en: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Schuebelbach, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Schuebelbach

en: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Schübelbach


waldabstandslinien-gemeinde-ingenbohl

title_for_slug: waldabstandslinien-gemeinde-ingenbohl

fr: oreb waldabstand waldgrenze

de: oreb waldabstand waldgrenze

en: oreb waldabstand waldgrenze

it: oreb waldabstand waldgrenze

label: geocat.ch permalink

state: active

type: dataset

fr: WFS-Dienst des Kantons Schwyz

de: WFS-Dienst des Kantons Schwyz

en: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

format: WFS

fr: ÖREB: Waldabstandslinien, Gemeinde Ingenbohl

format: WMS

fr: Waldabstandslinien gemäss §67 PBG "Bauten und Anlagen" haben gegenüber Wäldern einen Mindestabstand von 15 m ab Waldgrenze einzuhalten. Weitergehenden Bestimmungen bzw. Ausnahmeregelungen finden sich in den Baureglementen zu den Nutzungsplänen der Gemeinden. Der Datensatz enthält nur diejenigen Waldabstandslinien, die aufgrund einer Sonderbestimmung im Baureglement der Gemeinde gegenüber dem gesetzlich festgelegten Waldabstand von 15 m einen Minderabstand zulassen. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Ingenbohl

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz

de: Das Amt für Geoinformation verwaltet und veröffentlicht die Geodaten des Kantons Schwyz als OGC-Geodienste und als Datei-Download. Alle aktuell verfügbaren Geodaten, welche dem OGD unterliegen, sind hier aufgeführt.

political_level: canton

kanton-schwyz

capacity: public

type: organization

approval_status: approved

value: SZ-Kt Geoinformation - Geocat Harvester

fr: Waldabstandslinien Gemeinde Ingenbohl

de: Waldabstandslinien Gemeinde Ingenbohl

en: Waldabstandslinien Gemeinde Ingenbohl

it: Waldabstandslinien Gemeinde Ingenbohl


label: WebGIS Kanton Schwyz, Thema einblenden

fr: Hinweisflächen Naturgefahren

de: Hinweisflächen Naturgefahren

en: Hinweisflächen Naturgefahren

it: Hinweisflächen Naturgefahren

fr: In Ergänzung zu den detaillierten Gefahrenkarten zeigen Gefahrenhinweiskarten die potenziellen Gefahrengebiete ausserhalb des Siedlungsgebietes auf. Die Gefahrenhinweiskarte macht die Aussage, ob an einer bestimmten Stelle eine Gefahr vorhanden ist oder nicht. Diese Karten enthalten grobe, z.T. modellbasierte Abschätzungen über das bei einem Extremereignis maximal betroffene Gefahrengebiet; sie enthalten jedoch in der Regel keine Information über die dabei auftretenden Intensitäten und Wahrscheinlichkeiten.

spatial: Kanton Schwyz (SZ)

fr: Gefahrenhinweiskarte

de: Gefahrenhinweiskarte

en: Gefahrenhinweiskarte

it: Gefahrenhinweiskarte


fr: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Kuessnacht, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Kuessnacht

fr: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Küssnacht (SZ)


de: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Sattel, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Sattel

de: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Sattel

fr: Sondernutzungsplanung Gemeinde Sattel

de: Sondernutzungsplanung Gemeinde Sattel

en: Sondernutzungsplanung Gemeinde Sattel

it: Sondernutzungsplanung Gemeinde Sattel


netzgebiete

title_for_slug: netzgebiete

fr: Netzgebiet: Netzebene 3

de: Netzgebiet: Netzebene 3

en: Netzgebiet: Netzebene 3

it: Netzgebiet: Netzebene 3

fr: Netzgebiet: Netzebene 5

de: Netzgebiet: Netzebene 5

en: Netzgebiet: Netzebene 5

it: Netzgebiet: Netzebene 5

fr: Netzgebiet: Netzebene 7

de: Netzgebiet: Netzebene 7

en: Netzgebiet: Netzebene 7

it: Netzgebiet: Netzebene 7

fr: Dieser kantonal erweiterte Datensatz basiert auf dem minimalen Geodatenmodell (MGDM) «Stromversorgungssicherheit: Netzgebiete» und teilt den Kanton für jede Netzebene in verschiedene Versorgungsgebiete ein. Diese Gebiete definieren, durch welche der jeweiligen Netzanbietenden die Anschluss- und Lieferpflicht wahrzunehmen ist.

fr: Netzgebiete

de: Netzgebiete

en: Netzgebiete

it: Netzgebiete


lokalisationsplan

title_for_slug: lokalisationsplan

fr: WFS-Dienst des Kantons Schwyz

fr: A232a: Lokalisationsplan

de: A232a: Lokalisationsplan

en: A232a: Lokalisationsplan

it: A232a: Lokalisationsplan

fr: Der Lokalisationsplan zeigt, welche Hauseingänge welchen Strassen, Plätzen oder benannten Gebieten zugeordnet sind. Die Zuordnung geschieht anhand von Farben. Als Grundlage dienen die Daten der amtlichen Vermessung des Themas «Gebäudeadressen».

fr: Lokalisationsplan

de: Lokalisationsplan

en: Lokalisationsplan

it: Lokalisationsplan


waldgrenzen-oereb

title_for_slug: waldgrenzen-oereb

fr: waldrand waldgrenze waldfeststellung waldabstand forstrecht

fr: ÖREB: statische Waldgrenze

de: ÖREB: statische Waldgrenze

en: ÖREB: statische Waldgrenze

it: ÖREB: statische Waldgrenze

fr: Forstrechtlich relevante Grenzlinien von Waldflächen gegenüber Bauzonen. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

fr: Waldgrenzen

de: Waldgrenzen

en: Waldgrenzen

it: Waldgrenzen


fr: oreb zonenplan bauzone grundplan flachennutzungsplan

de: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Nutzungsplanung kommunal, Reichenburg, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Reichenburg

fr: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Reichenburg


it: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Schwyz, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Schwyz

it: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Schwyz

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz

fr: Sondernutzungsplanung Gemeinde Schwyz

de: Sondernutzungsplanung Gemeinde Schwyz

en: Sondernutzungsplanung Gemeinde Schwyz

it: Sondernutzungsplanung Gemeinde Schwyz


en: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB Sondernutzungsplanung Gemeinde Lachen

fr: ÖREB: Nutzungsplanung kommunal, Lachen, Sondernutzungsplanung

spatial: Lachen

de: Das Amt für Geoinformation verwaltet und veröffentlicht die Geodaten des Kantons Schwyz als OGC-Geodienste und als Datei-Download. Alle aktuell verfügbaren Geodaten, welche dem OGD unterliegen, sind hier aufgeführt.

fr: Sondernutzungsplanung Gemeinde Lachen

de: Sondernutzungsplanung Gemeinde Lachen

en: Sondernutzungsplanung Gemeinde Lachen

it: Sondernutzungsplanung Gemeinde Lachen


fr: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Nutzungsplanung kommunal, Wollerau, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Wollerau

en: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Wollerau

fr: Sondernutzungsplanung Gemeinde Wollerau

de: Sondernutzungsplanung Gemeinde Wollerau

en: Sondernutzungsplanung Gemeinde Wollerau

it: Sondernutzungsplanung Gemeinde Wollerau


fr: nutzungsplan zonenplan bauzone grundplan flachennutzungsplan

fr: Nutzungsplanung kommunal. Geobasisdatensätze Nr. 73D - 73F gemäss KGeoiV Kanton Schwyz (SRSZ 214.111). Dieser Datensatz ist ÖREB-relevant. D.h. diejenigen Objekte, die die Verbindlichkeit "Nutzungsplanfestlegung" aufweisen, sind auch im ÖREB-Kataster ausgewiesen. Unter den Fachdaten sind alle Objekte aufgeführt, also auch Objekte mit den Verbindlichkeiten "orientierend", "hinweisend" und "wegleitend".

spatial: Riemenstalden

fr: Nutzungsplanung kommunal Gemeinde Riemenstalden


fr: Das eidgenössische Gebäude- und Wohnungsregister (GWR) enthält die wichtigsten Grunddaten zu Gebäude und Wohnungen. Es wird für Statistik-, Forschungs- und Planungszwecke genutzt und dient den Kantonen und Gemeinden für den Vollzug von gesetzlichen Aufgaben. Die Nachführung erfolgt in Koordination mit der Bau- und Wohnbaustatistik. Jedes Gebäude und jede Wohnung verfügt über eine schweizweit eindeutige und einmalige Identifikationsnummer (EGID bzw. EWID) sowie über eine geokodierte, nach der SNV-Norm 612040 standardisierte Adresse. Parzellennummern, Gebäudenummern und metrische Gebäudekoordinaten erlauben eine exakte geografische Lokalisierung der Gebäude.

fr: Eidg. Gebäude- und Wohnungsregister GWR (SZ)


fr: oreb zonenplan bauzone grundplan flachennutzungsplan

en: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Nutzungsplanung kommunal, Galgenen, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Galgenen

spatial: Galgenen

fr: Sondernutzungsplanung Gemeinde Galgenen

de: Sondernutzungsplanung Gemeinde Galgenen

en: Sondernutzungsplanung Gemeinde Galgenen

it: Sondernutzungsplanung Gemeinde Galgenen


de: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB Sondernutzungsplanung Gemeinde Gersau

fr: ÖREB: Nutzungsplanung kommunal, Gersau, Sondernutzungsplanung

fr: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Gersau

fr: Sondernutzungsplanung Gemeinde Gersau

de: Sondernutzungsplanung Gemeinde Gersau

en: Sondernutzungsplanung Gemeinde Gersau

it: Sondernutzungsplanung Gemeinde Gersau


waldabstandslinien-gemeinde-kuessnacht

title_for_slug: waldabstandslinien-gemeinde-kuessnacht

fr: oreb waldabstand waldgrenze

de: oreb waldabstand waldgrenze

en: oreb waldabstand waldgrenze

it: oreb waldabstand waldgrenze

fr: WFS-Dienst des Kantons Schwyz

fr: Waldabstandslinien gemäss §67 PBG "Bauten und Anlagen" haben gegenüber Wäldern einen Mindestabstand von 15 m ab Waldgrenze einzuhalten. Weitergehenden Bestimmungen bzw. Ausnahmeregelungen finden sich in den Baureglementen zu den Nutzungsplänen der Gemeinden. Der Datensatz enthält nur diejenigen Waldabstandslinien, die aufgrund einer Sonderbestimmung im Baureglement der Gemeinde gegenüber dem gesetzlich festgelegten Waldabstand von 15 m einen Minderabstand zulassen. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

fr: Waldabstandslinien Gemeinde Kuessnacht

de: Waldabstandslinien Gemeinde Kuessnacht

en: Waldabstandslinien Gemeinde Kuessnacht

it: Waldabstandslinien Gemeinde Kuessnacht


fr: ÖREB: Nutzungsplanung kommunal, Innerthal, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Innerthal

de: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Innerthal


waldabstandslinien-gemeinde-arth

title_for_slug: waldabstandslinien-gemeinde-arth

fr: waldabstand waldgrenze oreb

de: waldabstand waldgrenze oreb

en: waldabstand waldgrenze oreb

it: waldabstand waldgrenze oreb

fr: ÖREB: Waldabstandslinien, Gemeinde Arth

de: ÖREB: Waldabstandslinien, Gemeinde Arth

en: ÖREB: Waldabstandslinien, Gemeinde Arth

it: ÖREB: Waldabstandslinien, Gemeinde Arth

de: Waldabstandslinien gemäss §67 PBG "Bauten und Anlagen" haben gegenüber Wäldern einen Mindestabstand von 15 m ab Waldgrenze einzuhalten. Weitergehenden Bestimmungen bzw. Ausnahmeregelungen finden sich in den Baureglementen zu den Nutzungsplänen der Gemeinden. Der Datensatz enthält nur diejenigen Waldabstandslinien, die aufgrund einer Sonderbestimmung im Baureglement der Gemeinde gegenüber dem gesetzlich festgelegten Waldabstand von 15 m einen Minderabstand zulassen. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Arth

fr: Waldabstandslinien Gemeinde Arth

de: Waldabstandslinien Gemeinde Arth

en: Waldabstandslinien Gemeinde Arth

it: Waldabstandslinien Gemeinde Arth


waldabstandslinien-gemeinde-unteriberg

title_for_slug: waldabstandslinien-gemeinde-unteriberg

fr: ÖREB: Waldabstandslinien, Gemeinde Unteriberg

en: Waldabstandslinien gemäss §67 PBG "Bauten und Anlagen" haben gegenüber Wäldern einen Mindestabstand von 15 m ab Waldgrenze einzuhalten. Weitergehenden Bestimmungen bzw. Ausnahmeregelungen finden sich in den Baureglementen zu den Nutzungsplänen der Gemeinden. Der Datensatz enthält nur diejenigen Waldabstandslinien, die aufgrund einer Sonderbestimmung im Baureglement der Gemeinde gegenüber dem gesetzlich festgelegten Waldabstand von 15 m einen Minderabstand zulassen. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Unteriberg

fr: Waldabstandslinien Gemeinde Unteriberg

de: Waldabstandslinien Gemeinde Unteriberg

en: Waldabstandslinien Gemeinde Unteriberg

it: Waldabstandslinien Gemeinde Unteriberg


fr: oreb zonenplan bauzone grundplan flachennutzungsplan

de: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Nutzungsplanung kommunal, Ingenbohl, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Ingenbohl


fr: oreb zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Einsiedeln, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Einsiedeln

spatial: Einsiedeln

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz


waldabstandslinien-gemeinde-feusisberg

title_for_slug: waldabstandslinien-gemeinde-feusisberg

fr: oreb waldabstand waldgrenze

fr: ÖREB: Waldabstandslinien, Gemeinde Feusisberg

it: Waldabstandslinien gemäss §67 PBG "Bauten und Anlagen" haben gegenüber Wäldern einen Mindestabstand von 15 m ab Waldgrenze einzuhalten. Weitergehenden Bestimmungen bzw. Ausnahmeregelungen finden sich in den Baureglementen zu den Nutzungsplänen der Gemeinden. Der Datensatz enthält nur diejenigen Waldabstandslinien, die aufgrund einer Sonderbestimmung im Baureglement der Gemeinde gegenüber dem gesetzlich festgelegten Waldabstand von 15 m einen Minderabstand zulassen. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Feusisberg

fr: Waldabstandslinien Gemeinde Feusisberg

de: Waldabstandslinien Gemeinde Feusisberg

en: Waldabstandslinien Gemeinde Feusisberg

it: Waldabstandslinien Gemeinde Feusisberg


krebsgewasser

title_for_slug: krebsgewasser

fr: Krebsgewässer

de: Krebsgewässer

en: Krebsgewässer

it: Krebsgewässer

fr: WFS-Dienst des Kantons Schwyz

fr: Darstellung der Krebsgewässer und der potentiellen Fischgewässer im Kanton Schwyz, welche im Rahmen des Krebsinventars 2013 erhoben wurden. Die Krebsgewässer zeigen Gewässer mit bekannten Beständen an einheimischen Krebsen, wobei die potentiellen Krebsgewässer solche Fliessgewässer ausweist, welche geeignete Lebensräume für die heimischen Krebsarten bieten können.

amt-geoinformation-sz

de: Das Amt für Geoinformation verwaltet und veröffentlicht die Geodaten des Kantons Schwyz als OGC-Geodienste und als Datei-Download. Alle aktuell verfügbaren Geodaten, welche dem OGD unterliegen, sind hier aufgeführt.


fr: Im Interesse der Landwirte, vor allem der Maisproduzenten, werden geeignete Massnahmen verfügt. In der Schweiz ist kein Insektizid gegen den Maiswurzelbohrer bewilligt. Eine Tilgung ist somit nicht möglich. infolgedessen sind Vorbeugemassnahmen anzuordnen. Dies gilt insbesondere im Rahmen der Fruchtfolge, da der Maiswurzelbohrer ein typischer Fruchtfolgeschädling ist. Mit diesen Massnahmen soll erreicht werden, dass der Entwicklungszyklus des Maiswurzelbohrers unterbrochen wird, in dem Mais nicht nach Mais angebaut wird. Es werden im Kanton Schwyz abgegrenzte Gebiete im Radius von 10 km ab den Fundorten der Maiswurzelbohrer gebildet, in welchem Bekämpfungsmass- nahmen gelten sollen.


fr: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)


waldabstandslinien-gemeinde-illgau

title_for_slug: waldabstandslinien-gemeinde-illgau

fr: waldabstand waldgrenze oreb

fr: ÖREB: Waldabstandslinien, Gemeinde Illgau

fr: Waldabstandslinien gemäss §67 PBG "Bauten und Anlagen" haben gegenüber Wäldern einen Mindestabstand von 15 m ab Waldgrenze einzuhalten. Weitergehenden Bestimmungen bzw. Ausnahmeregelungen finden sich in den Baureglementen zu den Nutzungsplänen der Gemeinden. Der Datensatz enthält nur diejenigen Waldabstandslinien, die aufgrund einer Sonderbestimmung im Baureglement der Gemeinde gegenüber dem gesetzlich festgelegten Waldabstand von 15 m einen Minderabstand zulassen. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Illgau

fr: Waldabstandslinien Gemeinde Illgau

de: Waldabstandslinien Gemeinde Illgau

en: Waldabstandslinien Gemeinde Illgau

it: Waldabstandslinien Gemeinde Illgau


fr: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Lauerz, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Lauerz

it: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Lauerz

fr: Sondernutzungsplanung Gemeinde Lauerz

de: Sondernutzungsplanung Gemeinde Lauerz

en: Sondernutzungsplanung Gemeinde Lauerz

it: Sondernutzungsplanung Gemeinde Lauerz


de: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Feusisberg, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Feusisberg


fr: Waldstandorte

de: Waldstandorte

en: Waldstandorte

it: Waldstandorte

fr: Die Karte der Waldstandorte setzt sich aus den Feldkartierungen und der Waldstandort-Hinweiskarte zusammen. Überall dort, wo eine Feldkartierung vorhanden ist, wird diese angezeigt. Wenn keine Feldkartierungen vorhanden sind, wird die Waldstandort-Hinweiskarte verwendet. Aus den Attributen ist ersichtlich, ob ein entsprechender Waldstandort kartiert (Polygone) oder modelliert (Pixel) wurde. Die Feldkartierungen wurden von Atragene und von Hans-Ulrich Frey erstellt. Kartiert wurden Teile der kantonalen Waldreservate, sowie ausgewählte Streifen aus dem gesamten Kantonsgebiet. Die Waldstandort-Hinweiskarte (Modellierung) bildet die Verbreitung der 74 wichtigsten Waldstandorttypen des Kanton Schwyz bestmöglich ab. Bei den Waldstandorttypen handelt es sich um eine Reihe von idealisierten Bestandesbeschreibungen, die es ermöglichen, einen realen Waldbestand darin wiederzuerkennen. Diese Beschreibungen (abrufbare Typusblätter) umfassen die Baumarten des Naturwaldes sowie typisierte Angaben zu Standortsfaktoren wie Hangneigung, Exposition, Höhenverbreitung, klimatischen Bedingungen, Untergrund, Boden, Lage im Ökogramm, häufigen Arten der Bodenvegetation (Zeigerarten), Bestandesstrukturen sowie von Abgrenzungskriterien zu ähnlichen Einheiten (Frey et al. 2021). Die Waldstandort-Hinweiskarte wurde von Barbara Huber und Andreas Zischg (2021-2022) erarbeitet. Die Einteilung der Waldstandorttypen lehnt sich an jene des Schwyzer Waldbuchs «Mehr als nur Bäume» von Hans-Ulrich Frey (2022) an.

spatial: Kanton Schwyz (SZ)

fr: Waldstandorte (Feldkartierungen und Waldstandort-Hinweiskarte)


fr: oreb zonenplan bauzone grundplan flachennutzung

fr: WFS-Dienst des Kantons Schwyz

it: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Nutzungsplanung kommunal, Morschach, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Morschach

en: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Morschach


waldabstandslinien-gemeinde-oberiberg

title_for_slug: waldabstandslinien-gemeinde-oberiberg

fr: oreb waldabstand waldgrenze

de: oreb waldabstand waldgrenze

fr: ÖREB: Waldabstandslinien, Gemeinde Oberiberg

spatial: Oberiberg

fr: Waldabstandslinien Gemeinde Oberiberg

de: Waldabstandslinien Gemeinde Oberiberg

en: Waldabstandslinien Gemeinde Oberiberg

it: Waldabstandslinien Gemeinde Oberiberg


waldabstandslinien-gemeinde-alpthal

title_for_slug: waldabstandslinien-gemeinde-alpthal

en: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Waldabstandslinien, Gemeinde Alpthal

fr: Waldabstandslinien gemäss §67 PBG "Bauten und Anlagen" haben gegenüber Wäldern einen Mindestabstand von 15 m ab Waldgrenze einzuhalten. Weitergehenden Bestimmungen bzw. Ausnahmeregelungen finden sich in den Baureglementen zu den Nutzungsplänen der Gemeinden. Der Datensatz enthält nur diejenigen Waldabstandslinien, die aufgrund einer Sonderbestimmung im Baureglement der Gemeinde gegenüber dem gesetzlich festgelegten Waldabstand von 15 m einen Minderabstand zulassen. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Alpthal

fr: Waldabstandslinien Gemeinde Alpthal

de: Waldabstandslinien Gemeinde Alpthal

en: Waldabstandslinien Gemeinde Alpthal

it: Waldabstandslinien Gemeinde Alpthal


fr: oreb zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Altendorf, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Altendorf

fr: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Altendorf


fr: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB Sondernutzungsplanung Gemeinde Oberiberg

fr: ÖREB: Nutzungsplanung kommunal, Oberiberg, Sondernutzungsplanung

de: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)


stockgrenzen

title_for_slug: stockgrenzen

fr: waldgrenze waldfeststellung waldrand waldabstand forstrecht

fr: Stockgrenzen

de: Stockgrenzen

en: Stockgrenzen

it: Stockgrenzen

fr: Stockgrenzen (Polylinien) dienen der forstrechtlichen Bestimmung des Waldrandes innerhalb oder in unmittelbarer Nähe von Bauzonen sowie bei waldrelevanten Bauten oder Nutzungen ausserhalb der Bauzone. Sie sind vom Amt für Wald und Naturgefahren gemäss Waldfeststellungs- und Rodungsrichtlinien verfügt.


en: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Nutzungsplanung kommunal, Wangen, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Wangen

spatial: Wangen (SZ)

fr: Sondernutzungsplanung Gemeinde Wangen

de: Sondernutzungsplanung Gemeinde Wangen

en: Sondernutzungsplanung Gemeinde Wangen

it: Sondernutzungsplanung Gemeinde Wangen


it: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: ÖREB: Nutzungsplanung kommunal, Steinerberg, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Steinerberg

spatial: Steinerberg


waldabstandslinien-gemeinde-muotathal

title_for_slug: waldabstandslinien-gemeinde-muotathal

fr: oreb waldabstand waldgrenze

en: oreb waldabstand waldgrenze

it: oreb waldabstand waldgrenze

fr: ÖREB: Waldabstandslinien, Gemeinde Muotathal

fr: Waldabstandslinien gemäss §67 PBG "Bauten und Anlagen" haben gegenüber Wäldern einen Mindestabstand von 15 m ab Waldgrenze einzuhalten. Weitergehenden Bestimmungen bzw. Ausnahmeregelungen finden sich in den Baureglementen zu den Nutzungsplänen der Gemeinden. Der Datensatz enthält nur diejenigen Waldabstandslinien, die aufgrund einer Sonderbestimmung im Baureglement der Gemeinde gegenüber dem gesetzlich festgelegten Waldabstand von 15 m einen Minderabstand zulassen. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Muotathal

fr: Waldabstandslinien Gemeinde Muotathal

de: Waldabstandslinien Gemeinde Muotathal

en: Waldabstandslinien Gemeinde Muotathal

it: Waldabstandslinien Gemeinde Muotathal


fr: ÖREB: Nutzungsplanung kommunal, Vorderthal, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Vorderthal

fr: Die Gemeinden können Sondernutzungspläne erlassen und damit die allgemeine Nutzungsplanung in einem konkreten, klar umgrenzten Areal weiter präzisieren. Der Datensatz ist auch Bestandteil des Katasters der öffentlich-rechtlichen Eigentumsbeschränkungen (ÖREB)

spatial: Vorderthal


sondernutzungsplanung-gemeinde-alpthal

title_for_slug: sondernutzungsplanung-gemeinde-alpthal

fr: oreb zonenplan bauzone grundplan flachennutzungsplan

fr: Sondernutzungsplanung Gemeinde Alpthal

de: Sondernutzungsplanung Gemeinde Alpthal

en: Sondernutzungsplanung Gemeinde Alpthal

it: Sondernutzungsplanung Gemeinde Alpthal


fr: oreb zonenplan bauzone grundplan nutzungsplan flachennutzungsplan

de: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Nutzungsplanung kommunal, Arth, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Arth

fr: Sondernutzungsplanung Gemeinde Arth

de: Sondernutzungsplanung Gemeinde Arth

en: Sondernutzungsplanung Gemeinde Arth

it: Sondernutzungsplanung Gemeinde Arth


fr: WFS-Dienst des Kantons Schwyz

fr: ÖREB: Nutzungsplanung kommunal, Rothenthurm, Sondernutzungsplanung

fr: ÖREB Sondernutzungsplanung Gemeinde Rothenthurm

spatial: Rothenthurm

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz


fr: Landwirtschaftliche Produktionsstaetten, Stand 2023

fr: Landw. Bewirtschaftung: Produktionsstätten 2023


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

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

de: baulinie eigentumsbeschrankungoreb nutzungsplanung wald zonenplan

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

format: SERVICE

de: Zeigt die statischen Waldgrenzen aufgrund einer formellen Waldfeststellung durch die Dienststelle Landwirtschaft und Wald (lawa).

spatial: Kanton Luzern

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

fr: La géoinformation du canton de Lucerne est responsable de la collecte, du traitement et de la gestion des données à référence spatiale. Elle dirige, coordonne et surveille les travaux de la géoinformation et de la mensuration officielle.

en: Geoinformation of the Canton of Lucerne is responsible for the collection, processing and management of spatial data. It manages, coordinates and monitors the work of geoinformation and of the cadastral surveying.

de: Die Geoinformation des Kantons Luzern ist für die Erhebung, Verarbeitung und Verwaltung von raumbezogenen Daten zuständig. Sie leitet, koordiniert und überwacht die Arbeiten der Geoinformation und der amtlichen Vermessung.

it: La Geoinformation del Cantone di Lucerna è responsabile della raccolta, dell'elaborazione e della gestione dei dati territoriali. Gestisce, coordina e monitora il lavoro della geoinformazione e della misurazione ufficiale.

value: LU-Kt - Geocat Harvester

de: Statische Waldgrenzen


maintainer: Vanessa Burg

en: review switzerland biogas manure bioenergy

en: Biogas from animal manure in Switzerland: energy potential, technology development and resource mobilization

media_type: application/pdf

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

format: PDF

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e 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.

political_level: other

key: guid

key: uri

value: Envidat Harvester


maintainer: Yohann Chauvier

en: ecological-indicator-values phylogenetic-diversity taxonomic-diversity soil grain-size functional-diversity climate

en: Data access

media_type: application/zip

format: ZIP

en:
This dataset comprises a large array of ecological data for the European Alps:

  (1) Current soil and climate predictors at various resolutions.
  (2) GBIF observations of the European Alps Flora (~4,000 species).
  (3) Species habitat suitability maps (1,109 species; based on species observations filtered at 40x40-km)
  at various resolutions used in the study to generate (4); except 'expert'...
  (4) Expert, Taxonomic, phylogenetic and functional diversity of the study region at various resolutions
  (from 100-m to 40-km --> 100-m aggregated & mean to km + non-aggregated/predicted) for CLIM,
  SOIL and CLIM-SOIL models.
  (5) Ecological and altitudinal preferences of the European Alps Flora.
  (6) Data outputs of the related published article.
  (7) All scripts used for analyses.
  (8) Additional files used for analyses.
  (9) Improved set of species habitat suitability maps (~2,600 species; based on species observations
  filtered at 1x1-km) and related taxonomic diversity at 100-m resolution (aggregated to km +
  non-aggregated/predicted) for CLIM, SOIL and CLIM-SOIL models ---> not incorporated in the study.

climate

display_name: climate

ecological-indicator-values

display_name: ecological-indicator-values

functional-diversity

display_name: functional-diversity

grain-size

display_name: grain-size

phylogenetic-diversity

display_name: phylogenetic-diversity

soil

display_name: soil

taxonomic-diversity

display_name: taxonomic-diversity

en: Resolution in species distribution models shapes spatial patterns of plant multifaceted diversity


maintainer: EnviDat Support

en: landuse topography antarctica cryowrf wrf

en: WPSinput

en: Input files to run the Weather Research and Forecasting model (WRF) preprocessing system WPS with REMA topography and AntarcticaLC2000 landuse data (see Documentation for details).

mimetype: application/zip

en: Scripts

en: Scripts to run the preprocessing to produce WRF binary tiles from REMA and AntarcticaLC2000 for topography and landuse (see Documentation for procedure).

en: Documentation

en: Documentation about how the provided dataset was produced including details to reproduce the dataset.

mimetype: application/pdf

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

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

en: REMA topography and AntarcticaLC2000 for WRF


swiss-fluxnet-site-davos

title_for_slug: swiss-fluxnet-site-davos

en: icos eddy-covariance meteorological-measurements swiss-forest-lab flux greenhouse-gas swiss-fluxnet forest

en: Site description

en: The flux and meteo data of the Swiss FluxNet site Davos are openly available. Near real-time flux and meteo data are uploaded daily to the ICOS Carbon Portal.

en: Processed data

en: Processed flux and meteo data are available from the European Fluxes Database Cluster.

en: Fluxnet2015 dataset

en: Processed flux and meteo data are also part of the Fluxnet2015 dataset.

en:
The Swiss FluxNet Site Davos is a managed subalpine evergreen forest, located on the Seehorn mountain near Davos in the Swiss Alps. The site is dominated by Norway spruce. The tower is owned by the Federal Office for the Environment (FOEN).
Ecosystem flux measurements of CO2, H2O (since 1997) as well as CH4 and N2O (since 2016) are performed with the eddy covariance method.
In addition to Swiss FluxNet, the site is part of the National Air Pollution Monitoring Network (NABEL), the Long term Forest Ecosystem Research (LWF), the biological drought and growth indicator network (TreeNet) and of ICOS Switzerland (Integrated Carbon Observation System). Since November 2019, the site is an ICOS Class 1 Ecosystem station.

Measurements

- Ecosystem flux measurements of CO2, H2O vapour (since 1997) as well a CH4 and N2O (since 2016) are performed with the eddy-covariance method. This method is based on measurements of trace gas mixing ratios, using infrared gas analyzers (for CO2, H2O vapor) and laser spectrometers (for CH4 and N2O), combined with wind speed and wind direction measurements, using 3D sonic anemometers. To resolve the short-term turbulent fluctuations in the atmosphere, very fast measurements are needed: we measure at 10-20 Hz, i.e., 10-20 times per second. To assess the energy budget of each ecosystem, also radiation sensors and soil climate profiles are installed at the site.
- Sub-canopy eddy fluxes (CO2, H2O, since 2023 also CH4).
- Continuous profile concentration and forest floor flux measurement of CO2, H2O, CH4, N2O.
- Auxiliary micrometeorology and soil climate measurements.

Data availability

Near real-time flux and meteo data uploaded daily to the ICOS Carbon Portal. Processed flux and meteo data are also available from the European Fluxes Database Cluster and part of Fluxnet2015 dataset.

Data policy

ICOS data license:
[https://www.icos-cp.eu/data-services/about-data-portal/data-license](https://www.icos-cp.eu/data-services/about-data-portal/data-license)

Detailed site info:
[https://www.swissfluxnet.ethz.ch/index.php/sites/ch-dav-davos/site-info-ch-dav/](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-dav-davos/site-info-ch-dav/)

eddy-covariance

display_name: eddy-covariance

flux

display_name: flux

forest

display_name: forest

greenhouse-gas

display_name: greenhouse-gas

icos

display_name: icos

meteorological-measurements

display_name: meteorological-measurements

swiss-fluxnet

display_name: swiss-fluxnet

swiss-forest-lab

display_name: swiss-forest-lab

en: Swiss FluxNet Site Davos


maintainer: Merin Reji Chacko

en: biodiversity-assessment environmental-dna spatial-ecology biomonitoring dna-metabarcoding

en: Genomic data

en: Fastq files, primer descriptions and the final output dataset.

en: Field Metadata

en: Information concerning the locations and times of sampling, as well as the identity of the samplers and relevant comments.

en: Analysis and Figures

en: This zipped file includes R scripts and the datasets required to run the analyses. A README describes the columns in each dataset.

en: This dataset contains the results of a five-day field excursion which the extent to which eDNA sampling can capture the diversity of a region with highly heterogeneous habitat patches across a wide elevation gradient through multiple hydrological catchments of the Swiss Alps. Using peristaltic pumps, we filtered 60 L of water at five sites per catchment for a total volume of 1 800 L. Using an eDNA metabarcoding approach focusing on vertebrates and plants, we detected 86 vertebrate taxa spanning 41 families and 263 plant taxa spanning 79 families across ten catchments. This dataset includes two sets of data. The first (Genomic data) includes all the necessary data for the bioinformatic pipeline, whereas the second (Analysis Figures) contains tidied data and scripts for the reproduction of all figures/analyses in the article describing this study.

biodiversity-assessment

display_name: biodiversity-assessment

biomonitoring

display_name: biomonitoring

dna-metabarcoding

display_name: dna-metabarcoding

environmental-dna

display_name: environmental-dna

spatial-ecology

display_name: spatial-ecology

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: Vertebrate and plant taxa recovered from 10 catchments in Vaud using an eDNA-metabarcoding approach


maintainer: Peter Bebi

en: climate-change experiment stillberg carbon-dioxide soil-temperature vegetation

en: Project Description FACE Stillberg

media_type: text/html

en: Link to FACE project description on the WSL website.

format: HTML

en: Metadata FACE Stillberg Data File Description

media_type: text/csv

en: List of descriptions for each of the .csv FACE data files.

format: CSV

en: Data FACE Stillberg

en: Folder in .zip format containing the FACE datasets.

en: Metadata FACE Stillberg Experimental Design

en: Schematic illustration and tabular listing of the FACE experimental design.

en:
 Background information

High elevation ecosystems are important in research about environmental change because shifts in climate associated with anthropogenic greenhouse gas emissions are predicted to be more pronounced in these areas compared to most other regions of the world. This project involved a Free Air CO2 Enrichment (FACE) and soil warming experiment located in a natural treeline environment near Davos, Switzerland (Stillberg, 2200 m a.s.l.). Elevated atmospheric CO2 concentrations (+200 ppm) were applied from 2001 until 2009, and a soil warming treatment (+4 °C) was applied from 2007 until 2012. The combined CO2 enrichment and warming treatment reflects conditions expected to occur in this region in approximately 2050. A broad range of ecological and biogeochemical research was carried out as part of this environmental change project.

 Experimental design

The experiment consisted of 40 hexagonal 1.1 m² plots, 20 with a *Pinus mugo* ssp. *uncinata* (mountain pine, evergreen) individual in the centre and 20 with a *Larix decidua* (European larch, deciduous) individual in the centre. A dense cover of understorey vegetation surrounded the tree in each plot, including the dominant dwarf shrub species *Vaccinium myrtillus* (bilberry), *Vaccinium gaultherioides* (group *V. uliginosum agg.*, northern bilberry) and *Empetrum nigrum* ssp. *hermaphroditum* (crowberry) plus several herbaceous and non-vascular species.
At the beginning of the experimental period, the 40 plots were assigned to ten groups of four neighbouring plots (two larch and two pine trees per group) in order to facilitate the logistics of CO2 distribution and regulation. Half of these groups were randomly assigned to an elevated CO2 treatment, while the remaining groups served as controls and received no additional CO2. In spring 2007, one plot of each tree species identity was randomly selected from each of the 10 CO2 treatment groups and assigned a soil warming treatment, yielding a balanced design with a replication of five individual plots for each combination of CO2 level, warming treatment and tree species.

 Data description

Soil and air conditions have been monitored closely throughout the study period, with most measurements made during the combined CO2 x warming experiment (2007-2009). The data comprise of air temperature, soil temperature, soil moisture, sapflow, tree diameter and CO2 measurements.

carbon-dioxide

display_name: carbon-dioxide

climate-change

display_name: climate-change

experiment

display_name: experiment

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

vegetation

display_name: vegetation

en: FACE: Stillberg CO2 enrichment and soil warming study


disdrometer-data-laret

maintainer: Daniel Wolfensberger

title_for_slug: disdrometer-data-laret

en: precipitation disdrometer hydrometeors visibility raclets

en: Disdrometer Data Laret

en: The zip folder contains one netCDF file per day for Laret from February 7 to March 29 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Laret_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

en:
A laser optical disdrometer (Parsivel² , OTT Hydromet) was used to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms.
The dataset contains information on precipitation amount and type for the period of February 7 to March 29 2019 in Laret.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility


wind-crust-formation-snowmicropen-data

title_for_slug: wind-crust-formation-snowmicropen-data

en: wind-packing smp snowmicropen snow wind-crust

en: Processing scripts

en: Contains the R-scripts used to process the SMPs

en: README

media_type: text/plain

en: Describes the dataset in detail

format: TXT

mimetype: text/plain

en: SMP data

en: Links to the dataset

en:
This dataset contains the SnowMicroPen (SMP) data from 38 wind tunnel experiments on wind-packing / wind crust formation. These experiments were performed in the winters 2015/16 and 2016/17 and include more than 1000 SMP measurements.

The SMPs are organized per experiment. Each experiment subfolder contains the processed SMP profiles and some additional files.

Please refer to the README for more details on the data. The processing scripts are available for download as well. The scripts are mainly provided as documentation and would need to be adjusted to be used.

This dataset is the basis of the following publication:

Sommer C.G., Lehning M., & Fierz C. (2017). Wind tunnel experiments: Saltation is necessary for wind-packing. Journal of Glaciology, 63(242), 950-958. doi:10.1017/jog.2017.53

smp

display_name: smp

snow

display_name: snow

snowmicropen

display_name: snowmicropen

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

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: Wind crust formation: SnowMicroPen data


en: remote-sensing sentinel-2 switzerland force raster-processing

media_type: image/tiff

en: An example of the index EVI for one of the generated 30 by 30 km tiles located around the city of Zürich. The values are multiplied by 10.000. The date of the image is 24.07.2018.

format: TIFF

en:
We processed Sentinel-2 images from 2017 to 2023 for Switzerland with the Software FORCE (Frantz 2019). The respective parameter files can be found here: [Github](https://github.com/TLKoch/Sentinel-2_CH). All the images consist of several TB and therefore, access will be granted upon request.
The available bands (in spatial reference system EPSG 3035) are the following:
*Red, Green, Blue, NIR, Red-Edge-1, Red-Edge-2, Red-Edge-3, SWIR-1, SWIR-2*
The available indices (in spatial reference system EPSG 3035) are the following:
*CCI, CIRE, NDWI/NDMI, NDVI, EVI*
Further indices might be provided upon request.

 Processing
After downloading Level 1 data for the 14 Sentinel-2 tiles covering Switzerland (T31TGN, T32TLT, T32TMT, T32UMU, T32TNT, T32TPT, T31TGM, T32TLS, T32TMS, T32TNS, T32TPS, T32TLR, T32TMR, T32TNR) with an estimated cloud cover of less than 80 \%, we processed the data further with FORCE v. 3.7.8-12.
FORCE was used for radiometric correction, including atmospheric and topographic corrections using the digital elevation model from Copernicus Land Monitoring Service (EU-DEM v. 1.1), with a 25 m spatial resolution, a bidirectional reflectance distribution function (BRDF) correction, and an adjacency effect correction. For cloud masking, the improved Fmask algorithm with buffers of 300 m for clouds, 90 m for shadows, and 30 m for snow were used (Frantz et al. 2018; Zhu et al. 2015). All bands were resampled using cubic convolution to 10 m spatial resolution. Shadows, low and poor illumination as well as saturation were masked out. The co-registration of all images was made with monthly composites of near-infrared Landsat Collection 2 images from 2014 to 2021 (Rengarajan et al. 2020;Rufin et al. 2021). With this the geometric consistency improved. The processed images are available in tiles of 30 by 30 km.

 Example images
Uploaded is an example of the index EVI for one of the generated 30 by 30 km tiles located around the city of Zürich. The values are multiplied by 10.000. The date of the image is 24.07.2018.

force

display_name: force

raster-processing

display_name: raster-processing

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

en: Sentinel-2 imagery of Switzerland


maintainer: Dirk Nikolaus Karger

en: iucn species-distribution-models generalized-linear-models random-forests climate-variablity chelsa amphibians sdm range-maps interannual-climate-variability generalized-additive-models niche-models mammals reptiles

en: File containing the record dimension, genus, and species of the respective netcdf files

en: Mammals

en: Species distribution models based on different climate predictor groups

en: Readme file containing the file naming convention, file dimensions, and variable names

en: Amphibians

en: File containing the climate predictors as SAGA grid files (.sgrd)

en: Reptiles

en: We modelled the global distribution of 730 amphibian, 1276 reptile, and 1961 mammal species globally as a function of current climate at a 0.5° spatial resolution using four different predictor groups composed of different combinations of input variables: mean climatic conditions, spatial climatic variability, and temporal (interannual) climatic variability.

amphibians

display_name: amphibians

chelsa

display_name: chelsa

climate-variablity

display_name: climate-variablity

generalized-additive-models

display_name: generalized-additive-models

generalized-linear-models

display_name: generalized-linear-models

interannual-climate-variability

display_name: interannual-climate-variability

iucn

display_name: iucn

mammals

display_name: mammals

niche-models

display_name: niche-models

random-forests

display_name: random-forests

range-maps

display_name: range-maps

reptiles

display_name: reptiles

sdm

display_name: sdm

species-distribution-models

display_name: species-distribution-models

en: Global species distributions for mammals, reptiles, and amphibians


en: irradiance energy mountain reflection snow albedo photovoltaic

en: Windows users use the 7-zip app to extract the zip-file.

en: PV Data

format: XLS

en:
 Overview
The SUNWELL Modelling Environment is a combination of data and code that models electricity production from satellite-derived irradiance data and other spatial data sets for all of Switzerland. This ensemble accompanies the publication "The bright side of PV production in snow-covered mountains", published in the Proceedings of the National Academy of Science and reproduces all results and figures of. Code and resources are in their original form (with documentation). A new version with a more generalized application to PV modelling and with more flexibility in terms of input and output formats will be released in the coming months.

 Format
All code is written and has to be executed in Matlab. The input and output data sets are also in the Matlab-specific .mat format. Whenever publicly available, the original data is provided as geotif, .xlsx or other common format.
This is the case for:

- Digital Elevation Model (InputsFromMatlab/MSG/OriginalData/ASTERDEM),
- Landsurface cover type (InputsFromMatlab/MSG/OriginalData/CORINE),
- Population Density (InputsFromMatlab/MSG/OriginalData/popdensRaster,
- Electricity production from three of our validation sites (/Validation/WSL),
- Measured irradiance for two validation sites (/Validation/ASRB)
The ‘Metadata’ documents in the respective folders provide further information about the data sources and processing. Figures are produced either in .pdf or .png format.

 Structure
The central level of the SUNWELL environment holds the 5 Mains, which run the different modelling aspects of the paper; each code is documented separately. Additional code is located in the ‘DataProcessing’ and the ‘functions’ folder. Functions are called in the different Mains.

‘InputsFromMatlab’ contains the radiation and albedo input data sets in separate subfolders (SIS/SISDIR/ALB). The original data is not publicly available, but can be requested for research purposes free of charge. We provide a processed subset of the data set that was used to run the SUNWELL simulations. The MSG subfolder contains additional spatial input data sets.

‘Outputs’ contains the output files from the different mains (matching names, Main_CHallpixels.m  Prod_CHallpixels)

‘Publication_figures’ contains all individual figures from the PNAS publication, as well as the generating code (/code_plot) and the power point figures (/ppts) that provide the combined final figures.

‘Validation’ contains the data sets used in the model validation:

- Electricity production from three of our validation sites (/WSL),
- Measured irradiance for two validation sites (/ASRB)

Electricity production from a validation site at Lac des Toules in Wallis (/LDT), this data set was provided under an NDA and cannot be made publicly available.

Paper Citation:
 > _Annelen Kahl; Jérôme Dujardin; Michael Lehning (2018). Dataset on PV Production in Snow Covered Mountains. PNAS - Proceedings of the National Academy of Sciences. (in press)_

albedo

display_name: albedo

energy

display_name: energy

irradiance

display_name: irradiance

mountain

display_name: mountain

photovoltaic

display_name: photovoltaic

reflection

display_name: reflection

snow

display_name: snow

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal


en: antarctica gridded-data terrestrial-laser-scans depth-of-snowfall terrestiral-laserscanning

en: Deprecated: Scan from 11 January 2019, 10 cm resolution, version 1

en: This resource is deprecated. It contains erroneous data.

en: Scan from 2 January 2019, 10 cm resolution

en: Scan from 4 January 2019, 1 mm resolution

en: Scan from 11 January 2019, 10 cm resolution, version 2

en: Scan from 4 January 2019, 10 cm resolution

en: Scan from 11 January 2019, 1 mm resolution

en: Scan from 21 December 2018, 10 cm resolution

en: Scan from 27 December 2018, 10 cm resolution

en: Scan from 2 January 2019, 1 mm resolution

en: Scan from 27 December 2018, 1 mm resolution

en: Scan from 21 December 2018, 1 mm resolution

en:
Surface topography maps (spatial extent: 400 m x 400 m) obtained at approximately 300 m from the top of the Hammarryggen Ice Rise in Dronning Maud Land, East Antarctica, using a Riegl VZ-6000 Terrestrial Laser Scanner (TLS). Scans were obtained on 5 days in the 2018-2019 Austral summer: on December 21 and 27, and January 2, 4 and 11. By using reflectors installed on bamboo poles, scans were registered with respect to the reflectors, such that the difference between two successive scans reveals the spatial patterns of erosion and deposition of snow. On each scan day, we used multiple scan positions to create one combined point cloud. After applying an octree filter on the point cloud, a 3D surface was obtained. For each day, the dataset contains a 1 mm and a 10 cm octree filter resolution file, only including points in a 400 m x 400 m area centered around the scan positions.

Notes:

* All files in the dataset are in the same coordinate system. However, this coordinate system is arbitrary (i.e., not related to any global coordinate system).

* From the installed reflectors, 4 reflectors could be used over the full period. The scan accuracy is generally higher within the area enclosed by the reflectors.

* The scans from January 2 were found to have exhibited small tilt during the scan and are of lesser accuracy.

* By walking along fixed corridors, disturbance of the snow was limited.

antarctica

display_name: antarctica

depth-of-snowfall

display_name: depth-of-snowfall

gridded-data

display_name: gridded-data

terrestiral-laserscanning

display_name: terrestiral-laserscanning

terrestrial-laser-scans

display_name: terrestrial-laser-scans

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: Terrestrial laser scans on Hammarryggen Ice Rise, Dronning Maud Land, East Antarctica


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

en: Data access

en:
Catchment-based sampling of river eDNA integrates terrestrial and aquatic biodiversity of alpine landscapes

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

edna

display_name: edna

environmental-dna

display_name: environmental-dna

freshwater

display_name: freshwater

spermatophytes

display_name: spermatophytes

switzerland

display_name: switzerland

vertebrates

display_name: vertebrates

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Environmental DNA Freshwater Switzerland VaudCatchment Modipl 2020


greenland-climate-network-gc-net-data

title_for_slug: greenland-climate-network-gc-net-data

en: net-radiation automatic-weather-station air-temperature climate aws greenland

en: Access the latest L1 data

en:
The GC-Net is kindly continued by the Geological Survey of Denmark and Greenland (GEUS).

Starting October 3, 2022, the access to the latest versions of the "ready to use" L1 data has been migrated to GEUS, (doi:10.22008/FK2/VVXGUT). Future versions will be available from GEUS, while the initial version of L1 data has been archived.

en: 22-Petermann ELA

en: GC Net Config for Stations

media_type: application/json

en: Stations Config from the static bucket

format: JSON

en: Archived GC-Net Data (deprecated)

en:
The GC-Net is kindly continued by the Geological Survey of Denmark and Greenland (GEUS).

Starting October 3, 2022, the access to the latest versions of the "ready to use" L1 data has been migrated to GEUS, (doi:10.22008/FK2/VVXGUT). Future versions will be available from GEUS, while the initial versions of L0 and L1 data have been archived.

en: GC Net Chart Parameters

en: Stations parameters from static bucket

en:
In Memory of Dr. Konrad (Koni) Steffen

Update October 2022: The GC-Net is kindly continued by the Geological Survey of Denmark and Greenland (GEUS).
Starting October 3, 2022, the access to the latest versions of the "ready to use" L1 data has been migrated to GEUS. Future data versions will be available at: [https://doi.org/10.22008/FK2/VVXGUT](https://doi.org/10.22008/FK2/VVXGUT)
 Background
Starting with a single station in 1991, the Greenland Climate Network (commonly known as GC-Net) is a set of Automatic Weather Stations (AWS) set up and managed by the late Prof. Dr. Konrad (Koni) Steffen, and spanning the Greenland Ice Sheet (GrIS). This first station was "Swiss Camp" or the "ETH-CU" camp (GC-Net station 01) which was used as a field science and education site by Koni for years. The GC-Net was expanded with multiple NASA, NOAA, and NSF grants throughout the years, and then supported by WSL in the later years. These data (see "C-file" below) were previously hosted by the Cooperative Institute for Research in Environmental Sciences (CIRES) in Boulder, Colorado.

 Overview
Provided in this dataset are the 16 longest running stations in the network, which are spread over a significant area of the GrIS and the majority of the unique climatic zones. From the South Dome high point in the South, to the Western Jakobshavn ablation region in the west, to the Petermann glacier in the North across east of the Northeast Greenland Ice Stream to the east, GC-Net is the longest running climatological record of Greenland.

 The standard GC-Net station consists of:
* Air temperature measurements at 2 heights above the surface
* Temperature and humidity measurements at 2 heights above the surface
* Wind speed and direction measured at 2 heights above the surface
* Sonic distance sounder measurements for 2 snow height and distance of instruments to surface
* Incoming shortwave radiation measurement
* Reflected shortwave radiation measurement
* Net broadband radiation (long- and short-wave) measurement
* Air pressure measurement
Data have often been repatriated in near-real time using one of either the GOES geostationary satellite or the ARGOS polar orbiting satellite transmission system. The stations were visited typically every 1-2 years for maintenance and service, and to download full uncorrupted data directly from the dataloggers. GC-Net stations were visited by Twin Otter equipped with snow skids to land directly on the open-ice at the AWS locations, or by helicopter near the west coast. The AWSs operate on solar and battery power and occasionally lost power during the dark and cold winter months, particularly when the batteries were aging.

 Dataset
This dataset consists of 2 main data levels; Level 0 and Level 1.
Level 0 is the raw data from the dataloggers, historical processing codes, satellite transmissions, and Koni’s personal data archive. Level 0 data (.zip) directories contain subdirectories:
* “C file” - contains the historical processed datafile for each station.
* “Campbell logger files” - contains the raw csv datafiles from the stations’ Campbell Scientific dataloggers since the CR1000 era (~2007-2008 for most stations).
* “Photos” - contains photographs of the station when available marked by year.
Level 1 is the appended, calibrated, cleaned, and quality flagged data. The full processing scheme is open-source and publicly available on the following GitHub repository (please also check GitHub for the latest L1 data):
[GC-Net L1 data on GitHub](https://github.com/GEUS-Glaciology-and-Climate/GC-Net-level-1-data-processing "GC-Net-level-1-data-processing")
Level 1 data is provided in the newly described csv-compatible [NEAD format](https://www.envidat.ch/#/metadata/nead "NEAD format").

 Additional Details
Dataset description publication will be forthcoming.
The Geological Survey of Denmark and Greenland (GEUS) has been imperative in the reprocessing and continuity mission of GC-Net. Multiple GC-Net stations have been replaced with updated and upgraded AWS hardware at the same coordinates by GEUS. This effort will ensure continuity of the GC-Net dataset into the future.

air-temperature

display_name: air-temperature

automatic-weather-station

display_name: automatic-weather-station

aws

display_name: aws

climate

display_name: climate

greenland

display_name: greenland

net-radiation

display_name: net-radiation

en: Greenland Climate Network (GC-Net) Data


en: genetic-structure reproductive-matieral molecular-markers pinus-cembra afforestation

en: metadata and description of dataset

en: The dataset contains individual genotypes at 11 nuclear microsatellite markers of samples of Swiss stone pine (*Pinus cembra*). Samples were collected in 12 natural and presumably planted stands in the canton of Fribourg (Switzerland). The dataset is complemented by individual genotypes (same markers) from samples of a subset of 40 populations across the European Alps (taken from Gugerli et al., Journal of Biogeography 2023; https://doi.org/10.1111/jbi.14586; dataset archived at Dryad, https://doi.org/10.5061/dryad.866t1g1v6).

afforestation

display_name: afforestation

genetic-structure

display_name: genetic-structure

molecular-markers

display_name: molecular-markers

pinus-cembra

display_name: pinus-cembra

reproductive-matieral

display_name: reproductive-matieral

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: Nuclear microsatellite genotypes of Pinus cembra


en: forest-inventory terrestiral-laserscanning tree-volume biomass lidar single-tree

en: Individual tree parameters and volume estimates based on TLS point clouds and allometric models

en:
"ASM" denotes volume estimates calculated by allometric scaling models (as used in Swiss NFI), based on tree height, DBH and D7.
"QSM" denotes volume estimates derived from TLS point clouds by quantitative structure models (QSM).
The remaining variables are geometrical features directly calculated from single tree TLS point clouds.
For more detailed variable descriptions see related publication.

en:
 Dataset
This dataset is based on terrestrial laser scanning (TLS) data acquired during winter 2020/2021 in leaf-off conditions, with a Leica BLK 360 instrument following a tree-centric scanning pattern.
The data was acquired on two sites (47.42°N 8.49°E and 47.504°N, 7.78°E), both of which were managed mixed temperate forest stands.
Individual trees were semi-automatically segmented from the co-registered TLS point clouds.

 Background
Accurate estimates of individual tree volume or biomass within forest inventories are essential for calibration and validation of biomass mapping products based on Earth observation data.
Terrestrial laser scanning (TLS) enables detailed and non-destructive volume estimation of individual trees, with existing approaches ranging from simple geometrical features to virtual 3D reconstruction of entire trees. Validating such approaches with weight measurements is a key step before the integration of TLS or other close-range technologies into operational applications such as forest inventories.
In this study, we firstly evaluate individual tree volume estimation approaches based on 3D reconstruction through quantitative structure models (QSM) against destructive reference data of 60 trees and compare them to operational allometric scaling models (ASM).
Secondly, we determine the explanatory power of TLS-derived geometric parameters regarding total tree, stem, coarse wood and fine branch volume.

biomass

display_name: biomass

forest-inventory

display_name: forest-inventory

lidar

display_name: lidar

single-tree

display_name: single-tree

terrestiral-laserscanning

display_name: terrestiral-laserscanning

tree-volume

display_name: tree-volume

educ

en: Education, culture and sport

en: EnviDat: the Environmental Data Portal

en: Individual tree TLS point clouds for tree volume estimation


en: cavity-nesting urban-ecology bees food-webs trap-nest hymenoptera management-intensity wasps urban-ecosystems urbanization zurich host-enemy-interactions

en: Script for the analyses v2.0

en: Cleaned script to reproduce the analyses

en: Script for the analyses v1.0

en: Thesaurus

en: Variable names and their description.

en: Raw data nests

en: Host-enemy interaction data, used to compute the interaction diversity metrics

en: Not used: raw questionnaires

en: Data of the study

en: The csv. file contains the response variable "interaction diversity" (idiv), and the values of the predictors used in the paper. The "id" column indicates the garden ID, each row in the dataset correspond to a garden and each column to the response (idiv), an explanatory variable or a descriptor (name, Lat, Long). See the thesaurus and the readme file for extended information on the variables.

en: Questionnaires management intensity anonymised

en: Results from the management intensity questionnaires anonymised. IDs are randomized and don't match those in the study data csv

en: Not used: data of the study

en: Not used: readme

en: Read me file

en:
The data supports the paper "Local and landscape factors shape alpha and beta trophic interaction diversity in urban gardens". It provides:
(1) the host-natural enemy interaction networks and network metrics between cavity-nesting bees and wasps and their natural enemies,
 (2) the explanatory variables reflecting urban intensity, temperature, habitat amount and management intensity.
(3) the questionnaires for assessing management intensity.
(4) a thesaurus for the variable names.
(5) a readme file.
(6) the R script used for the analyses.
The data is part of the BetterGardens project. It was sampled in 85 allotment and home gardens in the ctiy of Zurich in 2015 using standardized trapnests.

bees

display_name: bees

cavity-nesting

display_name: cavity-nesting

food-webs

display_name: food-webs

host-enemy-interactions

display_name: host-enemy-interactions

hymenoptera

display_name: hymenoptera

management-intensity

display_name: management-intensity

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wasps

display_name: wasps

zurich

display_name: zurich

en: Data on interaction diversity in urban gardens


maintainer: Rebecca Mott

en: snow-patch dischmex eddy-covariance-measurements turbulent-sensible-heat-fluxes patchy-snow-covers

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.6 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (DA-600, Kaijo-Denki) in 0.3 m on a daily basis.

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific Inc.) in 1.7 m on a daily basis.

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.2 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 0.7 m.

en: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific Inc.) in 3.2 m on a daily basis.

en: Output explanation

en: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 3.3 m.

en: Gletschboden setup

media_type: image/png

en: Background map based on data © 2014/2016 swisstopo (JD100042)

format: PNG

mimetype: image/png

en: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 3.5 m.

en:
This dataset contains eddy-covariance measurements in the ablation period of 2014-2016. Measurements were taken from two turbulence towers over a long-lasting snow patch, which are 5 m apart from each other (2014 and 2015). The turbulence towers were equipped with two YOUNG ultrasonic anemometers mounted 0.7 m (in 2014) and 3.3 m (in 2015) above snow-free ground, two ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) mounted at 2.6 m (in 2014) and 2.2 m (in 2015) above snow-free ground and one anemometer (DA-600, Kaijo Denki) mounted at 0.3 m above snow surface.

The measurement setup changed in 2016 and includes a measurement above the snow-free ground in upwind direction (Swiss coordinates: 790191/176689). The measurement tower is equipped with one ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 3.3 m above the snow-free ground. Additionally, one measurement tower is installed above the long-Lasting snow patch and equipped with the same setup as 2015.

Turbulence data were sampled at a frequency of 20 Hz. The processing of the data to quality controlled fluxes has been done with the Biomicrometeorology flux software (Thomas et al., 2009). The program applies plausibility tests and a despiking test after Vickers and Mahrt (1997) on the measured data. The routine further applies a time-lag correction and considers the deployment (e.g. the sonic azimuth). A frequency response correction (Moore, 1986) is done and a three-dimensional rotation is performed. Finally, quality assurance/quality control (QA/QC) flags after Foken et al., (2004) are issued and fast Fourier transform power and co-spectra are calculated. The change in snow height is considered in the post-processing for every measurement day. The turbulence data were averaged to 30 minute intervals.

dischmex

display_name: dischmex

eddy-covariance-measurements

display_name: eddy-covariance-measurements

patchy-snow-covers

display_name: patchy-snow-covers

snow-patch

display_name: snow-patch

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

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: DISCHMEX - Impact of extreme land-surface heterogeneity on micrometeorology over spring snow-cover


maintainer: Ionut Iosifescu Enescu

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

en: Open Science Support @ WSL (Poster)

en:
This poster was originally created for the swissuniversities Open Science Action Plan: Kick-Off Forum, and showed to the audience on 17.10.2019. It illustrates how the environmental data portal EnviDat provides the tools for fostering Open Science and Reproducibility of scientific research at WSL.

Supporting open science is a highly relevant user requirement for EnviDat and for implementing FAIR (Findability, Accessibility, Interoperability and Reusability) principles at dataset level.
EnviDat encourages WSL scientists to complement data publication with a complete description of research methods and the inclusion of the open source software, code or scripts used for processing the dataset or for obtaining the published results. By openly publishing open software (e.g. as Jupyter notebooks) alongside research data sets, researchers can contribute to mitigate reproducibility issues.

EnviDat also promotes and supports, where possible and practical, the publication of software as Jupyter notebooks. Jupyter notebooks provide a solution for improved documentation and interactive execution of open code in a wide range of programming languages (Python, R, Octave/Matlab, Java or Scala). These programming languages are widely used in environmental research at WSL and well supported by the Jupyter-compatible kernels. We have sucessfully interfaced EnviDat-hosted notebooks with the WSL High-Performance Computing (HPC) Linux Cluster through a JupyterHub/JuypterLab beta installation on the HPC cluster implemented in close collaboration with the WSL IT-Services.
For existing software that cannot be easily migrated to Jupyter Notebooks, the Open Science and Reproducibility is assisted by containerisation. We have proven that several Singularity containers can successfully run on WSL's HPC cluster.

Finally, the researchers can upload the data/results complemented by code (e.g. as Jupyter Notebooks, or Singularity containers) and any additional documentation in EnviDat. Consequently, they will receive a DOI for the entire dataset, which they can reference in their science paper in order to publish a more reproducible research.

_License_: This poster is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse this poster in any way you want, for any purposes and without restrictions.

hpc

display_name: hpc

jupyter-notebooks

display_name: jupyter-notebooks

open-data

display_name: open-data

open-science

display_name: open-science

open-source

display_name: open-source

reproducibility

display_name: reproducibility

research-data-management

display_name: research-data-management

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


en: conservation glaciers permafrost active-layer biobank swiss-alps extreme-habitat bacteria arctic plastisphere biodiversity collections fungi

en: Complete collection of bacterial and fungal isolates from Permafrost, active layer and glaciers in Switzerland, Svalbard, northern Greenland and Russia.

en:
The cold habitats of the Swiss Alps and the Arctic are undergoing change and are at risk of disappearing completely or partially in the future. Along with them, a poorly known diversity of microorganisms that have adapted to life in these supposedly hostile places. By cryopreserving microorganisms from these habitats, some of today's biodiversity can be preserved in biobanks.
The collection contains cryopreserved bacteria and fungi isolated from permafrost and active layer of Muot da Barba Peider and Val Lavirun, from the glacier forefield and glacier toe of the Damma glacier, from active layer in northern Greenland and from plastic waste in Svalbard, as well as isolates from plastic incubations in Muot da Barba Peider, northern Greenland and arctic Russian soils.
Project overview: https://www.wsl.ch/en/projects/life-at-chilly-temperatures-a-collection-of-microorganisms-from-extreme-habitats/

active-layer

display_name: active-layer

arctic

display_name: arctic

bacteria

display_name: bacteria

biobank

display_name: biobank

biodiversity

display_name: biodiversity

collections

display_name: collections

conservation

display_name: conservation

extreme-habitat

display_name: extreme-habitat

fungi

display_name: fungi

glaciers

display_name: glaciers

permafrost

display_name: permafrost

plastisphere

display_name: plastisphere

swiss-alps

display_name: swiss-alps

en: Life at chilly temperatures - A collection of microorganisms from extreme habitats


en: land-use-change urban-transformations large-scale-urban-development-projects strategic-spatial-planning spatial-planning land-use-transformations strategic-projects europe

en: QCA data set large-scale urban development projects

en: Please refer to the sections: 3. The data set lsUDPs: 3.1 Selection of cases and data collection; 3.2 Data management and operationalization in the Metadata for further details on this resource.

en: QCA R script large-scale urban development projects Europe

en:
For the set up of this R script, we used the “QCA” (Duşa, 2019) and “SetMethods” (Oana and Schneider, 2018) R packages.

The following further resources were also used:
Dusa, A. (2019). QCA with R: A comprehensive resource. Springer: Berlin.
Schneider, C. Q., & Wagemann, C. (2012). Set-theoretic methods for the social sciences. A guide to qualitative comparative analysis. Cambridge: Cambridge University Press.
Thomann, E., Oana, I.-E., & Wittwer, S. (2018). Performing fuzzy- and crisp set QCA with R. A user-oriented beginner's guide. Retrieved from http://www.evathomann.com/links/qca-r-manual

en:
Table of Content: 1. General context of the data set "lsUDPs" ; 2. Background and aims of the study using the data set lsUDPs; 3. The data set lsUDPs: 3.1 Selection of cases and data collection; 3.2 Data management and operationalisation

1. General context of the data set "lsUDPs"
The data set "lsUDPs" has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2020. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, strategic spatial plans) into quantitative land-change modelling approaches at the urban regional level. The first stage (2016-2017) of the CONCUR project focussed on 21 urban regions in Western Europe. The urban regions were selected through a multi-stage strategy for empirical research (see Hersperger, A. M., Grădinaru, S., Oliveira, E., Pagliarin, S., & Palka, G. (2019). Understanding strategic spatial planning to effectively guide development of urban regions. Cities, 94, 96–105. https://doi.org/10.1016/j.cities.2019.05.032 ).

2. Background and aims of the study using the data set lsUDPs
As part of the CONCUR project, a specific task was to examine the relationship between strategic spatial plans and the formulation and implementation (i.e. urban land change) of large-scale urban development projects in Western Europe.
Strategic urban projects are typically large-scale, prominent urban transformations implemented locally with the aim to stimulate urban growth, for instance in the form of urban renewals of deprived neighborhoods, waterfront renewals and transport infrastructures. While strategic urban projects are referred to in the literature with multiple terms, in the CONCOR project we call them large-scale urban development projects (lsUDPs).
Previous studies acknowledged both local and supra-local (or structural) factors impacting the context-specific implementation of lsUDPs. Local governance factors, such as institutional capacity, coordination among public and private actors and political leadership, intertwine with supra-local conditions, such as state re-scaling processes and devolution of state competencies in spatial planning, de-industrialisation and increasing social inequality. Hence, in implementing lsUDPs, multi-scalar factors act in combination.
Because the formulation and implementation of lsUDPs require multi-scalar coordination among coalitions of public and private actors over an extended period of time, they are generally linked to strategic spatial plans (SSPs). Strategic spatial plans convey collective visions and horizons of action negotiated among public and private actors at the local and/or regional level to steer future urban development, and can contain legally binding dispositions, but also indicative guidelines.
The key question remains as to what extent large-scale urban development projects and strategic spatial plans can be regarded as aligned. By alignment, or “concordance”, we mean that strategic projects are formulated and implemented as part of the strategic planning process (“high concordance”), or that the strategic role of projects is reconfirmed in (subsequent) strategic plans (“moderate concordance”). Lack of concordance is found when lsUDPs have been limitedly (or not at all) acknowledged in strategic spatial plans.
We assume that certain local and supra-local factors, characterising the development of the projects, foster (but not strictly “cause”) the degree of alignment between lsUPDs and SSPs. In this study, we empirically examine how, and to what extent, the concordance between 38 European large-scale urban development projects and strategic plans (outcome: CONCOR) has been enabled by five multi-scalar factors (or conditions): (i) the role of the national state (STATE), (ii) the role of (inter)national private actors (PRIVATE), (iii) the occurrence of supra-regional external events (EVENTS), (iv) the degree of transport connectivity (TRANSP), and (v) local resistance from civil society (RESIST). We adopted a (multi-data) case-based qualitative strategy for empirical research and applied the formalised procedure of within- and cross-case comparison offered by fuzzy-set Qualitative Comparative Analysis appropriate for the goal of this study. Based on set theory, QCA formally integrates contextual sensitivity to case specificities (within-case knowledge) with systematic comparative analysis (across-case knowledge).
The research question the data set has been created to reply to is the following: which conditions, and combinations of conditions, enable the concordance between large-scale urban development projects and strategic spatial plans?
The conditions (“independent variables”) considered are. STATE: the set of large-scale urban projects characterized by a high degree of state intervention and support in their formulation and implementation, PRIVATE: the set of large-scale urban projects characterized by a high degree of involvement of (inter)national private actors in their formulation and implementation, EVENTS: the set of large-scale strategic projects whose formulation and implementation have been strongly affected by unforeseen international events and/or global trends, TRANSP: the set of large-scale strategic projects with a high degree of road and/or transit connectivity, and RESIST: set of large-scale strategic projects whose realization has been characterized by resistances that have substantially delayed or modified the project implementation.
The outcome (“dependent variable”) under analysis is CONCOR: the set of large-scale urban projects having a high degree of concordance/alignment/integration with strategic spatial plans

3. The data set lsUDPs

   3.1 Selection of cases and data collection
To generate the current data set on large-scale urban development projects in European urban regions (data set "lsUDPs"), we identified 35 large-scale urban development projects in a sample of the 21 Western urban regions considered in the CONCUR project (see supra, Hersperger et al. 2019): Amsterdam, Barcelona, Copenhagen, Hamburg, Lyon, Manchester, Milan, Stockholm, Stuttgart. The criteria we followed to identify the 35 large-scale urban development projects are: geographical location, size (large-scale), site (located either in the city core or in the larger urban region) and urban function (e.g. housing, transportation infrastructures, service and knowledge economic functions). Employing these criteria facilitated the selection of diverse large-scale urban development projects while still ensuring sufficient comparability.
In 2016, we performed 47 in-depth interviews with experts in urban and regional planning and large-scale strategic projects and infrastructure (i.e. academics and practitioners) about the formulation, implementation and development (1990s–2010s) of each project in each of the 9 selected urban regions. On average, each interviewee answered questions on 3.1 large-scale urban development projects. Three cases were subdivided into two cases because a clear differentiation between specific implementation stages was identified by the interviewees (expansion of the Barcelona airport, cases “bcn_airport80-90” and “bcn_airport00-16”; realisation of Lyon Part-Dieu, cases “lyo_partdieu70-90” and “lyo_partdieu00-16”; MediaCityUK, cases “man_salfordquays80-00” and “man_mediacityuk00-16”). Therefore, from the initial 35 cases, the final number of analysed cases in the lsUDPs dataset is 38.

    3.2 The data set lsUDPs: Data management and operationalisation
Interviews were fully transcribed and analysed through MAXQDA (version 12.3, VERBI GmbH, Berlin, Germany), and intercoder agreement was evaluated on a sample of nine interviews. We also compiled “synthetic case descriptions” (SCD) for each case (totalling more than 160 SCDs) to spot potential inconsistencies among interviewees’ accounts and to facilitate completion of the “calibration table” for each case (see below). An online expert survey distributed to the interviewees (response rate 78%) helped systematise the information collected during the interviews. We also consulted both academic and gray literature on the case studies to check for possible ambiguity and inconsistencies in the interview data, and to solve discrepancies between our assigned set membership scores and questionnaire values. Site visits were also carried out to retrieve additional information on the selected cases.
For each case (i.e. each of the 38 selected large-scale urban development projects), we operationalised each condition (i.e. STATE, PRIVATE, EVENTS, TRANSP, RESIST) and the outcome (CONCOR) in terms of sets, for subsequent application of Qualitative Comparative Analysis. This process is called “calibration”; we used a number of indicators for each condition to qualitatively assess each large-scale project across the conditions. The case-based qualitative assessment was then transformed into fuzzy-set membership values. Fuzzy-set membership values range from 0 to 1, and should be conceived as “fundamentally interpretative tools” that “operationalize theoretical concepts in a way that enhances the dialogue between ideas and evidence” (Ragin 2000:162, in “Fuzzy-set Social Science”. Chicago: University Press). We employed a four-value fuzzy-set scale (0, 0.33, 0.67, 1) to “quantify” into set membership scores the individual histories of cases retrieved from interview data. Only the condition TRANSP was calibrated as a crisp-set (0, 1).
The translation of qualitative case-based information into numerical fuzzy-set membership values was iteratively performed by populating a calibration table following standard practices recently emerged in QCA when dealing with qualitative (interview) data.

europe

display_name: europe

land-use-change

display_name: land-use-change

land-use-transformations

display_name: land-use-transformations

large-scale-urban-development-projects

display_name: large-scale-urban-development-projects

spatial-planning

display_name: spatial-planning

strategic-projects

display_name: strategic-projects

strategic-spatial-planning

display_name: strategic-spatial-planning

urban-transformations

display_name: urban-transformations

en: lsUDPS Large-scale urban development projects in European urban regions


en: snow-water-equivalent snow-profile gcos snow-height snow

en: STATION METADATA

en: DATA ACCESS

en:
This dataset contains long-term snow water equivalent and corresponding snow depth data 11 observer sites in Switzerland between 1200 and 2500 m a.s.l. compiled for the Global Climate Observing System (GCOS) and supported by MeteoSwiss. Snow depth (cm) and snow water equivalent (mm) are manually recorded every 2 weeks since the 1947 (depending on station). The attached metadata file gives details for each station.
The measurement series agree with GCOS objectives according to the GCOS Implementation Plan: This inlcudes:
• Raw data are archived in the snow and avalanche database at SLF.
• Measuring techniques are traceable and documented as snow depth and snow water equivalent have in general remained the same since beginning up to now. When planning new systems or changes of existing systems in the future, their impact will be assessed prior to implementation.
• Historical data of these 11 stations have been digitized and all data have been quality controlled.
• Detailed metadata (location of measurements) are available.
• Data gaps for the two most important winter and spring dates were reconstructed based on a published SWE parameterization from co-located snow depth measurements.
• Public availability of the data has been ensured by publishing the data on the Envidat portal (https://www.envidat.ch/dataset/gcos-swe-data).

gcos

display_name: gcos

snow

display_name: snow

snow-height

display_name: snow-height

snow-profile

display_name: snow-profile

snow-water-equivalent

display_name: snow-water-equivalent

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: GCOS SWE data from 11 stations in Switzerland


bryophytes-of-europe-traits-bet-dataset

title_for_slug: bryophytes-of-europe-traits-bet-dataset

en: red-list bioclimatic-variables life-history-traits liverworts iucn hornworts indicator-values mosses

en: PDF including the (trait) explanations.

en: Text file including the BET dataset.

en: Excel file including the BET dataset and (trait) explanations.

en: The Bryophytes of Europe Traits (BET) dataset includes values for 65 biological and ecological traits and 25 bioclimatic variables for all 1816 bryophytes included in the European Red List (Hodgetts et al. 2019). The traits are compiled from several regional trait datasets and manually complemented using Floras, species-specific literature and expert knowledge. The bioclimatic variables are calculated using the European range of each species. Details regarding the trait compilation and extraction of bioclimatic variables can be found in the corresponding data paper (Van Zuijlen et al. 2023).

bioclimatic-variables

display_name: bioclimatic-variables

hornworts

display_name: hornworts

indicator-values

display_name: indicator-values

iucn

display_name: iucn

life-history-traits

display_name: life-history-traits

liverworts

display_name: liverworts

mosses

display_name: mosses

red-list

display_name: red-list


en: forest-fire bark-beetles extreme-events compound-events natural-hazards protection-forest protective-effect drought

en: Factsheet summarising the key results of the study (in German).

en: Factsheet summarising the key results of the study (in French).

en: Description of the study site, extreme event (trigger event) and informations about the survey.

en: Factsheet summarising the key results of the study (in Italian).

en:
This file contains the anonymous answers to the survey for the case study in the protective forest, Val Mesolcina, GR, Switzerland within the BAFU Project "Wenn Risiken kumulieren - Analyse und Umgang mit unerwarteten Ereignissen und kombinierten Risiken".
The survey consists of two parts, based on different concepts: "top-down" and "bottom-up". Answers for both concepts are available in two different worksheets within the Excel file.

en: Factsheet summarising the methods used in this project (in German).

en: Conclusions and recommendations of the project (in German).

en: Case study website

en: Page of the case study on the project website. It includes figures fo all questions of the survey and additional synthesis graphs.

en:
This dataset contains the results of a case study analysing the potential impacts of a compound meteorological extreme event on the protective forest in the Val Mesolcina. These impacts were assessed in an experts survey. 29 Experts from practice, administration and science estimated the probabilities for a loss of the protective function due to a drought-related compound extreme event based on different hazard scenarios. The experts not only assessed these probabilities but also provided estimates about the reliability of the scenarios, other socio-economic consequences and options for adaptation.
This dataset contains the following information:
- Table with all (anonymised) answers from the survey
- Factsheets summarising the results and methods in German, French and Italian
- A detailed description of the study site and survey instructions
- Link to the project website wit illustrations for each individual question of the survey

bark-beetles

display_name: bark-beetles

compound-events

display_name: compound-events

drought

display_name: drought

extreme-events

display_name: extreme-events

forest-fire

display_name: forest-fire

natural-hazards

display_name: natural-hazards

protection-forest

display_name: protection-forest

protective-effect

display_name: protective-effect

en: Experts survey protective forest and combined extremes in Val Mesolcina