cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.63cdts
title: Occurrence Download

description: A dataset containing 400 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Caiman crocodilus crocodilus"
 ]
}

 The dataset includes 400 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069438-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.weuhpu
title: Occurrence Download

description: A dataset containing 11488 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ageratum conyzoides L."
 ]
}

 The dataset includes 11488 records from 404 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0394670-210914110416597/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.28794806
title: Suzuki Data.xlsx

description: Effects of calcineurin inhibitors on intestinal barrier in Caco-2 cells
DOI: 10.15468/dl.txvezv
title: Occurrence Download

description: A dataset containing 49 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is France",
 "Country is Spain",
 "Country is Belgium",
 "Country is Andorra",
 "Country is Switzerland",
 "Country is Italy",
 "Country is Portugal"
 ]
 },
 "TaxonKey is Eisenia Michaelsen, 1900"
 ]
}

 The dataset includes 49 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027136-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.937356
title: Sun Photometer Data (AOD) 2012 from Ny-Ålesund, Svalbard (AWIPEV)

description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions.The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument.In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at AWIPEV for the time 19. March 2012 until 30. September 2012. The variables are in netcdf format for each measurement day.
description: Each measurement day contains in netcdf format the following variables:Time (minutes after midnight UTC)wavelengths (nm lambda)AODModified Angstrom parameters (3 values!)traditional Angstrom parameters (2 values)
DOI: 10.15468/dl.544jvp
title: Occurrence Download

description: A dataset containing 2710 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Netherlands",
 "TaxonKey is Populus nigra L.",
 "Year 1950-2023"
 ]
}

 The dataset includes 2710 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0113793-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n7jy7g
title: Occurrence Download

description: A dataset containing 22879 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coris monspeliensis L."
 ]
}

 The dataset includes 22879 records from 184 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0312096-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.938052
title: UAV-based NDVI data of four Arctic tundra environments (Abisko region) at summer vegetation peak for 2018 and 2019

description: Unmanned Aerial Vehicle (UAV) data were collected using an eBee fixed-wing mapping drone (senseFly, Switzerland) with a Sequoia multi-spectral (Parrot, France) camera sensor at four study areas in the Torneträsk region, northern Sweden. The areas have an extent of 15–21 ha (~350 m × ~500 m). The setup covers at large the climatic variability of the Fennoscandian forest-tundra ecotone. The imagery was recorded during vegetation peak productivity between July 27th and August 4th in 2018 and 2019. The Sequoia sensor provides imagery in green, red, red-edge and near-infrared bands (G,R,RE,NIR). The normalized difference vegetation index (NDVI) was extracted using the R and NIR bands. Overexposed snow areas were gap-filled following Siewert and Olofsson (2020). Radiometric calibration was performed using spectral reflectance panels (MosaicMill, Finland). The imagery has a ground resolution of 11.4 cm–13.5 cm depending on flight and area after photogrammetric processing using Pix4Dmapper (Pix4D SA, Switzerland). The imagery was georeferenced with 4–8 ground reference markers using centimetre precision DGPS. Co-registration between 2018 and 2019 was generally near pixel-perfect and did mostly not deviate more than 2-3 pixels for locations within the analyzed core mapping area.The imagery was collected to assess Arctic vegetation productivity and the impact that interannual rodent population cycles of voles and lemmings can have on key vegetation during population peaks. The results are published in Siewert and Olofsson (2021).
DOI: 10.15468/dl.rrqry1
title: Occurrence Download

description: A dataset containing 5055 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Panaeolus (Fr.) Quél., 1872"
 ]
}

 The dataset includes 5055 records from 111 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040287-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7fsnpv
title: Occurrence Download

description: A dataset containing 404 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cissus L.",
 "BasisOfRecord is one of (Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (United States of America, Canada)"
 ]
}

 The dataset includes 404 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0328487-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.87bx8q
title: Occurrence Download

description: A dataset containing 56699 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is University of British Columbia Herbarium (UBC) - Lichen Collection"
 ]
}

 The dataset includes 56699 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0113828-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.938077
title: UAV-based land cover maps for four Arctic tundra environments (Abisko region)

description: Object-based land cover maps reflecting different ecological habitats were generated for four study areas in the Torneträsk region, northern Sweden. Unmanned Aerial Vehicle (UAV) data was collected using an eBee fixed-wing mapping drone (senseFly, Switzerland) with a Sequoia multi-spectral (Parrot, France) camera sensor. The area was then segmented with all four bands (G,R,RE,NIR) at a resolution of 0.3 m using mean shift segmentation. Environmental data to inform the classification was extracted from early seasonal, peak seasonal and late seasonal UAV flights of 2018 using the spectral bands and the NDVI. Additional topographic layers were generated either from the UAV imagery or the Swedish national elevation data at 2 m resolution or laser data (Lantmäteriet). These additional layers were vegetation height, catchment slope, wetness index, relative slope position and slope. Based on the environmental data, the segments were then classified using a random forest machine learning classifier. Training areas were identified in the RGB UAV imagery and on field photographs. The classes describe common Arctic land cover types and reflect potential vole and lemming habitats. Accuracy was assessed using the out-of-bag error, Overall Accurcay and the Kappa index.
description: Accuracy assessment values of the land cover classifications.NF: OOB estimate of error rate: 3.22%, Accuracy : 0.67, Kappa : 0.60NT: OOB estimate of error rate: 5.67%, Accuracy : 0.58, Kappa : 0.50VJ: OOB estimate of error rate: 0.97%, Accuracy : 0.61, Kappa : 0.55KJ: OOB estimate of error rate: 0.32%, Accuracy : 0.70, Kappa : 0.65
DOI: 10.15468/dl.hlqp2f
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Orconectes illinoiensis Brown, 1956"
 ]
}

 The dataset includes 11 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040293-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.938381
title: Ice Surface Velocity in the Eastern Arctic from Past Spaceborne Satellite SAR data

description: Nearly complete mosaics of winter ice surface velocities for the 1990's over the Eastern Arctic (Novaya Zemlya, Franz-Josef-Land, Severnaya Zemlya and Svalbard) were compiled based on historical SAR data. Offset-tracking to JERS-1 SAR data of the time period 1992-1998 was mainly applied. Data gaps were complemented using SAR interferometry and offset-tracking of ERS-1/2 SAR data of the time period 1991-1997. Knowledge on ice surface velocity of glaciers and ice caps contributes to a better understanding of a wide range of processes related to glacier dynamics, mass change and response to climate. In order to study long-term variability of winter ice surface velocity from the 1990's to present, velocity maps computed with offset-tracking from 2008-2011 ALOS-1 PALSAR-1 and 2020-2021 Sentinel-1 data are also provided.
description: Two sets of data containing historical ice surface velocities over the Eastern Arctic (Novaya Zemlya, Franz-Josef-Land, Severnaya Zemlya and Svalbard) are provided.The velocities derived from offset-tracking of JERS-1 (1992-1998), ERS-1/2 (1991-2010) and ALOS-1 PALSAR-1 (2006-2011) data are available in vector format with metadata information for single image tracks. A comma-separated values (csv) file provides the northing and easting coordinates of measurement points, the elevation, the displacement in metres in the x, y and z directions, and the cross-correlation coefficient for each measurement. A metadata file in xml format provides information about the SAR images used, the processing parameters and quality aspects of the data such as the percent of valid information over ice and statistical measures over ice-free regions. In addition, for each image pair geotiff's of the three-dimensional ice surface displacement maps, the two intensity images, the differential interferogram, the phase coherence image, an RGB color composite of the coherence, intensity and intensity difference between both images, and the layover and shadow map are available.Mosaics of ice velocities from various sensors and time intervals are available in GeoTIFF format. This includes offset-tracking mosaics computed from the best winter JERS-1, ERS-1 and ALOS-1 PALSAR-1 image pairs, ERS-1/2 InSAR ice velocity maps of Nordaustlandet (Svalbard), South Svalbard and North-West Svalbard, and Sentinel-1 offset-tracking mosaics computed from winter 2020/2021 data.
DOI: 10.1594/pangaea.937619
title: Sun Photometer Data (AOD) 2018 from Ny-Ålesund, Svalbard (AWIPEV)

description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions.The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument.In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at AWIPEV for the time 10. March 2018 until 30. September 2018. The variables are in netcdf format for each measurement day. The used instrument for the measurment period was SP1A31.
description: Each measurement day contains in netcdf format the following variables:Time (minutes after midnight UTC)wavelengths (nm lambda)AODModified Angstrom parameters (3 values!)traditional Angstrom parameters (2 values)
DOI: 10.15468/dl.zav8aq
title: Occurrence Download

description: A dataset containing 3913 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-96.25371 31.37662,-89.07241 31.37662,-89.07241 37.02033,-96.25371 37.02033,-96.25371 31.37662))",
 "HasGeospatialIssue is false",
 "TaxonKey is Protonotaria citrea (Boddaert, 1783)",
 "Year 2021-2022"
 ]
}

 The dataset includes 3913 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0328489-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3sq27z
title: Occurrence Download

description: A dataset containing 1561 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Country is one of (United States of America, Mexico, Canada)",
 "Year is greater than 1978",
 "Year is less than 2014",
 "HasGeospatialIssue is false",
 "TaxonKey is Crotaphytus collaris (Say, 1822)"
 ]
}

 The dataset includes 1561 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0113839-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sh9g8z
title: Occurrence Download

description: A dataset containing 394 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-6.14315 37.09212,-4.79131 37.09212,-4.79131 37.69123,-6.14315 37.69123,-6.14315 37.09212))",
 "HasCoordinate is true",
 "TaxonKey is Ulex parviflorus Pourr.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 394 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000440-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k9eueu
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Antrodia alpina (Litsch.) Gilb. & Ryvarden)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 35 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0230982-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kbj7we
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calanthe hyacinthina Schltr."
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0113866-230224095556074/datasets/export for details.
DOI: 10.1594/pangaea.937400
title: A high-resolution dataset of farmland area in the Tibetan Plateau

description: It is of practical significance for optimizing and adjusting the farmland spatial utilization and maintaining regional food security to identify the spatial distribution of farmland resources. Farmland space research depends on the land use data that accurately reflects the spatial information. At present, the resolution of existing land use data is low, ranging from 10 m to 8 km. Among them, the 30 m-resolution land use data compiled using the Landsat images, as released by the Resource and Environmental Science and Data Center of the Chinese Academy of Sciences are the highest resolution and long-term series data product available for China. However, by high-resolution image interpretation and field verification, we found that the dataset involved large deviations and uncertainties, mainly due to the reasons that the farmland in Tibetan Plateau (TP) was fragmented with small parcels, and thus cannot be accurately extracted from the Landsat images. To this end, the 1 m-resolution farmland dataset was visually interpreted from Google Earth high-resolution images in this study, which contained farmland of the TP in 2018, and that of the Three River Region (TRR) and Huangshui River Basin (HRB) in 2000 and 2018. The objects in the Google Earth high-resolution images were clearly distinguishable, and the farming characteristics of land were obvious, ensuring the accuracy of the interpretation results. In addition, this study randomly checked 230 plots collected by field surveys in 2018–2021, finding that 95.22% of the farmland parcels has been correctly identified, which further improved the reliability of the interpreted farmland dataset. This farmland dataset can provide references for farmland and agriculture research in the TP.
description: Spatial farmland dataset contains 5 shp files, namely Farmland in the TP in 2018, Farmland in the TRR in 2000, Farmland in the TRR in 2018, Farmland in the HRB in 2000, and Farmland in the HRB in 2018, respectively, which can be read by ArcGIS software. County-level farmland area data are stored per county in Excel format, named as Farmland_county.xls. And the farmland altitude information data is stored in the attribute table of spatial farmland data in shp format.
DOI: 10.1594/pangaea.938422
title: Vertical displacement time series from GNSS stations in the great Alpine area

description: ASCII files reporting the position time-series, in the Eurasia-fixed reference frame, of GNSS in the great Alpine area (excluding Switzerland). The columns are: Time, U, Su, site, long, lati, representing, respectively, epoch (in decimal years), displacement in the Up component (in mm), uncertainty (one standard deviation) of the Up component (in mm), Station ID, Longitude of the station (°), Latitude of the station (°).
DOI: 10.15468/dl.6ny5ka
title: Occurrence Download

description: A dataset containing 446 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Système d'Information sur la Nature et les Paysages d'Ile de France - Données du/de la naturaliste Courbois Aymeric provenant de la base de donnée du SINP Île-de-France CETTIA"
 ]
}

 The dataset includes 446 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011168-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.