en:
**Article: "Species Species composition shapes canopy microclimate and foliar traits without modifying photosynthetic thermal acclimation in a beech-oak ecotone"**
Authors: **Janisse Deluigi**, Charlotte Grossiord, Alvaro Poretti, Lorenz Walthert, Christoph Bachofen
The study was conducted along a south-exposed elevational gradient ranging from 770 to 860 m a.s.l. in a central alpine valley (46°10`14``N, 7°10`01``E, Saillon, Switzerland). Along the elevational gradient, we selected three forest stands characterized by high coverage of mature European beech (Fagus sylvatica L.) and downy oak (Quercus pubescens Willd.) trees, with are naturally distributed in three species combinations: one pure beech stand (i.e., at least 80% of the basal area) at 860 m a.s.l. , one mixed beech-oak stand (i.e., similar relative abundances of the two species – at least 40% of the basal area each – and minimal presence of other tree species) at 785 m a.s.l., and one pure oak stand (i.e., at least 80% of the basal area) at 770 m a.s.l. An additional forest clearing of around 0.04 ha next to the pure oak stand was selected as reference for conditions outside the forest  (i.e., clearing or gap). At each forest stand, we selected five healthy, mature, overstory trees per tree species, resulting in a total of 20 individuals (5 individuals x 2 species x 2 mixture combinations, i.e., mixed vs. pure forest stand).
**Dataset 1: Climatic conditions at the study sites**
In 2023 and 2024 we monitored climatic conditions at each forest stand and in the clearing using climatic stations with air temperature, relative humidity and radiation sensors installed at 1.8 m height in a central position relative to the selected trees for each site. The meteo station in the clearing site had additionally a rain gauge and wind sensor.
**Dataset 2: Tree and canopy sizes**
Once in 2023 we measured tree height and diameter at breast height of all selected trees using a vertex hypsometer and a caliper. In August 2023 and 2024 we estimated canopy size measuring the height at which canopy starts (CS), canopy depth (= tree height - CS) and maximum canopy radius as the average of two orthogonal measurements (south and east direction) using a vertex hypsometer. We also estimated canopy total leaf area using species- and site-specific allometric equations from collected branches upscaled to the tree level.
**Dataset 3: Microclimatic conditions measured in tree canopies**
We monitored canopy microclimatic conditions in 2023 and 2024 attaching one air temperature and air humidity sensor (HOBO) on one branch at the top and one branch at the bottom of the south-exposed side of the canopy for each selected tree in June 2023.
**Dataset 4: Physiological traits**
During three field campaigns (June, August, September) per year (2023, 2024) we measured temperature response curves of leaf net photosynthesis and dark respiration. As in-situ measurements were not possible, tree-climbers collected one representative branch at the top and the bottom of the canopy from each selected tree at each site. Estimates of the thermal optimum of photosynthesis (Topt), photosynthetic rate at Topt (Aopt), respiration rate at a standard temperature of 25°C (R25) and thermal sensitivity of respiration (Q10) were extracted from the temperature response curves of photosynthesis and respiration, respectively.
Leaf water potentials at predawn and midday, as well as leaf chlorophyll content, were also measured on the same day for each selected tree at each site.
**Dataset 5: Physiological traits - specific leaf area and leaf size**
In August 2023 and 2024 we collected a random subset of 10 representative fully developed leaves of different sizes from a representative branch harvested at the top and bottom of the canopy of each selected tree to estimate the specific leaf area (SLA) and leaf size (average of the 10 leaves).
**Dataset 6: Soil water potentials**
Hourly soil water potentials and soil temperature were recorded during the two years of measurements (2023, 2024) at each forest site at different soil depths: 20 cm, 80 cm, 140 cm and 200 cm.

en: climate-change forest-canopy respiration species-interaction acclimation photosynthesis

en: Dataset Article "Species composition shapes canopy microclimate and foliar traits without modifying photosynthetic thermal acclimation in a beech-oak ecotone", Deluigi et al.

en:
Resource Title: 4_Physiological measurements Saillon 2023-2024.csv
    Size: 46961 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/e9f0e85f-b12b-4b29-a4e3-44600d37c34a/download/4_physiological-measurements-saillon-2023-2024.csv
    Description: #Dataset 4: Physiological traits
Year = year of measurement
Campaign = campaign of measurement (June, August, September)
Site	= forest site (pure beech, mixture, pure oak)
Species	= tree species (B = beech, O = downy oak)
Tree = tree ID within each site (5 trees per site and tree species)
Canopy_level = canopy level (top, bottom)
WP_predawn = leaf water potential at predawn (MPa)
WP_midday = leaf water potential at midday (MPa)
CHL = chlorophyll content (CCI)
Date = date of measurement (mm/dd/yyyy)
Aopt = photosynthetic rate at thermal optimum (µmol m-2 s-1)
sd_err_Aopt = standard error of Aopt estimates from temperature response curves of photosynthesis
b	= curvature coefficient of the temperature response curve of photosynthesis
sd_err_b = standard error of b estimates  from temperature response curves of photosynthesis
Topt = thermal optimum of photosynthesis (°C)
sd_err_Topt = standard error of Topt estimates from temperature response curves of photosynthesis
R25	= respiration rate at a standard temperature of 25°C (µmol m-2 s-1)
sd_err_R25 = standard error of R25 estimates from temperature response curves of dark respiration
Q10	= thermal sensitivity of respiration (i.e., increase in respiration rates for a 10°C increase in measurement temperature)
sd_err_Q10 = standard error of Q10 estimates from temperature response curves of dark respiration
Collection_time = time of the day at which the branch was collected (morning, midday)

en:
Resource Title: 3_Microclimatic measurements day and night Saillon 2023-2024.csv
    Size: 179804 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/69ce25f7-f502-4461-8336-0e0400182d03/download/3_microclimatic-measurements-day-and-night-saillon-2023-2024.csv
    Description: #Dataset 3: Microclimatic conditions measured in tree canopies
Site	= forest site (pure beech, mixture, pure oak)
Species	= tree species (B = beech, O = downy oak)
Tree = tree ID within each site (5 trees per site and tree species)
Time = time of the day (HH:MM:SS)
Tair_top	= air temperature at the top of the canopy (°C)
Tair_low	= air temperature at the bottom of the canopy (°C)
VPD_top = vapor pressure deficit at the top of the canopy (kPa)
VPD_low = vapor pressure deficit at the bottom of the canopy (kPa)
Tair_gap	= air temperature in the clearing (i.e., outside the forest) (°C)
VPD_gap = vapor pressure deficit in the clearing (kPa)
Tair_T_L	= difference in air temperature between the top and bottom of the canopy (°C)
VPD_T_L = difference in vapor pressure deficit between the top and bottom of the canopy (kPa)
Tair_T_gap	 =  difference in air temperature between the top of the canopy and the clearing (°C)
VPD_T_gap = difference in vapor pressure deficit between the top of the canopy and the clearing (kPa)
Tair_L_gap	= difference in air temperature between the bottom of the canopy and the clearing (°C)
VPD_L_gap = difference in vapor pressure deficit between the bottom of the canopy and the clearing (kPa)

en:
Resource Title: 2_Tree size and canopy Saillon 2023-2024.csv
    Size: 4465 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/b1b06195-b354-404b-b2e2-c44217446c54/download/2_tree-size-and-canopy-saillon-2023-2024.csv
    Description: #Dataset 2: Tree and canopy sizes
Year = year of measurement
Site = forest site (pure beech, mixture, pure oak)
Species = tree species (B = beech, O = downy oak)
Tree = tree ID within each site (5 trees per site and tree species)
height = tree height (m)
DBH = diameter at breast height (cm)
sapwood_depth = depth of sapwood from tree cores (cm)
sapwood_area = area of sapwood in tree trunks (cm2)
Al_As = ratio between branch total leaf area (Al, cm2) and branch section area (As, cm2) from sampled branches
WT_LA = canopy total leaf area estimated for each tree using allometric equations (m2)
radius_max = average maximum radius of the canopy (m) from two orthogonal measurements
radius_east = radius of the canopy (m) measured direction east
radius_south = radius of the canopy (m) measured direction south
crown_start = height at which the canopy starts (m)
canopy_depth = difference between tree height and height at which the canopy starts (m)
Asymetric = TRUE/FALSE to indicate whether the canopy was asymetric
Direction = direction to which the canopy was asymetric

en:
Resource Title: 1_Climatic conditions at the study sites Saillon 2023-2024.csv
    Size: 22240297 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/85ccee2d-7e73-40b2-ad63-c6ce1b030e26/download/1_climatic-conditions-at-the-study-sites-saillon-2023-2024.csv
    Description: #Dataset 1: Climatic conditions at the study sites
Datetime = date and time (CEST)
PAR	= photosynthetic photon flux density (µmol m-2 s-1)
RH = air relative humidity (%)
Temp = air temperature (°C)
site = forest site (pure beech, mixture, pure oak) and clearing (gap)
date = date (mm/dd/yyyy)
Precip	= rain precipitation (mm)
Wind = wind speed (m s-2)
Gusts = wind gusts (m s-2)
Direction = direction of the wind (°)
month = month of the year (1:12)
VPD = vapor pressure deficit (kPa)
Time = time of the day (HH:MM:SS)
Year = year of measurement

en:
Resource Title: 6_Soil moisture and temperature Saillon 2023-2024.csv
    Size: 16861102 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/305fbfa7-56fa-4f62-88d2-f5b87cb51452/download/6_soil-moisture-and-temperature-saillon-2023-2024.csv
    Description: #Dataset 6: Soil water potentials
Datetime = date and time (CEST)
Site	= forest site (pure beech, mixture, pure oak)
Depth	= soil depth (cm)
WP_corr	 = soil water potential corrected by temperature (MPa)
Temp = soil temperature (°C)
Date = date of measurement (mm/dd/yyyy)
Year = year of measurement

en:
Resource Title: 5_SLA and leaf size measurements Saillon 2023-2024.csv
    Size: 4444 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6d43eea8-791c-440c-9f96-d02098025f64/resource/b825d938-273b-43a5-83a8-9d5c89c895e5/download/5_sla-and-leaf-size-measurements-saillon-2023-2024.csv
    Description: #Dataset 5: Physiological traits - specific leaf area and leaf size
Year = year of measurement
Site	= forest site (pure beech, mixture, pure oak)
Species	= tree species (B = beech, O = downy oak)
Tree = tree ID within each site (5 trees per site and tree species)
Canopy_level = canopy level (top, bottom)
SLA	= specific leaf area (cm2 g-1)
leaf_size = leaf area (cm2)

acclimation

display_name: acclimation

climate-change

display_name: climate-change

forest-canopy

display_name: forest-canopy

photosynthesis

display_name: photosynthesis

respiration

display_name: respiration

species-interaction

display_name: species-interaction


$oid: OBSOLETE

en: This repository hosts the experimental data accompanying our publication "Testing the strength of buried surface hoar weak layers under combined compression and shear loading" submitted to Geophysical Research Letters.

en: experiment strength slab-avalanche weak-layer snow-mechanics

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: experiments_dataset_v1.csv
    Size: 9277 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/cfac66e0-5864-4ee4-a2fc-470b1168927c/resource/d5fff209-9307-44cf-aa73-c43bdcb873d5/download/experiments_dataset_v1.csv
    Description: Dataset containing the experimental results. The column "CT ID" allows to link this data to the CT parameter dataset.

format: CSV

media_type: text/csv

en:
Resource Title: Example_Video.mp4
    Size: 7402947 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/cfac66e0-5864-4ee4-a2fc-470b1168927c/resource/e0ec0699-86b1-462c-ae52-aab3ab644f26/download/20250601_sh25-1_ps2s4_30deg2.mp4
    Description: Example video of an biaxial experiment performed at a reaction-force angle of approximately 30 degree (sample SH25-1_PS2S4).

en:
Resource Title: CT_dataset_v1.csv
    Size: 9605 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/cfac66e0-5864-4ee4-a2fc-470b1168927c/resource/66fe8b1c-f13d-473a-8e9e-731ddb6ae09b/download/ct_dataset_v1.csv
    Description: Dataset containing the microstructural parameters obtained from the CT data.

experiment

display_name: experiment

slab-avalanche

display_name: slab-avalanche

snow-mechanics

display_name: snow-mechanics

strength

display_name: strength

weak-layer

display_name: weak-layer


en:
Monitoring fish diversity through eDNA metabarcoding along the Kinabatangan river
In 2019, water samples were collected in 25 locations along the Kinabatangan in Malaysia. Samples were taken either from a boat or by filtering from the side of the river. At each station, two filtration replicates were performed using a peristaltic pump to conduct environmental DNA (eDNA) sampling. Each filtration targeted a maximum duration of 30 min, during which approximately 30 liters of water were filtered through each filtration capsule. After filtration, the water inside the capsules was removed, and the capsules were filled with 50 ml of conservation buffer for preservation at room temperature. We followed strict contamination control protocols throughout both the fieldwork and laboratory processes, adhering to the guidelines of Valentini et al. (2016). To prevent contamination, each sample was processed using disposable gloves and single-use filtration equipment. We use primers for eukaryote and fish. The MiSeq Reagent Kit v3 (2x75 bp) (Illumina, San Diego, CA, USA) was used for paired-end sequencing at a theoretical sequencing depth of 200,000 reads per sample.
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: metabarcoding teleo malaysia edna fish

en: Environmental DNA Freshwater Malaysia Kinabatangan 2019

edna

display_name: edna

fish

display_name: fish

malaysia

display_name: malaysia

metabarcoding

display_name: metabarcoding

teleo

display_name: teleo


en:
Dataset supporting the paper "Herbivory mediates the response of below-ground food-webs to invasive grasses", published in the Journal of Animal Ecology.
The dataset refers to samples collected across 6 farms in the Bega Valley region of Australia. The farms are located in the grassy woodland ecoregion and are extensively managed with sheep and cattle grazing. Livestock shares the landscape with native mammalian and invertebrate herbivores. On each farm, two nested fenced exclosure systems were established. These included an open area, a fence excluding livestock but allowing access to native mammals and invertebrates, a fence excluding all mammals but allowing access to invertebrates and a shielded cage excluding all invertebrate herbivores as well. In each farm, one of these systems was located in a zone  dominated by the native Kangaroo grass, and another in a zone co-dominated by the Invasive African lovegrass. The sample and treatment numbering is provided in the file Sample_metadata.
Soil samples were taken and DNA was extracted and amplified for 16s and ITS markers. The resulting metabarcoding derived ASV tables are presented (16s_ASV_table and ITS_ASV_table), as are the inferred functional profiles for bacteria at the enzyme and pathway level (16s_picrust_enzymes and 16s_picrust_pathways), as derived by the PICRUSt2 pipeline, and the fungal guilds reconstructed with FunGuildR (FunguildR_output).
Chemical, physical and enzymatic assays were also performed on the soil samples (Chemical_data).
Nematodes were extracted from soil cores with a Baermann funnel, counted (Nematodes_counts) and had their DNA extracted and amplified (Nematodes_asv_table). Soil invertebrates were sampled with below-ground pitfall traps and identified to family level (Invertebrates) and earthworms were manually extracted from 20*20*20 cm monoliths ((Earthworm_counts).
Two 20 by 100 cm strips had their vegetation removed and their living and litter biomass quantified by dry weight (Biomass_summary). Sensors measuring moisture and temperature 10 cm beneath the soil surface were installed in each plot and their output is presented in Microclimate_summary.

en: herbivory ecosystem-functioning invasive-species grassland soil-biodiversity

en:
Resource Title: 16s_ASV_table.txt
    Size: 10331118 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/200c7de4-d400-47f6-9b28-a4710766338e/download/16s_asv_table.txt
    Description: ASV table of 16s (bacteria) communities. Columns are sampling sites, rows ASVs

format: TXT

media_type: text/plain

en:
Resource Title: Easrthworm_counts.csv
    Size: 1165 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/695104b9-95dd-4ee3-bd87-b99f62c82816/download/easrthworm_counts.csv
    Description: Earthworms counts and biomass for each sampling site

en:
Resource Title: Sample_metadata.csv
    Size: 1295 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/ef16a55a-9e7e-447e-9fb8-c07818c42b82/download/sample_metadata.csv
    Description: Metadata and treatment information for each of the sampling sites

en:
Resource Title: Nematodes_counts.csv
    Size: 2438 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/3b85e403-72c0-4f1c-bde3-c0464a59b660/download/nematodes_counts.csv
    Description: Summary counts and moisture adjustments for Baermann extracted nematode samples

en:
Resource Title: Invertebrates.csv
    Size: 6266 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/46a505cc-ced8-41da-92f6-c2db25b46550/download/invertebrates.csv
    Description: Summary table of pitfall-trap collected invertebrates.

en:
Resource Title: Biomass_summary.csv
    Size: 4005 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/a2d0a31a-cfb3-421c-9970-36f0f2ba9b5e/download/biomass_summary.csv
    Description: Summary of collected biomass data. Each row is the average of 2 20 by 100 cm strips.

en:
Resource Title: Nematodes_asv_table.csv
    Size: 1319550 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/5cd79f48-2967-4687-8a34-cf18c3e3f9b4/download/nematodes_asv_table.csv
    Description: ASV table of nematode communities

en:
Resource Title: FunGuildR_output.csv
    Size: 3471 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/d54a6c74-d9a7-4c1d-bff2-fe2aa355cfdc/download/funguildr_output.csv
    Description: FunGuildR derived ecological profiles of fungal communities

en:
Resource Title: Chemical_data.csv
    Size: 8011 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/9303e1cc-6bd5-4274-8e3c-64857ee50dff/download/chemical_data.csv
    Description: Summary of chemical and physical parameters. Each row is a sampling site

en:
Resource Title: 16s_picrust_enzymes.tsv.gz
    Size: 416613 bytes
    Format: application/gzip
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/b3783c93-6e3d-4e1b-a417-cbb1a489699c/download/16s_picrust_enzymes.tsv.gz
    Description: PICRUSt2 derived functional profiles of bacterial communities

format: gzip

en:
Resource Title: ITS_ASV_table.tsv.txt
    Size: 4203574 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/2569787f-d2d4-427e-a024-3a45d6bc9856/download/its_asv_table.tsv.txt
    Description: ASV table of fungal communities. Each column is a sampling site

en:
Resource Title: Microclimate_summary.csv.xlsx
    Size: 3575094 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/54ae1e37-c905-4e7a-84ef-bdd19489fedf/download/microclimate_summary.csv.xlsx
    Description: Summary of sensor-collected soil moisture and temperature data

format: XLS

en:
Resource Title: 16s_picrust_pathways.tsv.gz
    Size: 175067 bytes
    Format: application/gzip
    URL: https://www.envidat.ch/dataset/4bda5372-4c89-4db2-91c2-da8b2f55aacc/resource/a724bdd1-1af4-4719-a29d-00908d1ec218/download/16s_picrust_pathways.tsv.gz
    Description: PICRUSt2 derived inferred pathways for bacterial communities

ecosystem-functioning

display_name: ecosystem-functioning

grassland

display_name: grassland

herbivory

display_name: herbivory

invasive-species

display_name: invasive-species

soil-biodiversity

display_name: soil-biodiversity


en:
CHELSAcruts is a delta change monthly climate dataset for the years 1901-2016 for mean monthly maximum temperatures, mean monthly minimum temperatures, and monthly precipitation sum.  Here we use the delta change method by B-spline interpolation of anomalies (deltas) of the CRU TS 4.01 dataset. Anomalies were interpolated between all CRU TS grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2 (Karger et al. 2017, Scientific Data). This method has the assumption that climate only varies on the scale of the coarser (CRU TS) dataset, and the spatial pattern (from CHELSA) is consistent over time. This is certainly a rather crude assumption, and for time periods for which more accurate data is available CHELSAcruts should be avoided if possible (e.g. use CHELSA V1.2 for 1979-2015). Different to CHELSA V1.2, CHELSAcruts does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages.
CHELSAcruts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

en: minimum-temperature century air-temperature free-climate-data climate-layers precipitation climate maximum-temperature timeseries

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: CHELSAcruts -  High resolution temperature and precipitation timeseries for the 20th century and beyond

envi

en: Environment

en:
Resource Title: Data Access
    Size: 3298534883328 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav1%2F&prefix=chelsa_cruts%2F
    Description: CHELSAcruts is a delta change monthly climate dataset for the years 1901-2016 for mean monthly maximum temperatures, mean monthly minimum temperatures, and monthly precipitation sum.

en:
Resource Title: CHELSA_tech_specification_V1.2.pdf
    Size: 1146678 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/9c9c699a-e57f-49e9-b489-c6abdfa9b53b/resource/1d294699-c738-4a00-8500-2d64d3226819/download/chelsa_tech_specification_v1.2.pdf
    Description:

format: PDF

media_type: application/pdf

en:
Resource Title: CHELSA Technical Documentation
    Size: 0
    Format: application/pdf
    URL: http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf
    Description: As the CHELSA project is continuously expanded, certain new parameters, time scales etc. are not included anymore in the original publication (Karger et al. 2017). We are therefore provide this document as a guideline of the current climatic parameters available and will expand it as new parameters or time periods will become available. Please refer to the version history for changes made in the document.

air-temperature

display_name: air-temperature

century

display_name: century

climate

display_name: climate

climate-layers

display_name: climate-layers

free-climate-data

display_name: free-climate-data

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation

timeseries

display_name: timeseries


en:
Spatio-temporal vegetation models are essential for simulating dynamics and shifts
in species distributions over large areas, particularly under global change. One such
model is the dynamic forest landscape model TreeMig. We have developed a frame-
work that makes the model more user-friendly, improves its functionality, and expands
its possibilities. The framework consists of the improved TreeMig model, the R pack-
age ‘TreeMig-R’ for pre-processing input data, model execution and visualization and a
graphical user interface (GUI) for ease of use. The code of the TreeMig Package and the GUI is stored here.

en: forest-model gui landscape r-package dynamic-modelling

en: Code of TreeMig Package version 1

format: ZIP

dynamic-modelling

display_name: dynamic-modelling

forest-model

display_name: forest-model

gui

display_name: gui

landscape

display_name: landscape

r-package

display_name: r-package


en:
Research question / purpose
Timber is widely used for protection measures in torrent control. However, life span of woody constructions such as timber check dams is limited mainly due to fungal decay. In practice a controversial discussion has been going on if either Norway spruce (Picea abies) or silver fir (Abies alba) is more enduring and if bark removal increases resistance against fungal decay.
Description
This dataset contains monitoring information on a series of 15 timber check dams built in 1996 in Hergiswil, Switzerland. The constructions were alternatively realised with Norway spruce and silver fir, half of them each with remaining and removed bark, respectively. The data includes the identification of decayed zones with a simple practical approach (i.e. measurement of the penetration depth of a slotted screwdriver No. 3) from a total of 12 repeated surveys from 2001 to 2025.
The following information is contained (by column and column title):
•	Identification of decayed zone (column title “Decay_Id”)
•	Year of survey (column title “Year”)
•	Identification of check dam (column title “Check dam”)
•	Degree of decay (column title “Degree of decay”): 2 = reduced wood strength (penetration depth 2-10 mm); 3 = low wood strength (penetration depth - 10 mm)
•	Sectors 1 to 7 of check dams (column title “Sector”)
•	Element of check dam (column title “Element”): LH (longitudinal log, German: “Längsholz”), Z (transverse log, German: “Zange”), FH (infill log, German: “Füllholz”)
Plan of check dams and additional information on monitoring surveys: survey information (PDF)

en: long-term-behaviour fungal-decay check-dam torrent-control timber-structure

en: Long-term behaviour of timber constructions in torrent control

en:
Resource Title: decay_envidat.csv
    Size: 13209 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/25bbe989-95e3-4705-9807-248a0ab14884/resource/7db6f23d-ff20-4991-a626-616e2be7aa65/download/decay_envidat.csv
    Description:

en:
Resource Title: Survey Information.pdf
    Size: 357932 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/25bbe989-95e3-4705-9807-248a0ab14884/resource/37048955-41d9-4145-96cd-90c3edc4c83b/download/survey-information.pdf
    Description:

check-dam

display_name: check-dam

fungal-decay

display_name: fungal-decay

long-term-behaviour

display_name: long-term-behaviour

timber-structure

display_name: timber-structure

torrent-control

display_name: torrent-control


soil-erosion-mapping-on-steep-slopes

en:
The dataset contains Digital Terrain Models (DTMs) and orthophotos obtained from successive surveys used to quantify soil erosion on non-vegetated slopes in a torrent catchment. The research area is steep (mainly 30-60°), has a complex topography and the spatial extent is about 0.6 ha. Furthermore, it is partly forested, and the soils consist mainly of glacial till. Digital terrain models were compiled in spring and autumn of the years 2021 to 2025 using UAV based LiDAR (Riegel miniVUX-3) and Photogrammetry (DJI Phantom 4 RTK).
To derive DTMs from the LiDAR (miniVUX-3) and photogrammetric (Phantom 4RTK) point clouds ground classification was processed with lasground_new (LASTools) and further refined by applying a filtering, based on vegetation index (2*green channel – red channel – blue channel) to remove vegetation points falsely classified as ground. Documented accuracies of the DTMs heights compared to dGNSS measurements were mostly around 2-5 cm. All data is supplied in the reference system LV95 (epsg: 2056) / LN02 (epsg: 5728).
Dates of surveys (miniVUX-3UAV, DJI P4 RTK):
 * 15.06.2021
 * 10.11.2021
 * 20.04.2022
 * 17.11.2023
 * 18.04.2023
 * 24.11.2023
 * 19.03.2024
 * 14.11.2024
 * 25.03.2025
 * 12.11.2025

en: mountain-stream monitoring steep-slope gully erosion-scar erosion

en: Soil erosion mapping on steep slopes

title_for_slug: soil-erosion-mapping-on-steep-slopes

erosion

display_name: erosion

erosion-scar

display_name: erosion-scar

gully

display_name: gully

monitoring

display_name: monitoring

mountain-stream

display_name: mountain-stream

steep-slope

display_name: steep-slope


en:
Plant ecophysiological and associated environmental data for two tree species (*Fagus sylvatica* and *Quercus pubescens*) grown for five years in a factorial open-top climate chamber experiment (Model Ecosystem Facility, Birmensdorf, Switzerland) to test the long-term effects of heat (+5 °C) and soil drought (irrigation reduced by 50%). n = 4 trees per species and treatment, n = 48 trees total.
 Included data sheets:
- Environmental_Data.csv: Chamber-level environmental recorded every 10 minutes
- Tleaf.csv: Leaf temperatures recorded every 10 minutes
- Gas_exchange.csv: Leaf-level gas exchange data taken diurnally on four days during the growing season
- Leaf_traits.csv: Leaf functional traits
- TSMs_HSMs.csv: Photosynthetic thermal tolerance and leaf water potential data, summarized also in terms of leaf thermal safety margins and hydraulic safety margins, collected 3-4 times during the growing season
- Scorch.csv: Leaf-level leaf scorching data, including leaf thermal safety margins and scorching occurrence and presence, summarized by date

en: hot-drought thermal-safety-margins thermoregulation functional-traits quercus-pubescens fagus-sylvatica hydraulic-safety-margins gas-exchange leaf-scorching

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: Hydraulic stress limits thermal acclimation in trees under chronic drought

en:
Resource Title: README.txt
    Size: 8110 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/1fe7f58f-356a-4ed4-ae5f-a2b16755e9de/download/readme.txt
    Description: README file with more information about the dataset.

en:
Resource Title: Leaf_traits.csv
    Size: 7772 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/eaf9d8ce-80f5-489f-af97-e80760927aee/download/leaf_traits.csv
    Description: Tree-level leaf functional trait data.

Variable List:
	- TreeID: Unique identifier for individual trees
	- Chamber: open-top-chamber ID
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
 	- Species: Tree species
	- Leaf_width (cm)
	- Leaf_area (cm^2)
	- Stomatal_density (count per cm^2)
	- Pore_length: Stomatal pore length (micrometers)
	- Guard_cell_width: Stomatal guard cell width (micrometers)
	- Leaf_thickness (mm)
	- Epidermal_thickness (mm)
	- Parenchyma_thickness (mm)
	- Parenchyma:Epidermis: Ratio between parenchyma and epidermal thickness
	- Reflectance: Reflectance of photosynthetically active radiation (400-700), fraction
	- Transmittance: Transmittance of photosynthetically active radiation (400-700), fraction
	- Absorptance: Absorptance of photosynthetically active radiation (400-700), fraction
	- Absorbance: Optical absorbance of photosynthetically active radiation (400-700 nm), unitless
	- g1: Medlyn-style stomatal slope calculated with Licor LI6800 data

en:
Resource Title: README.txt
    Size: 8090 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/1f818ee5-bfba-4996-b8fb-e6dc1c96fbb4/download/readme.txt
    Description: README file with more information about the dataset.

en:
Resource Title: Scorch.csv
    Size: 129956 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/e153f13e-330e-4c0a-8cff-59e625dc7e7c/download/scorch.csv
    Description: Tree-level leaf scorching occurrence and severity data summarized by date with daily leaf thermal safety margins.

Variable List:
	- TreeID: Unique identifier for individual trees
	- Date (MM/DD/YYYY)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Species: Tree species
	- Tleaf: Leaf temperature (degrees C) *measured by an infrared sensor integrated into the Cavicam
	- Tcrit: Critical thermal threshold of Photosystem II (degrees C) *daily entries inherit the Tcrit measured onthe next measurement date and applied to the interval preceding it (or are forward-filled when Tcrit could not be estimated in August or September)
	- TSM: Leaf thermal safety margin (difference between Tcrit and Tleaf, in degrees C)
	- Scorch_binary: Binary indicating whether scorching occurred on that date (0 = no, 1 = yes)
	- Percent_affected: Percent of the camera window affected by scorching during a scorching event

en:
Resource Title: Environmental_Data.csv
    Size: 19996344 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/8113d780-83c8-43bd-a823-f726ad3f21ab/download/environmental_data.csv
    Description: Chamber-level abiotic data recorded every 10 minutes.

Variable List:
	- Time (MM/DD/YYYY HH:MM)
	- Chamber: open-top-chamber ID
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- Tair: Air temperature (degrees C)
	- Tair_sd: Standard deviation of air temperature
	- RH: Relative humidity
	- RH_sd: Standard deviation of relative humidity
	- VPD: Vapor pressure deficit (kPa)
	- Tsoil: Soil temperature (degrees C)
	- Soil_m: Volumetric soil water content (m^3/m^3)
	- PPFD: Photosynthetic photon flux density (micromoles m^-2 s^-1) *collected from a weather station next to the open-top-chambers (50% intensity inside chambers)
	- windspeed: (m/s) *collected from a weather station next to the open-top-chambers

en:
Resource Title: Gas_exchange.csv
    Size: 4413 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/cc7e702f-6d53-4192-944c-7671eaecf5bc/download/gas_exchange.csv
    Description: Mean values taken for each tree across the growing season. Measurements were taken diurnally (~1 measurement/hr) with a Licor LI6800 matching ambient chamber conditions on 4 days during the growing season (1 day in June, July, August, September).

- Number of variables: 11
- Number of cases/rows: 48
- Variable List:
	- TreeID: Unique identifier for individual trees
	- Chamber: open-top-chamber ID
	- Species: Tree species
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- gsw.mean: Mean stomatal conductance to water vapor (mol m^-2 s^-1)
	- gsw.mean: Mean stomatal conductance rate (mol m^-2 s^-2)
	- Tdiff.mean: Mean difference between leaf and air temperature on the day of Licor measurements
	- lngsw.mean: Mean of the natural log of stomatal conductance
	- lngsw.mean~Tdiff.mean_slope: The slope of the linear least-squares relationship between the natural log of lngsw.mean and Tdiff.mean

en:
Resource Title: Tleaf.csv
    Size: 28028436 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/1860aa5f-68f2-4889-b0c9-bd907e48111f/download/tleaf.csv
    Description: Tree-level leaf temperature data recorded every 10 minutes.

Variable List:
	- Timestamp (MM/DD/YYYY HH:MM)
	- TreeID: Unique identifier for individual trees
	- Chamber: open-top-chamber ID
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
 	- Species: Tree species
	- Tair: Air temperature (degrees C)
	- Tleaf: Leaf temperature (degrees C)
	- Tdiff: Leaf-to-air temperature differential (degrees C)

en:
Resource Title: Gas_exchange.csv
    Size: 4424 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/df082744-69a0-49b6-81b7-c3f02d24c9f0/download/gas_exchange.csv
    Description: Leaf-level gas exchange collected diurnally for each tree on 4 days of the growing season and summarized to growing-season mean.

Variable List:
	- TreeID: Unique identifier for individual trees
	- Chamber: open-top-chamber ID
	- Species: Tree species
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- gsw.mean: Mean stomatal conductance to water vapor (mol m^-2 s^-1)
	- E.mean: Mean transpiration rate (mol m^-2 s^-2)
	- Tdiff.mean: Mean difference between leaf and air temperature on the day of Licor measurements
	- lnE.mean: Mean of the natural log of the transpiration rate
	- lnE.mean~Tdiff.mean_slope: The slope of the linear least-squares relationship between the natural log of lnE.mean and Tdiff.mean

en:
Resource Title: TSMs_HSMs.csv
    Size: 15217 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/6c897b79-4cc6-46f5-87f0-83275921ede9/download/tsms_hsms.csv
    Description: Tree-level photosynthetic thermal tolerance, leaf water potentials, thermal safety margins, and hydraulic safety margins measured 3-4 times per tree during the growing season.

Variable List:
	- TreeID: Unique identifier for individual trees
 	- Species: Tree species
	- Campaign: Month of the growing season in which data was collected
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Waterpotential: midday leaf waterpotential (MPa)
	- WPtlp: Waterpotential at leaf turgor-loss-point (MPa) *Measured by Mas, E., Cochard, H., Deluigi, J., Didion-Gency, M., Martin-StPaul, N., Morcillo, L., Valladares, F., Vilagrosa, A., & Grossiord, C. (2024). Interactions between beech and oak seedlings can modify the effects of hotter droughts and the onset of hydraulic failure. New Phytologist, 241(3), 1021-1034. https://doi.org/https://doi.org/10.1111/nph.19358
	- HSM: Hydraulic safety margin (difference between WPtlp and Waterpotential, in MPa)
	- Tcrit: Critical thermal threshold of Photosystem II (degrees C)
	- T50: High leaf temperature at which Photosystem II function declines by 50% (degrees C)
	- Tleaf.max: Maximum leaf temperature during the week preceding thermal tolerance measurement
	- TSM.min: Minimum leaf thermal safety margin during the week preceeding thermal tolerance measurement (difference between Tcrit and Tleaf.max, in degrees C)

fagus-sylvatica

display_name: fagus-sylvatica

functional-traits

display_name: functional-traits

gas-exchange

display_name: gas-exchange

hot-drought

display_name: hot-drought

hydraulic-safety-margins

display_name: hydraulic-safety-margins

leaf-scorching

display_name: leaf-scorching

quercus-pubescens

display_name: quercus-pubescens

thermal-safety-margins

display_name: thermal-safety-margins

thermoregulation

display_name: thermoregulation


en: Photosynthetic thermal tolerance estimates for 36 tropical species following the static water bath method and measuring maximum quantum yield (Fv/Fm). Thermal tolerance assays were performed once each in near-darkness (~4 μmol photons m^-2 s^-1) and in sub-saturating light (280 μmol photos m^-2 s^-1).

en: irradiance photoinhibition chlorophyll-fluorescence tcrit photosystem-ii thermal-tolerance tropical-plants

en: Light exposure reshapes photosynthetic thermal tolerance curves, with idiosyncratic responses across 36 species.

envi

en: Environment

chlorophyll-fluorescence

display_name: chlorophyll-fluorescence

irradiance

display_name: irradiance

photoinhibition

display_name: photoinhibition

photosystem-ii

display_name: photosystem-ii

tcrit

display_name: tcrit

thermal-tolerance

display_name: thermal-tolerance

tropical-plants

display_name: tropical-plants


en:
Hourly Alpine photovoltaic (PV) potential profiles for Switzerland, covering the year 2016 and spatially aggregated to two levels: Swiss alpine municipalities and the nodes of the Swiss electricity transmission grid. Six scenarios combine land suitability mask, terrain restrictions (elevation, slope, aspect), road accessibility, hazard zones, and either an elevation range or a pixel-level winter specific yield filter, providing per-pixel installed capacity and aggregated hourly generation profiles for ~713 alpine communes and ~126 transmission grid nodes.
 What is in this dataset
- **Hourly generation profiles** (`energy_yield`, in Wh) for each aggregation unit
- **Installed capacity** (`installed_capacity_mwp`, in MWp) and **pixel count** (`pixel_count`) per unit
- **Seasonal sums** (`annual_gwh`, `winter_gwh`, `summer_gwh`, in GWh) per unit
- **Polygon geometries** (`geometry`, WKT in EPSG:2056) for each aggregation unit, embedded directly in the NetCDF
- **Global attributes** recording scenario name, panel tilt, GCR method, POA mode, and PV system parameters
 Six scenarios
Scenarios vary the site-selection approach (elevation range vs. pixel-level winter specific yield threshold) and the maximum slope:
- **1. `reusser_nowy_elev1900_3300_slope40`** — slope ≤ 40°, elevation 1900–3300 m, aspect 90–270° on steep slopes, no winter-yield filter
- **2. `reusser_nowy_elev1500_4400_slope40`** — slope ≤ 40°, elevation 1500–4400 m, aspect 90–270° on steep slopes, no winter-yield filter
- **3. `reusser_nowy_elev1900_3300_slope30`** — slope ≤ 30°, elevation 1900–3300 m, aspect 90–270° on steep slopes, no winter-yield filter
- **4. `reusser_nowy_elev1500_4400_slope30`** — slope ≤ 30°, elevation 1500–4400 m, aspect 90–270° on steep slopes, no winter-yield filter
- **5. `reusser_wy500_elev100_4400_slope40`** — slope ≤ 40°, elevation 100–4400 m, all aspects, winter specific yield ≥ 500 kWh/kWp
- **6. `reusser_wy500_elev100_4400_slope30`** — slope ≤ 30°, elevation 100–4400 m, all aspects, winter specific yield ≥ 500 kWh/kWp
The four `nowy_*` scenarios use a conventional elevation range together with an aspect restriction (north-facing pixels excluded on slopes - 10 deg). The two `wy500_*` scenarios apply a pixel-level winter specific yield threshold instead.
 Methodology
A pre-computed binary exclusion raster from the [Swiss SolarWind Explorer](https://swiss-solarwind-explorer.ethz.ch/) (Reusser et al., 2025) serves as the base land suitability mask, integrating land-cover, protected-area, and biodiversity exclusions developed through extensive consultation with governmental, expert, and biodiversity stakeholders. On top of this base mask, the pipeline clips to alpine communes, removes natural hazards (level -= 2), applies a 5 km effective road distance filter (with vertical penalty), and applies scenario-specific terrain restrictions.
For each qualifying 25 m pixel, the ground-cover ratio is computed using the Bao et al. (2022) parametrization with a 60 deg panel tilt, and the hourly yield is derived from the [CH-POA300](https://www.doi.org/10.16904/envidat.632) plane-of-array irradiance dataset (300 m resolution, 5 azimuth bins). A simplified PV system model is applied (module efficiency 20%, performance ratio 0.8, bifacial factor 1.2, inter-row shading loss 10%). For scenarios with the winter yield filter, only pixels whose simulated October--March specific yield exceeds 500 kWh/kWp are retained.
 Two aggregation levels
- **commune** — Swiss alpine municipality; 713 units; source swissBOUNDARIES3D; CRS EPSG:2056
- **node** — Transmission grid Voronoi node; 126 units; source [CH-RPV300 (grid_voronoi_v2)](https://www.doi.org/10.16904/envidat.733); CRS EPSG:2056
 File format
NetCDF-4 files, one per scenario and aggregation level (12 files total). Each file is self-contained: the hourly profiles, installed capacity, seasonal sums, polygon geometries, and scenario parameters are all embedded in the NetCDF. See `data_description_v*.md` included in the dataset for the full data model, coordinate definitions, and usage examples.

en: renewable-energy alpine-pv snow alps photovoltaic

en: CH-ALPV300: Hourly Alpine-PV  Potential Profiles in Switzerland

en:
Resource Title: data_description_v1.md
    Size: 12104 bytes
    Format: text/markdown
    URL: https://www.envidat.ch/dataset/fb06af0f-1ac6-4d2b-ae8e-1d6950cd0413/resource/4dc40d28-c071-4463-8030-1a1661b02869/download/data_description_v1.md
    Description:

format: markdown

en:
Resource Title: profiles_2016_v1.zip
    Size: 112449290 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/fb06af0f-1ac6-4d2b-ae8e-1d6950cd0413/resource/ecbc2326-e274-4734-9150-c394c0213a50/download/profiles_2016_v1.zip
    Description: Profiles 2016, version 1

media_type: application/zip

en:
Resource Title: specs_v1.pdf
    Size: 10108273 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/fb06af0f-1ac6-4d2b-ae8e-1d6950cd0413/resource/216f0204-0ac5-4510-8087-e6dfc7669078/download/specs_v1.pdf
    Description: Specifications, version 1

alpine-pv

display_name: alpine-pv

alps

display_name: alps

photovoltaic

display_name: photovoltaic

renewable-energy

display_name: renewable-energy

snow

display_name: snow


en:
We developed a monitoring system using low-cost lidar (Livox Avia) and optical sensors, to measure snow depth variations in an avalanche release area at a high spatiotemporal scale (centimeter to low decimeter spatial resolution and hourly temporal resolution). A detailed description of the setup and a first data analysis is published in:
[Ruttner, P., Voordendag, A., Hartmann, T., Glaus, J., Wieser, A., & Bühler, Y. (2024). Monitoring snow depth variations in an avalanche release area using low cost lidar and optical sensors. EGUsphere, 2024, 1-20.](https://nhess.copernicus.org/articles/25/1315/2025/)
This dataset contains hourly 3D lidar data of the snow surface at the test site Braemabuel in Davos, Switzerland from the winter season 2023-2024 (23.11.2023 - 14.04.2024). Braema1 is installed at 2191 m a.s.l. in the slope, looking up into the avalache release area, and Braema2 is installed at 2255 m a.s.l at the ridge, looking down. Both scans together cover an area of about 15000 m².
The data is in format ".las" and contains the points in XYZ [m], in the scanner own coordinate system
- scalar fields: intensity, return number, timestamp, tag, label
-- tag: binary code from Livox (see [Livox Avia Manual](https://terra-1-g.djicdn.com/65c028cd298f4669a7f0e40e50ba1131/Download/Avia/Livox%20Avia%20User%20Manual%20202204.pdf))
-- label: marking outliers (filtered by distance and SOR to get snow particles in the air)

en: avalanche lidar low-cost snow monitoring wind-drifted-snow

envidat

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

en: EnviDat: the Environmental Data Portal

en: Snow depth mapping by lidar station Braemabuel

en:
Resource Title: Braema1
    Size: 22441204122 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.581/braema1_23_24_v2.zip
    Description:

en:
Resource Title: Braema2
    Size: 20937965568 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.581/braema2_23_24.zip
    Description:

avalanche

display_name: avalanche

lidar

display_name: lidar

low-cost

display_name: low-cost

monitoring

display_name: monitoring

wind-drifted-snow

display_name: wind-drifted-snow


en:
Hourly rooftop photovoltaic (RPV) power generation profiles for Switzerland, covering 12 weather years (2008--2019) and spatially aggregated to the nodes of the Swiss electricity transmission grid. The dataset resolves 48 orientation and tilt combinations, five installation size classes, and three flat roof design scenarios per grid node, providing approximately 8,550 distinct candidate RPV generators nationwide.
 What is in this dataset
- **Hourly generation profiles** (`power`, in Wh) for each grid node, roof orientation, and tilt bin
- **Installed capacity** (`Wp`, in Wp) broken down by size class (1--10, 10--30, 30--100, 100--300, 300--1000 kWp)
- **Normalized capacity factor profiles** (`specificPower`, in Wh/Wp) enabling scaling to arbitrary deployment levels
- **Voronoi grid shapefiles** defining the spatial aggregation zones around each transmission node.
 Flat roof scenarios
Flat roofs (~23% of Swiss roof area) allow different module configurations. Three scenarios are included:
- **Winter** — South-facing, 35° tilt, GCR 0.45 — optimizes winter yield (Oct–Mar)
- **Annual** — South-facing, 15° tilt, GCR 0.70 — optimizes annual yield
- **Flat-EW** — East-West alternating, 15° tilt, GCR 1.04 — maximizes total installed capacity
Tilted roofs (tilt - 0) are identical in all three scenarios.
 Methodology
Generation profiles are derived from satellite-based hourly surface solar radiation data (HelioMont), downscaled to 300 m resolution using the NASADEM digital elevation model with terrain-scale shading and ground reflection ([CH-POA300](https://www.doi.org/10.16904/envidat.632)). The national roof inventory Sonnendach (v1.5) provides orientation, tilt, and area for over 10 million roof surfaces. A simplified PV system model (module efficiency 20%, performance ratio 0.8, roof cover factor 0.7) converts irradiance to AC power output. Only roofs with an installed capacity -= 1 kWp are included.
 Two grid versions
- **v1** —  135 nodes, CRS EPSG:21781
- **v2** —  126 nodes, CRS EPSG:21781
 File format
NetCDF-4 files, one per year and scenario. See `DATA_DESCRIPTION.md` included in the dataset for the full data model, coordinate definitions, and usage examples.

en: photovoltaic renewable-energy rooftop-pv solar-energy energy-transition

en: CH-RPV300: Hourly Rooftop-PV Potential Profiles in Switzerland

en:
Resource Title: profiles_grid_v2.zip
    Size: 4531190497 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73f6cac8-6a0e-469b-8eed-a9e7fcd75bb8/resource/d6a43092-bdce-4e14-a182-8c37e53b5f65/download/profiles_grid_v2.zip
    Description: This archive contains the RPV profiles aggregated using the second version (v2) of the transmission grid, also included.

en:
Resource Title: profiles_grid_v1.zip
    Size: 5894842614 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73f6cac8-6a0e-469b-8eed-a9e7fcd75bb8/resource/4e34b9ac-b8d5-408f-b9e0-70a559e44a2b/download/profiles_grid_v1.zip
    Description: This archive contains the RPV profiles aggregated using the first version (v1) of the transmission grid, also included.

en:
Resource Title: DATA_DESCRIPTION.md
    Size: 7762 bytes
    Format: text/markdown
    URL: https://www.envidat.ch/dataset/73f6cac8-6a0e-469b-8eed-a9e7fcd75bb8/resource/78340283-abd2-48e0-82aa-57707c46dc93/download/data_description.md
    Description:

energy-transition

display_name: energy-transition

rooftop-pv

display_name: rooftop-pv

solar-energy

display_name: solar-energy


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

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

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

envi

en: Environment

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

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

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

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

airborne-laser-scanning

display_name: airborne-laser-scanning

canopy-height

display_name: canopy-height

forest-structure

display_name: forest-structure

snow-depth

display_name: snow-depth

snow-distribution

display_name: snow-distribution


en:
This repository contains all WRF model outputs and observational data sets used for the paper:
Georgakaki, P., Sotiropoulou, G., Vignon, É., Billault-Roux, A.-C., Berne, A., and Nenes, A.: Secondary ice production processes in wintertime alpine mixed-phase clouds, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-760, in review, 2021.

en: liquid-water-content jungfraujoch blowing-snow wrf secondary-ice-production ice-crystal-number-concentration ice-water-content swiss-alps

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: Data for the publication "Secondary ice production processes in wintertime alpine mixed-phase clouds"

en:
Resource Title: Observational data
    Size: 4448 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a014f39f-34c3-499f-9627-0efde504d2e1/resource/4ea9d0c6-106e-424a-9d61-9fc1dc99f576/download/observations.zip
    Description: The .zip file contains 6 .csv files including all microphysical measurements taken at the Jungfraujoch station during the two periods of interest:

* 25-28 January 2014 : northwesterly-winds (NW)
* 29 January - 1 February 2014 : southeasterly-winds (SE)

The total Ice Crystal Number Concentration (ICNC; reported in L⁻¹) is measured by the two-dimensional stereo hydrometeor spectrometer (2D-S; Lawson et al., 2006) over the size range 10-1280 μm. The total ice water content (IWC; reported in gm⁻³) is also derived by the 2D-S data using the Brown and Francis (1995) mass-diameter relationship. Finally, the quantification of the liquid water content (LWC; reported in gm⁻³) is based on the liquid droplet size distribution data derived from a DMT cloud droplet probe (CDP; Lance et al., 2010) over the size range 2-50 μm. The frequency of the measurements in the .csv files is 30 min, to match the output frequency of the model. Datetime is also reported in the files (DD/MM/YYYY h:mm) in UTC.

__Acknowledgment__: Collection and pre-processing of the microphysical measurements has been performed by Gary Lloyd (gary.lloyd@manchester.ac.uk). More details about the instrumentation during the CLACE2014 campaign can be found in Lloyd et al. (2015).

en:
Resource Title: WRF outputs
    Size: 741751014 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a014f39f-34c3-499f-9627-0efde504d2e1/resource/45b96d72-d1ef-4208-8b22-6c6ab546208b/download/wrf-outputs.zip
    Description: The .zip file contains all the NetCDF outputs produced by the mesoscale Weather Research and Forecasting (WRF) model (version: 4.0.1). Two case studies were simulated in this study, between 25-28 January 2014 (00:00 UTC) and 29 January - 1 February 2014 (00:00 UTC), respectively. The former is denoted as "NW" and the latter as "SE", owing to the prevailing wind conditions at the Jungfraujoch (JFJ) station.

The outputs come from the innermost domain of the simulations with a spatial resolution of 1 km and are extracted from the nearest to JFJ model grid point (46.55°N 7.98°E). The dimensions of each model variable is [145,100], which corresponds to time and height, respectively. The frequency of the outputs is 30 min. Note that the first 24 hours of each simulation (i.e., the first 48 outputs) were considered spin up time.

The following sets of sensitivity simulations were presented in this study:

* CNTRL_NW.nc, CNTRL_SE.nc : Sensitivity simulations performed with the default version of WRF
* DS_PHILL_NW.nc, DS_PHILL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Phillips et al. (2018)
* DS_SULL_NW.nc, DS_SULL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Sullivan et al. (2018)
* PHILL_NW.nc, PHILL_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Phillips et al. (2017)
* TAKAH_NW.nc, TAKAH_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Sullivan et al. (2018) based on Takahashi et al. (1995)
* TAKAHrim_NW.nc, TAKAHrim_SE.nc : Same set-up as before but applied only to collisions between rimed ice particles
* BIPS_Xk0_DY_NW.nc, BIPS_Xk0_DY_SE.nc : Sensitivity simulations including a source of Xk0 (either 10.0 or 100.0 L⁻¹) ice crystals with sizes of DY (either 10 or 100 μm) in the first atmospheric level of the model
* BIPS100_PHILL_NW.nc, BIPS100_PHILL_SE.nc : Sensitivity simulations where the combined effect of blowing snow and ice-ice collisional break-up is examined

blowing-snow

display_name: blowing-snow

ice-crystal-number-concentration

display_name: ice-crystal-number-concentration

ice-water-content

display_name: ice-water-content

jungfraujoch

display_name: jungfraujoch

liquid-water-content

display_name: liquid-water-content

secondary-ice-production

display_name: secondary-ice-production

swiss-alps

display_name: swiss-alps

wrf

display_name: wrf


endsplit

en:
R scripts and demonstration data for end-member mixing and splitting: using isotopes and other tracers to determine where streamflow comes from (end-member mixing) and where precipitation goes (end-member splitting).
 This package includes two R scripts:
"EndSplit_v1.0_20200516.R" implements end-member mixing and splitting.
"EndSplit_demo_v1.0_20200516.R" demonstrates the application of EndSplit to the Hubbard Brook Watershed 3 isotope data set (see below).
Both of these scripts are copyright (C) 2020 ETH Zurich and James Kirchner.  Public use is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/
But… READ THIS CAREFULLY:
ETH Zurich and James Kirchner make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose.  Users are solely responsible for determining the suitability and reliability of this software for their own purposes.
These scripts implement end-member mixing and end-member splitting, as described in Kirchner and Allen, "Seasonal partitioning of precipitation between streamflow and evapotranspiration, inferred from end-member splitting analysis", Hydrology and Earth System Sciences, 24, 17-39, https://doi.org/10.5194/hess-24-17-2020, 2020.  Users publishing results based on these scripts should cite that paper.
Build 2020.05.16 is a minor bug fix of build 2019.10.25, which was previously released as EndSplit_v1.0_20191025.R.
 The zip file "demonstration input data.zip" contains 8 demonstration data files (all tab-delimited text):
"Hubbard Brook WS3 isotope data split by sampling date.txt" contains streamflow and precipitation isotope data from Hubbard Brook Watershed 3 isotope data (Campbell and Green, 2019).
"Hubbard Brook WS3 daily P and Q 1956-2014.txt" contains daily precipitation and streamflow totals for Hubbard Brook Watershed 3.  (USDA Forest Service Northern Research Station, 2016a and 2016b).
"Hubbard Brook WS3 isotope data WY2007.txt", "Hubbard Brook WS3 isotope data WY2008.txt", "Hubbard Brook WS3 isotope data WY2009.txt", "Hubbard Brook WS3 daily P and Q WY2007.txt", "Hubbard Brook WS3 daily P and Q WY2008.txt", and "Hubbard Brook WS3 daily P and Q WY2009.txt" contain subsets of these data for the designated water years.
As the work product of US federal employees, the data in these files are in the public domain.  However, any users of these data should cite the original sources:
Campbell, J. L., and Green, M. B.: Water isotope samples from Watershed 3 at Hubbard Brook Experimental Forest, 2006-2010, https://doi.org/10.6073/pasta/f5740876b68ec42b695c39d8ad790cee, 2019.
USDA Forest Service Northern Research Station: Hubbard Brook Experimental Forest (US Forest Service): Daily Streamflow by Watershed, 1956 - present, https://doi.org/10.6073/pasta/38b11ee7531f6467bf59b6f7a4d9012b, 2016a.
USDA Forest Service Northern Research Station: Hubbard Brook Experimental Forest (US Forest Service): Total Daily Precipitation by Watershed, 1956 - present, https://doi.org/10.6073/pasta/163e416fb108862dc6eb857360fa9c90, 2016b.
 The zip file "demonstration output files.zip" contains demonstration output files
These tab-delimited text files were generated by running EndSplit_demo_v1.0_20200516.R (which in turn calls EndSplit_v1.0_20200516.R) under R version 3.6.0, using the input files contained in "demonstration input data.zip"

en: isotopes end-member-mixing evapotranspiration streamflow precipitation end-member-splitting tracer

en: EndSplit

title_for_slug: endsplit

en:
Resource Title: EndSplit_demo version 1.0 build 2020.05.16
    Size: 14802 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/b12fafab-7730-4648-a8bc-6afb1944bf3b/resource/19e05849-5bd7-4d0e-9c90-98f9f2d78435/download/endsplit_demo_v1.0_20200516.r
    Description: EndSplit_demo_v1.0_20200516.R demonstrates the application of EndSplit to the Hubbard Brook Watershed 3 isotope data set.  It calls EndSplit_v1.0_20200516.R.

Both of these scripts are copyright (C) 2020 ETH Zurich and James Kirchner.  Public use is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

But… READ THIS CAREFULLY:
ETH Zurich and James Kirchner make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose.  Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

These scripts implement end-member mixing and end-member splitting, as described in Kirchner and Allen, "Seasonal partitioning of precipitation between streamflow and evapotranspiration, inferred from end-member splitting analysis", Hydrology and Earth System Sciences, 24, 17-39, https://doi.org/10.5194/hess-24-17-2020, 2020.  Users publishing results based on these scripts should cite that paper.

en:
Resource Title: demonstration input data
    Size: 387131 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/b12fafab-7730-4648-a8bc-6afb1944bf3b/resource/00207c87-63c7-4c9d-86c9-4873bf699035/download/demonstration-input-data.zip
    Description: # The zip file "demonstration input data.zip" contains 8 demonstration data files (all tab-delimited text): #

"Hubbard Brook WS3 isotope data split by sampling date.txt" contains streamflow and precipitation isotope data from Hubbard Brook Watershed 3 isotope data (Campbell and Green, 2019).

"Hubbard Brook WS3 daily P and Q 1956-2014.txt" contains daily precipitation and streamflow totals for Hubbard Brook Watershed 3.  (USDA Forest Service Northern Research Station, 2016a and 2016b).

"Hubbard Brook WS3 isotope data WY2007.txt", "Hubbard Brook WS3 isotope data WY2008.txt", "Hubbard Brook WS3 isotope data WY2009.txt", "Hubbard Brook WS3 daily P and Q WY2007.txt", "Hubbard Brook WS3 daily P and Q WY2008.txt", and "Hubbard Brook WS3 daily P and Q WY2009.txt" contain subsets of these data for the designated water years.

As the work product of US federal employees, the data in these files are in the public domain.  However, any users of these data should cite the original sources:

Campbell, J. L., and Green, M. B.: Water isotope samples from Watershed 3 at Hubbard Brook Experimental Forest, 2006-2010, https://doi.org/10.6073/pasta/f5740876b68ec42b695c39d8ad790cee, 2019.

USDA Forest Service Northern Research Station: Hubbard Brook Experimental Forest (US Forest Service): Daily Streamflow by Watershed, 1956 - present, https://doi.org/10.6073/pasta/38b11ee7531f6467bf59b6f7a4d9012b, 2016a.

USDA Forest Service Northern Research Station: Hubbard Brook Experimental Forest (US Forest Service): Total Daily Precipitation by Watershed, 1956 - present, https://doi.org/10.6073/pasta/163e416fb108862dc6eb857360fa9c90, 2016b.

en:
Resource Title: EndSplit version 1.0 build 2020.05.16
    Size: 18979 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/b12fafab-7730-4648-a8bc-6afb1944bf3b/resource/bdc05c4b-dd74-4868-b1fb-08cb26107158/download/endsplit_v1.0_20200516.r
    Description: EndSplit_v1.0_20200516.R implements end-member mixing and splitting.

This script is copyright (C) 2020 ETH Zurich and James Kirchner.  Public use is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

But… READ THIS CAREFULLY:
ETH Zurich and James Kirchner make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose.  Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

This script implements end-member mixing and end-member splitting, as described in Kirchner and Allen, "Seasonal partitioning of precipitation between streamflow and evapotranspiration, inferred from end-member splitting analysis", Hydrology and Earth System Sciences, 24, 17-39, https://doi.org/10.5194/hess-24-17-2020, 2020.  Users publishing results based on these scripts should cite that paper.

en:
Resource Title: demonstration output files
    Size: 14152 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/b12fafab-7730-4648-a8bc-6afb1944bf3b/resource/02360e0a-ceec-4bc8-968e-1b17a5a7ad1e/download/demonstration-output-files.zip
    Description: These tab-delimited text files were generated by running EndSplit_demo_v1.0_20200516.R (which in turn calls EndSplit_v1.0_20200516.R) under R version 3.6.0, using the input files contained in "demonstration input data.zip"

end-member-mixing

display_name: end-member-mixing

end-member-splitting

display_name: end-member-splitting

evapotranspiration

display_name: evapotranspiration

isotopes

display_name: isotopes

precipitation

display_name: precipitation

streamflow

display_name: streamflow

tracer

display_name: tracer


en:
Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds.
All metadata can be found in the attached documents.

en: vpd gas-exchange acclimation pinus-sylvestris photosynthesis fluorescence drought

en: 2013-2020 gas exchange at Pfynwald

envi

en: Environment

en:
Resource Title: Pfynwald gas exchange
    Size: 4072706 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/3d0f2a0a-c365-4f15-a8e7-312943cbcad6/download/pfynwald_gasexchange_201306_202010.csv
    Description: Full dataset of Pfynwald gas exchange data taken in the period from June 2013 to October 2020.
All metdata can be found in attached documents.
Data uploaded after quality control using guidelines by Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Methods light response
    Size: 607 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/c5ef8bc5-79ab-4aec-9e02-d031e1e7d976/download/methodsmetadata_lightcurves_darkresp.csv
    Description: Methods and parameters for light response curves

en:
Resource Title: Methods fluorescence
    Size: 534 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/1d2343e4-bdf9-4ff0-9582-0c9ef11e139e/download/methodsmetadata_fluoresence.csv
    Description: Parameters and methodology for Fluorescence measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Methods ACi curves
    Size: 731 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/c7536938-120e-4975-97e4-e40649637634/download/methodsmetadata_acicurves.csv
    Description: Parameters and methods for CO2 response curves of Photosynthesis.

Metatdata format by
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Variable names and units
    Size: 15839 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/39614a56-a982-4123-a8d6-e9aaa51c838a/download/variable_names_units.xlsx
    Description: Variable names, description and units for the Pfynwald Gas exchange data

en:
Resource Title: Methods survey
    Size: 596 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/229fbf92-a0ff-44b5-b799-b55fabe2b99c/download/methodsmetadata_point.csv
    Description: Parameters and methods for point measurements / survey measurements

en:
Resource Title: Methods diurnal measurements
    Size: 593 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/45f2d648-386c-42bb-b766-6f804e7c7de6/download/methodsmetadata_diurnal.csv
    Description: Parameters and methodology for diurnal measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Instrument details
    Size: 1174 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/e7342279-bf44-451b-afa2-78cb77babf5e/download/instrumentdetails_pfynwald.csv
    Description: Instrument details for all LiCor instruments used during collection of dataset.

Metatdata created following guidelines from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

acclimation

display_name: acclimation

drought

display_name: drought

fluorescence

display_name: fluorescence

gas-exchange

display_name: gas-exchange

photosynthesis

display_name: photosynthesis

pinus-sylvestris

display_name: pinus-sylvestris

vpd

display_name: vpd


en: In order to quantify effects of ozone on Swiss forest ozone flux calculations are needed. Currently 5 stations are operated to measure the ozone load on forests. These data form the basis for ozone flux calculations. The ozone flux calculation is carried out with the DO3SE model (Büker et al. 2012). This can then be used for epidemiological evaluations for the Swiss forest (Thomas et al. 2005, Braun et al. 2014, Braun et al. 2017, Braun et al. 2020, Braun et al. 2021, Braun et al. 2022).

en: ozone long-term-forest-ecosystem-research wdb swiss-forest-lab long-term-monitoring

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: Ozone measurement and analysis in the Intercantonal Forest Observation Program

format: HTML

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

long-term-monitoring

display_name: long-term-monitoring

ozone

display_name: ozone

swiss-forest-lab

display_name: swiss-forest-lab

wdb

display_name: wdb


en: The dataset contains for three variables (snow water equivalent, surface water input and liquid precipitation) 50 realizations of current and future climate periods for two time horizons (mid end end of century), two emission senarions (RCP 4.5 and 8.5) and 10 climate model chains (all EUR11 chains within CH2018). To quantify natural climate variability for projections of snow conditions and resulting rain-on-snow (ROS) flood events, a weather generator was applied to simulate inherently consistent climate variables for multiple realizations of current and future climates at 100 m spatial and hourly temporal resolution over a 12 x 12 km high-altitude study area in the Swiss Alps. The output of the weather generator was used as input for subsequent simulations with an energy balance snow model. The data was extracted in 2021 from original model output.

en: snow-water-equivalent uncertainty cryosphere rain-on-snow climate-change-impact natural-climate-variability

en: Multiple realizations of daily snow water equivalent, surface water input and liquid precipitation projections for mid- and late-century

climate-change-impact

display_name: climate-change-impact

cryosphere

display_name: cryosphere

natural-climate-variability

display_name: natural-climate-variability

rain-on-snow

display_name: rain-on-snow

snow-water-equivalent

display_name: snow-water-equivalent

uncertainty

display_name: uncertainty


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

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

envi

en: Environment

en:
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.

en:
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:
Monitoring of vertebrates of the lower Magdalena river through eDNA metabarcoding
The Magdalena River basin harbors a large biodiversity of vertebrates, with numerous endemic species, many of which are threatened. Here, we used environmental DNA (eDNA) metabarcoding, with two primer sets targeting different regions of the mitochondrial DNA 12S ribosomal RNA gene, to detect vertebrate diversity in the Magdalena River. We detected a total of 159 vertebrate taxa, not only aquatic but also terrestrial, arboreal, and aerial. The diversity of these vertebrates increases in relation to the proximity to the river mouth with a change in the composition of the assemblage of aquatic vertebrates detected. We conclude that eDNA metabarcoding allows characterizing vertebrate assemblages in large rivers, assessing conservation status, and elucidating biodiversity patterns with minimal ecosystem disturbance. Samples were taken at the sides of the river or in the center using a boat. At each station, we performed two filtration replicates using a peristaltic pump to conduct environmental DNA (eDNA) sampling. Each filtration targeted a maximum duration of 1 hours, during which a maximum of 30 liters of water were filtered through each capsule. After filtration, the water inside the capsules was removed, and the capsules were filled with 50 ml of conservation buffer for preservation at room temperature. We followed strict contamination control protocols throughout both the fieldwork and laboratory processes, adhering to the guidelines of Valentini et al. (2016). To prevent contamination, each sample was processed using disposable gloves and single-use filtration equipment. The MiSeq Reagent Kit v3 (2x75 bp) (Illumina, San Diego, CA, USA) was used for paired-end sequencing at a theoretical sequencing depth of 200,000 reads per sample.
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: edna fish teleo colombia magdalena metabarcoding vert01

en: Environmental DNA Freshwater Colombia Magdalena 2022

colombia

display_name: colombia

edna

display_name: edna

fish

display_name: fish

magdalena

display_name: magdalena

metabarcoding

display_name: metabarcoding

teleo

display_name: teleo


de: Die PLS Parkleitsystem St.Gallen AG misst die freien Parkplätze in den Parkhäusern der Stadt St.Gallen. Dieser Datensatz zeigt die freien Parkplätze in Echtzeit ([https://www.pls-sg.ch/parkraeume/](https://www.pls-sg.ch/parkraeume/)).Zu statistischen Auswertungen der Parkhausbelegung können die CityParking St. Gallen AG ([www.cityparking.ch](http://www.cityparking.ch)) oder die PLS Parkleitsystem St.Gallen AG Auskunft geben.

de: parkhaus parkplatz verkehr auto real-time

stadt-st-gallen

fr: Avec une population de 80 000 habitants, Saint-Gall, huitième ville de Suisse, est la métropole économique, politique, sociale et culturelle de la Suisse orientale. Ses 1400 ans d'histoire se mêlent à la créativité urbaine, à une économie innovante et à un paysage préservé.

en: With a population of 80,000, St.Gallen, Switzerland’s eighth largest city, is the economic, political, social and cultural metropolis of eastern Switzerland. Its 1400 years of history blend with urban creativity, an innovative economy and an unspoilt landscape.

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

it: Con una popolazione di 80.000 abitanti, San Gallo, l'ottava città più grande della Svizzera, è la metropoli economica, politica, sociale e culturale della Svizzera orientale. I suoi 1400 anni di storia si fondono con la creatività urbana, un'economia innovativa e un paesaggio incontaminato.

de: Stadt St.Gallen

en: City of St.Gallen

fr: Ville de Saint-Gall

it: Città di San Gallo

political_level: commune

de: stadt-st-gallen

value: DCAT Harvester Stadt St. Gallen

tran

de: Verkehr

en: Transport

fr: Transports

it: Trasporti

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (csv)

de: csv

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (json)

de: json

format: JSON

media_type: application/json

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (fgb)

de: fgb

format: OCTET

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (geojson)

de: geojson

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (gpx)

de: gpx

format: GPX

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (jsonl)

de: jsonl

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (kml)

de: kml

format: KML

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (ov2)

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (parquet)

de: parquet

format: PARQUET

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (rdfxml)

de: rdfxml

format: RDF XML

media_type: application/rdf+xml

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (jsonld)

de: jsonld

format: JSON-LD

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (turtle)

de: turtle

format: RDF Turtle

media_type: text/turtle

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (n3)

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (shp)

de: shp

de: Freie Parkplätze in der Stadt St.Gallen (PLS) (xls)

de: xls


de: Der Datensatz zeigt die verfügbaren E-Scooter in der Stadt St.Gallen. Die Daten stammen von der API der Shared Mobility Plattform des BFEs und beziehen sich auf sämtliche freefloating Angebote in der Stadt St.Gallen. Zurzeit sind in der Stadt St.Gallen lediglich die E-Scooter von Tier verfügbar.Weitere Informationen zum Datensatz unter: [https://opendata.swiss/de/dataset/standorte-und-verfugbarkeit-von-shared-mobility-angeboten](https://opendata.swiss/de/dataset/standorte-und-verfugbarkeit-von-shared-mobility-angeboten)[](https://opendata.swiss/de/dataset/standorte-und-verfugbarkeit-von-shared-mobility-angeboten)Beschreibung der API und der Daten unter: [https://www.sharedmobility.ch/info](https://www.sharedmobility.ch/info) und [https://github.com/NABSA/gbfs/blob/v2.0/gbfs.md](https://github.com/NABSA/gbfs/blob/v2.0/gbfs.md)

de: scooter tier sharing freefloating

stadt-st-gallen

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

de: Stadt St.Gallen

de: stadt-st-gallen

de: Verkehr

de: Verfügbare E-Scooter in der Stadt St.Gallen (csv)

de: csv

de: Verfügbare E-Scooter in der Stadt St.Gallen (json)

de: json

de: Verfügbare E-Scooter in der Stadt St.Gallen (fgb)

de: fgb

de: Verfügbare E-Scooter in der Stadt St.Gallen (geojson)

de: geojson

de: Verfügbare E-Scooter in der Stadt St.Gallen (gpx)

de: gpx

de: Verfügbare E-Scooter in der Stadt St.Gallen (jsonl)

de: jsonl

de: Verfügbare E-Scooter in der Stadt St.Gallen (kml)

de: Verfügbare E-Scooter in der Stadt St.Gallen (ov2)

de: Verfügbare E-Scooter in der Stadt St.Gallen (parquet)

de: Verfügbare E-Scooter in der Stadt St.Gallen (rdfxml)

de: Verfügbare E-Scooter in der Stadt St.Gallen (jsonld)

de: Verfügbare E-Scooter in der Stadt St.Gallen (turtle)

de: Verfügbare E-Scooter in der Stadt St.Gallen (n3)

de: Verfügbare E-Scooter in der Stadt St.Gallen (shp)

de: Verfügbare E-Scooter in der Stadt St.Gallen (xls)


entsorgungsstatistik-stadt-st-gallen

de: Die Stadt St.Gallen stellt ihre Entsorgungsstatistik als Open Data zur Verfügung. In diesem Datensatz enthalten sind die Mengen der verschiedenen Abfallfraktionen Kehrricht, Karton, Papier, Glas, Dosen / Alu, Altmetall, Sonderabfall und Altöl, falls vorhanden aufgeteilt nach Unterkategorie, Entsorgungsart (Strassensammlung/Annahmestelle) und Abfuhrgebiet. Der Datensatz zeigt die Statistik seit dem Jahr 2015 und wird laufend aktualisiert.

de: entsorgung recycling abfuhr abfall

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

de: Stadt St.Gallen

de: stadt-st-gallen

de: Entsorgungsstatistik Stadt St.Gallen

title_for_slug: entsorgungsstatistik-stadt-st-gallen

envi

de: Umwelt

de: Entsorgungsstatistik Stadt St.Gallen (csv)

de: csv

de: Entsorgungsstatistik Stadt St.Gallen (json)

de: json

de: Entsorgungsstatistik Stadt St.Gallen (jsonl)

de: Entsorgungsstatistik Stadt St.Gallen (parquet)

de: parquet

de: Entsorgungsstatistik Stadt St.Gallen (rdfxml)

de: rdfxml

de: Entsorgungsstatistik Stadt St.Gallen (jsonld)

de: jsonld

de: Entsorgungsstatistik Stadt St.Gallen (turtle)

de: turtle

de: Entsorgungsstatistik Stadt St.Gallen (n3)

de: Entsorgungsstatistik Stadt St.Gallen (xls)

de: xls

abfall

display_name: abfall

abfuhr

display_name: abfuhr

entsorgung

display_name: entsorgung

recycling

display_name: recycling


de: Der Datensatz bildet eine Schnittstelle zum Newsfeed der Medienmitteilungen der Stadtpolizei St.Gallen. Der Link zum Newsfeed befindet sich unter "Referenzen".

de: newsfeed polizei medienmitteilung real-time news

stadt-st-gallen

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

de: Stadt St.Gallen

de: stadt-st-gallen

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

fr: Gouvernement et secteur public

it: Governo e settore pubblico

de: Newsfeed Medienmitteilungen der Stadtpolizei St.Gallen (csv)

de: Newsfeed Medienmitteilungen der Stadtpolizei St.Gallen (json)

de: Newsfeed Medienmitteilungen der Stadtpolizei St.Gallen (jsonl)

de: jsonl

de: Newsfeed Medienmitteilungen der Stadtpolizei St.Gallen (parquet)

de: Newsfeed Medienmitteilungen der Stadtpolizei St.Gallen (rdfxml)

de: Newsfeed Medienmitteilungen der Stadtpolizei St.Gallen (jsonld)

de: Newsfeed Medienmitteilungen der Stadtpolizei St.Gallen (turtle)

de: Newsfeed Medienmitteilungen der Stadtpolizei St.Gallen (n3)

de: Newsfeed Medienmitteilungen der Stadtpolizei St.Gallen (xls)

medienmitteilung

display_name: medienmitteilung

news

display_name: news

newsfeed

display_name: newsfeed

polizei

display_name: polizei

real-time

display_name: real-time


de: Der Datensatz zeigt alle auf den Sites des Stadt St.Galler CMS verfügbaren Webseiten. Diese Webseiten werden mit den Analytics-Zahlen aus Siteimprove verknüpft (last_month, last_year) und mit vorhandenen Feedback-Umfragen aus Siteimprove. Die Daten stammen aus der Siteimprove API (Siehe Referenz)

de: webseite cms aufrufe klicks

de: Webseitenzugriffe der Stadt St.Gallen (Siteimprove Analytics) (csv)

de: csv

de: Webseitenzugriffe der Stadt St.Gallen (Siteimprove Analytics) (json)

de: json

de: Webseitenzugriffe der Stadt St.Gallen (Siteimprove Analytics) (jsonl)

de: Webseitenzugriffe der Stadt St.Gallen (Siteimprove Analytics) (parquet)

de: parquet

de: Webseitenzugriffe der Stadt St.Gallen (Siteimprove Analytics) (rdfxml)

de: rdfxml

de: Webseitenzugriffe der Stadt St.Gallen (Siteimprove Analytics) (jsonld)

de: jsonld

de: Webseitenzugriffe der Stadt St.Gallen (Siteimprove Analytics) (turtle)

de: turtle

de: Webseitenzugriffe der Stadt St.Gallen (Siteimprove Analytics) (n3)

de: Webseitenzugriffe der Stadt St.Gallen (Siteimprove Analytics) (xls)

de: xls

aufrufe

display_name: aufrufe

cms

display_name: cms

klicks

display_name: klicks

webseite

display_name: webseite


de: Die Stadt St.Gallen verfügt an der Vadianstrasse (Höhe St.Galler Stadtwerke) über einen Sensor, der die Anzahl vorbeigehender Fussgänger misst. Dieser Datensatz zeigt die Anzahl Personen von rechts (Neumarkt) und links (Multergasse) kommend, sowie deren Summe stündlich aggregiert.Der Datensatz zeigt unbearbeitete Live-Sensordaten. Das heisst, Messfehler oder Messunterbrüche beim Sensor werden nicht erfasst oder korrigiert.Die Archivdaten der früheren Jahre 2019-2024 (Juni) können Sie unter folgendem Link als .csv-Datei herunterladen:[Passantenfrequenz Vadianstrasse 2019-2024](http://stada.sg.ch/publicdocs/ogd_archiv/fussganger-stgaller-innenstadt-vadianstrasse-archivdaten-2019-2024.csv)

de: fussganger real-time sensor passanten offene-sensordaten

stadt-st-gallen

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

de: Stadt St.Gallen

de: stadt-st-gallen

tran

de: Verkehr

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (csv)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (json)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (fgb)

de: fgb

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (geojson)

de: geojson

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (gpx)

de: gpx

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (jsonl)

de: jsonl

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (kml)

de: kml

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (ov2)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (parquet)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (rdfxml)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (jsonld)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (turtle)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (n3)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (shp)

de: shp

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) (xls)