en:
The present dataset is part of the published scientific paper Hersperger, A.M., Bürgi, M., Wende, W., Bacău, S. and Grădinaru, S.R., 2020. Does landscape play a role in strategic spatial planning of European urban regions?. Landscape and Urban Planning, 194, p.103702.
The goal of this research was to assess the role of landscape in contemporary strategic spatial planning.  In order to assess the role of “landscape” in the strategic spatial plans, we focused on how plans took advantage of landscape’s integrative power, how plans are based on knowledge on functioning of landscape systems, and how plans show the contribution of landscapes to human well-being. For each aspect, a number of items (detailed in Table 1 of the paper) were selected to assist the assessment.
This study is based on content analysis of the strategic spatial plans of 18 European urban regions. The strategic spatial plans were retrieved from the planning authorities’ websites.  The cases study regions as well as the analyzed strategic spatial plans are presented in Table 2 of the paper.
The authors developed a protocol containing  28 items, out of which 16 were directly derived from information presented in Table 1. As a result, we provide the following outputs:
•	Protocol_items.docx – freely available - Detailed description of all the protocol items used to conduct the analysis.
•	Coding results.xlsx – available on request - Results of the coding procedure. Data were used to create Figures 2, 3, 4, 5, 6 and to qualitatively present the results in the research paper.

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

envidat

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

en: EnviDat: the Environmental Data Portal

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

de:
Resource Title: Coding results
    Size: 3846 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ce7486ec-fd91-479c-87a3-7c44b9d0178d/resource/724ff9bb-68ef-4a5b-bcae-2278b1347261/download/coding-results.csv
    Description: o	Results of the coding procedure. Data were used to create Figures 2, 3, 4, 5, 6 and to qualitatively present the results in the research paper.

de:
Resource Title: Protocol_items
    Size: 211462 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/ce7486ec-fd91-479c-87a3-7c44b9d0178d/resource/b59155ed-45d2-42ac-b9da-285808ee6c25/download/protocol_items_landscape.pdf
    Description: o	Detailed description of all the protocol items used to conduct the analysis and the way each question was coded

governance

display_name: governance

green-infrastructure

display_name: green-infrastructure

landscape-principles

display_name: landscape-principles

plan-evaluation

display_name: plan-evaluation

strategic-plan

display_name: strategic-plan


data-konzeptionelles-systemmodell

$oid: OBSOLETE

en:
This folder contains documents relevant to the project step Konzeptionelles Systemmodell. It specifically contains the following documents:
1. 0201_Konzeptionelles Systemmodell_20221027: This document is the final version of the Konzeptionelles Systemmodell. The underlying structure of the Konzeptionelles Systemmodell is explained in chapter 4.4 of the document 0202_Masterarbeit Elena Siegrist_UniBern_Herbstsemester 2022 also deposited in this folder. The document contains 3 sheets. The sheet "Bausteine" shows the different possible options for table columns of the type Bausteine (see chapter 4.4 of Masterarbeit), the sheet "Direkte Effekte" contains identified direct impact pathways and the sheet "Indirekte Effekte" contains identified indirect impact pathways.
2. 0202_Masterarbeit Elena Siegrist_UniBern_Herbstsemester 2022: This document is the Master Thesis of Elena Grace Siegrist submitted to and accepted by the University of Bern in the Autumn Semester 2022. Chapter 4.4 of the document explains the underlying structure of the Konzeptionelles Systemmodell.
3. 0203_Literaturverzeichnis_konzeptionelles Systemmodell_20221026: This document lists all literature and documents cited in the Konzeptionelle Systemmodell.

en: landscape-change climate-change scenarios policy-action qualitative-research

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.

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

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: Data Konzeptionelles Systemmodell

title_for_slug: data-konzeptionelles-systemmodell

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

de:
Resource Title: 0202_Masterarbeit Elena Siegrist_UniBern_Herbstsemester 2022
    Size: 20498856 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/63cdd109-d84d-4664-b9c8-cabff7206265/resource/59a6d667-fa1c-48c9-b219-56e6b60c0e6a/download/0202_masterarbeit-elena-siegrist_unibern_herbstsemester-2022.pdf
    Description:

format: PDF

media_type: application/pdf

de:
Resource Title: 0203_Literaturverzeichnis_konzeptionelles Systemmodell_20221026
    Size: 135744 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/63cdd109-d84d-4664-b9c8-cabff7206265/resource/a0b05adc-77b0-4c7e-bf7b-d073974e2cd8/download/0203_literaturverzeichnis_konzeptionelles-systemmodell_20221026.pdf
    Description:

de:
Resource Title: 0201_Konzeptionelles Systemmodell_20221027
    Size: 51597723 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/63cdd109-d84d-4664-b9c8-cabff7206265/resource/6943041d-18c9-4ef4-b114-1269f9d78811/download/0201_konzeptionelles-systemmodell_20221027.xlsx
    Description:

format: XLS

climate-change

display_name: climate-change

landscape-change

display_name: landscape-change

policy-action

display_name: policy-action

qualitative-research

display_name: qualitative-research

scenarios

display_name: scenarios


en:
This dataset contains the spatial layers showing future land change pathways in Europe between 2015 and 2050, as simulated by the CLUMondo model and according to the Agricultural Futures Framework (AFF) scenarios.
Three scenarios are included:
- Land for Food and Land for Nature (LFLN)
- Land as Culture (LaC)
- Land for Society (LfS)

en: land-use-modelling pathways agriculture scenarios land-change

en: AFF agricultural land change scenarios in Europe 2015-2050

de:
Resource Title: AFF_agricultural land_change scenarios_Europe_2015_2050.zip
    Size: 3851250 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/15ae8f00-310e-4cee-95ed-d00f0aa25dbe/resource/a8d3393e-178f-43a7-9538-1437b0afd8b3/download/aff_agricultural-land_change-scenarios_europe-2015_2050.zip
    Description: This dataset contains the spatial layers showing future land change pathways in Europe between 2015 and 2050, as simulated by the CLUMondo model according to the Agricultural Futures Framework (AFF) scenarios.

format: ZIP

de:
Resource Title: ReadMe.pdf
    Size: 87640 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/15ae8f00-310e-4cee-95ed-d00f0aa25dbe/resource/573e45b3-27b1-4139-b61b-06c3adc8871e/download/readme.pdf
    Description:

agriculture

display_name: agriculture

land-change

display_name: land-change

land-use-modelling

display_name: land-use-modelling

pathways

display_name: pathways


en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Chironico in Switzerland where one station is located within a natural coniferous forest stand (CIB) with Norway spruce (_Picea abies_; 160-180 yrs) and European silver fir (_Abies alba_; 140-160 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CIF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Chironico is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

en: Chironico, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 2000 onwards

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

de:
Resource Title: Site photo of the field station (CIF)
    Size: 595220 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/6d4df6e5-55ca-4706-84b8-02095fc7247e/download/cif.jpg
    Description: Site photo of the field station from the side.

de:
Resource Title: Site aerial photo (Chironico)
    Size: 8272921 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/c1beb5d4-0bb5-449c-9d68-428f5d7053dc/download/cifront.jpg
    Description: Site aerial photo from both Chironico stations. Source: Google. 2016. Site aerial photo from both Chironico stations. Retrieved November 11, 2016, from https://www.google.ch/maps

de:
Resource Title: Data plot of the field station (CIF)
    Size: 9381698 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/5993f35c-f254-4f4e-b603-82f1999524f4/download/ciffield.csv
    Description: Data file.

format: CSV

media_type: text/csv

de:
Resource Title: Data plot of the forest station (CIB)
    Size: 245044 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/806df5aa-7383-4d16-8318-4c26237ddd03/download/cibplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

de:
Resource Title: Data plot of the field station (CIF)
    Size: 298986 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/dbf82da9-d637-4660-ab4c-50943b190dde/download/cifplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

de:
Resource Title: Forest station data (CIB)
    Size: 9148615 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/d2125be5-ab36-4a79-8873-100747c9304a/download/cibforest.csv
    Description: Data file.

de:
Resource Title: Site photo of the forest station (CIB)
    Size: 2398813 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/aa85a779-49cb-4d55-bcaf-e957a48d0771/resource/d06f65e8-1a2a-4fc1-9b01-6f8c5f1854ef/download/cib.jpg
    Description: Site photo of the forest station from below (viewing upwards the slope).

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed


en:
This dataset includes data on species richness of vascular plants and bryophytes in 55 wetlands of the canton of Zürich (Switzerland) as well as recent and historic data on the area and connectivity of these 55 wetlands and was used for the paper Jamin A., Peintinger M., Gimmi U., Holderegger R., Bergamini A. (2020) Evidence for a possible extinction debt in Swiss wetland specialist plants. Ecology and Evolution.
Species richness data are available for vascular plants and bryophytes. The field survey was carried out between June 5 and August 10, 2012. The survey covered all wetland (fen) types in the canton of Zürich. For data collection, at least half a day per wetland was spent searching for species. Within each wetland all different vegetation types were covered until no new species were found to get as complete species lists as possible. In the Excel file information on species richness of the following groups is provided: (1) all vascular plant species; (2) wetlands specialists among vascular plants; (3) generalists, which were all non-specialist vascular plant species; (4) short-lived vascular plant specialists; (5) long-lived vascular plant specialists; (6) short-lived vascular plant generalists; (7) long-lived vascular plant generalists; (8) bryophyte species. Specialist vascular plant species included all characteristic species listed in Appendix 1a of the wetland inventory of Switzerland (BUWAL, 1990).
Based on the data of Gimmi et al. (2011), the area of all wetlands in 1850, 1900, 1950 and 2000 were determined as well as the wetland area within buffers 2km in radius with the center of the wetland as starting point. These data are also provided in the Excel sheet.
Moreover, for each wetland mean indicator values according to Landolt et al. (2010) and the standard deviation of these indicator values based on presence-absence data of vascular plants were calculated and are provided in Excel sheet. Indicator values for temperature, light availability, moisture, acidity, nutrients, amount of humus and soil aeration were considered.

en: bryophytes species-richness vascular-plants habitat-area nature-conservation habitat-fragmentation extinction-debt wetlands

en: Wetlands of the canton of Zürich (Switzerland): Data on species richness and recent and historic area and connectivity of 55 fens

bryophytes

display_name: bryophytes

extinction-debt

display_name: extinction-debt

habitat-area

display_name: habitat-area

habitat-fragmentation

display_name: habitat-fragmentation

nature-conservation

display_name: nature-conservation

species-richness

display_name: species-richness

vascular-plants

display_name: vascular-plants

wetlands

display_name: wetlands


en:
Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes, the Providencia island data set.
Between June 29 and July 5, 2018, we collected a total of 20 water samples from 10 stations around Providencia Island, with two filtration replicates per station. Providencia Island is located in the southwestern Caribbean Sea and forms part of the UNESCO Seaflower Biosphere Reserve in Colombia. This island, which belongs to the San Andrés, Providencia, and Santa Catalina Archipelago, is characterized by a complex barrier reef on a calcareous platform surrounding an extinct Miocene volcano. The high habitat diversity provides a range of substratum types and coral reefs, influencing the diversity, abundance, and distribution of coral reef fishes. Each station consisted of a transect of 2 km at an overall constant distance from the coast. We recorded the GPS coordinates at the start and end of the transect. We conducted eDNA sampling by using a filtration device composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 L/min), a VigiDNA® 0.20 μM cross-flow filtration capsule (SPYGEN, le Bourget du Lac, France) and disposable sterile tubing for each filtration capsule. We performed two filtration replicates in parallel on each side of a boat, at each station, for 30 min corresponding to a volume of ~30 L of water filtered by each capsule. At the end of each filtration, the water inside the capsules was emptied, and we filled the capsules with 80 ml of CL1 Conservation buffer (SPYGEN, le Bourget du Lac, France) and stored at room temperature. We followed a strict contamination control protocol in both field and laboratory stages (Valentini et al., 2016). Each water sample processing included the use of disposable gloves and single-use filtration equipment to avoid any risk of contamination. Libraries were prepared with ligation using the MetaFast protocol (Fasteris).
Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

en: biomonitoring biodiversity teleo edna reef-fish environmental-dna caribbean-region marine

en: Environmental DNA Marine Colombia Providencia 2018

biodiversity

display_name: biodiversity

biomonitoring

display_name: biomonitoring

caribbean-region

display_name: caribbean-region

edna

display_name: edna

environmental-dna

display_name: environmental-dna

marine

display_name: marine

reef-fish

display_name: reef-fish

teleo

display_name: teleo


invasive-neophytes-along-national-roads

en:
Streets and Highways are important corridors for the spread of invasive plant species. On behalf of the **Federal Roads Office, FEDRO**, WSL surveyed the national road network in 2021 and recorded the distribution of three invasive neophytes using **AI-based species recognition** in a total of **3.8 million georeferenced images**. The mapped species are the **tree of heaven *(Ailanthus altissima)***, **common ragweed *(Ambrosia artemisiifolia)*** and **narrow-leaved ragweed *(Senecio inaequidens)***.
The data here is part of the **FEDRO documentation** and shows the mapping results as images and interactive maps. The interactive maps are - technically speaking - **self-contained HTML files** that can be displayed with standard web browsers. To reduce the file size, the downloads are provided in zip format.
**License**: This is not an independent data publication by WSL. The data was published together with the written document Trocmé et al. 2023, **© FEDRO 2023** (see related publication: © ASTRA 2023, Abdruck - ausser für kommerzielle Nutzung - unter Angabe der Quelle gestattet).

en: automatic-detection artificial-intelligence plants computer-vision biological-invasions invasive-species

envidat

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

en: EnviDat: the Environmental Data Portal

en: Invasive neophytes along national roads

title_for_slug: invasive-neophytes-along-national-roads

de:
Resource Title: Senecio_NS2021.html.zip
    Size: 51366008 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/10898fd0-af14-464c-8b27-aeb2806bc6f9/resource/9160b659-6414-48a1-ac72-875c7ff1cb8e/download/senecio_ns2021.html.zip
    Description: Detected occurrences of Senecio inaequidens along Swiss national roads. Self-contained HTML file with an interactive map that can be displayed with standard web browsers. Species occurrences of the middle and side strips can be displayed separately.

media_type: application/zip

de:
Resource Title: Ambrosia_NS2021_kmeans4.png
    Size: 1521894 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/10898fd0-af14-464c-8b27-aeb2806bc6f9/resource/c650fa91-2152-4e14-9fa2-06be231faad4/download/ambrosia_ns2021_kmeans4.png
    Description: Generalized map of detected Ambrosia artemisiifolia occurrences along Swiss national roads.

format: PNG

media_type: image/png

de:
Resource Title: Ailanthus_ns2021.html.zip
    Size: 48932476 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/10898fd0-af14-464c-8b27-aeb2806bc6f9/resource/d3774833-80dd-454c-8e90-12662f908d2a/download/ailanthus_ns2021.html.zip
    Description: Detected occurrences of Ailanthus altissima along Swiss national roads. Self-contained HTML file with an interactive map that can be displayed with standard web browsers. Species occurrences of the middle and side strips can be displayed separately.

de:
Resource Title: Senecio_NS2021_kmeans4.png
    Size: 1517263 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/10898fd0-af14-464c-8b27-aeb2806bc6f9/resource/47ab7392-e462-47cb-a5b1-dca1e2b1bff3/download/senecio_ns2021_kmeans4.png
    Description: Generalized map of detected Senecio inaequidens occurrences along Swiss national roads.

de:
Resource Title: Ailanthus_ns2021_kmeans4.png
    Size: 1514672 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/10898fd0-af14-464c-8b27-aeb2806bc6f9/resource/c38d612c-7ea1-4b01-81c3-08169e101238/download/ailanthus_ns2021_kmeans4.png
    Description: Generalized map of detected Ailanthus altissima occurrences along Swiss national roads.

de:
Resource Title: Ambrosia_NS2021.html.zip
    Size: 33508731 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/10898fd0-af14-464c-8b27-aeb2806bc6f9/resource/d363c4f7-7b3d-4a57-b562-1c5559bd41ff/download/ambrosia_ns2021.html.zip
    Description: Detected occurrences of Ambrosia artemisiifolia along Swiss national roads. Self-contained HTML file with an interactive map that can be displayed with standard web browsers. Species occurrences of the middle and side strips can be displayed separately.

artificial-intelligence

display_name: artificial-intelligence

automatic-detection

display_name: automatic-detection

biological-invasions

display_name: biological-invasions

computer-vision

display_name: computer-vision

invasive-species

display_name: invasive-species

plants

display_name: plants


en:
Predicting future climatic conditions at high spatial resolution is essential for many applications in science. Here we present data for monthly time series of precipitation and minimum and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation sums at ~5km spatial resolution globally for the years 1850-2100. We validated the performance of the downscaling algorithm by comparing model output with observed climates for the years 1950-2069.
CHELSA_cmip5_ts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

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

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 monthly precipitation and temperature timeseries for the period 2006-2100

envi

de: Umwelt

en: Environment

air-temperature

display_name: air-temperature

climate-change

display_name: climate-change

orographic-precipitation

display_name: orographic-precipitation

precipitation-amount

display_name: precipitation-amount


en: A multitude of physical and biological processes on which ecosystems and human societies depend are governed by climatic conditions. Understanding how these processes are altered by climate change is central to mitigation efforts. Based on mechanistically downscaled climate data, we developed a set of climate-related variables at yet unprecedented spatiotemporal detail as a basis for environmental and ecological analyses. We created gridded data for near-surface relative humidity (hurs), cloud area fraction (clt), near-surface wind speed (sfcWind), vapour pressure deficit (vpd), surface downwelling shortwave radiation (rsds), potential evapotranspiration (pet), climate moisture index (cmi), and site water balance (swb), at a monthly temporal and 30 arcsec spatial resolution globally starting 1980 until 2018. At the same spatial resolution, we further estimated climatological normals of frost change frequency (fcf), snow cover days (scd), potential net primary productivity (npp), growing degree days (gdd), and growing season characteristics for the periods 1981-2010, 2011-2040, 2041-2070, and 2071-2100, considering three shared socioeconomic pathways (SSP126, SSP370, SSP585) and five Earth system models. Time-series variables showed high accuracy when validated against observations from meteorological stations. Climatological normals were also highly correlated to observations although some variables showed notable biases, e.g., snow cover days (scd). Together, the data sets presented here allow improving our understanding of patterns and processes that are governed by climate, including the impact of recent and future climate changes on the world’s ecosystems and associated services to societies.

en: precipitation relative-humidity soil-water-balance growing-season-length solar-radiation growing-degree-days temperature

en: CHELSA-BIOCLIM+ A novel set of global climate-related predictors at kilometre-resolution

de:
Resource Title: CHELSA-BIOCLIM+ Technical Documentation
    Size: 423097 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/21d662b7-9c59-41da-aa82-7d8a879b8db7/resource/aa676d1f-5f7f-479b-af20-26066b0537d1/download/chelsa_file_specification_bioclim_plus.pdf
    Description: Technical documentation document including the variable names, units, scaling, offset, and background.

de:
Resource Title: CHELSA-BIOCLIM+
    Size: 13194139533312 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav2%2F&prefix=%2F
    Description: Global extented set of bioclimatic variables at different temporal (e.g. monthly, annual, long term normals) resolution in Geotiff format.

growing-degree-days

display_name: growing-degree-days

growing-season-length

display_name: growing-season-length

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

soil-water-balance

display_name: soil-water-balance

solar-radiation

display_name: solar-radiation

temperature

display_name: temperature


en:
Resources associated with the manuscript *A case study on the application of spore sampling for the monitoring of macrofungi* ([Schlegel et al. 2024](https://doi.org/10.1111/1755-0998.13941)).
Airborne environmental DNA (eDNA) monitoring of fungi was evaluated on a species-rich grassland site. Extensive fruiting body surveys yielded 29 waxcap and clavarioid species, 19 of which were also detectable in air eDNA. The analysis indicates that spores of locally occurring fruiting bodies were detected, in addition to a large diversity of common fungal species, while rare and threatened species were under-represented in the air.
*Version 1* of the dataset was submitted during the review phase. *Version 2* contains minor changes and clarifications, and is up to date with the [published supplement](https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F1755-0998.13941&file=men13941-sup-0001-AppendixS1.pdf) of the study.
The contents of the ZIP archive:
* analysis scripts in [R-Markdown](https://rmarkdown.rstudio.com) format, including the rendered PDF output with figures and tables (*analysis* directory)
* eDNA sample metadata (*amplicon_meta*) and results of the amplicon clustering (*amplicon_data*) and the source code of the pipeline (*amplicon_pipeline*)
* positions of all fruiting body groups found in the surveys (3838 GPS points) (*surveys*)
* positions of the spore traps, taxonomy of studied grassland fungi and red-list species, and many more resources
Please refer to `README.pdf` inside the archive for a complete description of the file structure and information on how to reproduce the analyses.

en: metabarcoding monitoring spore-dispersal air-sampling environmental-dna

en: Supporting information for case study on the application of spore sampling for the monitoring of macrofungi

de:
Resource Title: Data files and analysis scripts (Version 1)
    Size: 29336906 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/5ecb89e0-7abf-42ce-b210-24dcdee781d9/resource/9ac066a9-e65a-4bf9-937e-a43f6aae41e3/download/suppinfo.zip
    Description: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of fungi". Please refer to README.pdf inside the archive for more information.

de:
Resource Title:  Data files and analysis scripts (Version 2)
    Size: 32072370 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/5ecb89e0-7abf-42ce-b210-24dcdee781d9/resource/d056b217-18c0-4733-b204-602289cf7eee/download/supplementary_data.zip
    Description: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of macrofungi". Please refer to README.pdf inside the archive for more information.

air-sampling

display_name: air-sampling

environmental-dna

display_name: environmental-dna

metabarcoding

display_name: metabarcoding

monitoring

display_name: monitoring

spore-dispersal

display_name: spore-dispersal


en:
This repository contains all observational data sets during CALISHTO campaign used for the paper:
Gao, K., Vogel, F., Foskinis, R., Vratolis, S., Gini, M. I., Granakis, K., Billault-Roux, A.-C., Georgakaki, P., Zografou, O., Fetfatzis, P., Berne, A., Papagiannis, A., Eleftheridadis, K., Möhler, O., and Nenes, A.: Biological and dust aerosol as sources of ice nucleating particles in the Eastern Mediterranean: source apportionment, atmospheric processing and parameterization, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-511, 2024.

en: aerosol-source-apportionment inp-parameterization ice-nucleation aerosol-cloud-interactions biological-particles

en: CALISHTO campaign dataset for the publication Biological and Dust Aerosols as Sources of Ice-nucleating Particles in the Eastern Mediterranean

aerosol-cloud-interactions

display_name: aerosol-cloud-interactions

aerosol-source-apportionment

display_name: aerosol-source-apportionment

biological-particles

display_name: biological-particles

ice-nucleation

display_name: ice-nucleation

inp-parameterization

display_name: inp-parameterization


en:
This dataset includes the FORTRAN code of the FSM2trans model version used in the paper: Quéno et al., Snow redistribution in an intermediate-complexity snow hydrology modelling framework, The Cryosphere, 2024.
The FSM2trans code is derived from the FSM2 model (Essery et al., 2015) and its variant FSM2oshd (Mott et al., 2023). In this model, we implemented and adapted the snowdrift model SnowTran-3D (Liston et al., 2007) and the avalanching model SnowSlide (Bernhardt and Schulz, 2010).
This dataset does not include the processing scripts to prepare meteorological input data for the model, provided as bin files.

en: source-code avalanche snow-modelling snowdrift snowpack

en: FSM2trans code

de:
Resource Title: README.txt
    Size: 957 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d2398461-752f-4984-a944-2e565ed0c1ce/resource/7446d1e9-634a-4da1-b7ef-7ffc28ea61c4/download/readme.txt
    Description:

format: TXT

media_type: text/plain

de:
Resource Title: namelist.zip
    Size: 1490 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/d2398461-752f-4984-a944-2e565ed0c1ce/resource/b59836a9-e725-4276-92d2-d3e17efc0966/download/namelist.zip
    Description:

de:
Resource Title: code.zip
    Size: 90894 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/d2398461-752f-4984-a944-2e565ed0c1ce/resource/2f7b6697-4863-4ab8-8975-11603ba6dd5e/download/code.zip
    Description:

avalanche

display_name: avalanche

snow-modelling

display_name: snow-modelling

snowdrift

display_name: snowdrift

snowpack

display_name: snowpack

source-code

display_name: source-code


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

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

envidat

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

en: EnviDat: the Environmental Data Portal

en: Multi-resolution CLM5 simulations across Switzerland

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

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

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

evapotranspiration

display_name: evapotranspiration

forest-productivity

display_name: forest-productivity

high-resolution

display_name: high-resolution

land-cover

display_name: land-cover

land-use

display_name: land-use

oshd

display_name: oshd

snow

display_name: snow

snow-simulation

display_name: snow-simulation


en:
Environmental DNA complements scientific trawling in surveys of marine fish biodiversity (Dataset 2020)
In October 2020 we chose 16 sites from the 2020 EVHOE survey for eDNA sampling. The French international EVHOE bottom trawl survey is carried out annually during autumn in the BoB to monitor demersal fish resources. All sites were located on the continental shelf (26–170 m depth), except one on the upper slope with a depth of 1045 m. To perform eDNA sampling, we collected water samples at 15 sites (Figure 1a). At each site, we sampled seawater using Niskin bottles deployed with a circular rosette. There were nine bottles on the rosette, each of them able to hold ∼5 l of water. At each site, we first cleaned the circular rosette and bottles with freshwater, then lowered the rosette (with bottles open) to 5 m above the sea bottom, and finally closed the bottles remotely from the boat. The 45 l of sampled water was transferred to four disposable and sterilized plastic bags of 11.25 l each to perform the filtration on-board in a laboratory dedicated to the processing of eDNA samples. To speed up the filtration process, we used two identical filtration devices, each composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 l min–1 ), a VigiDNA 0.20 μm filtration capsule (SPYGEN, le Bourget du Lac, France), and disposable sterile tubing. Each filtration device filtered the water contained in two plastic bags (22.5 l), which represent two replicates per sampling site. We followed a rigorous protocol to avoid contamination during fieldwork, using disposable gloves and single-use filtration equipment and plastic bags to process each water sample. At the end of each filtration, we emptied the water inside the capsule that we replaced by 80 ml of CL1 conservation buffer and stored the samples at room temperature following the specifications of the manufacturer (SPYGEN, Le Bourget du Lac, France). We processed the eDNA capsules at SPYGEN, following the protocol proposed by Polanco-Fernández et al., (2020). We performed library preparation and sequencing at Fasteris (Geneva, Switzerland). Specifically, we prepared four libraries using the MetaFast protocol (a ligation-based method) and sequenced them separately. We carried out paired-end sequencing using a MiSeq sequencer (2 × 125 bp, Illumina, San Diego, CA, USA) on two MiSeq Flow Cell Kits (v3; Illumina), following the manufacturer’s instructions. We analysed the sequence reads using the OBITools package (http:
//metabarcoding.org/obitools; Boyer et al., 2016), following the protocol described by Valentini et al. (2016).
Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

en: actinopterygii edna dna-metabarcoding bay-biscay fish-composition chondrichthyes teleo atlantic-region

en: Environmental DNA Marine France Evhoe 2020

envi

en: Environment

actinopterygii

display_name: actinopterygii

atlantic-region

display_name: atlantic-region

bay-biscay

display_name: bay-biscay

chondrichthyes

display_name: chondrichthyes

dna-metabarcoding

display_name: dna-metabarcoding

edna

display_name: edna

fish-composition

display_name: fish-composition

teleo

display_name: teleo


en:
Fish taxonomic, functional and phylogenetic composition variations recovered from eDNA metabarcoding along the coast of Curacao
In February 2020, we collected a total of 20 water samples, from 10 stations, with two filtration replicates per station, in the two investigated coastal areas. Each station consisted of a transect of 2 km at an overall constant distance from the coast. We recorded the GPS coordinates at the start and end of the transect, which we used to map the transect positions. We conducted eDNA sampling by using a filtration device composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 L/min), a VigiDNA® 0.20 μM cross-flow filtration capsule (SPYGEN, le Bourget du Lac, France) and disposable sterile tubing for each filtration capsule. We performed two filtration replicates in parallel on each side of a boat, at each station, for 30 min corresponding to a volume of ~30 L of water filtered by each capsule. At the end of each filtration, the water inside the capsules was emptied, and we filled the capsules with 80 ml of CL1 Conservation buffer (SPYGEN, le Bourget du Lac, France) and stored at room temperature. We followed a strict contamination control protocol in both field and laboratory stages (Valentini et al., 2016). Each water sample processing included the use of disposable gloves and single-use filtration equipment to avoid any risk of contamination. Libraries were prepared with ligation using the MetaFast protocol (Fasteris).

en: fish environmental-dna fish-composition caribbean-region curacao marine teleo coral-reefs edna

en: Environmental DNA Marine Curacao 2020

caribbean-region

display_name: caribbean-region

coral-reefs

display_name: coral-reefs

curacao

display_name: curacao

environmental-dna

display_name: environmental-dna

fish

display_name: fish

marine

display_name: marine


en:
Catchment-based sampling of river eDNA integrates terrestrial and aquatic biodiversity of alpine landscapes
From 22-Jun-2020 to 26-Jun-2020, we sampled five sites comprising one low, two intermediate and two high-elevation sites per catchment (Fig. 1a). We visited two catchments per day—one in the morning and one in the afternoon—for a total of ten catchments. All samples per catchment were collected within a maximum four-hour period by three groups of samplers. The intermediate and high-elevation sites were situated along two tributaries leading into the low-elevation site of the river. We used three filters for each relative elevation class and filtered 60 L per relative elevation class. We sampled 30 L per tributary for a combined volume of 60 L at the intermediate and high-elevation sites. In total, 180 L were sampled in total per catchment. A filtration device composed of either the Athena® peristaltic pump (Proactive Environmental Products LLC; 1 L/min nominal flow) or the Subspace® underwater peristaltic pump (Subspace Pictures; 1 L/min nominal flow), combined with a VigiDNA® 0.2 µM cross-flow filtration capsule (VigiDNA, SPYGEN) was used in order to filter a large water volume. We used a finer mesh than the recommended VigiDNA® 0.45 µM cross-flow filtration capsule to maximise the capture of biological material since mountain water does not transport high quantities of sediments. For each filtration capsule, we used disposable sterile tubing. At the end of each filtration, we emptied the water inside the capsules, replaced it with 80 ml of CL1 conservation buffer (SPYGEN), and stored it at room temperature. We followed a strict contamination control protocol in both field and laboratory stages (Goldberg et al. 2016; Valentini et al. 2016). Each water sample was processed using disposable gloves and single-use filtration equipment. We used two primer sets targeting vertebrates (Vert01, forward: − TTAGATACCCCACTATGC, reverse: − TAGAACAGGCTCCTCTAG, mean marker length: 97 bp) and spermatophytes (g-h/Sper01, forward: − GGGCAATCCTGAGCCAA, reverse: CCATTGAGTCTCTGCACCTATC, mean marker length: 48 bp). Though both primers are relatively broad with low species-level resolution, we selected them as the goal was to minimise cost and effort and maximise the identification of a broad range of taxa which can represent the species assemblages of the region. Libraries were prepared with ligation using the MetaFast protocol (Fasteris).

en: freshwater sper01 environmental-dna vertebrates vert01 switzerland spermatophytes edna

en: Environmental DNA Freshwater Switzerland VaudCatchment Modipl 2020

freshwater

display_name: freshwater

spermatophytes

display_name: spermatophytes

switzerland

display_name: switzerland

vertebrates

display_name: vertebrates


en: Supplementary animations for the publication (DOI to follow with pre-print) showing preferential deposition as modeled by the HICAR model. Complete descriptions of the animations, and a discussion of them, can be found in the publication.

en: orographic-precipitation numerical-model snow preferential-deposition atmospheric-dynamics alpine-precipitation

en: Preferential Deposition Processes Animations

de:
Resource Title: SnowfallProcess.gif
    Size: 19742647 bytes
    Format: image/gif
    URL: https://www.envidat.ch/dataset/0e19ff10-33d5-423c-bf3c-a8627bc00fe3/resource/44fed012-adfe-4edb-81ed-257b336d036c/download/snowfallprocess21.gif
    Description: Process-level view of Preferential Deposition

format: gif

de:
Resource Title: SnowfallMovie_Sattelhorn.gif
    Size: 1831082 bytes
    Format: image/gif
    URL: https://www.envidat.ch/dataset/0e19ff10-33d5-423c-bf3c-a8627bc00fe3/resource/9b3b85c7-9788-41ff-8b69-19e93e5517e5/download/snowfallmovie_sattelhorn1.gif
    Description: Ridge-scale hourly precipitation and cumulative SWE change amount during a snowfall event

de:
Resource Title: Preprint_SnowfallMovie_Sattelhorn.gif
    Size: 7237167 bytes
    Format: image/gif
    URL: https://www.envidat.ch/dataset/0e19ff10-33d5-423c-bf3c-a8627bc00fe3/resource/c8db3a64-660c-4425-803c-a06ad9547c3a/download/snowfallmovie_sattelhorn.gif
    Description: This movie is an older version of the file "SnonwfallMovie_Sattelhorn.gif" which appeared in the preprint for the relevant manuscript.

alpine-precipitation

display_name: alpine-precipitation

atmospheric-dynamics

display_name: atmospheric-dynamics

numerical-model

display_name: numerical-model

orographic-precipitation

display_name: orographic-precipitation

preferential-deposition

display_name: preferential-deposition

snow

display_name: snow


snow-height-classification-dataset

en:
Snow Height Classification dataset provides manually annotated snow height data that can be used for development and evaluation of automatic snow height classification approaches.
A subset of 20 IMIS stations which span different locations and elevations and vary in underlying surface (e.g., vegetation, bare ground, glacier, etc.) were selected and manually annotated with binary two-class ground truth information regarding snow height data:
 * **Class 0 - Snow** - the surface is covered by snow
 * **Class 1 - No Snow** - the surface is snow-free (e.g., vegetation, soil, rocks, etc.)
Data has been annotated with the help of domain experts. It should be mentioned that annotating historical data is problematic, as there is no way of checking whether there really was snow at the station or not. This means that assessing the presence of snow with the help of information from other sensors should be considered a best effort approach.
Besides the annotated snow height data, the dataset also contains additional data which are relevant to reproduce results in the following repository:
[https://gitlabext.wsl.ch/jan.svoboda/snow-height-classification](https://gitlabext.wsl.ch/jan.svoboda/snow-height-classification)
Any further use of the data has to comply with the CC BY-NC license:
[https://creativecommons.org/licenses/by-nc/4.0/](https://creativecommons.org/licenses/by-nc/4.0/)

en: snow-depth snow-height machine-learning imis deep-learning

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.

en: Snow Height Classification Dataset

title_for_slug: snow-height-classification-dataset

de:
Resource Title: Data Access
    Size: 21474836480 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.512%2Fsnow-height-classification-dataset%2F
    Description:

de:
Resource Title: snow-height-classification-dataset.zip
    Size: 5658619412 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.512/snow-height-classification-dataset.zip
    Description:

deep-learning

display_name: deep-learning

imis

display_name: imis

machine-learning

display_name: machine-learning

snow-depth

display_name: snow-depth

snow-height

display_name: snow-height


root-traits

en:
Fine-root traits of Scots pine in response to enhanced soil water availability deriving from long-term irrigation in the Pfynwald
Data_Fig.1.xlsx
Fine-root biomass of the topsoil (0-10 cm) in the dry and irrigated treatment of the Scots pine forest of the years 2003 to 2016 recorded by soil coring
Data_Tab1+2_2005.xlsx
Fine-root traits from roots of ingrowth cores from 2005 after two years of growth in the dry and irrigated treatment of the Scots pine forest
Data_Tab1+2_2016.xlsx
Fine-root traits from roots of ingrowth cores from 2016 after two years of growth, and from roots of the soil-coring sampling from 2016 in the dry and irrigated treatment of the Scots pine forest

en: soil-coring belowground-biomass fine-root-traits ingrowth-cores drought

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: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

de: EnviDat

en: Root-traits

title_for_slug: root-traits

envi

de: Umwelt

belowground-biomass

display_name: belowground-biomass

drought

display_name: drought

fine-root-traits

display_name: fine-root-traits

ingrowth-cores

display_name: ingrowth-cores

soil-coring

display_name: soil-coring


en:
Preferential deposition of snow and dust over complex terrain is responsible for a wide range of environmental processes, and accounts for a significant source of uncertainty in surface mass balances of cold and arid regions. Despite the growing body of literature on the subject, previous studies reported contradictory results on the location and magnitude of deposition maxima and minima. This study aims at unraveling the  governing processes of preferential deposition in neutrally stable atmosphere and to reconcile seemingly inconsistent results of previous works. For this purpose, a comprehensive modeling approach is developed, based on large eddy simulations of the turbulent airflow, Lagrangian stochastic model of particle trajectories, and immersed-boundary method to represent the underlying topography. The model performance is tested against wind tunnel measurements of dust deposition around isolated and sequential hills. A scale analysis is then performed to investigate the dependence of snowfall deposition on the particle Froude and Stokes numbers, which fully account for the governing processes of inertia, flow advection, and gravity. Additional simulations are performed, to test whether the often used assumption of inertialess particles yields accurate deposition patterns. We finally show that our scale analysis provides qualitatively similar results for hills with different aspect ratios.
This dataset contains the results of the LES-LSM model. Each Matlab file contains a 2D array of deposition values (in kg/m2) in each surface node (ix, iy) of the Cartesian grid. The file names are consistent with the simulation numbers listed  in the original paper. For additional information, please refer to "Preferential deposition of snow and dust over hills: governing processes and relevant scales" by F. Comola, M. G. Giometto, S. T. Salesky, M. B. Parlange, and M. Lehning, Journal of Geophysical Research: Atmospheres, 2019.

en: dust particles snow turbulence deposition hill atmosphere

envi

en: Environment

atmosphere

display_name: atmosphere

deposition

display_name: deposition

dust

display_name: dust

hill

display_name: hill

particles

display_name: particles

turbulence

display_name: turbulence


en:
The colonization of cut pine stems by wood-inhabiting insects was investigated at various elevations. The study sites were located in the regions of Aosta Valley (Italy), Valais (Switzerland), and Grisons (Switzerland). In each region, there were two gradients in pine (Pinus sylvestris) forests, with three study sites at 900 m, 1200 m, and 1600 m a.s.l. each. Vital trees were felled in late autumn and the stems were colonized by pioneering xylophagous insects and their natural enemies next spring. Pieces of these stems were cut and exposed in emergence traps in a greenhouse. In each region the survey was done in two consecutive years.
Please contact author for terms of use.

en: elevation insects bark-beetles parasitoids pests pinus gradient predators

en: Pine insects along elevational gradients

bark-beetles

display_name: bark-beetles

elevation

display_name: elevation

gradient

display_name: gradient

insects

display_name: insects

parasitoids

display_name: parasitoids

pests

display_name: pests

pinus

display_name: pinus

predators

display_name: predators


en: This dataset provides HS, TSS and TS50, TS100, TS150 at the station WFJ2 situated on the Weisfluhjoch research site (2536 m asl). It has been created from merging ENET and IMIS datsets to form a continuous timeseries from 1992- present. ENET is at 1 h resolution whereas IMIS is 30 min. This is a level 2 dataset as defined [here](http://models.slf.ch/p/dataset-processing/).

en: weissfluhjoch enet snow-temperatures imis snow-water-equivalent snow-height

en: WFJ2: Snow measurements from the Weissfluhjoch research site, Davos

enet

display_name: enet

imis

display_name: imis

snow-height

display_name: snow-height

snow-temperatures

display_name: snow-temperatures

snow-water-equivalent

display_name: snow-water-equivalent

weissfluhjoch

display_name: weissfluhjoch


en:
943 disturbances in the forest of southern Switzerland have been visited and characterized with various general and specific parameters and the presence absence of woody neophyte species has also been recorded.
A Generalized linear regression modelling approach with a binomial family (link function “logit”) was then used to analyse the effects of these parameters on the presence/absence of the six most widespread neophyte species separately (i.e Ailanthus altissima, Buddleja davidii, R. pseudoacacia, Paulownia tomentosa, Prunus laurocerasus, Trachycarpus fortunei). If needed, the models were refitted with the spmodel R-package to account for the spatial dependence.
The best model for every species have been used to predict the risk of invasion on a 25 X 25m grid of 1’773’603 million of points covering the entire forest area under 1’500 m a.s.l. Predictions over this new set of points have been computed with the predict function (v4.2.1; R core Team, 2023) and using the best select model for every neophyte species. The resulting prediction are available as a raster tiff.
These presence probability risk maps for the forest area of the entire canton Ticino provide a practical  tool to be used in combination with the waldmonitoring.ch data allowing to efficiently monitor the spread of woody neophyte species in new disturbances in the forest.

en: maps neophytes natural-disturbances forest-monitoring anthropic-disturbances

en: Presence probability risk maps neophyte Ticino

de:
Resource Title: neophytes risk map ticino 2024 V3.zip
    Size: 189857690 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/523d7675-93a9-4adf-a03d-883da21f4e91/resource/9a9cae21-b2cb-415f-a0a2-6fcee3516bd1/download/neophytes_risk_map_ticino.zip
    Description: Some models have been refined. These are the updated maps.
Pixel values represent the probability of presence for a given species. 0 = species absent, 1 = the probability that the species is present is 100%.
Four maps per species are available:
- "silvi" = the map shows the presence probability after a silvicultural intervention
- "other" = the map shows the presence probability after anthropic disturbance (e.g. powerline or road maintenance)
- "natural" = the map shows the presence probability after a natural disturbance (e.g. uprooted tree, forest fire)
- "average" =  the map shows the presence probability after a disturbance. The value is the average of the three disturbance types (silvicultural intervention, anthropic disturbance, natural disturbance)

de:
Resource Title: neophytes_risk_map_ticinoV2.zip
    Size: 52855473 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/523d7675-93a9-4adf-a03d-883da21f4e91/resource/bebc66a3-fc80-4f5f-9ee7-afae951b87dd/download/neophytes_risk_map_ticino.zip
    Description: Some models has been refined. Here are the updated raster.
Pixel values represent the proability of presence for a given species. 0 = absent, 1 = 100% of presence

de:
Resource Title: neophytes risk map ticino
    Size: 52879919 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/523d7675-93a9-4adf-a03d-883da21f4e91/resource/f0df95e9-0ca4-4023-99e2-43b9b1be6917/download/risk_map.zip
    Description: Pixel values represent the proability of presence for a given species. 0 = absent, 1 = 100% of presence

anthropic-disturbances

display_name: anthropic-disturbances

forest-monitoring

display_name: forest-monitoring

maps

display_name: maps

natural-disturbances

display_name: natural-disturbances

neophytes

display_name: neophytes


en:
This dataset contains the raw data that is analyzed in the publication entitled "Turbulence in The Strongly Heterogeneous Near-Surface Boundary Layer over Patchy Snow". Please find information on the individual data files in the description of the files.
The data was recorded during a comprehensive field campaign in May and June 2021 at Dürrboden at the end of Dischma valley close to Davos (Graubünden, CH).

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

de:
Resource Title: t2_2m.zip
    Size: 722480736 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/b060a56e-7c4f-4291-ac8d-c4d492455c67/resource/92f20d5d-be74-4586-a567-41195b9d7469/download/t2_2m.zip
    Description: Raw eddy covariance data from tower 2 at 2m height. Instrument is Campell Scientifc CSAT 3

de:
Resource Title: t2_1m.zip
    Size: 1076784960 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b060a56e-7c4f-4291-ac8d-c4d492455c67/resource/d788f7aa-6c97-4274-b560-e60910ee9c76/download/t2_1m.zip
    Description: Raw eddy covariance data from tower 2 at 1m height. Instrument is Campell Scientific IRGASON

de:
Resource Title: kaijo.zip
    Size: 31515684 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b060a56e-7c4f-4291-ac8d-c4d492455c67/resource/4cf92a16-33be-40ca-a415-3dd979eccc5c/download/kaijo.zip
    Description: Raw eddy covariance data from the short-path ultrasonic ("Kaijo") at 0.3m above the snow

de:
Resource Title: aws.zip
    Size: 869784619 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/b060a56e-7c4f-4291-ac8d-c4d492455c67/resource/79446543-af17-47ec-a794-2e56dfe2333d/download/aws.zip
    Description: Raw eddy covariance data from the automatic weather station (AWS). Instrument is Young Model 81000

de:
Resource Title: t2_3m.zip
    Size: 906522928 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/b060a56e-7c4f-4291-ac8d-c4d492455c67/resource/a850ebcc-a124-4e27-8c90-8781e10522ae/download/t2_3m.zip
    Description: Raw eddy covariance data from tower 2 at 3m height. Instrument is Campell Scientifc CSAT 3

de:
Resource Title: irdata.zip
    Size: 1240628362 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b060a56e-7c4f-4291-ac8d-c4d492455c67/resource/6f7f0d92-6dd4-440a-b581-19b30b65c942/download/irdata.zip
    Description: IR-data that is visualized in the video

atmospheric-turbulence

display_name: atmospheric-turbulence

eddy-covariance-measurements

display_name: eddy-covariance-measurements

patchy-snow-cover

display_name: patchy-snow-cover

snow-melt

display_name: snow-melt

surface-heat-exchange

display_name: surface-heat-exchange


en: This study investigated multi-year drought impacts on beech forests through a unique large-scale monitoring of 963 individual beech trees, which showed either premature leaf discoloration during the drought in summer 2018 or no visible damage. We conducted the study in two highly drought-affected regions in northern Switzerland and one less drought-affected region located further south. We quantified the development of crown dieback and tree mortality as well as secondary drought damage, i.e. the presence of bleeding cankers and bark beetle infestations, in these trees for three consecutive years. We also determined the impact of several potential climate- and stand-related (predisposing) factors  on  mortality  and  drought  legacy  processes.

en: drought-2018 european-summer-drought leaf-senescence forests fagus-sylvatica growth-reaction-to-drought-stress

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: Data on multi-year drought impacts on European beech in northern Switzerland

european-summer-drought

display_name: european-summer-drought

fagus-sylvatica

display_name: fagus-sylvatica

forests

display_name: forests

growth-reaction-to-drought-stress

display_name: growth-reaction-to-drought-stress

leaf-senescence

display_name: leaf-senescence


en:
The data presented here were prepared for publication in form of a data paper. The dataset presents an update of the information in Didion M, Herold A, Vulovic Z, Nitzsche J, Stillhard J (2022) Datasets for deriving functions for the stem- and branchwood volume in the Swiss National Forest Inventory. EnviDat. doi:https://www.doi.org/10.16904/envidat.358. The new dataset is based on an alternative, more accurate and comprehensive dataset, that was identified as the source of the dataset in Didion et al. 2022. It includes additional data, including newly digitized information.
The dataset includes section-wise stem measurements on 40’349 felled individual trees and empirically derived coarse (diameter -= 7 cm) and fine branch volume of 27’297 and 18’980, respectively, individual trees. The data were collected between 1888 and 1974 across Switzerland covering a large topographic gradient and a diverse species range. The dataset has undergone quality controls and due to its origin from 768 plots of the Experimental Forest Management project long-term consistency is assured.

en: section-wise-diameter branchwood stemwood growing-stock tree-volume allometry

envidat

en: EnviDat: the Environmental Data Portal

en: A dataset of 40000 trees with section-wise measured stem diameter and length and volume of branches from across Switzerland

de:
Resource Title: outdated_Stem&Branchchwood_2024-02-29.txt
    Size: 8114251 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/b23a6bfa-3a55-4677-91e2-d32f91945574/resource/cb7d58c5-e952-4a4e-af24-b590d7a25d87/download/stembranchchwood_2024-02-29.txt
    Description: dataset with section-wise stem diameter and branchwood volume measurements. For column definitions see Column_definitions.pdf.

de:
Resource Title: Column_definitions.pdf
    Size: 73134 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b23a6bfa-3a55-4677-91e2-d32f91945574/resource/6ac26fd6-4c7b-47d3-86ee-aaa59ab7f5d0/download/column_definitions.pdf
    Description: definitions of data in columns contained in the dataset Stem&Branchchwood_2024-02-29.txt

de:
Resource Title: StemBranchwood_Didionetal_revised_for publication.pdf
    Size: 306424 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b23a6bfa-3a55-4677-91e2-d32f91945574/resource/c8499517-f803-45e6-a7f2-7cde8e6afd3c/download/stembranchwood_didionetal_revised_for-publication.pdf
    Description: Revised version of the initial submission StemBranchwood_Didionetal_initialsubmission.pdf after review.

de:
Resource Title: Background.pdf
    Size: 132521 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b23a6bfa-3a55-4677-91e2-d32f91945574/resource/9006c9b7-0dc0-46f9-8b24-8aadef0ca654/download/background.pdf
    Description: additional background information on this work

de:
Resource Title: Stem&Branchchwood_2024-04-25.txt
    Size: 8211522 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/b23a6bfa-3a55-4677-91e2-d32f91945574/resource/8ba7cb02-3d90-409f-9113-4e9aa5e7d33c/download/stembranchchwood_2024-04-25.txt
    Description: Updated dataset of outdated_Stem&Branchchwood_2024-02-29.txt, including corrections to the assignment of tree species to NFI main species and location information for two additional sites.

de:
Resource Title: StemBranchwood_Didionetal_initialsubmission.pdf
    Size: 1174376 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b23a6bfa-3a55-4677-91e2-d32f91945574/resource/fbe9e951-31f7-43d3-ba1c-f8176380ee3f/download/stembranchwood_didionetal_forpublication.pdf
    Description: manuscript submitted for publication.

allometry

display_name: allometry

branchwood

display_name: branchwood

growing-stock

display_name: growing-stock

section-wise-diameter

display_name: section-wise-diameter

stemwood

display_name: stemwood

tree-volume

display_name: tree-volume


en:
Two raster maps (10m resolution) of: I) the most suitable extraction method for wood in the Swiss forest, and II) the overall suitability of the Swiss forest for economic wood extraction and transport.
A modern forest road system is important for the efficient management of forests. In order to assess the current forest accessibility in Switzerland on a comprehensive basis, the entire Swiss forest was investigated using a consistent methodology. In our model, wood extraction from the stand to the road and on-road transport are analysed in combination.
Suitable extraction methods for each forest parcel (10m x 10m) were determined using an approach in which ground-based, cable-based and air-based transport are distinguished. First, the areas for ground- and cable-based extraction were delineated. The trafficability of the forest areas was assessed based on the terrain and soil characteristics; trafficable areas also had to be connected to a forest road. To evaluate the suitability for cable-yarding (up to a maximum distance of 1500 m), terrain and possible obstacles (e.g., power lines) were considered. The remaining forest area, which was not suitable for either ground-based or cable-based methods, was assigned to the "helicopter" category. As a result of this analysis, a map of the most suitable skidding method for each plot could be created. When several methods were possible for a parcel, the priority was ground-based over cable-based over air-based.
Road transport was investigated using network analysis, based on the data set "Forest access roads 2013" from the Swiss National Forest Inventory (NFI), which contains information on width and weight limits of roads in the forest and up to the superordinate main road network. Thus, in addition to the distance, the largest type of vehicle allowed on the respective removal route could also be taken into account.
Based on the extraction method and the weight limits for on-road transport, the forest area was divided into three categories: 1) meets the requirements for efficient forest management (all forest parcels with ground-based extraction method or mobile cable-yarding, transport weight limit at least 28 tons); 2) limited suitability for efficient forest management; and 3) not suitable for efficient forest management (forest parcels in the "helicopter" category or transport with trucks under 26 tons).
The resulting maps cannot provide an accurate classification for each forest parcel. Missing or incorrect roads in the road dataset, insufficient information on ground trafficability or other local factors, the limitation to only three possible extraction systems, and failure to account for anchor trees, extraction methods changing over small distances, and unrealistically short cable-yarding distances can cause the model results to deviate from the assessment by an expert with knowledge of the local conditions. Also, protected areas were not excluded and harvesting intensity was not taken into account. The advantage of the method is that consistent criteria are used for the entire Swiss forest, making the results comparable throughout Switzerland.
The data are managed at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and are available to third parties on request. (NFI data policy: https://www.lfi.ch/dienstleist/daten.php)
Input data used:
- Forest road dataset of the NFI4 (only truck roads from 3.0 m width and 26 t carrying capacity) (2016).
- NFI forest mask, 10 m resolution (2015)
- Digital elevation model, 10m resolution (based on swissALTI3D 2016)
- Slope map, 10m resolution (based on swissALTI3D 2016)
- Soil suitability map, 10m resolution (based on soil suitability map BFS 2000)
- Obstacles for cable lines, 10m resolution (buildings, major roads, power lines, railroads, based on swissTLM3D 2016)

en: switzerland forest economic-efficiency wood-extraction wood-harvesting forest-accessibility forest-roads timber-transport

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: Accessibility of the Swiss forest for economic wood extraction (2021)

envi

en: Environment

de:
Resource Title: Data Request "Forest Accessibility"
    Size: 23228715 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/47871f44-7c5c-452e-b755-ff5643abb853/resource/b1a225d8-9db7-4a62-9d6a-224673f88b01/download/mapguete_merge_lv95_cog2.tif
    Description: Raster map (10m resolution) of the overall suitability of the Swiss forest for economic wood extraction and transport

format: TIFF

media_type: image/tiff

de:
Resource Title: Data Request "Extraction Method"
    Size: 28660858 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/47871f44-7c5c-452e-b755-ff5643abb853/resource/e57bf80a-9c2b-40d5-8938-5b9dad24549b/download/maperntemethoden_merge_lv95_cog2.tif
    Description: Raster map (10m resolution) of the most suitable extraction method for wood in the Swiss forest

economic-efficiency

display_name: economic-efficiency

forest

display_name: forest

forest-accessibility

display_name: forest-accessibility

forest-roads

display_name: forest-roads

switzerland

display_name: switzerland

timber-transport

display_name: timber-transport

wood-extraction

display_name: wood-extraction

wood-harvesting

display_name: wood-harvesting


en:
This dataset contains simulation data for *"Influence of Air Flow Features on Alpine Wind Energy Potential" (Kristianti et al., 2024).*
•	The WRF_dia2702 and WRF_dia1103 folders contain the namelist.wps, namelist.input, and output files from the simulation in the Diablerets region on 27/02/2021 and 11/03/2021, respectively.
•	The WRF_luk2310 and WRF_luk0912 folders contain the namelist.wps, namelist.input, and output files from the simulation in the Lukmanier region on 23/10/2020 and 09/12/2020, respectively.
•	The postprocessing file contains Python codes used to create figures in Kristianti et al. (2024).
**Notes:**
•	Topography input is provided by Gerber et al. (2021).
•	Simulations are run using the COSMO-WRF model developed by Gerber et al. (2018).
•	Visualization by Python code uses wrf-python provided by Ladwig et al. (2017).
*This dataset was produced by the EDGE consortium sponsored by the Swiss Federal Office of Energy's SWEET programme, Swiss National Science Foundation (SNSF): Grant 179130, and the Swiss National Supercomputing Centre (CSCS) projects s938, s1115 and s1242.*

en: numerical-simulation grayzone complex-terrain cosmo-wrf wrf

en: COSMO-WRF Dataset for Swiss Alps Simulations in Gray-Zone Resolution

envi

de: Umwelt

de:
Resource Title: WRF_luk0912.zip
    Size: 10844792422 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/WRF_luk0912.zip
    Description:

de:
Resource Title: WRF_dia1103.zip
    Size: 9126805504 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/WRF_dia1103.zip
    Description:

de:
Resource Title: postprocessing.zip
    Size: 4301 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/postprocessing.zip
    Description:

de:
Resource Title: WRF_dia2702.zip
    Size: 8482560410 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/WRF_dia2702.zip
    Description:

de:
Resource Title: WRF_luk2310.zip
    Size: 9985798963 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/WRF_luk2310.zip
    Description:

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

grayzone

display_name: grayzone

numerical-simulation

display_name: numerical-simulation

wrf

display_name: wrf


photogrammetric-drone-data-gruenbodeli

en:
We conducted various drone flights at Grüenbödeli near Davos with the Sony RX1R II mounted on a Wingtra drone during 2020/21/22. The data was processed with the Agisoft Metashape Professional Software.
The following products are available for download:
- DSM 10cm resolution
- Orthomosaic 3cm/25mm resolution
- Snow Raster 10cm resolution
- original RGB images

en: drone-data photogrammetry uav snow-depth-mapping orthophoto wingtra dsm

en: Photogrammetric Drone Data Grüenbödeli

title_for_slug: photogrammetric-drone-data-gruenbodeli

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

snow-depth-mapping

display_name: snow-depth-mapping

uav

display_name: uav

wingtra

display_name: wingtra


en: To map and assess snow depth on different dates, 9 flights were conducted in the winter season of 2020/21 at the Latschüelfurgga in Davos. The data was captured with a Sony RX1R II mounted on a Wingtra drone and was processed with the Agisoft Metashape software. High-resolution DSMs, orthomosaics and snow height rasters, as well as the original RGB images from each flight are available.

en: orthophoto photogrammetry dsm uav snow-depth-mapping wingtra drone-data

en: Photogrammetric Drone Data Latschuelfurgga


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

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

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

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

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

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

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed


en: We present forecasts of land-use/land-cover (LULC) change for Switzerland for three time-steps in the 21st century under the representative concentration pathways 4.5 and 8.5, and at 100-m spatial and 14-class thematic resolution. We modelled the spatial suitability for each LULC class with a neural network (NN) using -200 predictors and accounting for climate and policy changes. We used data augmentation to increase performance for underrepresented classes, resulting in an overall quantity disagreement of 0.053 and allocation disagreement of 0.15, which indicate good model performance. These class-specific spatial suitability maps outputted by the NN were then merged in a single LULC map per time-step using the CLUE-S algorithm, accounting for LULC demand for the future and a set of LULC transition rules. As the first LULC forecast for Switzerland at a thematic resolution comparable to available LULC  maps for the past, this product lends itself to applications in land-use planning, resource management, ecological and hydraulic modelling, habitat restoration and conservation.

en: modelling land-use land-cover landscape-change machine-learning landscape

envidat

en: EnviDat: the Environmental Data Portal

en: High resolution land use forecasts for Switzerland in the 21st century

de:
Resource Title: Code.zip
    Size: 407530 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/69945cd4-3dfc-4b1d-bdd4-e88cc577c3c9/resource/593cc9c4-deb1-4637-a328-9d68f0e15cd6/download/code.zip
    Description: Code used to produce the Land-use/land-cover forecasts for Switzerland across the 21st century at 100-m resolution.

The script is based on input data which are not included as they are not freely available, therefore it will not run as it is. These input data are described in the accompanying publication on Data Science access to them can be requested to their owners. Alternatively the code can be modified to run on other data.

de:
Resource Title: swiss_lulc_forecast_21th_century.zip
    Size: 16438707 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/69945cd4-3dfc-4b1d-bdd4-e88cc577c3c9/resource/347fffe5-f3cb-4309-914b-9057a30a32db/download/swiss_lulc_forecast_21th_century.zip
    Description: Compressed (.zip) file containing six georeferenced raster files in the GeoTIFF format with embedded coordinate reference system, and a table (comma separated values, .csv) encoding a colour palette for plotting (HEX colour codes for each class). GeoTIFF file names include the time-step and the RCP (e.g. “LULC_2020_2049_RCP45.tiff”). Each raster file has 3484x2207 square pixels (i.e. 7.7 megapixels) and is projected in the Swiss coordinate system CH1903+/LV95 (EPSG:2056).

land-cover

display_name: land-cover

land-use

display_name: land-use

landscape

display_name: landscape

landscape-change

display_name: landscape-change

machine-learning

display_name: machine-learning

modelling

display_name: modelling


en:
snowBedFoam 1.0. is a snow transport solver implemented in the computational fluid dynamics software OpenFOAM. It is adapted from the standard multi-phase flow solver DPMFoam for application in snow-influenced environments.
To simulate aeolian snow transport, snowBedFoam 1.0. handles coupled Eulerian–Lagrangian phases, which involve a finite number of particles (snow) spread in a continuous phase (air). The snow erosion and deposition are modelled through physics-based equations similar to the ones employed in the well-established LES-Lagrangian Stochastic Model (Comola and Lehning, 2017 ; Sharma et al., 2018 ; Melo et al., 2022). This modelling approach is computationally intensive and thus adapted to simulate snow movement and distribution on small scale terrain.
First, snowBedFoam 1.0. was applied to topographical data collected on Arctic sea ice during the MOSAiC expedition (Clemens-Sewall, 2021). Together with atmospheric data from the MOSAiC Met City (Shupe et al., 2021) used for the fluid forcing, the model was able to accurately simulate the zones of erosion and deposition of snow along a complex ice ridge structure (Hames et al., 2022).
Second, snowBedFoam 1.0. was used to simulate the snow distribution around the German Antarctic research station Neumayer Station III. The effect of snow properties, fluid forcing and aerodynamic structures on the snow accumulation were assessed.
snowBedFoam 1.0 was implemented in 2 different OpenFOAM versions, namely OpenFOAM-2.3.0 and OpenFOAM-5.0. The latter offers more options for turbulence models and boundary conditions. The fundamental model equations were not changed from one implementation to the other, thus both still correspond to snowBedFoam 1.0. The two branches are called snowBedFoam-v1-2.3.0 (OpenFOAM-2.3.0)  and snowBedFoam-v1-5.0 (OpenFOAM-5.0). The core codes of snowBedFoam 1.0. are directly accessible on the WSL/SLF GitLab repository (more details in the Resources section).

en: snow-transport arctic-sea-ice antarctica openfoam snow-deposition mosaic

en: snowBedFoam: an OpenFOAM Eulerian-Lagrangian solver for modelling snow transport

envi

en: Environment

de:
Resource Title: Paper Draft
    Size: 3025070 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/0c5b7c6e-afa2-4a08-bb12-351648d1e1f9/download/snowbedfoam_mosaicseaice.pdf
    Description: This is the initial draft of the paper where the snowBedFoam 1.0. results are tested against Terrestrial Laser Scan (TLS) measurements of snow dynamics on Arctic sea ice (MOSAiC expedition). It highlights the numerical limitations of our model as well as the measurement uncertainties, which may occur in such extreme environments.

de:
Resource Title: snowBedFoam-v1-5.0
    Size: 40167324 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/87b34f08-3ae1-44d3-bd5a-aa502f8e83c3/download/snowbedfoam-v1-5.0.zip
    Description: OpenFOAM-5.0 scripts containing the implemented Eulerian-Lagrangian snow transport model.

The code file provided here is not updated. The most recent version of the script can be found on the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/atmospheric-models/snowbedfoam-v1-0.git

de:
Resource Title: snowBedFoam-v1-2.3.0
    Size: 38674582 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/056080d7-e68d-4cb8-9b63-34ebf5998fe7/download/snowbedfoam-v1-0-main.zip
    Description: OpenFOAM-2.3.0. scripts containing the implemented Eulerian-Lagrangian snow transport model.

The code file provided here is not updated. The most recent version of the script can be found on the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/atmospheric-models/snowbedfoam-v1-0.git

de:
Resource Title: MOSAiC Met City preliminary (Level 2) wind data
    Size: 37737 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/a9b2c876-ac90-4aa5-ab56-a06e82221894/download/mosaic_mettowerdata_level2.zip
    Description: Extract from the preliminary MOSAiC atmospheric data (Level 2) for the time period 6th to 13th of November, 2019.
This data was used to set up the fluid forcing parameters in the snowBedFoam simulations on MOSAiC sea ice. It is being published in this repository with the kind permission from Matthew Shupe and his team.
The final processed and quality controlled version of this dataset (Level 3) has not been published yet. A complete reference will be added in this description once it is released.

de:
Resource Title: Snowdrift measurements around Neumayer Station III
    Size: 32270 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/a6d100a5-ab97-41f4-b45a-dbed9fb30619/download/nm3-measurements.zip
    Description: Files containing the topographical data barometrically measured in June 2009 around the German Antarctic Research station Neumayer III. Those measurements are compared to the snowBedFoam simulations to assess the ability of the model to reproduce real snow distribution observations.

de:
Resource Title: Neumayer III simulations
    Size: 296665509 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/6bce1ab3-5fab-4fe6-afb0-7aa90760e9d2/download/nm3-simulations.zip
    Description: Snow distribution results around Neumayer Station III obtained for the sensitivity analysis and comparison to measurements. The file contains several sub-folders, namely:
-COMP: simulation output for the comparison to measurements;
-FLOW: simulation output for the study of wind forcing impact;
-simulation_exampleCase: example case of a snowBedFoam simulation with the reference Neumayer Station mesh;
-SNOW: simulation output for the study of snow properties impact;
-STRUCT: simulation output for the study of structure properties impact.

antarctica

display_name: antarctica

arctic-sea-ice

display_name: arctic-sea-ice

mosaic

display_name: mosaic

openfoam

display_name: openfoam

snow-deposition

display_name: snow-deposition

snow-transport

display_name: snow-transport


en:
This dataset provides distribution data of lichens in Switzerland of the National Data and Information Centre, called Swiss Lichens. SwissLichens is a partner of InfoSpecies, the network of Swiss data and information centres for fauna, flora and fungi. One of its main objectives is to document the spatial and temporal distribution of species in Switzerland.
The SwissLichens database currently contains more than 120’000 georeferenced lichen observations, distributed throughout Swizerland. The oldest observations date back to 1790. A large portion of the records dtae from the last two decades of the last century to the present day. The database is continuously updated with new findings. 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.
Each record consists of the species name, information of the location (Swiss Coordinates, precision of the coordinates, elevation above sea level, municipality and canton), the date of observation, the ecotype (epiphytic, terricol, lignicol, saxicol), as well as information on the conservation status of the species (red list status, conservation priority status, status in the Nature and Cultural Heritage Act). Information on the ecology (habitat, substrate) is partially available.
They are free of charge for research projects and can be requested from InfoSpecies using a form.
Licence under www.infospecies.ch. Data is free of charge for research projects and available on request.

en: biodiversity switzerland lichen-distribution lichen-conservation national-data-centre swisslichens lichens

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: SwissLichens - Distribution of lichens in Switzerland

envi

de: Umwelt

biodiversity

display_name: biodiversity

lichen-conservation

display_name: lichen-conservation

lichen-distribution

display_name: lichen-distribution

lichens

display_name: lichens

national-data-centre

display_name: national-data-centre

swisslichens

display_name: swisslichens

switzerland

display_name: switzerland


en:
This study examines the siting scenarios for renewable energy infrastructure (REI) in Switzerland, incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed.
MARXAN was run for 2 versions: a) without ground-mounted open space PV infrastructure (excl. OS) and b) with ground-mounted open space PV infrastructure (incl. OS). In each version optimization was done using ecological costs (ECUess) or social costs (ECUsoc) in a regular grid of 4x4km (planning unit).
File:
PU_data.shp: compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.
Headers are described below:
X01 = Planning_units (PUs)
X02 = incl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)
geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).
For MARXAN optimizations (for meaning of standard files in MARXAN see https://scholar.google.ch/scholar_url?url=https://courses.washington.edu/cfr590/software/Marxan1810/marxan_manual_1_8_2.pdf&hl=de&sa=X&ei=NAWHZI6JJ8PFmAGMo47oDQ&scisig=AGlGAw-DBrsV4kUzkR6GkN1jtG66&oi=scholarr), pu_data.shp was used to generate MARXAN files input.dat, pu.dat, puvfeat.dat, spec.dat.
Coordinate Reference System: CH1903 / LV03. EPSG: 21781.

en: social-acceptance ecosystem-services marxan energy photovoltaic landscape wind-power optimization spatial-planning

en: Optimizing renewable energy siting in the Swiss landscape

ecosystem-services

display_name: ecosystem-services

energy

display_name: energy

landscape

display_name: landscape

marxan

display_name: marxan

optimization

display_name: optimization

photovoltaic

display_name: photovoltaic

social-acceptance

display_name: social-acceptance

spatial-planning

display_name: spatial-planning

wind-power

display_name: wind-power