cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.964690
title: Measurements of CH4 concentration and 𝜹13C-CH4 in seawater after the Nord Stream 2 detonation in October 2022

description: Our sampling took place on the RV Skagerak on 3-5 October 2022 . In total, 20 stations Northeast of the island Bornholm were covered. 16 sites were located within the methane plume formed by the intense methane bubbling in the week after the explosion, but outside the 7 NM wide security circle around the leaks. In addition, we included 4 sites on the track to the explosion site to detect natural background concentrations.  Profiles of salinity and temperature in the water column were recorded by a Sea-Bird SBE911, a conductivity–temperature–depth (CTD) system. Water samples for the analysis of concentrations of dissolved methane and 𝜹13C-CH4 values were taken from up to 10 discrete water depths across the entire water from Niskin bottles mounted on a rosette sampler. The deepest bottles were closed at about 1–2 m above the sea floor. The selection of water sampling depths was determined taking the thermocline and halocline depths into consideration.  Sampling procedure was performed as follows: Seawater from the rosette were filled in 500 ml glass vials, sealed with rubber stoppers and crimped with aluminum caps. Care was taken to avoid any bubbles. A headspace was created by injecting 20 ml hydrocarbon free synthetic air while at the same time water was pushed out via a second needle to balance the pressure. When equilibrated, a subsample was removed with a gas tight syringe and injected to the SSIM (Small Sample Isotope Module) coupled to a Picarro G2132-i cavity ring-down spectrometer. For calibration, we used standard gas mixtures with different concentrations (Fa. Linde), and standard gas mixtures with isotopic ratios of -25 ‰ vs. VPDB, -45 ‰ vs. VPDB and 69 ‰ vs. VPDB (Fa Airgas). Considering the complete sampling procedure, the overall total uncertainty was &lt; 5% estimated on duplicates. The calculation of the dissolved methane concentration followed Wiesenburg and Guinasso (1979).
DOI: 10.1594/pangaea.955870
title: Geochemistry of the Pauzhetka tephra intervals in sediment core SO264_55-1

description: he XRF-scanning measurements were carried out with an Avaatech XRF core scanner at the AWI in Bremerhaven. The X-ray excitation scanning settings were 10 kV at 150 mA with no filter for a count time of 10 s, and a rhodium target X-ray tube was deployed. The sample distance was 10 mm, with a 10x12 mm slit size.
DOI: 10.1594/pangaea.955871
title: Geochemistry of the Pauzhetka tephra intervals in sediment core SO264_56-2

description: he XRF-scanning measurements were carried out with an Avaatech XRF core scanner at the AWI in Bremerhaven. The X-ray excitation scanning settings were 10 kV at 150 mA with no filter for a count time of 10 s, and a rhodium target X-ray tube was deployed. The sample distance was 10 mm, with a 10x12 mm slit size.
DOI: 10.1594/pangaea.955864
title: Geochemistry of the Pauzhetka tephra intervals in sediment core SO264_45-2

description: he XRF-scanning measurements were carried out with an Avaatech XRF core scanner at the AWI in Bremerhaven. The X-ray excitation scanning settings were 10 kV at 150 mA with no filter for a count time of 10 s, and a rhodium target X-ray tube was deployed. The sample distance was 10 mm, with a 10x12 mm slit size.
DOI: 10.1594/pangaea.955867
title: Geochemistry of the Pauzhetka tephra intervals in sediment core SO264_47-2

description: he XRF-scanning measurements were carried out with an Avaatech XRF core scanner at the AWI in Bremerhaven. The X-ray excitation scanning settings were 10 kV at 150 mA with no filter for a count time of 10 s, and a rhodium target X-ray tube was deployed. The sample distance was 10 mm, with a 10x12 mm slit size.
DOI: 10.1594/pangaea.955868
title: Geochemistry of the Pauzhetka tephra intervals in sediment core SO264_49-2

description: he XRF-scanning measurements were carried out with an Avaatech XRF core scanner at the AWI in Bremerhaven. The X-ray excitation scanning settings were 10 kV at 150 mA with no filter for a count time of 10 s, and a rhodium target X-ray tube was deployed. The sample distance was 10 mm, with a 10x12 mm slit size.
DOI: 10.1594/pangaea.955869
title: Geochemistry of the Pauzhetka tephra intervals in sediment core SO264_53-2

description: he XRF-scanning measurements were carried out with an Avaatech XRF core scanner at the AWI in Bremerhaven. The X-ray excitation scanning settings were 10 kV at 150 mA with no filter for a count time of 10 s, and a rhodium target X-ray tube was deployed. The sample distance was 10 mm, with a 10x12 mm slit size.
DOI: 10.1594/pangaea.974015
title: Master tracks in different resolutions from POLAR 6 flight P6-252_SLOGIS_2024_2407310201
DOI: 10.1594/pangaea.974007
title: Master tracks in different resolutions from POLAR 6 flight P6-252_SLOGIS_2024_2408030501
DOI: 10.1594/pangaea.974016
title: Master track from POLAR 6 flight P6-252_SLOGIS_2024_2408010301 in 1 sec resolution (zipped, 1 MB)
DOI: 10.1594/pangaea.974008
title: Master track from POLAR 6 flight P6-252_SLOGIS_2024_2407270101 in 1 sec resolution (zipped, 1 MB)
DOI: 10.1594/pangaea.974009
title: Master tracks in different resolutions from POLAR 6 flight P6-252_SLOGIS_2024_2408020401
DOI: 10.1594/pangaea.974010
title: Master track from POLAR 6 flight P6-252_SLOGIS_2024_2408030501 in 1 sec resolution (zipped, 865 KB)
DOI: 10.1594/pangaea.962006
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Trail Valley Creek, Canada (subset 06)

description: As part of the MOSES airborne campaign led by the Alfred Wegener Institute in 2018, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 13.96 px/m³ and 4.74 px/m³ respectively. This dataset covers approximately 21.40 km² of Trail Valley Creek, Canada, with all images collected on 22 August 2018. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.974011
title: Master track from POLAR 6 flight P6-252_SLOGIS_2024_2407310201 in 1 sec resolution (zipped, 1 MB)
DOI: 10.1594/pangaea.974012
title: Master tracks in different resolutions from POLAR 6 flight P6-252_SLOGIS_2024_2407270101
DOI: 10.1594/pangaea.974013
title: Master track from POLAR 6 flight P6-252_SLOGIS_2024_2408020401 in 1 sec resolution (zipped, 1 MB)
DOI: 10.1594/pangaea.962010
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Trail Valley Creek, Canada (subset 07)

description: As part of the MOSES airborne campaign led by the Alfred Wegener Institute in 2018, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 14.12 px/m³ and 5.05 px/m³ respectively. This dataset covers approximately 21.41 km² of Trail Valley Creek, Canada, with all images collected on 22 August 2018. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962011
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Trail Valley Creek, Canada (subset 08)

description: As part of the MOSES airborne campaign led by the Alfred Wegener Institute in 2018, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 11.92 px/m³ and 3.96 px/m³ respectively. This dataset covers approximately 15.46 km² of Trail Valley Creek, Canada, with all images collected on 22 August 2018. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.974014
title: Master tracks in different resolutions from POLAR 6 flight P6-252_SLOGIS_2024_2408010301
DOI: 10.1594/pangaea.962543
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of the Central North Slope, Alaska (subset 03)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 8.57 pts/m² and 3.00 pts/m², respectively. This dataset covers approximately 15.08 km² of the central North Slope in Alaska, with all images collected on 29 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962321
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Ketik Fire Scar, Alaska (subset 09)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 36.17 pts/m² and 12.62 pts/m², respectively. This dataset covers approximately 6.66 km² of the Ketik fire scar in Alaska, with all images collected on 27 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962534
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Meade Fire Scar, Alaska (subset 01)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 9.82 pts/m² and 3.44 pts/m², respectively. This dataset covers approximately 31.63 km² of the Meade fire scar in Alaska, with all images collected on 29 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962536
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Meade Fire Scar, Alaska (subset 02)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 9.11 pts/m² and 3.21 pts/m², respectively. This dataset covers approximately 21.10 km² of the Meade fire scar in Alaska, with all images collected on 29 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962539
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of the Central North Slope, Alaska (subset 01)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 9.00 pts/m² and 3.15 pts/m², respectively. This dataset covers approximately 13.79 km² of the central North Slope in Alaska, with all images collected on 29 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962541
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of the Central North Slope, Alaska (subset 02)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 8.78 pts/m² and 3.07 pts/m², respectively. This dataset covers approximately 15.15 km² of the central North Slope in Alaska, with all images collected on 29 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962544
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of the Central North Slope, Alaska (subset 04)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 8.92 pts/m² and 3.11 pts/m², respectively. This dataset covers approximately 14.54 km² of the central North Slope in Alaska, with all images collected on 29 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.866273
title: Underway physical oceanography and carbon dioxide measurements during Trans Future 5 cruise PAT520140812

description: Cruise QC flag: B (see further details). The Fair Data Use Statement for SOCAT can be found at hdl:10013/epic.48576.d001
DOI: 10.1594/pangaea.962718
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of the Northern Noatak Valley, Alaska (subset 01)

description: As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 28.77 pts/m² and 9.89 pts/m², respectively. This dataset covers approximately 12.16 km² of the northern Noatak Valley in Alaska, with all images collected on 2 July 2021. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962798
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of the Imuruk Volcanic Field, Alaska (subset 03)

description: As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 12.85 pts/m² and 4.68 pts/m², respectively. This dataset covers approximately 16.94 km² of the Imuruk volcanic field in Alaska, with all images collected on 10 July 2021. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962776
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Lake Basins on the Northern Seward Peninsula, Alaska (West, subset 01)

description: As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 8.93 pts/m² and 3.18 pts/m², respectively. This dataset covers approximately 18.30 km² of drained thermokarst lake basins on the northern Seward Peninsula in Alaska, with all images collected on 9 July 2021. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.961941
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Trail Valley Creek, Canada (subset 01)

description: As part of the MOSES airborne campaign led by the Alfred Wegener Institute in 2018, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 12.36 pts/m³ and 4.28 pts/m³ respectively. This dataset covers approximately 17.35 km² of Trail Valley Creek, Canada, with all images collected on 22 August 2018. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962091
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Anaktuvuk River Fire Scar (subset 01)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 24.86 pts/m² and 8.60 pts/m², respectively. This dataset covers approximately 5.81 km² of the Anaktuvuk River fire scar in Alaska, with all images collected on 22 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.961944
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Trail Valley Creek, Canada (subset 02)

description: As part of the MOSES airborne campaign led by the Alfred Wegener Institute in 2018, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 16.19 px/m³ and 5.15 px/m³ respectively. This dataset covers approximately 21.36 km² of Trail Valley Creek, Canada, with all images collected on 22 August 2018. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.