de: Datenstruktur auf Deutsch

de: Datenwürfel auf Deutsch

de: Kurzarbeitsentschädigung nach Jahr, Grund der Entschädigung und Betrag

en: Short-time compensation by Year, Reason of compensation and Amount

arbeitslosigkeit

display_name: arbeitslosigkeit

unemployment

display_name: unemployment

de: Kurzarbeitsentschädigung nach Grund der Entschädigung seit 2005

en: Short-time compensation by reason of compensation since 2005


state: active

type: dataset

en: Data structure in German

media_type: application/json

format: JSON

de: Datenwürfel auf Englisch

en: Data cube in English

media_type: text/html

format: HTML

de: Datenstruktur auf Englisch

en: Data structure in English

en: Data cube in German

de: Erstzugelassene leichte Nutzfahrzeuge bis 3.5 t nach Jahr, Importart, Fahrzeuggruppe und Kennzahlen

en: Utility vehicles up to 3.5 t registered for the first time by Year, Kind of import, Utility vehicles up to 3.5 t and Key figures

fahrzeug-erstzulassungen

display_name: fahrzeug-erstzulassungen

mobility-and-transport

display_name: mobility-and-transport

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

political_level: other

liechtenstein

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: DCAT Harvester Amt für Statistik FL

de: Erstzugelassene leichte Nutzfahrzeuge bis 3.5 t nach Importart und Fahrzeuggruppe sowie mittlere CO2-Emission

en: Utility vehicles up to 3.5 t registered for the first time by kind of import and vehicle group as well as average CO2 emission


de: Baukosten bei Bewilligungsquartal, Art der Bauwerke und Art der Arbeiten

en: 381.501 Construction costs by Year of approval, Type of buildings and Type of work

bautatigkeit

display_name: bautatigkeit

construction-activity

display_name: construction-activity

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

de: Baukosten nach Art der Bauwerke und Art der Arbeiten seit 2015

en: 381.501 Construction costs by type of buildings and type of work since 2015


de: Personenwagenbestand nach Stichtag, Leergewichtsklasse, Leistungsklasse und Altersklasse (Jahre)

en: Licensed passenger cars by Reference date, Unladen weight class, Engine power class and Age category (years)

fahrzeugbestand

display_name: fahrzeugbestand

licensed-vehicles

display_name: licensed-vehicles

de: Personenwagenbestand nach Leergewichtsklasse, Leistungsklasse und Altersklasse seit 2013

en: Licensed passenger cars by unladen weight class, engine power class and age category since 2013


de: Schulpersonal in Liechenstein nach Jahr, Universität, Personalkategorie und Geschlecht

en: School staff in Liechtenstein by Academic year, University, Category of staff and Sex

hochschulen

display_name: hochschulen

tertiary-education

display_name: tertiary-education

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

de: Schulpersonal in Liechtenstein nach Jahr, Universität, Personalkategorie und Geschlecht seit 2010/11

en: School staff in Liechtenstein by Academic year, University, Category of staff, and Sex since 2010/2011


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Datenwürfel auf Deutsch

de: Produktionskonto zu laufenden Preisen 2013 - 2016 bei Jahr, Transaktion und Wirtschaftsbereich

en: Production account at current prices 2013 - 2016 by Year, Transaction and Economic activity

national-accounts

display_name: national-accounts

volkswirtschaftliche-gesamtrechnungen

display_name: volkswirtschaftliche-gesamtrechnungen

de: Produktionskonto zu laufenden Preisen 2013 - 2016 nach Wirtschaftsbereich

en: Production account at current prices 2013 - 2016 by economic activity


de: Datenwürfel auf Englisch

en: Data cube in English

en: Data cube in German

de: Datenstruktur auf Englisch

en: Data structure in English

de: Wertstoffe bei Jahr und Wertstoffkategorie

en: Recyclable materials by Year and Recyclable material category

abfall

display_name: abfall

waste

display_name: waste

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

de: Wertstoffe nach Wertstoffkategorie seit 1985

en: Recyclable materials by recyclable material category since 1985


de: Erleichterte Einbürgerung infolge längerfristigem Wohnsitz nach Jahr, Geschlecht und Altersklasse nach Jahr, Geschlecht und Altersklasse

en: Facilitated naturalisation due to long-term residence by Year, Sex and Age group by Year, Sex and Age group

einburgerungen

display_name: einburgerungen

naturalisations

display_name: naturalisations

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

intr

fr: Questions internationales

de: Internationale Themen

en: International issues

it: Tematiche internazionali

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Erleichterte Einbürgerung infolge längerfristigem Wohnsitz nach Geschlecht und Altersklassen seit 2000

en: Facilitated naturalisation due to long-term residence by sex and age group since 2000


de: Einwohner und Erwerbstätige im Jahresmittel seit 2013 bei Jahr und Einwohner und Erwerbstätige

en: Average population and employed persons since 2013 by Year and Population and employed persons

econ

de: Wirtschaft und Finanzen

en: Economy and finance


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Bevölkerung nach Szenario, Heimat, Geschlecht, Fünfjahresklasse und Jahr

en: Population by Scenario, Citizenship, Sex, five-year age group and Year

bevolkerungsszenarien

display_name: bevolkerungsszenarien

population-scenarios

display_name: population-scenarios

de: Bevölkerung nach Szenario, Heimat, Geschlecht und Fünfjahresklasse von 2023 bis 2060

en: Population by Scenario, Citizenship, Sex and five-year age group from 2023 to 2060


de: Datenwürfel auf Deutsch

en: Data cube in English

de: Eheschliessungen bei Jahr, Staatsbürgerschaft Frau und Staatsbürgerschaft Mann

en: Marriages by Year, Females' citizenship and Males' citizenship

ehen-partnerschaften

display_name: ehen-partnerschaften

marriages-partnerships

display_name: marriages-partnerships

de: Eheschliessungen nach Staatsbürgerschaft seit 1999

en: Marriages by citizenship since 1999


de: Datenstruktur auf Englisch

en: Data structure in English

de: Datenwürfel auf Englisch

en: Data cube in German

de: Bauprojekte bei Bewilligungsquartal, Art der Arbeiten, Art der Bauwerke und Gemeinde

en: Construction projects by Year of approval, Type of work, Type of buildings and Municipality

de: Bauprojekte nach Art der Arbeiten, Art der Bauwerke und Gemeinde seit 2015

en: Construction projects by type of work, type of buildings and municipality since 2015


de: Monatlicher Bruttolohn nach Jahr, Vollzeit/Teilzeit, Aufenthaltsstatus, Geschlecht und Kennzahl

en: Gross monthly wage by Year, Full-time/Part-time, Residence permit category, Sex and Key figure

lohne

display_name: lohne

wages

display_name: wages

de: Monatlicher Bruttolohn nach Voll-/Teilzeit, Aufenthaltsstatus und Geschlecht

en: Gross monthly wage by full-/part-time, residence permit category and sex


de: Erstzugelassene Personenwagen nach Jahr, Leergewichtsklasse, Gesamtgewichtsklasse und CO2-Emissionsklasse NEFZ (bis 2021) /  WLTP (ab 2021)

en: Passenger cars registered for the first time by Year, Unladen weight class, Maximum gross weight class and CO2 emission class

fahrzeug-erstzulassungen

display_name: fahrzeug-erstzulassungen

mobility-and-transport

display_name: mobility-and-transport

tran

de: Verkehr

en: Transport

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Erstzugelassene Personenwagen nach Leergewichtsklasse, Gesamtgewichtsklasse, CO2-Emissionsklasse sowie mittlere CO2-Emission

en: Passenger cars registered for the first time by unladen weight class, maximum gross weight class, CO2 emission class as well as average CO2 emission


de: Erstzugelassene Anhänger nach Jahr, Fahrzeugart, Gesamtgewichtsklasse, Anzahl Achsen und Nutzlastklasse

en: Trailers registered for the first time by Year, Type of vehicle, Maximum gross weight class, Number of axles and Load weight class

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Erstzugelassene Anhänger nach Fahrzeugart, Gesamtgewichtsklasse, Anzahl Achsen und Nutzlastklasse

en: Trailers registered for the first time by maximum gross weight class, number of axles and load weight class


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Ständige Bevölkerung ab 15 Jahren nach Stichtag, Anzahl Kinder, Heimat, Geschlecht und Gemeinde

en: Permanent resident population aged 15 years and over by Reference date, Number of children, Citizenship, Sex and Municipality

bevolkerungsstruktur

display_name: bevolkerungsstruktur

population-structure

display_name: population-structure

soci

de: Bevölkerung und Gesellschaft

en: Population and society

de: Ständige Bevölkerung ab 15 Jahren nach Anzahl Kindern, Heimat, Geschlecht und Gemeinde

en: Permanent resident population aged 15 years and over by number of children, citizenship, sex and municipality


de: Datenstruktur auf Englisch

en: Data structure in English

en: Data cube in English

de: Datenwürfel auf Deutsch

de: Indikatoren der Fruchtbarkeit bei Jahr und Kennzahl

en: Fertility Indicators by Year and Key figure

births-deaths

display_name: births-deaths

geburten-todesfalle

display_name: geburten-todesfalle

de: Indikatoren der Fruchtbarkeit seit 1999

en: Fertility Indicators since 1999


de: Datenwürfel auf Englisch

en: Data cube in German

de: Bevölkerungsbewegung nach Jahr, Wohnsitz und Kennzahl bei Jahr, Wohnsitz und Kennzahl

en: Population change by Year, Place of residence and Key figure by Year, Place of residence and Key figure by Year, Place of residence and Key figure

bevolkerungsbewegung

display_name: bevolkerungsbewegung

population-change

display_name: population-change

de: Bevölkerungsbewegung der ständigen Bevölkerung nach Wohnsitz seit 2011

en: Population change of the permanent population by place of residence since 2011


de: Ergebnisse der Vorsteherwahlen nach Jahr, Partei und Gemeinde

en: Results of mayorial elections by Year, Political party and Municpality

elections-referendums

display_name: elections-referendums

wahlen-abstimmungen

display_name: wahlen-abstimmungen

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

de: Ergebnisse der Vorsteherwahlen nach Gemeinde und Partei seit 1975

en: Results of mayoral elections by municipality and political party since 1975


de: Personenwagenbestand nach Stichtag, CO2-Emissionsklasse, mittlere CO2-Emission und Altersklasse (Jahre)

en: Licensed passenger cars by Reference date, CO2 emission class, average CO2 emission and Age category (years)

fahrzeugbestand

display_name: fahrzeugbestand

licensed-vehicles

display_name: licensed-vehicles

tran

de: Verkehr

en: Transport

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Personenwagenbestand nach CO2-Emissionsklasse (NEFZ), mittlere CO2-Emission und Altersklasse Jahr von 2013 bis 2022

en: Licensed passenger cars by CO2 emission class (NEFZ), average CO2 emission and age category year 2013 until 2022


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Arealstatistik bei Jahr und Bodenbedeckung

en: Land use statistics by Year and Land cover

raum-flachennutzung

display_name: raum-flachennutzung

territory-land-use

display_name: territory-land-use

envi

de: Umwelt

en: Environment

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Arealstatistik nach Bodenbedeckung seit 1984

en: Land use statistics by land cover since 1984


de: Datenstruktur auf Englisch

en: Data structure in English

de: Datenwürfel auf Deutsch

en: Data cube in English

de: Durchschnittlicher Bruttomietpreis nach Stichtag, Zimmerzahl der Wohnungen und Gemeinde

en: Average gross rent by Reference date, Number of rooms and Municipality

mietpreise

display_name: mietpreise

rental-prices

display_name: rental-prices

econ

de: Wirtschaft und Finanzen

en: Economy and finance

de: Durchschnittlicher Bruttomietpreis nach Zimmerzahl der Wohnungen und Gemeinde

en: Average gross rent by number of rooms and municipality


en: Data cube in German

de: Nutztierbestand nach Jahr, Tierkategorie und Zone | Region

landwirtschaft

display_name: landwirtschaft

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

de: Nutztierbestand nach Tierkategorie (detailliert), Zone und Region seit 2005


de: Datenwürfel auf Englisch

de: Wahlbeteiligung bei Landtagswahlen nach Jahr, Wahlkreis, Kennzahl und Gruppe

en: Voter turnout in parliamentary elections by Year, Constituency, Key figure and Group

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

de: Wahlbeteiligung bei Landtagswahlen nach Wahlkreis, Gruppe und Kennzahl seit 2019

en: Voter turnout in parliamentary elections by constituency, group and key figure since 2019


de: Datenstruktur auf Deutsch

de: Asylgesuche und Schutzsuchende nach Jahr, Staatsbürgerschaft, Geschlecht und Monat bei Jahr, Staatsbürgerschaft, Geschlecht, Bewilligungstyp und Monat

en: Asylum applications and Protection applications by Year, Citizenship, Sex and Month by Year, Citizenship, Sex, Type of authorization and Month

asylum

display_name: asylum

asylwesen

display_name: asylwesen

soci

de: Bevölkerung und Gesellschaft

en: Population and society

intr

de: Internationale Themen

en: International issues

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Asylgesuche und Schutzsuchende nach Staatsbürgerschaft, Geschlecht und Monat seit 2011

en: Asylum applications and Protection applications by citizenship, sex and month since 2011


de: Datenwürfel auf Deutsch

de: Datenstruktur auf Englisch

en: Data structure in German

de: Heiratende Personen bei Jahr, Geschlecht, Staatsbürgerschaft und Staatsbürgerschaft des Partners

en: Marrying persons by sex, citizenship and partner's citizenship by Year, Sex, Citizenship and Partner's citizenship

ehen-partnerschaften

display_name: ehen-partnerschaften

marriages-partnerships

display_name: marriages-partnerships

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Heiratende Personen nach Geschlecht, Staatsbürgerschaft und Staatsbürgerschaft des Partners seit 1999

en: Marrying persons by sex, age group, citizenship and partners citizenship since 1999


en: Data cube in English

en: Data structure in English

de: Erwerbstätige ständige Bevölkerung nach Jahr, Wirtschaftszweig, Geschlecht, Arbeitsland und Heimat

en: Permanent resident population in gainful employment by Year, Economic activity, Sex, Country of work and Citizenship

erwerbstatigkeit

display_name: erwerbstatigkeit

population-in-gainful-employment

display_name: population-in-gainful-employment

econ

de: Wirtschaft und Finanzen

de: Erwerbstätige ständige Bevölkerung nach Wirtschaftszweig, Geschlecht, Arbeitsland und Heimat seit 2006

en: Permanent resident population in gainful employment by economic activity, sex, country of work and citizenship since 2006


en: Data cube in German

de: Datenwürfel auf Englisch

de: Erleichterte Einbürgerung infolge längerfristigem Wohnsitz nach Jahr, Vormalige Staatsbürgerschaft und Geschlecht nach Jahr, Vormalige Staatsbürgerschaft und Geschlecht

en: Facilitated naturalisation following long-term residence by Year, Former citizenship and Sex by Year, Former citizenship and Sex

einburgerungen

display_name: einburgerungen

naturalisations

display_name: naturalisations

de: Erleichterte Einbürgerung infolge längerfristigem Wohnsitz nach vormaliger Staatsbürgerschaft und Geschlecht seit 2000

en: Facilitated naturalisation due to long-term residence by former citizenship and sex since 2000


de: Datenstruktur auf Deutsch

de: Migration nach Jahr, Richtung, Heimat, Herkunfts- bzw. Zielland, Geschlecht und Wohngemeinde bei Jahr, Richtung, Heimat, Herkunfts- bzw, Geschlecht und Wohngemeinde

en: Migration by Year, Direction, Citizenship, Country of origin / Country of destination, Sex and Municipality of residence by Year, Direction, Citizenship, Country of origin / Country of destination, Sex and Municipality of residence

migration-binnenwanderung

display_name: migration-binnenwanderung

migration-internal-migration

display_name: migration-internal-migration

de: Migration nach Richtung, Herkunfts- bzw. Zielland, Geschlecht, Wohngemeinde und Heimat seit 2011

en: Migration by direction, country of origin/country of destination, sex, municipality of residence and citizenship since 2011


de: Privathaushalte mit Personen ab 65 Jahren nach Stichtag, Haushaltstyp und Gemeinde

en: Private households with people aged 65 years and over by Reference date, Type of household and Municipality

haushalte-familien

display_name: haushalte-familien

households-families

display_name: households-families

soci

de: Bevölkerung und Gesellschaft

en: Population and society

de: Privathaushalte mit Personen ab 65 Jahren nach Haushaltstyp und Gemeinde

en: Private households with people aged 65 years and over by type of household and municipality


de: Datenwürfel auf Deutsch

de: Konsolidiert - Konsolidierte verwaltete Vermögen und Neugeldzufluss nach Jahr und Verwaltete Vermögen / Neugeldzufluss

en: Consolidated - Consolidated assets under management and new money inflow by Year and Assets under management / new money inflow

banken

display_name: banken

banking-institutions

display_name: banking-institutions

econ

en: Economy and finance

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Konsolidiert - Konsolidierte verwaltete Vermögen und Neugeldzufluss seit 2017

en: Consolidated - Consolidated assets under management and new money inflow since 2017


en: Data structure in German

de: Datenstruktur auf Englisch

de: Motorräderbestand nach Stichtag, Fahrzeugart, Karosserie, Marke, Hubraumklasse und Altersklasse (Jahre)

en: Licensed motorcycles by Reference date, Type of vehicle, Type of body, Make, Engine capacity class and Age category (years)

fahrzeugbestand

display_name: fahrzeugbestand

licensed-vehicles

display_name: licensed-vehicles

tran

de: Verkehr

en: Transport

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Motorräderbestand nach Fahrzeugart, Karosserie, Marke, Hubraumklasse und Altersklasse seit 2015

en: Licensed motorcycles by type of vehicle, body, make, engine capacity class and age category since 2015


en: Data structure in English

en: Data cube in German

de: Datenwürfel auf Englisch

en: Data cube in English

de: Einzelbasis - Verbindlichkeiten gegenüber Kunden nach Jahr, Anzahl Konti / Einlage, Verbindlichkeiten gegenüber Kunden, Einlageklasse und Domizil

en: Individual basis - Liabilities to clients by Year, Number of accounts / deposit, Liabilities to clients, Deposit class and Domicile

econ

de: Wirtschaft und Finanzen

de: Einzelbasis - Verbindlichkeiten gegenüber Kunden nach Anzahl Konti, Einlage, Einlageklasse und Domizil seit 2017

en: Individual basis - Liabilities to clients by number of accounts, deposit, deposit class and domicile since 2017


de: Datenstruktur auf Deutsch

de: Ständige Bevölkerung ab 15 Jahren nach Stichtag, Anzahl Kinder, Heimat, Geschlecht und Fünfjahresklassen

en: Permanent resident population aged 15 years and over by Reference date, Number of children, Citizenship, Sex and Age group

bevolkerungsstruktur

display_name: bevolkerungsstruktur

population-structure

display_name: population-structure

de: Ständige Bevölkerung ab 15 Jahren nach Anzahl Kindern, Heimat, Geschlecht und Fünfjahresklassen

en: Permanent resident population aged 15 years and over by number of children, citizenship, sex and age group


de: Erstzugelassene Personentransportfahrzeuge nach Jahr, Karosserie, Fahrzeugart nach EU und Anzahl Sitzplätze

en: Passenger vehicles registered for the first time by Year, Type of body, Type of vehicle as per EU and Number of seats

fahrzeug-erstzulassungen

display_name: fahrzeug-erstzulassungen

mobility-and-transport

display_name: mobility-and-transport

de: Erstzugelassene Personentransportfahrzeuge nach Karosserie, Fahrzeugart nach EU und Anzahl Sitzplätze

en: Passenger vehicles registered for the first time by type of body, type of vehicle as per EU and number of seats


de: Datenwürfel auf Deutsch

de: Familienhaushalte mit ledigen Kindern unter 25 Jahren nach Stichtag, Familientyp, Anzahl Kinder, Haushaltsgrösse und Gemeinde

en: Family households with unmarried child(ren) younger than 25 years by Reference date, Type of family, Number of children, Size of household and Municipality

soci

de: Bevölkerung und Gesellschaft

en: Population and society

de: Familienhaushalte mit ledigen Kindern unter 25 Jahren nach Familientyp, Anzahl Kinder, Haushaltsgrösse und Gemeinde

en: Family households with unmarried child(ren) younger than 25 years by type of family, number of children, size of household and municipality


en: Data structure in German

de: Datenstruktur auf Englisch

de: Einzelbasis - Forderungen gegenüber Kunden und Hypothekarforderungen nach Jahr, Bilanzposition und Deckungsart

en: Individual basis - Claims against clients and mortgage loans by Year, Balance sheet item and Type of collateral

econ

en: Economy and finance

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Einzelbasis - Forderungen gegenüber Kunden und Hypothekarforderungen nach Deckungsart seit 2017

en: Individual basis - Claims against clients and mortgage loans by type of collateral since 2017


de: Datenwürfel auf Englisch

en: Data structure in English

de: Kontensystem der gesamten Volkswirtschaft zu laufenden Preisen 1998 - 2013 by Jahr and Konto / Transaktion

en: Sequence of national accounts at current prices 1998 - 2013 by Year and Account / transaction

national-accounts

display_name: national-accounts

volkswirtschaftliche-gesamtrechnungen

display_name: volkswirtschaftliche-gesamtrechnungen

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.


en: Data cube in German

de: Lernende in Liechtenstein an Berufsmaturitätsschulen nach Jahr, Bildungsfeld, Geschlecht und Wohnland

duale-ausbildung

display_name: duale-ausbildung

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

de: Lernende in Liechtenstein an Berufsmaturitätsschulen nach Bildungsfeld, Wohnland und Geschlecht seit 2014/2015


de: Datenstruktur auf Deutsch

en: Data cube in English

de: Erstzugelassene Fahrzeuge nach Jahr, Fahrzeuggruppe und Emissionscode gemäss EU

en: Vehicles registered for the first time by Year, Vehicle group and Emission code as per EU definition

tran

de: Verkehr

en: Transport

de: Erstzugelassene Fahrzeuge nach Fahrzeuggruppe und Emissionscode gemäss EU

en: Vehicles registered for the first time by vehicle group and emission code as per EU definition


de: Datenwürfel auf Deutsch

de: Wohnungen nach Stichtag, Bewohnertyp, Zimmerzahl, Wohnungsfläche und Gemeinde

en: Dwellings by Reference date, Type of occupant, Number of rooms, Useful floor space and Municipality

buildings-dwellings

display_name: buildings-dwellings

gebaude-wohnungen

display_name: gebaude-wohnungen

de: Wohnungen nach Bewohnertyp, Zimmerzahl, Wohnungsfläche und Gemeinde

en: Dwellings by type of occupant, number of rooms, useful floor space and municipality


de: Datenstruktur auf Englisch

de: Einzelbasis - Verbindlichkeiten gegenüber Kunden nach Jahr, Anzahl Konti / Einlagen, Verbindlichkeiten gegenüber Kunden und Domizil / Sektor

en: Individual basis - Liabilities to clients by Year, Number of accounts / deposits, Liabilities to clients and Domicile / Sector

econ

de: Wirtschaft und Finanzen

de: Einzelbasis - Verbindlichkeiten gegenüber Kunden nach Anzahl Konti, Einlagen, Domizil und Sektor seit 2017

en: Individual basis - Liabilities to clients by number of accounts, deposits, domicile and sector since 2017


en: Data structure in German

de: Datenwürfel auf Englisch

de: Bodenversiegelung bei Jahr und Kategorie

en: Soil sealing by Year and Category

landscape-forest-soil-biodiversity

display_name: landscape-forest-soil-biodiversity

landschaft-wald-boden-biodiversitat

display_name: landschaft-wald-boden-biodiversitat

envi

de: Umwelt

en: Environment

amt-fuer-statistik-fl

de: Amt für Statistik

de: Bodenversiegelung nach Kategorie seit 1984

en: Soil sealing by category since 1984


en: Data structure in English

de: Privathaushalte, Erwerb und Steuern bei Jahr, Haushaltsgrösse, Kennzahl und Steuerklasse

en: Private households, earnings and taxes by Year, Household size, Key figure and Tax group

vermogens--und-einkommensverteilung

display_name: vermogens--und-einkommensverteilung

wealth-and-income-distribution

display_name: wealth-and-income-distribution

soci

de: Bevölkerung und Gesellschaft

en: Population and society

en: Office of Statistics

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Privathaushalte, Erwerb und Steuern nach Steuerbetrag und Altersgruppe seit 2020

en: Private households, earnings and taxes by tax group and age group since 2020


de: Datenstruktur auf Deutsch

en: Data cube in English

en: Data cube in German

de: Produktionskonto zu laufenden Preisen seit 2016 bei Jahr, Wirtschaftszweig (NOGA-Abschnitt) und Transaktion

en: Production account at current prices since 2016 by Year, Economic activity (NOGA Section) and Transaction

econ

en: Economy and finance

amt-fuer-statistik-fl

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Produktionskonto zu laufenden Preisen seit 2016 nach Wirtschaftszweig (Abschnitt)

en: Production account at current prices since 2016 by economic activity (Section)


de: Datenwürfel auf Deutsch

de: Wohnungen nach Jahr, Bauperiode, Nutzungsart und Zimmerzahl

en: Dwellings by Year, Period of construction, Purpose of use and Number of rooms

de: Wohnungen nach Bauperiode, Nutzungsart und Zimmerzahl seit 2015

en: Dwellings by period of construction, purpose of use and number of rooms since 2015


de: Datenstruktur auf Englisch

en: Data structure in German

de: Erwerbstätige Bevölkerung nach Stichtag, Hauptverkehrsmittel, Arbeitsgemeinde und Wohngemeinde

en: Population in gainful employment by Reference date, Main mean of transport, Place of work and Municipality of residence

passenger-transport

display_name: passenger-transport

personenverkehr

display_name: personenverkehr

tran

de: Verkehr

en: Transport

de: Erwerbstätige Bevölkerung nach Hauptverkehrsmittel für den Arbeitsweg, Arbeitsgemeinde und Wohngemeinde

en: Population in gainful employment by main mean of transport, place of work and municipality of residence


en: Data structure in English

de: Datenwürfel auf Englisch

de: Arbeitsplätze nach Jahr, Voll-/ Teilzeit, Wohnsitz, Arbeitsgemeinde und Geschlecht

en: Jobs by Year, Part-/ full-time, Place of residence, Municipality of work and Sex

enterprises-jobs

display_name: enterprises-jobs

unternehmen-arbeitsplatze

display_name: unternehmen-arbeitsplatze

econ

de: Wirtschaft und Finanzen

de: Arbeitsplätze nach Voll-/ Teilzeit, Wohnsitz, Arbeitsgemeinde und Geschlecht seit 2008

en: Jobs by part-/ full-time, place of residence, municipality of work and sex since 2008


de: Einkommensverteilungskonto zu laufenden Preisen seit 2013 bei Jahr, Transaktion und Institutioneller Sektor

en: Allocation of primary income account at current prices since 2013 by Year, Transaction and Institutional sector

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Einkommensverteilungskonto zu laufenden Preisen seit 2013 nach Sektor

en: Allocation of primary income account at current prices since 2013 by institutional sector


de: Datenstruktur auf Deutsch

en: Data cube in German

en: Data cube in English

de: Steuerpflichtige Personen, Erwerb und Steuern bei Jahr, Altersklasse, Kennzahl und Steuerklasse

en: Taxable persons by Year, Age group, Key figure and Tax category

soci

de: Bevölkerung und Gesellschaft

en: Population and society

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Steuerpflichtige Personen, Erwerb und Steuern nach Steuerbetrag und Altersgruppe seit 2020

en: Taxable persons, earnings and taxes by Tax category and age group since 2020


de: Datenwürfel auf Deutsch

de: Nutztierhalter und Nutztierbestand nach Jahr, Kennzahl, Tierkategorie und Zone | Region

landwirtschaft

display_name: landwirtschaft

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

econ

en: Economy and finance

amt-fuer-statistik-fl

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Nutztierhalter und Nutztierbestände nach Tierkategorie, Zone und Region seit 2005


de: Datenstruktur auf Englisch

en: Data structure in German

de: Erstzugelassene Personenwagen nach Jahr, Marke, Hubraumklasse und Leistungsklasse

en: Passenger cars registered for the first time by Year, Make, Engine capacity class and Engine power class

tran

de: Verkehr

de: Erstzugelassene Personenwagen nach Marke, Hubraumklasse und Leistungsklasse

en: Passenger cars registered for the first time by make, engine capacity class and engine power class


de: Motorräderbestand nach Stichtag, Hubraumklasse und Gemeinde

fahrzeugbestand

display_name: fahrzeugbestand

licensed-vehicles

display_name: licensed-vehicles

en: Transport

de: Motorräderbestand nach Hubraumklasse und Gemeinde seit 2013


de: Datenwürfel auf Englisch

en: Data structure in English

de: Luftschadstoffemissionen bei Jahr und Schadstoff

en: Air pollutant emissions by Year and Air pollutant

air-climate

display_name: air-climate

luft-klima

display_name: luft-klima

envi

de: Umwelt

en: Environment

amt-fuer-statistik-fl

de: Amt für Statistik

de: Luftschadstoffemissionen nach Schadstoff seit 1985

en: Air pollutant emissions by air pollutant since 1985


de: Datenstruktur auf Deutsch

de: Baukosten (in Mio. CHF) nach Bewilligungsjahr, Kategorie der Bauwerke und Gebiet

en: Construction costs (in million CHF) by Year of approval, Building categories and Region

bautatigkeit

display_name: bautatigkeit

construction-activity

display_name: construction-activity

econ

de: Wirtschaft und Finanzen

en: Office of Statistics

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Baukosten nach Kategorie der Bauwerke seit 2010

en: Construction costs (in million CHF) by building categories and region since 2010


en: Data cube in English

de: Datenwürfel auf Deutsch

en: Data cube in German

de: Einzelbasis - Zinskonditionen (Jahresdurchschnitt) nach Jahr und Kredit / Anlage

en: Individual basis - Interest rate conditions (annual average) by Year and Loan / Investment

banking-interests

display_name: banking-interests

bankzinsen

display_name: bankzinsen

de: Einzelbasis - Zinskonditionen (Jahresdurchschnitt) für die Aufnahme von Krediten und die Anlage von Geldern in CHF in Liechtenstein seit 1980

en: Individual basis - Interest rate conditions (annual average) for borrowing and investing funds in CHF in Liechtenstein since 1980


de: Datenstruktur auf Englisch

de: Erleichterte Einbürgerung infolge längerfristigem Wohnsitz nach Jahr, Heimatgemeinde und Geschlecht nach Jahr, Heimatgemeinde und Geschlecht

en: Facilitated naturalisation due to long-term residence by Year, Home municipality and Sex by Year, Home municipality and Sex

einburgerungen

display_name: einburgerungen

naturalisations

display_name: naturalisations

soci

de: Bevölkerung und Gesellschaft

en: Population and society

intr

de: Internationale Themen

en: International issues

de: Erleichterte Einbürgerung infolge längerfristigem Wohnsitz nach Heimatgemeinde und Geschlecht seit 2000

en: Facilitated naturalisation due to long-term residence by home municipality and sex since 2000


maintainer: EnviDat Support

en: wetlands environmental--policy switzerland ecology environmental---history historical-carthography

en: Wetlands 1850 - 2010 (shapefiles)

media_type: application/zip

en:
 History of wetlands - GIS-Layers
 Location of wetlands based on signatures in topographic maps
* Basis 1850: original measuring table sheets Dufour created between the years 1834 and 1863.
* Basis 1900/ Basis 1950: The Siegfried maps were updated and published at regular intervals between 1870 and 1949. This long period of time made it possible to reconstruct wetlands for two periods based on the Siegfried Maps: the first edition (hereinafter referred to as "1900") and the last edition ("1950").
* Basis 2010: Map sheets from the National Map from 2006 to 2011 were used for the most recent time period of the reconstruction.
 Location of wetlands due to reconstructions
The reconstruction **must not** be interpreted in the sense of a surface-accurate separation, but shows without claim to location accuracy the approximate extent of the areas that would have corresponded to the mapping criteria for wetlands used in today's topographic maps around 1850, 1900 and 1950. The basics can be found in Stuber & Bürgi 2019, chapter 5.4.

format: ZIP

mimetype: application/zip

en:
Naturally, large parts of the Swiss Plateau are characterised by wetlands
and meandering rivers. That this is no longer the case today is the result
of centuries of efforts to obtain dry land. But how did this process take
place? What were the relevant actors and what were their motivations? And
what can be said about the ecological consequences of this development?

In a research project on the history of wetlands in Switzerland since 1700,
we conducted (a) a historical analysis of the development of land use in
wetlands and the actors involved, (b) a historical-cartographic
reconstruction of wetland extent since 1850 and (c) an evaluation of
ecological effects of changes in wetlands on various organisms groups.

The series of GIS layers on wetland history stem from the second part of
the project. The area reconstruction is based on digitized and homogenized
signatures from national map series, as they have been available since
about 1850. Details about the digitalization process and the homogenization
procedures applied ("Rekonstruktionen") are included in Stuber & Bürgi
2019.

Book Citation:
 > Stuber M, Bürgi M (2019) Vom «eroberten Land» zum Renaturierungsprojekt. Geschichte der Feuchtgebiete in der Schweiz seit 1700. "Bristol Schriftenreihe", Band 59. Haupt Verlag, Bern, Stuttgart, Wien. 262 Seiten.

ecology

display_name: ecology

environmental---history

display_name: environmental---history

environmental--policy

display_name: environmental--policy

historical-carthography

display_name: historical-carthography

switzerland

display_name: switzerland

wetlands

display_name: wetlands

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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.

value: Envidat Harvester

en: History of wetlands in Switzerland since 1850


dischmex-meteorological-measurements

maintainer: Rebecca Mott

title_for_slug: dischmex-meteorological-measurements

en: meteorological-measurements dischmex meteorological-data dischma meteo-station

en: Meteorological measurements 2014

media_type: application/pdf

en: Location of the meteorological stations

format: PDF

mimetype: application/pdf

en: Overview sensors

format: XLS

en: Meteorological measurement 2015

en: Meteorological measurements 2016

en: data

en: Meteorological measurement 2014

en:
Meteorological measurements recorded in the Dischma valley from 2014-2016. In 2014 and 2015 we used 11 mobile weather stations from sensorscope to record meteorological parameter in the upper Dischma valley in the closer surroundings of the Gletschboden area. The meteorological stations are eqiupped with at least air temperature/humidity, wind velocity and wind direction sensors. Some stations are additionally equipped with precipitation, shortwave radiation and snow surface temperature sensors.
Three transects were installed at different aspects and were equipped with air temperature/humidity and wind sensors. Transect 1 (stations 2-4) provides meteorological Information on an east-north-east facing slope at elevations ranging between 2100 m and 2500 m. Transect 2 (stations 5-7) provides meteorological Information on a south-west slope and transect 3 (stations 8-10) on a north-west slope. Station 1 is fully equipped with meteorological sensors (temperature/humidity, wind, IR, up and downwand shortwave radiation and precipitation).
In 2016, mobile stations from sensorscope were replaced with six permanent meteorological stations. Meteorological stations 1-3 are equipped with an air temperature/humidity sensor, two wind speed sensors, a wind direction sensor and an incoming and outgoing shortwave radiation sensor. Stations 4 and 6 are equipped with an air temperature/humidity sensor and a wind speed/direction sensor. Station 5 is a equipped with an air temperature/humidity sensor, a wind speed/direction sensor, a snow surface temperature sensor, an incoming and outgoing shortwave radiation sensor and an incoming longwave radiation sensor.

dischma

display_name: dischma

dischmex

display_name: dischmex

meteo-station

display_name: meteo-station

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

en: DISCHMEX - Meteorological measurements


en: isotopes scots-pine dendrochronology tree-ring-cellulose tree-rings pfynwald pinus-sylvestris

media_type: text/csv

format: CSV

en: Read me file.docx

format: SERVICE

en: Isotope measurements of tree-level tissues for the vegetative season 2019.

en:
Data from a 17-year-long irrigation experiment (Pfynwald, Switzerland) in a naturally dry forest dominated by 100-year-old pine trees (Pinus sylvestris). This dataset includes measure tree-ring width and tree-ring isotope chronologies (stable isotope ratios of non-exchangeable hydrogen δ2H, oxygen δ18O, and carbon δ13C), for the Pfynwald experiment, including control trees, irrigation and irrigation-stop treatments until the year 2019.

This dataset contains all data on which the following publication below is based.
Please cite this paper together with the citation for the datafile.

dendrochronology

display_name: dendrochronology

isotopes

display_name: isotopes

pfynwald

display_name: pfynwald

pinus-sylvestris

display_name: pinus-sylvestris

scots-pine

display_name: scots-pine

tree-ring-cellulose

display_name: tree-ring-cellulose

tree-rings

display_name: tree-rings

en: Pfynwald 2019 - Dendrochronological and tree-ring isotope dataset


en: crispr-cas african-manatee biodiversity-monitoring threatened-species qpcr crispr-dx environmental-dna field-based-protocol edna

media_type: text/plain

en: Description of project and folders and files

format: TXT

en:
Folder containing the data files with Cp values (qPCR) and the CRISPR-Dx classifications. CRISPR_field_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection) for the African manatee (Trichechus senegalensis).
CRISPR_lab_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection).
qPCR_Cp_2nd_derivative.csv file contains the Cp value of the 8 replicates of each extract.

en: File containing overview of site names and extract number (field-based or lab-based extraction). The extract_number_field_based corresponds to the identically called column in CRISPR_field_based_classifications.csv file in the data folder, as the extract_number_lab_based to the column in the file CRISPR_lab_based_classifications.csv file and the qPCR_Cp_2nd_derivative.csv file (also in the data folder). The file includes the GPS coordinates of the sampling location (transect start point).

en:
Data associated to the publication "Rapid field-based detection of a threatened and elusive species with environmental DNA and CRISPR-Dx"

 Authors:

Flurin Leugger, Martina Lüthi, Michel Schmidlin, Zacharias Kontarakis and Loïc Pellissier

 Contact:

flurinleugger@gmail.com
loic.pellissier@usys.ethz.ch

 Project description:

We collected eDNA samples in the Conkouati-Douli National Park in the Republic of Congo in 2023 in collaboration with Beauval Nature and HELP Congo. We analyzed the samples on site in the national park using CRISPR-Dx assays to detect the African manatee (*Trichechus senegalensis*). Additionally, we transported the remaining samples (buffer) to Switzerland and used a high-sensitivity protocol with CRISPR-Dx assays and a qPCR assay to verify the field-based detections. The qPCR of Hunter et al. (2018) detects the genus manatee (Trichechus). See publication for more details (doi will be added after publication).

 Folders:

 lateral_flow_tests_images\:

Images of the lateral flow tests used to analyze the eDNA extracts in the national park. File names correspond to the site names. At each site, we took two filter replicates. We ran 8 PCRs per filter/extract and pooled two PCRs together, resulting in 4 CRISPR-Dx assays per extract. The EVE number on top of the tests indicates the environmental extract number we use to track the extracts in our data base. It corresponds to the extract_number_field_based in the metadata and data folder. The negative extraction control with the strongest "band" was placed right to the eDNA extract on each image (labelled hand written with NC x.y).

 metadata\:

File containing overview of site names and extract number (field-based or lab-based extraction). The extract_number_field_based corresponds to the identically called column in CRISPR_field_based_classifications.csv file, as the extract_number_lab_based to the column in the file CRISPR_lab_based_classifications.csv file and the qPCR_Cp_2nd_derivative.csv file. The file includes the GPS coordinates of the sampling location (transect start point).

 data\:

Folder containing the files with Cp values (qPCR) and the CRISPR-Dx classifications. CRISPR_field_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection) for the African manatee (Trichechus senegalensis).
CRISPR_lab_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection).
qPCR_Cp_2nd_derivative.csv file contains the Cp value of the 8 replicates of each extract.

african-manatee

display_name: african-manatee

biodiversity-monitoring

display_name: biodiversity-monitoring

crispr-cas

display_name: crispr-cas

crispr-dx

display_name: crispr-dx

edna

display_name: edna

environmental-dna

display_name: environmental-dna

field-based-protocol

display_name: field-based-protocol

qpcr

display_name: qpcr

threatened-species

display_name: threatened-species

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Field-based eDNA analysis to detect the threatened and elusive African manatee


en: photovoltaic winter-electricity snow alps bifaciality

en:
Title: Monitoring data set at A2 (utility-scale power-plant Muttsee), months 10.2022-09.2023
Provider: AXPO - IWB Industrielle Werke Basel
Last edition: 17.01.2024
Editor: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL
File name structure:
The power-plant is made of 23 string boxes (GAK) and inverters (WR) named after their given number. One file per device is provided in the data/ subfolder, following the same naming convention (e.g. for the string box number 1, the file name is: “A2_GAK01.csv” and for the corresponding inverter, the file name is “A2_WR01.csv”). Refer to the publication for further details on the setup of the power plant.
File format:
All files are provided in the CSV format.
Column headings:
	String boxes and inverters (GAK & WR):
	⁃	device_name (string): name of the device (same as file name)
	⁃	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC
	String boxes (GAK):
	⁃	I_ (double): input current from the substring number (W)
	⁃	I_SUM (double): output current of string box (A)
	⁃	U_DC (double): output voltage of string box (V)
	⁃	P_DC_ (double): input DC power from the substring number (W)
	⁃	P_DC (double): output DC power of string box (W)
	⁃	$S$_T#_$T$ (double): temperature from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S) of table T. Two types of temperature measurements (#) are available: 1=standard cell temperature (°C) , 2=module temperature on the rear side (°C) .
	⁃	$S$_SRAD_T (double): poa irradiation (W/m**2) from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S) of table T.
		Inverters (WR):
	⁃	I_DC (double): input DC current(A)
	⁃	U_DC(double): input DC voltage(V)
	⁃	P_DC (double): input DC power (W)
	⁃	P_AC (double): output AC power (W)
Preprocessing:
	1. Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.

	2. Missing data:
	⁃	Data holes of less or equal to 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).
	3. Wiring losses:
	⁃	To be consistent with A1, wiring losses are corrected at A2. The wiring loss between the string boxes and the inverters is removed by multiplying the value of input P_DC at the inverter level (P_DC,inv) by the mean ratio P_DC,inv / P_DC,arr.
	⁃	The computed mean wiring loss is 2.3\%. It is computed from 2023-02-01 to 2023-09-30, after the long data hole in the data sets of the string boxes.

Mean uptime:
	Raw:
	⁃	WR: 98.2%
	⁃	GAK*: 38.5%
	Processed:
	⁃	WR: 99.6%
	⁃	GAK*: 56.4%

	*The uptime at the string box level (GAK) is low because PMUs at this level shut down during steady and low signal leading to unavailable data at night. In addition, the 23 days downtime of 	January 2023 could not be interpolated nor replaced.

en:
Title: Monitoring data set at A1 (test-site of Totalp), years 2018-2022
Provider: ZHAW - EKZ
Edition: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL
Last edition: 17.01.2024
File name structure:
The test site contains 6 segments named from A to F. The six files provided in the data/ subfolder follow the same naming convention (e.g. for segment A, the file name is: “A1_A.csv”). Refer to the publication for further details on the setups of the segments.
File format:
All files are provided in the CSV format.
Column headings:
	•	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC
	•	poa_front (double): front plane-of-array irradiation (W/m**2)
	•	poa_back (double): rear plane-of-array irradiation (W/m**2)
	•	mod_temp (double): module’s temperature (°C)
	•	P_AC (double): output AC power (W)
Preprocessing:
	Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.
	Missing data:
	⁃	Data holes of less than 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).
	Wiring losses :
	⁃	As described in [1] , the test-site setup caused abnormally large wiring losses, mainly due to the distance to optimisers and to the low installed power per DC-wire.
	⁃	The wiring losses comprised between 10% and 15%, are averaged hourly and added to the measured DC power.

	Misc.:
	⁃	P_AC is computed for each segment based on the measured DC power and the average inverter’s efficiency (96.1%).
	⁃	As described in [1], the peak power of the installed module, used to compute the final yield is slightly different from the values announced by the manufacturer.
Mean uptime:
	Raw:
	⁃	95.2%
	Processed:
	⁃	100%
References:
[1] 	D. Anderegg, S. Strebel, and J. Rohrer, “Alpine Photovoltaik Versuchsanlage Davos Totalp : Erkenntnisse aus 5 Jahren Betrieb,” de, Sep. 	2023, Accepted: 2023-09-29T09:13:16Z Publisher: ZHAW Zürcher Hochschule für Angewandte Wissenschaften.DOI: 10.21256/	zhaw-2524. [Online]. Available: https://digitalcollection.zhaw.ch/handle/11475/28797 (visited on 12/15/2023).

en:
On this repository you can find the monitoring data of the 3 PV power-plants analysed in the article _"Confirmation of the power gain for solar photovoltaic systems in alpine areas"_ (doi: 10.3389/fenrg.2024.1372680) . Each folder contains the following two elements:
1. **README.txt** : describes the content of the folder. Especially it describes the plant's monitoring system's architecture and relates it to the various files included in the data sub-folder. It also provides a detailed description of all processing steps leading to the data sets as available in the data sub-folder and used in the pre-cited article.
3. **data/** : sub-folder containing the file(s) used in the referenced article.

alps

display_name: alps

bifaciality

display_name: bifaciality

photovoltaic

display_name: photovoltaic

snow

display_name: snow

winter-electricity

display_name: winter-electricity

en: Monitoring data sets of alpine photovoltaic power-plants


en: urbanization land-use modeling landscape-services statistical-model switzerland land-use-change

en: Scripts for Assessing potential landscape service trade-offs driven by urbanization in Switzerland

en:
Scripts ordered by their main purpose within sequential folders in this ReadMe marked with

Within the folders the capital letters refer to the parallel or sequential use of the scripts; scripts here in ReadMe are marked with

 00_Function Scripts
 Functions.r
Script containing several functions for analyzing statistical models: cohen.kappa, meva.table, D2, max-Tss, plot-TSS

 Service_functions.R
Script containing functions for calculating all services and returning sums (and median for bd and rec) as well as rasters

 01_Data Preparation
 A_AS_raster_preparation.R
Preparation of the land use rasters for the years 1985, 1997, and 2009 based on the original Arealstatistik (AS/ASCH); Assigning our categories and assining new values to all "construction sites" for calibrating the models
For model projection starting point (2009) and for service calculations (all ASCH years) the "other" categories were assigned to the land use categories based on dominant neighbor, so that there were no empty cells
Creation of water & mountainous area raster that stayed stable throughout the projections
Creation of MFH raster (2009), to have as base for all new projection years, as this category never becames any other

 B_Factors_preparation.R
Preparation of the factor rasters that were used to calculate service values per cell (see Table 2): LWfactor, Transportation, Vol, Rivers, Lakes, slope, TWW, Hazard_risk

 B_Predictors_preparation.R
Preparation of the raster of the predictors used for calibrating (ASCH years) and projecting (stable) the transition models that do not depend on the land use categories: Temperature (ASCH years), solar radiation (stable), Public transportation access (stable), Elevation (stable), Workers density (ASCH years), Population change (ASCH transitions)

 B_Regions_preparation.R
Preparation of bioregions as raster to be used to mask asxxxx later to calculated services and land use area just for one region

 C_Pred_proj.R
Projecting the dynamic predictors into the future for projecting the land use transitions with the model: Linear extrapolations for workers densities and population; more detailed extrapolation of temperature (based on data for all stations that matched between the temp table we used for the calibration period and the projections from CS2M, and then making a spatial interpolation for all years based on the interpolation of temperature for all years per station)

 02_Model calibration
 A_Bioreg_pred_corr.R
Calculating correlation between the predictors for each bioregion and land use category, Output are those with too high correlation so that one predictor can be removed from transitions were both predictors occur

 A_trans_numbers_bioreg.R
Calculate transition numbers for each bioregion to decide which transitions to primarily consider

 B_Bioreg_ext_eval.R
Calculating TSS based on the external evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 85-97, evaluation data: 97-09)

 B_Bioreg_int_eval.R
Calculating TSS based on the internal evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 70%, evaluation data: 30%)

 C_Bioreg_TSS_analysis.R
Extracting TSS numbers from internal and external evaluation, calculating mean and median for each transition for each region for each evaluation method and saving as csv per region to be able to select only the transitions with high enough model performance

 D_Bioreg_Models_for_prediction.R
Calibration of the models that were then used to project land use transitions into the future; calibrated separately for each bioregion

 E_Residuals_trans_models.R
Calculation of Moran's I statistics to analyze the residuals of the land use transition models

 03_Projections
 A_Bioreg_Projections_run.R
Master script for: Extrapolaitng into the future with the regional models and then assembling for each time step to calculate new AS predictors; Several Outputs: txt file to test for NAs in Predictors, txt file with random seed number for sampling, txt file with times for calculation steps (check progress of script while running), csv sheet with projected transition frequencies, tif-rasters for every region and time step, pdf with raster plot for every region and time step

 04_Service calculation
 A_Bioreg_as_services.R
Calculate services per bioregion for years 1985, 1997, 2009

 A_Service_calculation_bioregions.R
Extracting service numbers(sums) per bioregions for all projection runs and storing them in a list of matrixes to be available for further plotting; can be run for swiss wide projections or regional ones

 05_Analysis
 A_Bioreg_ASCH_development.R
Extracting the occurrence of each category per region for all runs (first part), then for ASCH years, and then plotting them nicely; only works for regional projections

 A_Bioreg_Predictors_importanceD2.R
Calculating D2 for each transition and each considered predictor from bivariate models to get value of importance

 B_Bioreg_Pred_imp_analysis.R
Using calculated D2 to sort Predictors according to their importance for each transition

 A_Bioreg_Spatial_results_analysis.R
Plotting randomly sampled runs for ASCH and services to analyses their spatial development

 A_Bioreg_Transition_numbers_check_v1.R
Analyzing the frequency for all transitions for all regions and producing the point plots for each transition separately

 A_Bioreg_Transition_numbers_check_v2.R
Analyzing percentage and numbers of all transitions but plotting them per region and originating ASCH category

 B_Transition_Analysis.R
Further Analysis of transition numbers

 A_Service_analysis.R
Plotting of the service development for bioregions in several ways for analyzing

en: Data for Assessing potential landscape service trade-offs driven by urbanization in Switzerland

en:
The provided folder structure follows the set up of the scripts.
Data is only provided when it has been fully produced by us, otherwise dummies are given.
For data that will be produced by one of the scripts, no dummies are given.
The folders may contain sub-folders, which would be filled if the scripts were all run

 00_Analysis_Data
Data produced throughout the process of the calibration and projection that is later needed for analysis

 01_Raw_Data
Primary data from external sources that were used to compile the rasters and numbers used during the calibration and projection of landscape transitions as well as service calculation

 02_Prepared_Data
Data that will be prepared for further use by scripts are put in here
Additionally it contains the parameter sheets for the transition predictors that we compiled

 03_Model_Data
 Model outputs
Folder were the projection models statistics will be saved
 Models
Folder into which the actual transition models will be saved
 Residuals
Folder into which data on models residuals will be saved for future use

 04_Projected_Data
The output of the projections will be saved into this folder

 05_Service_Data
Any service calculations will be saved in here

 06_Results_Analysis
Any Analysis plots and tables as well as intermediate data will be saved here in the respective sub-folder

en:
Data and scripts of publication:

Madleina Gerecke, Oskar Hagen, Janine Bolliger, Anna M. Hersperger, Felix Kienast, Bronwyn Price, Loïc Pellissier (2019) Assessing potential landscape service trade-offs driven by urbanization in Switzerland. Palgrave communications.

Contains land use projections for Switzerland and scripts and data for these projections as well as the calculation of landscape services.

Data Folder:
Contains sub-folder with the data necessary for this study (provided were no copyright issues, otherwise placeholders with descriptions), and folders where produced data may be stored

Scripts Folder:
Contains scripts organized into subfolders depending on their purpose

Note: Some abbreviations within the scripts and data are derived from German words and not English.

land-use

display_name: land-use

land-use-change

display_name: land-use-change

landscape-services

display_name: landscape-services

modeling

display_name: modeling

statistical-model

display_name: statistical-model

switzerland

display_name: switzerland

urbanization

display_name: urbanization

en: Land use projections and services for Switzerland


maintainer: Matthias Haeni

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

en: Data plot of the forest station (JUB)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Site photo of the field station (JUF)

en: Site photo of the field station from the side.

mimetype: image/jpeg

en: Forest station data (JUB)

en: Data file.

mimetype: text/csv

en: Site aerial photo (Jussy)

en: Site aerial photo from both Jussy stations. Source: Google. 2016. Site aerial photo from both Jussy stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: Data plot of the field station (JUF)

en: Site photo of the forest station (JUB)

en: Site photo of the forest station from the side.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Jussy in Switzerland where one station is located within a natural broad-leaved forest stand (JUB) with sessile oak (_Quercus petrea_; 90 yrs), aspen (_Populus tremula_; 60 yrs) and European hornbeam (_Carpinus betulus_; 60 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, JUF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Jussy is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


en: climate-change fagus-sylvatica forest forest-management ground-vegetation air-pollution

en: Taxa Data

en: This table contains information about the individual taxa found in the historic and current vegetation relevés in Scherrer et al. 2024.

en: Site Information

en: This table contains information about the 254 forest sites used in the publication of Scherrer et al. 2024.

en: This dataset comprised 254 historical (1937 – 1948) and resurveyed (2019 – 2022) vegetation relevés of beech-dominated forests sites in the Swiss Jura mountains. The data contains species lists as well as site information.

air-pollution

display_name: air-pollution

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

forest-management

display_name: forest-management

ground-vegetation

display_name: ground-vegetation

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Resurveyed vegetation releves of beech forests in the Swiss Jura Mountains


maintainer: Sofia Pagliarin

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

en: Information on data sources

en: 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

en:
Dataset description

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)

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).

 Dataset composition

The dataset is provided in .csv format and is composed of:

_IMD15_BCN_MI_Sources.csv_: Information on data sources

 _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)

 _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)

_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).

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.

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.

 Further information on the Dataset

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.

 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.

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).

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.

 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.

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.

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: Soil sealing Barcelona and Milan different territorial levels


maintainer: Frank Techel

en: avalanche-danger switzerland extended-column-test norway rutschblock-test avalanche-observations

en: avalanche occurrence data (Norway, Sitzerland) - largest avalanche size per day and warning region

en: ECT data (Norway, Switzerland)

en: avalanche occurrence data (Norway, Sitzerland) - avalanche sizes per day and warning region

en: Rutschblock data (Switzerland)

en:
Observational data used to quantitatively describe the key elements describing avalanche danger: snowpack stability, the frequency distribution of snowpack stability, and avalanche size.
The data set consists of
- Rutschblock test results (Switzerland)
- Extended Column Test results (Switzerland, Norway)
- Avalanche occurrence data (Switzerland, Norway).
The data were extracted from the respective operational databases of the national avalanche warning services in Switzerland (WSL Institute for Snow and Avalanche Research SLF Davos, Switzerland) and Norway (The Norwegian Water Resources and Energy Directorate NVE).
For further information regarding the data, please refer to the publication or contact the author.

avalanche-danger

display_name: avalanche-danger

avalanche-observations

display_name: avalanche-observations

extended-column-test

display_name: extended-column-test

norway

display_name: norway

rutschblock-test

display_name: rutschblock-test

switzerland

display_name: switzerland

en: Stability tests, avalanche observations, Switzerland, Norway


en: monitoring bayesian-inference occupancy-model detectability observer-error biodiversity lichens swisslichens inter-observer-difference detection-probability cryptogams sessile-species

en: Repository containing the full data, code, README and workflow files.

en:
The available lichen data consists of detection/nondetection data (1/0) of 373 tree-inhabiting (*corticolous*) lichen species from 416 plots surveyed 1-2 times. The lichen data were originally collected for the purpose of the Red List of epiphytic lichen species in Switzerland ([Scheidegger *et al.* 2002](https://www.bafu.admin.ch/bafu/de/home/themen/biodiversitaet/publikationen-studien/publikationen/rote-liste-gefaehrdete-arten-baum-erdbewohnende-flechten.html)), but updated to recent nomenclature for the purpose of this study.
This repository contains all the supporting data and R code for the paper:
von Hirschheydt, G., Kéry, M., Ekman, S., Stofer, S., Dietrich, M., Keller, C., Scheidegger, C. (2024) **Occupancy model reveals limited detectability of lichens in a standardised large-scale monitoring**. *Journal of Vegetation Science*.
Results and figures presented in the manuscript should be reproducible (with small differences in the latter digits due to stochasticity of the MCMC sampler) with the provided data and code.
The downloadable `.zip` folder has the following structure:
* `0_data/`
* `1_code/`
* `2_output/`
* `lichen_detectability.Rproj`
* `README.txt`
* `workflow.html`
- `workflow.Rmd`

The main folder and the three subordinate folders each have their own `README*.txt` file. These describe each available file in detail and should be consulted prior to using the data or running any code. The file `lichen_detectability.Rproj` stores the information about the R project. The user can open the project by clicking/double-clicking on this file which will automatically define the repository as working directory for the R session. If the user does not use RStudio/Posit, they may have to set the working directory manually to the stored location in the R files. The files `workflow.*` guide the user through the analysis (`1_code/*.R`) in the correct order so that they can:
- bundle the cleaned data into a data list readable for JAGS
- fit the multi-species occupancy model to the data and store the output
- assess the goodness-of-fit of the model to the data
- conduct a prior sensitivity analysis with 2 additional sets of priors
- extract the summary statistics reported in the manuscript and supplementary materials
- generate the figures shown in the manuscript and supplementary materials

bayesian-inference

display_name: bayesian-inference

biodiversity

display_name: biodiversity

cryptogams

display_name: cryptogams

detectability

display_name: detectability

detection-probability

display_name: detection-probability

inter-observer-difference

display_name: inter-observer-difference

lichens

display_name: lichens

monitoring

display_name: monitoring

observer-error

display_name: observer-error

occupancy-model

display_name: occupancy-model

sessile-species

display_name: sessile-species

swisslichens

display_name: swisslichens

en: Repeated detection-nondetection data of corticolous lichens from a standardised monitoring across Switzerland


causal-effect-of-mfoz

title_for_slug: causal-effect-of-mfoz

en: built-up-land-change selection-bias propensity-score-matching causality the-major-function-oriented-zone fujian-province

en: Data and Stata code for repeating the results

en:
Data.xlsx is the variables of 952 townships
Table 1-2 NN(1-1)_noreplace_caliper(0.01).do is STATA code to produce the results in Table 1 and 2
Figure 5 Distribution of the propensity scores.R is R code rto produce Figure 5
Figure 5 Standard mean difference.R is R code rto produce Figure 5

en:
Title: Closer to causality: How effective is spatial planning in governing built-up land expansion in Fujian Province, China?

Research objective: The Major Function Oriented Zone (MFOZ), the first strategic spatial plan in China, is developed to achieve a coordinated regional development, through spatial regulation and zoning of development. The MFOZ he MFOZ divided land into four major function-oriented zones: The development-optimized zone, the development-prioritised zone, the development-restricted zone, and the development-prohibited zone. We used propensity score marching to evaluate the effect of the MFOZ on built-up land expansion in Fujian Province over three time intervals (2013–2015, 2013–2018 and 2013–2020).

Data: Data.xlsx contains the variables of 954 towns in Fujian Province.
Town_ID is the town unique ID;
County_ID is the county unique ID;
City_ID is the city unique ID;
MFOZ is the the development-prioritised zone and the development-restricted zone (The development-optimized zone and the development-prohibited zone are excluded);
Builtup_13_15 is the built-up land expansion from 2013 to 2015;
Builtup_13_18 is the built-up land expansion from 2013 to 2018;
Builtup_13_20 is the built-up land expansion from 2013 to 2020;
Dis2water is the Euclidean distance from the town to the nearest waterbody;
Slope is the the average slope within the town;
GDP is the average GDP in 2010 within the town;
Pop is the average population in 2010 within the town;
Road is the average population in 2010 within the town;
Dis2city is the Euclidean distance from the town to the nearest prefectural city centre;
Nei_Arable, Nei_Forest, and Nei_Built.up are the area of arable land, forest land, and built-up land neighbouring town i in 2010.

Method: we used the propensity score matching to compare the changes in the amount of built-up land in the towns of the development-prioritised zone with the matched towns of the development-restricted zone. Additionally, we used three evaluation intervals (2013–2015, 2013–2018 and 2013–2020) to evaluate temporal variation in the causal effect of the MFOZ on built-up land expansion.

built-up-land-change

display_name: built-up-land-change

causality

display_name: causality

fujian-province

display_name: fujian-province

propensity-score-matching

display_name: propensity-score-matching

selection-bias

display_name: selection-bias

the-major-function-oriented-zone

display_name: the-major-function-oriented-zone

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Causal effect of MFOZ


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

en: Overview over the soil dependency and endangerment status of different groups of organisms.

en: Proportion of endangered species grouped by the four soil dependency classes.

en: Raw dataset of species and their soil dependency as well as endangerment status.

en:
This dataset contains all data on which the following publication below is based.

Paper Citation:
Frey B., Maurer C., Schneider K. (2023) Informationen zum Boden anhand der Gebundenheit der Rote-Liste Arten BAFU. Bundesamt für Umwelt BAFU. 26 p.

Please cite this paper together with the citation for the datafile.

Soil is the habitat and basis of life for countless creatures. The great importance of soil organisms for the fertility of our soils is widely recognized, but information is sparse on their distribution and possible endangerment in Switzerland. In the present project, target species, i.e. species that are closely linked to the soil, were identified, and for the the first time, information was gathered on the degree of endangerment of the soil ecosystem in Switzerland on the basis of Red List species. For eleven Red List groups, the species' soil dependency was determined, i.e. whether their life cycle includes stages in or on the soil. The assessment of soil dependency was made using four classes, which enabled the classification not only of insects but also of vertebrates, land snails, lichens and fungi.

conservation

display_name: conservation

database

display_name: database

eco-fauna

display_name: eco-fauna

ecosystem-protection

display_name: ecosystem-protection

fauna

display_name: fauna

fungi

display_name: fungi

info-fauna

display_name: info-fauna

red-list

display_name: red-list

soil-biodiversity

display_name: soil-biodiversity

soil-dependency

display_name: soil-dependency

soil-organisms

display_name: soil-organisms

soil-quality

display_name: soil-quality

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


biogas-aus-hofdunger-in-der-schweiz

title_for_slug: biogas-aus-hofdunger-in-der-schweiz

en: review manure switzerland bioenergy biogas

en: Biogas aus Hofdünger in der Schweiz

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

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland


wind-lidar-davos-wolfgang

title_for_slug: wind-lidar-davos-wolfgang

en: lidar wolfgangpass profiles raclets wind

en: Wind LIDAR data Wolfgang

en: A Leosphere WidCube 100S was deployed at Davos Wolfang, measuring wind profiles as well as performing PPI and RHI scans. Time format is in UTC with highest time resolution of 5 seconds.

en: Scanning wind Lidar from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 200 m above ground to 8100 m. The time resolution is up to 5 seconds. The Lidar was measuring wind profiles but also performed plan position indicator (PPI) and range height indicator (RHI) scans.

lidar

display_name: lidar

profiles

display_name: profiles

raclets

display_name: raclets

wind

display_name: wind

wolfgangpass

display_name: wolfgangpass

en: Wind LIDAR Davos Wolfgang


radiosondes

maintainer: Jörg Wieder

title_for_slug: radiosondes

en: wind radiosonde temperature holoballoon raclets relative-humidity pressure wind-direction

en: Radiosond Sounding Files

en:
The "soundings" radiosond data contains information on ambient pressure (mbar), temperature (C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), and are ordered with respect to the height above ground (m AGL) with a step size of 20 m. The first line of each file idicates the geographic location and the start time (in UTC) of the ascent. If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

en: Radiosond Template Files

en:
The "template" files contain standard parameters, i.e. ambient pressure (mbar and Pa), temperature (°C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), as well as additional information, e.g. time (UTC and local time), dew point (°C), mixing ration (g/kg), density (kg m³), altitude (m MSL), height above ground (ft and m AGL), and geographic coordinates (longitude, latitude). If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

en: Radiosondes (Windsond, Sparv Embedded AB) were started in Davos Wolfgang (LON: 9.853594, LAT: 46.835577) to report height profiles of pressure, relative humidity and temperature at specific days. In addition to regular launches of radiosondes, sondes were attached to [HoloBalloon](https://www.envidat.ch/group/clouds-in-situ-raclets) to report the ambient conditions of the in-situ measurements. Further profiles of meteorological measures were recorded at [HoloGondel](https://www.envidat.ch/group/clouds-in-situ-raclets) which was installed at the gondola moving between Gotschnaboden and Gotschnagrat at 2285 m a.s.l.

holoballoon

display_name: holoballoon

pressure

display_name: pressure

radiosonde

display_name: radiosonde

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

wind-direction

display_name: wind-direction

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Radiosondes


maintainer: Leo Gallus Bont

en: digital-elevation-model seilaplan cable-yarding swiss-geodata geoinformation-system open-source digital-planning swiss-geo-downloader qgis-plugin

en: View video on youtube!

en: Herunterladen des DHM mit SwissGeoDownloader

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. The plugin ‘Swiss Geo Downloader’, which is available for the open source geoinformation software QGIS, allows freely available Swiss geodata to be downloaded and displayed directly within QGIS. It was developed in 2021 by Patricia Moll in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. In this tutorial we describe how to download the high accuracy elevation model ‘swissALTI3D’ with the help of the ‘Swiss Geo Downloader’ and how to use it for digital planning of a cable line with the plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to the Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

Link to Seilaplan website: https://seilaplan.wsl.ch

*********************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Das Plugin Swiss Geo Downloader, welches für das Open Source Geoinformationssystem QGIS zur Verfügung steht, ermöglicht frei verfügbare Schweizer Geodaten direkt innerhalb von QGIS herunterzuladen und anzuzeigen. Es wurde 2021 von Patricia Moll in Zusammenarbeit mit der eidgenössischen Forschungsanstalt Wald, Schnee und Landschaft WSL entwickelt. In diesem Tutorial beschreiben wir, wie man mit Hilfe des Swiss Geo Downloaders das hochgenaue Höhenmodell swissALTI3D herunterladen und für die Seillinienplanung mit dem Plugin Seilaplan verwenden kann.

Link zum Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

Link zur Seilaplan-Webseite: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geo-downloader

display_name: swiss-geo-downloader

swiss-geodata

display_name: swiss-geodata

envidat

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

en: Seilaplan Tutorial: DTM download with SwissGeoDownloader


en: stable-water-isotopes paleoclimate post-depositional-processes sublimation weissfluhjoch latent-heat snow natural-tracer

en:
Details on the data collected during the different field campaigns and available in this dataset.
Information on the sampling procedure of the snow isotopes samples.

en: Stable water isotopes in snow

en: Stable water isotopes in snow measurements

en: Stable water isotopes in vapor

en:
Stable water isotopes in vapor measurements. Processed (calibrated) and raw data for February - June 2017. Raw data for January and February 2020.
For the time in between July 2017 and April 2020, raw vapor isotopic measurements are available, but no calibrations were performed during that time. For data delivery, please contact one of the authors.
This folder also contains the post-processing scripts for stable water isotopes in vapor measurements.

en: Details about the different folders

en: Weather

en: Meteorological data, snow height measurement, and SNOWPACK simulations covering the different field campaigns.

en: Folder containing the scripts and data used in "Surface snow isotopic composition: post-depositional processes in an alpine snowpack" (Sadowski et al., 2022)

en:
Notice: Changes to the dataset are still possible. Please do not use this dataset until the final publication with a DOI. Contact the authors if you have questions about this.

This dataset contains measurements of stable water isotopes in snow and vapor on the Weissfluhjoch from different field campaigns (Winter 2017 (Trachsel, 2019), January 2020, December 2020, and March 2021 (Sadowski et al., 2022).
Snow profiles and surface samples are available at different frequencies for each campaign. Please see "Data_description.pdf" for details.

Scripts and SNOWPACK simulations used in (Trachsel, 2019) and (Sadowski et al., 2022) are also provided.

latent-heat

display_name: latent-heat

natural-tracer

display_name: natural-tracer

paleoclimate

display_name: paleoclimate

post-depositional-processes

display_name: post-depositional-processes

snow

display_name: snow

stable-water-isotopes

display_name: stable-water-isotopes

sublimation

display_name: sublimation

weissfluhjoch

display_name: weissfluhjoch

en: Stable Water Isotopes in snow and vapor on the Weissfluhjoch


maintainer: Milojevic

en: low-flow return-periods extreme-values alpine-precipitation reservoir-inflow

en: R codes for Extreme Values Analysis

en: Zip file containing R codes for running extreme value analyses for high precipitation and inflow events as well as code for determining return levels of low inflow and low precipitation events

en: Daily Luzzone Reservoir Inflow 01-01-2000 to 31-12-2019

en: Daily total water inflow to Luzzone reservoir. Natural inflow (LUZ_inflow_raw) is back-calculated based on daily water level in reservoir (removing hydropower inputs and spills). Linear interpolation between daily values is used to bring all inflow values into positive space (LUZ_inflow_intrp).

en:
 Summary

* Dataset of daily inflow to Luzzone reservoir in Ticino, Switzerland

* R scripts used to generate return levels for low reservoir inflow, low precipitation, high inflow, and extreme high precipitation based on various methods from extreme value analysis

 Data
The dataset included here is the "natural" reservoir inflow for the Luzzone reservoir.
Additional analyses were conducted on daily total precipitation of 6 meteorological stations (abbreviations: TIOLI, TIOLV, COM, VRN, VLS, ZEV). These precipitation data are freely available for teaching and research from the MeteoSwiss IDAweb portal (https://www.meteoswiss.admin.ch/services-and-publications/service/weather-and-climate-products/data-portal-for-teaching-and-research.html).

 Codes
R scripts used to determine return levels of the data set are included for both extreme high events and low events. The scripts include the following methods for calculating return levels:

* GEV (Generalized Extreme Value)

* GPD and GPDd (Generalized Pareto Distribution including declustered version)

* eGPD (extended Generalized Pareto Distribution)

* MEV (Metastatistical Extreme Value)

alpine-precipitation

display_name: alpine-precipitation

extreme-values

display_name: extreme-values

low-flow

display_name: low-flow

reservoir-inflow

display_name: reservoir-inflow

return-periods

display_name: return-periods

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Data and Code on Extreme Inflow and Lowflow Analysis for Alpine Reservoirs