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.

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

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

envi

de: Umwelt

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


$oid: OBSOLETE

en: The data results from a questionnaire survey conducted at 8 schools in the cantons Zurich, Aargau and St. Gallen. Respondents aged 13-22 years. The aim of the survey was to gain insight into teenagers' relationship to the forest, reasons for visiting or not visiting the forest and activities in the forest.

en: childhood adolescents forest teenagers recreational-activities

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

en: Factors influencing teenagers' forest visit frequency

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

en: Environment

fr: Environnement

it: Ambiente

de:
Resource Title: Survey at schools 2017
    Size: 638125 bytes
    Format: application/x-spss-sav
    URL: https://www.envidat.ch/dataset/04ecf3b8-76aa-4b45-af4e-e06da88a8fcd/resource/fe6746a6-96c4-484e-99c4-8f8556d76d86/download/datensatz-umfrage-schulen.sav
    Description: The dataset of the questionnaire survey at schools in SPSS-format.

de:
Resource Title: Dataset comments
    Size: 32680 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/04ecf3b8-76aa-4b45-af4e-e06da88a8fcd/resource/29308f48-7be2-4afb-9b4d-829c5618e50a/download/datensatz-kommentar.xlsx
    Description: The codebook to the dataset

format: XLS

de:
Resource Title: Dataset survey at schools
    Size: 844175 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/04ecf3b8-76aa-4b45-af4e-e06da88a8fcd/resource/9b9bee0b-a041-4870-b845-1115c5deed6d/download/datensatz-umfrage-schulen.xlsx
    Description: The dataset of the questionnaire survey at schools in excel format.

de:
Resource Title: Questionnaire school survey
    Size: 141278 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/04ecf3b8-76aa-4b45-af4e-e06da88a8fcd/resource/c7f5fdd3-361e-44bf-ba4c-fa97f6164bf0/download/fragebogenv2.pdf
    Description: The questionnaire used in the survey at 8 schools aimed at teenagers in German.

format: PDF

media_type: application/pdf

adolescents

display_name: adolescents

childhood

display_name: childhood

forest

display_name: forest

recreational-activities

display_name: recreational-activities

teenagers

display_name: teenagers


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.

en: cryosphere cordex downscaling rcm software toposcale

en: TopoCLIM v1.1 code

format: ZIP

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: L'objectif de ce livre blanc est de fournir aux décideurs, aux administrations et aux parties prenantes les résultats de recherche les plus récents afin de promouvoir l'utilisation optimale de la bioénergie issue des engrais de ferme dans la transition énergétique suisse. A cette fin, les résultats du centre de compétence suisse pour la recherche en bioénergie - SCCER BIOSWEET - sont résumés et présentés dans un contexte plus large. Si rien d'autre n'est mentionné, les résultats se réfèrent à la Suisse et, dans le cas de la matière première, aux potentiels nationaux de biomasse.

en: switzerland bioenergy biogas manure review

en: Production de biogaz à partir d’engrais de ferme en Suisse

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland


en: Ziel dieses Whitepapers ist es, Entscheidungsträgern, Verwaltungen und Stakeholdern die aktuellsten Forschungsergebnisse zur Verfügung zu stellen, um die optimale Nutzung von Bioenergie aus Hofdünger in der Schweizer Energiewende zu fördern. Zu diesem Zweck werden die Ergebnisse des Schweizer Kompetenzzentrums für Bioenergieforschung - SCCER BIOSWEET - zusammengefasst und in einem breiteren Kontext dargestellt. Wenn nichts anderes erwähnt wird, beziehen sich die Ergebnisse auf die Schweiz und im Falle der Ressourcen auf die heimischen Biomassepotenziale.

en: manure review switzerland bioenergy biogas

en: Biogas aus Hofdünger in der Schweiz


en: Aim of this white paper is to provide decision-makers, administrations and stakeholders with the most current research findings in order to promote the optimal use of bioenergy from manure in the Swiss energy transition. For this purpose, the results of the Swiss competence center for bioenergy research - SCCER BIOSWEET - are summarized and presented in a broader context. If nothing else is mentioned, the results refer to Switzerland and in case of the feedstock to the domestic biomass potentials.

en: Biogas from animal manure in Switzerland


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

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

de:
Resource Title: TPI300
    Size: 11941205 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3a51f451-aa57-4d4e-b4a8-a07786d7a18b/download/tpi300.tif
    Description: Topographic Index Position (TPI)

format: TIFF

media_type: image/tiff

de:
Resource Title: waste_inc_0010
    Size: 1528622 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/e50c4311-9521-4ec1-a177-cc9952a5cff3/download/waste_inc_0010.tif
    Description: Increase in waste collection service

de:
Resource Title: forest_gain_0515
    Size: 1359475 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/cc2499a2-e179-473d-ba04-ba7502d0e1ca/download/forest_gain_0515.tif
    Description: Native forest cover gains from 2005 to 2015

de:
Resource Title: pop_0010.
    Size: 2604307 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/21d0b38e-7066-4ac1-9c43-4c6fb732f337/download/pop_0010.tif
    Description: Population density per pixel (change per year)

de:
Resource Title: forest_persist_0515
    Size: 1675441 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/a7d6f906-ee5d-4d64-a713-754764577b8a/download/forest_persist_0515.tif
    Description: Native forest cover persistence from 2005 to 2015

de:
Resource Title: infill
    Size: 1337272 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/5b598ade-cb86-4f8b-aadc-c18e12814d15/download/infill.tif
    Description: New built-up pixels classified as infill

de:
Resource Title: ndvi_inc
    Size: 1552732 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3f14dfcc-668a-4321-9719-f0b58737deda/download/ndvi_inc.tif
    Description: Increase in Normalized Difference Vegetation Index

de:
Resource Title: house_inc_0010
    Size: 1559472 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/309672b6-4fa2-411c-999a-5b119c72fbef/download/house_inc_0010.tif
    Description: Permanent housing density increase

de:
Resource Title: EEZ_2005
    Size: 755680 bytes
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    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/df399923-2f14-45df-bc12-707385ea2fe7/download/eez_2005.7z
    Description: Ecological-Economic Zoning (EEZ)

de:
Resource Title: water_inc_0010
    Size: 1464652 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/5f52216a-8f44-472b-b70d-6bb003968d1d/download/water_inc_0010.tif
    Description: Increase in clean water provision service

de:
Resource Title: Descricao dos dados em portiuguês
    Size: 93276 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3142ea4a-a5cf-41e9-b04e-3eea956e32af/download/tabela.pdf
    Description: Portugues description

de:
Resource Title: master_plan_Ilhabela
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    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/b3f65b7e-8f44-4cb1-8f3b-21e45da6ecd4/download/master_plan_ilhabela.7z
    Description: Master plan Ihabela (zones)

de:
Resource Title: Variables description
    Size: 89561 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/8a4afdc9-9af4-4922-8856-6c0e67a1bcca/download/table.pdf
    Description: Table of content. Variables description, source, and other important information

de:
Resource Title: sanit_inc_0010
    Size: 1424839 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/a9a2d0d1-2de5-4a14-9b82-eb22e9dd2a8f/download/sanit_inc_0010.tif
    Description: Increase in sanitation service

de:
Resource Title: hdi_0010
    Size: 1672974 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/4e9794cf-e518-4b03-abe9-8c797b3a0562/download/hdi_0010.tif
    Description: Human Development Index (HDI) per municipality (change per year)

de:
Resource Title: master_plan_Ubatuba
    Size: 458342 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3c1e0ad8-fb01-447a-b325-a9574bdaeb06/download/master_plan_ubatuba.7z
    Description: Master plan Ubatuba (zones)

de:
Resource Title: income_0010
    Size: 2453471 bytes
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    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/d4800254-34c8-4699-ad14-78a32d90a8e8/download/income_0010.tif
    Description: Mean income in Reais (R$) per census sector (change per year)

de:
Resource Title: Axial
    Size: 1360715 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/7dc6ab63-6a3b-4744-8b8e-b899427e95a5/download/axial.tif
    Description: New built-up pixels classified as axial

de:
Resource Title: urban_persistence
    Size: 1412319 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/09b0444f-8dbd-4a8a-b5ac-26ba6d463401/download/urban_persistence.tif
    Description: Urban persistence: Built-up 2005 = Built-up 2015

de:
Resource Title: slope
    Size: 10630454 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3ad576ef-181c-485a-b794-53381eed55d5/download/slope.tif
    Description: Slope °

de:
Resource Title: alfa_0010
    Size: 2405447 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/b0604e68-15bf-4c85-a4ca-9bfe519fd03a/download/alfa_0010.tif
    Description: Basic education in % per census sector (change per
year)

de:
Resource Title: isolated
    Size: 1365075 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/08978ae8-8980-446a-af9b-28b6e18b8dcb/download/isolated.tif
    Description: New built-up pixels classified as isolated

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


en:
This dataset includes the parallel application and the main results supporting the research article "Modeling snow saltation: the effect of grain size and interparticle cohesion" published at the Journal of Geophysical Research: Atmospheres.
The code is a flow solver based on the Large Eddy Simulation (LES) technique coupled with a Lagrangian Stochastic Model (LSM). The interaction of snow particles with the bed is modeled with statistical and physically-based models for aerodynamic entrainment, rebound and splash, following the works of Groot Zwaaftink et al. (2014), Comola and Lehning (2017) and Sharma et al. (2018). This algorithm was also used by Sigmund et al. (2021) to model snow sublimation.

en: snow-cohesion saltation large-eddy-simulations mixed-grain-transport 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.

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.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

de: EnviDat

envi

de: Umwelt

de:
Resource Title: Data in Figures
    Size: 312666 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c4543b3d-d898-4364-8194-bb56f2fe41f9/resource/9824aead-cf4d-4499-ac43-d392daca5417/download/figures_data.zip
    Description: Simulation results presented in Figures 1 to 11 of the research article "Modeling snow saltattion: the effect of grain size and interparticle cohesion" in csv format.

media_type: application/zip

de:
Resource Title: LES-LSM code
    Size: 405936 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/c4543b3d-d898-4364-8194-bb56f2fe41f9/resource/aa04cdac-a8cc-446d-84ef-b9f69b767d83/download/les-lsm.tar.xz
    Description: Source code used to perform the analysis presented at the research article "Modeling snow saltation: the effect of grain size and interparticle cohesion". The source code is also available at the WSL/SLF GitLab Repository (https://gitlabext.wsl.ch/atmospheric-models/les-lsm).

drifting-snow

display_name: drifting-snow

large-eddy-simulations

display_name: large-eddy-simulations

mixed-grain-transport

display_name: mixed-grain-transport

saltation

display_name: saltation

snow-cohesion

display_name: snow-cohesion


en: Animal biodiversity in cities is generally expected to be uniformly reduced, but recent studies show that this is modulated by the composition and configuration of Urban Green Areas (UGAs). UGAs represent a heterogeneous network of vegetated spaces in urban settings that have repeatedly shown to support a significant part of native diurnal animal biodiversity. However, nocturnal taxa have so far been understudied, constraining our understanding of the role of UGAs on maintaining ecological connectivity and enhancing overall biodiversity. We present a well-replicated multi-city study on the factors driving bat and nocturnal insect biodiversity in three European cities. To achieve this, we sampled bats with ultrasound recorders and flying insects with light traps during the summer of 2018. Results showed a greater abundance and diversity of bats and nocturnal insects in the city of Zurich, followed by Antwerp and Paris. We identified artificial lighting in the UGA to lower bat diversity by probably filtering out light-sensitive species. We also found a negative correlation between both bat activity and diversity and insect abundance, suggesting a top-down control. An in-depth analysis of the Zurich data revealed divergent responses of the nocturnal fauna to landscape variables, while pointing out a bottom-up control of insect diversity on bats. Thus, to effectively preserve biodiversity in urban environments, UGAs management decisions should take into account the combined ecological needs of bats and nocturnal insects and consider the specific spatial topology of UGAs in each city.

en: zurich nocturnal-fauna paris urban-biodiversity urbanisation antwerp flying-arthropods chiroptera

en: Bats and nocturnal insects in urban green areas

envi

en: Environment

de:
Resource Title: Bats Insects Sites dataset
    Size: 207680 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/607ea77c-e95c-44c0-9b8e-c17c07a3d5e2/resource/49adcde7-5754-44ba-a207-5fbe7997b433/download/batsinsectssites_dataset.txt
    Description: Tab-delimited data file containing data analysed. First row is column header. Column headers are described in tab-delimited file 'Variable_description.txt"

format: TXT

media_type: text/plain

de:
Resource Title: BIOVEINS raw bat data.csv
    Size: 65886395 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/607ea77c-e95c-44c0-9b8e-c17c07a3d5e2/resource/0739a2ad-9dba-4fd9-aa5d-906234917ec0/download/bioveins-raw-bat-data.csv
    Description: Raw bat identification data from which the analysis data were derived

format: CSV

media_type: text/csv

de:
Resource Title: Variable description
    Size: 6797 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/607ea77c-e95c-44c0-9b8e-c17c07a3d5e2/resource/043c4cd9-2e09-4f5a-bcc6-65dd8cdbee02/download/variable_description.txt
    Description: Tab-delimited file containing names and description of data contained in the tab-delimited data file 'BatsInsectsSites_Date.txt'.

de:
Resource Title: BIOVEINS raw bat explanatory data.csv
    Size: 1146 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/607ea77c-e95c-44c0-9b8e-c17c07a3d5e2/resource/94de18a6-f835-42fd-ab2c-218c050a5f7a/download/bioveins-raw-bat-explanatory-data.csv
    Description: Explanation for column headers in file 'BIOVEINS raw bat data.csv'

antwerp

display_name: antwerp

chiroptera

display_name: chiroptera

flying-arthropods

display_name: flying-arthropods

nocturnal-fauna

display_name: nocturnal-fauna

paris

display_name: paris

urban-biodiversity

display_name: urban-biodiversity

urbanisation

display_name: urbanisation

zurich

display_name: zurich


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.

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

de:
Resource Title: Interview guide and transcripts (CONCUR Aim 2 on Governance)
    Size: 8562463 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7525a7f3-0c4a-4755-905f-2c6ccb4db2bd/resource/ff5af77b-e68b-474e-a303-10a3f69bb6cd/download/interview_transcripts_concur_wsl_aim2.pdf
    Description: 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).

de:
Resource Title: Guiding document for the interview transcripts (Metadata of the written transcripts)
    Size: 188059 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7525a7f3-0c4a-4755-905f-2c6ccb4db2bd/resource/ab58cbfa-6c08-4b56-b1d0-4d1d9c1d0c77/download/guiding_document.pdf
    Description: This is a guiding document supporting the dataset Interview guide and transcripts (CONCUR Aim 2 on Governance).

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


en:
For the release of a slab avalanche, crack propagation within a weak snowpack layer below a cohesive snow slab is required. As crack speed measurements can give insight into the underlying processes, we analysed three crack propagation events that occurred in similar snowpacks and covered all scales relevant for avalanche release. For the largest scale, up to 400 m, we estimated crack speed from an avalanche movie, for scales between 5 and 25 meters, we used accelerometers placed on the snow surface, and for scales below 5 meters, we performed a Propagation Saw Test. The mean crack speeds ranged from 36 ± 6 to 49 ± 5 m s^{-1}, and did not exhibit scale dependence. Using the Discrete Element Method and the Material Point Method, we reproduced the measured crack speeds reasonably well, in particular the terminal crack speed observed at smaller scales.
This dataset includes raw data as well as crack speed estimates from the three crack propagation events.
Where possible, we reproduced these field experiments with numerical models based on Discrete Element Method (DEM, Bobillier and others, 2020 and 2021) and Material Point Method (MPM. Gaume and others, 2018 and Trottet and others, 2021). The input parameters of the models were estimated from the corresponding snow profiles conducted at each test site.
 The raw data include:
* Propagation Saw Test movie with mechanical fields derived from Digital image Correlation analysis of the recording
* Acceleration data recorded with wireless time synchronized accelerometers placed on the snow surface during crack propagation in a whumpf.
*Video of an artificially triggered avalanche with widespread crack propagation. The video was used to georeference surface cracks in order to estimate crack propagation time and distance, providing crack propagation speed estimates.
* Snow profile recorded at each test site
 Experimental crack speed estimates include:
* Crack speed evolution within the first meters derived from the Propagation Saw Test.
* Crack speeds estimated from the time delay of the collapse, observed between different accelerometers during crack propagation of a whumpf.
* Crack speed estimates from video analysis of the artificially triggered avalanche.
 Reproduced crack speeds using the DEM an MPM model:
* Modelled Propagation Saw Test using MPM (2D and 3D system) and DEM.
* Modelled whumpf using MPM (beam and areal configuration)
* Modelled avalanche using MPM (beam and areal configuration)
Beside the movies (mp4 format), all data is either provided as netCDF files or excel sheets (see readme file), depending on the amount of data. A detailed description of the three crack propagation events and how crack speed was derived, can be found in the related publication:
 References for applied models:
Bobillier, G., B. Bergfeld, A. Capelli, J. Dual, J. Gaume, A. van Herwijnen and J. Schweizer 2020. Micromechanical modeling of snow failure. The Cryosphere, 14(1): 39-49.
Bobillier, G., B. Bergfeld, J. Dual, J. Gaume, A. van Herwijnen and J. Schweizer 2021. Micro-mechanical insights into the dynamics of crack propagation in snow fracture experiments. Scientific Reports, 11: 11711.
Gaume, J., T. Gast, J. Teran, A. van Herwijnen and C. Jiang 2018. Dynamic anticrack propagation in snow. Nature Communications, 9(1): 3047.
Trottet, B., R. Simenhois, G. Bobillier, A. van Herwijnen, C. Jiang and J. Gaume 2021. From sub-Rayleigh to intersonic crack propagation in snow slab avalanche release. EGU General Assembly 2021, Online, 19-30 Apr 2021, EGU21-8253.

en: crack-speed propagation-saw-test slab-avalanche snow whumpf dynamic-crack-propagation weak-layer

en: Crack propagation speeds in weak snowpack layers from three events: PST, whumpf and slab avalanche

de:
Resource Title: Readme
    Size: 2507 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/ad08d108-113f-4236-b141-a16edc3e4e1c/resource/a900aa3c-ab2b-4d31-bf35-d45906ebf869/download/readme.txt
    Description: Information how to interpret the data in "crack propagation speeds.zip".

de:
Resource Title: crack propagation speeds
    Size: 200147125 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ad08d108-113f-4236-b141-a16edc3e4e1c/resource/cbe26adb-d263-488d-beb3-e98eabd6c95d/download/data.zip
    Description: Please find the readme file.

crack-speed

display_name: crack-speed

dynamic-crack-propagation

display_name: dynamic-crack-propagation

propagation-saw-test

display_name: propagation-saw-test

slab-avalanche

display_name: slab-avalanche

snow

display_name: snow

weak-layer

display_name: weak-layer

whumpf

display_name: whumpf


pollination-experiment-insect-traits

en: Understanding the interplay of local and landscape-scale drivers of plant-pollinator interactions is crucial to maintaining pollination services in urban environments. The data contains plant-pollinator interactions changed across two independent gradients of local flowering plant species richness and landscape-scale urbanisation level (proportional area of impervious surface within a 500-m radius) in 24 home gardens in the city of Zurich, Switzerland. The data also contains the trait values (tongue length, body size and activity time) of all visiting wild- and honeybees.

en: urban-ecology plant-pollinator-interactions bees gardens zurich urbanization hoverflies insects phytometer biodiversity seed-production

en: Pollination experiment: insect traits

title_for_slug: pollination-experiment-insect-traits

bees

display_name: bees

biodiversity

display_name: biodiversity

gardens

display_name: gardens

hoverflies

display_name: hoverflies

insects

display_name: insects

phytometer

display_name: phytometer

plant-pollinator-interactions

display_name: plant-pollinator-interactions

seed-production

display_name: seed-production

urban-ecology

display_name: urban-ecology

urbanization

display_name: urbanization


en:
This dataset contain measurements of solute and stable water isotopes in stream water and precipitation in the Alp catchment and two of its tributaries (between 2015 -2018) . The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.  The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (precipitation rates, discharge) at daily intervals from several sampling locations.
An updated version of the isotope dataset is available here: https://www.doi.org/10.16904/envidat.242

en: spatially-distributed-sampling precipitation geochemical-solutes stable-water-isotopes stream-water

en: Daily data of solute and stable water isotopes in stream water and precipitation in the Alp catchment, Central Switzerland

de:
Resource Title: Daily-solute-and-isotope-database_Version_2
    Size: 3017011 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/53f4e1d8-506e-403d-b874-e294c6e8b2eb/resource/2a929c69-5e6e-4c10-a284-08798e5354f7/download/envidat-daily.isotope.solute.database.alptal-ch-18.07.2019_level02.xlsx
    Description: The dataset contains daily measurements of volumes, isotopes and solutes of stream water as well as precipitation measured several locations; meteorological variables are added. Date: 18.07.2019

de:
Resource Title: Daily-solute-and-isotope-database_Version1
    Size: 3080831 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/53f4e1d8-506e-403d-b874-e294c6e8b2eb/resource/7ae45f32-4411-4ad9-ac84-fd8f28dfc933/download/01.daily.isotope.solute.database.alptal-ch-13.05.2019_envidat.xlsx
    Description: The dataset contains daily measurements of volumes, isotopes and solutes of stream water as well as precipitation measured several locations; meteorological variables are added.

geochemical-solutes

display_name: geochemical-solutes

precipitation

display_name: precipitation

spatially-distributed-sampling

display_name: spatially-distributed-sampling

stable-water-isotopes

display_name: stable-water-isotopes

stream-water

display_name: stream-water


en:
This data contain volumes, solutes and isotopes of snowpack outflow measured by a snowmelt lysimeter system at three locations in the southern Alp catchment, situated Central Switzerland.  The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.
The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (snowpack outflow volumes) at daily intervals from several sampling locations. Additionally, the data measured by the snowmelt lysimeter system are provided in 10-minute resolution.

en: snowmelt-rate stable-water-isotopes solutes snowpack-outflow snowmelt-lysimeter

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: Daily data of the volumes, solutes and isotopes in snowpack outflow measured at three locations in the southern Alp catchment

de:
Resource Title: Daily-Snowmelt.Lysimeter-solute-and-isotope-database_Version1
    Size: 3017002 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/d234a921-9000-4ffc-b723-a663d390b9f8/resource/db3801e0-1b14-4290-ab6a-3f1148e9e0ed/download/envidat-daily.isotope.solute.database.alptal-ch-18.07.2019_level02.xlsx
    Description: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution.  10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

de:
Resource Title: Daily-Snowmelt.Lysimeter-solute-and-isotope-database_Version2
    Size: 42211381 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/d234a921-9000-4ffc-b723-a663d390b9f8/resource/cb7620a7-6854-4dd9-b11d-290395d64f4b/download/lysimeterdatabase.alptal-ch_27062019_level02.xlsx
    Description: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution.  10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes


en:
This dataset includes snow depth, canopy height and terrain elevation maps of forest stands in the Grisons (CH) and at Grand Mesa (CO,USA) derived from airborne lidar. Data were acquired i) within a pilot mission of NASA's Airborne Snow Observatory in the Swiss Alps in March 2017 and ii) during NASA’s SnowEx campaign at Grand Mesa in February 2017. Snow depth maps are available for two dates separated by approx.1 week, and include an area of ca. 0.5km2 for each of the three sites Davos, Engadine and Grand Mesa.
All data were presented and analyzed in the publication 'Revisiting Snow Cover Variability and Canopy Structure within Forest Stands: Insights from Airborne Lidar Data' (Mazzotti et al., 2019, WRR, doi: 10.1029/2019WR024898). This publication must be cited when using this dataset.
Paper Citation:
 - _Giulia Mazzotti; William Ryan Currier; Jeffrey S. Deems; Justin M. Pflug; Jessica D. Lundquist; Tobias Jonas (2019). Revisiting Snow Cover Variability and Canopy Structure Within Forest Stands: Insights From Airborne Lidar Data. Water Resources Research, 55, 6198– 6216,  [doi: 10.1029/2019WR024898](https://doi.org/10.1029/2019WR024898)._

en: snow-distribution forest-structure snow-depth airborne-laser-scanning canopy-height

envidat

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.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

en: ALS-based snow depth and canopy height maps from flights in 2017 (Grisons, CH and Grand Mesa, CO)

de:
Resource Title: Canopy height maps
    Size: 4159760 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/98ab851f-7d0e-4c96-9eea-79db59cd83a2/resource/3451cb50-b6af-4df6-8b73-aeda7eb01215/download/canopy-height.zip
    Description: Canopy height maps of each of the three field areas Davos, Engadine and Grand Mesa

de:
Resource Title: Snow depth maps
    Size: 3113408 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/98ab851f-7d0e-4c96-9eea-79db59cd83a2/resource/e41d41ca-810c-4ec6-87ef-6daa709f8316/download/snow-depth.zip
    Description: Snow depth maps from two snow-on flights at each of the three field areas Davos (March 20th and 31st 2017), Engadien (March 20th and 31st, 2017) and Grand Mesa (February 8th and 16th, 2017)

de:
Resource Title: Readme
    Size: 997 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/98ab851f-7d0e-4c96-9eea-79db59cd83a2/resource/a8109354-2581-4863-bcf5-301f3dc361a8/download/readme.txt
    Description:

de:
Resource Title: Terrain elevation maps
    Size: 2545725 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/98ab851f-7d0e-4c96-9eea-79db59cd83a2/resource/9c82946c-09f9-4815-974d-31828e45f439/download/terrain-elevation.zip
    Description: Digital elevation model computed from snow-off flights for each of the field areas Davos, Engadine and Grand Mesa

airborne-laser-scanning

display_name: airborne-laser-scanning

canopy-height

display_name: canopy-height

forest-structure

display_name: forest-structure

snow-depth

display_name: snow-depth

snow-distribution

display_name: snow-distribution


en:
This dataset contains forest canopy structure data acquired in a spruce forest at Laret, Switzerland, and a pine forest at Sodankylä, Finland. Data include:
* Hemispherical photographs taken at transect intersection points of 13 experimental plots (40x40m each)
* a Canopy Height Model (tree height map) derived by rasterizing airborne LiDAR data, encompassing the entire simulation domain at Laret (150'000 m2)
These data provide the necessary basis for creating canopy structure datasets to be used as input to the forest snow snow model FSM2. These datasets, the model input derivatives and the radiation and snow modelling are described in detail in the following publication:
_Mazzotti, G., Webster, C., Essery, R., and Jonas, T. (2021) Improving the physical representation of forest snow processes in coarse-resolution models: lessons learned from upscaling hyper-resolution simulations. Water Resources Research 57, e2020WR029064. [doi: 10.1029/2020WR029064](https://doi.org/10.1029/2020WR029064)_
This publication must be cited when using the data.
 See also:
For additional information on the FSM2 model, see the corresponding [GitHub repository](https://github.com/GiuliaMazzotti/FSM2/tree/hyres_enhanced_canopy)
The datasets and the model have also been used in _Mazzotti et al. (2020) Process-level evaluation of a hyper-resolution forest snow model using distributed multi-sensor observations. [doi: 10.1029/2020WR027572](https://doi.org/10.1029/2020WR027572)

en: upscaling energy-balance forest-canopy mass-balance snow-modelling

de: EnviDat

en: Forest canopy structure data for radiation and snow modelling (CH/FIN)

envi

de: Umwelt

en: Environment

de:
Resource Title: Hemispherical Photographs
    Size: 935848934 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/5d071a02-e48e-4719-bce4-2e662d452dfe/download/hemisphericalphotos.zip
    Description: Hemispherical images at the intersection points of the experimental plots at Laret (CH) and Sodankylä (FIN)

de:
Resource Title: Canopy height model
    Size: 2759360 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/1b4aaf5f-545f-4afc-a045-73ccd4885747/download/chm_cropped.asc
    Description: Canopy height model of the lidar domain at Laret

energy-balance

display_name: energy-balance

forest-canopy

display_name: forest-canopy

mass-balance

display_name: mass-balance

snow-modelling

display_name: snow-modelling

upscaling

display_name: upscaling


en:
Table of Content: 1. General context of the data set "LUSzoning”; 2. Background and aims of the study using the data set LUSzoning; 3. The data set LUSzoning.
1. General context of the data set "LUSzoning".
The data set "LUSzoning" stands for Land-use simulations integrating zoning regulations in Spanish functional urban areas. The data set has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2021. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, digital zoning plans) into quantitative land-change modelling approaches at the urban regional level.
2.	Background and aims of the study using the data set “LUSzoning”.
As part of the CONCUR project, a specific task was to integrate planning spatial policies in land-change modelling. Planning can be implemented in modelling using either hard or gradual restrictions. Different studies have addressed the inclusion of spatial planning policies in land-use change modelling. However, the integration of zoning constraints is generally established as hard or Boolean-based restrictions (e.g., whether urban development is allowed or not), while not accounting for the spatial heterogeneity or gradual characteristics within planning zones (e.g., whether planning regulations allow low, medium or high urban density), though these could improve real patterns simulations in urban areas. We assume Spanish General Zoning plans were suitable to explore the integration of planning into land-change modelling as soft constrains because they define land-use intensities in the buildable zoning areas. In light of the above considerations, the overall aim of the study was to model urban land-use changes using a multi-scenario approach that integrates digitized zoning plans for the Functional Urban Areas (FUAs) of Madrid, Barcelona, Valencia, and Zaragoza. The following specific objectives were addressed: i) to analyse the role of planning by defining three future scenarios that integrate digitized zoning plans and one scenario that assumes almost no planning intervention; ii) to introduce zoning constraints that reflect different degrees of urban densities; iii) to generate a transferable spatially-explicit modelling framework to integrate planning into land-use change simulations.
Four future land-use demands scenarios were defined for the FUAs. Storylines were created considering probable development scenarios related to zoning plans, current Spanish legislation and sustainability goals defined along two axes: a high market-oriented vs. high planning-intervention axis, and an axis of short-term economic growth vs. long-term sustainable growth. The sustainable development scenario (S1) is characterized by low gross floor area (GFA) growth that is limited to areas that are currently under development according to zoning plans. The business-as-usual scenario (S2) is characterized by medium GFA growth in the range of on-going trends. The strong development scenario (S3) is characterized by high GFA growth rates. Growth is restricted to buildable areas without urbanization project designated in zoning plans. The unrestricted development scenario (S4) prioritizes a high degree of market liberalization characterized by high GFA growth that surpasses population demands. S4 follows a rapid economic growth pattern with almost no planning intervention.
3.	 The data set “LUSzoning”.
The dataset includes 16 .asc raster layers providing the simulated land-uses under four defined scenarios for Barcelona, Madrid, Valencia and Zaragoza Functional Urban Areas (FUAs) for 2030. The simulated raster layers were created using CLUMondo simulation framework and have a spatial resolution of 30m. The .asc layers name include the name of the FUA and scenario number. For example, the output from simulating the urban growth for the city of Zaragoza under Scenario 2 is named “Zaragoza_S2.tif”. Furthermore, a .txt file named “Legend.txt” includes the numeric value of the land-use and the category of land-use that represents to interpret the .asc raster layers. The name of the land-use classes is a reclassification of the Urban Atlas 2012 land-use classes within the four Spanish FUAs analyzed.

en: spatial-planning land-use-transformations land-use-change land-use-simulations digital-zoning-plans

en: LUSzoning: Land-use simulations integrating zoning regulations in Spanish functional urban areas

de:
Resource Title: Valencia_S1
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    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/b0e6fefc-b2ca-48ee-bbaf-a478e4f027ee/download/valencia_s1.asc
    Description:

format: pgp-keys

de:
Resource Title: Valencia_S4
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    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/ad431d08-3481-4b61-9d4c-a7b75e6c04e9/download/valencia_s4.asc
    Description:

de:
Resource Title: Zaragoza_S3
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    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/46cd42ea-2ea9-4881-9056-0c80433cdced/download/zaragoza_s3.asc
    Description:

de:
Resource Title: Madrid_S1
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    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/bc4b8ca6-76a2-43b0-9a5b-4c43394b3fda/download/madrid_s1.asc
    Description:

de:
Resource Title: Zaragoza_S4
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    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/c5dc051d-16e0-49cc-99cb-3bc105aaa390/download/zaragoza_s4.asc
    Description:

de:
Resource Title: Zaragoza_S1
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    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/bf187ffd-59a7-4018-b7f8-d843cd03737e/download/zaragoza_s1.asc
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de:
Resource Title: Zaragoza_S2
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    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/7b5ad8ca-1f63-4492-89ad-d8e902c4b102/download/zaragoza_s2.asc
    Description:

de:
Resource Title: Barcelona_S4
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    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/0da0d9eb-d2a7-41b0-a050-1a34770fc7e1/download/barcelona_s4.asc
    Description:

de:
Resource Title: Valencia_S3
    Size: 6757947 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/94d52c98-ae61-4a1d-8b51-75d8b2994a04/download/valencia_s3.asc
    Description:

de:
Resource Title: Madrid_S2
    Size: 25343034 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/5d6fb94e-2557-4428-aae5-30aebd2048a1/download/madrid_s2.asc
    Description:

de:
Resource Title: Barcelona_S1
    Size: 51075742 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/2a6f3cb5-a88e-4abe-865a-12a6fa2bd838/download/barcelona_s1.asc
    Description:

de:
Resource Title: Valencia_S2
    Size: 6759489 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/af2a0484-7e5e-4cc3-963c-c14ef137131a/download/valencia_s2.asc
    Description:

de:
Resource Title: Madrid_S3
    Size: 25291019 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/dfb0ce17-3c3c-4c40-a406-5fbbd69d7859/download/madrid_s3.asc
    Description:

de:
Resource Title: Barcelona_S3
    Size: 51044440 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/78f91bc4-cec9-4e30-9db9-a1c2cb4ba546/download/barcelona_s3.asc
    Description:

de:
Resource Title: Madrid_S4
    Size: 25185335 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/21a40989-9a12-403a-9dff-15d37a59caf6/download/madrid_s4.asc
    Description:

de:
Resource Title: Barcelona_S2
    Size: 51045666 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/a555ffc0-0266-4987-b70e-e7fddb0abdf2/download/barcelona_s2.asc
    Description:

de:
Resource Title: Legend simulated maps
    Size: 906 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/927372ee-e8b2-4f36-abc3-7367b112b4fb/download/legend.txt
    Description:

digital-zoning-plans

display_name: digital-zoning-plans

land-use-change

display_name: land-use-change

land-use-simulations

display_name: land-use-simulations

land-use-transformations

display_name: land-use-transformations

spatial-planning

display_name: spatial-planning


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

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

envidat

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.

de: EnviDat: das Umwelt-Datenportal

de: EnviDat

en: High resolution static data for WRF over Switzerland

envi

de: Umwelt

de:
Resource Title: soiltype_bot_1s
    Size: 403644 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d3db35e-eb6b-4e7f-a88e-733c363133c9/resource/c63e5b14-d5b7-45f5-ba0d-57bc72394e0e/download/soiltype_bot_1s.zip
    Description: Static data for WRF - Soiltype bottom

de:
Resource Title: topo_1s
    Size: 458474836 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d3db35e-eb6b-4e7f-a88e-733c363133c9/resource/ab9f6e89-9101-4250-bb4c-b8e5e8e2363f/download/topo_1s.zip
    Description: Static data for WRF - Topography

de:
Resource Title: landuse_1s
    Size: 21215915 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d3db35e-eb6b-4e7f-a88e-733c363133c9/resource/e3ef8012-d73d-4ad4-b51e-b327f5a6bcf9/download/landuse_1s.zip
    Description: Static data for WRF - Landuse

de:
Resource Title: soiltype_top_1s
    Size: 403644 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d3db35e-eb6b-4e7f-a88e-733c363133c9/resource/33bc67ca-6ee6-440e-985b-46ce84e724b0/download/soiltype_top_1s.zip
    Description: Static data for WRF - Soiltype top

de:
Resource Title: namelist.wps
    Size: 1411 bytes
    Format: application/vnd.ms-works
    URL: https://www.envidat.ch/dataset/9d3db35e-eb6b-4e7f-a88e-733c363133c9/resource/2b73cbec-bfba-4788-bfd8-5cf6dae371dd/download/namelist.wps
    Description: Example namelist.wps to use with the 1s static data

de:
Resource Title: GEOGRID.TBL-aster-121-1
    Size: 15835 bytes
    Format: No Info
    URL: https://www.envidat.ch/dataset/9d3db35e-eb6b-4e7f-a88e-733c363133c9/resource/246daa44-7f9a-4666-9aba-e8dbc244c148/download/geogrid.tbl-aster-121_1
    Description: Example GEOGRID.TBL to use with the 1s static data;
Note about naming:
* 121 -> 1-2-1 topography smoothing applied to dataset
* 1 -> one smoothing cycle applied to the data (needs to be changed depending on the chosen resolution to avoid too steep slope angles)

de:
Resource Title: Documentation
    Size: 166718 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/9d3db35e-eb6b-4e7f-a88e-733c363133c9/resource/793e2a23-a8a5-4bbc-8497-d00eb2b9f28a/download/documentation-wrf_static_data_for_alps.pdf
    Description: Documentation of the dataset

cosmo-wrf

display_name: cosmo-wrf

cryowrf

display_name: cryowrf

landuse

display_name: landuse

static-data

display_name: static-data

topography

display_name: topography

wrf

display_name: wrf


en:
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 iap fraxinus ash-dieback forest

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

ash-dieback

display_name: ash-dieback

forest

display_name: forest

fraxinus

display_name: fraxinus

iap

display_name: iap

monitoring

display_name: monitoring


en:
This poster was originally created for the swissuniversities Open Science Action Plan: Kick-Off Forum, and showed to the audience on 17.10.2019. It illustrates how the environmental data portal EnviDat provides the tools for fostering Open Science and Reproducibility of scientific research at WSL.
Supporting open science is a highly relevant user requirement for EnviDat and for implementing FAIR (Findability, Accessibility, Interoperability and Reusability) principles at dataset level.
EnviDat encourages WSL scientists to complement data publication with a complete description of research methods and the inclusion of the open source software, code or scripts used for processing the dataset or for obtaining the published results. By openly publishing open software (e.g. as Jupyter notebooks) alongside research data sets, researchers can contribute to mitigate reproducibility issues.
EnviDat also promotes and supports, where possible and practical, the publication of software as Jupyter notebooks. Jupyter notebooks provide a solution for improved documentation and interactive execution of open code in a wide range of programming languages (Python, R, Octave/Matlab, Java or Scala). These programming languages are widely used in environmental research at WSL and well supported by the Jupyter-compatible kernels. We have sucessfully interfaced EnviDat-hosted notebooks with the WSL High-Performance Computing (HPC) Linux Cluster through a JupyterHub/JuypterLab beta installation on the HPC cluster implemented in close collaboration with the WSL IT-Services.
For existing software that cannot be easily migrated to Jupyter Notebooks, the Open Science and Reproducibility is assisted by containerisation. We have proven that several Singularity containers can successfully run on WSL's HPC cluster.
Finally, the researchers can upload the data/results complemented by code (e.g. as Jupyter Notebooks, or Singularity containers) and any additional documentation in EnviDat. Consequently, they will receive a DOI for the entire dataset, which they can reference in their science paper in order to publish a more reproducible research.
_License_: This poster is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse this poster in any way you want, for any purposes and without restrictions.

en: reproducibility research-data-management hpc open-science jupyter-notebooks open-data open-source

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: Open Science Support at the Swiss Federal Research Institute WSL. The EnviDat Concept

hpc

display_name: hpc

jupyter-notebooks

display_name: jupyter-notebooks

open-data

display_name: open-data

open-science

display_name: open-science

open-source

display_name: open-source

reproducibility

display_name: reproducibility

research-data-management

display_name: research-data-management


en: We developed a map of cropland and grassland allocation for Switzerland based on several indices dominantly derived from Sentinel-2 satellite imagery captured over multiple growing seasons. The classification model was trained based on parcel-based data derived from landholder reporting. The mapping was conducted on Google Earth Engine platform using random forest classifier. Areas of high vegetation, shrubland,  sealed surface and non-vegetated areas were masked out from the country-wide map. The resulting map has high accuracy in lowlands as well as mountainous areas.

en: vegetation-indices machine-learning grassland phenology habitat switzerland sentinel-2 agriculture remote-sensing cropland

envidat

en: EnviDat: the Environmental Data Portal

en: Cropland and grassland map of Switzerland based on Sentinel-2 data

de:
Resource Title: (current version) Cropland, grassland, and shrubland map of Switzerland (v.1.5)
    Size: 46196707 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/014565ae-748b-4f64-bf14-53443386cf56/download/ch_cropgrassshrubmap_v1_5.tif
    Description: (1) cropland; (2) grassland; (3) shrubland; other LC classes are masked out from the map

de:
Resource Title: Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.6  (v1.0)
    Size: 20469824 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/b358e0ad-50c8-45a8-b4fd-98ccf6d59532/download/comb_sen2maskbuiltup06.tif
    Description: !!! Please check out the newer version in the repository !!!
Mask of unsealed surfaces of Switzerland based on 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.6

de:
Resource Title: Cropland and grassland map of Switzerland  (v.1.0)
    Size: 773453532 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/0bb5fc4c-8331-4851-81fb-6c8b5f331207/download/ch_cropgrassmap_v2_4.tif
    Description: !!! Please check out the newer version in this repository !!! (1) cropland; (2) grassland; other LC classes are masked out from the map

de:
Resource Title: (current version) Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.6 (v1.5)
    Size: 21028763 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/b583e418-92c3-4e34-9f1b-de7f8823234c/download/comb_sen2maskbuiltup06.tif
    Description: Assuming that sealed surfaces have little or no phenological response we calculated a mask of unsealed surfaces based on the 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.6.

de:
Resource Title: (current version) Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.7 (v1.5)
    Size: 22951009 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/1433230e-25d2-40e4-b512-f9216f158c62/download/comb_sen2maskbuiltup07.tif
    Description: Assuming that sealed surfaces have little or no phenological response we calculated a mask of unsealed surfaces based on the 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.7.

de:
Resource Title: GEE (Google Earth Engine) script (JavaScript) to derived the output map  (v1.0)
    Size: 10103 bytes
    Format: text/javascript
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/5b8620ec-a059-4f05-a131-c559049e5a44/download/sentinel12_wholech_croplandgraslandshrubland_published_v1.js
    Description: !!! Please check out the newer version in the repository !!! The code used in Google Earth Engine to derive the cropland, grassland and shrubland map of Switzerland

format: javascript

de:
Resource Title: Mask of unsealed surfaces of Switzerland based on 3 years Sentinel-2 NDVI 95th percentile threshold value: 0.7 (v1.0)
    Size: 22351282 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/4643ef04-e299-4ed2-b03d-f16624ce2f29/download/comb_sen2maskbuiltup07.tif
    Description: !!! Please check out the newer version in this repository !!! Assuming that sealed surfaces have little or no phenological response we calculated a mask of unsealed surfaces based on the 3 years (2017-2019) Sentinel-2 NDVI 95th percentile threshold value: 0.7.

de:
Resource Title: GEE (Google Earth Engine) script (JavaScript) to derived the output map  (v1.5)
    Size: 12925 bytes
    Format: text/javascript
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/44ff8fb6-ac93-4278-a645-9a1e81d1ce2f/download/sentinel12_wholech_croplandgraslandshrubland_published_v2.js
    Description: The code used in Google Earth Engine to derive the cropland, grassland and shrubland map of Switzerland. Compare to the previous version the newer version includes the shadow masking procedure which might be important in the mountainous areas.

de:
Resource Title: Cropland, grassland, and shrubland map of Switzerland (v1.0)
    Size: 773453532 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/63a7c7f1-af24-49eb-a082-2f9244034b19/download/ch_cropgrassmap_v2_4_withshrubs.tif
    Description: !!! Please check out the newer version in this repository !!! (1) cropland; (2) grassland; (3) shrubland; other LC classes are masked out from the map

de:
Resource Title: (current version) Cropland and grassland map of Switzerland (v.1.5)
    Size: 36873826 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/00ff9ac3-c96b-4cb5-a300-b205ad9698cc/resource/05a74913-fbe7-477a-9d8a-d1e4f97c30c2/download/ch_cropgrassmap_v1_5.tif
    Description: (1) cropland; (2) grassland; other LC classes are masked out from the map

agriculture

display_name: agriculture

cropland

display_name: cropland

grassland

display_name: grassland

habitat

display_name: habitat

machine-learning

display_name: machine-learning

phenology

display_name: phenology

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

vegetation-indices

display_name: vegetation-indices


en: This dataset includes data from three vegetation surveys in a restored raised bog (Hagenmoos) in the lowland of the canton of Zürich (Switzerland). The bog Hagenmoos was restored by cutting shrubs and trees within the formerly peat-cutting pits and by blocking drainages. The vegetation surveys were carried out before (1989), ten years after (1999) and 30 years after restoration (2020). In each vegetation survey, all vascular plant and bryophyte species within 72 permanent plots were recorded. Of these plots, 34 are located within the formerly peat-cutting pits and 38 are located outside the peat pits. Based on presence-absence data of vascular plants and bryophytes, mean ecological indicator and strategy values based on Landolt et al. (2010) were calculated and are provided in the Excel sheet. Indicator values for light, moisture, pH, nutrients, humus, temperature and continentality and strategy values for stress, competition and ruderality were considered. Furthermore, species richness for the following groups were calculated: (1) all plant species, (2) all vascular plant species, (3) bog specialists among vascular plant species, (4) all bryophyte species, (5) bog specialists among bryophyte species. As bog specialist species, we considered all plant species listed as characteristic species of raised bogs by Feldmeyer-Christe and Küchler (2018: Moore der Schweiz. Haupt, Bern).

en: nature-conservation indicator-values raised-bog restoration vegetation peat switzerland sphagnum

envidat

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.

de: EnviDat: das Umwelt-Datenportal

de: EnviDat

en: Restoration of the lowland raised bog Hagenmoos (Switzerland): Data on vegetation, ecological indicator values and species richness from 1989 until 2020

envi

de: Umwelt

en: Environment

indicator-values

display_name: indicator-values

nature-conservation

display_name: nature-conservation

peat

display_name: peat

raised-bog

display_name: raised-bog

restoration

display_name: restoration

sphagnum

display_name: sphagnum

vegetation

display_name: vegetation


espon-digiplan

en: The dataset as a part of the international project ESPON Digiplan. The aim of this international project is to assess the extent, organisation and financing of digitisation of plan data as well as the use of these data in ESPON member countries. As a part of the in-depth case study, 7 virtual expert interviews in Switzerland and 5 virtual expert interviews in Germany were conducted with experts on the topic of digitisation of plan data. The documents contain the transcripts of the interviews. The transcripts aim to capture the content of the interviews, which is why voice raising and lowering, as well as pauses in the interview, were not specifically recorded. The interviews were conducted in German, therefore the transcripts are also in German.

en: transparency spatial-planning digitalisation geoportal innovation efficiency

en: ESPON Digiplan

title_for_slug: espon-digiplan

de:
Resource Title: Germany 2020 all transcripts Digiplan Task 2
    Size: 502404 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dc5060f4-2052-41a5-a7c5-227b611557dc/resource/c0f4a9ef-7d46-4fd9-9ce6-e5d3d08d54c2/download/de_alletranskripte.pdf
    Description: All transcripts are written in German.

de:
Resource Title: Metadata of the written transcripts
    Size: 132966 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dc5060f4-2052-41a5-a7c5-227b611557dc/resource/3c9de37e-179d-4748-b272-ff8726b8cfdc/download/metadaten-interviews.pdf
    Description: Additional information (position of expert, date of the interviews) on the transcripts can be found in this document.

de:
Resource Title: Switzerland 2020 all transcripts Digiplan Task 2
    Size: 535152 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dc5060f4-2052-41a5-a7c5-227b611557dc/resource/16bdbf18-f762-4fbb-989c-af523b9bd21b/download/ch_alletranskripte.pdf
    Description: All transcripts are written in German.

de:
Resource Title: Questionnaire Digiplan Task 2 CH_D
    Size: 274808 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/dc5060f4-2052-41a5-a7c5-227b611557dc/resource/bfeb6348-7031-431c-8422-3a04eba98f4c/download/fragebogen-task-2-ch_d.pdf
    Description: This document contains the questionnaire, which was used for the expert interviews in the context of Digiplan Task 2. The questionnaire was adapted to the context of the country or the to the context of the interviewee in some interviews. Therefore, some additional questions were asked or some questions were skipped.

digitalisation

display_name: digitalisation

efficiency

display_name: efficiency

geoportal

display_name: geoportal

innovation

display_name: innovation

spatial-planning

display_name: spatial-planning

transparency

display_name: transparency


en: Data from pulse-labelling experiment with 100-year old trees of a naturally dry pine forest exposed to a 15-year-long irrigation experiment. Canopies of 10 trees were labelled for 3 hours with 13CO2 and the fate of this label was traced for one year in stem and soil respiration and in microbial biomass around these trees. Data include (1) microclimatic data and soil respiration rates of the year following pulse labelling. (2) Temporal patterns of the 13C signal and 13C excess in soil respired CO2 and microbial biomass. (3) Spatial distribution of 13C signal in the soil.

en: rhizosphere forest pfynwald soil drought allocation microbial-biomass

en: Drought alters C footprint of trees in soil: tracking the spatio-temporal fate of 13C labelled assimilates in the soil

allocation

display_name: allocation

drought

display_name: drought

forest

display_name: forest

microbial-biomass

display_name: microbial-biomass

pfynwald

display_name: pfynwald

rhizosphere

display_name: rhizosphere

soil

display_name: soil


en: Groundwater time series between 2010 and 2014 of the distributed monitoring system in the Studibach (C7), Alptal, Switzerland. Data published in Rinderer M., van Meerveld I, McGlynn B. (2019): From points to patterns – Assessing runoff source area dynamics and hydrological connectivity using time series clustering. Water Resources Research, doi: 2018WR023886R

en: alptal groundwater switzerland studibach time-series

en: Groundwater time series Studibach (Rinderer et al., 2019, WRR)

alptal

display_name: alptal

groundwater

display_name: groundwater

studibach

display_name: studibach

switzerland

display_name: switzerland

time-series

display_name: time-series


wood-mobilization-survey

en:
Understanding the market behavior of forest owners and managers is important to identify effective and efficient policy instruments that enhance wood provisioning. We conducted a choice experiment (CE) at two study sites in south-eastern Germany (Upper Bavaria and Lower Franconia) and two in north-eastern Switzerland (Grisons and Aargau) to elicit foresters’ preferences for different supply channels, contract lengths, wood prices and duration of business relations.
CE belong to the stated preference methods to analyze individual decision making. Respondents had to choose among three options based on different attribute levels in 12 consecutive choice sets.
Our study site comparison identified regional differences and particularities, which should be taken into account when promoting wood mobilization. The success of policy instruments, such as the promotion of bundling organizations and long-term contracts, can vary depending on the specific structural and institutional conditions, like existing marketing channels, as well as on behavioral aspects of the particular public and private decision makers.

en: distribution-channels wood-harvest trading-preferences forest-owners forest-managers

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: Wood Mobilization Survey

title_for_slug: wood-mobilization-survey

de:
Resource Title: Survey in German
    Size: 243256 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/fa067e5c-349f-4d8e-b3ca-75587044a3d6/resource/7bdc54fa-2c34-4dac-b065-b6961a1deb79/download/survey_german.pdf
    Description:

de:
Resource Title: Survey in English
    Size: 235341 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/fa067e5c-349f-4d8e-b3ca-75587044a3d6/resource/4ff59cce-4b69-4cf2-b9b3-57a8c83c3960/download/survey_english.pdf
    Description:

de:
Resource Title: CE Lower Franconia
    Size: 34772 bytes
    Format: .dat
    URL: https://www.envidat.ch/dataset/fa067e5c-349f-4d8e-b3ca-75587044a3d6/resource/c6010822-2f54-4004-b2db-0af7391e27e5/download/ce_tum_-dat_uf_new.dat
    Description:

de:
Resource Title: CE CH
    Size: 83095 bytes
    Format: .dat
    URL: https://www.envidat.ch/dataset/fa067e5c-349f-4d8e-b3ca-75587044a3d6/resource/1c3a0311-8794-4e15-8e73-85ef0a9742c4/download/gr_ag_resp_first_final.dat
    Description:

de:
Resource Title: CE GER
    Size: 85880 bytes
    Format: .dat
    URL: https://www.envidat.ch/dataset/fa067e5c-349f-4d8e-b3ca-75587044a3d6/resource/edbdb72f-c881-4077-8c84-3a651103344a/download/ce_tum_-dat_obuf_new.dat
    Description:

de:
Resource Title: CE Grisons
    Size: 48781 bytes
    Format: .dat
    URL: https://www.envidat.ch/dataset/fa067e5c-349f-4d8e-b3ca-75587044a3d6/resource/f0b0333f-4f58-4be7-9809-78591431cbe7/download/gr_68resp_first_final.dat
    Description:

de:
Resource Title: CE Upper Bavaria
    Size: 51328 bytes
    Format: .dat
    URL: https://www.envidat.ch/dataset/fa067e5c-349f-4d8e-b3ca-75587044a3d6/resource/e9cee600-2ca9-460f-980b-0917e413541a/download/ce_tum_-dat_ob_new.dat
    Description:

de:
Resource Title: CE Aargau
    Size: 34534 bytes
    Format: .dat
    URL: https://www.envidat.ch/dataset/fa067e5c-349f-4d8e-b3ca-75587044a3d6/resource/b08670c9-4eac-45bd-9369-881d328b0a92/download/ag_48resp_first_final.dat
    Description:

distribution-channels

display_name: distribution-channels

forest-managers

display_name: forest-managers

forest-owners

display_name: forest-owners

trading-preferences

display_name: trading-preferences

wood-harvest

display_name: wood-harvest


en: Seasonal variation in environmental constraints (vapor pressure deficit – VPD, air temperature, and soil moisture) on tree growth for the potential distribution range of seven widespread Central European tree species. We simulated environmental constraints on growth fusing 3-PG model or the species’ potential distribution range within the forested area of Switzerland on a 1×1 km grid for seven dominant tree species: _Larix decidua_, _Picea abies_, _Abies alba_, _Fagus sylvatica_, _Acer pseudoplatanus_, _Pinus sylvestris_, and _Quercus robur_. For this purpose, we simulated the growth of these tree species in monocultures with the average climate observed during 1961–1990 or 1991-2018. The stands were initialized as 2-year-old plantations with an initial density of 2,500 trees ha-1 and simulated until the age of 30 years. For each simulated month, we obtained the relative contribution of environmental constraints (VPD, temperature, and soil water) on tree growth.

en: drought 3-pg vpd climate-change growth-limitation tree-rings

envidat

en: EnviDat: the Environmental Data Portal

en: Environmental constraints on tree growth

climate-change

display_name: climate-change

growth-limitation

display_name: growth-limitation

tree-rings

display_name: tree-rings

vpd

display_name: vpd


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

en: antarctica landuse topography wrf cryowrf

en: REMA topography and AntarcticaLC2000 for WRF

envi

en: Environment

de:
Resource Title: Documentation
    Size: 2136909 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/886f1b73-459a-4d41-aca5-0af9dc86ae7b/resource/ddb02d97-7e22-4aca-ab56-29f57ef2ad8e/download/documentation_rema_antarcticalc2000.pdf
    Description: Documentation about how the provided dataset was produced including details to reproduce the dataset.

de:
Resource Title: WPSinput
    Size: 15462767 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/886f1b73-459a-4d41-aca5-0af9dc86ae7b/resource/13f9afab-ef62-4454-965f-19b3e6288cc7/download/wpsinput.zip
    Description: Input files to run the Weather Research and Forecasting model (WRF) preprocessing system WPS with REMA topography and AntarcticaLC2000 landuse data (see Documentation for details).

de:
Resource Title: Scripts
    Size: 24621 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/886f1b73-459a-4d41-aca5-0af9dc86ae7b/resource/97db282f-c028-4d1e-8bf9-6cda65aa5f7a/download/scripts.zip
    Description: Scripts to run the preprocessing to produce WRF binary tiles from REMA and AntarcticaLC2000 for topography and landuse (see Documentation for procedure).

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf


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).

en: growth forest npp dvm assimilation

envidat

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.

de: EnviDat: das Umwelt-Datenportal

de: EnviDat

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

assimilation

display_name: assimilation

dvm

display_name: dvm

forest

display_name: forest

growth

display_name: growth

npp

display_name: npp


en:
To validate the critical crack length as implemented in the snow cover model SNOWPACK, PST experiments were conducted for three winter seasons (2015-2017) at two field site above Davos, Switzerland. This dataset contains manually observed snow profiles and stability tests. Furthermore, corresponding SNOWPACK simulations are included.
These data were analyzed and results were published in Richter et al. (2019).
Please refer to the Readme file for further details on the data.
These data are the basis of the following publication:
Richter, B., Schweizer, J., Rotach, M. W., and van Herwijnen, A.: Validating modeled critical crack length for crack propagation in the snow cover model SNOWPACK, The Cryosphere, 13, 3353–3366, https://doi.org/10.5194/tc-13-3353-2019, 2019.

en: snow snowpack snow-stability-evaluation avalanche avalanche-forecast

en: Validating and improving the critical crack length in SNOWPACK

envi

de: Umwelt

de:
Resource Title: Extracted data
    Size: 197562 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/42774021-73e4-49b2-a714-b192a0e3cc14/download/extracted_data.zip
    Description: Extracted data contain validation and results published in Richter et al. (2019).

de:
Resource Title: Stability tests
    Size: 6975 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/98cbbb6e-bfad-4b71-b920-e3def95143d3/download/stability_tests.zip
    Description: Stability tests including csv-files with CT, ECT and PST experiments for each year and each field site.

de:
Resource Title: Manually observed snow profiles
    Size: 27333 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/74bf515b-cd6b-4e97-be6d-4356f0af6d3d/download/manual_snow_profiles.zip
    Description: Manually observed snow profiles as csv-files containing depth [cm], thickness [cm], density [kg m-3], hand hardness, first grain type, second grain type, first grain size [mm], and second grain size [mm] of each layer.

de:
Resource Title: README
    Size: 18771 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/b6cfb0c3-2bb3-4fa1-859d-5861983aa785/download/readme.txt
    Description: README file explaining data structure and content

de:
Resource Title: SNOWPACK simulations
    Size: 21903741 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/6b0dc93f-34d1-48e2-bf69-3f9254e34692/download/snowpack.zip
    Description: This dataset contains all SNOWPACK simulations, including input files, setup and output files.

avalanche

display_name: avalanche

avalanche-forecast

display_name: avalanche-forecast

snow

display_name: snow

snow-stability-evaluation

display_name: snow-stability-evaluation

snowpack

display_name: snowpack


en: The WFJ_ICE_LAYERS dataset contains multi-instrument snowpack measurements at high temporal resolution, which enable to monitor the formation of deep ice layers due to preferential water flow, at the Weissfluhjoch research site, Davos, Switzerland. It covers the winter 2016/2017, with a focus on the early melting season. This dataset includes traditional snowpack profiles (weekly resolution, 15/11/2016-29/05/2017), SnowMicroPen penetration resistance profiles (daily resolution, 01/02/2017-19/04/2017), snow temperatures measured at different heights in the snowpack (half-hourly resolution, 01/03/2017-15/04/2017) and the water front height derived from an upward-looking ground penetrating radar (3-hour resolution, 04/03/2017-08/04/2017). The measurements are complemented by initialization files for SNOWPACK model simulations with the ice reservoir parameterization at Weissfluhjoch for the winter 2016/2017.

en: snowmicropen water-front snow-temperature snow-stratigraphy weissfluhjoch ice-layers

en: WFJ_ICE_LAYERS: Multi-instrument data for monitoring deep ice layer formation in an alpine snowpack

de:
Resource Title: README
    Size: 476 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2bf03a26-ee90-4e13-8ed0-63fbfada5733/resource/55d88599-ae7a-4ba6-af25-9544893de2be/download/readme.txt
    Description:

de:
Resource Title: WFJ_ICE_LAYERS dataset
    Size: 4289873 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2bf03a26-ee90-4e13-8ed0-63fbfada5733/resource/06794e9d-cbac-4a14-9d3b-a06f7f6c2061/download/wfj_ice_layers_dataset.zip
    Description:

ice-layers

display_name: ice-layers

snow-stratigraphy

display_name: snow-stratigraphy

snow-temperature

display_name: snow-temperature

snowmicropen

display_name: snowmicropen

water-front

display_name: water-front

weissfluhjoch

display_name: weissfluhjoch


en: We investigated the sensitivity of modeled snow instability to meteorological input data using SNOWPACK. We therefore used input data from the automatic weather station at the Weissfluhjoch field site for the year 2016-2017. We investigated three scenarios and performed 14'000 simulations for each scenario.  The dataset contains extracted output data from modeled SNOWPACK simulations, including setup files to reproduce the simulations. For further information read the README file.

en: snowpack snow-instability global-sensitivity-analysis numerical-avalanche-forecasting snow-cover-modeling

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: Sensitivity of modeled snow instability

de:
Resource Title: Manually observed snow profiles
    Size: 12725 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/5bd23cea-d4e3-4f87-8b0c-bfa3dc82afec/download/manual_profiles.zip
    Description: Manually observed snow profiles at Weissfluhjoch field site for winter season 2016-2017, including layer depth, hand hardness, grain size and grain shape for each layer.

de:
Resource Title: Reference run
    Size: 9909880 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/7eb0f753-02d2-4592-b822-cf91745ea196/download/reference.zip
    Description: Reference run for the sensitivity analysis at Weissfluhjoch field site for winter season 2016-2017. Meteorological data from the automatic weather stations are used. No biases were introduced to the input data.

de:
Resource Title: Case ALL
    Size: 346790131 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/fd47ae3d-77a9-4f79-8c95-57b11de523bb/download/case_all.zip
    Description: Extracted output data for case ALL. Here biases were introduced to meteorological input data during the whole simulation period. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

de:
Resource Title: Case WL
    Size: 342942228 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/84ee8947-54aa-40d6-86bb-b6e0ffc14d25/download/case_wl.zip
    Description: Extracted output data for case ALL. Here biases were introduced to meteorological input data during the period of weak layer formation. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

de:
Resource Title: Case SL
    Size: 277264559 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/716fdeb9-b2e2-4613-bba3-691eff467c1b/resource/7635f568-e96c-4901-a385-c369150aaad6/download/case_sl.zip
    Description: Extracted output data for case SL. Here biases were introduced to meteorological input data during the period of slab formation. Data include quasi random biases, which were introduced, extracted output of simulated snow profiles and sobol indices for each output variable.

global-sensitivity-analysis

display_name: global-sensitivity-analysis

numerical-avalanche-forecasting

display_name: numerical-avalanche-forecasting

snow-cover-modeling

display_name: snow-cover-modeling

snow-instability

display_name: snow-instability


en:
This dataset provides distribution data of fungi in Switzerland of the National Data and Information Centre, called  [SwissFungi](https://swissfungi.wsl.ch/en/index.html). SwissFungi is a partner of [InfoSpecies](https://www.infospecies.ch/de/), the network of Swiss data and information centres for [fauna](http://www.cscf.ch/cscf/de/home.html), [flora](https://www.infoflora.ch/en/) and [fungi](https://swissfungi.wsl.ch/en/index.html). One of its main objectives is to document the spatial and temporal distribution of species in Switzerland.
The SwissFungi database currently contains more than 670'000 geo-referenced fungi observations, distributed throughout Switzerland. The oldest observations date back to 1770. A large portion of the records are from the last two decades of the last century to the present day. The database is continuously updated with new fungi records. The data have been validated and originate from national inventories, from research projects, from floristic observations by volunteers as well as from private and public herbaria and from the literature.
The data from the distribution atlas of fungi in Switzerland are available for research and practice (nature conservation projects, environmental impact assessments etc.) and can be obtained via an [application form](https://www.infospecies.ch/de/assets/content/documents/Formular_Datenanfrage20190625.pdf). Please note the tariffs for data requests and submit your request directly to the [InfoSpecies](https://www.infospecies.ch/de/) office. Applications are usually answered within two working weeks. Details on the use of data are regulated in the current guidelines of the national data centers. Please note that the data center SwissFungi is not able to verify all incoming fungal records completely for a correct identification or coordinate errors and therefore cannot guarantee the correctness of the information.
License under [InfoSpecies](https://www.infospecies.ch/de/). Data is free of charge for research projects and available on request.

en: swissfungi biodiversity records-database national-data-center fungi-conservation fungi

envidat

en: EnviDat: the Environmental Data Portal

en: SwissFungi - Records Database for the Fungi of Switzerland

biodiversity

display_name: biodiversity

fungi

display_name: fungi

fungi-conservation

display_name: fungi-conservation

national-data-center

display_name: national-data-center

records-database

display_name: records-database

swissfungi

display_name: swissfungi


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.

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

en: Digitizing historical plague

envi

en: Environment

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