained from the same source used for the LULC data. With the Google Engine platform, we used an annual average for the best pixels (without clouds) for 2005 and 2015, and we calculated the changes between dates. We used increases of - 0.2 NDVI to represent an improvement in forest quality.
2)	Federal Census data organization: Urban Basic Services and Housing indicator, socioeconomic and population:
The data used to infer the values of basic services provision, socioeconomic and population drivers was derived from the Brazilian National Census data (IBGE, 2000 and 2010). Population density, permanent housing unit density, mean income, basic education, and the percentage of houses receiving waste collection, sanitation and water provision services, called basic services in the context of this study, were calculated per 30 m pixel. The Human Development Index is only available at the municipality level. We attributed the HDI for the vector file with the municipality border, and we rasterized (30 m resolution) this file in QGIS. Annual rates of change were then calculated to allow comparability between LULC periods. To infer the BSH, we used only areas with an increase in permanent housing density and basic services provision (See Supplementary Material I at the original publication).
3)	Topographic drivers
To infer the values of the topographic driver, we used the slope data and the Topographic Index Position (TPI) based on the digital elevation model from SRTM (30 m resolution) produced by ALOS (freely available at eorc.jaxa.jp/ALOS/en/about/about_index.htm), and both variables were considered constant from 2005 to 2015 (See Supplementary Material I at the original publication).

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

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

envidat

en: EnviDat: the Environmental Data Portal

envi

en: Environment

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    Description: Native forest cover gains from 2005 to 2015

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Resource Title: urban_persistence
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    Description: Urban persistence: Built-up 2005 = Built-up 2015

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    Description: Ecological-Economic Zoning (EEZ)

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

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

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    Description: New built-up pixels classified as isolated

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    Description: Increase in sanitation service

basic-services

display_name: basic-services

built-up-classification

display_name: built-up-classification

forest-gain

display_name: forest-gain

forest-persistence

display_name: forest-persistence

land-use-and-cover-change

display_name: land-use-and-cover-change

nature-conservation

display_name: nature-conservation

planning-outcome

display_name: planning-outcome


$oid: OBSOLETE

en:
DESCRIPTION
The dataset is used to run snowpack simulations with various forcing data at different resolutions with the Flexible Snow Model (FSM2oshd). A dynamical downscaling model (HICAR) and a semi-statistical downscaling approach (COSD) are used to downscale COSMO data to resolutions of 250 m, 100 m and 50 m. Simulations are run with the operational snow cover model and a model extension including wind- and gravity-induced snow redistribution (FSM2trans).
 Input Data
This paragraph describes the input data used to run simulations with FSM2trans
 HICAR
The HICAR input data is created by the High-resolution Intermediate Complexity Atmospheric Research model. The input data is available for different resolutions (250m, 100m and 50m) for a domain covering complex terrain in the Swiss Alps (Dischma)
 COSD
The COSD data was statistically downscaled within the OSHD framework to different resolutions (250m, 100m, 50m) for a domain covering complex terrain in the Swiss Alps (Dischma)
 Simulation files
For the Simulations, a landuse file and a namelist file with the parametrizations need to be supplied to the model
 simulation output
This simulation output that is used for the analysis of the study is provided.

en: FSM2trans snowpack simulations with HICAR input

en: dischma snowpack snow-hydrology fsm2 fsm2trans hicar

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: 2017.01_HCIAR_50.zip
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format: ZIP

media_type: application/zip

en:
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en:
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en:
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en:
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en:
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- rainfall
- snowfall
- runoff
- snowmelt
- temperature

en:
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    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/34e952ac-5973-4da0-997f-ab88dfcbd564/download/2017.07_hicar_50.zip
    Description: Input data July 2017 HICAR 50m resolution

en:
Resource Title: 2016.11_HICAR_100.zip
    Size: 549614230 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/668af1cb-d429-4163-82ed-175818ba5870/download/2016.11_hicar_100.zip
    Description: Input data november 2016 HICAR 100m resolution

en:
Resource Title: 2017.01_COSD.zip
    Size: 272140667 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/b9490aeb-da86-494f-877c-9eb6be651d8c/download/2017.01_cosd.zip
    Description: Input data January 2017 COSD

en:
Resource Title: 2017.02_HICAR_50.zip
    Size: 1097463760 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/35a80379-3a54-4792-aa57-30d77f5cab02/download/2017.02_hicar_50.zip
    Description: Input data February 2017 HICAR 50m resolution

en:
Resource Title: 2017.02_HICAR_250.zip
    Size: 303548366 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/ec1636b8-1bce-4cff-b1f1-a38069ac89c1/download/2017.02_hicar_250.zip
    Description: Input data February 2017 HICAR 250m resolution

en:
Resource Title: 2016.11_HICAR_250.zip
    Size: 326225322 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/87223396-acb5-4f85-8969-e9c1e37be822/download/2016.11_hicar_250.zip
    Description: Input data November 2016 HICAR 250m resolution

en:
Resource Title: FSM_sntrans.zip
    Size: 117802989 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/4a6c39e8-ef52-439e-9f68-ac4f17423188/download/fsm_sntrans.zip
    Description: Available input files for running with FSM2trans

en:
Resource Title: 2017.03_HICAR_250.zip
    Size: 340805883 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/0b313459-557e-4e48-aaa5-3f3ecea99ef1/download/2017.03_hicar_250.zip
    Description: Input data March 2017 HICAR 250m resolution

en:
Resource Title: output_validation_LiDAR.zip
    Size: 3626428 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/a24da30f-627b-413c-9ed9-aad3acaef5e2/download/output_validation_lidar.zip
    Description: snowheight output of validation days (LiDAR days) for all simulation runs
- 20.03.2027
- 31.03.2017
- 17.05.2017

en:
Resource Title: 2017.02_COSD.zip
    Size: 251637401 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/2b9d9c27-0e23-47c5-8e88-bc6406fcb01f/download/2017.02_cosd.zip
    Description: Input data February 2017 COSD

en:
Resource Title: 2017.05_HICAR_50.zip
    Size: 2561728437 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/d0e98236-f5fc-495d-a6e2-2ed08fd62f2f/download/2017.05_hicar_50.zip
    Description: Input data May 2017 HICAR 50m resolution

en:
Resource Title: 2017.06_COSD.zip
    Size: 294775835 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/14c5c921-6d52-409b-a542-04e46024f319/download/2017.06_cosd.zip
    Description: Input data June 2017 COSD

en:
Resource Title: 2017.06_HICAR_100.zip
    Size: 573560621 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/78ed5fc9-112a-48dd-996a-f84b26b3263c/download/2017.06_hicar_100.zip
    Description: Input data June 2017 HICAR 100m resolution

en:
Resource Title: 2016.11_COSD.zip
    Size: 264224065 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/b4507205-372a-42fb-a9c1-e8d92552d040/download/2016.11_cosd.zip
    Description: input data november 2016 COSD

en:
Resource Title: 2017.03_HICAR_100.zip
    Size: 571345359 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/0cbd4ca1-2bb7-4e95-a68f-aa1cab01552c/download/2017.03_hicar_100.zip
    Description: Input data March 2017 HICAR 100m resolution

en:
Resource Title: 2017.05_COSD.zip
    Size: 301461076 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/fc51e6dc-0217-4260-acdd-4774487412d4/download/2017.05_cosd.zip
    Description: Input data May 2017 COSD

en:
Resource Title: FSM.zip
    Size: 33570817 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/969d40cd-9460-4500-8a49-3ec7d0e13b70/download/fsm.zip
    Description: Available input files for running with FSM2

en:
Resource Title: 2017.07_COSD.zip
    Size: 301251879 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/8a792b31-ff97-439d-8eb3-2515cf2499c6/download/2017.07_cosd.zip
    Description: Input data July 2017 COSD

en:
Resource Title: 2017.06_HICAR_50.zip
    Size: 1248134155 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/06001feb-2337-46e6-884d-8d1f6b27472e/download/2017.06_hicar_50.zip
    Description: Input data June 2017 HICAR 50m resolution

en:
Resource Title: 2017.04_HICAR_100.zip
    Size: 565969532 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f9eb2878-7c48-443c-82bf-f86908dea39a/resource/b9ec85e4-e78a-4c97-9fd6-1a2dede5e261/download/2017.04_hicar_100.zip
    Description: Input data April 2017 HICAR 100m resolution


en:
This dataset supports a related publication (Sigmund et al., 2025) and contains
- results of four **large-eddy simulations** (LES) coupled to a Lagrangian model (LM) for snow transport, aiming to reproduce field measurements, especially latent heat fluxes, at the S17 site near Syowa Station, East Antarctica, in conditions of drifting and blowing snow,
- references to the **source code** of the LES-LM model,
- the source code and results of a simple **one-dimensional (1D) model** inspired by the large-scale model CRYOWRF (Sharma et al., 2023), aiming to reproduce the LES-LM results,
- post-processed **measurements** shown in the figures of the related publication,
- **programming code** for post-processing and plotting the results.
The LES-LM simulations solve the Navier-Stokes equations for incompressible flows and advection-diffusion equations for air temperature and specific humidity in a domain of 19.2 x 18.32 x 18.32 m³. In these simulations, the airflow is driven by a prescribed large-scale pressure gradient. We assume that the air density is constant (1.18 kg/m³) and the snow particles have a spherical shape and a density of 918.4 kg/m³. Further methodological details are described in the related publication. The 1D model and post-processing code was created using the R software version 4.3.2 (R Core Team, 2024).
References
- Sharma, V., Gerber, F., & Lehning, M. (2023): Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling. Geosci. Model Dev. 16, 719–749. [https://doi.org/10.5194/gmd-16-719-2023](https://doi.org/10.5194/gmd-16-719-2023)
- Sigmund, A., Melo, D. B., Dujardin, J., Nishimura, K., & Lehning, M. (2025). Parameterizing snow sublimation in conditions of drifting and blowing snow. Journal of Advances in Modeling Earth Systems, 17, e2024MS004332. [https://doi.org/10.1029/2024MS004332](https://doi.org/10.1029/2024MS004332)

en: Modeled and measured fluxes of latent and sensible heat and snow transport at S17 near Syowa in Antarctica

en: large-eddy-simulation parameterization antarctica blowing-snow turbulence snow-sublimation drifting-snow

envidat

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

en: EnviDat: the Environmental Data Portal

en: Environment

en:
Resource Title: (c) LES-LM_code_settings.zip
    Size: 38912 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_code_settings.zip
    Description: Simulation-specific settings (part of the LES-LM source code).

en:
Resource Title: (f) LES-LM_particles_case_2.Rdata
    Size: 1288490189 bytes
    Format: application/x-r-data
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_particles_case_2.Rdata
    Description: Properties of individual drifting and blowing snow particles in the LES-LM simulation of Case 2.

en:
Resource Title: (h) LES-LM_particles_case_3b.Rdata
    Size: 2040109466 bytes
    Format: application/x-r-data
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_particles_case_3b.Rdata
    Description: Properties of individual drifting and blowing snow particles in the LES-LM simulation of Case 3b.

en:
Resource Title: (b) Data_of_figures.zip
    Size: 51098 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/Data_of_figures.zip
    Description: Folder containing the data (csv files) visualized in figures of the related publication. The filenames specify the respective figure(s). However, data shown in Figures S5 and S6 are included in data resource (d).

en:
Resource Title: (k) Postprocessing_code.zip
    Size: 417382 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/Postprocessing_code.zip
    Description: R scripts used to post-process the results of the LES-LM model and 1D model and produce the figures.

en:
Resource Title: (e) LES-LM_particles_case_1.Rdata
    Size: 1036936806 bytes
    Format: application/x-r-data
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_particles_case_1.Rdata
    Description: Properties of individual drifting and blowing snow particles in the LES-LM simulation of Case 1.

en:
Resource Title: (i) 1D_model_code.zip
    Size: 29082 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/1D_model_code.zip
    Description: Source code of the 1D model (R scripts).

en:
Resource Title: (g) LES-LM_particles_case_3a.Rdata
    Size: 2147483648 bytes
    Format: application/x-r-data
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_particles_case_3a.Rdata
    Description: Properties of individual drifting and blowing snow particles in the LES-LM simulation of Case 3a.

en:
Resource Title: (a) Readme.pdf
    Size: 418202 bytes
    Format: application/pdf
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/Readme.pdf
    Description: Meta data for the whole dataset including a link to the LES-LM source code.

format: PDF

media_type: application/pdf

en:
Resource Title: (d) LES-LM_main_results.zip
    Size: 22963814 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/LES-LM_main_results.zip
    Description: Main results of the LES-LM simulations. We do not provide the complete raw output of the simulations because of the large amount of data. For example, the three-dimensional fields of wind velocity components, air temperature and specific humidity are only provided in horizontally averaged form.

en:
Resource Title: (j) Turbulence_measurements_case_1.txt
    Size: 1258291 bytes
    Format: text/plain
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.645/Turbulence_measurements_case_1.txt
    Description: Post-processed high-frequency measurements used to plot turbulence cospectra (data underlying Figure S2 of the related publication). Further measurements are published in a related dataset (Sigmund et al., 2021).

format: TXT

media_type: text/plain

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

drifting-snow

display_name: drifting-snow

large-eddy-simulation

display_name: large-eddy-simulation

parameterization

display_name: parameterization

snow-sublimation

display_name: snow-sublimation

turbulence

display_name: turbulence


en:
This dataset contains Community Land Model 5 (CLM5) simulation output over the spatial extent of Switzerland at different resolutions and based on a range of input datasets. It further contains land-use surface data used for the CLM5-simulations.
**Detailed description of the CLM5  simulation setup and the various input datasets  can be found in the accompanying publication: https://doi.org/10.5194/egusphere-2023-1832.**
 CLM5 simulation output
This dataset includes gridded CLM5 simulations of snow depth, gross primary productivity (GPP) and evapotranspiration at different resolutions ( 1km, 0.25° and 0.5°) and based on a range of input datasets over the spatial extent of Switzerland (see folder *gridded_CLM5_simulations*). Additionally, point-scale CLM5 simulations of snow depth and snow-water-equivalent at 36 snow-station locations (see folder *point_scale_CLM5_simulations*) are included. Latitude, longitude and elevation for these station locations can be found in table A1 of the above-mentioned publication. All simulation output spans from 01/01/2015 - 31/12/2019.
Included CLM5 simulation results are based on 3 different meteorological forcing datasets:
* Clim_CRU: standard global dataset, we used the recent state-of-the-art standrd global dataset CRU-JRA (https://catalogue.ceda.ac.uk/uuid/aed8e269513f446fb1b5d2512bb387ad)
* Clim_CRU*: ClimCRU upraded by downscaling temperature data using a temperature lapse rate of -6.5K/1000m and a high-resolution DEM
* Clim_OSHD: highest level of detail, meteorological forcing generated according to methods developed by the Operational Snow Hydrological Service (OSHD), at 1km spatial and 1hour temporal resolution-/li-
 Land-use surface data
This dataset further includes forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution (see folder *surface_landuse_datasets*). For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR), which includes a higher level of detail and is based on a more up-to-date land use datase, are provided. More details on these two datasets can be found in the above-mentioned publication.

en: Multi-resolution CLM5 simulations across Switzerland

en: snow snow-simulation land-use forest-productivity land-cover evapotranspiration oshd high-resolution clm5

en:
Resource Title: point_scale_CLM5_simulations.zip
    Size: 4515857 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/5c9bd5b4-baf0-4aa3-83c0-0864f9275f4e/resource/7e90ee76-d274-4add-8f66-d7f75c1f3621/download/point_scale_clm5_simulations.zip
    Description: Point-scale CLM5 simulation output of snow depth and snow water equivalent for 9 different simulation scenarios, each performed at 36 snow station locations across Switzerland. Please have a look at table A1 in the appendix of the linked publication for coordinates of the stations. Additional information on the setup, and the differences between simulation setups can also be found in the linked publication.

en:
Resource Title: surface_landuse_datasets.zip
    Size: 127856024 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/5c9bd5b4-baf0-4aa3-83c0-0864f9275f4e/resource/bb64e97d-c86d-491a-8671-b3f010812344/download/surface_landuse_datasets.zip
    Description: Forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution. For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR) are provided.

en:
Resource Title: gridded_CLM5_simulations.zip
    Size: 1275381556 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/5c9bd5b4-baf0-4aa3-83c0-0864f9275f4e/resource/2a1eed91-e1dd-41dd-993f-8533051685b9/download/gridded_clm5_simulations.zip
    Description: 12 gridded CLM5 simulations over the spatial extent of Switzerland:
- 1km, 0.25deg, 0.5deg
- 3 different meteorological forcings (Clim_CRU, CLIM_CRU*, CLIM_OSHD)
- 2 different land use forcings
each with the following outputs:
- daily snow depth (file SNOW_DEPTH.nc)
- monthly summed gross primary production (file FPSN_MONTH_SUM.nc)
- monthly summed evapotranspiration (file QFLX_EVAP_TOT_MONTH_SUM.nc).
Temporal extent of all simulations: 01/01/2015 - 31/12/2020.

evapotranspiration

display_name: evapotranspiration

forest-productivity

display_name: forest-productivity

high-resolution

display_name: high-resolution

land-cover

display_name: land-cover

land-use

display_name: land-use

oshd

display_name: oshd

snow

display_name: snow

snow-simulation

display_name: snow-simulation


en:
This repository contains data from the alpine Dischma watershed and its surroundings in eastern Switzerland and includes: (a) hourly hydrometeorological data with 100m spatial resolution, (b) remotely sensed snow depth data with 100m spatial resolution obtained at peak of winter, and (c) station measurements of variables such as snow depth and catchment runoff.
This dataset is particularly suited for (a) different simulation experiments using distributed and process-based models, including physics-based snow and hydrological models, (b) testing various snow data assimilation schemes, and (c) developing models representing snow-forest interactions.
The dataset is described in detail in:
Magnusson, J., Bühler, Y., Quéno, L., Cluzet, B., Mazzotti, G., Webster, C., Mott, R., and Jonas, T.: High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2024-374, in review, 2024.
This dataset was published within the INARCH project:
https://inarch.usask.ca/

en: A high-resolution snow and hydrometeorological dataset for the Dischma region in Switzerland

en: snow modelling cryosphere hydrology dischma inarch

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

cryosphere

display_name: cryosphere

dischma

display_name: dischma

hydrology

display_name: hydrology

inarch

display_name: inarch

modelling

display_name: modelling


en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for one meteorological station in Lens in Switzerland which is located within a natural coniferous forest with Scots pine (_Pinus sylvestris_; 150-170 yrs)) as dominant tree species. The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lens is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

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

en:
Resource Title: Forest station data (LEB)
    Size: 9240564 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fea7c28b-0a5b-4f38-b3df-c1ce66c2cf43/resource/21e6ffa5-4cc5-4310-be18-91c2d579163c/download/lebforest.csv
    Description: Data file.

format: CSV

media_type: text/csv

en:
Resource Title: Site photo of the forest station (LEB)
    Size: 382534 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/fea7c28b-0a5b-4f38-b3df-c1ce66c2cf43/resource/15eb26e6-46a4-43e6-8cdb-fd7072968eb3/download/leb.jpg
    Description: Site photo of the forest station from below (viewing upwards the slope)

format: jpeg

en:
Resource Title: Data plot of the forest station (LEB)
    Size: 234314 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/fea7c28b-0a5b-4f38-b3df-c1ce66c2cf43/resource/569d951e-97b2-44e0-9ad5-d861994a78eb/download/lebplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed


en:
For the investigation of microstructural and mechanical properties of snow unconfined compression experiments and 3D computed tomography (CT) imaging were performed on sintered rounded grain snow and spherical model snow. The spherical model snow was generated to create geometrically simplified, well-defined microstructures for calibration of numerical models, such as discrete element models (DEM) in which the microstructure is represented by spherical particles.
In the experiments, microstructural variation was created by varying the sintering time (contact size) and the density of the ice sphere samples (number of contacts). The 3D CT images allow for a complete reconstruction of the entire experimental sample (cylindrical sample dimension: diameter = 33.6 mm; height = 14 mm).

en: Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples

en: 3d-ct-images unconfined-compression-experiments discrete-element-modelling spherical-model-snow microstructure snow-mechanics

en:
Resource Title: Data Access
    Size: 161061273600 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.83/3dct/Data/
    Description:

en:
Resource Title: Data Structure (Python Notebook)
    Size: 335872 bytes
    Format: application/x-ipynb+json
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.83/3dct/Data_Structure.ipynb
    Description:

en:
Resource Title: README.txt
    Size: 1925 bytes
    Format: text/plain
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.83/3dct/readme.txt
    Description:

discrete-element-modelling

display_name: discrete-element-modelling

microstructure

display_name: microstructure

snow-mechanics

display_name: snow-mechanics

spherical-model-snow

display_name: spherical-model-snow

unconfined-compression-experiments

display_name: unconfined-compression-experiments


en:
This repository contains data related to the field experiments of the RESTORE project. This project is a collaboration between the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and the Swiss Federal Laboratories for Materials Science & Technology (EMPA). It has received funding from the Swiss National Science Foundation. The overall objective of the RESTORE project was to assess the effects of green spaces as facilitators and noise as impediment to recover from stress in people's daily environments across Switzerland.
We conducted a randomized, controlled field study to compare the psychophysiological benefits of exposure to forests and urban built environments with different levels of road traffic noise in healthy adults during 30-minute walks in Zürich, Switzerland to explore:
1) The psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure
2) The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world
3) The effects of a mindful walking intervention in urban forests for healthy adults
Accordingly, this repository includes data and documentation for the 3 scientific articles:
Scientific article 1. “Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: study protocol of a randomized controlled trial", BMC Psychology, 2024. https://doi.org/10.1186/s40359-024-01720-x
Scientific article 2. "Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial“. Journal of Environmental Psychology, 2025.
Scientific article 3. “The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world: A randomized controlled trial". To be submitted to PLOS One, 2025.
Scientific article 4: "Effects of a mindful walking intervention in urban forests for healthy adults". To be submitted to Current Psychology, 2025.

en: urban-landscape restoration traffic-noise field-data forest

en:
Resource Title: 06_Studyprotocol_GPS tracks of the walking routes.zip
    Size: 30328 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/1f04524c-c476-4fa7-9ca0-6707c86b1966/download/06_studyprotocol_gps-tracks-of-the-walking-routes.zip
    Description: This folder contains the GPS tracks of the walking routes in the test sites.

en:
Resource Title: 08_P2P3_Restore_WP2_P2P3_used_variables.sav
    Size: 198944 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/b4fd276d-bd46-4917-b0cb-b44c4ff73beb/download/08_p2p3_restore_wp2_p2p3_used_variables.sav
    Description: This SPSS data file includes the data used for analysis in paper 2 (Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial) and paper 3 ("The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world: A randomized controlled trial").

format: OCTET

en:
Resource Title: 11_P4_S1_Instructions for individual mindful walking.pdf
    Size: 26444740 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/85bc4150-32f9-480b-bbfb-d158b3dc74ac/download/11_p4_s1_instructions-for-individual-mindful-walking.pdf
    Description: This document contains the booklet with instructions for mindful walking, which participants in the mindfulness condition were encouraged to take with them and use during their individual walks over the 10 days following on-site participation.

en:
Resource Title: 12_P4_S2_Description of mindful walking intervention on site.pdf
    Size: 20117 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/de768dda-757a-451f-a331-e247dea5ee45/download/12_p4_s2_description-of-mindful-walking-intervention-on-site.pdf
    Description: This file includes the guided mindful walking instructions provided to participants in the mindfulness condition during the on-site walks.

en:
Resource Title: 09_P2_Fotos Noise ROS paper.zip
    Size: 6219160 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/b356ecb1-c0b6-4bb5-8df6-61a6295696e1/download/09_p2_fotos-noise-ros-paper.zip
    Description: This folder included the example pictures of the conditions included in paper 2  ("Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial“).

en:
Resource Title: 10_P2P3_Questionnaire_t3.pdf
    Size: 1174475 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/6c4eca4c-4221-4681-a1f1-bba704aa9c60/download/10_p2p3_questionnaire_t3.pdf
    Description: This document includes the questionnaire for Papers 2 and 3, administered at the third measurement time point (10 days after participation on site).

en:
Resource Title: 10_P2P3_Questionnaire_t2.pdf
    Size: 1190943 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/e666658c-7a4b-459c-8194-265e76b140a4/download/10_p2p3_questionnaire_t2.pdf
    Description: This document includes the questionnaire for Papers 2 and 3, administered at the second measurement time point (after the walk).

en:
Resource Title: 02_Studyprotocol_Data on Laeq from noise recordings of walking routes_Studyprotocol.sav
    Size: 6067 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/49d0a13e-5a9f-4809-a8cf-4468ea7050b9/download/02_studyprotocol_data-on-laeq-from-noise-recordings-of-walking-routes_studyprotocol.sav
    Description: This data file contains information on the LAeq levels recorded along the final walking routes between September 2021 and March 2022, prior to the commencement of data collection.

en:
Resource Title: 03b_Studyprotocol_Script_Analysis stationary noise evaluation.sps.sps
    Size: 7156 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/5e018e9b-3ef2-4946-a3fc-d95094e3a0ad/download/03b_studyprotocol_script_analysis-stationary-noise-evaluation.sps.sps
    Description: This SPSS syntax file contains a script for analyzing data related to the stationary evaluation of the acoustic impressions at the test sites, which is numbered 03a in this repository.

en:
Resource Title: 10_P2P3_Questionnaire_t1.pdf
    Size: 925030 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/f23f8436-97d5-47c8-8ef4-788b85d77149/download/10_p2p3_questionnaire_t1.pdf
    Description: This document includes the questionnaire for Papers 2 and 3, administered at the first measurement time point (before the walk began).

en:
Resource Title: 05_Studyprotocl_Participant consent form.pdf
    Size: 103303 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/cca35a46-b79c-4d2e-8063-03ca1a7c52f4/download/05_studyprotocl_participant-consent-form.pdf
    Description: This file contains the informed consent document that participants signed to participate in the study.

en:
Resource Title: 04_Studyprotocol_Participant information sheet.pdf
    Size: 96790 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/7015619c-1cfc-4c66-a512-3a8b1c526f89/download/04_studyprotocol_participant-information-sheet.pdf
    Description: This file includes the information sheet provided to participants before they consented to take part in the study.

en:
Resource Title: 03a_Studyprotocol_Data on evaluation of acoustic impression of the test settings_Studyprotocol.sav
    Size: 21982 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/2bbb96b2-6470-4f1a-8ef0-5b23c7d4c964/download/03a_studyprotocol_data-on-evaluation-of-acoustic-impression-of-the-test-settings_studyprotocol.sav
    Description: This data file includes information for an additional post hoc classification of the sound environment of the test sites. This evaluation was conducted in the afternoons of the same week in 2023 at two locations within each test site by a civil servant who was not familiar with the study's research questions.

en:
Resource Title: 13_P4_Data mindful walking.sav
    Size: 514314 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/f47540a6-0876-46df-b9a1-49385dfee573/download/13_p4_data-mindful-walking.sav
    Description: This file contains data for the manuscript "Effects of a mindful walking intervention in urban forests for healthy adults".

en:
Resource Title: 07_Studyprotocol_Test site pictures.zip
    Size: 39574345 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/ccb268cb-692e-4051-8710-59add9c23e68/download/07_studyprotocol_test-site-pictures.zip
    Description: This folder includes two pictures of each test site. The locations for the two pictures on each route were chosen to be as characteristic as possible in terms of the visual and acoustical impressions of the walk.

en:
Resource Title: 01_Studyprotocol_Locations of the starting points of the walking routes in the test settings.pdf
    Size: 68897 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dfd6af83-8ea8-4914-a18f-bb1e6ca3d533/resource/9e531b35-7406-4ffc-acd5-fd78757775ac/download/01_studyprotocol_locations-of-the-starting-points-of-the-walking-routes-in-the-test-settings.pdf
    Description: This document includes GPS coordinates of the starting points of the walking routes in the test sites.

field-data

display_name: field-data

forest

display_name: forest

restoration

display_name: restoration

traffic-noise

display_name: traffic-noise

urban-landscape

display_name: urban-landscape


en:
This repository hosts the experimental data accompanying our publication "Field measurements of multiaxial strength of weak snow layers" submitted to the Journal of Glaciology.
It contains:
**1. Details on the multiaxial shear--compression unit (MSCU):**
-CAD files of the MSCU design
-The loading unit of the MSCU is based on the SnowMicroPen (SMP) created by the WSL Snow and Avalanche Research Institute SLF. For more details, the SLF should be contacted.
**2. Experimental data related to the publication "Field measurements of multiaxial strength of weak snow layers", submitted to the Journal of Glaciology**:
-the raw .pnt files containing the force as a function of distance as measured by the force sensor.
-csv files with the data from the multiaxial field tests performed on weak layers containing buried surface hoar, on 14 February 2024 and between 23 and 28 February 2025: loading angle, date, and compressive and shear strength values.
-a representative video of the multiaxial loading experiment, showing experiment ID 1332 (2025). Video recordings of other experiments are available upon request.
-microstructural values obtained via micro-computed tomography scans.

en: Field measurements of multiaxial strength of buried surface hoar weak layers measured with the mobile shear--compression unit (MSCU)

en: strength dry-snow-avalanche weak-layer snow-mechanics field-tests

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: MSCU_CAD_Drawings.zip
    Size: 1184891 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/e612c030-d34c-48ee-bfa1-7cd716f020b2/resource/84b11bf7-a38a-4414-9abe-8888ea9d5e43/download/cad_mscu.zip
    Description: CAD files and drawings of the mobile shear-compression unit (MSCU).

en:
Resource Title: strength_data_2025_buriedsurfacehoar.csv
    Size: 5949 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e612c030-d34c-48ee-bfa1-7cd716f020b2/resource/ccc70b4a-d9aa-4bd1-a660-bef7a0b2cbfa/download/strength_data_2025_buriedsurfacehoar.csv
    Description: Strength data of 2025 MSCU surface hoar campaign

en:
Resource Title: raw_PNT_files25.zip
    Size: 1352663 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/e612c030-d34c-48ee-bfa1-7cd716f020b2/resource/7acf32a9-8704-4d60-a721-4d7292f5f3c7/download/raw_pnt_files25.zip
    Description: Raw .pnt files from the 2025 MSCU campaign, including force versus distance of the loading unit

en:
Resource Title: Video_ID1332.mp4
    Size: 37989908 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/e612c030-d34c-48ee-bfa1-7cd716f020b2/resource/9d603cff-f4c3-4053-a67e-613851da9e75/download/video_id1332.mp4
    Description: Representative video of a loading experiment in 2025.

en:
Resource Title: raw_PNT_files24.zip
    Size: 2757755 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/e612c030-d34c-48ee-bfa1-7cd716f020b2/resource/848ae1be-ba2e-433d-965c-98608fd63d49/download/raw_pnt_files24.zip
    Description: Raw .pnt files from the 2024 campaign, including force versus distance of the loading unit.

en:
Resource Title: microCT_data.xlsx
    Size: 16671 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/e612c030-d34c-48ee-bfa1-7cd716f020b2/resource/bbd67a6e-024b-496f-ad46-d705e6d0e5fc/download/microct_data.xlsx
    Description: Microstructural data obtained via microCT scans

format: XLS

en:
Resource Title: strength_2024_buriedsurfacehoar.csv
    Size: 3523 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e612c030-d34c-48ee-bfa1-7cd716f020b2/resource/9933f4ec-5c5b-4157-b2bb-969330bee920/download/strength_2024_buriedsurfacehoar.csv
    Description: Strength data of 2024 MSCU surface hoar campaign

dry-snow-avalanche

display_name: dry-snow-avalanche

field-tests

display_name: field-tests

strength

display_name: strength

weak-layer

display_name: weak-layer


en:
This dataset contains all data on which the following publication below is based.
Paper Citation:
Frey B., Maurer C., Schneider K. (2023) Informationen zum Boden anhand der Gebundenheit der Rote-Liste Arten BAFU. Bundesamt für Umwelt BAFU. 26 p.
Please cite this paper together with the citation for the datafile.
Soil is the habitat and basis of life for countless creatures. The great importance of soil organisms for the fertility of our soils is widely recognized, but information is sparse on their distribution and possible endangerment in Switzerland. In the present project, target species, i.e. species that are closely linked to the soil, were identified, and for the the first time, information was gathered on the degree of endangerment of the soil ecosystem in Switzerland on the basis of Red List species. For eleven Red List  groups, the species' soil dependency was determined, i.e. whether their life cycle includes stages in or on the soil. The assessment of soil dependency was made using four classes, which enabled the classification not only of insects but also of vertebrates, land snails, lichens and fungi.

en: Information on soil based on the soil dependency of the FOEN red list species

en: fungi lichens soil-organisms soil-dependency ecosystem-protection info-fauna database eco-fauna fauna soil-quality red-list conservation soil-biodiversity

en:
Resource Title: raw_data.xlsx
    Size: 422329 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/006ebf36-0cbf-415f-bd0c-0261bc32b1f5/resource/b2f4f53a-4ffa-4a44-8290-0c3c9c6b1a82/download/raw_data.xlsx
    Description: Raw dataset of species and their soil dependency as well as endangerment status.

en:
Resource Title: soil_dependency.xlsx
    Size: 1367091 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/006ebf36-0cbf-415f-bd0c-0261bc32b1f5/resource/73beef16-17c8-46e4-a77b-adc5ec694918/download/soil_dependency.xlsx
    Description: Overview over the soil dependency and endangerment status of different groups of organisms.

en:
Resource Title: percentages_endangerment-categories.xlsx
    Size: 14873 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/006ebf36-0cbf-415f-bd0c-0261bc32b1f5/resource/a79f2c66-cf27-4427-b7ad-829931cb175a/download/percentages_endangerment-categories.xlsx
    Description: Proportion of endangered species grouped by the four soil dependency classes.

conservation

display_name: conservation

database

display_name: database

eco-fauna

display_name: eco-fauna

ecosystem-protection

display_name: ecosystem-protection

fauna

display_name: fauna

fungi

display_name: fungi

info-fauna

display_name: info-fauna

lichens

display_name: lichens

red-list

display_name: red-list

soil-biodiversity

display_name: soil-biodiversity

soil-dependency

display_name: soil-dependency

soil-organisms

display_name: soil-organisms

soil-quality

display_name: soil-quality


data-set-on-snow-instability

en:
These data on snow instability include three data subsets that were analyzed and the results published by Reuter and Schweizer (2018) who suggest a novel framework on how to describe snow instability by failure initiation, crack propagation and slab tensile support.
Please refer to the Read-me file for further details on the data.
These data are the basis of the following publication:
Reuter, B. and Schweizer, J., 2018. Describing snow instability by failure initiation, crack propagation and slab tensile support. Geophys. Res. Lett., 45, doi: 10.1029/2018GL078069.

en: Data set on snow instability

en: rutschblock slab-tensile-support failure-initiation snow-avalanche crack-propagation avalanche-forcasting slab snow-stability-evaluation propgatoin-saw-test weak-layer

title_for_slug: data-set-on-snow-instability

en:
Resource Title: Read-me file on snow instability data
    Size: 172308 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/3735a11a-34a5-4a83-b2db-ed22484589d8/resource/7ca3bf86-f927-43d0-bc49-56b444d42dcb/download/read-me_data_sets_snow_instability.pdf
    Description:

en:
Resource Title: data set on snow instability
    Size: 10332 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3735a11a-34a5-4a83-b2db-ed22484589d8/resource/25cec3bc-4c79-411b-b04f-5bee43114c42/download/snow_instability_data.csv
    Description:

avalanche-forcasting

display_name: avalanche-forcasting

crack-propagation

display_name: crack-propagation

failure-initiation

display_name: failure-initiation

propgatoin-saw-test

display_name: propgatoin-saw-test

rutschblock

display_name: rutschblock

slab

display_name: slab

slab-tensile-support

display_name: slab-tensile-support

snow-avalanche

display_name: snow-avalanche

snow-stability-evaluation

display_name: snow-stability-evaluation


en:
This data set was used in the analysis by Techel et al. **Can model-based avalanche forecasts match the discriminatory skill of human danger level forecasts? A comparison from Switzerland**. Please note that the title of the preprint was *Forecasting avalanche danger: human-made forecasts vs. fully automated model-driven predictions*, submitted to *Natural Hazards Earth System Sciences* on 20 Aug 2024.
The final manuscript used data from three forecasting seasons (2022/2023, 2023/2024, 2024/2025) , the preprint two forecasting seasons (2022/2023, 2023/2024) .
Currently, the repository contains data from two avalanche forecasting seasons in Switzerland. The third season will be added (to be done, 30 June 2025).
**Interpolated predictions**
- The .zip file contains the interpolated predictions for the three models in nowcast- and forecast- mode. This data is needed to reproduce the figures and tables in the submitted preprint.
The other data are the **raw data** underlying the interpolations:
- Avalanche forecast by WSL Institute for Snow and Avalanche Research SLF, published at 17.00 local time, valid for the following 24 hours and relating to dry snow avalanche conditions.
- Model predictions in *nowcast*- and *forecast*-mode for three models (*danger level*, *instability*, *natural avalanche*), valid for 12.00 local time
- Subset of points extracted from GPS tracks (courtesy of Skitourenguru GmbH)
- Avalanche observations - natural avalanches and human-triggered avalanches
- Estimates of the snowline
- Randomly chosen subset of grid points used for generating reference distributions
For details regarding the data sets refer to the publication.

en: Evaluating the predictive performance of human avalanche forecasts and model predictions in Switzerland

en: avalanche-forecast forecast-models machine-learning spatial-modelling avalanche-release-probability

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: GPS data and human-triggered avalanches
    Size: 291620 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/48dfa07a-0f63-4e09-9160-6777085094e6/download/tracksavalanches_parametersubset.csv
    Description: Contains (1) the subset of points extracted from GPS tracks recorded during backcountry touring and uploaded to the website skitourenguru.ch and (2) the corresponding subset of human-triggered avalanches. Data (1) was provided by Skitourenguru GmbH and data (2) was collected by SLF. - Variables contained are date, Swiss coordinates (x, y), aspect (N = 0, NE = 45, ...), elevation (ele), and event (event = 1, non-event = 0).

en:
Resource Title: Human-triggered avalanches 2023/2024
    Size: 38243 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/4e3cc5ed-ff9a-4d74-ae66-08a868de5332/download/human-triggered_avalanches_2023-2024.csv
    Description: The file contains the reported human-triggered avalanches. The variables are as follows: id, release date (date), name, Swiss coordinates (x,y), elevation (ele), remark, reported avalanche size expressed using avalanche activity index (sizeAAI), aspect, event type (type), event (yes = 1, no = 0)

en:
Resource Title: Avalanche forecast
    Size: 10232922 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/80146d72-7abb-4b39-8336-613b49ed9a3c/download/bulletinprepared.csv
    Description: Data contains forecasts relating to dry-snow avalanche conditions only. Forecast issued at 17.00 local time. Contains variables for the warning region (sector_id), publication date (date), danger level - sub-level combination expressed using numeric values (integer value of danger level -0.33 for sub-level minus, -0 for sub-level neutral, +0.33 for sub-level plus, altitude as indicated in the bulletin, and whether aspect (North = 0, Northeast = 45, ...) was indicated in the bulletin (no: 0, yes: 1).

en:
Resource Title: Snowline estimates 2023/2024
    Size: 2695027 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/87671683-a61d-45c0-92ff-d60fa3bd7e88/download/schneegrenze_beobachtungen_23-24.csv
    Description: Daily snowline estimates provided by observers for North (aspect = 0) and South (aspect = 180) slopes for the 2023/2024 season. For aspects in between North and South, values are interpolated. Contains observation date (date), coordinates (Swiss coordinates x, y), snowline elevation (snowline), and aspect.

en:
Resource Title: Human-triggered avalanches 2022/2023
    Size: 41461 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/32c06c01-381b-4def-9cc8-b0db86c457e9/download/human-triggered_avalanches_2022-2023.csv
    Description: The file contains the reported human-triggered avalanches. The variables are as follows: id, release date (date), name, Swiss coordinates (x,y), elevation (ele), remark, reported avalanche size expressed using avalanche activity index (sizeAAI), aspect, event type (type), event (yes = 1, no = 0)

en:
Resource Title: Model predictions (interpolated)
    Size: 85948873 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/d0599e29-dbf1-4d54-8c4b-10a248fd9fa2/download/model_predictions_interpolated.zip
    Description: The zip file contains csv-files the interpolated model predictions for three models, in forecast and nowcast-mode, for the three different data sets, as described in the publication.

en:
Resource Title: Snowline estimates 2022/2023
    Size: 2504217 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/be143570-31b9-4f62-a51c-05bde676f461/download/schneegrenze_beobachtungen_22-23.csv
    Description: Daily snowline estimates provided by observers for North (aspect = 0) and South (aspect = 180) slopes for the 2022/2023 season. For aspects in between North and South, values are interpolated. Contains observation date (date), coordinates (Swiss coordinates x, y), snowline elevation (snowline), and aspect.

en:
Resource Title: Model predictions (raw data)
    Size: 24502560 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/cb2836c0-bab2-4686-b38b-2f3562827e89/download/modelpredictions_rawdata.zip
    Description: Model predictions (raw data) for three models, in nowcast and forecast mode. Not all models are available for both seasons. - These data are the basis for the interpolated predictions, which can be found in the other zip-folder

en:
Resource Title: Natural avalanches 2022/2023
    Size: 73735 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/ca5a219a-bf68-49ee-82b2-d386e221f5ef/download/natural_avalanches_2022-2023.csv
    Description: Natural avalanche observation (dry avalanches). 2022-2023 forecasting season.

en:
Resource Title: Randomly sampled subset of grid points from 1 km DEM
    Size: 17861 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/021d90e0-68bd-42b6-8815-e26c10d3a363/download/dem_filteredavalancheelevations.csv
    Description: Contains the randomly sampled subset of grid points from 1 km DEM. Three variables: coordinates (x, y) and elevation (elev).

en:
Resource Title: Natural avalanches 2023/2024
    Size: 75730 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/00b8d3db-ecf1-4a75-9ed9-b707fa2f6324/download/natural_avalanches_2023-2024.csv
    Description: Natural avalanche observation (dry avalanches). 2023/2024 forecasting season.

avalanche-forecast

display_name: avalanche-forecast

avalanche-release-probability

display_name: avalanche-release-probability

forecast-models

display_name: forecast-models

machine-learning

display_name: machine-learning

spatial-modelling

display_name: spatial-modelling


en:
Individual genotypes assessed at six nuclear microsatellite loci (two alleles per locus) for individuals of the butterfly Melanargia galathea (Marbled white) that were collected throughout Switzerland, along the regular grid of the Biodiversity Monitoring (BDM) of Switzerland. For each individual, the sampling site (number) and the genotype are given. Note that due to privacy restrictions, the original geographic coordinates remain disclosed. For original coordinates, data holders should be contacted (Swiss Federal Office for the Environment; Biodiversity Monitoring Switzerland).
The data refer to the following publication: Terzer et al., Distinct spatial patterns of genetic structure and diversity in the butterfly Marbled White (Melanargia galathea) inhabiting fragmented grasslands. Conservation Genetics, https://doi.org/0.1007/s10592-023-01593-4.

en: Nuclear microsatellite genotypes of the butterfly Melanargia galathea

en: genetic-structure monitoring conservation-genetics melanargia-galathea genetic-diversity

conservation-genetics

display_name: conservation-genetics

genetic-diversity

display_name: genetic-diversity

genetic-structure

display_name: genetic-structure

melanargia-galathea

display_name: melanargia-galathea

monitoring

display_name: monitoring


en:
Continuous stem radius measurements to investigate carbon balance and water relations of trees
 Purpose:
Assessment of growth and water related stem changes

en: Automated point dendrometer measurements at LWF sites

en: swiss-forest-lab long-term-forest-ecosystem-research stem-diameter icp-forests tree-growth

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.

format: HTML

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

stem-diameter

display_name: stem-diameter

swiss-forest-lab

display_name: swiss-forest-lab

tree-growth

display_name: tree-growth


en:
In this experiment, we investigated the inoculation-effects of two ectomycorrhizal fungi (EMF) species with contrasting evolutionary histories, ecological properties, host-preferences, and habitat-ranges on phenotypic responses and growth dynamics of pedunculate oak (*Quercus robur*), an ecologically and economically important temperate forest tree species.
We set up the mycorrhization experiment using 96 plants of a genetically uniform *Q. robur* clone (DF159) and applied four treatments: A control treatment; an inoculation-treatment with the cosmopolitan Ascomycete *Cenococcum geophilum*, which is commonly found in oak forests; an inoculation-treatment with the Basidiomycete *Piloderma croceum*, which has not yet been found in natural oak forests but has been shown in previous experiments to support oak growth; and a co-inoculation treatment. We then assessed growth stage development of the trees over eight experimental weeks and measured various phenotypic traits during a destructive sampling.

en: Phenotypic and Growth Stage Development Data of a Quercus robur Mycorrhization Experiment

en: oak ectomycorrhiza cenococcum-geophilum rhythmic-growth quercus-robur piloderma-croceum

envidat

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: time_series.csv
    Size: 83281 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d0661cc-cbbc-452e-8bd9-574161c73cd1/resource/2664abc3-ba85-4000-bb9d-162677eb47b7/download/time_series.csv
    Description: Contains growth stage data assessed over the experimental period.

Columns:
- ID = Tree identifier.
- Set = Date of plant preparation.
- Treatment = Experimental treatment.
- Date = Date of growth stage assessment,
- Days = Number of past days since start of experiment.
- Stage = Growth stage (XY = Groth cycle & development stage).
- Week = Experimental week.

en:
Resource Title: pheno_data.csv
    Size: 24577 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d0661cc-cbbc-452e-8bd9-574161c73cd1/resource/e0197cc6-6279-4f22-8e6a-3cc51a8973e1/download/pheno_data.csv
    Description: Contains phenotypic data assessed during the destructive sampling step of the experiment.

Columns:
- ID = Tree identifier.
- Treatment = Experimental treatment.
- nSF = Number of completed shoot flushes.
- Max_Stages_Reached = Total number of growth stages reached during the experiment.
- n_L_SF1 = Number of leaves of the second newest shoot flush at time of sampling.
- n_L_SF2 = Number of leaves of the newest shoot flush at time of sampling.
- Alive = Plant alive or not.
- Contamination = Plant contaminated or not.
- Exclude = Exclude plant or not.
- Shoot_Length_Init = Shoot length at start of the experiment.
- Shoot_Length = Shoot length at sampling.
- Delta_Length = Shoot length increase during experiment.
- FW_Plant = Fresh weight total plant.
- DW_Plant = Dry weight total plant.
- FW_Shoot = Fresh weight shoot.
- DW_Shoot = Dry weight shoot.
- FW_Stem = Fresh weight stem.
- DW_Stem = Dry weight stem.
- FW_L_SF1 = Fresh weight leaves second newest shoot flush.
- DW_L_SF1 = Dry weight leaves second newest shoot flush.
- FW_L_SF2 = Fresh weight leaves newest shoot flush.
- DW_L_SF2 = Dry weight leaves newest shoot flush.
- FW_L_Rest = Fresh weight remaining leaves.
- DW_L_Rest = Dry weight remaining leaves.
- FW_Bud = Fresh weight bud.
- DW_Bud = Dry weight bud.
- FW_Roots_Total = Fresh weight total roots.
- DW_Roots_Total = Dry weight total roots.
- FW_PR = Fresh weight principal roots.
- DW_PR = Dry weight principal roots.
- FW_LR = Fresh weight lateral roots.
- DW_LR = Dry weight lateral roots.
- A_L_SF1 = Leave area second newest shoot flush.
- A_L_SF2 = Leave area newest shoot flush.
- N_Ceno = Number of root tips mycorrhized by *Cenococcum geophilum*.
- N_Pilo = Number of root tips mycorrhized by *Piloderma croceum*.
- N_Other = Number of root tips mycorrhized by other species.
- N_No = Number of not mycorrhized root tips.
- Length_Tot = Total root length.
- Area_Tot = Total root surface area.
- Diameter_Avg = Average root diameter.
- Root_Vol = Total root volume.
- Tips = Total number root tips.
- Forks = Total number root forks.
- Crossings = Total number root crossings.
- Length_Fine = Root length fine roots (diameter < 1mm).
- SA_Fine = Surface area fine roots (diameter < 1mm).
- Vol_Fine = Volume fine roots (diameter < 1mm).

cenococcum-geophilum

display_name: cenococcum-geophilum

ectomycorrhiza

display_name: ectomycorrhiza

oak

display_name: oak

piloderma-croceum

display_name: piloderma-croceum

quercus-robur

display_name: quercus-robur

rhythmic-growth

display_name: rhythmic-growth


en:
Surface topography maps (spatial extent: 400 m x 400 m) obtained at approximately 300 m from the top of the Hammarryggen Ice Rise in Dronning Maud Land, East Antarctica, using a Riegl VZ-6000 Terrestrial Laser Scanner (TLS). Scans were obtained on 5 days in the 2018-2019 Austral summer: on December 21 and 27, and January 2, 4 and 11. By using reflectors installed on bamboo poles, scans were registered with respect to the reflectors, such that the difference between two successive scans reveals the spatial patterns of erosion and deposition of snow. On each scan day, we used multiple scan positions to create one combined point cloud. After applying an octree filter on the point cloud, a 3D surface was obtained. For each day, the dataset contains a 1 mm and a 10 cm octree filter resolution file, only including points in a 400 m x 400 m area centered around the scan positions.
Notes:
* All files in the dataset are in the same coordinate system. However, this coordinate system is arbitrary (i.e., not related to any global coordinate system).
* From the installed reflectors, 4 reflectors could be used over the full period. The scan accuracy is generally higher within the area enclosed by the reflectors.
* The scans from January 2 were found to have exhibited small tilt during the scan and are of lesser accuracy.
* By walking along fixed corridors, disturbance of the snow was limited.

en: Terrestrial laser scans on Hammarryggen Ice Rise, Dronning Maud Land, East Antarctica

en: depth-of-snowfall terrestiral-laserscanning gridded-data antarctica terrestrial-laser-scans

en:
Resource Title: Scan from 21 December 2018, 1 mm resolution
    Size: 271646425 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/0bf20a3a-f462-4313-9393-dcba4c207bfe/download/20181221_combi_2.5d_0.001m.zip
    Description: Scan from 21 December 2018, 1 mm resolution

en:
Resource Title: Scan from 11 January 2019, 10 cm resolution, version 2
    Size: 21786633 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/11ab1fc7-2eba-4506-823c-c06120c538e2/download/20190111_combi_2.5d_0.1m.zip
    Description: Scan from 11 January 2019, 10 cm resolution, version 2

en:
Resource Title: Scan from 27 December 2018, 1 mm resolution
    Size: 324407426 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/713d2875-611c-483f-af9c-2756125153d7/download/20181227_combi_2.5d_0.001m.zip
    Description: Scan from 27 December 2018, 1 mm resolution

en:
Resource Title: Scan from 4 January 2019, 1 mm resolution
    Size: 371000882 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/f6bacba5-c126-496c-aae8-0cea0a7db3c1/download/20190104_combi_2.5d_0.001m.zip
    Description: Scan from 4 January 2019, 1 mm resolution

en:
Resource Title: Scan from 27 December 2018, 10 cm resolution
    Size: 26161402 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/3493a5ce-398d-482c-942f-2ebd558acd10/download/20181227_combi_2.5d_0.1m.zip
    Description: Scan from 27 December 2018, 10 cm resolution

en:
Resource Title: Deprecated: Scan from 11 January 2019, 10 cm resolution, version 1
    Size: 33017091 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/ca01d845-b9c9-4ff4-9721-e52096546a03/download/20190111_combi_2.5d_0.1m.zip
    Description: This resource is deprecated. It contains erroneous data.

en:
Resource Title: Scan from 2 January 2019, 10 cm resolution
    Size: 33632491 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/31da45fa-770b-44ee-8121-cdbccffa9f03/download/20190102_combi_2.5d_0.1m.zip
    Description: Scan from 2 January 2019, 10 cm resolution

en:
Resource Title: Scan from 11 January 2019, 1 mm resolution
    Size: 384645137 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/2abd22ce-9aa5-48d3-85d6-16fce30e4dac/download/20190111_combi_2.5d_0.001m.zip
    Description: Scan from 11 January 2019, 1 mm resolution

en:
Resource Title: Scan from 2 January 2019, 1 mm resolution
    Size: 358665175 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/cce4e4f2-713a-4ced-8276-994c3c6d1fca/download/20190102_combi_2.5d_0.001m.zip
    Description: Scan from 2 January 2019, 1 mm resolution

en:
Resource Title: Scan from 21 December 2018, 10 cm resolution
    Size: 20747718 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/24c7f00b-bffd-4ecd-b1cc-b8595cf9cabc/download/20181221_combi_2.5d_0.1m.zip
    Description: Scan from 21 December 2018, 10 cm resolution

en:
Resource Title: Scan from 4 January 2019, 10 cm resolution
    Size: 31421084 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/85476f78-5964-4d09-9b39-bf6b44cf3ea2/download/20190104_combi_2.5d_0.1m.zip
    Description: Scan from 4 January 2019, 10 cm resolution

antarctica

display_name: antarctica

depth-of-snowfall

display_name: depth-of-snowfall

gridded-data

display_name: gridded-data

terrestiral-laserscanning

display_name: terrestiral-laserscanning

terrestrial-laser-scans

display_name: terrestrial-laser-scans


en:
In 2013, the Institute for Applied Plant Biology (IAP) started a monitoring programme to study the development and the spatial variation of the ash dieback disease with the aim to find some partially resistant European ash trees (Fraxinus excelsior).
We collaborate as co-authors for the publication: Spread and Severity of Ash Dieback in Switzerland - Tree Characteristics and Landscape Features Explain Varying Mortality Probability (Klesse et al. 2021 in frontiers)

en: Monitoring of ash trees as part of the Intercantonal Forest Observation Programme

en: monitoring iap ash-dieback forest fraxinus

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

ash-dieback

display_name: ash-dieback

forest

display_name: forest

fraxinus

display_name: fraxinus

iap

display_name: iap

monitoring

display_name: monitoring


en:
Sampling of deadwood for density and chemical analysis during summer 2009
 Purpose:
Determination of N and C pools of deadwood
 Paper Citation:
 * WEGGLER, K.; DOBBERTIN, M.; JÜNGLING, E.; KAUFMANN, E.; THÜRIG, E., 2012. Dead wood volume to dead wood carbon: the issue of conversion factors. European Journal of Forest Research 131, 1423-1438.

en: Deadwood sampling at Sanasilva and LWF sites

en: swiss-forest-lab lignin long-term-forest-ecosystem-research icp-forests carbon nitrogen deadwood

carbon

display_name: carbon

deadwood

display_name: deadwood

icp-forests

display_name: icp-forests

lignin

display_name: lignin

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

nitrogen

display_name: nitrogen

swiss-forest-lab

display_name: swiss-forest-lab


snow-depth-mapping

en:
The available datasets are snow depth maps with a spatial resolution of 2m generated from image matching of ADS 80/100 data. Image acquisition took place at peak of winter (time when the thickest snowpack is expected). The snow depth maps are the difference of a summer DSM from the winter DSM of the corresponding date . The summer DSM used is a product of image matching of ADS 80 data from summer 2013. In the available products buildings, vegetation and outliers were masked (set to NoData).
For the elimination of buildings the TLM layer (swisstopo) was used, because this layer might not represent exactly the
state of infrastructure at time of image acquisition, it is possible that mainly in dense settlement some buildings were not successfully masked. For the relevant area above treeline the masking of buildings showed good results. Vegetation got masked for a height above ground - 1m and was detected in a combination of summer and winter data sets. As Outliers were considered unrealistic snow depths caused by a failure of the image matching algorithm. Snow depths - 15m and smaller than - -15m were classified as outliers. Negative snow depth were kept, because of an uncertainty in image orientation accuracy. It is expected that in regions with negative snow depth also positive snow depth are underestimated by the same amount, which means that an estimation of snow volume should be carried out summing up the absolute values of snow depth (also the negative ones). For volume estimation in small regions the user has to take into account, that orientation accuracy of the images is roughly around 1-2 GSD (30cm), which propagates directly to the snow depth product. Areas which are not covered by snow got assigned a value of 0 as snow depth.
The work is published in:
Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C., (2015). Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9 (1), 229-243. doi: 10.5194/tc-9-229-2015

en: Snow Depth Mapping

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

title_for_slug: snow-depth-mapping

en:
Resource Title: Snow depth map 20150415
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/578e95ce-ffa0-4fc6-8109-d9653b2c622a/download/snowmap_2015_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

format: TIFF

media_type: image/tiff

en:
Resource Title: Snow depth map 20140417
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/5cf5d3a5-555d-429e-9819-6c93ccce6dfc/download/snowmap_2014_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.18 m

en:
Resource Title: Snow depth map 20120320
    Size: 412272526 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/aff41055-8e6e-4287-b52d-2c2fb61633c2/download/snowmap_2012_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20160309
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/ceae68a6-28f9-43f4-8ff5-9715588ade57/download/snowmap_20160309_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

en:
Resource Title: Snow depth map 20100416
    Size: 412324171 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/4ba96052-9e3e-4b7a-9968-2dcc58fc96c0/download/snowmap_2010_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth mapping in high-alpine catchments using digital photogrammetry
    Size: 8122296 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/3b711e29-cea1-48e8-8de6-a008850c4f94/download/snow-depth-mapping-in-high-alpine-catchments.pdf
    Description:

en:
Resource Title: Snow depth map 20160126
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/9229984f-b417-45e5-8dbe-031f295d0406/download/snowmap_20160126_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m
Because of very diffuse light conditions at time of image acquisition the quality of the resulting snow depth values are in some regions quite poor.

en:
Resource Title: Snow depth map 20130415
    Size: 412272526 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/da3ca703-c629-45c0-8dac-e78645b0fa5e/download/snowmap_2013_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20160420
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/bc035833-3193-4394-af92-f8d195d5e034/download/snowmap_20160420_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

aerial-imagery

display_name: aerial-imagery

avalanche

display_name: avalanche

dsm

display_name: dsm

image-matching

display_name: image-matching

snow-depth

display_name: snow-depth

snow-hydrology

display_name: snow-hydrology

snow-water-equivalent

display_name: snow-water-equivalent