cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26037/yareta:cripcwu4nbh5vprpqzhorbycry
title: Preprocessed EEG and iEEG data

description: This dataset contains:

(1) the preprocessed EEG data from 15 participants in a speech perception experiment using virtual characters and synthetic speech. The EEG data for all participants are contained in a large MATLAB data file. A text file briefly describes the organization of the MATLAB data structure.

(2) the preprocessed intracranial EEG (iEEG) data from one patient who participated in the same experiment. A text file briefly describes the organization of the MATLAB data structure.
DOI: 10.26037/yareta:e6oihsllezf63ne3z4vkerqjle
title: Landsat 8 Surface Reflectance Analysis Ready Data 2016

description: Data for 2016
This dataset is the Landsat 8 Surface Reflectance Analysis Ready Data (ARD) collection archive for Switzerland, generated by USGS (https://www.usgs.gov/land-resources/nli/landsat/landsat-surface-reflectance).

Detailed description about the Landsat 8 mission can be found in the CEOS Earth Observation Handbook: http://database.eohandbook.com/database/missionsummary.aspx?missionID=547.

The Landsat archive is extremely interesting because this is the longest EO program, initiated in 1972, it has provided continual and consistent observations for almost 50 years. Since 2008, the complete data archive has been provided under a free and open access policy. This has enabled dense time-series analysis, moving beyond simple diachronic comparison of a set of images, therefore dramatically improving capabilities to monitor environmental changes. To cover the whole of Switzerland, it requires eight Landsat 8 scenes (Path/Row: 193/027, 194/027, 195/027, 196/027, 193/028, 194/028, 195/028, 196/028) representing an area of latitude 44.9 to 48.7 and longitude 4.1 to 12.8. Data are downloaded as Collection 1/Tier 1 – Level 2 Surface Reflectance encompassing a surface of approximately 185km by 180km. Collection 1/Tier 1 scenes are data with the highest available data quality (e.g., geometric and radiometric corrections) and considered suitable for time-series analysis (https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1). Level 2 corresponds to surface reflectance (i.e., the estimate based on Landsat sensor observations of the fraction of incoming solar radiation reflected from Earth’s surface). These data are corrected for atmospheric perturbations (e.g., aerosol scattering, thin clouds) enabling direct comparison between multiple images and dates. This corresponds to the ARD level.

Landsat data are provided by USGS with Quality Assessment (QA) information to help users to determine their suitability for specific applications. An 8-bit LandsatLook Quality Image and 16-bit Quality Assessment Band40 are also included. Details on each file are described at: https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1-level-1-quality-assessment-band. Level 2 products are generated by the USGS from level 1 product and using the official LEDAPS/LASRC algorithm. "A Pixel Quality Assurance (pixel_qa) band is provided with all Landsat Surface Reflectance-derived Spectral Indices. The band is in unsigned 16-bit format, values are bit-packed and provide information pertaining to a pixel condition of fill, clear, water, cloud shadow, snow, cloud (yes/no), cloud confidence and cirrus cloud confidence (Landsat 8 only)" https://www.usgs.gov/land-resources/nli/landsat/landsat-sr-derived-spectral-indices-pixel-quality-band.
DOI: 10.26037/yareta:ptcntolyqndn5gp7m37uj6czri
title: Landsat 5 Surface Reflectance Analysis Ready Data 2002

description: Data for 2002
This dataset is the Landsat 5 Surface Reflectance Analysis Ready Data (ARD) collection archive for Switzerland, generated by USGS (https://www.usgs.gov/land-resources/nli/landsat/landsat-surface-reflectance).

Detailed description about the Landsat 5 mission can be found in the CEOS Earth Observation Handbook: http://database.eohandbook.com/database/missionsummary.aspx?missionID=226.

The Landsat archive is extremely interesting because this is the longest EO program, initiated in 1972, it has provided continual and consistent observations for almost 50 years. Since 2008, the complete data archive has been provided under a free and open access policy. This has enabled dense time-series analysis, moving beyond simple diachronic comparison of a set of images, therefore dramatically improving capabilities to monitor environmental changes. To cover the whole of Switzerland, it requires eight Landsat 5 scenes (Path/Row: 193/027, 194/027, 195/027, 196/027, 193/028, 194/028, 195/028, 196/028) representing an area of latitude 44.9 to 48.7 and longitude 4.1 to 12.8. Data are downloaded as Collection 1/Tier 1 – Level 2 Surface Reflectance encompassing a surface of approximately 185km by 180km. Collection 1/Tier 1 scenes are data with the highest available data quality (e.g., geometric and radiometric corrections) and considered suitable for time-series analysis (https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1). Level 2 corresponds to surface reflectance (i.e., the estimate based on Landsat sensor observations of the fraction of incoming solar radiation reflected from Earth’s surface). These data are corrected for atmospheric perturbations (e.g., aerosol scattering, thin clouds) enabling direct comparison between multiple images and dates. This corresponds to the ARD level.

Landsat data are provided by USGS with Quality Assessment (QA) information to help users to determine their suitability for specific applications. An 8-bit LandsatLook Quality Image and 16-bit Quality Assessment Band40 are also included. Details on each file are described at: https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1-level-1-quality-assessment-band. Level 2 products are generated by the USGS from level 1 product and using the official LEDAPS/LASRC algorithm. "A Pixel Quality Assurance (pixel_qa) band is provided with all Landsat Surface Reflectance-derived Spectral Indices. The band is in unsigned 16-bit format, values are bit-packed and provide information pertaining to a pixel condition of fill, clear, water, cloud shadow, snow, cloud (yes/no), cloud confidence and cirrus cloud confidence (Landsat 8 only)" https://www.usgs.gov/land-resources/nli/landsat/landsat-sr-derived-spectral-indices-pixel-quality-band.
DOI: 10.26037/yareta:uhetyluiendc5hjbh4n5426l6e
title: Landsat 5 Surface Reflectance Analysis Ready Data 2000

description: Data for 2000
This dataset is the Landsat 5 Surface Reflectance Analysis Ready Data (ARD) collection archive for Switzerland, generated by USGS (https://www.usgs.gov/land-resources/nli/landsat/landsat-surface-reflectance).

Detailed description about the Landsat 5 mission can be found in the CEOS Earth Observation Handbook: http://database.eohandbook.com/database/missionsummary.aspx?missionID=226.

The Landsat archive is extremely interesting because this is the longest EO program, initiated in 1972, it has provided continual and consistent observations for almost 50 years. Since 2008, the complete data archive has been provided under a free and open access policy. This has enabled dense time-series analysis, moving beyond simple diachronic comparison of a set of images, therefore dramatically improving capabilities to monitor environmental changes. To cover the whole of Switzerland, it requires eight Landsat 5 scenes (Path/Row: 193/027, 194/027, 195/027, 196/027, 193/028, 194/028, 195/028, 196/028) representing an area of latitude 44.9 to 48.7 and longitude 4.1 to 12.8. Data are downloaded as Collection 1/Tier 1 – Level 2 Surface Reflectance encompassing a surface of approximately 185km by 180km. Collection 1/Tier 1 scenes are data with the highest available data quality (e.g., geometric and radiometric corrections) and considered suitable for time-series analysis (https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1). Level 2 corresponds to surface reflectance (i.e., the estimate based on Landsat sensor observations of the fraction of incoming solar radiation reflected from Earth’s surface). These data are corrected for atmospheric perturbations (e.g., aerosol scattering, thin clouds) enabling direct comparison between multiple images and dates. This corresponds to the ARD level.

Landsat data are provided by USGS with Quality Assessment (QA) information to help users to determine their suitability for specific applications. An 8-bit LandsatLook Quality Image and 16-bit Quality Assessment Band40 are also included. Details on each file are described at: https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1-level-1-quality-assessment-band. Level 2 products are generated by the USGS from level 1 product and using the official LEDAPS/LASRC algorithm. "A Pixel Quality Assurance (pixel_qa) band is provided with all Landsat Surface Reflectance-derived Spectral Indices. The band is in unsigned 16-bit format, values are bit-packed and provide information pertaining to a pixel condition of fill, clear, water, cloud shadow, snow, cloud (yes/no), cloud confidence and cirrus cloud confidence (Landsat 8 only)" https://www.usgs.gov/land-resources/nli/landsat/landsat-sr-derived-spectral-indices-pixel-quality-band.
DOI: 10.26037/yareta:woolye23yndrxkvwwz3hl2xhf4
title: Vidéos/Photos Qingxian 07-08.2017

description: Matériel visuel récolté à Qingxian dans la province du Hebei lors de l'enquête de terrain 2017
DOI: 10.26037/yareta:wzdq3padsjai3ntbzrimz6ezji
title: Sentinel-2 Surface Reflectance Analysis Ready Data 2016-Q4

description: Data for 2016-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:xgapyc6sgne2dozzjh2tz2uoj4
title: Landsat 5 Surface Reflectance Analysis Ready Data 1990

description: Data for 1990
This dataset is the Landsat 5 Surface Reflectance Analysis Ready Data (ARD) collection archive for Switzerland, generated by USGS (https://www.usgs.gov/land-resources/nli/landsat/landsat-surface-reflectance).

Detailed description about the Landsat 5 mission can be found in the CEOS Earth Observation Handbook: http://database.eohandbook.com/database/missionsummary.aspx?missionID=226.

The Landsat archive is extremely interesting because this is the longest EO program, initiated in 1972, it has provided continual and consistent observations for almost 50 years. Since 2008, the complete data archive has been provided under a free and open access policy. This has enabled dense time-series analysis, moving beyond simple diachronic comparison of a set of images, therefore dramatically improving capabilities to monitor environmental changes. To cover the whole of Switzerland, it requires eight Landsat 5 scenes (Path/Row: 193/027, 194/027, 195/027, 196/027, 193/028, 194/028, 195/028, 196/028) representing an area of latitude 44.9 to 48.7 and longitude 4.1 to 12.8. Data are downloaded as Collection 1/Tier 1 – Level 2 Surface Reflectance encompassing a surface of approximately 185km by 180km. Collection 1/Tier 1 scenes are data with the highest available data quality (e.g., geometric and radiometric corrections) and considered suitable for time-series analysis (https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1). Level 2 corresponds to surface reflectance (i.e., the estimate based on Landsat sensor observations of the fraction of incoming solar radiation reflected from Earth’s surface). These data are corrected for atmospheric perturbations (e.g., aerosol scattering, thin clouds) enabling direct comparison between multiple images and dates. This corresponds to the ARD level.

Landsat data are provided by USGS with Quality Assessment (QA) information to help users to determine their suitability for specific applications. An 8-bit LandsatLook Quality Image and 16-bit Quality Assessment Band40 are also included. Details on each file are described at: https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1-level-1-quality-assessment-band. Level 2 products are generated by the USGS from level 1 product and using the official LEDAPS/LASRC algorithm. "A Pixel Quality Assurance (pixel_qa) band is provided with all Landsat Surface Reflectance-derived Spectral Indices. The band is in unsigned 16-bit format, values are bit-packed and provide information pertaining to a pixel condition of fill, clear, water, cloud shadow, snow, cloud (yes/no), cloud confidence and cirrus cloud confidence (Landsat 8 only)" https://www.usgs.gov/land-resources/nli/landsat/landsat-sr-derived-spectral-indices-pixel-quality-band.
DOI: 10.26037/yareta:23jacb27ibdm5erlqxcdluzwrm
title: Ripamonti et al., Communications Biology 2021

description: Microscopy source data and additional material
Structural and functional analysis of LIM domain-dependent recruitment of paxillin to αvβ3 integrin-positive focal adhesions
DOI: 10.26037/yareta:5lshxc3bwjekfgsdgobd37ljg4
title: Landsat 5 Surface Reflectance Analysis Ready Data 1984

description: Data for 1984
This dataset is the Landsat 5 Surface Reflectance Analysis Ready Data (ARD) collection archive for Switzerland, generated by USGS (https://www.usgs.gov/land-resources/nli/landsat/landsat-surface-reflectance).

Detailed description about the Landsat 5 mission can be found in the CEOS Earth Observation Handbook: http://database.eohandbook.com/database/missionsummary.aspx?missionID=226.

The Landsat archive is extremely interesting because this is the longest EO program, initiated in 1972, it has provided continual and consistent observations for almost 50 years. Since 2008, the complete data archive has been provided under a free and open access policy. This has enabled dense time-series analysis, moving beyond simple diachronic comparison of a set of images, therefore dramatically improving capabilities to monitor environmental changes. To cover the whole of Switzerland, it requires eight Landsat 5 scenes (Path/Row: 193/027, 194/027, 195/027, 196/027, 193/028, 194/028, 195/028, 196/028) representing an area of latitude 44.9 to 48.7 and longitude 4.1 to 12.8. Data are downloaded as Collection 1/Tier 1 – Level 2 Surface Reflectance encompassing a surface of approximately 185km by 180km. Collection 1/Tier 1 scenes are data with the highest available data quality (e.g., geometric and radiometric corrections) and considered suitable for time-series analysis (https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1). Level 2 corresponds to surface reflectance (i.e., the estimate based on Landsat sensor observations of the fraction of incoming solar radiation reflected from Earth’s surface). These data are corrected for atmospheric perturbations (e.g., aerosol scattering, thin clouds) enabling direct comparison between multiple images and dates. This corresponds to the ARD level.

Landsat data are provided by USGS with Quality Assessment (QA) information to help users to determine their suitability for specific applications. An 8-bit LandsatLook Quality Image and 16-bit Quality Assessment Band40 are also included. Details on each file are described at: https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1-level-1-quality-assessment-band. Level 2 products are generated by the USGS from level 1 product and using the official LEDAPS/LASRC algorithm. "A Pixel Quality Assurance (pixel_qa) band is provided with all Landsat Surface Reflectance-derived Spectral Indices. The band is in unsigned 16-bit format, values are bit-packed and provide information pertaining to a pixel condition of fill, clear, water, cloud shadow, snow, cloud (yes/no), cloud confidence and cirrus cloud confidence (Landsat 8 only)" https://www.usgs.gov/land-resources/nli/landsat/landsat-sr-derived-spectral-indices-pixel-quality-band.
DOI: 10.26037/yareta:6v7khie5fbh77bnhls6j66cjx4
title: Sentinel-2 Surface Reflectance Analysis Ready Data 2017-Q1

description: Data for 2017-Q1
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:d3jri4w4kbbzlcmoikcrs4yh5m
title: Sentinel-2 Surface Reflectance Analysis Ready Data 2017-Q3

description: Data for 2017-Q3
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:dgrqsd24ljdrlhbwkal22ni4wq
title: Computational imaging during video-game playing shows dynamic synchronization of cortical and sub-cortical networks of emotions 

description: Emotions are multifaceted phenomena affecting mind, body, and behavior. Previous studies sought to link particular emotion categories (e.g., fear) or dimensions (e.g., valence) to specific brain substrates, but generally found distributed and overlapping activation patterns across various emotions. In contrast, distributed patterns accord with multi-componential theories whereby emotions emerge from appraisal processes triggered by current events, combined with motivational, expressive, and physiological mechanisms orchestrating behavioral responses. According to this framework, components are recruited in parallel and dynamically synchronized during emotion episodes. Here, we use fMRI to investigate brain-wide systems engaged by theoretically-defined components and measure their synchronization during an interactive emotion-eliciting video-game. We show that each emotion component recruits large-scale cortico-subcortical networks, and that moments of dynamic synchronization between components selectively engage basal ganglia, sensory-motor structures, and midline brain areas. These neural results support theoretical accounts grounding emotions onto embodied and action-oriented functions triggered by synchronized component processes.

Paper:  https://doi.org/10.1371/journal.pbio.3000900
Summary Data: https://identifiers.org/neurovault.collection:8740 
Presentation Scripts: https://github.com/joleitao/Arcade-Game-for-Emotion-Study