rinder-anzahl-abkalbungen-von-kuhen

title_for_slug: rinder-anzahl-abkalbungen-von-kuhen

fr: bovins velage animaux-de-rente age

de: rinder alter abkalbung nutztiere

en: age livestock cattle calving

it: parto bovini animale-da-reddito eta

identifier: cattle-calvingNumbers

fr: Répartition du nombre de vêlage par an de l'abattage et par type de race de la vache (races laitières ou races à viande). Ce nombre est représenté dans la fourchette 1-20 vêlages sous la forme d'un boxplot. Le nombre d'observations par catégorie et par année se trouve dans le .csv.

de: Verteilung der Anzahl Abkalbungen von Kühen nach Jahr der Schlachtung und Rassentyp (Milchrassen oder Fleischrassen). Die Anzahl wird im Bereich von 1-20 in Form eines Boxplots wiedergegeben. Die Anzahl Beobachtungen pro Rassentyp und Jahr findet sich im .csv.

en: Distribution of the number of calvings by year of slaughter and by breed type of the cow (dairy breeds or beef breeds). The number is shown in the range of 1-20 in the form of a boxplot. The number of observations per year and by breed type can be found in the .csv.

it: Ripartizione dei numero di parti delle vacche per anno della macellazione e per tipo di razza (razze da latte o razze di carne). Questo numero è rappresentato nell'intervallo 1-20 parti come un boxplot. Il numero di osservazioni per tipo di razza e anno si trova nel file .csv.

abkalbung

display_name: abkalbung

age

display_name: age

alter

display_name: alter

bovini

display_name: bovini

bovins

display_name: bovins

calving

display_name: calving

cattle

display_name: cattle

eta

display_name: eta

nutztiere

display_name: nutztiere

parto

display_name: parto

rinder

display_name: rinder

velage

display_name: velage

identitas

de: Identitas AG

en: Identitas AG

fr: Identitas AG développe et exploite des applications pour l'identification, l'enregistrement et la surveillance des animaux de rente et de compagnie. En tant que prestataire leader de services IT en Suisse pour les données en rapport avec les animaux et la production végétale, nous contribuons à la création de valeur ajoutée pour la santé et le bien-être animale et pour la sécurité des denrées alimentaires. A notre siège à Berne, nous employons environ 110 collaborateurs.

de: Identitas AG entwickelt und betreibt Applikationen zur Identifizierung, Registrierung und zum Monitoring von Nutz- und Heimtieren. Als führender Schweizer IT-Dienstleister für Daten rund um das Tier und den Pflanzenbau schaffen wir Mehrwert für gesunde Tiere und sichere Lebensmittel. An unserem Sitz in Bern beschäftigen wir rund 110 Mitarbeitende.

fr: Bovins - Nombre de velâge des vaches

en: Cattle - Number of calvings per cow

de: Rinder - Anzahl Abkalbungen von Kühen

it: Bovini - Numero di parti delle vacche


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: naturwaldreservate sonderwaldreservate nutzungsverzicht langfristiger-schutz mcpfe walddynamik

label: geocat.ch permalink

state: active

type: dataset

fr: WFS für Open-Government-Data des Kantons Zürich (OGD ZH WFS)

format: WFS

fr: Naturwaldreservate im Kanton Zürich sind durch Verträge langjährig gesicherte Waldflächen, in denen weitestgehend auf Pflegeeingriffe verzichtet wird (Typ MCPFE1_2), um sie den natürlichen Alterungs- und Zerfallsprozessen zu überlassen. Dadurch erhöht sich der Alt- und Totholzanteil und die Strukturvielfalt, welche spezialisierten Tier- und Pflanzenarten Lebensraum bietet. Sonderwaldreservate (Typ: MCPFE1_3) lassen gezielte Eingriffe zur Biodiversitätsförderung zu. Sie sind entweder langjährig vertraglich gesichert oder als Waldteile mit Reservatscharakter durch überkommunale Schutzanordnungen geschützt.

spatial: Kanton Zürich

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

fr:
Le département de géomatique est le centre de compétence du system d'information géographique du canton de Zurich.
Nous coordinons l'aquisition des géodonnées d'intérêt commun sur le territoire cantonal et les mettons à disposition des
secteurs public et privé et des particuliers.

en:
The department of geoinformation is the geospatial competency center of the Canton of Zurich.
We coordinate the acquisition of geodata within the cantonal territory and provide public, private, and government sectors with data of outstanding quality.

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

it: La divisione della geoinformazione è il centro d'eccellenza del Cantone di Zurigo per dati georeferenziati. Mettiamo a disposizione dati geografici e informazioni di alta qualità per l'economia, la società e la pubblica amministrazione su tutto il cantone.

political_level: canton

kanton-zuerich

capacity: public

type: organization

approval_status: approved

value: ZH - Geocat Harvester

fr: Waldreservate - Geolion Eintrag in Bearbeitung


maintainer: Bundesamt für Energie BFE

title_for_slug: Schweizerische Elektrizitätsstatistik: Schweizerische Elektrizitätsbilanz - Monatswerte

fr: ogd35-bfe electricite production importation exportation consommation

de: ogd35-bfe elektrizitat produktion import export verbrauch

en: ogd35-bfe electricity production import export

it: ogd35-bfe elettricita produzione importazione esportazione consumo

fr: Statistique suisse de l'électricité: bilan mensuel suisse de l'électricité

it: Statistica svizzera dell'elettricità: bilancio svizzero dell'elettricità - valori mensili

author: Bundesamt für Energie BFE

format: SERVICE

format: CSV

fr: Cette statistique recense sur une base mensuelle la production, l'importation, l'exportation et la consommation d'électricité en Suisse. Elle présente la production des centrales hydrauliques, des centrales nucléaires, des centrales thermiques classiques et renouvelables. Elle indique la consommation des installations de pompage d'accumulation et les pertes en ligne. Elle est établie dans le cadre de la Statistique de l'électricité, qui fait partie de la statistique publique de la Suisse (base légale: LSF).

de: Die Schweizerische Elektrizitätsbilanz - Monatswerte gibt Auskunft über Produktion, Import / Export und Verbrauch von Elektrizität in der Schweiz auf monatlicher Basis. Bei der Produktion werden Wasserkraftwerke, Kernkraftwerke, konventionell-thermische und erneuerbare Kraftwerke unterschieden. Der Verbrauch der Speicherpumpen und die Leitungsverluste werden ausgewiesen. Die monatliche Elektrizitätsbilanz wird im Rahmen der Elektrizitätsstatistik erstellt, welche Teil der öffentlichen Statistik der Schweiz ist (gesetzliche Grundlage: BStatG).

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).

political_level: confederation


label: Fixpunkte der Amtlichen Vermessung

fr: Service WMS-IFDG, couche "Points fixes altimétriques PFA1"

de: WMS-BGDI Dienst, Layer "Höhenfixpunkte HFP1"

en: WMS-FSDI service, layer "Height control points HFP1"

it: Servizio WMS-IFDG, strato "Punti fissi altimetrici PFA1"

format: WMS

fr: RESTful API de geo.admin.ch

de: RESTful API von geo.admin.ch

en: RESTful API from geo.admin.ch

it: RESTful API da geo.admin.ch

format: API

fr: Download de data/geo.admin.ch

de: Download von data/geo.admin.ch

en: Download from data/geo.admin.ch

it: Download da data/geo.admin.ch

format: HTML

fr: Les points de mensuration constituent la base de toutes les données à référence spatiale. L’utilisation des points dits fixes est recommandée pour tous les travaux techniques nécessitant des mesures fiables et précises d’ouvrages. Par point fixe altimétrique, on entend un point matérialisé de façon durable à l'aide d'une cheville dont l'altitude est connue. La mensuration nationale (swisstopo) est responsable des points fixes altimétriques de première catégorie (PFA1). Ces derniers composent le cadre de référence altimétrique de tous les travaux de mensuration effectués en Suisse. L'altitude usuelle NF02 des PFA1 a été déterminée par nivellement de précision fédéral.

de: Vermessungspunkte bilden die Grundlage aller Daten mit Raumbezug. Die so genannten Fixpunkte werden für alle vermessungstechnischen Arbeiten genutzt, die eine zuverlässige und präzise Bestimmung erfordern. Unter einem Höhefixpunkt versteht man einen dauerhaft mit einem Bolzen gekennzeichneten Punkt mit bekannter Höhe. Die Landesvermessung (swisstopo) ist für die Höhefixpunkte der Kategorie 1 (HFP1) zuständig. Diese bilden den Höhenbezugsrahmen für sämtliche Vermessungsarbeiten in der Schweiz. Die Gebrauchshöhen LN02 der HFP1 wurden mittels einem eidgenössischen Präzisionsnivellement bestimmt.

en: All spatial data is based on measurement points. It is recommended to use the so-called fixed control points for all technical works which need reliable and accurate position measurements. A height fixed control point ("Höhefixpunkte" in german) is a surveyed point permanently marked with a bolt with known height. The Swiss national land survey is responsible for height fixed control points of the first class (HFP1). Those provide the reference framework for all survey work in Switzerland. HFP1 points usual elevation LN02 have been established by precise federal levelling.

it: I punti di misurazione costituiscono la base di tutti i dati a riferimento spaziale. L’utilizzo dei punti cosiddetti fissi è raccomandato per tutti i lavori tecnici che necessitano di misure affidabili e precise nelle zone considerate. Per punto fisso altimetrico s'intende un punto assicurato durevolmente con un bollone con altezza conosciuta. La misurazione nazionale (swisstopo) è responsabile dei punti fissi altimetrici di prima categoria (PFA1). Quest’ultimi compongono il quadro di riferimento altimetrico di tutti i lavori di misurazione effettuati in Svizzera. L’altitudine usuale NF02 dei PFA1 è stata determinata per livellamento di precisone federale.

spatial: Topografisches Landschaftsmodell

name: Bundesamt für Landestopografie swisstopo

fr: Office fédéral de topographie swisstopo

en: Federal Office of Topography swisstopo

it: Ufficio federale di topografia swisstopo

fr: Le centre de compétence de la Confédération suisse pour les informations géographiques, c'est-à-dire pour la description, la représentation et l’archivage de données à référence spatiale.

de: Das Kompetenzzentrum der Schweizerischen Eidgenossenschaft für Geoinformation, d.h. für die Beschreibung, Darstellung und Archivierung von raumbezogenen Geodaten.

en: The centre of competence for the Swiss Confederation responsible for geographical reference data, for instance the description, representation and archiving of geographic spatial data.

it: Il centro d’eccellenza della Confederazione Elvetica per geoinformazione, cioè per la descrizione, rappresentazione e archiviazione dei dati georeferenziati (geodati).

value: Swisstopo - Geocat Harvester

fr: Points fixes altimétriques (PFA1) (mensuration nationale)

de: Höhenfixpunkte HFP1 (Landesvermessung)

en: Height control points HFP1 (National Survey)

it: Punti fissi altimetrici PFA1 (misurazione nazionale)


regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

it: Ambiente

fr: Map (Preview) Aperçu map.geo.admin.ch

de: Map (Preview) Vorschau map.geo.admin.ch

en: Map (Preview)  map.geo.admin.ch

it: Map (Preview) Previsione map.geo.admin.ch

fr: Aperçu map.geo.admin.ch

de: Vorschau map.geo.admin.ch

en: Preview map.geo.admin.ch

it: Previsione map.geo.admin.ch

fr: Service WMS-IFDG, couche "Points fixes planimétriques PFP1"

de: WMS-BGDI Dienst, Layer "Lagefixpunkte LFP1"

en: WMS-FSDI service, layer "Planimetric control points LFP1"

it: Servizio WMS-IFDG, strato "Punti fissi planimetrici PFP1"

fr: Les points de mensuration constituent la base de toutes les données à référence spatiale. L’utilisation des points dits fixes est recommandée pour tous les travaux techniques nécessitant des mesures fiables et précises d’ouvrages. Par point fixe planimétrique, on entend un point matérialisé de façon durable à l'aide d'une borne ou d'une cheville (parfois située dans un regard) dont les coordonnées et éventuellement l'altitude sont connues. La mensuration nationale (swisstopo) est responsable des points fixes planimétriques de première catégorie. Il en existe plusieurs types: * Les points fixes planimétriques de la première catégorie (PFP1) composent le cadre de référence planimétrique de tous les travaux de mensuration effectués en Suisse. Les coordonnées MN03 des points fixes planimétriques historiques ont été déterminées par triangulation au début du 20ème siècle. * Les points d’appui pour la transformation (PAT1) sont des points fixes planimétriques dont les coordonnées ont été mesurées de façon précise dans les cadres de références MN03 et MN95. * Les points EUREF sont des points fixes planimétriques du réseau de référence GNSS européen EUREF (European Reference Frame). * Les points MN95 sont des points fixes planimétriques servant de base pour le nouveau cadre de référence MN95. Leurs coordonnées ont été mesurées de façon précise par GNSS. Puisqu'un point fixe peut être à la fois de plusieurs types, les symboles de la légende peuvent être superposés sur la carte.

de: Vermessungspunkte bilden die Grundlage aller Daten mit Raumbezug. Die so genannten Fixpunkte werden für alle vermessungstechnischen Arbeiten genutzt, die eine zuverlässige und präzise Bestimmung erfordern. Unter einem Lagefixpunkt versteht man einen dauerhaft mit einem Stein oder einem Bolzen (zum Teil unter Schacht) versicherten Punkt mit bekannten Koordinaten und eventuell bekannter Höhe. Die Landesvermessung (swisstopo) ist für die Lagefixpunkte der Kategorie 1 zuständig. Es gibt verschiedene Typen: * Die Lagefixpunkte der Kategorie 1 (LFP1) bilden den Lagebezugsrahmen für sämtliche Vermessungsarbeiten in der Schweiz. Die LV03-Koordinaten der historischen Lagefixpunkte wurden zu Beginn des 20. Jahrhunderts mittels Triangulation bestimmt. * Die Transformationsstützpunkte (TSP1) sind Lagefixpunkte, welche über präzise gemessene Koordinaten sowohl im Bezugsrahmen LV03 wie auch LV95 verfügen. * Die EUREF Punkte sind Lagefixpunkte des europäischen GNSS-Referenznetzes EUREF (European Reference Frame). * Die LV95 Punkte sind Lagefixpunkte, welche die Grundlage für den neuen Bezugsrahmen LV95 bilden. Die Koordinaten dieser Punkte wurden sehr präzise mittels GNSS bestimmt. Da ein Lagefixpunkt mehreren Typen zugeordnet werden kann, sind überlagernde Symbole auf der Karte möglich.

en: All spatial data is based on measurement points. It is recommended to use the so-called fixed control points for all technical works which need reliable and accurate position measurements. A planimetric fixed control point ("Lagefixpunkte" in german) is a surveyed point permanently marked with a stone monument or a bolt (sometimes covered by a manhole) with known coordinates and potentially height. The Swiss national land survey is responsible for the first category of planimetric fixed control points. There are several types of those: * Planimetric fixed points of the first categorie LFP1 provide the reference framework for all survey work in Switzerland. LV03 coordinates from historical fixed control points have been established by triangulation at the beginning of the 20th century. * TSP1 pass points (“Transformationsstützpunkte” in german) are very accurately measured surveying points in both reference frames LV03 and LV95, . * EUREF points are planimetric fixed points from the European GNSS reference network EUREF (European Reference Frame). * LV95 points are planimetric fixed points used as basis for the new reference frame LV95. Their coordinates have been with GNSS precisely measured. Since a planimetric fixed points can be simultaneously from different types, the symbols of this layer can be overlayed.

it: I punti di misurazione costituiscono la base di tutti i dati a riferimento spaziale. L’utilizzo dei punti cosiddetti fissi è raccomandato per tutti i lavori tecnici che necessitano di misure affidabili e precise nelle zone considerate. Per punto fisso planimetrico s'intende un punto assicurato durevolmente con un cippo o un bollone (talvolta sotto chiusino) con coordinate conosciute e eventualmente altezza conosciuta. I punti fissi planimetrici della prima categoria sono di responsabilità della confederazione (swisstopo). Ne esistono di diversi tipi: * I punti fissi della prima categoria (PFP1) costituiscono la base per tutti i lavori di misurazione in Svizzera. Le coordinate MN03 dei punti fissi planimetrici storici sono state determinate tramite triangolazione all’inizio del 20esimo secolo. * I punti d'appoggio per la trasformazione (PAT1) sono dei punti misurati in modo preciso nei quadri di riferimento MN03 e MN95. * I punti EUREF sono punti fissi planimetrici della rete di riferimento GNSS europea EUREF (European Reference Frame). * I punti MN95 sono dei punti fissi planimetrici che servono da base per il nuovo quadro di riferimento MN95. Le loro coordinate sono state misurate in maniera precisa secondo il metodo GNSS. Siccome a volte un punto fisso può essere di differenti tipi, i simboli della leggenda possono sovrapporsi sulla carta.

de: Bundesamt für Landestopografie swisstopo

fr: Points fixes planimétriques (PFP1) (mensuration nationale)

de: Lagefixpunkte LFP1 (Landesvermessung)

en: Planimetric control Points LFP1 (National Survey)

it: Punti fissi planimetrici PFP1 (misurazione nazionale)


wasserrechte

en: Environment

title_for_slug: wasserrechte

de: konzession wasserrecht entnahme ruckgabe kanal wasserrechtskanal stauwehr stauwehrreglement wasserrechtskonzession eheliche-konzession wasserrechtsbezirk wasserrechtsnummer

fr: WFS für Open-Government-Data des Kantons Zürich (OGD ZH WFS)

fr: Öffentliche Oberflächengewässer, Gewässerraum und Wasserrechte

fr: Die konzessionierten Wasserrechte wurden ab 1997 mit den öffentlichen Oberflächengewässern im GIS erfasst und werden seit 1998 als eigener Datensatz in Abstimmung zu den öffentlichen Oberflächengewässern vom AWEL, Abt. Wasserbau nachgeführt. Seit Januar 2022 werden aktive und gelöschte Wasserrechte in getrennten Datensätzen zu Verfügung gestellt. Die Daten sind auf dem SDE Server vom GIS-ZH abgelegt unter: GISZHPUB.WASSERRECHTE_F für die Wasserrechtsweiher (Flächendaten) GISZHPUB.WASSERRECHTE_GELOESCHT_F für die gelöschten Wasserrechtsweiher (Flächendaten) GISZHPUB.WASSERRECHTE_L für die Wasserrechtskanäle und Leitungen (Liniendaten) GISZHPUB.WASSERRECHTE_GELOESCHT_L für die gelöschten Wasserrechtskanäle und Leitungen (Liniendaten) GISZHPUB.WASSERRECHTE_P für die Entnahme- und Rückgabeorte (Punktdaten) GISZHPUB.WASSERRECHTE_GELOESCHT_P für die gelöschten Entnahme- und Rückgabeorte (Punktdaten)

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

fr:
Le département de géomatique est le centre de compétence du system d'information géographique du canton de Zurich.
Nous coordinons l'aquisition des géodonnées d'intérêt commun sur le territoire cantonal et les mettons à disposition des
secteurs public et privé et des particuliers.

en:
The department of geoinformation is the geospatial competency center of the Canton of Zurich.
We coordinate the acquisition of geodata within the cantonal territory and provide public, private, and government sectors with data of outstanding quality.

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

it: La divisione della geoinformazione è il centro d'eccellenza del Cantone di Zurigo per dati georeferenziati. Mettiamo a disposizione dati geografici e informazioni di alta qualità per l'economia, la società e la pubblica amministrazione su tutto il cantone.

fr: Wasserrechte

de: Wasserrechte

en: Wasserrechte

it: Wasserrechte


abfallanlagen-und-sammelstellen

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

title_for_slug: abfallanlagen-und-sammelstellen

de: abfall-sammelstelle abfallanlage

fr: Map (Preview)

de: Map (Preview) Stadtplan

en: Map (Preview)

it: Map (Preview)

de: Link zum Thema im Internet-Stadtplan der Stadt Bern

de: WMS Abfallsammelstellen

de: Web Map Services WMS

de: WFS Abfallsammelstellen

de: Web Feature Services WFS

de: Standorte der Entsorgungshöfe und öffentlichen Sammelstellen in der Stadt Bern. Informationen, welche Abfallarten abgegeben werden können. Die Standorte von privaten Unterflursammelstellen für Kehricht und Papier/Karton werden nicht abgebildet.

spatial: Stadt Bern

geoinformation-der-stadt-bern

fr: L’Office du cadastre de la ville de Berne

de: Geoinformation Stadt Bern

en: The Land Surveying Office of the City of Bern

it: L'ufficio del catasto nella Città di Berna

fr: L’Office du cadastre (Geoinformation Stadt Bern) est l’organisme compétent pour la collecte, l’accès et la diffusion d’informations géographiques dans la ville de Berne.

de: Geoinformation Stadt Bern (ehemals Vermessungsamt) ist die Kompetenzstelle für die Beschaffung, den Zugang und die Verbreitung von Geoinformationen in der Stadt Bern.

en: The Surveying Office (Geoinformation Stadt Bern) is the centre of competence in the City of Bern for the procurement of, access to and dissemination of geographic information.

it: L'ufficio del catasto (Geoinformation Stadt Bern) è il centro di competenza per il reperimento, l'accesso e la diffusione di geoinformazioni nella Città di Berna.

political_level: commune

value: Geoinformation Stadt Bern - Geocat Harvester

de: Abfallanlagen und Sammelstellen


okoinfomobil

regi

fr: Régions et villes

de: Regionen und Städte

envi

fr: Environnement

de: Umwelt

title_for_slug: okoinfomobil

de: oekomobil okomobil

de: WMS OekoInfoMobil

de: WFS OekoInfoMobil

de: Haltestellen, an welchen das ÖkoInfoMobil einmal die Woche für 20 Minuten hält und kleine Abfallmengen entgegennimmt. Der Fahrplan ist fix und die Haltezeiten für die jeweiligen Standorte sind angegeben. Die Mitarbeitenden im Mobil beraten kompetent zu Entsorgungsfragen.

de: ÖkoInfoMobil


educ

de: Bildung, Kultur und Sport

ener

de: Energie

protocol: WWW:DOWNLOAD:TEXT, comma separated (CSV)

de: Csv

protocol: WWW:DOWNLOAD:OGC Geopackage (GPKG)

de: Geopackage

format: GPKG

protocol: WWW:DOWNLOAD:INTERLIS 2 (XTF)

de: Interlis

format: INTERLIS

fr: Service WMS-IFDG, couche "Grandes installations solaires"

de: WMS-BGDI Dienst, Layer "Photovoltaik-Grossanlagen"

en: WMS-FSDI service, layer "Large-scale photovoltaic systems"

it: Servizio WMS-IFDG, strato "Grandi impianti fotovoltaici"

fr: RESTful API de geo.admin.ch

de: RESTful API von geo.admin.ch

en: RESTful API from geo.admin.ch

it: RESTful API da geo.admin.ch

fr: Map (Preview) Aperçu map.geo.admin.ch

de: Map (Preview) Vorschau map.geo.admin.ch

fr: Les installations photovoltaïques de haute altitude peuvent produire plus d'électricité par kilowatt de puissance installée et, selon l'emplacement et l'orientation, pendant le semestre d'hiver que des installations comparables en plaine. Ceci parce que les conditions de rayonnement sont meilleures (atmosphère plus fine, moins de brouillard) et parce que la lumière du soleil est réfléchie par la neige (ce qu'on appelle l'effet albédo). Ce jeu de données contient toutes les informations sur les grandes installations photovoltaïques prévues ou réalisées qui ont été notifiées à l'OFEN.

de: Hochalpine Photovoltaik-Anlagen können pro installierte Kilowatt Leistung und je nach Standort und Ausrichtung im Winterhalbjahr mehr Strom erzeugen als vergleichbare Anlagen im Flachland. Dies weil die Einstrahlungsverhältnisse besser sind (dünnere Atmosphäre, weniger Nebel) und weil das Sonnenlicht vom Schnee reflektiert wird (sogenannter Albedo-Effekt). Dieser Datensatz enthält alle Informationen zu den geplanten oder realisierten Photovoltaik-Grossanlagen, die dem BFE gemeldet wurden.

en: Depending on their location and orientation, high-alpine photovoltaic systems can generate more electricity per installed kilowatt of power in the winter months than comparable systems in the lowlands. This is because the radiation conditions are better (thinner atmosphere, less fog) and because the sunlight is reflected by the snow (known as the albedo effect). This dataset contains all information on planned or realised large-scale photovoltaic installations that have been reported to the SFOE.

it: A seconda della loro posizione e del loro orientamento, gli impianti fotovoltaici in alta montagna possono generare più elettricità per chilowatt di potenza installata nei mesi invernali rispetto a impianti analoghi in pianura. Questo perché le condizioni di irraggiamento sono migliori (atmosfera più sottile, meno nebbia) e perché la luce solare viene riflessa dalla neve (il cosiddetto effetto albedo). Questo set di dati contiene tutte le informazioni sugli impianti fotovoltaici di grandi dimensioni, pianificati o realizzati, che sono stati segnalati all'UFE.

spatial: Schweiz

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).

value: BFE - Geocat Harvester

fr: Grandes installations photovoltaïques en Suisse

de: Photovoltaik Grossanlagen in der Schweiz

en: Large-scale photovoltaic systems in Switzerland

it: Impianti fotovoltaici di grandi dimensioni in Svizzera


regi

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

de: Umwelt

it: Ambiente

label: Link zum Fachportal

en: Map (Preview)  map.geo.admin.ch

it: Map (Preview) Previsione map.geo.admin.ch

fr: Aperçu map.geo.admin.ch

de: Vorschau map.geo.admin.ch

en: Preview map.geo.admin.ch

it: Previsione map.geo.admin.ch

fr: Service WMS-IFDG, couche "Carte hydrogéologique au 100"

de: WMS-BGDI Dienst, Layer "Hydrogeologische Karte 100"

en: WMS-FSDI service, layer "Hydrogeological map 100"

it: Servizio WMS-IFDG, strato "Carta idrogeologica 100"

fr: Service WMTS-IFDG, couche , Layer "Carte hydrogéologique au 100"

de: WMTS-BGDI Dienst, Layer "Hydrogeologische Karte 100"

en: WMTS-FSDI service, layer "Hydrogeological map 100"

it: Servizio WMTS-IFDG, strato "Carta idrogeologica 100"

format: WMTS

fr: Lien vers la distribution des données

de: Link zum Datenbezug

en: Link for download

it: Link per le fonti dei dati

fr: Publiée par l’Office fédéral de l’environnement (OFEV), office compétent du Service géologique national pour l’hydrogéologie.La carte hydrogéologique 1:100 000 présente le sous-sol dans la perspective des trois domaines spécialisés : géologie, hydrologie et hydrogéologie. Le sous-sol est classé d’après des critères lithologiques-pétrographiques et de perméabilité. Les données ponctuelles et linéaires (sources, puits, liaisons hydrauliques, nappes phréatiques, etc.) montrent les voies de circulation des eaux souterraines ainsi que l'utilisation actuelle de ces eaux et des eaux de source. La représentation à l’échelle 1:100 000 donne une vue d’ensemble des caractéristiques hydrogéologiques régionales. Voici les cartes disponibles : 1. Bözberg/Beromünster, 1972; 2. Bodensee, 1980; 3. Panixerpass, 1985; 4. Biel, 1991/92; 5. Toggenburg, 1993/94; 6. Saane, 1999; 8. Vallorbe - Léman nord, 2006; 7. Basel, 2014. Un jeu de données vectorielles, indépendant du découpage en feuilles, a été créé à partir des feuilles 4, 6, 7 et 8 pour le Nord-ouest de la Suisse. Les données peuvent être commandées à l’OFEV (www.bafu.admin.ch  Données, indicateurs, cartes).

de: Herausgegeben vom Bundesamt für Umwelt BAFU, der zuständigen Fachstelle der Landesgeologie für die Hydrogeologie. Die Hydrogeologische Karte 1:100‘000 zeigt den Untergrund aus der Sicht von drei Fachbereichen: der Geologie, Hydrologie und Hydrogeologie. Der Untergrund ist nach lithologisch-petrografischen Kriterien und der Durchlässigkeit klassiert. Punkt- und Liniendaten (Quellen, Brunnen, hydraulische Verbindungen, Grundwasservorkommen etc.) zeigen die Zirkulationswege des Grundwassers und dessen Nutzung an Förderbrunnen und Quellfassungen. Die Darstellung im Massstab 100'000 gibt Einblick in die regionalen hydrogeologischen Gegebenheiten. Folgende Karten sind verfügbar: 1. Bözberg/Beromünster, 1972; 2. Bodensee, 1980; 3. Panixerpass, 1985; 4. Biel, 1991/92; 5. Toggenburg, 1993/94; 6. Saane, 1999; 8. Vallorbe - Léman nord, 2006; 7. Basel, 2014. Für die NW-Schweiz wurde ein blattschnittfreier Vektordatensatz der Kartenblätter 4, 6, 7, 8 erstellt. Die Daten können beim BAFU bezogen werden (www.bafu.admin.ch  Daten, Karten, Indikatoren).

en: Published by the Federal Office for the Environment FOEN, the specialist office of the Swiss Geological Survey responsible for hydrogeology.The hydrogeological map 1:100,000 shows the subsurface from the perspective of three disciplines: geology, hydrology and hydrogeology. The subsurface is classified according to lithological-petrographical criteria and permeability. Point and line data (springs, wells, hydraulic connections, groundwater resources, etc.) indicate the flow paths of groundwater and its exploitation at wells and tapped springs. The representation at a scale of 100,000 provides insight into the regional hydrogeological conditions. The following maps are available: 1. Bözberg/Beromünster, 1972; 2. Lake Constance, 1980; 3. Panixerpass, 1985; 4. Biel-Bienne, 1991/92; 5. Toggenburg, 1993/94; 6. Saane, 1999; 8. Vallorbe - Léman nord, 2006; 7. Basel, 2014. For North West Switzerland, a seamless vector data set of maps 4, 6, 7 and 8 was created. The data can be obtained from the FOEN (www.bafu.admin.ch Data, indicators, maps).

it: Pubblicata dall’Ufficio federale dell’ambiente (UFAM), il servizio specializzato del Servizio geologico nazionale competente per l’idrogeologia.La carta idrogeologica 1:100 000 rappresenta il sottosuolo dalla prospettiva di tre discipline: la geologia, l’idrologia e l’idrogeologia. Il sottosuolo è classificato secondo criteri litologico-petrografici e in funzione della permeabilità. I dati lineari e puntiformi (sorgenti, pozzi, relazioni idrauliche, falde freatiche ecc.) mostrano le vie di circolazione delle acque sotterranee come pure la loro utilizzazione in pozzi di pompaggio e captazioni di sorgenti. La rappresentazione in scala 1:100 000 fornisce una panoramica delle caratteristiche idrogeologiche regionali. Sono disponibili le seguenti carte: 1. Bözberg/Beromünster, 1972; 2. Bodensee, 1980; 3. Panixerpass, 1985; 4. Biel, 1991/92; 5. Toggenburg, 1993/94; 6. Saane, 1999; 8. Vallorbe - Léman nord, 2006; 7. Basel, 2014. Per la Svizzera nord-occidentale è stato creato un set di dati vettoriali senza suddivisioni a partire dai fogli 4, 6, 7, 8. I dati possono essere richiesti all’UFAM (www.bafu.admin.ch  Dati, carte, indicatori).

spatial: Schweizerisches Mittelland

bundesamt-fur-umwelt-bafu

fr: Office fédéral de l'environnement OFEV

de: Bundesamt für Umwelt BAFU

en: Federal Office for the Environment FOEN

it: Ufficio federale dell'ambiente UFAM

fr: L’autorité compétente pour les questions environnementales. Il est à ce titre chargé de gérer les ressources naturelles selon les principes du développement durable et de protéger l’homme contre les dangers naturels et l’environnement contre les pollutions.

de: Die Fachbehörde für die Umwelt. Es ist zuständig für die nachhaltige Nutzung der natürlichen Ressourcen sowie für den Schutz des Menschen vor Naturgefahren und den Schutz der Umwelt vor übermässigen Belastungen.

en: The federal environmental authority. It is responsible for ensuring that natural resources are used sustainably, that the public is protected against natural hazards, and that the environment is protected from unacceptable adverse impacts.

it: Il servizio specializzato in materia ambientale, è competente per quanto riguarda l'utilizzazione sostenibile delle risorse naturali, la protezione delle persone dai pericoli naturali e dell'ambiente da un inquinamento eccessivo.

value: BAFU - Geocat Harvester

fr: Carte hydrogéologique de la Suisse 1:100000

de: Hydrogeologische Karte der Schweiz 1:100000

en: Hydrogeological map of Switzerland 1:100000

it: Carta idrogeologica della Svizzera 1:100000


regi

fr: Régions et villes

envi

en: Environment

label: Web GIS Client des Kanton Uri. Die Daten können direkt via dem Portal in den unterschiedlichsten Datenformaten heruntergeladen werden.

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: Übersicht der Massnahmen aus den Agglomerationsprogrammen. Es sind nur die Massnahmen mit Umsetzungshorizont A gemäss Bund publiziert.

spatial: Canton of Uri (UR)

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

value: Uri-Kt - Geocat Harvester

fr: Agglomerationsprogramm Massnahmen

de: Agglomerationsprogramm Massnahmen

en: Agglomerationsprogramm Massnahmen

it: Agglomerationsprogramm Massnahmen


jagdbanngebiete-kantonal-ur

envi

fr: Environnement

title_for_slug: jagdbanngebiete-kantonal-ur

fr: district-franc geodonnees-de-base

de: jagdbanngebiet geobasisdaten

en: game-reserve official-geodata

it: bandita-di-caccia geodati-di-base

fr: Dieser Datensatz enthält die Jagdbanngebiete des Kanton Uris (CH168) Die Jagdbanngebiet des Bundes können bei Bedarf über den Geodatenkatalog als WMS eingebunden werden.

fr: Jagdbanngebiete kantonal (UR)

de: Jagdbanngebiete kantonal (UR)

en: Jagdbanngebiete kantonal (UR)

it: Jagdbanngebiete kantonal (UR)


larmbelastungskataster-strassen-tag-ur

regi

de: Regionen und Städte

title_for_slug: larmbelastungskataster-strassen-tag-ur

fr: Der Kanton (kantonale Vollzugsbehörde) ist nach Art. 37 (LSV) verpflichtet, für seine Strassen einen Lärmbelastungskataster zu führen und diesen periodisch zu aktualisieren. Der Lärmbelastungskataster für Haupt- und übrige Strassen ist ein wichtiges Informations- und Planungsinstrument für die Behörden in der Raumplanung und in der Beurteilung des Umweltzustand Lärmbelastung. Dargestellt werden die Belastungsgrenzwerte für die Beurteilung des Lr Tag.

fr: Lärmbelastungskataster Strassen (Tag) (UR)


ausserorts-innerorts-kantonsstrassen

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

title_for_slug: ausserorts-innerorts-kantonsstrassen

fr: Ausserorts- und Innerortsabschnitte der Kantonsstrassen.

fr: Ausserorts Innerorts Kantonsstrassen

de: Ausserorts Innerorts Kantonsstrassen

en: Ausserorts Innerorts Kantonsstrassen

it: Ausserorts Innerorts Kantonsstrassen


geschwindigkeit-kantonsstrasse

regi

en: Regions and cities

it: Regioni e città

title_for_slug: geschwindigkeit-kantonsstrasse

fr: Angaben der Geschwindigkeit auf der Kantonsstrasse.

fr: Geschwindigkeit Kantonsstrasse

de: Geschwindigkeit Kantonsstrasse

en: Geschwindigkeit Kantonsstrasse

it: Geschwindigkeit Kantonsstrasse


waldabstandslinien-differenz-ur

envi

de: Umwelt

it: Ambiente

title_for_slug: waldabstandslinien-differenz-ur

de: waldabstand baulinie geobasisdaten

fr: Mit Waldabstandslinien wird im Nutzungsplan der Waldabstand gegenüber der festgelegten Waldgrenze, in Abweichung zum generellen Waldabstand von 20 Metern gemäss Artikel 93 Absatz 1 des Planungs- und Baugesetzes (PBG; RB 40.1111), festgelegt. Sie entsprechen einer Baulinie Wald gemäss Artikel 48 Absatz 2 PBG.

fr: Waldabstandslinien Differenz (UR)

de: Waldabstandslinien Differenz (UR)

en: Waldabstandslinien Differenz (UR)

it: Waldabstandslinien Differenz (UR)


seilbahnen-mit-konzession

regi

fr: Régions et villes

title_for_slug: seilbahnen-mit-konzession

fr: WMS-Dienst des Kanton Uri

fr: Der Datensatz umfasst die im Kanton Uri konzessionierten Personenseilbahnen, Sessellifte und Skilifte.

fr: Seilbahnen mit Konzession

de: Seilbahnen mit Konzession

en: Seilbahnen mit Konzession

it: Seilbahnen mit Konzession


schutzinventar-landschaft

envi

fr: Environnement

title_for_slug: schutzinventar-landschaft

fr: WFS-Dienst des Kanton Uri

fr: Der Datensatz zeigt die schutzwürdigen Landschaften. Das Kantonale Schutzinventar hat gemäss kNHG Art. 17 hinweisenden Charakter. Es ist nicht abschliessend und wird laufend nachgeführt. Für die vollständige Anzeige des Schutzinventars müssen noch die beiden Layer "Schutzinventar: Kultur" und "Schutzinventar: Natur" dazugeladen werden. Link zu den Inventarlisten des Kantons Uri

fr: Schutzinventar Landschaft

de: Schutzinventar Landschaft

en: Schutzinventar Landschaft

it: Schutzinventar Landschaft


strassenverkehrslarm-nacht

title_for_slug: strassenverkehrslarm-nacht

fr: Der Strassenlärmkataster wurde mit dem Berechnungsprogramm SLIP erstellt. Grundlagen für die Berechnungen bilden die Verkehrszahlen der Kantons- und Gemeindestrassen aus dem Jahr 2018. Bei den Berechnungen werden die Topographie wie auch Hindernisse (Lärmschutzwände, Gebäude, usw.) mitberücksichtigt.

fr: Strassenverkehrslärm Nacht

de: Strassenverkehrslärm Nacht

en: Strassenverkehrslärm Nacht

it: Strassenverkehrslärm Nacht


schutzinventar-natur

title_for_slug: schutzinventar-natur

fr: zone-alluviale bas-marais cours-deau geotope haut-marais nature geodonnees-de-base

de: auengebiet flachmoor fliessgewasser geotop hochmoor natur geobasisdaten

en: alluvial-site swamp watercourse geotope raised-bog nature official-geodata

it: zona-golenale palude corso-dacqua geotopo torbiera-alta natura geodati-di-base

de: WMS-Dienst des Kanton Uri

fr: Der Datensatz zeigt die schutzwürdigen Objekte (Gebiete, Einzelobjekte) im Bereich Natur. Das Kantonale Schutzinventar hat gemäss kNHG Art. 17 hinweisenden Charakter. Es ist nicht abschliessend und wird laufend nachgeführt. Für die Anzeige des vollständigen Schutzinventars müssen noch die beiden Layer "Schutzinventar: Kultur" und "Schutzinventar: Landschaft" dazugeladen werden. Link zu den Inventarlisten des Kantons Uri

fr: Schutzinventar Natur

de: Schutzinventar Natur

en: Schutzinventar Natur

it: Schutzinventar Natur


strassenverkehrslarm-tag

title_for_slug: strassenverkehrslarm-tag

de: WFS-Dienst des Kanton Uri

de: Der Strassenlärmkataster wurde mit dem Berechnungsprogramm SLIP erstellt. Grundlagen für die Berechnungen bilden die Verkehrszahlen der Kantons- und Gemeindestrassen aus dem Jahr 2018. Bei den Berechnungen werden die Topographie wie auch Hindernisse (Lärmschutzwände, Gebäude, usw.) mitberücksichtigt.

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

fr: Strassenverkehrslärm Tag

de: Strassenverkehrslärm Tag

en: Strassenverkehrslärm Tag

it: Strassenverkehrslärm Tag


gerichtsbezirke

regi

de: Regionen und Städte

envi

en: Environment

title_for_slug: gerichtsbezirke

it: WMS-Dienst des Kanton Uri

fr: Zuständigkeitsgebiete der Gerichte im Kanton Uri

fr: Gerichtsbezirke

de: Gerichtsbezirke

en: Gerichtsbezirke

it: Gerichtsbezirke


tran

fr: Transports

de: Verkehr

url: https://geo.ur.ch/?layers=Strassenverkehrszählung reg. und lok. Netz

en: WMS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

fr: Die Datensätze der Strassenverkehrszählung enthalten Informationen über die Standorte der Verkehrszählung, d.h. die Messstellen. Dabei handelt es sich in der Regel um automatische Verkehrszählungen. Der Verkehr wird entweder permanent erhoben oder es findet eine temporäre Messung (z.B. von 2 Wochen Dauer) statt. Die bei der Verkehrszählung erhobenen Verkehrswerte sind nicht Gegenstand des minimalen Geodatenmodells. Das minimale Geodatenmodell enthält hingegen Kennzahlen (z.B. DTV, DWV) auf Jahresbasis, die aus den Verkehrswerten aggregiert bzw. hochgerechnet werden.

fr: Strassenverkehrszählung reg. und lok. Netz (UR)


regi

fr: Régions et villes

envi

de: Umwelt

de: baulinie eigentumsbeschrankungoreb fliessgewasser nutzungsplanung oberflachengewasser raumplanung strasse

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: Kantonale und kommunale Baulinien, die in einem grundeigentümerverbindlichen, öffentlich-rechtlichen Planwerk festgelegt wurden.

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: Baulinien nach Strassen- und Baulinienplänen


maintainer: EnviDat Support

en: paleo-climate precipitation last-glacial-maximum orography air-temperature glaciers

en: Data Access via S3

en:
High resolution, downscaled climate model data are used in a wide variety of applications in environmental sciences. Here we present the CHELSA-TraCE21k downscaling algorithm to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100 year time steps for the last 21,000 years. Paleo orography at high spatial resolution and at each timestep is created by combining high resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases with the interpolation of a dynamic ice sheet model (ICE6G) and a coupling to mean annual temperatures from CCSM3-TraCE21k. Based on the reconstructed paleo orography, mean annual temperature and precipitation was downscaled using the CHELSA V1.2 algorithm.

The data is published under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

format: GeoTIFF

en: Technical documentation

media_type: application/pdf

en: Technical documentation containing file metadata and variable descriptions.

format: PDF

mimetype: application/pdf

air-temperature

display_name: air-temperature

glaciers

display_name: glaciers

last-glacial-maximum

display_name: last-glacial-maximum

orography

display_name: orography

paleo-climate

display_name: paleo-climate

precipitation

display_name: precipitation

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

en: CHELSA-TraCE21k: Downscaled transient temperature and precipitation data since the last glacial maximum


rorcc

maintainer: Tobias Wechsler

title_for_slug: rorcc

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

en: RoRCC

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

format: XLS

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

climate-change

display_name: climate-change

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants


maintainer: Michael Lehning

en: alpine-precipitation snow-cover snow-distribution alpine3d-simulations snow alpine3d snow-hydrology

en: ADS datasets and simulation inputs

media_type: application/zip

en: The file contains the ADS datasets of snow depth and input data used for simulations.

format: ZIP

mimetype: application/zip

en:
Dataset (Model input, snow distribution and validation) for the precipitation scaling paper, which should be cited along with the data set citation.

This data is useful for distributed hydrological modelling or other tasks that involve the study of snow distribution and precipitation in the high Alpine.

The format of the data is for Alpine3D (models.slf.ch) model runs but other models could be used, too.

Please cite:

_Vögeli, C., Lehning, M., Wever, N., Bavay M., 2016: Scaling Precipitation Input to Spatially Distributed Hydrological Models by Measured Snow Distribution., Front. Earth Sci. 4: 108. doi: 10.3389/feart.2016.00108._

Dataset is provided as a single zip file.
The archive contains two directories, the valuable distributed snow depth maps for the landscape Davos and the simulation input.
The archive also contains the file: "ReadMeMetadataDataSetPrecipitationScaling" which explains the data structure.

alpine-precipitation

display_name: alpine-precipitation

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-distribution

display_name: snow-distribution

snow-hydrology

display_name: snow-hydrology

en: Precipitation Scaling Data Set (Vögeli et al., Frontiers)


maintainer: Giulia Francesca Azzurra Donati

en: ecological-corridors network-analysis urban-planning biodiversity ecosystem-services circuit-theory

en: Amphibian movement resistance layers and scripts for connectivity modelling - part 2

en: The zipped folder includes the script to create and analyse the networks from Circuitscape outputs. The subfolders “Boundaries”, “Layers”, and “Reference_net” contain files either called by the code or created in the process. The subfolder “Outputs_from_Circuitscape” contains the outputs from Circuitscape including node and branch cumulative currents in a network format.

en: Amphibian movement resistance layers and scripts for connectivity modeling - part 1

en: The zipped folder includes the script to aggregate the resistance layers into squared and hexagonal grids. The subfolders “Boundaries”, “Layers”, “Reference_grids”, and “Resistance_from_SDMs” contain files either called by the code or created in the process.The subfolder “Inputs_for_Circuitscape” contains the inputs to run Circuitscape, after doing some subsequent processing steps in QGIS (listed in the R script) with the files created with the script.

en: This data includes (1) Scripts to aggregate landscape resistance layers into squared and hexagonal grids (i.e., different representations and resolutions), (2) Input resistance layers and focal nodes in .txt format to run in Circuitscape (Python implementation v4.0.5). Circuitscape is a software tool for modeling and analyzing landscape connectivity, which simulates movement of organisms across landscapes by estimating resistance to movement across each point of the landscape. (3) Scripts for the ecological network analysis, and (4) environmental predictors for amphibian whole-life cycle habitats used to describe the local environment for BGI design (i.e. topographic, hydrologic, edaphic, vegetation, land-use derived, movement-ecology related).

biodiversity

display_name: biodiversity

circuit-theory

display_name: circuit-theory

ecological-corridors

display_name: ecological-corridors

ecosystem-services

display_name: ecosystem-services

network-analysis

display_name: network-analysis

urban-planning

display_name: urban-planning

en: Multi-Scale Prioritization framework for Urban Blue-Green Infrastructure Planning to Support Biodiversity: Data & Codes


maintainer: Matthias Haeni

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

en: Site aerial photo (Isone)

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

mimetype: image/jpeg

en: Data plot of the forest station (ISB)

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

en: Data plot of the field station (ISF)

en: Forest station data (ISB)

media_type: text/csv

en: Data file.

mimetype: text/csv

en: Site photo of the field station (ISF)

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

en: Site photo of the forest station (ISB)

en: Site photo of the forest station from below (viewing upwards the slope).

en: Field station data (ISF)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Isone in Switzerland where one station is located within a natural broad-leaved forest stand (ISB) with European beech (_Fagus sylvatica_; 70-100 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, ISF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Isone is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


en: hazard-mapping natural-hazard snow avalanche satellite

en: SPOT6 Avalanche outlines 24 January 2018

en: Shapefile of the manually mapped avalanche outlines. Please only use this data together with the example key document provided with this dataset.

format: SHP

en:
Outlines of 18'737 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 24 January 2018. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping.pdf)

The generation of the data is described in:

Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.

Abstract.
Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12’500 km2).

We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18’737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.

This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data is of great value to validate avalanche bulletins, complete existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.

Koordinate System: CH1903+ LV95 LN02

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


maintainer: Nander Wever

en: precipitation-amount air-temperature humidity snow-depth longwave-radiation wind-direction wind-speed shortwave-radiation snow-ice-temperature

en: SNOWPACK ini file (new syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using the new MeteoIO Filter, Generator and Interpolation syntax.

en: Version 3

en:
Deprecated version. Release notes:

Bug fix: in version 2, the undercatch correction was not applied correctly

Bug fix: in version 2, snow lysimeter data was missing for extended periods of time

Update: dataset extended to 2016-01-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Undercatch correction

en: This document describes how the undercatch correction for the Weissfluhjoch measurement site was determined.

en: Version 6

en:
Deprecated version.

Release notes:

- Missing ISWR for 2009-09-30 and 2010-04-30 has been replaced by data from WFJ Gipfel

This dataset is the basis for the Weissfluhjoch dataset in ESM-SnowMIP (doi: http://dx.doi.org/10.16904/16).

en: Version 7 (current)

en:
Release notes:

Bug fix: in previous versions, snow lysimeter data from September 2010 onwards was erroneously reported for UTC+2, instead of UTC+1 (i.e., reported one hour later than should have been).

Update: dataset extended to 2017-07-11T00:30.

en: Version 2

en:
Deprecated version. Release notes:

Bug fix: in v1, incoming radiation components were taken from WFJ_Gipfel station, instead of WFJ Versuchsfeld.

en: Version 4

en:
Deprecated version. Release notes:

Update: dataset extended to 2016-09-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 1

en:
Deprecated version. Release notes:

First release of dataset.

en: SNOWPACK sno file

en: This sno-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en: Version 5

en:
Deprecated version. Release notes:

Update: using the incoming and outgoing short- and longwave radiation data from the new processing chain from 2010 onwards, filling also data gaps in pre-2010 data.

Update: dataset extended to 2016-10-04T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: All versions

en: SNOWPACK ini file (old syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en:
Dataset of meteorological and snowpack measurements from the automatic weather station at Weissfluhjoch, Davos, Switzerland, suitable for driving snowpack models. The dataset contains standard meteorological measurements, and additionally snowpack runoff data from a snow lysimeter. Where possible, data is quality checked and missing data are replaced from backup sensors from the measurement site itself, or (in only a few cases) from the MeteoSwiss weather station at 470 m distance and 150 m above the measurement site.

Publication
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M. Verification of the multi-layer SNOWPACK model with different water transport schemes. 2015. The Cryosphere. Volume 9. 2271-2293. http://dx.doi.org/10.5194/tc-9-2271-2015.

air-temperature

display_name: air-temperature

humidity

display_name: humidity

longwave-radiation

display_name: longwave-radiation

precipitation-amount

display_name: precipitation-amount

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

snow-ice-temperature

display_name: snow-ice-temperature

wind-direction

display_name: wind-direction

en: WFJ_MOD: Meteorological and snowpack measurements from Weissfluhjoch, Davos, Switzerland


maintainer: Anita C. Risch

en: mineralization worldwide nutrient-network global soil-chemistry soil-biology grassland soil

en:
site.code: Site code

Continent: Continent

sampleID: Sample ID

nn.latitude: Lattitude

nn.longitude: Longitude

bioclim.T.ann: Mean annual temperature (°C)

bioclim.T.var: Temperature variability (°C)

bioclim.T.q.wet: Temperature of the wettest quarter (°C)

bioclim.T.q.dry: Temperature of the driest quarter (°C)

bioclim.T.q.warm: Temperature of the warmest quarter (°C)

bioclim.P.ann: Mean annual preciptiation (mm)

bioclim.P.q.wet: Precipitation of the wettest quarter (mm)

ch.pH: pH

ch.WSK.vol: Water holding capacity (vol%)

ch.bulkdensity.gcm3: Bulk density (g cm-3)

ch.porespace: Pore space (vol%)

ch.sand.perc: Soil texture: sand (%)

ch.silt.perc: Soil texture: silt (%)

ch.clay.perc: Soil texture: clay (%)

ch.NO3start.mgg: NO3 at the beginning of the incubation (mgkg)

ch.Ntot.perc: Total soil N (%)

ch.Ctot.perc: Total soil C (%)

ch.Corg.perc: Soil organic C (%)

ch.netNminfield.mgkgd: Realised soil net N mineralisation (mg kg-1 d-1)

ch.netNminlab.mgkgd: Potential soil ne N mineralisation (mg kg-1 d-1)

archaea.cpg.log: Ammonia oxidising archaea (archaeal amoA gene copies g-1 soil)

bacteria.cpg.log: Ammonia oxidising bacteria (bacterial amoA gene copies g-1 soil)

micr.biom: Microbial biomass (ug g-1 soil)

ch.CtoN: C to N ratio

ch.netNnitriffield.mgkgd.sqrt: Realised soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniffield.mgkgd.sqrt: Realised soil net ammonification, transformed (mg kg-1 d-1)

ch.netNnitriflab.mgkgd.sqrt: Potential soil net nitrification, transformed (mg kg-1 d-1)

ch.netNammoniflab.mgkgd.sqrt: Potential soil net ammonifiation, transformed (mg kg-1 d-1)

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

Paper Citation:

Risch, A. C.; Zimmermann, S.; Ochoa-Hueso, R.; Schütz, M.; Frey, B.; Firn, J. L.; Fay, P. A.; Hagedorn, F.; Borer, E. T.; Seabloom, E. W.; et al. Soil net nitrogen mineralisation across global grasslands. Nat. Commun. 2019, 10 (1), 4981 (10 pp.). doi.org/10.1038/s41467-019-12948-2

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

We conducted coordinated measurements of realised and potential soil net Nmin, and assessed water holding capacity, bulk density, C and N content, texture, pH, pore space, microbial biomass, and archaeal (AOA) and bacterial (AOB) ammonia oxidiser abundance using identical materials and methods across 30 grasslands on six continents. The sites covered a globally relevant range of climatic and edaphic conditions. Climate data was obtained from worldclim - Global climate data https://www.worldclim.org/

global

display_name: global

grassland

display_name: grassland

mineralization

display_name: mineralization

nutrient-network

display_name: nutrient-network

soil

display_name: soil

soil-biology

display_name: soil-biology

soil-chemistry

display_name: soil-chemistry

worldwide

display_name: worldwide

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: snow-precipitation precipitation-variability cosmo-wrf orographic-precipitation complex-terrain

en: StationData

en: Snow depth maps over Dischma valley for 26 January 2016 and 9 March 2016 and snow depth differences between the two dates.

en:
The data presented here corresponds to the publication "Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain" (Gerber et al., 2018a), which investigates the precipitation variability of snow precipitation in the central northern part of the Grisons (CH) and the publication "The importance of near-surface winter precipitation processes in complex alpine terrain" (Gerber et al., 2018b). The dataset contains:

* WRFsimulations: WRF simulation output for simulations with 4x (14x) terrain smoothing with an output timestep of 30 min/5 min and horizontal grid spacings of 1350 m, 450 m, 150 m and 50 m (currently: data available upon request).
* StationData: Meteorological station data of 18 meteorological stations in the central northern part of the Grisons with 30 minute resolution for the period 1 January 2016 till 1 May 2016.
* ADS80data: Photogrammetrically determined snow depth distribution data over the Dischma valley for the 26 January 2016 and 9 March 2016. Snow heights are corrected for buildings, vegetation (> 1m), outliers, and pixles, which are obivously snow-free on the pictures (Bühler et al., 2015). In addition the snow depth differences (snow depth on 9 March 2016 minus snow depth on 26 January 2016) are provided.

For more details about the simulation and observation data, see Gerber et al., 2018 and Gerber and Sharma (2018).

Publications:

Bühler, Y., Marty, M., Egli, L., Veitinger, J., Jonas, T., Thee, P., and Ginzler, C.: Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9, 229–243, doi:10.5194/tc-9-229-2015, 2015.

Gerber, F., Besic, N., Sharma, V., Mott, R., Daniels, M., Gabella, M., Berne, A., Germann, U., and Lehning, M.: Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain, The Cryosphere, 12, 3137–3160, doi:10.5194/tc-12-3137-2018, 2018.

Gerber, F., Mott, R. and Lehning, M.: The importance of near-surface winter precipitation processes in complex alpine terrain, Journal of Hydrometeorology, accepted, 2018.

Gerber, F., and Sharma, V.: Running COSMO-WRF on very-high resolution over complex terrain. Laboratory of Cryospheric Sciences CRYOS, École Polytechnique Fédérale de Lausanne EPFL, Lausanne, Switzerland. doi:10.16904/envidat.35, 2018.

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

orographic-precipitation

display_name: orographic-precipitation

precipitation-variability

display_name: precipitation-variability

snow-precipitation

display_name: snow-precipitation

en: DISCHMEX - High-resolution WRF simulations in complex alpine terrain and station measurements


maintainer: Jana von Freyberg

en: precipitation hydrology stream-water alptal catchment stable-water-isotope

media_type: text/plain

en: Single comma-separated txt-file with daily data of stable water isotopes measured in streamwater and precipitation in the Swiss Alptal catchment and two of its tributaries (Erlenbach and Vogelbach), as well as daily data of key hydrometeorological variables from the Alptal valley

format: TXT

en:
Version 2 of the dataset contains additional information on:
- line-conditioned (lc) excess
- precipitation sample volumes
- isotope data quality

en: Data Set Documentation: alptal_Isotopes_daily_2015-2019_v2

en: Documentations contains meta data of the data columns and information about the study catchments.

en: This dataset contains four years of daily measurements of the natural isotopic composition (2H, 18O) of precipitation and stream water at the Alp catchment (area 47 km2) in Central Switzerland and two of its tributaries (0.73 km2 and 1.55 km2). In addition, the dataset contains daily measurements of key hydrometeorological variables.

alptal

display_name: alptal

catchment

display_name: catchment

hydrology

display_name: hydrology

precipitation

display_name: precipitation

stable-water-isotope

display_name: stable-water-isotope

stream-water

display_name: stream-water

en: Four years of daily stable water isotope data in stream water and precipitation from three Swiss catchments


en: Data Source

en: Coordinates of Grid Points

en: Description

en: Full Data Description

en: Hourly Gridded Wind Power Time Series

en:
This dataset consist of simulated hourly power production from an Enercon E82 Turbine at 100 m hub-height. It describes the hourly power output a 1MW turbine would produce in each 0.01° grid cell for the years 2016 and 2017.

100 m wind speed data was taken from the COSMO-1 model (Consortium for Small-scale Modeling 2017), which has a 0.01° horizontal resolution. The domain covered is the whole of Switzerland, with the exclusion of lakes. As such, the number of 0.01◦ pixels within Switzerland amounts to 48657.
Conversion to power output was done based on the power curve of the Enercon E82 Turbine. As power output is lower at altitude due to lower air density, we corrected for this effect as described in (Kruyt et al. 2017).

Please cite the following paper in connection with the dataset:

Paper Citation:
 > _Bert Kruyt, Jérôme Dujardin, and Michael Lehning: Improvement of wind power assessment in complex terrain: The case of COSMO-1 in the Swiss Alps, Front. Energy Res., [doi:10.3389/fenrg.2018.00102] (https://doi.org/10.3389/fenrg.2018.00102)_

mountain-wind-potential

display_name: mountain-wind-potential

topography

display_name: topography

wind-energy

display_name: wind-energy

en: Dataset on Cosmo-1 based Energy Potential in Swiss Alps


en: model-calibration-data snow-depth snow-water-equivalent snow-density model-validation-data

en: swe2hs calibration and validation data

en:
 Contents of this archive

 README.md

 A readme file containing a description of the other files.

 automatic_stations_validation_data.csv

 Daily data from the automatic weather stations used for validation.

 Data sources and providers are listed in the SWE2HS paper, Table 1.

 Columns:

  * date: timestamp of the format YYYY-MM-DD
  * HS_[m]: snow depth in [m]
  * SWE_[m]: snow water equivalent in [m]
  * site_id: code for the measurement site
  - HS_interpolated: boolean flag for interpolated values
  - SWE_interpolated: : boolean flag for interpolated values

 coordinates_swe2hs_paper_stations.csv

 Coordinates of all measurement sites used in the SWE2HS paper.

 Columns:

  * site_id: code for the measurement site
  * location_name: location name of the measurement site
  * lon_[wgs84]: longitude in WGS84
  * lat_[wgs84]: latitude in WGS84
  * elevation_[m]: atitude of the measurement site in [m]
  * dataset: dataset in which the station is included

 manual_station_calibration_data.csv

 Calibration data from the Swiss manual observer stations. Long station records
 trmmed to 15 random water-years.

 Columns:

  * date: timestamp of the format YYYY-MM-DD
  * HS_[m]: snow depth in [m]
  * SWE_[m]: snow water equivalent in [m]
  * SWE_from_profile_[m]: biweekly measurement from the SWE in the measurement
   pit. Corrected with the bulk density in order to match the snow depth from
   the measurement stake. Please refer to the paper for further details.
  * site_id: code for the measurement site

 manual_stations_validation_data.csv

 Validation data from the Swiss manual observer stations. Remaining water-years
 from the long sttaion record not used for the calibration data.

 Columns:

  * date: timestamp of the format YYYY-MM-DD
  * HS_[m]: snow depth in [m]
  * SWE_[m]: snow water equivalent in [m]
  * SWE_from_profile_[m]: biweekly measurement from the SWE in the measurement
   pit. Corrected with the bulk density in order to match the snow depth from
   the measurement stake. Please refer to the paper for further details.
  * site_id: code for the measurement site

 manual_stations_used_deltasnow_parameters.csv

 Site specific DeltaSNOW model parameters used for the calculation of the daily
 SWE series in 'manual_stations_calibration_data.csv' and
 'manual_stations_validation_data.csv'.

 Parameters were optimized by reducing RMSE to the biweekly snow pit SWE measurements.
 Please refer to the paper for further details.

 A python implementation of the DeltaSNOW model was used for the calculation:
 pydeltasnow (https://pypi.org/project/pydeltasnow/)

 For a detailed description of the DeltaSNOW model parameters please see the
 respective publication:

 Winkler, M., Schellander, H., & Gruber, S. (2021). Snow water equivalents
 exclusively from snow depths and their temporal changes: the Δ snow model.
 Hydrology and Earth System Sciences, 25(3), 1165-1187.

 Columns:

  * site_id: code for the measurement site
  * rho_max: Maximum density of an individual snow layer produced by the DeltaSNOW model in [kg/m3]
  * rho_null: Fresh snow density for a newly created layer [kg/m3
  * c_ov: Overburden factor due to fresh snow [-]
  * k_ov: Defines the impact of the individual layer density on the compaction due to overburden [-]
  * k: Exponent of the exponential-law compaction [m3/kg]
  * tau: Uncertainty bound [m]
  * eta_null: Effective compactive viscosity of snow for “zero-density” [Pa s]

en:
The data in this repository was used for the calibration and validation of the
SWE2HS model in the following publication:
Aschauer, J., Michel, A., Jonas, T., & Marty, C. (2023). An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0. Geoscientific Model Development Discussions, 1-19. https://doi.org/10.5194/gmd-2022-258
Contains daily snow water equivalent and snow depth timeseries from stations in the European Alps.

model-calibration-data

display_name: model-calibration-data

model-validation-data

display_name: model-validation-data

snow-density

display_name: snow-density

snow-depth

display_name: snow-depth

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: SWE2HS model calibration and validation data


en: time-series gridded-data geodata core research-data-management video-encoding sentinel-2 raster

en: View publication in the Digital Object Repository at WSL (DORA)

media_type: text/html

en:
Shell script to reproduce the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software for working with CORE will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en:
Shell script to extract data from the CORE format. You can 1) download and unzip the file, 2) make the script executable and 3) run it.
Disclaimer: only provided for peer review. Proper software will become available in time on https://github.com/EnviDat/?q=core (both Web/JS for Frontend and Python for Backend).

en: CORE Dataset (80 GB)

en:
DISCLAIMER: CORE is still in development. Interested parties are warmly invited to join common development, to comment, discuss, find bugs, etc.

Acknowledgement: The CORE format was proudly inspired by the Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) format, by considering how to leverage the ability of clients issuing HTTP GET range requests for a time-series of remote sensing and aerial imagery (instead of just one image).

License: The Cloud Optimized Raster Encoding (CORE) specifications are released to the public domain under a Creative Commons 1.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

-----------------------

Summary:
The Cloud Optimized Raster Encoding (CORE) format is being developed for the efficient storage and management of gridded data by applying video encoding algorithms. It is mainly designed for the exchange and preservation of large time series data in environmental data repositories, while in the same time enabling more efficient workflows on the cloud. It can be applied to any large number of similar (in pixel size and image dimensions) raster data layers. CORE is not designed to replace COG but to work together with COG for a collection of many layers (e.g. by offering a fast preview of layers when switching between layers of a time series).

WARNING: Currently only applicable to RGB/Byte imagery. The final CORE specifications may probably be very different from what is written herein or CORE may not ever become productive due to a myriad of reasons (see also 'Major issues to be solved').

With this early public sharing of the format we explicitly support the Open Science agenda, which implies "shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process" (quote from: European Commission, Directorate General for Research and Innovation, 2016. Open innovation, open science, open to the world).

CORE Specifications:

1) a MP4 or WebM video digital multimedia container format (or any future video container playable as HTML video in major browsers)

2) a free to use or open video compression codec such as H.264, VP9, or AV1 (or any future video codec that is open sourced or free to use for end users)

Note: H.264 is currently recommended because of the wide usage with support in all major browsers, fast encoding due to acceleration in hardware (which is currently not the case for AV1 or VP9) and the fact that MPEG LA has allowed the free use for streaming video that is free to the end users. However, please note that H.264 is restricted by patents and its use in proprietary or commercial software requires the payment of royalties to [MPEG LA](https://www.mpegla.com/programs/avc-h-264/). However, when AV1 matures and accelerated hardware encoding becomes available, AV1 is expected to offer 30% to 50% smaller file size in comparison with H.264, while retaining the [same quality](https://trac.ffmpeg.org/wiki/Encode/AV1).

3) the encoding frame rate should be of one frame per second (fps) with each layer segmented in internal tiles, similar to COG, ordered by the main use case when accessing the data: either layer contiguous or tile contiguous;

Note: The internal tile arrangement should support an easy navigation inside the CORE video format, depending on the use case.

4) a CORE file is optimised for streaming with the moov atom at the beginning of the file (e.g. with -movflags faststart) and optional additional optimisations depending on the codec used (e.g. -tune fastdecode -tune zerolatency for H.264)

5) metadata tags inside the moov atom for describing and using geographic image data (that are preferably compatible with the [OGC GeoTIFF standard](https://www.ogc.org/standards/geotiff) or any future standard accepted by the geospatial community) as well as list of original file names corresponding to each CORE layer

6) it needs to encode similar source rasters (such as time series of rasters with the same extent and resolution, or different tiles of the same product; each input raster should be having the same image and pixel size)

7) it provides a mechanism for addressing and requesting overviews (lower resolution data) for a fast display in web browser depending on the map scale (currently external overviews)

Major issues to be solved:

- Internal overviews (similar to COG), by chaining lower resolution videos in the same MP4 container for fast access to overviews first); Currently, overviews are kept as separate files, as external overviews.

- Metadata encoding (how to best encode spatial extent, layer names, and so on, for each of the layer inside the series, which may have a different geographical extent, etc...; Known issues: adding too many tags with FFmpeg which are not part of the standard MP4 moov atom; metadata tags have a limited string length.

- Applicability beyond RGB/Byte datasets; defining a standard way of converting cell values from Int16/UInt16/UInt32/Int32/Float32/Float64/ data types into multi-band Byte values (and reconstructing them back to the original data type within acceptable thresholds)

Example

Notice: The provided CORE (.mp4) examples contain modified Copernicus Sentinel data [2018-2021].

For generating the CORE examples provided, 50 original Sentinel 2 (S-2) TCI data images from an area located inside Switzerland were downloaded from www.copernicus.eu, and then transformed into CORE format using ffmpeg with H.264 encoding using the [x264 library](https://www.videolan.org/developers/x264.html).

For full reproducibility, we provide the original data set and results, as well scripts for data encoding and extraction (see resources).

core

display_name: core

geodata

display_name: geodata

gridded-data

display_name: gridded-data

raster

display_name: raster

research-data-management

display_name: research-data-management

time-series

display_name: time-series

video-encoding

display_name: video-encoding


maintainer: Yohann Chauvier

en: independent-dataset survey-effort plant-species point-process-model covariate-correction background-data environmental-stratification cluster random-stratified-sampling target-group

en: Non-copyright data, scripts, diversity outputs

en:
Aim: While species distribution models (SDMs) are standard tools to predict species distributions, they can suffer from observation and sampling biases, particularly presence-only SDMs that often rely on species observations from non-standardized sampling efforts. To address this issue, sampling background points with a target-group strategy is commonly used, although more robust strategies and refinements could be implemented. Here, we exploited a dataset of plant species from the European Alps to propose and demonstrate efficient ways to correct for observer and sampling bias in presence-only models.

Innovation: Recent methods correct for observer bias by using covariates related to accessibility in model calibrations (classic bias covariate correction, Classic-BCC). However, depending on how species are sampled, accessibility covariates may not sufficiently capture observer bias. Here, we introduced BCCs more directly related to sampling effort, as well as a novel corrective method based on stratified resampling of the observational dataset before model calibration (environmental bias correction, EBC). We compared, individually and jointly, the effect of EBC and different BCC strategies, when modelling the distributions of 1’900 plant species. We evaluated model performance with spatial block split-sampling and independent test data, and assessed the accuracy of plant diversity predictions across the European Alps.

Main conclusions: Implementing EBC with BCC showed best results for every evaluation method. Particularly, adding the observation density of a target group as bias covariate (Target-BCC) displayed most realistic modelled species distributions, with a clear positive correlation (r≃0.5) found between predicted and expert-based species richness. Although EBC must be carefully implemented in a species-specific manner, such limitations may be addressed via automated diagnostics included in a provided R function. Implementing EBC and bias covariate correction together may allow future studies to address efficiently observer bias in presence-only models, and overcome the standard need of an independent test dataset for model evaluation.

background-data

display_name: background-data

cluster

display_name: cluster

covariate-correction

display_name: covariate-correction

environmental-stratification

display_name: environmental-stratification

independent-dataset

display_name: independent-dataset

plant-species

display_name: plant-species

point-process-model

display_name: point-process-model

random-stratified-sampling

display_name: random-stratified-sampling

survey-effort

display_name: survey-effort

target-group

display_name: target-group

en: Novel methods to correct for observer and sampling bias in presence-only species distribution models


en: phytochemistry herbivory climate-change fagus-sylvatica drought-legacy

en:
What are the research data files about:
Raw data on various beech (Fagus sylvatica) leaf traits. Beech leaf chemistry (primary and specialized metabolites), leaf damage measurements from various herbivore feeding guilds and crown health assessment

Which methods were used:
Field surveys on trees that showed either prematured defoliation due to drought-stress or showed not pre-mature defoliation. .

When and where was the data collected/analyzed:
Field data was collected in 2019, 2020
Data was analyzed in 2021-2023

climate-change

display_name: climate-change

drought-legacy

display_name: drought-legacy

fagus-sylvatica

display_name: fagus-sylvatica

herbivory

display_name: herbivory

phytochemistry

display_name: phytochemistry

en: Legacy effects of premature defoliation in response to an extreme drought event modulate phytochemical profiles with subtle consequences for leaf herbivory in European beech


maintainer: Chunhong Zhao

en: land-dynamics urban-morphology land-use austin landscape

en: Land use dynamics in Austin since 1992

en: The present dataset is part of the published scientific paper Zhao C, Weng Q, Hersperger A M. Characterizing the 3-D urban morphology transformation to understand urban-form dynamics: a case study of Austin, Texas, USA. Landscape and urban planning, 2020, 203:103881. The overall objective of this paper is to understand urban form dynamics in the Austin metropolitan area for the periods 2006–2011 and 2011–2016. The study also aims to understand to what extent the changes in the built environment (in terms of ‘efficient growth’ versus ‘inefficient growth’) from the 1990s to 2016 in the Austin metropolitan area corresponded with ‘compact and efficient growth’ planning policy documents. The UMT distribution can be found in the paper. The area of transitioning UMT was provided in Table 2 and Table 3 can be found in the Appendix of the paper. A protocol was developed to perform the content analysis of the strategic plans and gather the data. The detailed list of protocol items can be found in Appendix B of the paper. This study demonstrates the advantage of applying Lidar data to characterize 3-D urban morphology type (UMT) transition and understand its dynamics, which helps develop a comprehensive understanding of the urbanization process and provides a tool for planning intentions and policies evaluation on urban development over time. The UMT maps can be found in Appendix A of the paper. The Lidar point datasets and the 30 × 30 m National Land Cover Database (NLCD) are the two main data sources of UMT mapping. Lidar datasets were gathered from different projects that had been conducted and collected by state agencies and other organizations between 2007 and 2017. Table A1 in the appendix in the paper shows the accuracies and acquisition parameters of the Lidar projects from 2007 to 2017. Land use/cover dynamics in Austin metropolitan area dataset provides Land use/cover patterns in the years 1992, 2001, 2004, 2006, 2008, 2011, 2013, 2016 with a spatial resolution of 30 meters. Since NLCD 1992 used a different classification system for the urban land classes, we first reclassified the NLCD 1992 using a customized Arcpy package.

austin

display_name: austin

land-dynamics

display_name: land-dynamics

land-use

display_name: land-use

landscape

display_name: landscape

urban-morphology

display_name: urban-morphology

educ

en: Education, culture and sport

en: Land use/cover dynamics in Austin metropolitan area since 1992


en: hymenoptera wasps cities performance-traits hymennoptera richness cavity-nesting bees urban-ecology urbanization life-history-traits natural-enemies

en: Taxonomic metrics on CNBW

en:
The data contains at the site level the species richness of cavity-nesting bees and wasps. It also contains site level estimates of the life-history traits and the performance traits.

We calculated species richness, abundance, and number of nests of the hatched hosts separately for bees and wasps. We calculated the abundance of hatched hosts as the number of brood cells where an individual emerged, i.e. the total number of brood cells minus the number of parasitized cells and the number of cells with no emergence for reasons other than parasitism.

City codes: An =Antwerp, Pa = Paris; Po = Poznan; Ta =Tartu; Zu= Zurich

en: Taxonomic metrics on the natural enemies

en: It contains the species richness and the abundance of natural enemies per site.

en: Information on the study sites

en: For each site, the IDs, city, coordinates, structure where the trapnest was attached and height is provided

en: Performance traits and life-history traits

en:
It contains the data of two performance traits (survival and parasitism) and two life-history traits (sex ratio and number of offspring per nest for the hosts) at the nest level.

We assessed performance traits, i.e. survival and parasitism, at the individual cell level. Specifically, for each cell within a nest, we noted whether the cell was alive or dead (survival), and whether it had a parasite or not (parasitism). Further, we calculated the parasitism rate as the number of cells with a parasite divided by the total number of cells. Concerning life-history traits, we calculated the total number of brood cells per nest as the total number of brood cells within a single nest, regardless of whether the larvae were dead, alive or parasitized. Finally, we used the probability that a femalehost emerged from a given cell as a proxy for the sex ratio. To do so, we first identified the sex of the individual hosts. Then, we noted it in a binary way to indicate whether the host was a female or not. We could identify the sex of all hatched hosts. Further, because CNBW first lay females and then males, on some occasions we could also identify the host sex in dead and parasitized cells, that is, when we had already identified the sex of the preceding and the following cells.

en: Predictors of the study

en:
 Background
Urban ecosystems are associated with socio-ecological conditions that can filter and promote taxa. However, the strength of the effect of ecological filtering on biodiversity could vary among biotic and abiotic factors. Here, we provide the data used to investigate the effects of habitat amount, temperature, and host-enemy biotic interactions in shaping communities of cavity-nesting bees and wasps (CNBW) and their natural enemies. To do so, we installed trap-nests in 80 sites distributed along urban intensity gradients in 5 European cities (Antwerp, Paris, Poznan, Tartu and Zurich). We quantified the species richness and abundance of CNBW hosts and their natural enemies, as well as two performance traits (survival and parasitism) and two life-history traits (sex ratio and number of offspring per nest for the hosts).
The dataset contains:
* The taxonomic metrics on CNBW
* The taxonomic metrics on the natural enemies from CNBW
* The life-history traits and performance traits

bees

display_name: bees

cavity-nesting

display_name: cavity-nesting

cities

display_name: cities

hymennoptera

display_name: hymennoptera

hymenoptera

display_name: hymenoptera

life-history-traits

display_name: life-history-traits

natural-enemies

display_name: natural-enemies

performance-traits

display_name: performance-traits

richness

display_name: richness

urban-ecology

display_name: urban-ecology

urbanization

display_name: urbanization

wasps

display_name: wasps

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: Community structure, life-history traits and performance traits of urban cavity-nesting bees annd wasps


en: belowground-biomass afforestation picea-abies subalpine isotopes

en: This data set provides soil organic carbon, total nitrogen, and stable carbon isotope (13C) values of mineral soil (0-45cm), organic horizons (Oi, Oe, Oa), and root biomass of an afforestation sequence (0-130years) on a subalpine pasture in Jaun, Switzerland.

afforestation

display_name: afforestation

belowground-biomass

display_name: belowground-biomass

isotopes

display_name: isotopes

picea-abies

display_name: picea-abies

subalpine

display_name: subalpine

en: Soil organic carbon stock of an afforestation sequence on a subalpine pasture


maintainer: Adam Winstral

en: snow-simulation snow jim jules-investigation-model snow-depth

en: DEM

en: 1-km resolution DEM used for downscaling gridded NWP data to stations and for distributing BDE evaluations at HS-stations to SWE-stations

mimetype: text/plain

en: HS and SWE observations

en: Automated (HS) and manual (SWE) data used to evaluate model simulations

en: Station forcing data

en: All forcing data need to run JIM at HS and SWE stations. These are data downscaled directly from COSMO NWP data (WY14, WY15) and further enhanced by additional station observations of snow depth (HS) and air temperature (Ta) in WY17. Further information can be found in README file. Note that in WY14 and WY15, shortwave radiation was not split into direct and diffuse (not necessary for JIM) and that the default method in JIM for splitting precipitation phase was used. In WY 17, direct and diffuse were combined as input to JIM and JIM was forced with pre-processed liquid and solid precipitation phases.

en: File/data descriptor

en: These data were used to drive and evaluate Jules Investigation Model (JIM) snow simulations. The data provided are the forcing data used for the "deterministic" runs as described in Winstral et al., 2019. The bias-detecting ensemble (Winstral et al., 2019) used observed snow depths (HS) to detect biases in these deterministic simulations related to precipitation and energy inputs to JIM. Simulations that included the BDE evaluations substantially improved JIM simulations.

jim

display_name: jim

jules-investigation-model

display_name: jules-investigation-model

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-simulation

display_name: snow-simulation

educ

en: Education, culture and sport

en: Meteorological data used to develop and validate the bias-detecting ensemble (BDE)


data-broedlin-cnp

title_for_slug: data-broedlin-cnp

en: dissolved-organic-matter carbon drying-rewetting forest nitrogen mineralization phosphorus stoichiometry soil

en: Data Broedlin-CNP

en: Data Broedlin-CNP-Release

en: Raw data of C-N-P mobilization experiment from Oi, Oe/Oa, and A horizons of beech forest soils along a nutrient availability gradient.

en: Mircocosm experiment to identify the individual patterns and controls of C, N, and P mobilization in soils under beech forests. Organic and mineral horizons sampled along a nutrient availability gradient in Germany were exposed to either permanent moist conditions or to dry spells in microcosms and quantified the release of inorganic and organic C, N, and P.

carbon

display_name: carbon

dissolved-organic-matter

display_name: dissolved-organic-matter

drying-rewetting

display_name: drying-rewetting

forest

display_name: forest

mineralization

display_name: mineralization

nitrogen

display_name: nitrogen

phosphorus

display_name: phosphorus

soil

display_name: soil

stoichiometry

display_name: stoichiometry

envidat

en: EnviDat: the Environmental Data Portal

en: Data Broedlin CNP