cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.950924
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200212_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950925
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200217_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950926
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200217_02, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950927
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200227_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950928
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200321_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950929
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200321_02, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950931
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200323_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950942
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200630_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950944
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200630_02, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950946
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200707_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950947
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200717_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950949
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200722_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.
DOI: 10.1594/pangaea.950950
title: Geolocated sea-ice or snow surface elevation point cloud segments from helicopter-borne laser scanner during the MOSAiC expedition flight 20200806_01, version 1

description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data &gt;85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.