cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ahhu6d
title: Occurrence Download

description: A dataset containing 28529 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Trachemys scripta elegans (Wied, 1838)"
 ]
}

 The dataset includes 28529 records from 191 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059737-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4tp6ee
title: Occurrence Download

description: A dataset containing 740 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Peniocereus maculatus (Weing.) Cutak, Peniocereus lazaro-cardenasii (J.L.Contr., J.Jiménez Ram., Sánchez-Mej. & C.Toledo) D.R.Hunt, Peniocereus greggii (Engelm.) Britton & Rose)"
 ]
}

 The dataset includes 740 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0145080-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6r9cgf
title: Occurrence Download

description: A dataset containing 44 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.30_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Sterculia pexa Pierre"
 ]
}

 The dataset includes 44 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028621-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sen6gf
title: Occurrence Download

description: A dataset containing 407977 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Equisetum arvense L."
 ]
}

 The dataset includes 407977 records from 1064 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059744-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gcpdf2
title: Occurrence Download

description: A dataset containing 27147 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-100.39039 25.55863,-100.28078 25.55863,-100.28078 25.63368,-100.39039 25.63368,-100.39039 25.55863))",
 "HasGeospatialIssue is false",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 27147 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0376062-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4g89aa
title: Occurrence Download

description: A dataset containing 224 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Strabomantis bufoniformis (Boulenger, 1896))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 224 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054679-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yt37ux
title: Occurrence Download

description: A dataset containing 1451 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cyprinodon pecosensis Echelle & Echelle, 1978"
 ]
}

 The dataset includes 1451 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0201673-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4u64dm
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aloe nubigena Groenew."
 ]
}

 The dataset includes 38 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0381099-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xcwr8c
title: Occurrence Download

description: A dataset containing 351 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eleutherodactylus bakeri Cochran, 1935, Eleutherodactylus walkeri Lynch, 1974)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 351 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054640-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.urzgxs
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Pakistan",
 "GadmGid is PAK.7_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aedes aegypti (Linnaeus, 1762)"
 ]
}

 The dataset includes 96 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0233643-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xfawf4
title: Occurrence Download

description: A dataset containing 393 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cordulephya pygmaea Selys, 1871"
 ]
}

 The dataset includes 393 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0134443-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mpc6ru
title: Occurrence Download

description: A dataset containing 212 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eleutherodactylus auriculatoides Noble, 1923)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 212 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054629-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7vaetj
title: Occurrence Download

description: A dataset containing 5660 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((-123.49161 48.42479,-123.48602 48.41987,-123.47251 48.41597,-123.4559 48.43026,-123.4465 48.42906,-123.44791 48.43683,-123.45736 48.4367,-123.46945 48.43938,-123.47714 48.44052,-123.48433 48.43843,-123.49161 48.42479))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5660 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0167328-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nvyy4z
title: Occurrence Download

description: A dataset containing 4129 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "VerbatimScientificName is Calliphlox amethystina"
 ]
}

 The dataset includes 4129 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0376065-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3axnc3
title: Occurrence Download

description: A dataset containing 1686 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Xeranthemum annuum L.",
 "HasCoordinate is true",
 "Year is greater than or equal to 1900",
 "BasisOfRecord is one of (Human Observation, Specimen, Unknown evidence)"
 ]
}

 The dataset includes 1686 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054630-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mcjxh6
title: Occurrence Download

description: A dataset containing 3245 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 {
 "or" : [
 "Continent is North America",
 "Continent is South America"
 ]
 },
 "OccurrenceStatus is Present",
 "TaxonKey is Brachiopoda"
 ]
}

 The dataset includes 3245 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0167337-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5kve68
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Psopheticus Alcock, 1894",
 "HasCoordinate is true",
 "Year is greater than or equal to 1970",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((108.080642 16.439832, 121.84182 16.084389, 123.975906 41.313386, 108.669355 40.867975, 108.080642 16.439832))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012431-230828120925497/datasets/export for details.
DOI: 10.15468/dl.zwbegj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Grapsus intermedius De Man, 1888",
 "HasCoordinate is true",
 "Year is greater than or equal to 1970",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((108.080642 16.439832, 121.84182 16.084389, 123.975906 41.313386, 108.669355 40.867975, 108.080642 16.439832))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012440-230828120925497/datasets/export for details.
DOI: 10.15468/dl.ugrzew
title: Occurrence Download

description: A dataset containing 655 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Buxus balearica Lam."
 ]
}

 The dataset includes 655 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0365357-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9suu3c
title: Occurrence Download

description: A dataset containing 1838 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (France, United Kingdom of Great Britain and Northern Ireland)",
 "TaxonKey is Dicentrarchus labrax (Linnaeus, 1758)",
 "Year 1000-2022"
 ]
}

 The dataset includes 1838 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022239-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4d3nrq
title: Occurrence Download

description: A dataset containing 19228974 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "Year 2003-2023"
 ]
}

 The dataset includes 19228974 records from 1762 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004091-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8301378
title: LGHAP v2:  Global daily 1-km gap-free AOD grids (2021)

description: A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP dataset (LGHAP v2), we provide 22-year-long gap free aerosol optical depth (AOD) and near-surface PM2.5 concentrations with daily 1-km resolution covering the global land area from 2000 to 2021. Leveraging an improved big earth data analytic framework with attention-reinforced tensor construction and adaptive background information updating schemes, gap-free AOD grids were firstly derived via an integration of multimodal AODs and air quality measurements acquired from diverse satellites, ground monitors, and numerical models. For better predicting PM2.5 concentration across the globe, a scene-aware ensemble learning graph attention network (SCAGAT) was then developed to account for large modeling bias over regions with limited or even none in situ air quality measurements. These datasets were archived in the NetCDF (nc) format, while data in every year were archived as an individual submission. Python, MATLAB, R, and IDL codes were also provided to help users read and visualize the LGHAP v2 data.
DOI: 10.5281/zenodo.8301379
title: LGHAP v2:  Global daily 1-km gap-free AOD grids (2021)

description: A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP dataset (LGHAP v2), we provide 22-year-long gap free aerosol optical depth (AOD) and near-surface PM2.5 concentrations with daily 1-km resolution covering the global land area from 2000 to 2021. Leveraging an improved big earth data analytic framework with attention-reinforced tensor construction and adaptive background information updating schemes, gap-free AOD grids were firstly derived via an integration of multimodal AODs and air quality measurements acquired from diverse satellites, ground monitors, and numerical models. For better predicting PM2.5 concentration across the globe, a scene-aware ensemble learning graph attention network (SCAGAT) was then developed to account for large modeling bias over regions with limited or even none in situ air quality measurements. These datasets were archived in the NetCDF (nc) format, while data in every year were archived as an individual submission. Python, MATLAB, R, and IDL codes were also provided to help users read and visualize the LGHAP v2 data.
DOI: 10.5281/zenodo.8313614
title: LGHAP v2:  Global daily 1-km gap-free PM2.5 grids (2021)

description: A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP dataset (LGHAP v2), we provide 22-year-long gap free aerosol optical depth (AOD) and near-surface PM2.5 concentrations with daily 1-km resolution covering the global land area from 2000 to 2021. Leveraging an improved big earth data analytic framework with attention-reinforced tensor construction and adaptive background information updating schemes, gap-free AOD grids were firstly derived via an integration of multimodal AODs and air quality measurements acquired from diverse satellites, ground monitors, and numerical models. For better predicting PM2.5 concentration across the globe, a scene-aware ensemble learning graph attention network (SCAGAT) was then developed to account for large modeling bias over regions with limited or even none in situ air quality measurements. These datasets were archived in the NetCDF (nc) format, while data in every year were archived as an individual submission. Python, MATLAB, R, and IDL codes were also provided to help users read and visualize the LGHAP v2 data.
DOI: 10.5281/zenodo.8313615
title: LGHAP v2:  Global daily 1-km gap-free PM2.5 grids (2021)

description: A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP dataset (LGHAP v2), we provide 22-year-long gap free aerosol optical depth (AOD) and near-surface PM2.5 concentrations with daily 1-km resolution covering the global land area from 2000 to 2021. Leveraging an improved big earth data analytic framework with attention-reinforced tensor construction and adaptive background information updating schemes, gap-free AOD grids were firstly derived via an integration of multimodal AODs and air quality measurements acquired from diverse satellites, ground monitors, and numerical models. For better predicting PM2.5 concentration across the globe, a scene-aware ensemble learning graph attention network (SCAGAT) was then developed to account for large modeling bias over regions with limited or even none in situ air quality measurements. These datasets were archived in the NetCDF (nc) format, while data in every year were archived as an individual submission. Python, MATLAB, R, and IDL codes were also provided to help users read and visualize the LGHAP v2 data.
DOI: 10.15468/dl.ymdugz
title: Occurrence Download

description: A dataset containing 97 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyporthodus septemfasciatus (Thunberg, 1793)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 97 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027868-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8310585
title: LGHAP v2:  Global daily 1-km gap-free PM2.5 grids (2011)

description: A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP dataset (LGHAP v2), we provide 22-year-long gap free aerosol optical depth (AOD) and near-surface PM2.5 concentrations with daily 1-km resolution covering the global land area from 2000 to 2021. Leveraging an improved big earth data analytic framework with attention-reinforced tensor construction and adaptive background information updating schemes, gap-free AOD grids were firstly derived via an integration of multimodal AODs and air quality measurements acquired from diverse satellites, ground monitors, and numerical models. For better predicting PM2.5 concentration across the globe, a scene-aware ensemble learning graph attention network (SCAGAT) was then developed to account for large modeling bias over regions with limited or even none in situ air quality measurements. These datasets were archived in the NetCDF (nc) format, while data in every year were archived as an individual submission. Python, MATLAB, R, and IDL codes were also provided to help users read and visualize the LGHAP v2 data.
DOI: 10.5281/zenodo.8310586
title: LGHAP v2:  Global daily 1-km gap-free PM2.5 grids (2011)

description: A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP dataset (LGHAP v2), we provide 22-year-long gap free aerosol optical depth (AOD) and near-surface PM2.5 concentrations with daily 1-km resolution covering the global land area from 2000 to 2021. Leveraging an improved big earth data analytic framework with attention-reinforced tensor construction and adaptive background information updating schemes, gap-free AOD grids were firstly derived via an integration of multimodal AODs and air quality measurements acquired from diverse satellites, ground monitors, and numerical models. For better predicting PM2.5 concentration across the globe, a scene-aware ensemble learning graph attention network (SCAGAT) was then developed to account for large modeling bias over regions with limited or even none in situ air quality measurements. These datasets were archived in the NetCDF (nc) format, while data in every year were archived as an individual submission. Python, MATLAB, R, and IDL codes were also provided to help users read and visualize the LGHAP v2 data.
DOI: 10.5281/zenodo.8308232
title: LGHAP v2:  Global daily 1-km gap-free PM2.5 grids (2009)

description: A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP dataset (LGHAP v2), we provide 22-year-long gap free aerosol optical depth (AOD) and near-surface PM2.5 concentrations with daily 1-km resolution covering the global land area from 2000 to 2021. Leveraging an improved big earth data analytic framework with attention-reinforced tensor construction and adaptive background information updating schemes, gap-free AOD grids were firstly derived via an integration of multimodal AODs and air quality measurements acquired from diverse satellites, ground monitors, and numerical models. For better predicting PM2.5 concentration across the globe, a scene-aware ensemble learning graph attention network (SCAGAT) was then developed to account for large modeling bias over regions with limited or even none in situ air quality measurements. These datasets were archived in the NetCDF (nc) format, while data in every year were archived as an individual submission. Python, MATLAB, R, and IDL codes were also provided to help users read and visualize the LGHAP v2 data.
DOI: 10.5281/zenodo.8308233
title: LGHAP v2:  Global daily 1-km gap-free PM2.5 grids (2009)

description: A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP dataset (LGHAP v2), we provide 22-year-long gap free aerosol optical depth (AOD) and near-surface PM2.5 concentrations with daily 1-km resolution covering the global land area from 2000 to 2021. Leveraging an improved big earth data analytic framework with attention-reinforced tensor construction and adaptive background information updating schemes, gap-free AOD grids were firstly derived via an integration of multimodal AODs and air quality measurements acquired from diverse satellites, ground monitors, and numerical models. For better predicting PM2.5 concentration across the globe, a scene-aware ensemble learning graph attention network (SCAGAT) was then developed to account for large modeling bias over regions with limited or even none in situ air quality measurements. These datasets were archived in the NetCDF (nc) format, while data in every year were archived as an individual submission. Python, MATLAB, R, and IDL codes were also provided to help users read and visualize the LGHAP v2 data.