cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.940002
title: Raw data from Triaxus topAWI (towed ocean profiler of the AWI) during MERIAN cruise MSM93

description: The MacArtney Triaxus extended version is a remotely operated towed vehicle (ROTV). It is towed behind the ship between 2 and 10 knots and can undulate in a saw tooth pattern between a few meters below the surface and 350m depth. The umbilical provides power and a fiber optic link to sensors that are mounted on the Triaxus (see SensorWeb). The data collected by the sensors were recorded on separate computers, one computer per sensor (including the flight information from the Triaxus itself). Thus, there are 7 separate data streams saved in separate folders plus a folder with metadata information about the different dives. During long Triaxus operations, new data files would be started approximately every 4 hours, because some of the employed software programs do not allow for backing up of the files while they are still being written to. A front in the open ocean region in the vicinity of the ice edge in Fram Strait was searched for with a ~100km long constant depth Triaxus transect on July 8. When a front had been found, it was surveyed in 3D by parallel UCTD sections and drifters were deployed. The front was followed until July 16 with the repeat of parallel UCTD and Triaxus sections. In total 17 sections were occupied with the Triaxus.
DOI: 10.1594/pangaea.940576
title: Master tracks in different resolutions of HEINCKE cruise HE588, Bremerhaven - Bremerhaven, 2021-10-24 - 2021-11-04

description: Raw data acquired by position sensors on board RV Heincke during expedition HE588 were processed to receive a validated master track which can be used as reference of further expedition data. During HE588 the inertial navigation system IXSEA PHINS III and the GPS receivers Trimble Marine SPS461 and SAAB R5 SUPREME NAV were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.awi.de) with a resolution of 1 sec. Processing and evaluation of the data is outlined in the data processing report found at EPIC repository hdl:10013/epic.7ca8d284-9d84-432c-8649-0a006aa4175b. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
description: This dataset contains the master track in 10 min resolution, for other resolutions please see "Further details" and Other version" references.
DOI: 10.15468/dl.vu5eeu
title: Occurrence Download

description: A dataset containing 115 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Caecilia gracilis Shaw, 1802"
 ]
}

 The dataset includes 115 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0312143-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.939663
title: Windlidar data 2015 from Ny-Ålesund, Svalbard (AWIPEV)

description: Since December 2012 AWIPEV operates a commercial Wind Lidar (WindCube 200, Leosphere) on the roof of the AWIPEV observatory in Ny-Ålesund, which runs unattended and continuously. It uses the Doppler effect of an eye safe laser at 1.5 μm wavelength to measure the 3-dimensional vertically resolved wind with typically 10min temporal resolution. The resolution in altitude is 50m. Its range depends on weather conditions and can reach up to 5km. In this dataset the wind lidar data of 2015 from AWIPEV are presented, recorded for every day individually, saved in netcdf format and provided for download here.
description: The netcdf file for every day includes:- Time- Time for Matlab- Height- u, v and w component of the tropospheric wind field- absolute wind speed- wind direction
DOI: 10.1594/pangaea.940264
title: Mapping canopy cover in African dry forests from combined use of Sentinel-1 and Sentinel-2 data: application to Tanzania for year 2018

description: The monitoring of tropical forests has benefited from the increased availability of high-resolution earth observation data. However, the seasonality and openness of the canopy of dry tropical forests remains a challenge for optical sensors. The availability of time series of remote sensing images at 10-meters is changing this paradigm. In the context of REDD+ national reporting requirements, we investigate a methodology that is reproducible and adaptable in order to ensure user appropriation. The overall methodology consists of three main steps: (i) the generation of Sentinel-1 (S1) and Sentinel-2 (S2) layers, (ii) the collection of an ad-hoc training/validation dataset and (iii) the classification of the satellite data. Three different classification workflows are compared in terms of their capability to capture the canopy cover of forests in East Africa. The method is tested at scale, over Tanzania. Two big data computing platforms are combined to exploit the important volume of satellite data available over a yearly period. The study also explores the accuracy of two products derived from these mapping approaches: i) binary tree cover/no tree cover (TC/NTC) map, and ii) map of canopy cover classes. We demonstrate the potential of the combination of S1 SAR and S2 optical sensors to derive an accurate map of forest cover in East Africa at a spatial resolution of 10 meters for the year 2018. Our approach uses the high temporal resolution of S2 that allows to produce bimonthly cloud-free composites that reflect the seasonality of the vegetation. An overall accuracy (OA) of about 95% is reached for the TC/NTC map. When mapping different categories of forest and canopy cover, we obtain an OA over 85% both with a per pixel accuracy approach and when considering the neighbouring pixels in the classification training. The potential of S1 and S2 data for single trees discrimination is also assessed. The reference dataset (training and validation), the three best maps and the codes to produce the S1 and S2 composites on Google Earth Engine are shared here.
DOI: 10.1594/pangaea.940003
title: Raw spectra data alongside derived concentrations from the Cataract Scout Park, Australia, taken during the COALA-2020 campaign

description: Raw spectra data in .cdf format alongside derived concentrations from the Cataract Scout Park, Australia, taken during the COALA-2020 campaign.
DOI: 10.1594/pangaea.940004
title: An improved Remote Sensing-based global Surface Soil Moisture dataset (RSSSM, 2003-2020)

description: This dataset is an update of our previous dataset published on doi:10.1594/PANGAEA.912597. Based on 11 well-acknowledged global-scale microwave remote sensing-based surface soil moisture products, and with 9 main quality impact factors of microwave-based soil moisture retrieval incorporated, we developed the Remote Sensing-based global Surface Soil Moisture dataset (RSSSM, 2003~2020) through a complicated neural network approach. The spatial resolution of RSSSM is 0.1°, while the temporal resolution is approximately 10 days. The original dataset covered 2003~2018, but now it has been updated to 2020. RSSSM dataset is outstanding in terms of temporal continuity, and has full spatial coverage except for snow, ice and water bodies. The comparison against the global-scale in-situ soil moisture measurements indicates that RSSSM has a higher spatial and temporal accuracy than most of the frequently-used global/regional long-term surface soil moisture datasets. In addition, although RSSSM is remote sensing based, without the incorporation of any precipitation data or records, its interannual variation generally conforms with that of precipitation (e.g., the GPM IMERG precipitation data) and Standardized Precipitation Evapotranspiration Index (SPEI). Moreover, RSSSM can also reflect the impact of human activities, e.g., urbanization, cropland irrigation and afforestation on soil moisture changes to some degree. The data is in 'Tiff' format, and the size after compression is 2.44 GB. The relevant data describing paper has been published in the Journal 'Earth System Science Data' in 2021.
DOI: 10.15468/dl.khsdgp
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Neophascogale lorentzi (Jentink, 1911)"
 ]
}

 The dataset includes 10 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013924-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qenx6g
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arenifera stylosa (L.Bolus) H.E.K.Hartmann"
 ]
}

 The dataset includes 39 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030532-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.940014
title: Sun Photometer Data (RAW) 2017 from Ny-Ålesund, Svalbard (AWIPEV)

description: Voltages are 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.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.
description: This data set is only the raw data corresponding to doi:10.1594/PANGAEA.937596 . No calculation, for example for AOD, is done, but can be performed by everyone with the provided data in the following way (the gauge values of every day can be found in the header):1) spectra transmission: TR = (U20/UE *KFM)^(1/M), with U20: measured voltage, UE: gauge voltage/extraterrestrial signal, KFM = solar eccentricity, M: air mass2) total AOD: tau_G = |ln(TR)|3) ozone AOD: tau_O3 = (O3_Dob * O3_Gaug) / 1000, with O3_Dob: external measurement value for total ozone concentration in column [DU], O3_Gaug: Gauge value of filter4) AOD of Rayleigh atmosphere: tau_R = P/P0 * (0.00865*λ^ex), ex = - (3.9164 + 0.074*λ + 0.05/λ), with P = 1013.25hPa, P0: pressure at measurement point [hPa], λ: wavelength of filter [µm]5) AOD of aerosol: tau_AE = tau_G - tau_R - tau_O3---The data is a tar.gz file. Each measurement day contains in netcdf format the following variables:Time (minutes after midnight UTC)wavelengths ([nm], lambda)pressure [hPa]voltage [V]Header with gauge values
DOI: 10.1594/pangaea.940017
title: Sun Photometer Data (RAW) 2018 from Ny-Ålesund, Svalbard (AWIPEV)

description: Voltages are 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.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.
description: This data set is only the raw data corresponding to doi:10.1594/PANGAEA.937619. No calculation, for example for AOD, is done, but can be performed by everyone with the provided data in the following way (the gauge values of every day can be found in the header):1) spectra transmission: TR = (U20/UE *KFM)^(1/M), with U20: measured voltage, UE: gauge voltage/extraterrestrial signal, KFM = solar eccentricity, M: air mass2) total AOD: tau_G = |ln(TR)|3) ozone AOD: tau_O3 = (O3_Dob * O3_Gaug) / 1000, with O3_Dob: external measurement value for total ozone concentration in column [DU], O3_Gaug: Gauge value of filter4) AOD of Rayleigh atmosphere: tau_R = P/P0 * (0.00865*λ^ex), ex = - (3.9164 + 0.074*λ + 0.05/λ), with P = 1013.25hPa, P0: pressure at measurement point [hPa], ?: wavelength of filter [µm]5) AOD of aerosol: tau_AE = tau_G - tau_R - tau_O3---The data is a tar.gz file. Each measurement day contains in netcdf format the following variables:Time (minutes after midnight UTC)wavelengths ([nm], lambda)pressure [hPa]voltage [V]Header with gauge values
DOI: 10.15468/dl.kmgxh9
title: Occurrence Download

description: A dataset containing 4912 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Amyloporia sinuosa (Fr.) Rajchenb., Gorjón & Pildain)",
 "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 4912 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0230988-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.940283
title: Contribution of nitrogen deposition to global forest carbon sequestration

description: Human activities have drastically increased inputs of reactive nitrogen globally. Increased deposition of N onto forests may alleviate N limitation and thereby stimulated productivity and carbon (C) sequestration in forest aboveground woody biomass (AGWB), a stable C pool with long turn-over times. The associated reduction in atmospheric CO2 concentrations use represents a cooling effect of human N use that may partly offsets the warming effect of human-induced N2O emissions.The accompanying datasets give information on global spatial variation in the contribution of atmospherically deposited nitrogen (N) to carbon (C) sequestration in forest aboveground woody biomass, as well as the net climatic footprint of human N use resulting from the warming effect of N-induced direct and indirect N2O emissions on the one hand, and the cooling effect of N-induced C sequestration in forest aboveground woody biomass on the other.
description: Datasets include information on spatial variation in:* Forest biomass C-N response (additional unit of carbon sequestration in forest aboveground woody biomass per unit of atmospheric N deposition; in kg C per kg N). Forest C-N response was predicted by a regression model that was derived from data from forest fertilization experimetns which measured biomass response to N addition.* N-induced forest aboveground woody biomass C sequestration, which was derived by multiplying forest biomass C-N response with total N deposition to forests.* Net climate footprint of human N use, expressed as the ratio between additional C sequestration in forest aboveground woody biomass due to anthropogenic N deposition (as shown in Fig_2a, though Fig_2a considers total N deposition while here we only consider anthropogenic N deposition) and anthropogenic N2O emissions, both expressed as 100-year Global Warming Potential in Tg Ceq yr-1.For most variables, we provide the mean value as well as the 95% Confidence Inverval.Projection: WGS84Resolution: 0.5x0.5 degrees
DOI: 10.1594/pangaea.940022
title: Sun Photometer Data (RAW) 2019 from Ny-Ålesund, Svalbard (AWIPEV)

description: Voltages are 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.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.
description: This data set is only the raw data corresponding to doi:10.1594/PANGAEA.937629 . No calculation, for example for AOD, is done, but can be performed by everyone with the provided data in the following way (the gauge values of every day can be found in the header):1) spectra transmission: TR = (U20/UE *KFM)^(1/M), with U20: measured voltage, UE: gauge voltage/extraterrestrial signal, KFM = solar eccentricity, M: air mass2) total AOD: tau_G = |ln(TR)|3) ozone AOD: tau_O3 = (O3_Dob * O3_Gaug) / 1000, with O3_Dob: external measurement value for total ozone concentration in column [DU], O3_Gaug: Gauge value of filter4) AOD of Rayleigh atmosphere: tau_R = P/P0 * (0.00865*λ^ex), ex = - (3.9164 + 0.074*λ + 0.05/λ), with P = 1013.25hPa, P0: pressure at measurement point [hPa], λ: wavelength of filter [µm]5) AOD of aerosol: tau_AE = tau_G - tau_R - tau_O3 ---The data is a tar.gz file. Each measurement day contains in netcdf format the following variables:Time (minutes after midnight UTC)wavelengths ([nm], lambda)pressure [hPa]voltage [V]Header with gauge values
DOI: 10.1594/pangaea.939689
title: Windlidar data 2016 from Ny-Ålesund, Svalbard (AWIPEV)

description: Since December 2012 AWIPEV operates a commercial Wind Lidar (WindCube 200, Leosphere) on the roof of the AWIPEV observatory in Ny-Ålesund, which runs unattended and continuously. It uses the Doppler effect of an eye safe laser at 1.5 μm wavelength to measure the 3-dimensional vertically resolved wind with typically 10min temporal resolution. The resolution in altitude is 50m. Its range depends on weather conditions and can reach up to 5km. In this dataset the wind lidar data of 2016 from AWIPEV are presented, recorded for every day individually, saved in netcdf format and provided for download here.
description: The netcdf file for every day includes:- Time- Time for Matlab- Height- u, v and w component of the tropospheric wind field- absolute wind speed- wind direction
DOI: 10.15468/dl.dfch6a
title: Occurrence Download

description: A dataset containing 7797 species occurrences available in GBIF matching the query:
{
 "and" : [
 "VerbatimScientificName is Thamnophilus palliatus",
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Year 2011-2021",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen, Material citation, Material sample)"
 ]
 }
 }
 ]
}

 The dataset includes 7797 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0087185-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.939710
title: Windlidar data 2017 from Ny-Ålesund, Svalbard (AWIPEV)

description: Since December 2012 AWIPEV operates a commercial Wind Lidar (WindCube 200, Leosphere) on the roof of the AWIPEV observatory in Ny-Ålesund, which runs unattended and continuously. It uses the Doppler effect of an eye safe laser at 1.5 μm wavelength to measure the 3-dimensional vertically resolved wind with typically 10min temporal resolution. The resolution in altitude is 50m. Its range depends on weather conditions and can reach up to 5km. In this dataset the wind lidar data of 2017 from AWIPEV (except the months February and April) are presented, recorded for every day individually, saved in netcdf format and provided for download here.
description: The netcdf file for every day includes:- Time- Time for Matlab- Height- u, v and w component of the tropospheric wind field- absolute wind speed- wind direction
DOI: 10.1594/pangaea.939712
title: Physical Oceanography measured with UCTD (Underway CTD) during MERIAN cruise MSM93

description: The Teledyne Underway CTD was operated in tow-yo mode: the winch brake is disengaged and the probe is in approximate free-fall at 4m/s to 1m/s vertical speed collecting data for a cast. Then the brake is engaged and the probe is hauled in until it is within 10m horizontal behind the vessel at the sea surface. The winch is then disengaged and the next cast starts. A straight section is collected with the same probe in the water. At the end of the section, the probe is recovered. The data is recorded internally on the probe and only read out once the probe is back on deck. Here we provide 1 m vertically averaged data from the downcasts. The processing follows Ullman and Hebert: “Processing of Underway CTD Data”, Journal of Atmospheric and Oceanic Technology (2014), https://doi.org/10.1175/JTECH-D-13-00200.1. A front in the open ocean region in the vicinity of the ice edge in Fram Strait was searched for with a ~100km long constant depth Triaxus transect on July 8. When a front had been found, it was surveyed in 3D by parallel UCTD sections and drifters were deployed. The front was followed until July 16 with the repeat of parallel UCTD and Triaxus sections. During one UCTD section, an operator error resulted in the fact that the probe appeared to have been started while in fact it had not been started before deployment. In total 21 sections were occupied excluding the section where no data was recorded (station MSM93_62-1).
DOI: 10.15468/dl.hj79wp
title: Occurrence Download

description: A dataset containing 13697 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((8.36795 45.40135,18.68318 45.40135,18.68318 51.08992,8.36795 51.08992,8.36795 45.40135))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Strix aluco Linnaeus, 1758"
 ]
}

 The dataset includes 13697 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027430-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.