cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26037/yareta:yhtr4z73dzd6lkqbese65znezm
title: Enhanced Vegetation Index (EVI) - Switzerland [1984-1989, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Enhanced Vegetation Index (EVI) computed from Landsat 5-7-8 data. EVI quantifies vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs) using the forumla EVI=2.5*(NIR − Red)/(NIR + 6*Red − 7.5*Blue + 1) . See Huete et al. (2002) DOI: 10.1016/S0034-4257(02)00096-2

EVI is usually used for areas with high LAI where NDVI is expected to saturate.
EVI is used to quantify vegetation greenness and is useful in understanding vegetation density and assessing changes in plant health.  

EVI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:zu7tohdrpbasbmoxgwdyhgi4fa
title: Leaf Area Index (LAI) - Switzerland [2020-2021, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Leaf Area Index (LAI) computed from Landsat 5-7-8 data. LAI is designed to analyze the foliage surface of our planet and it estimates the quantity of leaves in a specific region using the forumla LAI= 3.618*EVI - 0.118. For more details see Boegh et al. (2002) DOI: 10.1016/S0034-4257(01)00342-X

LAI is a unitless measure that is calculated as the ratio of the one-sided (illuminated) foliage area to the soil surface it can cover. This vegetation index is important to monitor crop and forest health, the environment, and climatic conditions. 

Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)
 
Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:2bkp5t6wdfck5m3xutzqdzm4by
title: Green Chlorophyll Vegetation Index (GCI) - Switzerland [2020-2021, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Green Chlorophyll Vegetation Index (GCI) computed from Landsat 5-7-8 data. GCI is used to estimate the content of leaf chlorophyll in various species of plants using the forumla GCI=(NIR/Green) – 1. See Gitelson et al. (2003) DOI: 10.1029/2002gl016450

The chlorophyll content reflects the physiological state of vegetation; it decreases in stressed plants and can therefore be used as a measurement of vegetation health. 

GCI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:33ylesvms5heboezppb7nkcpau
title: Passive and weight bearing knee kinematics of 8 patients undergoing total knee arthroplasty

description: This database includes motion capture of the knee kinematics of 8 patients (mean ± SD: age, 70.4 ± 8.9 years; height, 161.9 ± 10 cm; weight, 78.6 ± 26.7 kg; 7 females) with end-stage knee osteoarthritis (grade III to IV on the Kellgren–Lawrence classification) that underwent total knee arthroplasty.

Patients performed a standardized barefoot treadmill gait analysis using the KneeKG™ system (Emovi, Montreal, Canada) one week before and three months after TKA.

Additionally, passive flexion-extension was recorded before and after total knee arthroplasty implantation using the Knee 3 computer assisted surgery system (Brainlab, Munich, Germany).

The anatomical axes of the KneeKG™ and CAS systems were homogenised using two-level, multi-body kinematics optimisation. Knee kinematics computations followed the International Society of Biomechanics conventions.
DOI: 10.26037/yareta:aahr5y2rxvc7zcjngovkssi7me
title: Enhanced Vegetation Index (EVI) - Switzerland [2010-2019, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Enhanced Vegetation Index (EVI) computed from Landsat 5-7-8 data. EVI quantifies vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs) using the forumla EVI=2.5*(NIR − Red)/(NIR + 6*Red − 7.5*Blue + 1) . See Huete et al. (2002) DOI: 10.1016/S0034-4257(02)00096-2

EVI is usually used for areas with high LAI where NDVI is expected to saturate.
EVI is used to quantify vegetation greenness and is useful in understanding vegetation density and assessing changes in plant health.  

EVI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:avdkeolymjdj3oechqu5qolgx4
title: Green Chlorophyll Vegetation Index (GCI) - Switzerland [2017, Sentinel-2]

description: This dataset is an time-serie of Sentinel-2 Analysis Ready Data (ARD)- derived Green Chlorophyll Vegetation Index (GCI) computed from Sentinel-2 data. GCI is used to estimate the content of leaf chlorophyll in various species of plants using the forumla GCI=(b8/b3) – 1. See Gitelson et al. (2003) DOI: 10.1029/2002gl016450

The chlorophyll content reflects the physiological state of vegetation; it decreases in stressed plants and can therefore be used as a measurement of vegetation health. 

GCI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:e5oat4lhijfhng327ghdlw32em
title: Green Chlorophyll Vegetation Index (GCI) - Switzerland [2000-2009, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Green Chlorophyll Vegetation Index (GCI) computed from Landsat 5-7-8 data. GCI is used to estimate the content of leaf chlorophyll in various species of plants using the forumla GCI=(NIR/Green) – 1. See Gitelson et al. (2003) DOI: 10.1029/2002gl016450

The chlorophyll content reflects the physiological state of vegetation; it decreases in stressed plants and can therefore be used as a measurement of vegetation health. 

GCI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:entxglkdbvbcpcksppkxvukd5y
title: Enhanced Vegetation Index (EVI) - Switzerland [2000-2009, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Enhanced Vegetation Index (EVI) computed from Landsat 5-7-8 data. EVI quantifies vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs) using the forumla EVI=2.5*(NIR − Red)/(NIR + 6*Red − 7.5*Blue + 1) . See Huete et al. (2002) DOI: 10.1016/S0034-4257(02)00096-2

EVI is usually used for areas with high LAI where NDVI is expected to saturate.
EVI is used to quantify vegetation greenness and is useful in understanding vegetation density and assessing changes in plant health.  

EVI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:hrtcvjesrnbihp3azbsc6oykui
title: Green Chlorophyll Vegetation Index (GCI) - Switzerland [1990-1999, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Green Chlorophyll Vegetation Index (GCI) computed from Landsat 5-7-8 data. GCI is used to estimate the content of leaf chlorophyll in various species of plants using the forumla GCI=(NIR/Green) – 1. See Gitelson et al. (2003) DOI: 10.1029/2002gl016450

The chlorophyll content reflects the physiological state of vegetation; it decreases in stressed plants and can therefore be used as a measurement of vegetation health. 

GCI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:ml2gqzy5nbf3vnksfvym2kvcam
title: Green Chlorophyll Vegetation Index (GCI) - Switzerland [2010-2019, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Green Chlorophyll Vegetation Index (GCI) computed from Landsat 5-7-8 data. GCI is used to estimate the content of leaf chlorophyll in various species of plants using the forumla GCI=(NIR/Green) – 1. See Gitelson et al. (2003) DOI: 10.1029/2002gl016450

The chlorophyll content reflects the physiological state of vegetation; it decreases in stressed plants and can therefore be used as a measurement of vegetation health. 

GCI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:qafj7krrozc2hkwte4tydh2bq4
title: Enhanced Vegetation Index (EVI) - Switzerland [1990-1999, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Enhanced Vegetation Index (EVI) computed from Landsat 5-7-8 data. EVI quantifies vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs) using the forumla EVI=2.5*(NIR − Red)/(NIR + 6*Red − 7.5*Blue + 1) . See Huete et al. (2002) DOI: 10.1016/S0034-4257(02)00096-2

EVI is usually used for areas with high LAI where NDVI is expected to saturate.
EVI is used to quantify vegetation greenness and is useful in understanding vegetation density and assessing changes in plant health.  

EVI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:vc2lydaosrdefcej2ql54mwhte
title: Derenne_Eve_2021_PhD_thesis_UniversityGeneva

description: The Bell Beaker phenomenon in third millennium BCE Switzerland: Investigating its local integration and exploring the relationship between funerary and domestic contexts through the lens of pottery technical traditions in the Upper Rhône valley
DOI: 10.26037/yareta:xeqh47gzffdxficnutpazlfac4
title: Leaf Area Index (LAI) - Switzerland [1990-1999, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Leaf Area Index (LAI) computed from Landsat 5-7-8 data. LAI is designed to analyze the foliage surface of our planet and it estimates the quantity of leaves in a specific region using the forumla LAI= 3.618*EVI - 0.118. For more details see Boegh et al. (2002) DOI: 10.1016/S0034-4257(01)00342-X

LAI is a unitless measure that is calculated as the ratio of the one-sided (illuminated) foliage area to the soil surface it can cover. This vegetation index is important to monitor crop and forest health, the environment, and climatic conditions. 

Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)
 
Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:yoeeninfy5d4fgs4eqm3grha6m
title: Green Chlorophyll Vegetation Index (GCI) - Switzerland [2020, Sentinel-2]

description: This dataset is an time-serie of Sentinel-2 Analysis Ready Data (ARD)- derived Green Chlorophyll Vegetation Index (GCI) computed from Sentinel-2 data. GCI is used to estimate the content of leaf chlorophyll in various species of plants using the forumla GCI=(b8/b3) – 1. See Gitelson et al. (2003) DOI: 10.1029/2002gl016450

The chlorophyll content reflects the physiological state of vegetation; it decreases in stressed plants and can therefore be used as a measurement of vegetation health. 

GCI values ranges from -1 to +1.
Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)

Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project
DOI: 10.26037/yareta:2l67hobrufaarox3wmvg564dka
title: Snakebite vulnerability analysis and optimization of access to health in the Terai region of Nepal

description: This data includes four sets of geospatial rasters resulting from travel time and vulnerability analysis of the Terai region of Nepal for multiple scenarios, as described in the original publication. Additionally, the ReadMe.txt file provides extra information on the characteristics of the files.
DOI: 10.26037/yareta:3tqbhxx3evgw5askd2zoexe7gm
title: Structural and Electronic Properties of SrCuO2+delta Thin Films

description: Data repository for the paper published in APL Materials
DOI: 10.26037/yareta:5ie4m42p7va7xkrk3vb5rvfjzy
title: reserve cell activation

description: data associated with paper published in Cells: activation and migration of human skeletal muscle stem cells in vitro differently rely on calcium signals
DOI: 10.26037/yareta:ar2yfvbqfrhn7pvzlilno4uvym
title: Intraprofessional Conflict Exercise

description: Scores from the Intraprofessional Conflict Exercise 2018-2019
DOI: 10.26037/yareta:kludip3sovhwrmslm7grhjzboq
title: Torsional disorder and planarisation dynamics: 9,10-bis(phenylethynyl)anthracene as a case study

description: Data published in the article: 
'Torsional disorder and planarisation dynamics: 9,10-bis(phenylethynyl)anthracene as a case study', Ina Fureraj, Darya Budkina and Eric Vauthey, Phys. Chem. Chem. Phys. (24) , 2022, 25979-25979
https://doi.org/10.1039/D2CP03909E
DOI: 10.26037/yareta:mdrfwk26wzhgbfz5bxe4lv3v4i
title: Physical Activity, Heart Rate, and Sleep data collected with a Smartwatch (N=12)

description: When using this resource, please cite the original publication:

"Dejà vu: Recurrent Neural Networks for health wearables data forecast," Igor Matias and Katarzyna Wac, 2022, IEEE Xplore.
https://doi.org/10.1109/ICMLA55696.2022.00264

1. DESCRIPTION:

This dataset includes 12 files with long-term recordings of physical activity, heart rate, and sleep collected for 290 days with a clinically tested smartwatch, Withings ScanWatch. 
Each file refers to an individual and includes additional chronological data for each point (day of the week, month, and astronomical season in the northern hemisphere). 
The data collection occurred between 6 July 2021 and 21 April 2022 (290 days), mainly within Switzerland and surrounding regions of France.
The dataset contains data points missing at random. No data imputation was performed.

2. DEMOGRAPHICS:

Gender:
- 7 identified with the male gender.
- 5 identified with the female gender.
- 0 identified with another gender.

Age:
- Mean age = 28.2.
- 20 to 34 years old.
- Standard deviation = 4.8 years.

Education:
- 1 reported having less than a high school degree.
- 2 had a high school degree or equivalent.
- 0 reported having a bachelor's degree.
- 7 had a master's degree.
- 2 had a Ph.D. degree.

3. DATA:

Check the "ANNOTATORS" file for more information regarding the type of data included.

4. STUDY PROTOCOL:

The study protocol was approved by CUREG.
DOI: 10.26037/yareta:nn4n7vtvbbcy7lfc2axgzna5em
title: Sentinel-2 Surface Reflectance Analysis Ready Data 2020-Q4

description: Data for 2020-Q4
This dataset is the Sentinel-2 Surface Reflectance Analysis Ready Data (ARD) archive for Switzerland, generated sen2cor 2.5 (http://step.esa.int/main/third-party-plugins-2/sen2cor/).

Detailed description about the Sentinel-2 A & B missions can be found in the CEOS Earth Observation Handbook:
http://database.eohandbook.com/database/missionsummary.aspx?missionID=552 
http://database.eohandbook.com/database/missionsummary.aspx?missionID=553 

Sentinel-2 (S2) is a constellation of two sun-synchronous satellites operated by ESA respectively from 2015 to 2022 (Sentinel-2A) and 2017-2024 (Sentinel-2B). Switzerland is covered by twelve Sentinel-2 scenes (ID: 31TGM, 31TGN, 32TLR, 32TLS, 32TLT, 32TMR, 32TMS, 32TMT, 32TNS, 32TNT, 32TPS, 32TPT). This corresponds to a spatial extent of latitude 45.0 to 47.9N, longitude 5.5 to 11.8E. Data are downloaded as L1C products corresponding to 100x100km2 geometrically corrected Top Of the Atmosphere (TOA) tiles.It supports land monitoring related services, including generation of generic land cover maps, risk mapping and fast images for disaster relief, generation of leaf coverage leaf chlorophyll content and leaf water content42,43. Both satellites carry the MultiSpectral Instrument (MSI).

Sentinel-2 processed to level 2A with Sen2Cor comes with a scene classification (similar to the pixel_qa band provided by USGS for Landsat data) with 12 classes as described at: https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/level-2a/algorithm. It helps identifying pixels that are saturated or defective as well as cloud and cloud shadows that may affect the quality of the images. In addition, ESA provides a monthly status of the quality of Sentinel-2 data through Data Quality Reports (DQR). These reports document geometric and radiometric performances against initial sensor specifications together with observed anomalies and issues. DQR are available at: https://sentinels.copernicus.eu/web/sentinel/data-product-quality-reports.
DOI: 10.26037/yareta:rj5oxgsdxrhqdm7g6p6gnu4iiy
title: Dataset of Circularly polarized luminescence from Tb(III) interacting with chiral polyether macrocycles

description: A straightforward two-step synthesis protocol affords a series of chiral amide-based bis-pyridine substituted polyether macrocycles. One ligand is particularly able to complex Terbium(III) ion spontaneously. Upon complexation, interesting chiroptical properties are observed both in absorbance (ECD) and in fluorescence (CPL). In ligand-centered electronic circular dichroism, a sign inversion coupled with a signal enhancement is measured; while an easily detectable metal-centered circularly polarized luminescence with a glum of 0.05 is obtained for the main 5D4 → 7F5 terbium transition. The coordination mode and structure of the complex was studied using different analysis methods (NMR analysis, spectrophotometric titration and solid-state elucidation)
DOI: 10.26037/yareta:uwuhhcukevfapgaiznhjh42xia
title: Leaf Area Index (LAI) - Switzerland [2000-2009, Landsat]

description: This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Leaf Area Index (LAI) computed from Landsat 5-7-8 data. LAI is designed to analyze the foliage surface of our planet and it estimates the quantity of leaves in a specific region using the forumla LAI= 3.618*EVI - 0.118. For more details see Boegh et al. (2002) DOI: 10.1016/S0034-4257(01)00342-X

LAI is a unitless measure that is calculated as the ratio of the one-sided (illuminated) foliage area to the soil surface it can cover. This vegetation index is important to monitor crop and forest health, the environment, and climatic conditions. 

Values are provided as integer and multiplied by 1000 

Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range)
 
Data format: GeoTiff  

This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project (https://www.valpar.ch)
DOI: 10.26037/yareta:yxwyvumeynf4hninr6qgjgppzq
title: Allogeneic hematopoietic stem cell transplantation cohort of 116 donor/recipient pairs : immunosequencing and HLA data 

description: This public dataset contains the HLA typing data in a cohort of 116 recipients of an allogeneic hematopoietic stem cell transplantation. It also contains the TCR beta immunosequencing data of these patients at one year post-transplantation and of their respective donors just prior to transplantation.

More information is provided in the README.txt
DOI: 10.26037/yareta:2qeof6w2k5cyvj77gkee3g5cti
title: Corpus de l'humanitaire

description: Corpus comparable spécialisé du domaine de l’humanitaire, conçu dans le cadre du projet Humanitarian Encyclopedia, en anglais, contenant des textes classés selon le type et le sous-type d’organisation d’où ils proviennent, selon leur date de publication, selon la région où sont basées les organisations et selon le type de textes.
DOI: 10.26037/yareta:3dj64ii4brgevih6ubre5ecsjq
title: Scale Nanostructure Diversity in Snakes

description: Dataset for 'Phylogenetic mapping of scale nanostructure diversity in snakes'
BMC Evolutionary Biology volume 19, Article number: 91 (2019)
DOI: https://doi.org/10.1186/s12862-019-1411-6
Marcelle I. Arrigo, Luis Miguel de Oliveira Vilaca, Anamarija Fofonjka, 
Achyuthan N. Srikanthan, Adrien Debry
DOI: 10.26037/yareta:4hpihszjk5h7pegfpvdq36rtra
title: Dynamical conductivity of disordered quantum chains

description: Data set for European Physical Journal D 76, 213 (2022), https://doi.org/10.1140/epjd/s10053-022-00524-1