cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.27085879
title: Comparison of MODIS and SGLI Albedo Retrievals Over the Sea of Okhotsk (January-May 2021)

description: This dataset contains surface shortwave albedo retrieval and surface classification data derived from both MODIS and SGLI satellite sensors over the Sea of Okhotsk, covering the period from January to May 2021. The data is stored in NetCDF format and standardized on a 1-km grid, allowing for direct pixel-to-pixel comparison. The dataset consists of albedo values and surface classifications, enabling an in-depth analysis of retrieval consistency and discrepancies between the two sensors. Data were averaged over weekly time periods for valid sea-ice pixels. The specific dates for each weekly period are provided.The retrieval algorithm is described in https://doi.org/10.5194/tc-17-1053-2023.The dataset includes the following variables:1. MODIS_SW_albedo:<br>Albedo values retrieved from the MODIS sensor using the SciML albedo retrieval algorithm. Values are provided for the period January-May 2021 on a grid with a spatial resolution of 1 km.<br>2. MODIS_mask:<br>Surface classification mask for the MODIS sensor. The mask values correspond to different surface types and features:<br>• 0: Water<br>• 1: Sea-ice<br>• 2: Sea-covered ice<br>3. SGLI_SW_albedo:<br>Albedo values retrieved from the SGLI sensor using the the SciML albedo retrieval algorithm. These values are provided for the same time period (January-May 2021) and grid as the MODIS data.<br>4. SGLI_mask:<br>Surface classification mask for the SGLI sensor. The mask uses the same classification scheme as the MODIS mask:<br>• 0: Water<br>• 1: Sea-ice<br>• 2: Sea-covered ice<br>Time Periods Covered:<br>The dataset spans eight weekly time intervals, corresponding to the following periods:• 2021-01-08 ~ 2021-01-13<br>• 2021-01-31 ~ 2021-02-06<br>• 2021-02-11 ~ 2021-02-17<br>• 2021-03-05 ~ 2021-03-12<br>• 2021-03-15 ~ 2021-03-20<br>• 2021-04-01 ~ 2021-04-07<br>• 2021-04-22 ~ 2021-04-30<br>• 2021-05-07 ~ 2021-05-12Each period represents a weekly aggregate of albedo and surface classification data from both sensors, averaged where valid sea-ice pixels were present.Spatial Coverage:• Latitude: 40° to 64° N<br>• Longitude: 135° to 165° E<br>Format:<br>The dataset is provided in NetCDF format (.nc), which can be read and analyzed using common geospatial and scientific data tools such as Python’s xarray or Panoply.
DOI: 10.6084/m9.figshare.27085879.v1
title: Comparison of MODIS and SGLI Albedo Retrievals Over the Sea of Okhotsk (January-May 2021)

description: This dataset contains surface shortwave albedo retrieval and surface classification data derived from both MODIS and SGLI satellite sensors over the Sea of Okhotsk, covering the period from January to May 2021. The data is stored in NetCDF format and standardized on a 1-km grid, allowing for direct pixel-to-pixel comparison. The dataset consists of albedo values and surface classifications, enabling an in-depth analysis of retrieval consistency and discrepancies between the two sensors. Data were averaged over weekly time periods for valid sea-ice pixels. The specific dates for each weekly period are provided.The retrieval algorithm is described in https://doi.org/10.5194/tc-17-1053-2023.The dataset includes the following variables:1. MODIS_SW_albedo:<br>Albedo values retrieved from the MODIS sensor using the SciML albedo retrieval algorithm. Values are provided for the period January-May 2021 on a grid with a spatial resolution of 1 km.<br>2. MODIS_mask:<br>Surface classification mask for the MODIS sensor. The mask values correspond to different surface types and features:<br>• 0: Water<br>• 1: Sea-ice<br>• 2: Sea-covered ice<br>3. SGLI_SW_albedo:<br>Albedo values retrieved from the SGLI sensor using the the SciML albedo retrieval algorithm. These values are provided for the same time period (January-May 2021) and grid as the MODIS data.<br>4. SGLI_mask:<br>Surface classification mask for the SGLI sensor. The mask uses the same classification scheme as the MODIS mask:<br>• 0: Water<br>• 1: Sea-ice<br>• 2: Sea-covered ice<br>Time Periods Covered:<br>The dataset spans eight weekly time intervals, corresponding to the following periods:• 2021-01-08 ~ 2021-01-13<br>• 2021-01-31 ~ 2021-02-06<br>• 2021-02-11 ~ 2021-02-17<br>• 2021-03-05 ~ 2021-03-12<br>• 2021-03-15 ~ 2021-03-20<br>• 2021-04-01 ~ 2021-04-07<br>• 2021-04-22 ~ 2021-04-30<br>• 2021-05-07 ~ 2021-05-12Each period represents a weekly aggregate of albedo and surface classification data from both sensors, averaged where valid sea-ice pixels were present.Spatial Coverage:• Latitude: 40° to 64° N<br>• Longitude: 135° to 165° E<br>Format:<br>The dataset is provided in NetCDF format (.nc), which can be read and analyzed using common geospatial and scientific data tools such as Python’s xarray or Panoply.
DOI: 10.15468/dl.4m2wkx
title: Occurrence Download

description: A dataset containing 66818 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-69.10248 48.64447,-69.1209 48.60086,-69.08874 48.5925,-69.07004 48.63103,-69.07581 48.65083,-69.09561 48.65119,-69.10248 48.64447))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 66818 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026812-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qqzukp
title: Occurrence Download

description: A dataset containing 442 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Desmatophocidae",
 "Continent is one of (North America, South America)"
 ]
}

 The dataset includes 442 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026814-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rh4t9t
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Enaliarctidae",
 "Continent is one of (North America, South America)"
 ]
}

 The dataset includes 38 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026815-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6mftc9
title: Occurrence Download

description: A dataset containing 26489 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Centaurea solstitialis L."
 ]
}

 The dataset includes 26489 records from 580 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026807-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uufw7n
title: Occurrence Download

description: A dataset containing 1346 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Allophylus cobbe (L.) Forsyth fil."
 ]
}

 The dataset includes 1346 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026816-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n28uwq
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eupleridae",
 "Continent is one of (North America, South America)"
 ]
}

 The dataset includes 10 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026817-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.27085882
title: Albedo Retrievals from MODIS Over the Sea of Okhotsk (Validation Data, 2002–2014)

description: This dataset contains satellite-based albedo retrievals and surface classifications from MODIS sensors over the Sea of Okhotsk, collected during multiple voyages of the Soya Icebreaker from 2002 to 2014. The dataset focuses on validating MODIS retrievals by comparing them to in-situ albedo measurements collected by the Soya Icebreaker. The retrieval data is standardized on a 1-km grid and includes albedo and surface classification values for each available time period. Only satellite retrievals were uploaded, without the in-situ measurements.Key features of this dataset include:• Albedo retrieval data using the retrieval algorithm is described in https://doi.org/10.5194/tc-17-1053-2023.<br>• Surface classification masks indicating different surface types (e.g., land, water, snow-covered ice).The dataset was used to analyze and quantify the discrepancies between satellite-based retrievals and in-situ measurements under varying conditions of sea ice, snow, and meltwater, and to understand the impacts of time differences between satellite overpasses and ground-based measurements.Variables:1. SW:<br>Shortwave albedo values retrieved from the MODIS sensor using the SciML albedo retrieval algorithm. The retrievals were made over the Sea of Okhotsk region, focusing on the validation period (2002–2014).<br>2. mask:<br>Surface classification mask for the MODIS sensor. This mask classifies each grid point based on surface type:<br>• 0: Invalid<br>• 1: Land<br>• 2: Water<br>• 3: Snow on land<br>• 4: Bare Sea-ice<br>• 5: Snow-covered Sea Ice<br>• 6: Cloud/Fog (nullified)<br>Time Periods:<br>The dataset spans the following time periods, during which MODIS data was validated against in-situ measurements:• 2002-02-14<br>• 2002-02-16<br>• 2003-02-06<br>• 2003-02-07<br>• 2003-02-11<br>• 2004-02-07<br>• 2004-02-08<br>• 2004-02-09<br>• 2004-02-10<br>• 2006-02-12<br>• 2007-02-10<br>• 2008-02-09<br>• 2008-02-10<br>• 2008-02-11<br>• 2009-02-10<br>• 2013-02-25<br>• 2013-02-26<br>• 2014-02-15<br>Spatial Coverage:• Latitude: 43.5° to 46° N (region where Soya Icebreaker operated)<br>• Longitude: 141° to 146° E<br>Format:The data is provided in NetCDF format (.nc), with dimensions for date, latitude, and longitude. Each time step corresponds to a specific satellite overpass date, and the spatial data are aligned to a grid covering the Sea of Okhotsk.Usage:This dataset is intended for validating MODIS satellite retrievals against ground-based measurements, particularly for studying discrepancies in albedo measurements under different ice and snow conditions.<br>
DOI: 10.6084/m9.figshare.27085882.v1
title: Albedo Retrievals from MODIS Over the Sea of Okhotsk (Validation Data, 2002–2014)

description: This dataset contains satellite-based albedo retrievals and surface classifications from MODIS sensors over the Sea of Okhotsk, collected during multiple voyages of the Soya Icebreaker from 2002 to 2014. The dataset focuses on validating MODIS retrievals by comparing them to in-situ albedo measurements collected by the Soya Icebreaker. The retrieval data is standardized on a 1-km grid and includes albedo and surface classification values for each available time period. Only satellite retrievals were uploaded, without the in-situ measurements.Key features of this dataset include:• Albedo retrieval data using the retrieval algorithm is described in https://doi.org/10.5194/tc-17-1053-2023.<br>• Surface classification masks indicating different surface types (e.g., land, water, snow-covered ice).The dataset was used to analyze and quantify the discrepancies between satellite-based retrievals and in-situ measurements under varying conditions of sea ice, snow, and meltwater, and to understand the impacts of time differences between satellite overpasses and ground-based measurements.Variables:1. SW:<br>Shortwave albedo values retrieved from the MODIS sensor using the SciML albedo retrieval algorithm. The retrievals were made over the Sea of Okhotsk region, focusing on the validation period (2002–2014).<br>2. mask:<br>Surface classification mask for the MODIS sensor. This mask classifies each grid point based on surface type:<br>• 0: Invalid<br>• 1: Land<br>• 2: Water<br>• 3: Snow on land<br>• 4: Bare Sea-ice<br>• 5: Snow-covered Sea Ice<br>• 6: Cloud/Fog (nullified)<br>Time Periods:<br>The dataset spans the following time periods, during which MODIS data was validated against in-situ measurements:• 2002-02-14<br>• 2002-02-16<br>• 2003-02-06<br>• 2003-02-07<br>• 2003-02-11<br>• 2004-02-07<br>• 2004-02-08<br>• 2004-02-09<br>• 2004-02-10<br>• 2006-02-12<br>• 2007-02-10<br>• 2008-02-09<br>• 2008-02-10<br>• 2008-02-11<br>• 2009-02-10<br>• 2013-02-25<br>• 2013-02-26<br>• 2014-02-15<br>Spatial Coverage:• Latitude: 43.5° to 46° N (region where Soya Icebreaker operated)<br>• Longitude: 141° to 146° E<br>Format:The data is provided in NetCDF format (.nc), with dimensions for date, latitude, and longitude. Each time step corresponds to a specific satellite overpass date, and the spatial data are aligned to a grid covering the Sea of Okhotsk.Usage:This dataset is intended for validating MODIS satellite retrievals against ground-based measurements, particularly for studying discrepancies in albedo measurements under different ice and snow conditions.<br>
DOI: 10.15468/dl.dmfjvx
title: Occurrence Download

description: A dataset containing 659 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Specimen, Living Specimen)",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Alternaria Nees ex Wallroth, 1816",
 "Year 2010-2024"
 ]
}

 The dataset includes 659 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026819-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13828932
title: Road-deposited sediment wash-off experiments on a large-scale laboratory

description: This dataset includes raw and processed data from a series of large-scale laboratory tests that were conducted to assess and study the wash-off process of RDS (Road deposited sediments) considering variations in rainfall intensity, for two scenarios: 30 mm/h and 50 mm/h; and modifying RDS loads applied on BLOCK for three scenarios: 100 g/m2, 150 g/m2, 200 g/m2. First, the hydraulic was detailly characterized including rainfall intensity maps, water flows, surface water depths and surface water velocities for both rainfall intensities tested. A synthetic granulometric of RDS was homogeneously distributed on the physical model surface and then washed-off by the simulated rainfall. A total of 31 water samples were collected at the manhole discharge per each experiment. Total RDS mass that remain on the surface and inside the gully was collected by a wet vacuum after the rainfall event. A mass balance considering the initial RDS applied and the total RDS recollected in the three samples locations, was calculated. TUR (Turbidity), EC (Conductivity), TS (Total Solids), TSS (Total suspended solids), TDS (Total dissolved solids), RDS mass by flow, and RDS mass flow variables were measured for the RDS samples recollected in the Manhole discharge. The behaviour of each RDS fraction was also analysed through laser diffraction (Beckman Coulter LS 13 320, Aqueous Liquids Module). This work is part of a Transnational Access developed by the Universidad Distrital Francisco José de Caldas (Colombia) and Universidade da Coruña (Spain) within the scope of Co-UDlabs project. Data may be used to increase knowledge on road-deposited sediment wash-off process, allowing also for calibrating, developing, and validating new and existing urban wash-off models.
DOI: 10.5281/zenodo.13828933
title: Road-deposited sediment wash-off experiments on a large-scale laboratory

description: This dataset includes raw and processed data from a series of large-scale laboratory tests that were conducted to assess and study the wash-off process of RDS (Road deposited sediments) considering variations in rainfall intensity, for two scenarios: 30 mm/h and 50 mm/h; and modifying RDS loads applied on BLOCK for three scenarios: 100 g/m2, 150 g/m2, 200 g/m2. First, the hydraulic was detailly characterized including rainfall intensity maps, water flows, surface water depths and surface water velocities for both rainfall intensities tested. A synthetic granulometric of RDS was homogeneously distributed on the physical model surface and then washed-off by the simulated rainfall. A total of 31 water samples were collected at the manhole discharge per each experiment. Total RDS mass that remain on the surface and inside the gully was collected by a wet vacuum after the rainfall event. A mass balance considering the initial RDS applied and the total RDS recollected in the three samples locations, was calculated. TUR (Turbidity), EC (Conductivity), TS (Total Solids), TSS (Total suspended solids), TDS (Total dissolved solids), RDS mass by flow, and RDS mass flow variables were measured for the RDS samples recollected in the Manhole discharge. The behaviour of each RDS fraction was also analysed through laser diffraction (Beckman Coulter LS 13 320, Aqueous Liquids Module). This work is part of a Transnational Access developed by the Universidad Distrital Francisco José de Caldas (Colombia) and Universidade da Coruña (Spain) within the scope of Co-UDlabs project. Data may be used to increase knowledge on road-deposited sediment wash-off process, allowing also for calibrating, developing, and validating new and existing urban wash-off models.
DOI: 10.15468/dl.eycyxe
title: Occurrence Download

description: A dataset containing 1362064 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Specimen)",
 "Geometry POLYGON((-169 29,-50 29,-50 34,-169 34,-169 29))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae",
 "Year 2023-2024"
 ]
}

 The dataset includes 1362064 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026787-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.99rky3
title: Occurrence Download

description: A dataset containing 11726 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Spheniscus humboldti Meyen, 1834"
 ]
}

 The dataset includes 11726 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026820-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ae9kn3
title: Occurrence Download

description: A dataset containing 1910 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Herpestidae",
 "Continent is one of (North America, South America)"
 ]
}

 The dataset includes 1910 records from 82 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026821-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c96xqy
title: Occurrence Download

description: A dataset containing 159031 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Monitoreo de peces en la cuenca media y baja del río Cauca en el marco del Proyecto Hidroeléctrico Ituango, durante los años 2010 - 2020"
 ]
}

 The dataset includes 159031 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026795-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4jv85h
title: Occurrence Download

description: A dataset containing 8326 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "TaxonKey is Eriocaulaceae"
 ]
}

 The dataset includes 8326 records from 111 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026822-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13829114
title: Consórcios Públicos Intermunicipais na Região Sul - Rio Grande do Sul, Santa Catarina e Paraná (2021-2022)

description: Mapeamento dos 158 Consórcios Públicos Intermunicipais identificados nos três estados da Região Sul - 43 no Rio Grande do Sul, 45 em Santa Catarina e 70 no Paraná, no período de 2021-2022.

Esse levantamento foi realizado na pesquisa de tese "Cidades pequenas e cooperação interfederativa: Estratégias dos Consórcios Públicos em relação ao planejamento e gestão das políticas públicas no Rio Grande do Sul", 2020-2024. (Doutorado em Planejamento Urbano e Regional) – Programa de Pós-Graduação em Planejamento Urbano e Regional, UFRGS, Porto Alegre.
DOI: 10.5281/zenodo.13829115
title: Consórcios Públicos Intermunicipais na Região Sul - Rio Grande do Sul, Santa Catarina e Paraná (2021-2022)

description: Mapeamento dos 158 Consórcios Públicos Intermunicipais identificados nos três estados da Região Sul - 43 no Rio Grande do Sul, 45 em Santa Catarina e 70 no Paraná, no período de 2021-2022.

Esse levantamento foi realizado na pesquisa de tese "Cidades pequenas e cooperação interfederativa: Estratégias dos Consórcios Públicos em relação ao planejamento e gestão das políticas públicas no Rio Grande do Sul", 2020-2024. (Doutorado em Planejamento Urbano e Regional) – Programa de Pós-Graduação em Planejamento Urbano e Regional, UFRGS, Porto Alegre.
DOI: 10.15468/dl.gdu98h
title: Occurrence Download

description: A dataset containing 196 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyaenidae",
 "Continent is one of (North America, South America)"
 ]
}

 The dataset includes 196 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026824-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.npsd9w
title: Occurrence Download

description: A dataset containing 625850 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Living Specimen, Specimen, Occurrence evidence)",
 "Continent is Europe",
 "CoordinateUncertaintyInMeters 0.0-100.0",
 "OccurrenceStatus is Present",
 "TaxonKey is Salix L.",
 "Year 1960-2024"
 ]
}

 The dataset includes 625850 records from 505 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026790-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hqyy6z
title: Occurrence Download

description: A dataset containing 3843 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coeligena prunellei (Bourcier, 1843)"
 ]
}

 The dataset includes 3843 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027822-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.