name: Direction générale de l'office médico-pédagogique

fr: L'Office médico-pédagogique (OMP) est reconnu par la Direction générale de la santé comme un établissement médical public, qui assure des soins psychiques destinées aux mineurs scolarisés dans les établissements publics ou résidant dans le canton de Genève. Le pôle médico-psychologique couvre dans ce cadre les prestations de soins, de promotion et de prévention de la santé (consultations, centres et interventions en milieu scolaire). Les consultations de l'OMP proposent une aide aux enfants et adolescents rencontrant des difficultés médico-psychologiques, logopédiques ou de psychomotricité.

fr: Pôle médico-psychologique de l'Office médico-pédagogique

heal

fr: Santé

fr: GML

fr: KML


$oid: OBSOLETE

fr: BiblioDIP, le réseau des bibliothèques scolaires, regroupe l'ensemble des bibliothèques scolaires du département de la formation et de la jeunesse (DFJ), du SEM Documentation et de la Cité des métiers. Les bibliothèques du réseau partagent un catalogue collectif géré avec le logiciel Flora et accessible via son portail.

canton-geneve

approval_status: approved

fr: Le canton de Genève s'est engagé dans une démarche d’ouverture des données publiques depuis plusieurs années. Sur ce portail, vous trouvez toutes les données provenant de l'administration cantonale genevoise qui répondent aux principes de l'Open Government Data, ainsi que les géodonnées OpenData du Système d’Information du Territoire à Genève (SITG).

de: Der Kanton Genf verfolgt seit einigen Jahren eine Open Data Strategie. Auf diesem Portal finden Sie Daten aus der kantonalen Verwaltung die die Prinzipien des Open Government Data erfüllen, sowie sämtliche "Open-Geodaten" des Genfer Geoinformationssystems (SITG). ***Die Datensätze finden Sie unter der betreffenden Organisation***

en: The canton of Geneva has been committed to making public data open for a few years now. On this portal, you will find all the data from the Geneva cantonal administration that meet the principles of Open Government Data, as well as geodata from the geographic information system of Geneva (SITG) that fall under the OpenData policy.

it: Il cantone di Ginevra si è impegnato in un processo di apertura dei dati pubblici per diversi anni. Su questo portale, è possibile trovare tutti i dati dell'amministrazione del cantone di Ginevra che soddisfano i principi del Open Government Data, inoltre ai geodati OpenData del Sistema Informativo Territoriale di Ginevra (SITG).

de: Kanton Genf

en: Canton of Geneva

fr: Canton de Genève

it: Cantone di Ginevra

political_level: canton

state: active

type: organization

fr: Service écoles-médias

de: geocat.ch Permalink

fr: geocat.ch permalien

it: geocat.ch link permanente

en: geocat.ch permalink

spatial: GE

fr: BiblioDIP : Réseau des bibliothèques scolaires

type: dataset

soci

de: Bevölkerung und Gesellschaft

en: Population and society

fr: Population et société

it: Popolazione e società

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

fr: Éducation, culture et sport

it: Istruzione, cultura e sport

format: API

format: WFS

format: WMS

fr: Serveur de fichiers Opendata

fr: CSV

format: CSV

media_type: text/csv

fr: GDB

format: ZIP

format: GML

format: KML

fr: SHP

format: SHP

value: GEOCAT canton GE


name: Direction générale de l'enseignement secondaire II

fr: Localisation des écoles de commerce

fr: Ecoles de commerce


name: Direction générale de l'enseignement obligatoire

fr: L'école primaire constitue la première étape de la scolarité obligatoire. Elle concerne les élèves de 4 à 12 ans et se décline sur huit années de scolarité réparties en deux cycles : - le cycle élémentaire (CE) des années1P à 4P pour les élèves de 4 à 8 ans - le cycle moyen (CM) des années 5P à 8P pour les élèves de 8 à 12 ans. Les objectifs d'apprentissage, fixés par le Plan d'études romand, cherchent à développer chez les élèves leur personnalité, leur créativité ainsi que leurs aptitudes intellectuelles, manuelles, physiques et artistiques. Le principe d'une école inclusive vise à offrir à chaque élève l'environnement scolaire le plus adapté lui permettant de maximiser son potentiel, quels que soient ses besoins, son handicap, son talent, son origine et ses conditions de vie économiques et sociales. La lutte contre l'échec scolaire, notamment avec le réseau d'enseignement prioritaire, et l'intégration des élèves allophones, notamment par les classes d'accueil, sont des priorités majeures poursuivies dès la première année d'école.

fr: Ecoles primaires (bâtiments)


fr: L'enseignement spécialisé s'adresse à des élèves de 4 à 20 ans. Il offre une scolarisation et un encadrement adaptés aux besoins des élèves présentant des handicaps et/ou des besoins éducatifs particuliers. Les élèves bénéficient d'un programme d'apprentissage et de développement individualisé, qui tient compte de leurs particularités et de leurs besoins. Les élèves qui fréquentent l'enseignement spécialisé présentent des handicaps et/ou des difficultés importantes d'apprentissage et de développement.

fr: Direction générale de l'office médico-pédagogique

fr: Enseignement spécialisé

fr: GML

fr: KML


fr: Localisation des écoles de culture générale

canton-geneve

fr: Le canton de Genève s'est engagé dans une démarche d’ouverture des données publiques depuis plusieurs années. Sur ce portail, vous trouvez toutes les données provenant de l'administration cantonale genevoise qui répondent aux principes de l'Open Government Data, ainsi que les géodonnées OpenData du Système d’Information du Territoire à Genève (SITG).

fr: Canton de Genève

fr: Direction générale de l'enseignement secondaire II

fr: geocat.ch permalien

fr: Ecoles de culture générale


fr: Direction générale de l'enseignement obligatoire

fr: Ecoles primaires (points)

soci

fr: Population et société

educ

fr: Éducation, culture et sport

fr: Serveur de fichiers Opendata

fr: CSV

fr: GDB


fr: Localisation des collèges

fr: Collèges

fr: SHP


fr: Établissements des diverses facultés de l'enseignement Universitaire

fr: Université de Genève

fr: Universités

fr: GML

fr: KML


fr: Établissements délivrant une formation professionnelle ouvrant les portes de professions variées et pointues. Elle passe par un apprentissage en entreprise (système dual) ou en école (système plein temps).

canton-geneve

fr: Le canton de Genève s'est engagé dans une démarche d’ouverture des données publiques depuis plusieurs années. Sur ce portail, vous trouvez toutes les données provenant de l'administration cantonale genevoise qui répondent aux principes de l'Open Government Data, ainsi que les géodonnées OpenData du Système d’Information du Territoire à Genève (SITG).

fr: Canton de Genève

fr: Direction générale de l'enseignement secondaire II

fr: geocat.ch permalien

fr: Formation professionnelle


fr: Le cycle d'orientation regroupe les années de scolarité 9, 10 et 11 Harmos (ex- 7, 8 et 9) de la scolarité obligatoire. Il représente le secondaire I. Il dispense un enseignement de culture générale et vise à développer l'ouverture d'esprit, la faculté de discernement, l'autonomie, la solidarité, toutes compétences qui contribuent à l'éducation citoyenne. A l'articulation entre l'école primaire et le secondaire II, il assure un équilibre dans le développement des différentes aptitudes (intellectuelles, manuelles, physiques et artistiques) des adolescentes et des adolescents, qui leur permet de trouver du sens dans leurs apprentissages et leur donne progressivement les éléments de choix pour leur parcours de formation. Les périmètres administratifs de cette classe d'objet, servent d'aide à la décision lors de chaque nouvelle répartition scolaire.

fr: Direction générale de l'enseignement obligatoire

fr: Cycles d'orientation (points)

soci

fr: Population et société

educ

fr: Éducation, culture et sport

fr: Serveur de fichiers Opendata


de: Abschlüsse von Lernenden aus Liechtenstein, bei Jahr, Bildungsfeld, Geschlecht und Abschluss

en: Graduates of apprentices from Liechtenstein by Year, Field of education, Sex and Graduation

amt-fuer-statistik-fl

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

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

de: Amt für Statistik

en: Office of Statistics

political_level: other

liechtenstein

capacity: public

de: Abschlüsse von Lernenden aus Liechtenstein, nach Bildungsfeld und Geschlecht seit 2015

en: Graduates of apprentices from Liechtenstein by fields of education and sex since 2015

key: guid

key: uri

value: DCAT Harvester Amt für Statistik FL

en: Data structure in German

de: Datenstruktur auf Deutsch

format: JSON

media_type: application/json

de: Datenwürfel auf Englisch

en: Data cube in English

format: HTML

media_type: text/html

en: Data structure in English

de: Datenstruktur auf Englisch

de: Datenwürfel auf Deutsch

en: Data cube in German

berufliche-grundbildung

display_name: berufliche-grundbildung

vocational-education-and-training

display_name: vocational-education-and-training


de: Number of training companies in Liechtenstein bei Jahr und Gemeinde

en: Number of training companies in Liechtenstein by municipality since 2010/11


de: Training companies in Liechtenstein bei Jahr und Lehrbetriebsgrösse

en: Training companies in Liechtenstein by number of apprentices since 2010/11


de: Lernende aus Liechtenstein bei Jahr, Lehrbetriebsland, Bildungsfeld, Geschlecht und Lehrjahr

en: Apprentices from Liechtenstein by Year, Country of company, Field of education, Sex and Training year

de: Lernende aus Liechtenstein nach Lehrbetriebsland, Bildungsfeld, Lehrjahr und Geschlecht seit 2014/15

en: Apprentices from Liechtenstein by country of company, field of education, training year and sex since 2014/15


de: Lernende aus Liechtenstein mit Berufsmaturität (BMS I) bei Jahr, Bildungsfeld und Geschlecht

en: Apprentices from Liechtenstein with vocational baccalaureate by Year, Field of education and Sex

de: Lernende aus Liechtenstein mit Berufsmaturität (BMS I) nach Jahr, Bildungsfeld und Geschlecht seit 2010/11

en: Apprentices from Liechtenstein with vocational baccalaureate by year, field of education and sex since 2010/11


de: Abschlüsse von Lernenden in Liechtenstein bei Jahr, Bildungsfeld, Geschlecht und Abschluss

en: Graduates of apprentices in Liechtenstein by Year, Field of education, Sex and Graduation

de: Abschlüsse von Lernenden in Liechtenstein nach Bildungsfeld und Geschlecht seit 2015

en: Graduates of apprentices in Liechtenstein by fields and sex since 2015


de: Lernende in Liechtenstein bei Jahr, Bildungsfeld, Geschlecht und Wohnland

en: Apprentices in Liechtenstein by Year, Field of education, Sex and Country of residence

de: Lernende in Liechtenstein nach Bildungsfeld, Wohnland und Geschlecht seit 2014/15

en: Apprentices in Liechtenstein by field of education, country of residence and sex since 2014/15


de: Lernende in Liechtenstein mit Berufsmaturität (BMS I) bei Jahr, Bildungsfeld, Geschlecht und Wohnland

en: Apprentices in Liechtenstein with vocational baccalaureate by Year, Field of education, Sex and Country of residence

amt-fuer-statistik-fl

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

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

de: Lernende in Liechtenstein mit Berufsmaturität (BMS I) nach Bildungsfeld, Wohnland und Geschlecht seit 2014/15

en: Apprentices in Liechtenstein with vocational baccalaureate by field of education, country of residence and sex since 2014/15


en:
This data set includes 589 snow profile observations including a rutschblock test, observations of signs of instability and an assessment of the local avalanche danger level, mainly recorded in the region of Davos (eastern Swiss Alps) during the winter seasons 2001-2002 to 2018-2019.
These data were analyzed and results published by Schweizer et al. (2021). They characterized the avalanche danger levels based on signs of instability (whumpfs, shooting cracks, recent avalanches), snow stability class and new snow height.
The data are provided in a csv file (589 records); the variables are described in the corresponding read-me file.
These data are the basis of the following publication: Schweizer, J., Mitterer, C., Reuter, B., and Techel, F.: Avalanche danger level characteristics from field observations of snow instability, Cryosphere, 15, 3293-3315, https://doi.org/10.5194/tc-15-3293-2021, 2021.
 Acknowlegements
Many of the data were recorded by SLF observers and staff members, among those Roland Meister, Stephan Harvey, Lukas Dürr, Marcia Phillips, Christine Pielmeier and Thomas Stucki. Their contribution is gratefully acknowledged.

en: snow snow-instability avalanche-danger avalanche danger-level avalanche-forecasting

envidat

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

de: EnviDat

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: Field observations of snow instabilities
    Size: 107300 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/321f2050-93be-4772-b5d8-562f46658256/resource/5927f50c-3a33-4ceb-91bf-d583efd14cfe/download/snow_instability_field_data.csv
    Description: This data set includes 589 snow profile observations including a rutschblock test, observations of signs of instability and an assessment of the local avalanche danger level, mainly recorded in the region of Davos (eastern Swiss Alps) during the winter seasons 2001-2002 to 2018-2019.

en:
Resource Title: Read-me file
    Size: 133885 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/321f2050-93be-4772-b5d8-562f46658256/resource/b3aeef4d-1b54-467c-88b4-4d2da8076885/download/read-me.pdf
    Description: This read-me file contains the descriptions of the variables.

format: PDF

media_type: application/pdf

avalanche

display_name: avalanche

avalanche-danger

display_name: avalanche-danger

avalanche-forecasting

display_name: avalanche-forecasting

danger-level

display_name: danger-level

snow

display_name: snow

snow-instability

display_name: snow-instability


en:
Atmospheric drought (high vapor pressure deficit, VPD) and soil drought frequently co-occur, yet plants respond to these stressors through partially distinct physiological pathways, potentially altering source (photosynthesis) and sink (growth and respiration) activities. Despite significant advances in understanding drought impacts on photosynthesis and plant hydraulics, the independent and interactive effects of soil vs. atmospheric drought on whole-tree carbon balance, including non-structural carbohydrate (NSC) dynamics, allocation priorities, and growth, remain insufficiently understood.
This project aims to disentangle the effects of soil and atmospheric droughts on tree sink and source dynamics in European forests, by studying leaf-to-whole-tree ecophysiological processes that drive growth, carbon sequestration and tree mortality. Research will primarily be conducted in Pfynwald (Valais, Switzerland), as part of the VPDrought experiment, where mature Scots pines (Pinus sylvestris) are exposed to increased soil drought and reduced VPD.
Our study addresses the research question: how do soil and atmospheric droughts differentially affect tree carbon uptake and allocation to growth? We hypothesize that atmospheric drought primarily limits carbon assimilation via stomatal closure, leading to reduced growth and respiration (sink activity), whereas soil drought suppresses both carbon uptake (source activity) and sink strength (growth and respiration), leading to stronger shifts in carbon allocation and early reductions in sink demand. Soil drought restricts carbon transport to belowground sinks, while atmospheric drought promotes NSC accumulation in source tissues due to stomatal closure and reduced sink demand.
**Methods:**
Four campaigns (~4 days each) will be conducted at VPDrought during the summer of 2026-2028, covering four experimental treatments: 1) soil drought + ambient air, 2) soil drought + reduced VPD, 3) irrigation + ambient air, 4) irrigation + reduced VPD. Each treatment will include 6-9 replicates.
During the campaigns, gas exchange measurements will be performed, including net photosynthesis, stomatal conductance, temperature responses of photosynthesis and respiration, and A/Ci curves, using three LI-COR systems (LI-6800). Twig water potential (pre-dawn and midday) will be measured with a Scholander pressure chamber (PMS, model 1505D). Twig, needles, and root samples will be collected across treatments for non-structural carbohydrate (NSC) analyses. Stem respiration measurements will be taken using a custom-made chamber and analyzed with the LI-COR (LI-8100A). In addition, stem radial growth (measured with dendrometers) and leaf area development (using Lidar measurements) will be utilized as proxies for sink activity and carbon allocation to structural growth.  Measurements will be repeated across all years, with additional assessments in 2027 and 2028, including resin flow and phloem transport efficiency using a 13C pulse labeling approach.

en: soil-drought vpd gas-exchange carbon-dynamics pinus-sylvestris

en: Carbon balance under dual droughts: Disentangling the effects of soil and atmospheric moisture on tree sink and source dynamics in European forests.

format: TXT

carbon-dynamics

display_name: carbon-dynamics

gas-exchange

display_name: gas-exchange

pinus-sylvestris

display_name: pinus-sylvestris

soil-drought

display_name: soil-drought

vpd

display_name: vpd


en:
The dataset includes spatially aggregated canopy temperature measurements (°C) of one to two tree crowns obtained using infrared (IR) point sensors.
The dataset was quality screened using a multi-step outlier detection procedure based on Median Absolute Deviation (MAD) statistics within a defined analysis period (= 1 year).
**Three complementary quality-control checks were applied**:
1\. Global MAD screening – detects observations that strongly deviate from the overall distribution of each individual sensor time series.
2\. Local spike detection – identifies short-term anomalous spikes within each sensor time series using rolling median and rolling MAD statistics.
3\. Cross-sensor consistency screening – compares measurements across all sensors recorded at the same timestamp to identify extreme deviations relative to the network-wide median behaviour.
Each observation received individual QC flags for all three checks, followed by a combined final quality flag. Observations passing all criteria were labelled as `good`, while flagged observations were labelled as `outlier` if considered suspect, or as `bad` if associated with known sensor drifts. Observations labelled as `outlier` may still represent physically plausible values, while observations labelled as `bad` should not be considered for further analysis. All observations were retained in the exported dataset for traceability.

en: pfynwald heat-stress transpiration irrigation pinus-sylvestris ir-sensor cooling vpdrought

en: Pfynwald VPDrought experiment canopy temperature parameter

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_1min_2025.zip
    Size: 50905903 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/3ed284f7-5ca4-4b25-9441-00722b92e58d/download/pfynwald_vpdrought_canopy_temperature_1min_2025.zip
    Description:

media_type: application/zip

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_10min_2024.zip
    Size: 5872908 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/212221fb-14a0-4157-97e9-1670e221959d/download/pfynwald_vpdrought_canopy_temperature_10min_2024.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_10min_2025.zip
    Size: 5833672 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/66747b91-d345-4e98-97c7-9d7b3ce92266/download/pfynwald_vpdrought_canopy_temperature_10min_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_1min_2024.zip
    Size: 51370310 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/966309dc-3bf5-4bbc-9964-6af79bf294fd/download/pfynwald_vpdrought_canopy_temperature_1min_2024.zip
    Description:

cooling

display_name: cooling

heat-stress

display_name: heat-stress

ir-sensor

display_name: ir-sensor

irrigation

display_name: irrigation

pfynwald

display_name: pfynwald

transpiration

display_name: transpiration

vpdrought

display_name: vpdrought


en:
The dataset refers to samples collected across 6 farms in the Bega Valley region of Australia. The farms are located in the grassy woodland ecoregion and are extensively managed with sheep and cattle grazing. Livestock shares the landscape with native mammalian and invertebrate herbivores. On each farm, two nested fenced exclosure systems were established. These included an open area, a fence excluding livestock but allowing access to native mammals and invertebrates and a fence excluding all mammals but allowing access to invertebrates. In each farm, one of these systems was located in a zone dominated by the native Kangaroo grass, and another in a zone co-dominated by the Invasive African lovegrass. The sample and treatment numbering, as well as a summary of the aggregated indicators is provided in the file Indicator_summary.
Leaf swab s(phyllosphere) samples were taken and DNA was extracted and amplified for 16s and ITS markers. The resulting metabarcoding derived tables are presented (Bacteria_swabs and Fungi_swabs respectively), as are the inferred functional profiles for bacteria at the pathway level (PICRUSt2_pathways), as derived by the PICRUSt2 pipeline.
Two 20 by 100 cm strips had their vegetation removed and their living and litter biomass quantified by dry weight (Biomass). Sensors measuring temperature 10 cm above the soil surface were installed in each plot and their output is presented in Climate. Invertebrates were collected with both pitfall traps and sweepnets and the counts for both sampling techniques can be found in Invertebrates. Damage scores across different categories were collected on 5 leaves of the two species in each plot and the average scores can be found in Leaf_damage.

en: grassland invertebrates biological-invasions herbivore-exclusion phyllosphere

en: Herbivory disrupts invasion_associated phyllosphere and arthropod community shifts in grasslands

en:
Resource Title: Biomass.csv
    Size: 3031 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/ac6aecef-5a8d-4539-b231-3403691fc3f9/download/biomass.csv
    Description: Dry biomass weight of collected plant material

en:
Resource Title: Invertebrates.csv
    Size: 18842 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/493ae610-9929-4499-8dfb-fdb7c8feafed/download/invertebrates.csv
    Description: Counts of invertebrates collected with pitfall traps and sweepnets

en:
Resource Title: Leaf_damage.csv
    Size: 2007 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/5c2f7e5f-cc22-4ac6-aa16-f3ef13d27ea7/download/leaf_damage.csv
    Description: Aggregated leaf damage scores for African lovegrass and Kangaroo grass

en:
Resource Title: PICRUSt2.csv
    Size: 469821 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/665f8907-396a-4b1e-b564-fa100a2b5968/download/picrust2.csv
    Description: Predicted pathway profiles of sampled phyllosphere bacterial communities

en:
Resource Title: Indicator_summary.csv
    Size: 19067 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/d68e884c-0153-4d0f-95c6-eb5702972cce/download/indicator_summary.csv
    Description: Sample metadata and aggregate indicators

en:
Resource Title: Fungi_swabs.csv
    Size: 1059062 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/02fb3082-a33e-4af4-8ea1-d4c4953eec4e/download/fungi_swabs.csv
    Description: OTU table of fungal phyllosphere communities

en:
Resource Title: Climate.csv
    Size: 5096079 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/787a3947-a316-4ac5-aeda-ffacfd832bed/download/climate.csv
    Description: Sensor collected soil surface temperatures

en:
Resource Title: Bacteria_swabs.csv
    Size: 1153434 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/f97a1423-4749-45fa-a07e-93697dd72676/download/bacteria_swabs.csv
    Description: OTU table of bacterial phyllosphere communities

biological-invasions

display_name: biological-invasions

grassland

display_name: grassland

herbivore-exclusion

display_name: herbivore-exclusion

invertebrates

display_name: invertebrates

phyllosphere

display_name: phyllosphere


en:
Dataset content
Continuous soil measurements (10-min resolution) from the Pfynwald long-term irrigation experiment, covering five treatments: **control, irrigation, irrigation+VPD, roof, roof+VPD**.
Measurements were taken at multiple plots and at three depths (-0.1, -0.8, -1.2 m below soil surface).
Sensors include TEROS-21 (matric potential), TEROS-12 (volumetric water content), TEROS-21 (soil temperature), and TEROS-12 (electrical conductivity).
 Processing steps
**1. Raw retrieval** from the LWF database (`ada.v_messvar`, project `Pfynwald irrigation`), 10-min cadence.
**2. Range filtering** to remove physically implausible values:
   - SWP: drop values ≥ 0 kPa or ≤ −8000 kPa
   - VWC: drop values ≤ 0 or - 0.8 m³/m³
   - TEM: drop values - 40 °C or - −20 °C
**3. Duplicate aggregation** within the same 10-min timestamp by mean (median for SWP).
**4. Temperature correction (SWP_TC)**: matric potential is temperature-corrected using the TEROS-21 manufacturer equation referenced to T_ref = 20 °C:
   - Convert SWP (kPa) to head h = |SWP|·10.197, then pF = log10(h)
   - ΔpF = (919.890694·ΔT − 6.945352·ΔT²)·exp(−150.754657 / (pF + 9.153084))
   - SWP_TC = −10^(pF + ΔpF) / 10.197
**5. No gap filling applied.** Missing values remain absent from the delivered CSV.
 Methods
- Database query and aggregation: R, `data.table`, `rLWFpg`
- Temperature correction: in-house implementation of TEROS-21 manufacturer formula
- See repository / script reference below
 Limitations
- Values flagged out of range during step 2 are absent (not interpolated)
- Winter periods may include frozen-soil readings — these pass the range filter as physical sensor outputs but should be interpreted with caution by downstream users
- SWP_TC rows carry the messvar_id of the underlying SWP sensor; the corresponding TEM sensor used for correction is paired via site/plot/depth/datetime but not encoded in the messvar_id
- Sensor calibration uses manufacturer defaults; site-specific calibration was not performed
- Roofs were installed in spring 2024. Readings under "roof" / "roof_vpd" treatments before that reflect ambient conditions, not the experimental treatment.
- In 2025, three additional TEROS-21 sensors were added per roofed treatment at 10 cm depth to obtain a balanced sample relative to roof position (under panels, at panel edges, and in inter-panel gaps).
  This expansion means roofed treatments have six positions at 10 cm from 2025 onward, compared to three before.

en: teros-12 soil-moisture electrical-conductivity irrigation-manipulation teros-21 vpdrought water-potential pfynwald soil-temperature drought-experiment irrigation pinus-sylvestris

envidat

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

en: EnviDat: the Environmental Data Portal

en: Pfynwald VPDrought experiment soil parameters

envi

en: Environment

en:
Resource Title: pfynwald_vpdrought_soil_10Minutes_2024.zip
    Size: 59025329 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/12bc2274-e48f-4ff1-8961-b86699aaa450/resource/3606ad5b-f308-4bfc-8aa4-db5b017ee47a/download/pfynwald_vpdrought_soil_10minutes_2024.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_soil_10Minutes_2025.zip
    Size: 66201780 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/12bc2274-e48f-4ff1-8961-b86699aaa450/resource/edaa3e3a-1045-4d2f-952f-e23689c20bb9/download/pfynwald_vpdrought_soil_10minutes_2025.zip
    Description:

drought-experiment

display_name: drought-experiment

electrical-conductivity

display_name: electrical-conductivity

irrigation-manipulation

display_name: irrigation-manipulation

soil-moisture

display_name: soil-moisture

soil-temperature

display_name: soil-temperature

water-potential

display_name: water-potential


en:
Description
This dataset contains continuous sap-flow measurements and derived whole-tree transpiration estimates for 45 Pinus sylvestris trees at the Pfynwald experimental platform in southwestern Switzerland during 2024–2025. Trees were distributed across five treatment combinations established within the VPDrought experiment: Control, Irrigation, Irrigation + VPD reduction, Roof, and Roof + VPD reduction. Sap flux density was measured every 10 min using heat-ratio sap-flow sensors (IX-SF30, Implexx, Melbourne, Australia) installed at breast height on the north-facing side of each tree.
Raw temperature signals were converted to sap flux density following the heat ratio method (Marshall 1958; Burgess et al. 2001; Forster 2019). Thermal diffusivity and related wood properties were parameterized using increment cores collected near the site and tree-specific allometric relationships. Probe misalignment was corrected by estimating a zero-flow offset from nighttime measurements during well-watered, low-VPD conditions in February 2024 and subtracting this offset from the full time series.
Sap flux density measurements at 0.5 and 1.5 cm sapwood depth were combined to total sap flow for the depth where the sensors were installed. Whole-tree transpiration can be calculated by integrating sap flux density across concentric sapwood depth of 2 cm.
The dataset includes processed sap flux density values together with metadata on treatment, tree identity, sensor depth, and quality-control corrections. Limitations include possible residual uncertainty due to sensor drift, assumptions in the sapwood depth, and the replacement of two trees that died during summer 2024 and lost parts of their crown in 2025.
 Additional Information
Data processing was performed in an R environment following the heat ratio method workflow described by Forster (2019). Raw heat-pulse measurements were converted to sap flux density and subsequently corrected for thermal diffusivity, and probe misalignment. Outliers and implausible values were identified and removed using the R package datacleanr (Hurley et al. 2022). Sensor needle misalignment was corrected by defining a zero-flow offset during periods of low atmospheric demand and assumed zero sap flow (i.e. rainy periods), and subtracting this offset from the time series. The processing script used to derive the dataset is available from the authors upon request.
Relevant literature:
- Burgess S.S.O., Adams M.A., Turner N.C., Beverly C.R., Ong C.K., Khan A.A.H. & Bleby T.M. (2001) An improved heat pulse method to measure low and reverse rates of sap flow in woody plants†. Tree Physiology 21, 589–598.
- Forster M.A. (2019) The Dual Method Approach (DMA) Resolves Measurement Range Limitations of Heat Pulse Velocity Sap Flow Sensors. Forests 10.
- Hurley A.G., Peters R.L., Pappas C., Steger D.N. & Heinrich I. (2022) Addressing the need for interactive, efficient, and reproducible data processing in ecology with the datacleanr R package. PLOS ONE 17, e0268426-.
- Marshall D.C. (1958) Measurement of Sap Flow in Conifers by Heat Transport. 1. Plant Physiology 33, 385–396.

en: vpd reduction sap-flow vpdrought forest-ecophysiology xylem-flux rain-exclusion pfynwald tree-transpiration transpiration drought-experiment irrigation pinus-sylvestris continuous-monitoring rhone-valley

en: Pfynwald VPDrought  experiment sap flow parameter

en:
Resource Title: pfynwald_vpdrought_sapflow_10Minutes_2025.zip
    Size: 53424631 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9e439e5-827a-40a7-956c-1a05699e6adc/resource/455662d6-f0b7-4ea8-8cb6-d31eb714952e/download/pfynwald_vpdrought_sapflow_10minutes_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_sapflow_10Minutes_2024.zip
    Size: 53546175 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9e439e5-827a-40a7-956c-1a05699e6adc/resource/6a0cd3b8-8e29-4b85-9296-86196808fd32/download/pfynwald_vpdrought_sapflow_10minutes_2024.zip
    Description:

continuous-monitoring

display_name: continuous-monitoring

forest-ecophysiology

display_name: forest-ecophysiology

pinus-sylvestris

display_name: pinus-sylvestris

rain-exclusion

display_name: rain-exclusion

reduction

display_name: reduction

rhone-valley

display_name: rhone-valley

sap-flow

display_name: sap-flow

tree-transpiration

display_name: tree-transpiration

vpd

display_name: vpd

xylem-flux

display_name: xylem-flux


en:
Project description:
Forest soils are among the largest terrestrial carbon pools. How soil carbon (C) responds to changing water availability is still poorly understood, particularly in already water-limited systems. This project investigates the composition and persistence of soil organic matter (SOM) and associated microbial communities in a dry inner-Alpine Scots pine forest exposed to long-term changes in precipitation and atmospheric demand. Earlier work showed that 19 years of irrigation redistributed bulk soil C from the organic layer into the mineral soil. Although total soil C stocks remained unchanged, a higher incorporation into mineral soils may increase long-term C storage (Guidi et al., 2022; Minich et al., 2026). We now ask, how persistent this redistributed C is, in which soil C fraction (particulate or mineral-associated) it resides, and which microbial communities are associated with it.
The work is based at Pfynwald, where a long-term irrigation experiment (since 2003) and the recently installed [VPDrought platform](https://vpdrought.wsl.ch/de/) together span three precipitation regimes (≈300, 600, and 1200 mm per year) crossed with manipulation of atmospheric vapour-pressure deficit. This setup allows us to disentangle the effects of soil and atmospheric drought, which typically co-vary in nature but may shape soil carbon dynamics through distinct pathways. SOM is separated by physical fractionation into particulate (POM) and mineral-associated (MAOM) fractions, characterized through elemental and isotopic analyses (C, N, δ¹³C, δ¹⁵N, ¹⁴C) and fraction-specific microbial community profiling. At the bulk soil level, we measure nutrient pools and extracellular enzyme activities, continue year-round soil respiration, and complement them by CH4 fluxes. Together, these data will reveal how soil carbon stocks and microbial processing respond to changing precipitation in a water-limited pine forest.

en: pfynwald som radiocarbon drought microbial-communities

en: Soil organic matter dynamics under altered precipitation in a dry Scots pine forest

drought

display_name: drought

microbial-communities

display_name: microbial-communities

pfynwald

display_name: pfynwald

radiocarbon

display_name: radiocarbon

som

display_name: som


historical-vegetation-height-model-nfi

en:
The main datasets available are 4 nationwide **Digital Surface Models (DSMs)** and corresponding **Vegetation Height Models (VHMs)** with a spatial resolution of 1 m.
The Vegetation Height Models are calculated by subtraction of a Digital Terrain Model (swissAlti3d version 2017, swisstopo) from the generated DSMs. DSMs were derived by image matching of **scanned historical images** (panchromatic 8-bit) acquired with a RC10 frame camera, in the context of the swisswide image acquisition campaigns of swisstopo.
Nationwide products could be generated for the **four epochs**
 1979-1985 / 1985-1991 / 1990-1998 / 1998-2006.
Additional information about successful image matching vs. interpolation of pixels and about the year of image acquisition are available in the corresponding files (**matched_area_xxxx_xxxx_binay.tif** and **meta_acquisition_year_xxxx_xxxx.json**, respectively).
To separate vegetation from non-vegetation areas a mask derived from a combination of information of the Topographic landscape model - TLM (swisstopo) and a NDVI layer was used and is supplied as **"TLM_mask.tif"**
Due to the occurrence of unrealistic vegetation height values caused by the failure of the image matching process (mainly overexposed images and clouds or very steep rocky terrain), pixel values - 60 m were set to NoData and - 0 m to 0.
All datasets are available in the Reference System **LV95 (EPSG: 2056) LN02 (EPSG: 5728)** and share the common **extent definition** (xmin ymin xmax ymax): 2480000 1070000 2840000 1300000

en: dsm historical nfi vhm photogrammetry forest

en: Historical Vegetation Height Model NFI

title_for_slug: historical-vegetation-height-model-nfi

en:
Resource Title: 1985-1991 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1985-1991_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1979-1985 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1979-1985_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: readme.txt
    Size: 2045 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d16d27e5-b239-4909-b914-1b0b5337dab3/resource/f6cabeaa-bf7c-4141-bea9-af99d3224487/download/readme.txt
    Description: Description of available data

media_type: text/plain

en:
Resource Title: 1990-1998 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1990-1998_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1998-2006 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1998-2006_vegetation_height_model_nfi%2F
    Description:

dsm

display_name: dsm

forest

display_name: forest

historical

display_name: historical

nfi

display_name: nfi

photogrammetry

display_name: photogrammetry

vhm

display_name: vhm


vegetation-height-model-lidar-nfi

en:
Countrywide **vegetation height models (VHM)** were generated for Switzerland based on
LiDAR data acquired in the framework of the **swissSURFACE3D** campaign (swisstopo).
To derive vegetation height, the classified point cloud got normalized by calculating height above ground for all points not belonging to the class ground (2). Vegetation point (class 3,4,5) got then rasterized to a grid size of 0.5 m using an interpolation distance of one grid cell. Raster cells not belonging to a vegetation class got set to 0 m above ground.
These VHM's are produced in the framework of the Swiss National forest Inventory (NFI).
Each year about 1/6 of switzerland surface is updated using swissSURFACE3D data in leaf-off state.

en: vegetation vegetation-height forest nfi vegetation-classification point-cloud three-dimensional

envidat

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

en: EnviDat: the Environmental Data Portal

en: Vegetation Height Model LiDAR NFI

title_for_slug: vegetation-height-model-lidar-nfi

envi

en: Environment

en:
Resource Title: 2024 Vegetation Height Model LiDAR NFI
    Size: 149786984448 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2024%2F
    Description: Vegetation Height Model of Switzerland for the year 2024 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

en:
Resource Title: 2025 Vegetation Height Model LiDAR NFI (current)
    Size: 160202280141 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2025%2F
    Description: Vegetation Height Model of Switzerland for the year 2025 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

point-cloud

display_name: point-cloud

three-dimensional

display_name: three-dimensional

vegetation

display_name: vegetation

vegetation-classification

display_name: vegetation-classification

vegetation-height

display_name: vegetation-height


en:
The data show locations of the most recent outdoor activity (referred to as restorative location, RL) of Swiss residents, and descriptive characteristics of these places. The data was collected via an online participatory mapping survey targeting residents of urban, peri-urban, and rural areas across Switzerland. Respondents were selected using a stratified random sampling method, considering the greenness and noise exposure of their home locations, and demographic factors such as age, gender, and language region.
The survey was conducted using Maptionnaire software (https://maptionnaire.com). Participants were asked to map the location of their most recent outdoor activity (referred to as restorative location, RL) and provide additional information on their experience in these places. The responses were integrated with the quantitative spatial information (biophysical landscape characteristics, referred to as metrics) on the visited locations, obtained from spatial and remote sensing data.

en: soundscape restorative-environments gis-analysis quiet-areas traffic-noise sensory-perception

en: Restorative locations from participatory mapping by Swiss residents

gis-analysis

display_name: gis-analysis

quiet-areas

display_name: quiet-areas

restorative-environments

display_name: restorative-environments

sensory-perception

display_name: sensory-perception

soundscape

display_name: soundscape

traffic-noise

display_name: traffic-noise


en:
This study examines the siting scenarios for renewable energy infrastructure (REI) in Switzerland, incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed.
MARXAN was run for 2 versions: a) without ground-mounted open space PV infrastructure (excl. OS) and b) with ground-mounted open space PV infrastructure (incl. OS). In each version optimization was done using ecological costs (ECUess) or social costs (ECUsoc) in a regular grid of 4x4km (planning unit).
File:
PU_data.shp: compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.
Headers are described below:
X01 = Planning_units (PUs)
X02 = incl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)
geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).
For MARXAN optimizations (for meaning of standard files in MARXAN see https://scholar.google.ch/scholar_url?url=https://courses.washington.edu/cfr590/software/Marxan1810/marxan_manual_1_8_2.pdf&hl=de&sa=X&ei=NAWHZI6JJ8PFmAGMo47oDQ&scisig=AGlGAw-DBrsV4kUzkR6GkN1jtG66&oi=scholarr), pu_data.shp was used to generate MARXAN files input.dat, pu.dat, puvfeat.dat, spec.dat.
Coordinate Reference System: CH1903 / LV03. EPSG: 21781.

en: wind-power photovoltaic landscape marxan social-acceptance spatial-planning energy optimization ecosystem-services

en: Optimizing renewable energy siting in the Swiss landscape

ecosystem-services

display_name: ecosystem-services

energy

display_name: energy

landscape

display_name: landscape

marxan

display_name: marxan

optimization

display_name: optimization

photovoltaic

display_name: photovoltaic

social-acceptance

display_name: social-acceptance

spatial-planning

display_name: spatial-planning

wind-power

display_name: wind-power


en: Site description of the Seehornwald Davos (CH-DAV) research site. The material provided offers information on the biomass and growth of trees in CH-DAV, including supporting materials such as maps, geolocations and analyses. CH-DAV is part of networks such as ICOS, LWF, TreeNet, ICPForests and is dedicated to forest monitoring and research.

en: icp-forests treenet seehornwald water-relations ecophysiology metadata forest-monitoring forest-area forest-dynamics climate-change forest-biomass forest-canopy open-data eddy-covariance atmospheric-conditions eddy-covariance-measurements sap-flow forest-ecosystems ilter davos dendrometer forest ecosystem-functioning carbon-cycle carbon-dioxide forest-characteristics picea-abies subalpine carbon-sequestration co2 carbon-storage climate-growth dbh twd biomass flux automated-monitoring tree-stem stem-growth icos lwf forest-function

en: Site description Davos Seehornwald CH-DAV

en:
Resource Title: CH-DAV_Site_2024_V2.zip
    Size: 27267396 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4d332ffa-d5f5-413c-ba1c-5f73ceebbed6/resource/41e3d87c-7907-4a01-bf5e-36a0d4457c40/download/ch-dav_site_2024_v2.zip
    Description: Collection of files with information about the research site Seehornwald Davos CH-DAV

en:
Resource Title: CH-DAV_Site_2024.zip
    Size: 34214528 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4d332ffa-d5f5-413c-ba1c-5f73ceebbed6/resource/73875879-bec0-4e15-a805-e6cd9d4fe596/download/ch-dav_site_2024.zip
    Description: Collection of files with information about the research site Seehornwald Davos CH-DAV

en:
Resource Title: Readme
    Size: 2476 bytes
    Format: application/rtf
    URL: https://www.envidat.ch/dataset/4d332ffa-d5f5-413c-ba1c-5f73ceebbed6/resource/7f13f634-76b5-4d56-aa5a-61140240f616/download/readme.rtf
    Description:

format: rtf

atmospheric-conditions

display_name: atmospheric-conditions

automated-monitoring

display_name: automated-monitoring

biomass

display_name: biomass

carbon-cycle

display_name: carbon-cycle

carbon-dioxide

display_name: carbon-dioxide

carbon-sequestration

display_name: carbon-sequestration

carbon-storage

display_name: carbon-storage

climate-change

display_name: climate-change

climate-growth

display_name: climate-growth

davos

display_name: davos

dbh

display_name: dbh

dendrometer

display_name: dendrometer

ecophysiology

display_name: ecophysiology

ecosystem-functioning

display_name: ecosystem-functioning

eddy-covariance

display_name: eddy-covariance

eddy-covariance-measurements

display_name: eddy-covariance-measurements

flux

display_name: flux

forest

display_name: forest

forest-area

display_name: forest-area

forest-biomass

display_name: forest-biomass

forest-canopy

display_name: forest-canopy

forest-characteristics

display_name: forest-characteristics

forest-dynamics

display_name: forest-dynamics

forest-ecosystems

display_name: forest-ecosystems

forest-function

display_name: forest-function

forest-monitoring

display_name: forest-monitoring

icos

display_name: icos

icp-forests

display_name: icp-forests

ilter

display_name: ilter

lwf

display_name: lwf

metadata

display_name: metadata

open-data

display_name: open-data

picea-abies

display_name: picea-abies


alan-spongy-moth-laboratory-experiment

en:
Data and Code for ALAN Spongy Moth lab experiment
In this repository you will find all the raw datasets used for the data analysis performed in our paper about the impacts of artificial light at night (ALAN) on the development of Spongy Moth caterpillars. The files are attached as a csv file.
Also attached is all the R-code later used for the statistical analysis and for generating the graphics displayed in the paper. This files are attached as an R.file.

en: lab-experiment alan insect-development spongy-moth light-pollution

envidat

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

en: EnviDat: the Environmental Data Portal

en: ALAN Spongy Moth Laboratory Experiment

title_for_slug: alan-spongy-moth-laboratory-experiment

en:
Resource Title: Pupation_analysis.R
    Size: 7606 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/f5ad6fb7-b540-4742-8b77-e5fa86855b1d/download/pupation_analysis.r
    Description: R code for the pupation analysis and producing the graphics.

format: OCTET

en:
Resource Title: SM_R_NvK.csv
    Size: 56547 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/c93124fd-448c-403b-bc42-70f4b6722636/download/sm_r_nvk.csv
    Description: Raw data used for the Pupation and Cox Hazard/Kaplan Meier Analysis.

en:
Resource Title: BodyMass_analysis.R
    Size: 4254 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/0ff15832-2eb3-4420-9afd-869e36ce92ef/download/bodymass_analysis.r
    Description: R code for the bodymass analysis and producing the graphics.

en:
Resource Title: CoxHazard_KaplanMeier_Mort_Pup.R
    Size: 3933 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/0a205353-8812-4f39-af3f-8d67d2d1495c/download/coxhazard_kaplanmeier_mort_pup.r
    Description: R code for the Cox hazard analysis and producing the Kaplan Meier survival curves for both Mortality and Pupation.

en:
Resource Title: SM_R_long_NvK.csv
    Size: 567035 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/401242a6-4430-4725-8c41-263a4f769041/download/sm_r_long_nvk.csv
    Description: Raw data modified and used for the Bodymass Analysis

alan

display_name: alan

insect-development

display_name: insect-development

lab-experiment

display_name: lab-experiment

light-pollution

display_name: light-pollution

spongy-moth

display_name: spongy-moth


forest-canopy-layer

en: This dataset provides a LiDAR-based classification of the forest canopy layer for selected Swiss cantons. Combining an area-based and tree-centred approach, forest areas are categorised into four canopy layering classes that differentiate between single-layered and multi-layered canopies.

en: forest-management nfi forest-canopy forest-structure lidar mountain-forest

en: Forest Canopy Layer

title_for_slug: forest-canopy-layer

envi

en: Environment

en:
Resource Title: ForestCanopyLayer.tif
    Size: 558505541 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/90bcde13-c71d-4618-a198-362ebccd0516/download/forestcanopylayer.tif
    Description: Forest Canopy Layer (class 1: single-layered; class 2: probably single-layered; class 3: probably multi-layered; class 4: multi-layered).

format: TIFF

media_type: image/tiff

en:
Resource Title: ForestCanopyLayer.qml
    Size: 8139 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/378dbed2-33a3-4398-8a41-5c341d27557d/download/forestcanopylayer.qml
    Description: QGIS QML file with stored layer style definitions for the ForestCanopyLayer.tif.

en:
Resource Title: IFA_Data.csv
    Size: 3837 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/a15b3bdb-c45e-4a8a-b526-8d43b265862c/download/ifa_data.csv
    Description: Validation data from the Independent Forester Assessment (IFA). x- /y-coordinate (CH1903+ LV03) and layer (1: single-layered; 2: multi-layered; -999: NA).

forest-canopy

display_name: forest-canopy

forest-management

display_name: forest-management

forest-structure

display_name: forest-structure

lidar

display_name: lidar

mountain-forest

display_name: mountain-forest

nfi

display_name: nfi


en:
Regional disturbance predisposition maps for windthrow, bark beetle and snow breakage. The maps are created using spatially explicit data of classified forest structure and site factor parameters. The classified input parameters were weighted according to their effect on windthrow, bark beetle and snow breakage predisposition using an expert-based model. The predisposition raster maps (10 x 10 m) represent the sum of expert-weighted effects on the predisposition and are provided as raw values (sum of the effects on predisposition) and as classified layers.
Classified predisposition maps are encoded as follows:
1: low predisposition (-50% quantile based on raw predisposition values)
2: increased predisposition (50–75% quantile)
3: high predisposition (-75–95% quantile)
4: extreme predisposition (-95% quantile)
Also included are the derived forest structure maps for development stage, dominant stand height, number of stems and canopy cover used for the predisposition mapping, as well as the R scripts and example data to re-create these parameters. Forest structure parameters are based on a data set of individual trees detected using a high-resolution vegetation height model. Further included are ArcPy scripts and example data to re-create the predisposition maps. Running the ArcPy scripts requires a valid ArcGis license including the extensions "SpatialAnalyst", "ImageAnalyst" and "3D".
The example data provided here is assembled from different sources; please check the related publication Bührle et al. (in review) for data sources and further information about the processing, the expert-based model, the forest structure derivation and the predisposition mapping.
Also consider reviewing the related datasets and publications Bast et al. (2025) for more information about canopy layering derivation and individual tree detection (ITD).

en: stem-number forest-structure predisposition als stand-height tree-detection bark-beetle canopy-cover snow-breakage predisposition-mapping development-stage itd windthrow

en: Regional bark beetle windthrow and snow breakage disturbance predisposition maps

en:
Resource Title: 02_python_scripts_predisposition_mapping.zip
    Size: 438323 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/e165fc12-ca86-423f-807a-d7cf1c8535a5/download/02_python_scripts_predisposition_mapping.zip
    Description: ArcPy-Python scripts and demo data to create the bark beetle, windthrow and snow breakage predisposition maps.

en:
Resource Title: 04_forest_structure_maps.zip
    Size: 34068234 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/cd162993-bc30-46c1-816b-0722c3d83a50/download/04_forest_structure_map.zip
    Description: Maps of development stage, number of stems, dominant stand height and canopy coverage based on single trees detected from a vegetation height model.

en:
Resource Title: 03_rcode_forest_structure.zip
    Size: 103693681 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/42199442-7c55-48ed-a3a7-04aaf9967da0/download/03_rcode_forest_structure.zip
    Description: R-codes and demo data to derive the forest structure parameters: development stage, number of stems, dominant stand height, and canopy coverage based on single trees detected from a vegetation height model. These parameters are necessary input parameters for predisposition mapping.

en:
Resource Title: 01_predispostion_maps.zip
    Size: 19881001 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/59df8818-2e56-4794-9152-3652c20fe6fc/download/01_predispostion_maps.zip
    Description: Classified and raw value predisposition maps for bark beetle, windthrow and snow breakage

als

display_name: als

bark-beetle

display_name: bark-beetle

canopy-cover

display_name: canopy-cover

development-stage

display_name: development-stage

itd

display_name: itd

predisposition

display_name: predisposition

predisposition-mapping

display_name: predisposition-mapping

snow-breakage

display_name: snow-breakage

stand-height

display_name: stand-height

stem-number

display_name: stem-number

tree-detection

display_name: tree-detection

windthrow

display_name: windthrow


en:
This dataset contains the input data generated for the pseudo-global warming (PGW) experiments used in the study of the March 2022 Antarctic heatwave with the CRYOWRF model. It includes:
- PGW delta fields derived from CMIP6 simulations, used to perturb ERA5 reanalysis data for past and  future storyline experiments.
- Model configuration files required to reproduce the CRYOWRF simulations.
These resources allow researchers to reproduce the experimental setup and generate model outputs consistent with the results presented in the study.

en: era5 antarctica cmip6 event-attribution heatwave extreme-events atmospheric-rivers climate-change

envidat

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

en: EnviDat: the Environmental Data Portal

en: Storylines of the March 2022 heatwave event at Concordia - East Antarctica

en:
Resource Title: PGW_deltas.tar
    Size: 3701853962 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/79b7c457-e689-49bd-8330-29b0508d2b2c/resource/9936c23c-dc86-4eaa-8a6f-5a49cffb338c/download/pgw_deltas.tar
    Description: PGW delta fields derived from CMIP6 simulations, used to perturb ERA5 reanalysis data for future storyline experiments.

en:
Resource Title: CRYOWRF_ANT_20220315_ConfigFiles.tar
    Size: 912259096 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/79b7c457-e689-49bd-8330-29b0508d2b2c/resource/7f77d116-cd3b-4eec-a6d6-061b0d7b43f6/download/cryowrf_ant_20220315_configfiles.tar
    Description: Model configuration files required to reproduce the CRYOWRF simulations over Antarctica.

antarctica

display_name: antarctica

atmospheric-rivers

display_name: atmospheric-rivers

climate-change

display_name: climate-change

event-attribution

display_name: event-attribution

extreme-events

display_name: extreme-events

heatwave

display_name: heatwave


en:
This dataset contains gridded snow depth projections for Switzerland at 1km X 1km resolution. This study was supported by Speed2Zero. The dataset contains the following structure:
- data/data_reference/hs_reference_1991_2020.nc
- data/data_projection_flat/hs_projection_flat.nc
- data/data_projection_aspect/hs_projection_aspect.nc
The data is based on climatological SPASS dataset (Marty et al., 2015) using the reference period 1991-2020. For this reference data, median snow depth evolution, as well as 5th and 95th percentile were computed for each grid point and can be found in this dataset (data/data_reference/*). Future snow depth evolutions for the flat field (data/data_projection_flat/*) were projected for the temperature scenarios +1°C, +2°C, +3°C and +4°C (deviation from 1991-2020 annual mean temperature in Switzerland) following the literature-based approach of Richter and Marty, 2026. Furthermore, this dataset contains gridded projections for north- and south-facing ascpects with a slope anle of 15° (data/data_projection_aspect/*). Detailed can be found in the related publication Richter et al., in preparation.
The files in this data set have a similar structure. Each file is a NetCDF-file containing snow depths (median, 5th, 95th percentile) for each day of the year, coordinate, temperature scenario (data_projection_flat and data_projection_aspect) and aspect (data_projection_aspect).
References:
Marty, C., Michel, A., Jonas, T., Steijn, C., Muelchi, R., and Kotlarski, S.: SPASS – new gridded climatological snow datasets for Switzerland: potential and limitations, The Cryosphere, 19, 4391–4407, https://doi.org/10.5194/tc-19-4391-2025, 2025.
Richter, B. and Marty, C.: Technical note: Literature based approach to estimate future snow, Hydrol. Earth Syst. Sci., 30, 659–670, https://doi.org/10.5194/hess-30-659-2026, 2026.
Richter et al., Gridded snow depth projections, in prepration.

en: switzerland scenario gridded-data climate-projections swiss-alps snow future snow-depth climate-change

en: Gridded projections of snow depth for Switzerland

envi

en: Environment

climate-projections

display_name: climate-projections

future

display_name: future

gridded-data

display_name: gridded-data

scenario

display_name: scenario

snow

display_name: snow

snow-depth

display_name: snow-depth

swiss-alps

display_name: swiss-alps

switzerland

display_name: switzerland


individual-detected-trees

en: This dataset provides individual detected trees for selected Swiss Cantons (Appenzell Outer-Rhodes - AR, Grisons - GR, Nidwald - NW, Obwald - OW and St. Gall - SG), including the derived diameter at breast height and the derived NFI development stage. Data show the Individual detected trees (ITD) with the x- and y-positions of each detected tree based on a spike-free vegetation height model based on nationwide LiDAR data. The shapefile contains the following attributes: tree height [m] (Height), estimated diameter at breast height [cm] (BHD), and the NFI development stage (Ent; 1: young growth/thicket (- 12 cm); 2: pole timber (12-30 cm); 3: young timber (31-40 cm); 4: medium timber (41-50 cm); 5: old timber (- 50 cm).

en: forest-structure development-stage mountain-forest itd forest-management nfi

en: Individual Detected Trees

title_for_slug: individual-detected-trees

development-stage

display_name: development-stage

forest-management

display_name: forest-management

forest-structure

display_name: forest-structure

itd

display_name: itd

mountain-forest

display_name: mountain-forest

nfi

display_name: nfi


en:
This dataset contains all necessary data to reproduce the validation simulations performed in the linked manuscript.
The validation data includes:
- 2 cm DEM of the study site Weissfluhjoch. For the 3 cm DEM of the study site Chant Sura, see [this dataset](https://www.doi.org/10.16904/envidat.174).
- roughness index rasters for both study sites
- rock point clouds of EOTA and Real Equant shapes
- release points used in the validation simulations of both study sites
- a sample XML input file for the rockfall simulator

en: numerical-simulation natural-hazards surface-roughness rockfall validation

en: Validation Data for Rockfall Simulations with Geometric Roughness Model

en:
Resource Title: Rock Pointclouds
    Size: 3779 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/c99baa33-50ba-480a-8e4b-82450130900b/download/rocks.zip
    Description: Rock point clouds of EOTA and Real Equant shapes

en:
Resource Title: DEM Weissfluhjoch
    Size: 1005521469 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/9598c524-85b4-4dad-981c-59a126314973/download/dem_weissfluhjoch_2cm.tif
    Description: Digital Elevation Model (DEM) of validation test site Weissfluhjoch with a grid resolution of 2 cm. The DEM for test site Chant Sura can be found in the linked dataset.

en:
Resource Title: Roughness Index Rasters
    Size: 36884 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/2c863503-c73d-4b97-a660-d2998b717093/download/roughness.zip
    Description: Roughness index rasters used for the validation simulations. They have a resolution of 3 m.

en:
Resource Title: Sample Simulation
    Size: 126372 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/230c5218-e7a2-4e4f-8633-0c00695cff71/download/sample_sim.zip
    Description: This dataset contains a small sample simulation to showcase the recommended folder/file structure to run rockfall simulations. The input parameters for the simulation can be changed in the XML file, which is then also used as input for the rockfall simulator.

en:
Resource Title: Release Points
    Size: 4649 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/636d34b5-5031-4bb6-aa28-b3d1cb11b80e/download/release.zip
    Description: Release points used in the validation simulations of both study sites. Use the *.txt files as input for the simulator.

natural-hazards

display_name: natural-hazards

numerical-simulation

display_name: numerical-simulation

rockfall

display_name: rockfall

surface-roughness

display_name: surface-roughness

validation

display_name: validation


iwet-insect-weight-estimation-tool

en:
Because of some corrections, a new version of the whole Dataset will be published soon.
We present a novel tool called IWET (Insect Weight Estimation Tool) for estimating morphometrics of arthropod samples using image analysis. IWET is a Java application built around ImageJ libraries and is designed to estimate length, width, area and body mass of individual arthropods from images of specimens sorted into pre-defined taxonomic groups. Using allometric relationships from Sohlströhm et al. (2018), we developed specific regression models to calculate both the individual body mass and the total biomass of arthropod taxonomic groups. IWET provides several advantages: it is non-destructive, cost-effective, and capable of processing large numbers of samples, making it particularly well-suited for biodiversity monitoring projects investigating changes in abundance and biomass, as well as for automating measurements such as specimen length, width and area.

en: automatic-detection biomass temperate arthropods body-size image-analysis allometric

envidat

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

en: EnviDat: the Environmental Data Portal

en: IWET – Insect Weight Estimation Tool

title_for_slug: iwet-insect-weight-estimation-tool

en:
Resource Title: R-Script_and_suppl.zip
    Size: 2243953 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/3d7e7b44-af7f-4824-84b8-fc2abd1f04b3/resource/6ca41ee8-bda9-4e65-b859-1dd9c0184c50/download/r-script_and_suppl.zip
    Description: R Script for Regression models

en:
Resource Title: IWET_EnviDat.zip
    Size: 10255073 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/3d7e7b44-af7f-4824-84b8-fc2abd1f04b3/resource/7f5681bf-cf49-47b0-a8cc-a1e8dde61354/download/iwet_envidat.zip
    Description: IWET-Software with prorpriety and model files (inkl. materials)

allometric

display_name: allometric

arthropods

display_name: arthropods

automatic-detection

display_name: automatic-detection

biomass

display_name: biomass

body-size

display_name: body-size

image-analysis

display_name: image-analysis

temperate

display_name: temperate


sliding-deadwood-geometry-generator

en: This dataset contains a python code to create deadwood log geometries as well as sample data used for simulations of sliding deadwood with RAMMS::Rockfall.

en: deadwood protection-forest natural-hazards mass-movements forest-management

en: Sliding Deadwood Geometry Generator

title_for_slug: sliding-deadwood-geometry-generator

envi

en: Environment

en:
Resource Title: Sliding deadwood geometry generator
    Size: 6062 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/a6325cb3-bdb3-4b7c-90f6-1ca41c159918/resource/6fc08e26-7bbe-45c9-8ea1-ab85c36c1793/download/sliding_deadwood_geometry-main.zip
    Description: Python code to create deadwood logs as input for RAMMS::Rockfall.

This version was used for the linked publication. The most recent version and the full documentation can be found in the [GitHub Repository](https://github.com/joelborner/sliding_deadwood_geometry)

en:
Resource Title: Sample Data
    Size: 108780 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/a6325cb3-bdb3-4b7c-90f6-1ca41c159918/resource/5ba5fd5d-1b1e-485f-ab24-422df5a509ac/download/sample_data.zip
    Description: Contains all necessary data to do a sample simulation of sliding deadwood:
- Deadwood log geometries (*.pts)
- Release points of the logs (*.shp)
- Treefiles (*.txt), containing the locations, heights, BHD and energy absorption capacities of the standing trees

The data is from the two case studies Gruobenwald and Rhäzüns presented in the linked publication. The DEM for these case studies can be downloaded from swisstopo (swissALTI3D dataset)

deadwood

display_name: deadwood

forest-management

display_name: forest-management

mass-movements

display_name: mass-movements

protection-forest

display_name: protection-forest


en:
The dataset contains the time series of: overland flow (OF) and topsoil interflow (TIF) measured at two large runoff plots (8 m large by 10 m long), streamflow from two sub-catchments of the Studibach catchment, and streamflow from the outlet of the Studibach and Erlenbach catchments. The time series cover 12 rainfall events in the summer 2022.
OF, TIF and the streamflow of the sub-catchments and the Studibach catchment outlet were measured at a 5-min resolution. The streamflow at the Erlenbach catchment outlet was measured at 10-min resolution.
The precipitation was measured with a tipping bucket at the Erlenhöhe meteorological station and has a 10-min resolution.

en: upscaling overland-flow alptal studibach topsoil-interflow erlenbach runoff-plot streamflow

en: Time serie of overland flow, topsoil interflow and stream flow in the Studibach Catchment and streamflow in the Erlenbach catchment - summer 2022

alptal

display_name: alptal

erlenbach

display_name: erlenbach

overland-flow

display_name: overland-flow

runoff-plot

display_name: runoff-plot

streamflow

display_name: streamflow

studibach

display_name: studibach

topsoil-interflow

display_name: topsoil-interflow

upscaling

display_name: upscaling


en:
ERRA is a data-driven, nonparametric, model-independent method for quantifying rainfall-runoff relationships across a spectrum of time lags, in systems that may be nonlinear, nonstationary, and spatially heterogeneous.
Researchers using ERRA in published work should cite J.W. Kirchner, "Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using Ensemble Rainfall-Runoff Analysis (ERRA): proof of concept", Hydrology and Earth System Sciences, https://doi.org/10.5194/hess-28-4427-2024, 2024 (for ERRA itself) and J.W. Kirchner, "Impulse response functions for nonlinear, nonstationary, and heterogeneous systems, estimated by deconvolution and de-mixing of noisy time series", Sensors, 22(9), 3291, https://doi.org/10.3390/s22093291, 2022 (for the underlying mathematics).
This data set includes two versions of the ERRA script written in the open-source programming language R, a detailed user's guide, and sample scripts and source data for all of the results in Kirchner (2024).
These scripts are made publicly available under GNU General Public License 3; for details see https://www.gnu.org/licenses/.  The data and documentation are made available under Creative Commons Attribution Share-Alike CC-BY-SA.
ETH Zurich, WSL, and James Kirchner make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose. Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

en: ecohydrology streamflow hydrology time-series nonstationarity precipitation rainfall-runoff-modelling nonlinear-deconvolution

en: ERRA -- an R script for Ensemble Rainfall-Runoff Analysis

en:
Resource Title: ERRA_scripts_v1.12.zip
    Size: 2621440 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/11af276e-c779-468c-9504-ef56bd490c7d/download/erra_scripts_v1.12.zip
    Description: Zip-compressed folder containing two versions of the ERRA script. ERRA_v1.12.R uses Rcpp to speed up several key calculations, but requires a C++ compiler. ERRA_v1.12_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp. Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: {{deprecated version}} An introduction to ERRA v1.06.pdf
    Size: 3166700 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/0c048816-816a-4c1f-bedf-32be20e4d4c2/download/an-introduction-to-erra-v1.06.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them. This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

en:
Resource Title: An introduction to ERRA v1.12.pdf
    Size: 3072328 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/927de1da-fef7-4b05-8534-ae8330bbb48c/download/an-introduction-to-erra-v1.12.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them. This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

en:
Resource Title: {{deprecated version}} ERRA_scripts_v1.06.zip
    Size: 114452 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/64819efe-d661-41c8-8410-f61665564c05/download/erra_scripts_v1.06.zip
    Description: Zip-compressed folder containing two versions of the ERRA script. ERRA_v1.06.R uses Rcpp to speed up several key calculations, but requires a C++ compiler. ERRA_v1.06_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp. Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: Demonstration scripts.zip
    Size: 65399685 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/ca1f4818-aff6-4b13-a83d-82376dde2834/download/demonstration-scripts.zip
    Description: Zip-compressed folder containing demonstration scripts, source data, and output files for the ERRA results shown in "Introduction to ERRA" and in J.W. Kirchner, "Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using Ensemble Rainfall-Runoff Analysis (ERRA): proof of concept", Hydrology and Earth System Sciences, 2024.

en:
Resource Title: {{deprecated version}} ERRA_scripts_v1.11.zip
    Size: 2621440 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/6e05e468-ccd2-4d42-be7b-b7578a68061e/download/erra_scripts_v1.11.zip
    Description: Zip-compressed folder containing two versions of the ERRA script. ERRA_v1.11.R uses Rcpp to speed up several key calculations, but requires a C++ compiler. ERRA_v1.11_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp. Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: {{deprecated version}} ERRA_scripts.zip
    Size: 114811 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/9e833898-3a78-4e79-83bd-d23c5ba76765/download/erra_scripts.zip
    Description: Zip-compressed folder containing two versions of the ERRA script.  ERRA_v1.0.R uses Rcpp to speed up several key calculations, but requires a C++ compiler.  ERRA_v1.0_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp.  Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: {{deprecated version}} An introduction to ERRA.pdf
    Size: 3156214 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/51f419cd-f933-4cad-88b4-a20ac7dcf545/download/an-introduction-to-erra.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them.  This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

en:
Resource Title: {{deprecated version}} An introduction to ERRA v1.11.pdf
    Size: 3072328 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/eee3eb76-74b7-4d84-bd23-fa2a97544b58/download/an-introduction-to-erra-v1.11.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them. This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

ecohydrology

display_name: ecohydrology

hydrology

display_name: hydrology

nonlinear-deconvolution

display_name: nonlinear-deconvolution

nonstationarity

display_name: nonstationarity

precipitation

display_name: precipitation

rainfall-runoff-modelling

display_name: rainfall-runoff-modelling

time-series

display_name: time-series


en:
**CH-POA300** is a dataset of hourly solar irradiance maps projected onto tilted surfaces (analogous to monofacial solar panels).
- **Spatial resolution:** 300 m
- **Coverage:** Switzerland
Two temporal extents are available, depending on the number of surface orientations (azimuth–tilt combinations):
 1. Long-term
- **Period:** 2004–2020
- **Orientations:**
  - Azimuth: 180° (South)
  - Tilts: 0°, 35°, 60°, 90°
 2. Typical year
- **Period:** 2016
- **Orientations:**
  - Azimuths: 0° (North), 90° (East), 135°, 180° (South), 225°, 270° (West)
  - Tilts: 0°, 3°, 8°, 15°, 25°, 35°, 45°, 60°, 80°, 90°
 Notes
- Azimuth angles: 0° = North, 90° = East, 180° = South, 270° = West
- Tilt angles: 0° = horizontal, 90° = vertical
 Additional data
- Seasonal and annual statistics derived from the maps are included.
- Methodology and quality assessment are documented in *CH-POA300-v-specs.pdf*.

en: plane-of-array solar-irradiance agri-pv rooftop-pv alpine-pv speed2zero sweet-edge

envidat

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

en: EnviDat: the Environmental Data Portal

en: CH-POA300 -- Hourly Plane-of-Array Solar Irradiance at High Resolution for Switzerland

envi

en: Environment

en:
Resource Title: Data 2016
    Size: 751619276800 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2FCHPOA300%2F&prefix=2016
    Description:

en:
Resource Title: CH-POA300_v1_statistics
    Size: 1445061901 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/ea36025c-c855-488d-857d-f658bace53e2/download/chpoa300_statistics.zip
    Description: Contains seasonal and annual statistics (mean, sum) of the CH-POA300 dataset.

- "yyyy_agg_period_hourly_stat.nc": statistic <stat> for the period <agg_period> of the year <yyyy>
- "all_agg_period_stat_mean.nc": statistic <stat> for the period <agg_period> reduced on the entire dataset (all years).
\
yyyy: [2004, 2020]
agg_period: [winter, summer, annual]
stat: [mean, sum]

en:
Resource Title: CH-POA300-v2-statistics
    Size: 1889349528 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/ed1238d2-b8c0-42f1-9b65-b837ac2dd259/download/stats.zip
    Description: Contains seasonal and annual statistics (mean and sum) derived from the CH-POA300 dataset.
File naming conventions:
yyyy_agg_period_hourly_stat.nc : statistic <stat> for aggregation period <agg_period> in year <yyyy>
all_agg_period_stat_mean.nc : statistic <stat> for aggregation period <agg_period> computed over the entire dataset (all years)
Definitions:
yyyy = year (2004–2020)
agg_period = winter, summer, annual
stat = mean, sum

en:
Resource Title: CH-POA300-v2-specs
    Size: 11473219 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/c184fb33-6751-47cd-a936-2f04de24c760/download/ch-poa300-v2-specs.pdf
    Description: This document provides an in-depth description of the CH-POA300 dataset. It includes methodology and validation details.

en:
Resource Title: CH-POA300_v1_specs
    Size: 11472383 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/7146fc4a-df12-44a8-923f-69476b147a55/download/chpoa300_specs_v1.pdf
    Description: This document provides an in-depth description of the CH-POA300 dataset. It includes methodology and validation details.

en:
Resource Title: Data 2004-2020
    Size: 858993459200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2FCHPOA300/&prefix=2004-2020
    Description:

agri-pv

display_name: agri-pv

alpine-pv

display_name: alpine-pv

plane-of-array

display_name: plane-of-array

rooftop-pv

display_name: rooftop-pv

solar-irradiance

display_name: solar-irradiance

sweet-edge

display_name: sweet-edge


en:
Lebensraumkarte der Schweiz v1.2 2025/La carte des milieux naturels de Suisse v1.2 2025
The FOEN funded project ‘The Habitat Map of Switzerland:continual improvement’ conducted at the WSL, has improved on versions 1.0 and 1.1 of a map of Swiss habitats according to the TypoCH classification (Delarze et al. 2015). The datasets is now separated into two data sets:  The Habitat Map of Switzerland v1.2, ground cover layer,  and The Habitat Map of Switzerland v1.2, individual trees and shrubs outside forest v1.0 (above ground) layer.
The Habitat Map of Switzerland maps the TypoCH habitat types wall-to-wall across the whole of Switzerland, to at least the classification’s 2nd level of detail (where possible to the 3rd level of detail).
Habitats are mapped through a variety of approaches that can be grouped as either:
1: Derived from the existing Swiss-wide datasets a) the high quality landcover mapping from Swisstopo’s Topographical Landscape Model (TLM), b) the harmonised mapping of agricultural fields area from the ‘Landwirtschaftliche Nutzfläche’ (LWN) mapping and, in settlements areas, c) the harmonised cadastral data (‘Amitliche Vermessung’ AV).
2: Modelled within the project using Random Forest or Ensemble Modelling techniques to model the spatial distribution of individual habitat types (further detail below),
3: Combining existing species distribution models to determine habitat types, or
4: Classification with relatively simple rule-sets based on auxiliary spatial datasets, i.e. vegetation height models (based on digital aerial photogrammetry and/or SwissSurface3D aerial laser scanning (ALS) data), the digital terrain model, the normalised difference vegetation index (NDVI) derived from aerial imagery and/or time-series of growing season Sentinel-2 or Planet satellite imagery.
Further detail on the methodology can be found within the README document.

en: shrub-forest sentinel-2 lidar urban remote-sensing dwarf-shrubs forest lebensraumkarte tof wetland grasslands milieux-naturels typoch random-forest habitat-modelling ensemble-modelling

en: The Habitat Map of Switzerland v1_2 2025

en:
Resource Title: LUT_einzelbaum_gebuesch_v_1_0.csv
    Size: 216 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/0035dd77-ea6d-4d3a-89bd-3ad6ee36302e/download/lut_einzelbaum_gebuesch_v_1_0.csv
    Description: Look up table for the data N2025_einzelbaum_gebuesche_v1_0_20251216
giving the full text names for each habitat type in German, French and Italian

en:
Resource Title: N2025_HabitatMap_CH_v1_2_20251211.gdb.zip
    Size: 7247757312 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/a90d17bf-221e-4819-a8b1-94b807a33720/download/n2025_habitatmap_ch_v1_2_20251211.gdb.zip
    Description: The Habitat Map of Switzerland version 1.2 2025. Ground cover layer, All of Switzerland. Vector data in file geodatabase format. Is complemented by the trees and shrubs layer.

en:
Resource Title: N2025_einzelbaum_gebuesche_v1_0_20251216.gdb.zip
    Size: 2469606195 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/cd4e36db-926c-4e2b-bb89-27dbe606dac3/download/n2025_einzelbaum_gebuesche_v1_0_20251216.gdb.zip
    Description: The Habitat Map of Switzerland v1.2, non-forest trees and shrubs layer, v1.0. Vector dataset in file geodatabase format. Complements the ground cover layer dataset

en:
Resource Title: symbology_v1_2_2025.zip
    Size: 61778 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/47c0e914-986f-4ad3-9bcf-49160023c030/download/symbology_v1_2_2025.zip
    Description: Symbology for the Habitat Map, ground layer and tree and shrub layer, and in ArcGIS and QGIS layer formats. German, French and Italian versions

en:
Resource Title: TypoCH_NUM_LookupTable_26112025.csv
    Size: 46705 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/28aace15-eb00-4ec2-98ef-b55acc18286f/download/typoch_num_lookuptable_26112025.csv
    Description: Look up table for the data N2025_HabitatMap_CH_v1_2_20251211
giving the full text names for habitat types in German, French and Italian for each habitat type as well as the key for the type of methodology used

en:
Resource Title: Data_Description_Lebensraumkarte_v1_2_Dec2025.pdf
    Size: 645376 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/564b16e5-0523-4431-94bc-3e6d1415c5a1/download/data_description_lebensraumkarte_v1_2_dec2025.pdf
    Description: Data description and documentation of methods

dwarf-shrubs

display_name: dwarf-shrubs

ensemble-modelling

display_name: ensemble-modelling

forest

display_name: forest

grasslands

display_name: grasslands

habitat-modelling

display_name: habitat-modelling

lebensraumkarte

display_name: lebensraumkarte

lidar

display_name: lidar

milieux-naturels

display_name: milieux-naturels

random-forest

display_name: random-forest

remote-sensing

display_name: remote-sensing

shrub-forest

display_name: shrub-forest

tof

display_name: tof

typoch

display_name: typoch

urban

display_name: urban

wetland

display_name: wetland


en: This data supplement contains the data associated with the manuscript: "Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions" (Janzing et al., 2025). It contains the data to create the figures in the paper and consists of model output from **PCRaster Global Water Balance Model (PCR-GLOBWB) 2.0** model over the larger Alpine region at 30 arcsec resolution. As the full model output takes up very high memory space, we here mostly provide time series for the different measurement stations used for evaluation and some additional maps needed to recreate the figures in the manuscript.

en: hydrological-simulations hydrology large-scale discharge european-alps

envidat

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

en: EnviDat: the Environmental Data Portal

en: Data supplement to Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions

discharge

display_name: discharge

european-alps

display_name: european-alps

hydrological-simulations

display_name: hydrological-simulations

hydrology

display_name: hydrology

large-scale

display_name: large-scale