en:
This data set includes information on all observed and simulated snow profiles that were used to train and validate the
random forest model described in Mayer et al. (2022). The RF model was trained to assess snow instability from simulated snow stratigraphy. The data set contains observed snow profiles from the region of Davos (DAV subset, 512 profiles) and from all over Switzerland (SWISS subset, 230 profiles). For each observed snow profile, there is a corresponding simulated profile which was obtained using meteorological input data for the numerical snow cover model SNOWPACK. The information on the observed snow profile contains a Rutschblock test result including the depth of the failure interface. As part of the study described in Mayer et al. (2022), each observed snow profile was manually compared to its simulated counterpart and the simulated layer corresponding to the Rutschblock failure layer was identified.
The data are provided in the following form: one file each per observed and simulated snow profile (2x512 files DAV, 2x230 files SWISS), two files (1 file DAV, 1 file SWISS) containing the observed information on snow instability, the allocation between observed and simulated failure layer, and all features extracted from the simulated weak layers that were used to develop the RF model.

en: Observed and simulated snow profile data

en: snow-stratigraphy snow-instability snowpack-simulation snow-profiles snowpack rutschblock failure-layer

de:
Resource Title: Observed snow profiles
    Size: 261432 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f109f639-c6c8-46d6-82fd-6a5dbc2bb114/resource/89fd369e-f7d9-49b1-8d24-f9fe3b15cd08/download/observed_snow_profiles.zip
    Description: Observed snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding simulated profile in the "simulated_profiles" folder. One row corresponds to one observed snow layer. The content of the columns is described in Table 2  of the ReadMe file.

de:
Resource Title: Simulated snow profiles
    Size: 8635143 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f109f639-c6c8-46d6-82fd-6a5dbc2bb114/resource/adaf78bb-27a6-4ab9-ae40-ff114e683496/download/simulated_snow_profiles.zip
    Description: Simulated snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding observed profile in the "observed_profiles" folder. One row corresponds to one simulated snow layer. The content of the columns 1-7 is described in Table 3 of the ReadMe file. The remaining columns (8-31) contain all features that were used in the development of the RF model and  are described in Table 1 of the ReadMe file.

de:
Resource Title: ReadMe
    Size: 140674 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/f109f639-c6c8-46d6-82fd-6a5dbc2bb114/resource/2156a195-28ea-418e-ad7e-4af7b5337d7a/download/readme.pdf
    Description: ReadMe file explaining data structure and content

de:
Resource Title: SWISS data set: Properties of observed snow profiles and simulated failure layers
    Size: 105662 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f109f639-c6c8-46d6-82fd-6a5dbc2bb114/resource/8307de98-3d32-40de-97e8-e938a026cf2b/download/properties_observed_and_simulated_swiss.csv
    Description: For each profile pair from the SWISS data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. Please note that only those profile pairs which fulfilled the similarity criteria (column similarity_obs_sim = 1, 121 profiles) were used to validate the RF model. The content of the columns is explained in Table 1 of the ReadMe file.

de:
Resource Title: DAV data set: Properties of observed snow profiles and simulated failure layers
    Size: 228035 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f109f639-c6c8-46d6-82fd-6a5dbc2bb114/resource/98972dcd-f6bb-4391-8dfa-1ce22cd3d7cc/download/properties_observed_and_simulated_dav.csv
    Description: For each profile pair from the DAV data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. The content of the columns is explained in Table 1 of the ReadMe file. Only those profile pairs which fulfilled predefined similarity criteria (column
"similarity_obs_sim" = 1) and which belonged to the stability classes "stable" and "unstable" (column "stability_class"
= 0 or 1) were used to train the RF model. Please note that for each of the two snow profiles with RB score 7 (profile
IDs 7228 and 9526), three additional layers were included in this data set to obtain a balanced set of training data (73
unstable and 73 stable profiles).

failure-layer

display_name: failure-layer

rutschblock

display_name: rutschblock

snow-instability

display_name: snow-instability

snow-profiles

display_name: snow-profiles

snow-stratigraphy

display_name: snow-stratigraphy

snowpack

display_name: snowpack

snowpack-simulation

display_name: snowpack-simulation


$oid: OBSOLETE

de: EnviDat

en: Compiled data on the impacts of seven important NNTs (Acacia dealbata, Ailanthus altissima, Eucalyptus globulus, Prunus serotina, Pseudotsuga menziesii, Quercus rubra, Robinia pseudoacacia) on physical and chemical soil and biodiversity in Europe, and summarise commonalities and differences. A total of 107 publications considered, studies referred to biodiversity attributes and soil properties: 2804 lines and 30 rows.

en: Impact of non-native tree species in Europe on soil properties and biodiversity: a review

en: biogeography biodiversity soil-impacts forest-management pairwise-stand-comparisons

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

type: dataset

key: guid

value: Envidat Harvester

key: uri

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

de:
Resource Title: references
    Size: 24932 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/74062fb9-588e-462b-9125-26bc8cb7d1e6/resource/f55b90cb-3baa-4557-82e9-d870a1d02655/download/references.xlsx
    Description: Bibliography of all references cited in data_wohlgemuth_etal_Neobiota_2022.

format: XLS

de:
Resource Title: headers
    Size: 10213 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/74062fb9-588e-462b-9125-26bc8cb7d1e6/resource/4c8d584a-399a-48a9-a20a-c42f71b08dbf/download/headers.xlsx
    Description: Description of headers for data_wohlgemuth_etal_Neobiota_2022

de:
Resource Title: data_wohlgemuth_neobiota_2022
    Size: 729955 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/74062fb9-588e-462b-9125-26bc8cb7d1e6/resource/84c48309-eef7-4b07-baa2-59a0a1d75015/download/wohlgemuth_etal_neobiota_2022.csv
    Description: Baseline data

format: CSV

media_type: text/csv

biodiversity

display_name: biodiversity

biogeography

display_name: biogeography

forest-management

display_name: forest-management

pairwise-stand-comparisons

display_name: pairwise-stand-comparisons

soil-impacts

display_name: soil-impacts


en:
This data set was used to test whether species specialized to high elevations or with narrow elevational ranges show more conservative (i.e. less variable) trait responses across their elevational distribution, or in response to neighbours, than species from lower elevations or with wider elevational ranges. We did so by studying intraspecific trait variation of 66 species along 40 elevational gradients in four countries (Switzerland, Australia, New Zealand, China) in both hemispheres. As an indication of potential neighbour interactions that could drive trait variation, we also analysed plant species’ height ratio, its height relative to its nearest neighbour.
The following traits and parameters were measured and are available in this data set:
As an indication of plant stature, we measured vegetative and generative height, where vegetative height was distance from soil to highest vegetative leaf and generative height was distance to the highest point on the reproductive shoot. As a measure of reproductive investment, we noted the presence of flowers on the randomly chosen individuals (see below). As a measure of individual and genet basal area, we measured individual plant and patch diameters, in two dimensions (along the largest diameter and perpendicular to it). In clonal plant species, plant diameter was equivalent to an individual rosette, whereas patch diameter referred to the whole genet and could represent the size of a tuft, tussock or cushion. For genera with more singular growth forms (e.g., some Gentiana species) plant and patch diameter were the same. The two diameter measurements were made at right angles, allowing estimates of patch and plant areas to be calculated as an ellipse (i.e., area = 0.5 a 0.5 b Π). All traits were measured on ten randomly selected individuals per site. Flower count data was considered in a binary fashion on a per individual basis (because for some species individuals only produce one flower when flowering) so that the presence or absence of flower(s) was a nominal value between 0 and 10 for each species at each site. We then collected at least three leaves (up to 30 for small and light leaves) from each of the first three individuals selected from each species for determination of leaf dry matter content (LDMC) and specific leaf area (SLA). For calculations of LDMC and SLA, fresh leaves were scanned on a flatbed scanner to determine leaf area. Leaves were then weighed on a balance to a precision of +/- 0.001g, prior to being air dried and reweighed with a balance to a precision of +/- 0.0001g. LDMC was calculated by dividing dry leaf mass by fresh leaf mass. SLA was calculated by dividing leaf area by dry leaf mass. Additionally, within an area of 10 cm diameter around the target individual, we determined the tallest neighbouring species and measured its vegetative and generative height, and estimated the percent cover of the target species, other vegetation, rock, and bare soil.
For more details see Rixen et al. 2022, Journal of Ecology.

en: intratrait

en: plant-traits cold-adapted-plants elevation-range elevation-gradient neighbour-interactions climate-change

de:
Resource Title: R code Rixen_etal_2022_JEcol_AllTraitData
    Size: 74099 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/58a5f3e7-89e3-41c9-a880-5971ecaceab5/resource/bcff4cc4-e77a-4018-8a88-7b0f38d295e6/download/final_code_lme4_supplement.r
    Description:

de:
Resource Title: Rixen_etal_2022_JEcol_AllTraitData
    Size: 3679833 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/58a5f3e7-89e3-41c9-a880-5971ecaceab5/resource/d6845438-a41c-49a6-be0a-254e258a9acd/download/rixen_etal_2022_jecol_alltraitdata.csv
    Description: Plant trait data along elevation gradients on mountains

climate-change

display_name: climate-change

cold-adapted-plants

display_name: cold-adapted-plants

elevation-gradient

display_name: elevation-gradient

elevation-range

display_name: elevation-range

neighbour-interactions

display_name: neighbour-interactions

plant-traits

display_name: plant-traits


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

en: RoRCC

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

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants


energieproduktion-im-kanton-graubunden

de: Der Datensatz enthält eine Aufstellung der jährlichen Energieproduktion in Kilowattstunden (kWh), unterteilt nach verschiedenen Energieträgern im Kanton Graubünden. In den Daten finden sich spezifische Werte für die Erzeugung aus Biomasse, Windkraft, der thermischen Verwertung von Abfällen sowie aus Trinkwasserkraftwerken, Wasserkraftwerken und Photovoltaik-Anlagen.

it: L'insieme di dati contiene una distinta della produzione di energia annua in chilowattora (kWh), suddivisa per diversi vettori energetici nel Cantone dei Grigioni. Nei dati si trovano valori specifici per la produzione da biomassa, energia eolica, valorizzazione termica di rifiuti nonché centrali idroelettriche alimentate da acqua potabile, centrali idroelettriche e impianti fotovoltaici.

kanton-graubuenden

fr: Le canton des Grisons publie progressivement des données publiques en libre accès (Open Government Data) d’offices et de services cantonaux.

de: Der Kanton Graubünden veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.

en: The Canton of Graubünden is gradually publishing open government datasets from cantonal offices and agencies.

it: Il Cantone dei Grigioni pubblica su base continua serie di dati di uffici e servizi cantonali come Open Government Data.

de: Kanton Graubünden

en: Canton of Graubünden

fr: Canton des Grisons

it: Cantone dei Grigioni

political_level: canton

de: kanton-graubuenden

de: Energieproduktion im Kanton Graubünden

title_for_slug: energieproduktion-im-kanton-graubunden

value: DCAT Harvester Kt Graubünden GR

ener

de: Energie

en: Energy

fr: Énergie

it: Energia

de: Energieproduktion im Kanton Graubünden (csv)

it: Produzione di energia nel Cantone dei Grigioni (csv)

de: csv

it: csv

de: Energieproduktion im Kanton Graubünden (json)

it: Produzione di energia nel Cantone dei Grigioni (json)

de: json

it: json

format: JSON

media_type: application/json

de: Energieproduktion im Kanton Graubünden (jsonl)

it: Produzione di energia nel Cantone dei Grigioni (jsonl)

de: jsonl

it: jsonl

de: Energieproduktion im Kanton Graubünden (parquet)

it: Produzione di energia nel Cantone dei Grigioni (parquet)

de: parquet

it: parquet

format: PARQUET

de: Energieproduktion im Kanton Graubünden (rdfxml)

it: Produzione di energia nel Cantone dei Grigioni (rdfxml)

de: rdfxml

it: rdfxml

format: RDF XML

media_type: application/rdf+xml

de: Energieproduktion im Kanton Graubünden (jsonld)

it: Produzione di energia nel Cantone dei Grigioni (jsonld)

de: jsonld

it: jsonld

format: JSON-LD

de: Energieproduktion im Kanton Graubünden (turtle)

it: Produzione di energia nel Cantone dei Grigioni (turtle)

de: turtle

it: turtle

format: RDF Turtle

media_type: text/turtle

de: Energieproduktion im Kanton Graubünden (n3)

it: Produzione di energia nel Cantone dei Grigioni (n3)

de: Energieproduktion im Kanton Graubünden (xlsx)

it: Produzione di energia nel Cantone dei Grigioni (xlsx)

de: xlsx

it: xlsx

energia-rinnovabile

display_name: energia-rinnovabile


de: EnviDat

en:
Based on the detailed tree stump inventory implemented in the Swiss NFI5 (https://www.lfi.ch/lfi/lfi.php), a study was conducted to obtain an accurate assessment of the stumps pool in the Swiss NFI over the last 30 years and to identify its significance for the total dead wood (DW) pool. The NFI5 includes a detailed stump inventory to improve accuracy and completeness of the above-ground DW- pool. Based on available data, stump volume estimates were derived at different accuracies to evaluate the contribution to the total DW-pool over time.
The study found that in Swiss Forests the contribution of stumps to total DW-pool is approximately 25%, and that applying simplifying assumptions to estimate stump volume can result in a significant underestimation of the true size of this pool. This study demonstrates that stumps can be a significant proportion of DW in forests, which should be accounted for in order to improve accuracy and completeness of NFI estimates and derived data such as C stocks for greenhouse gas reporting.
The study is published in Annals of Forest Science (2022) 79:34, https://doi.org/10.1186/s13595-022-01155-7 (open access).
The data can be obtained from the authors upon reasonable request.

en: Stumps as a dead wood resource in forests - data based on the Swiss National Forest Inventory

en: volume national-forest-inventory biodiversity biomass protection-forest carbon

envidat

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

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

it: EnviDat: il portale dei dati ambientali

envi

de: Umwelt

it: Ambiente

de:
Resource Title: NFI2
    Size: 78643 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/69071e62-9dc2-4b61-91c1-322b0c340a60/download/nfi2.zip
    Description: Data on dead standing and downed trees for the NFI2

format: ZIP

media_type: application/zip

de:
Resource Title: Artikel - Annals of Forest Science
    Size: 1673213 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/dd13b5a9-758e-4416-ac74-446370307374/download/didionabegg2022.pdf
    Description:

format: PDF

media_type: application/pdf

de:
Resource Title: NFI1
    Size: 42999 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/9f931dea-8d9b-4d16-b8bd-d933a98e8d9e/download/nfi1.zip
    Description: Data on dead standing and downed trees for the NFI1

de:
Resource Title: ReadMe_Files
    Size: 1278 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/8de64d6a-4d7a-4233-a5ab-c4485b1f40a6/download/readme_files.csv
    Description: Files and contents

de:
Resource Title: Lanz 2014
    Size: 105307 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/72f417d6-3d19-4790-831c-9511f2169b8d/download/international_de.pdf
    Description: A short overview over stump assessment (field protocol) in some European NFIs

de:
Resource Title: NFI3
    Size: 482387 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/f8dc0cfb-50f1-4f74-b428-27b8a690e406/download/nfi3.zip
    Description: Data on dead standing and downed trees, lying dead wood, and stumps for the NFI3

de:
Resource Title: NFI5
    Size: 488946 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/b27ae215-7eff-4546-9d08-b0c15d82a6e0/download/nfi5.zip
    Description: Data on dead standing and downed trees, lying dead wood, and stumps for the NFI5

de:
Resource Title: NFI4
    Size: 526483 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/94d92a0e-4b3a-43e0-9c1b-1293acda5938/download/nfi4.zip
    Description: Data on dead standing and downed trees, lying dead wood, and stumps for the NFI4

de:
Resource Title: Site Description
    Size: 510752 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/723bfcc7-f2b5-4030-94d5-86bac0f52250/download/sites_2022-03-09.csv
    Description: information on NFI sites throughout the five NFIs considered in this study

de:
Resource Title: ReadMe_Variables
    Size: 3109 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/82cad928-4741-415e-a3c7-f19ca4a0d72e/download/readme_variables.csv
    Description: Variable definitions for the datasets NFI1, NFI2, NFI3, NFI4 and NFI5

biomass

display_name: biomass

carbon

display_name: carbon

national-forest-inventory

display_name: national-forest-inventory

protection-forest

display_name: protection-forest

volume

display_name: volume


de:
Beschreibung
Der Datensatz beinhaltet die Messergebnisse der Zählstellen für den motorisierten Individualverkehr auf Kantonsstrassen im Kanton Thurgau auf Stundenbasis, aufgeschlüsselt nach verschiedenen Fahrzeugklassen.Verkehrszähler sind Teil des Verkehrsmonitorings und beinhalten die Datenerfassung an ausgewählten Strassenquerschnitten auf Kantonsstrassen sowie die Datenübertragung zu den Datenverarbeitungsstellen. Nutzendende der Verkehrsdaten sind unter anderem das Verkehrsmanagement und die Verkehrsstatistik.Datenbezug
Aus Kostengründen können nur die Werte der letzten zwei Wochen direkt von data.tg.ch bezogen werden. Alle anderen Daten - hier für das Jahr 2024 - können auf Jahresbasis über folgenden Link heruntergeladen werden:[https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/2024_fzkl_data.csv.gz](https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/2024_fzkl_data.csv.gz)Die Daten sind verfügbar bis ins Jahr 2011 und die Link Struktur ist dabei jeweils gleich: [https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/[JAHR]_fzkl_data.csv.gz.](https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/[JAHR]_fzkl_data.csv.gz.)Die Daten für das Jahr 2023 können also zum Beispiel über folgenden Link bezogen werden: [https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/2023_fzkl_data.csv.gz](https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/2023_fzkl_data.csv.gz)[](https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/2024_fzkl_data.csv.gz)Hinweise zur NutzungBei der Nutzung der Daten ist zu beachten das lediglich die Daten bis zum letzten abgeschlossenen Jahr validiert sind. Bei den Daten des aktuell laufenden Jahres handelt es sich um Rohdaten, welche zum Ende des Jahres validiert werden.Beachten Sie bei der Interpretation der Daten bitte auch eventuell vorliegende Verkehrsbehinderungen auf der entsprechenden Strasse, welche die Zählung beeinflussen können. Aktuelle Hinweise zu Verkehrsbehinderungen finden sie hier:[https://tiefbauamt.tg.ch/publikationen-zum-verkehr/baustellen/verkehrsbehinderungen.html/4343](https://tiefbauamt.tg.ch/publikationen-zum-verkehr/baustellen/verkehrsbehinderungen.html/4343)Die Zählstellen sind auf MET eingestellt (Spalten zeit_von und zeit_bis), d.h. die Zeitumstellung wird wie in Mitteleuropa ausgeführt. Bei der Umstellung von Winter- auf Sommerzeit fehlt die Stunde der Umstellung, dieser Tag hat dann 23 Stunden. Bei der Umstellung von Sommer- auf Winterzeit ist eine Stunde zu viel enthalten (der Tag hat dann 25 Stunden), die Stunde der Umstellung ist dann doppelt, aber mit unterschiedlichen Verkehrsdaten (da die gleiche Stunde zweimal durchlaufen wird).Auf [map.geo.tg.ch](https://map.geo.tg.ch/apps/mf-geoadmin3/?lang=de&topic=ech&time=2020&layers=strassenverkehrszaehlung_messdaten&layers_timestamp=20200101&E=2723900.00&N=1269850.00&zoom=0) sind alle permanenten Messstellen inkl. einer Jahresübersicht zum Durchschnittlichen Täglichen Verkehr (DTV) dargestellt.Die Daten des laufenden Jahres sind nicht plausibilisiert, es besteht kein Anspruch auf Vollständigkeit

de: verkehr strasse zahlstelle individualverkehr lkw pkw motorrad auto lastwagen anhanger motorisiert verkehrszahlung verkehrszahldaten

kanton-thurgau

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

de: Kanton Thurgau

en: Canton of Thurgau

fr: Canton de Thurgovie

it: Cantone di Turgovia

de: kanton-thurgau

value: TG-Kt DCAT Harvester

tran

de: Verkehr

en: Transport

fr: Transports

it: Trasporti

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (csv)

de: csv

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (json)

de: json

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (fgb)

de: fgb

format: OCTET

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (geojson)

de: geojson

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (gpx)

de: gpx

format: GPX

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (jsonl)

de: jsonl

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (kml)

de: kml

format: KML

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (ov2)

format: TXT

media_type: text/plain

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (parquet)

de: parquet

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (rdfxml)

de: rdfxml

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (jsonld)

de: jsonld

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (turtle)

de: turtle

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (n3)

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (shp)

de: shp

de: Verkehrszähldaten motorisierter Individualverkehr nach Fahrzeugklassen (xls)

de: xls


de: EnviDat

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

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

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

envidat

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

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

de: EnviDat: das Umwelt-Datenportal

envi

de: Umwelt

de:
Resource Title: Soil water pools with soil depth
    Size: 12009 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/2c4be745-1a68-46ed-8e7b-085b9a942230/download/sf3_awc_depth.xlsx
    Description: Average plant available - (AWC), gravitational (GWC) and residual (RES) water capacity per soil depth layer of the Swiss forest.

de:
Resource Title: Posterior LWF-Brook90 model parameters
    Size: 57259 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/d6d84cfe-e544-4422-a271-d8c9a58e76e2/download/f3_pars_ag_bg.csv
    Description: Sensitive above and belowground parameters of LWF-Brook90 model are provided for best runs of the calibration against soil matric potential data.

de:
Resource Title: measured soil matric potential
    Size: 493436 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/f250f13e-94ef-4533-961e-30745b76d75b/download/f2_swp_both.csv
    Description: In daily resolution for a site near Neunkirch and Hohtenn from 2014 to 2018.

de:
Resource Title: monthly covariance measurements
    Size: 17375 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/9c48a9dd-1229-473d-a1a7-a89feb7439e8/download/f2_eddy_bothl.csv
    Description: Data from Davos and Lägeren from 2013-2019

de:
Resource Title: Ratio of actual to potential transpiration
    Size: 2946824 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/44457b71-c66d-4034-891a-f5231b17d8d5/download/f7_tatp.zip
    Description: Simulated monthly values at 500m spatial resolution.

de:
Resource Title: water balance fluxes
    Size: 1644317 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/4117d785-23a1-4638-81d5-c8817578fa80/download/f5_water_balance.zip
    Description: Average yearly simulated water fluxes (mm) for the Swiss forest at 500m spatial resolution.

de:
Resource Title: Root distribution and root water uptake
    Size: 38338 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/52c00def-d990-49ea-bd5d-12c16f66418f/download/f6_root_distribution.zip
    Description: Root density distribution derived from 44 soil profiles and simulated daily root water uptake (mm) aggregated for deciduous and coniferous trees across Switzerland.

de:
Resource Title: Gravitational water capacity (mm)
    Size: 554202 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/1d8bc26b-abec-48ac-bc2d-9d56a0e9de19/download/sf1_gwc_mrd.zip
    Description: Calculated for 1m soil depth and the potential rooting depth at 500m spatial resolution.

de:
Resource Title: available water storage capacity (AWC)
    Size: 554752 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/d0b72ce4-9b37-4eba-9a52-680bee79dca4/download/f4_awc_mrd.zip
    Description:

de:
Resource Title: Uncertainties of the available water storage capacity (mm)
    Size: 536920 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/5f0d5d89-207f-4171-8782-0ee50dba382d/download/sf2_awc_uncertainty.zip
    Description: Calculated for 1m soil depth and the potential rooting depth (mrd).

de:
Resource Title: Soil matric potential (kPa)
    Size: 294550 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cd80f5ce-1a2a-46d0-b309-10b0531e71ce/resource/43b22e36-1f5b-4404-9fe4-32259f194426/download/f8_swp_meanaug.tif
    Description: Mean simulated values for August 2018 with 500m spatial resolution.

format: TIFF

media_type: image/tiff

european-summer-drought

display_name: european-summer-drought

physiological-drought

display_name: physiological-drought

plant-available-water-storage-capacity

display_name: plant-available-water-storage-capacity

root-water-uptake

display_name: root-water-uptake

water-balance

display_name: water-balance


de:
BeschreibungDer Datensatz beinhaltet die Messergebnisse der Zählstellen für den motorisierten Individualverkehr auf Kantonsstrassen im Kanton Thurgau auf Stundenbasis.Verkehrszähler sind Teil des Verkehrsmonitorings und beinhalten die Datenerfassung an ausgewählten Strassenquerschnitten auf Kantonsstrassen sowie die Datenübertragung zu den Datenverarbeitungsstellen. Nutzendende der Verkehrsdaten sind unter anderem das Verkehrsmanagement und die Verkehrsstatistik.DatenbezugAus Kostengründen können nur die Werte der letzten zwei Wochen direkt von data.tg.ch bezogen werden. Alle anderen Daten - hier für das Jahr 2024 - können auf Jahresbasis über folgenden Link heruntergeladen werden:[https://ogdtg.ch/verkehrsdaten/total/2024_data.csv.gz](https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/2024_fzkl_data.csv.gz)Die Daten sind verfügbar bis ins Jahr 2011 und die Link Struktur ist dabei jeweils gleich: [https://ogdtg.ch/verkehrsdaten/total/[JAHR]_data.csv.gz.](https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/[JAHR]_fzkl_data.csv.gz.)Die Daten für das Jahr 2023 können also zum Beispiel über folgenden Link bezogen werden: [https://ogdtg.ch/verkehrsdaten/total/2023_data.csv.gz](https://ogdtg.ch/verkehrsdaten/total/2023_data.csv.gz)[](https://ogdtg.ch/verkehrsdaten/fahrzeugklassen/2023_fzkl_data.csv.gz)Hinweise zur NutzungBei der Nutzung der Daten ist zu beachten das lediglich die Daten bis zum letzten abgeschlossenen Jahr validiert sind. Bei den Daten des aktuell laufenden Jahres handelt es sich um Rohdaten, welche zum Ende des Jahres validiert werden.Beachten Sie bei der Interpretation der Daten bitte auch eventuell vorliegende Verkehrsbehinderungen auf der entsprechenden Strasse, welche die Zählung beeinflussen können. Aktuelle Hinweise zu Verkehrsbehinderungen finden Sie hier:[https://tiefbauamt.tg.ch/publikationen-zum-verkehr/baustellen/verkehrsbehinderungen.html/4343](https://tiefbauamt.tg.ch/publikationen-zum-verkehr/baustellen/verkehrsbehinderungen.html/4343)Die Zählstellen sind auf MET eingestellt (Spalten zeit_von und zeit_bis), d.h. die Zeitumstellung wird wie in Mitteleuropa ausgeführt. Bei der Umstellung von Winter- auf Sommerzeit fehlt die Stunde der Umstellung, dieser Tag hat dann 23 Stunden. Bei der Umstellung von Sommer- auf Winterzeit ist eine Stunde zu viel enthalten (der Tag hat dann 25 Stunden), die Stunde der Umstellung ist dann doppelt, aber mit unterschiedlichen Verkehrsdaten (da die gleiche Stunde zweimal durchlaufen wird).Auf [map.geo.tg.ch](https://map.geo.tg.ch/apps/mf-geoadmin3/?lang=de&topic=ech&time=2020&layers=strassenverkehrszaehlung_messdaten&layers_timestamp=20200101&E=2723900.00&N=1269850.00&zoom=0) sind alle permanenten Messstellen inkl. einer Jahresübersicht zum Durchschnittlichen Täglichen Verkehr (DTV) dargestellt.Die Daten des laufenden Jahres sind nicht plausibilisiert, es besteht kein Anspruch auf
Vollständigkeit

de: verkehr individualverkehr zahlstelle auto pkw strasse motorisiert verkehrszahlung verkehrszahldaten

kanton-thurgau

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

de: Kanton Thurgau

de: kanton-thurgau

tran

de: Verkehr

de: Verkehrszähldaten motorisierter Individualverkehr (csv)

de: csv

de: Verkehrszähldaten motorisierter Individualverkehr (json)

de: json

de: Verkehrszähldaten motorisierter Individualverkehr (fgb)

de: fgb

de: Verkehrszähldaten motorisierter Individualverkehr (geojson)

de: geojson

de: Verkehrszähldaten motorisierter Individualverkehr (gpx)

de: gpx

de: Verkehrszähldaten motorisierter Individualverkehr (jsonl)

de: jsonl

de: Verkehrszähldaten motorisierter Individualverkehr (kml)

de: kml

de: Verkehrszähldaten motorisierter Individualverkehr (ov2)

de: Verkehrszähldaten motorisierter Individualverkehr (parquet)

de: parquet

de: Verkehrszähldaten motorisierter Individualverkehr (rdfxml)

de: rdfxml

de: Verkehrszähldaten motorisierter Individualverkehr (jsonld)

de: jsonld

de: Verkehrszähldaten motorisierter Individualverkehr (turtle)

de: turtle

de: Verkehrszähldaten motorisierter Individualverkehr (n3)

de: Verkehrszähldaten motorisierter Individualverkehr (shp)

de: shp

de: Verkehrszähldaten motorisierter Individualverkehr (xls)


de: EnviDat

en:
Extreme events impact on the Swiss forest economy: the sawmill perspective
Supplementary Information
This survey aimed at answering three main questions: (i) What are the Swiss sawmills challenges and actions taken after a large storm/windthrow?, (ii) How do these challenges and actions vary across sawmill size and location?, and (iii) is adaptation from the sawmills to extreme events possible, with regards to wood type, products and required infrastructure?
Informations supplémentaires
Cette enquête visait à répondre à trois questions principales : (i) Quels sont les défis et les mesures prises par les scieries suisses après une grosse tempête ou un coup de vent ? (ii) Comment ces défis et ces mesures varient-ils selon la taille et l'emplacement de la scierie ? et (iii) l'adaptation des scieries aux événements extrêmes est-elle possible, en ce qui concerne le type de bois, les produits et l'infrastructure requise ?

Ziel dieser Umfrage war die Beantwortung von drei Hauptfragen: (i) Welche
s sind die Herausforderungen und Massnahmen der Schweizer Sägewerke nach einem grossen Sturm/Windwurf?, (ii) Wie unterscheiden sich diese Herausforderungen und Massnahmen je nach Grösse und Standort des Sägewerks? und (iii) Ist eine Anpassung der Sägewerke an Extremereignisse möglich, in Bezug auf Holzart, Produkte und erforderliche Infrastruktur?

en: Impact des événements météorologiques extrêmes sur l'économie forestière suisse: le point de vue des scieries

en: wood-market damaged-wood stockage-humide chablis scieries wind-disturbance wet-storage bois-endommage marche-du-bois sawmills

envidat

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

envi

de: Umwelt

en: Environment

bois-endommage

display_name: bois-endommage

chablis

display_name: chablis

damaged-wood

display_name: damaged-wood

marche-du-bois

display_name: marche-du-bois

sawmills

display_name: sawmills

scieries

display_name: scieries

stockage-humide

display_name: stockage-humide

wet-storage

display_name: wet-storage

wind-disturbance

display_name: wind-disturbance

wood-market

display_name: wood-market


en:
This is the freely available part of the data used in the publication by Techel et al. (2022): _On the correlation between a sub-level qualifier refining the danger level with observations and models relating to the contributing factors of avalanche danger_
- danger signs
- human triggered avalanches
- rutschblock test results  (still to be added)
- extended column test results    (still to be added)

en: Observational data: avalanche observations, danger signs and stability test results, Switzerland (2016/2017 to 2020/2021 )

en: avalanche stability-tests avalanche-danger avalanche-danger-level avalanche-observations

de:
Resource Title: Human-triggered avalanches
    Size: 96836 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dfacb44d-49d2-4841-b3ee-a4e9eee8d22f/resource/5fee4967-1a72-4ef1-be4a-cfdbe9184802/download/humantriggeredavalanches_exportenvidat.csv
    Description: This CSV contains the density of human-triggered avalanches relative to the total potential release area for each day and region with the same forecast sub-level. The following variables are contained:

- *date* - date
- *dangerLevel*  - the danger level forecast valid on the day of interest
- *levelBullSub*  - the sub-level forecast valid on the day of interest
- *rhoSz2* - density of avalanche larger or equal than size 2 per *pra*
- *rhoSz3* - density of avalanche larger or equal than size 3 per *pra*
- *pra*  - total surface area in km^2, which is considered as a potential release area within the warning regions forecast with the same sub-level on the day of interest
- *nRegions* - number of warning regions with the same sub-level

de:
Resource Title: Observed danger signs
    Size: 180841 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dfacb44d-49d2-4841-b3ee-a4e9eee8d22f/resource/576b0dd4-fd5a-4c25-998c-e50ef630428d/download/dangersigns_exportenvidat.csv
    Description: This CSV contains observational data on danger signs. The following variables are contained:
- *date* - date of the observation
- *sectorId* - this is the sector id as used in the Swiss avalanche forecast
- *whumpfCracksFrequency* - observations with three classes NONE, RARELY, OFTEN
- *dangerLevel*  - danger level as forecast in the avalanche forecast the evening before
- *levelBullSub*  - sub level as forecast in the avalanche forecast the evening before

de:
Resource Title: Rutschblock test results
    Size: 58925 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dfacb44d-49d2-4841-b3ee-a4e9eee8d22f/resource/ff4243d8-5462-4c4b-b45a-db5c78b7a762/download/rbdata_exportenvidat.csv
    Description: This CSV contains the Rutschblock results used in the study. The following variables are provided:

- *date* - the date the Rutschblock was observed
- *sectorId* - the warning region identifier
- *rbStab*  - the stability class, as described in Figure 3
- *dangerLevel* - the danger level as forecast for the respective warning region on the day of the observation
- *levelBullSub* - the danger level as forecast for the respective warning region on the day of the observation

avalanche

display_name: avalanche

avalanche-danger

display_name: avalanche-danger

avalanche-danger-level

display_name: avalanche-danger-level

avalanche-observations

display_name: avalanche-observations

stability-tests

display_name: stability-tests


en:
Dataset description-br /-
This dataset is a recalculation of the Copernicus 2015 high resolution layer (HRL) of imperviousness density data (IMD) at different spatial/territorial scales for the case studies of Barcelona and Milan. The selected spatial/territorial scales are the following:
 * a)	Barcelona city boundaries
 * b)	Barcelona metropolitan area, Àrea Metropolitana de Barcelona (AMB)
 * c)	Barcelona greater city (Urban Atlas)
 * d)	Barcelona functional urban area (Urban Atlas)
 * e)	Milan city boundaries
 * f)	Milan metropolitan area, Piano Intercomunale Milanese (PIM)
 * g)	Milan greater city (Urban Atlas)
 * h)	Milan functional urban area (Urban Atlas)-br /-
In each of the spatial/territorial scales listed above, the number of 20x20mt cells corresponding to each of the 101 values of imperviousness (0-100% soil sealing: 0% means fully non-sealed area; 100% means fully sealed area) is provided, as well as the converted measure into squared kilometres (km2). -br /- -br /-
-br /- Dataset composition-br /-
The dataset is provided in .csv format and is composed of: -br /-
_IMD15_BCN_MI_Sources.csv_: Information on data sources -br /-
 _IMD15_BCN.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Barcelona:
 * a)	Barcelona city boundaries (label: bcn_city)
 * b)	Barcelona metropolitan area, Àrea metropolitana de Barcelona (AMB) (label: bcn_amb)
 * c)	Barcelona greater city (Urban Atlas) (label: bcn_grc)
 * d)	Barcelona functional urban area (Urban Atlas) (label: bcn_fua)-br /-
 _IMD15_MI.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Milan:
 * e)	Milan city boundaries (label: mi_city)
 * f)	Milan metropolitan area, Piano intercomunale milanese (PIM) (label: mi_pim)
 * g)	Milan greater city (Urban Atlas) (label: mi_grc)
 * h)	Milan functional urban area (Urban Atlas) (label: mi_fua)-br /-
_IMD15_BCN_MI.mpk_: the shareable project in Esri ArcGIS format including the HRL IMD data in raster format for each of the territorial boundaries as specified in letter a)-h). -br /-
Regarding the territorial scale as per letter f), the list of municipalities included in the Milan metropolitan area in 2016 was provided to me in 2016 from a person working at the PIM. -br /-
In the IMD15_BCN.csv and IMD15_MI.csv, the following columns are included:
 * Level: the territorial level as defined above (a)-d) for Barcelona and e)-h) for Milan);
 * Value: the 101 values of imperviousness density expressed as a percentage of soil sealing (0-100%: 0% means fully non-sealed area; 100% means fully sealed area);
 * Count: the number of 20x20mt cells corresponding to a certain percentage of soil sealing or imperviousness;
 * Km2: the conversion of the 20x20mt cells into squared kilometres (km2) to facilitate the use of the dataset.-br /- -br /-
-br /- Further information on the Dataset-br /-
This dataset is the result of a combination between different databases of different types and that have been downloaded from different sources. Below, I describe the main steps in data management that resulted in the production of the dataset in an Esri ArcGIS (ArcMap, Version 10.7) project.-br /-
 1. The high resolution layer (HRL) of the imperviousness density data (IMD) for 2015 has been downloaded from the official website of Copernicus. At the time of producing the dataset (April/May 2021), the 2018 version of the IMD HRL database was not yet validated, so the 2015 version was chosen instead. The type of this dataset is raster.
 2. For both Barcelona and Milan, shapefiles of their administrative boundaries have been downloaded from official sources, i.e. the ISTAT (Italian National Statistical Institute) and the ICGC (Catalan Institute for Cartography and Geology). These files have been reprojected to match the IMD HRL projection, i.e. ETRS 1989 LAEA.
 3. Urban Atlas (UA) boundaries for the Greater Cities (GRC) and Functional Urban Areas (FUA) of Barcelona and Milan have been checked and reconstructed in Esri ArcGIS from the administrative boundaries files by using a Eurostat correspondence table. This is because at the time of the dataset creation (April/May 2021), the 2018 Urban Atlas shapefiles for these two cities were not fully updated or validated on the Copernicus Urban Atlas website. Therefore, I had to re-create the GRC and FUA boundaries by using the Eurostat correspondence table as an alternative (but still official) data source. The use of the Eurostat correspondence table with the codes and names of municipalities was also useful to detect discrepancies, basically stemming from changes in municipality names and codes and that created inconsistent spatial features. When detected, these discrepancies have been checked with the ISTAT and ICGC offices in charge of producing Urban Atlas data before the final GRC and FUA boundaries were defined.-br /-
Steps 2) and 3) were the most time consuming, because they required other tools to be used in Esri ArcGIS, like spatial joins and geoprocessing tools for shapefiles (in particular dissolve and area re-calculator in editing sessions) for each of the spatial/territorial scales as indicated in letters a)-h). -br /-
Once the databases for both Barcelona and Milan as described in points 2) and 3) were ready (uploaded in Esri ArcGIS, reprojected and their correctness checked), they have been ‘crossed’ (i.e. clipped) with the IMD HRL as described in point 1) and a specific raster for each territorial level has been calculated. The procedure in Esri ArcGIS was the following:
 * Clipping: Arctoolbox - Data management tools - Raster - Raster Processing - Clip. The ‘input’ file is the HRL IMD raster file as described in point 1) and the ‘output’ file is each of the spatial/territorial files. The option "Use Input Features for Clipping Geometry (optional)” was selected for each of the clipping.
 * Delete and create raster attribute table: Once the clipping has been done, the raster has to be recalculated first through Arctoolbox - Data management tools - Raster - Raster properties - Delete Raster Attribute Table and then through Arctoolbox - Data management tools - Raster - Raster properties - Build Raster Attribute Table; the "overwrite" option has been selected. -br /-
-br /- Other tools used for the raster files in Esri ArcGIS have been the spatial analyst tools (in particular, Zonal - Zonal Statistics). As an additional check, the colour scheme of each of the newly created raster for each of the spatial/territorial attributes as per letters a)-h) above has been changed to check the consistency of its overlay with the original HRL IMD file. However, a perfect match between the shapefiles as per letters a)-h) and the raster files could not be achieved since the raster files are composed of 20x20mt cells.-br /-
The newly created attribute tables of each of the raster files have been exported and saved as .txt files. These .txt files have then been copied in the excel corresponding to the final published dataset.

en: Soil sealing Barcelona and Milan different territorial levels

en: milan imperviousness soil-sealing urban-atlas barcelona copernicus

de:
Resource Title: IMD15_BCN
    Size: 9402 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/34fc9c0c-1c90-4f87-b3a9-76cc0e888eda/resource/b49ab377-1058-44b0-9db3-eae5af4bb518/download/imd15_bcn.csv
    Description: 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Barcelona

de:
Resource Title: IMD15_BCN_MI
    Size: 9649908 bytes
    Format: .mpk
    URL: https://www.envidat.ch/dataset/34fc9c0c-1c90-4f87-b3a9-76cc0e888eda/resource/feb17f6a-9d3d-49d7-b072-654e3d210975/download/imd15_bcn_mi.mpk
    Description: Shareable project in Esri ArcGIS format including the HRL IMD data in raster format for each of the territorial boundaries as specified in letter a)-h), see Dataset description

de:
Resource Title: IMD15_BCN_MI_Sources
    Size: 2730 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/34fc9c0c-1c90-4f87-b3a9-76cc0e888eda/resource/d023c81b-4318-492a-abbf-44e429e9855d/download/imd15_bcn_mi_sources.csv
    Description: Information on data sources

de:
Resource Title: IMD15_MI
    Size: 9229 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/34fc9c0c-1c90-4f87-b3a9-76cc0e888eda/resource/e4750d6b-e92c-4266-8d15-a04a673ba248/download/imd15_mi.csv
    Description: 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Milan

barcelona

display_name: barcelona

copernicus

display_name: copernicus

imperviousness

display_name: imperviousness

milan

display_name: milan

soil-sealing

display_name: soil-sealing

urban-atlas

display_name: urban-atlas


en:
Supplementary Data Sample Plot Inventory Sihlwald
The Sihlwald is one of the largest contiguous beech forests in the Swiss Plateau region. In the year 2000, timber harvesting was abandoned. Since 2007 the forest has been under strict protection as a natural forest reserve on an area of 1098 ha and since 2008 as a cantonal nature and landscape conservation area (SVO Sihlwald). Since 2010, it carries the national label ‘Nature discovery park’ (‘Naturerlebnispark’). As part of the national monitoring in nature forest reserves, a sampling inventory (calipering threshold of 7 cm) with 226 plots on an area of 917 ha was carried out in the Sihlwald in autumn and early winter 2017. The aim was to describe the state and development of the forest structure and make comparisons with earlier sampling inventories in the same area from 1981, 1989 and 2003.
This dataset contains supplementary tables for the publication by Brändli et al. (2020). The metadata file describes the structure of the tables.

en: natural-forest-dynamics sihlwald fagus-sylvatica forest-reserves forest-inventory

de:
Resource Title: Standing dead trees 2003 - 2017
    Size: 7650 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/19f63643-114b-4e04-afc7-75d9cf73a7d9/resource/9d94affc-b8b6-4e94-8980-87df0df70749/download/standingdeadwood2003_2017.csv
    Description: Contains data on standing dead trees with a DBH >= 8 cm.

de:
Resource Title: Standing living trees 2017
    Size: 92715 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/19f63643-114b-4e04-afc7-75d9cf73a7d9/resource/ffa9e767-aa7b-45d7-8cbd-3347932957c6/download/trees2017.csv
    Description: Contains data on standing, living trees with a DBH >= 7 cm.

de:
Resource Title: Standing dead trees 2017
    Size: 16479 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/19f63643-114b-4e04-afc7-75d9cf73a7d9/resource/2ea64c14-798e-4816-a80f-e88095720643/download/standingdeadwood2017.csv
    Description: Contains data on standing dead trees with a DBH >= 7 cm.

de:
Resource Title: Standing living trees 1981 - 2017
    Size: 417555 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/19f63643-114b-4e04-afc7-75d9cf73a7d9/resource/d3cc5592-e46f-4247-b36d-70214772ee68/download/trees1981_2017.csv
    Description: Contains data on standing, living trees with a DBH >= 8 cm.

de:
Resource Title: Data Description
    Size: 106663 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/19f63643-114b-4e04-afc7-75d9cf73a7d9/resource/fc55aacc-4927-4e94-a405-7e6a26a63388/download/supplementarymaterialsihlwald.pdf
    Description: Describes the available tables

de:
Resource Title: Regeneration 2017
    Size: 67773 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/19f63643-114b-4e04-afc7-75d9cf73a7d9/resource/27f21626-d1a3-4941-815d-019c88c8c618/download/regeneration2017.csv
    Description: Data on regeneration inventory 2017 (living trees between 10 cm height and DBH < 7 cm)

de:
Resource Title: Lying deadwood 2017
    Size: 1349 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/19f63643-114b-4e04-afc7-75d9cf73a7d9/resource/39f93467-552f-4f37-b59f-def4b99ac897/download/lyingdeadwood2017.csv
    Description: Contains data on lying deadwood assessed on 3 transects.

fagus-sylvatica

display_name: fagus-sylvatica

forest-inventory

display_name: forest-inventory

forest-reserves

display_name: forest-reserves

natural-forest-dynamics

display_name: natural-forest-dynamics

sihlwald

display_name: sihlwald


de: EnviDat

en:
This dataset includes discharge and rainfall measurements and deuterium compositions of streamflow, rainfall and groundwater, for four rainfall events and three baseflow snapshot campaigns in the Studibach (Alptal, Switzerland). More specifically, we present the following data:
- Specific discharge at the catchment outlet at 5-minute resolution (mm per hour);
- Rainfall at 5-minute resolution (mm per hour);
- Rainfall deuterium composition (‰);
- Stormflow deuterium composition (‰);
- Groundwater and baseflow deuterium compositions (‰).
For the files containing rainfall and discharge timeseries (QP), and rainfall and streamwater deuterium compositions ("Deuterium_Rainfall" and "Deuterium_Streamwater"), we added the corresponding event identifier (A, B, C or extra) to the file names. For the files containing the groundwater and baseflow deuterium values ("Deuterium_Snapshot") we added the sample collection date to the file name. We included the X and Y coordinates for each data point (coordinate system: CH1903 LV3) as well as the date and time (UTC).
More information on the data collection and preparation can be found in Kiewiet et al. (in review). A detailed description of the baseflow snapshot campaigns can also be found in Kiewiet et al., 2019.

en: Discharge, rainfall, and deuterium compositions of streamwater, rainwater and groundwater, for four rainfall events in the Studibach, Alptal, Switzerland

en: groundwater runoff alptal stable-water-isotopes streamflow

envidat

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

de:
Resource Title: Precipitation and discharge event A
    Size: 13862 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2d765186-0ae0-4b43-bc34-cbad9edba879/download/qp_eventa.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

de:
Resource Title: Deuterium rainfall event A
    Size: 960 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/712f8d2e-129c-4ed4-ae19-eab3d2836511/download/deuterium_rainfall_eventa.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

de:
Resource Title: Precipitation and discharge event C
    Size: 8146 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/684ec1fc-df96-42ab-ba3c-0b4f981776ad/download/qp_eventc.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

de:
Resource Title: Deuterium streamwater event A
    Size: 1273 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2add59a1-5621-4b0b-949e-e144e66de9e8/download/deuterium_streamwater_eventa.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

de:
Resource Title: Deuterium rainfall event C
    Size: 1044 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/993b5d45-b0aa-4bf8-a9b9-1a8fc950ba7a/download/deuterium_rainfall_eventc.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

de:
Resource Title: Deuterium rainfall extra event
    Size: 2228 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2f6feb1a-ccfa-4aac-bacd-335760905550/download/deuterium_rainfall_extraevent.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

de:
Resource Title: Precipitation and discharge extra event
    Size: 45996 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/6983ae41-90ad-4000-9b13-d6a4942e38cb/download/qp_extraevent.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

de:
Resource Title: Deuterium groundwater and baseflow October 2017
    Size: 2208 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/cc4b2f2b-537d-49e2-ac0a-c82216ad99d9/download/deuterium_snapshot_oct2017.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

Date: Date (year-month-day)
Location: Well number or outlet
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)
riparian: riparian wells (i.e. from the riparian-like cluster as presented in Kiewiet et al. (2019)) are marked a one, all other wells are marked a zero
d.D (per mil): Deuterium composition (per mil)

de:
Resource Title: Deuterium groundwater and baseflow August 2017
    Size: 2022 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/287f9bcc-b876-4170-bce7-1e508982c8b9/download/deuterium_snapshot_aug2017.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

Date: Date (year-month-day)
Location: Well number or outlet
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)
riparian: riparian wells (i.e. from the riparian-like cluster as presented in Kiewiet et al. (2019)) are marked a one, all other wells are marked a zero
d.D (per mil): Deuterium composition (per mil)

de:
Resource Title: Precipitation and discharge event B
    Size: 9733 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/51bf0d6f-a68c-4e75-b5a1-1c81bbc7a9ea/download/qp_eventb.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

de:
Resource Title: Deuterium rainfall event B
    Size: 880 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/98b1bd86-e4a4-46f9-a75a-e871cab67aad/download/deuterium_rainfall_eventb.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

de:
Resource Title: Deuterium streamwater event C
    Size: 1246 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2b90dbcd-8fd7-440d-b0e0-4b724d688dc5/download/deuterium_streamwater_eventc.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

de:
Resource Title: Deuterium groundwater and baseflow October 2016
    Size: 2170 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/73fc4834-881f-4547-9b7b-52ca2be61f71/download/deuterium_snapshot_oct2016.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

Date: Date (year-month-day)
Location: Well number or outlet
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)
riparian: riparian wells (i.e. from the riparian-like cluster as presented in Kiewiet et al. (2019)) are marked a one, all other wells are marked a zero
d.D (per mil): Deuterium composition (per mil)

de:
Resource Title: Deuterium streamwater event B
    Size: 1300 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2e8bed6f-98be-47ef-8976-2df51703db3f/download/deuterium_streamwater_eventb.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

de:
Resource Title: Deuterium streamwater extra event
    Size: 1907 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/c09c3cd0-6a4b-4e3d-aa6e-7541241be20a/download/deuterium_streamwater_extraevent.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

alptal

display_name: alptal

groundwater

display_name: groundwater

runoff

display_name: runoff

stable-water-isotopes

display_name: stable-water-isotopes

streamflow

display_name: streamflow


hydrometrie-thurgau-messstaionen

de: Der Datensatz beinhaltet Informationen zu den Messtationen des Hydrologischen Messnetzes im Kanton Thurgau. Über die im Datensatz enthaltene Objekt ID (obj_id) können die Daten mit den jeweiligen Messwerten gejoint werden. Es ist zu beachten, dass eine Messstation mehrere Objekt ID enthalten kann. Jeder Parameter einer Messstation hat eine Objekt ID.Datenbezug erfolgt über ThurGIS. Hier können alle Messtationen und deren Standorte kartografisch eingesehen werden.https://map.geo.tg.ch/apps/mf-geoadmin3/?lang=de&topic=ech&layers=hydrologische_messnetze_werterhebung&layers_opacity=0.9

de: gewasserqualitat fliessgewasser gewasser grundwasserschutz temperatur wasserstand bodensee fluss untersee abfluss pegel hydrologie

kanton-thurgau

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

de: Kanton Thurgau

en: Canton of Thurgau

de: kanton-thurgau

de: Hydrometrie Thurgau - Messstationen

title_for_slug: hydrometrie-thurgau-messstaionen

envi

de: Umwelt

de: Hydrometrie Thurgau - Messstationen (csv)

de: csv

de: Hydrometrie Thurgau - Messstationen (json)

de: json

de: Hydrometrie Thurgau - Messstationen (fgb)

de: fgb

de: Hydrometrie Thurgau - Messstationen (geojson)

de: geojson

de: Hydrometrie Thurgau - Messstationen (gpx)

de: gpx

de: Hydrometrie Thurgau - Messstationen (jsonl)

de: jsonl

de: Hydrometrie Thurgau - Messstationen (kml)

de: kml

de: Hydrometrie Thurgau - Messstationen (ov2)

de: Hydrometrie Thurgau - Messstationen (parquet)

de: parquet

de: Hydrometrie Thurgau - Messstationen (rdfxml)

de: rdfxml

de: Hydrometrie Thurgau - Messstationen (jsonld)

de: jsonld

de: Hydrometrie Thurgau - Messstationen (turtle)

de: turtle

de: Hydrometrie Thurgau - Messstationen (n3)

de: Hydrometrie Thurgau - Messstationen (shp)

de: shp

de: Hydrometrie Thurgau - Messstationen (xls)


de: Der Datensatz beinhaltet Daten zur Parkplatzbelegung auf fünf öffentlichen Parkplätzen in Frauenfeld, die in städtischer Hand sind: Unteres Mätteli, Oberes Mätteli, Marktplatz (2 Stunden und 10 Stunden), Altstadt (Freie-Strasse, Bankplatz) sowie Zürcherstrasse (Abschnitt Innenstadt). Die Daten sind auf Stundenbasis aggregiert und beinhalten die durchschnittliche Belegung in %, die Anzahl der Aus- und Einfahrten sowie die mittlere Standzeit (Median) der Fahrzeuge. Alle Parkplätze sind zudem geokodiert. Die Daten werden jeden Tag aktualisiert und beinhalten Daten bis zum Vortag.Die Daten sind Teil des Pilotprojekts Smart Parking Frauenfeld. Mithilfe von Kameras und künstlicher Intelligenz werden hier Daten zur Parksituation auf den jeweiligen Parkplätzen ermittelt.Über die [Regio Frauenfeld App](https://regiofrauenfeld.citymobile.ch/index.php?brandid=11579&apid=1155685913) kann die aktuelle Parksituation auf den fünf Parkplätze anhand von Echtzeit-Daten geprüft werden.[Link zur Desktopansicht der App](https://frauenfeld.citymobile.ch/index.php?apid=2096681313)Datenquelle: Stadt Frauenfeld

de: frauenfeld parken parkplatz marktplatz app live einfahrt ausfahrt standzeit marktplatz oberes-matteli altstatdt zurcherstrasse parquery region-frauenfeld regio-frauenfeld-app frei belegt belegung smart parking pilotprojekt kamera ki kunstliche intelligenz

kanton-thurgau

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

de: Kanton Thurgau

de: kanton-thurgau

regi

de: Regionen und Städte

en: Regions and cities

fr: Régions et villes

it: Regioni e città

tran

de: Verkehr

en: Transport

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (csv)

de: csv

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (json)

de: json

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (fgb)

de: fgb

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (geojson)

de: geojson

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (gpx)

de: gpx

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (jsonl)

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (kml)

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (ov2)

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (parquet)

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (rdfxml)

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (jsonld)

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (turtle)

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (n3)

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (shp)

de: Parkplatzbelegung Stadt Frauenfeld nach Stunden (xls)


parkplatzbelegung-stadt-frauenfeld

de:
Der Datensatz beinhaltet Daten zur Parkplatzbelegung auf fünf öffentlichen Parkplätzen in Frauenfeld, die in städtischer Hand sind: Unteres Mätteli, Oberes Mätteli, Marktplatz (2 Stunden und 10 Stunden), Altstadt (Freie-Strasse, Bankplatz) sowie Zürcherstrasse (Abschnitt Innenstadt). Die Daten werden alle 5 Minuten aktualisiert und beinhalten die Anzahl der belegten, nicht belegbaren und freien Parkplätze, die Gesamtanzahl aller Parkplätze sowie die Koordinaten des jeweiligen Parkplatzes. Die Daten sind Teil des Pilotprojekts Smart Parking Frauenfeld. Mithilfe von Kameras und künstlicher Intelligenz werden hier Daten zur Parksituation auf den jeweiligen Parkplätzen ermittelt.Aus Kapazitätsgründen können über data.tg.ch immer nur die Daten für den aktuellen Tag direkt heruntergeladen werden. Alle Daten werden jedoch historisiert und können jeweils für einen Monat über folgenden Link als komprimierte CSV-Datei (Zip-Datei) bezogen werden:[https://ogdtg.ch/parkdaten/2024_09_parkdaten.csv.gz](https://ogdtg.ch/parkdaten/2024_05_parkdaten.csv.gz) Die URL beinhaltet jeweils den gewünschten Monat für ein Jahr. Mit obigem Link können z. B. Daten für September 2024 (2024-09) bezogen werden.Die generelle Linkstruktur lautet entsprechend wie folgt: [https://ogdtg.ch/parkdaten/JJJJ_MM_parkdaten.csv.gz](https://ogdtg.ch/parkdaten/JJJJ_MM_parkdaten.csv.gz), wobei JJJJ das Jahr (vierstellig) und MM den Monat (zweistellig) bezeichnet.Wichtiger Hinweis: Bei den Daten handelt es sich um unvalidierte Messdaten. Fehlerhafte Datenpunkte aufgrund von Messfehlern können daher nicht ausgeschlossen werden.Über die [Regio Frauenfeld App](https://regiofrauenfeld.citymobile.ch/index.php?brandid=11579&apid=1155685913) kann die aktuelle Parksituation auf den fünf Parkplätze anhand von Echtzeit-Daten geprüft werden.[Link
zur Desktopansicht der App](https://frauenfeld.citymobile.ch/index.php?apid=2096681313)Datenquelle: Stadt Frauenfeld

de: frauenfeld parken live parkplatz marktplatz app oberes-matteli altstatdt zurcherstrasse parquery regio-frauenfeld-app frei belegt belegung smart parking pilotprojekt kamera ki kunstliche intelligenz

kanton-thurgau

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

de: Kanton Thurgau

de: kanton-thurgau

de: Parkplatzbelegung Stadt Frauenfeld

title_for_slug: parkplatzbelegung-stadt-frauenfeld

regi

de: Regionen und Städte

de: Verkehr

de: Parkplatzbelegung Stadt Frauenfeld (csv)

de: csv

de: Parkplatzbelegung Stadt Frauenfeld (json)

de: json

de: Parkplatzbelegung Stadt Frauenfeld (fgb)

de: Parkplatzbelegung Stadt Frauenfeld (geojson)

de: Parkplatzbelegung Stadt Frauenfeld (gpx)

de: Parkplatzbelegung Stadt Frauenfeld (jsonl)

de: jsonl

de: Parkplatzbelegung Stadt Frauenfeld (kml)

de: kml

de: Parkplatzbelegung Stadt Frauenfeld (ov2)

de: Parkplatzbelegung Stadt Frauenfeld (parquet)

de: parquet

de: Parkplatzbelegung Stadt Frauenfeld (rdfxml)

de: rdfxml

de: Parkplatzbelegung Stadt Frauenfeld (jsonld)

de: jsonld

de: Parkplatzbelegung Stadt Frauenfeld (turtle)

de: turtle

de: Parkplatzbelegung Stadt Frauenfeld (shp)

de: Parkplatzbelegung Stadt Frauenfeld (xls)


de: EnviDat

en: Habitat shift caused by human impact on vegetation structure poses a great threat to species which are special- ized on unique habitats. Single layered beech forests, the main foraging habitat of Greater Mouse-eared Bats (My- otis myotis), are threatened by recent changes in forest structure. After this species suffered considerable popula- tion losses until the 1970s, their roosts in buildings are strictly protected. However, some populations are still de- clining. Thus, the spatial identification of suitable foraging habitat would be essential to ensure conservation pol- icy. The aim of this study was (a) to verify the relevance of forest structural variables for the activity of M. myotis and (b) to evaluate the potential of LiDAR (Light Detection and Ranging) in predicting suitable foraging habitat of the species. We systematically sampled bat activity in forests close to 18 maternity roosts in Switzerland and applied a generalized linear mixed model (GLMM) to fit the activity data to forest structure variables recorded in the field and derived from LiDAR. We found that suitable forest foraging habitat is defined by single layered for- est, dense canopy, no shrub layer and a free flight space. Most importantly, this key foraging habitat can be well predicted by airborne LiDAR data. This allows for the first time to create nationwide prediction maps of potential foraging habitats of this species to inform conservation management. This method has a special significance for endangered species with large spatial use, whose key resources are hard to identify and widely distributed across the landscape.

en: LiDAR metrics predict suitable forest foraging areas of endangered Mouse-eared bats (Myotis myotis)

en: echolocation habitat-modelling chiroptera vegetation-structure forest-management

envidat

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

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

de: EnviDat: das Umwelt-Datenportal

envi

de: Umwelt

de:
Resource Title: Fielddata_2020-02-14_Guilds.csv
    Size: 241361 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/b64e697c-bef8-455f-a2ca-96e269fdfd1c/resource/8b121238-5319-4a48-ad15-a0382e8e37f8/download/fielddata_2020-02-14_guilds.csv
    Description: Complete set of field data and LiDAR data including bat activity measurements

de:
Resource Title: Variable description_20220411.csv
    Size: 3254 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/b64e697c-bef8-455f-a2ca-96e269fdfd1c/resource/121b2a4d-d2a0-416e-bd23-3a744cb57b1b/download/variable-description_20220411.csv
    Description: Description of all variables given in the file 'Felddaten_2020-02-14_Guilde.csv'

de:
Resource Title: R_Script_Publication_20220405.R
    Size: 27971 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/b64e697c-bef8-455f-a2ca-96e269fdfd1c/resource/50bc0f40-a3ab-49d6-82bb-35ffe03d387f/download/r_script_publication_20220405.r
    Description: R scripts for all analyses

chiroptera

display_name: chiroptera

echolocation

display_name: echolocation

forest-management

display_name: forest-management

habitat-modelling

display_name: habitat-modelling

vegetation-structure

display_name: vegetation-structure


en:
These data include all avalanches that were mapped in the region of Davos, Switzerland during the winters 1998-1999 to 2018-2019 (21 years), in total 13,918 avalanches, and the corresponding forecast danger level valid on the day of avalanche occurrence, 3533 days and danger ratings in total.
This avalanche activity data set was analysed and results published by Schweizer et al. (2020). They found that the
number of avalanches per day strongly increased with increasing danger level, but avalanche size was poorly related  to avalanche danger level.
The data are provided in two files: the first includes the avalanche data (13,918 records); the second includes the avalanche activity per day (3533 records).
Please refer to the Read-me file for further details on the data.
These data are the basis of the following publication:
Schweizer, J., Mitterer, C., Techel, F., Stoffel, A. and Reuter, B., 2020. On the relation between avalanche occurrence and avalanche danger level. The Cryosphere, 14, 737-750, https://doi.org/10.5194/tc-14-737-2020.

en: Snow avalanche data Davos, Switzerland, 1999-2019

en: avalanche-size snow-avalanche avalanche-forcasting danger-level avalanche-activity

envidat

en: EnviDat: the Environmental Data Portal

envi

en: Environment

de:
Resource Title: Snow avalanche data
    Size: 936455 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ce11efbe-4dac-4ff5-9a3d-f01e2c573292/resource/4c2b7c38-a874-45fc-9833-fdf83823067b/download/data_set_1_avalanche_observations_wi9899_to_wi1819_davos.csv
    Description: This data file includes data on the avalanches mapped in the region of Davos.

de:
Resource Title: Readme
    Size: 159745 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/ce11efbe-4dac-4ff5-9a3d-f01e2c573292/resource/f8d6835f-3ef6-4fe6-94a2-6b7f7b5827ce/download/read_me.pdf
    Description: The Readme file contains the description of the two data files.

de:
Resource Title: Avalanche activity data
    Size: 929518 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ce11efbe-4dac-4ff5-9a3d-f01e2c573292/resource/39e6dd9e-9b52-439e-a4d1-5e17a8e18eca/download/data_set_2_danger_avalanches.csv
    Description: This data file includes data on the avalanche activity per day aggregated from the avalanche data.

avalanche-activity

display_name: avalanche-activity

avalanche-forcasting

display_name: avalanche-forcasting

avalanche-size

display_name: avalanche-size

danger-level

display_name: danger-level

snow-avalanche

display_name: snow-avalanche


en:
Aerosol properties were measured between February 8 and March 31 2019  at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (- 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.
Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 &956;m) and GT-526S (0.3 – 5 &956;m), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM&8321;, PM&8322;,&8325; and PM&8321;&8320; (assumptions: particle density: 1.65 g cm&713;&179;, refractive index: 1.5+i0).
Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 &956;m and ~20 &956;m by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cm&713;&179;).
Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cm&713;&179;).
Coriolis &956; and LINDA: A microbial air sampler (Coriolis &956;, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 &956;m were drawn with an air flow rate of up to 300 l min&8254;&185; into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

en: Aerosol Data Weissfluhjoch

en: ice-nucleation inp linda particles aerosol raclets

de:
Resource Title: OPC-N3 Dataset Weissfluhjoch
    Size: 54387041 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/3932aae8-fa08-4dd7-bb1c-35cdfe3859bf/download/opc-n3_weissfluhjoch.csv
    Description: Particle concentrations in a size range of 0.35 μm to 40 μm were measured with an OPC-N3 (Alphasense, Inc.) in a resolution of 20 seconds (time in UTC). PM₁, PM₂,₅ and PM₁₀ were directly derived.

de:
Resource Title: APS Dataset Weissfluhjoch
    Size: 98624420 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/c7846a5d-4a0f-462b-bddc-594bfb6a578b/download/aps_weissfluhjoch.nc
    Description: The APS file contains aerosol data (total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) for aerodynamic diameters between 0.5 μm and ~20 μm as well as instrument characteristics, in a temporal resolution of 20 seconds, with time in UTC, measured at Weissfluhjoch.

de:
Resource Title: LINDA Dataset Weissfluhjoch
    Size: 191898 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/6451c23d-b1ec-4100-8f78-ba35611e540f/download/raclets_inp_wfj.nc
    Description: The LINDA file contains information on temperature (in °C) dependent frozen fractions, number of Ice Nuleating Particles (INP, per standard liter) and differential INP concentrations (per standard liter and Kelvin).

de:
Resource Title: SMPS Dataset Weissfluhjoch
    Size: 32316159 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/585a81d2-1d89-4453-b9b0-49176e48359d/download/smps_weissfluhjoch.nc
    Description: The SMPS file contains aerosol data (particle concentration, total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) in a size range between 12 and 460 nm (electrical mobility diameter) as well as instrument characteristics (sample temperature, pressure, relative humidity, mean free path and gas viscosity) in a temporal resolution of 2 minutes, with time in UTC, measured at Weissfluhjoch.

de:
Resource Title: OPC-GT526S Dataset Weissfluhjoch
    Size: 11552644 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/6e0ab260-4ec2-4b08-b485-63bbed6b4433/download/opc-gt526s_weissfluhjoch.csv
    Description: Particle counts were recorded in six size channels (0.3, 0.5, 0.8, 1.5, 2.5 and 5 μm) in a resolution of 20 seconds (time in UTC) by a particle counter (GT-526S, Met One Instruments, Inc.).

aerosol

display_name: aerosol

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

linda

display_name: linda

particles

display_name: particles

raclets

display_name: raclets


de:
Die hier veröffentlichten Datensätze für die Messstationen Weinfelden und Konstanz stammen aus dem automatischen Messnetz von Ostluft, das kontinuierlich verschiedene Luftschadstoffe (z.B. NO₂, PM₁₀, O₃) und teilweise meteorologische Parameter (z.B. Temperatur, Luftdruck, Wind) erfasst.
Jeder Datensatz enthält zeitlich aufgelöste Einzelmesswerte im Halbstunden-, Stun-den- oder Tagesintervall, je nach Version. Die Daten geben an: Start- und Endzeit der Messung, die bezeichnende Messstelle, den Messwert, sowie den zugehöri-gen Indikator (z.B. „Luftdruck“, „NO₂“) und eine eindeutige Stations-ID (Messstation-ID).
Die Daten werden direkt aus dem standardisierten Ostluft Messnetz übernommen. Die Qualitätssicherung erfolgt gemäß den Richtlinien der Schweizer Luftreinhaltever-ordnung (LRV). Es handelt sich bei den exportierten Daten um vorläufige Werte, die erst mit der Veröffentlichung des Jahresberichts definitiv bestätigt werden. In der Regel ist die vollständige Datenbereinigung Ende April des Folgejahres abgeschlossen.
Aus Speicherplatzgründen finden sich hier nur die Daten für die letzten 365 Tage. Vollständige Datensätze für ganze Jahre können über folgenden Link als gezippte CSV heruntergeladen werden:

[https://ogdtg.ch/ostluft/stundenwert_JAHR.csv.gz](https://ogdtg.ch/ostluft/stundenwert_JAHR.csv.gz)
Beispiel 2023: [https://ogdtg.ch/ostluft/stundenwert_2023.csv.gz](https://ogdtg.ch/ostluft/stundenwert_2023.csv.gz)
Alle verfügbaren Jahre: [https://ogdtg.ch/ostluft/stundenwert_full.csv.gz](https://ogdtg.ch/ostluft/stundenwert_full.csv.gz)

Gemäss Ostluft Messkonzept wird die Messstation beim Berufsbildungszentrum in Weinfelden alle zwei Jahre (gerade Jahre; Wechselstandort), die Messstation Konstanz Wallgutstrasse alljährlich betrieben.
Die Daten können außerdem über [ostluft.ch/messwerte/datenabfrage](https://www.ostluft.ch/messwerte/datenabfrage) individuell gefiltert und als CSV-Datei heruntergeladen werden.
Weitere Informationen zu den gemessenen Schadstoffen und Indikatoren finden Sie [hier](https://www.ostluft.ch/grundlagen).
Bei Fragen wenden Sie sich an die Ostluft Datenzentrale: [datenzentrale@ostluft.ch](mailto:datenezentrale@ostluft.ch)

de: luftschadstoff luft schadstoffbelastung schadstoff feinstaub luftdruck temperatur ostluft stickstoff ozon wind luftqualitat

kanton-thurgau

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

de: Kanton Thurgau

de: kanton-thurgau

de: Luftqualitätsmessungen Ostluft Thurgau – Stundenwerte (csv)

de: csv

de: Luftqualitätsmessungen Ostluft Thurgau – Stundenwerte (json)

de: json

de: Luftqualitätsmessungen Ostluft Thurgau – Stundenwerte (jsonl)

de: jsonl

de: Luftqualitätsmessungen Ostluft Thurgau – Stundenwerte (parquet)

de: parquet

de: Luftqualitätsmessungen Ostluft Thurgau – Stundenwerte (rdfxml)

de: rdfxml

de: Luftqualitätsmessungen Ostluft Thurgau – Stundenwerte (jsonld)

de: jsonld

de: Luftqualitätsmessungen Ostluft Thurgau – Stundenwerte (turtle)

de: turtle

de: Luftqualitätsmessungen Ostluft Thurgau – Stundenwerte (n3)

de: Luftqualitätsmessungen Ostluft Thurgau – Stundenwerte (xls)

de: xls

feinstaub

display_name: feinstaub

luft

display_name: luft

luftdruck

display_name: luftdruck

luftqualitat

display_name: luftqualitat

luftschadstoff

display_name: luftschadstoff

ostluft

display_name: ostluft

ozon

display_name: ozon

schadstoff

display_name: schadstoff

schadstoffbelastung

display_name: schadstoffbelastung

stickstoff

display_name: stickstoff

temperatur

display_name: temperatur

wind

display_name: wind