Drone-based mapping of calving rates of Borebreen in Svalbard ...
This database contains drone-based mapping data of the crevassed and surging glacier of Borebreen in Svalbard, Norway. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape (version 1.8.5) and the processed data...
Main Authors: | , , , , |
---|---|
Format: | Dataset |
Language: | unknown |
Published: |
DataverseNO
2024
|
Subjects: | |
Online Access: | https://dx.doi.org/10.18710/b553mb https://dataverse.no/citation?persistentId=doi:10.18710/B553MB |
id |
ftdatacite:10.18710/b553mb |
---|---|
record_format |
openpolar |
spelling |
ftdatacite:10.18710/b553mb 2024-03-31T07:52:55+00:00 Drone-based mapping of calving rates of Borebreen in Svalbard ... Hann, Richard Rodes, Nil Gajek, Wojciech Pearce, Danni Harcourt, William 2024 https://dx.doi.org/10.18710/b553mb https://dataverse.no/citation?persistentId=doi:10.18710/B553MB unknown DataverseNO https://dx.doi.org/10.18710/b553mb/q1w9t0 https://dx.doi.org/10.18710/b553mb/rvo5if https://dx.doi.org/10.18710/b553mb/og4oh7 https://dx.doi.org/10.18710/b553mb/8azv81 https://dx.doi.org/10.18710/b553mb/snypu0 https://dx.doi.org/10.18710/b553mb/0spl08 https://dx.doi.org/10.18710/b553mb/r2fhyc https://dx.doi.org/10.18710/b553mb/vgv45b https://dx.doi.org/10.18710/b553mb/wez1wv https://dx.doi.org/10.18710/b553mb/bbirof https://dx.doi.org/10.18710/b553mb/abwhwf https://dx.doi.org/10.18710/b553mb/u4n9sh https://dx.doi.org/10.18710/b553mb/xy5r9g https://dx.doi.org/10.18710/b553mb/yytqm5 https://dx.doi.org/10.18710/b553mb/vyqjbh https://dx.doi.org/10.18710/b553mb/fwvrpl https://dx.doi.org/10.18710/b553mb/isg8tk https://dx.doi.org/10.18710/b553mb/zj20xv https://dx.doi.org/10.18710/b553mb/qepf7l https://dx.doi.org/10.18710/b553mb/egqt2y dataset Dataset 2024 ftdatacite https://doi.org/10.18710/b553mb10.18710/b553mb/q1w9t010.18710/b553mb/rvo5if10.18710/b553mb/og4oh710.18710/b553mb/8azv8110.18710/b553mb/snypu010.18710/b553mb/0spl0810.18710/b553mb/r2fhyc10.18710/b553mb/vgv45b10.18710/b553mb/wez1wv10.18710/b553mb/bbirof10.1 2024-03-04T13:45:20Z This database contains drone-based mapping data of the crevassed and surging glacier of Borebreen in Svalbard, Norway. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape (version 1.8.5) and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF, and textured 3D models in .STL and .PDF file format. In addition, a process report in archived .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 2 Pro Enterprise. The fieldwork was conducted in August of 2023 over several days with access to Borebreen via boat. The mapping area covers the crevassed glacier front on five days between 01 Aug 2023 and 12 Aug 2023. In addition, the glacier forefield was mapped over several days and combined into one fileset. There are two subsets of data. First, there are the files Glacier-subset-A/B for the 20230811 dataset. This ... Dataset glacier glacier Svalbard DataCite Metadata Store (German National Library of Science and Technology) Borebreen ENVELOPE(14.014,14.014,78.414,78.414) Norway Svalbard |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
description |
This database contains drone-based mapping data of the crevassed and surging glacier of Borebreen in Svalbard, Norway. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape (version 1.8.5) and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF, and textured 3D models in .STL and .PDF file format. In addition, a process report in archived .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 2 Pro Enterprise. The fieldwork was conducted in August of 2023 over several days with access to Borebreen via boat. The mapping area covers the crevassed glacier front on five days between 01 Aug 2023 and 12 Aug 2023. In addition, the glacier forefield was mapped over several days and combined into one fileset. There are two subsets of data. First, there are the files Glacier-subset-A/B for the 20230811 dataset. This ... |
format |
Dataset |
author |
Hann, Richard Rodes, Nil Gajek, Wojciech Pearce, Danni Harcourt, William |
spellingShingle |
Hann, Richard Rodes, Nil Gajek, Wojciech Pearce, Danni Harcourt, William Drone-based mapping of calving rates of Borebreen in Svalbard ... |
author_facet |
Hann, Richard Rodes, Nil Gajek, Wojciech Pearce, Danni Harcourt, William |
author_sort |
Hann, Richard |
title |
Drone-based mapping of calving rates of Borebreen in Svalbard ... |
title_short |
Drone-based mapping of calving rates of Borebreen in Svalbard ... |
title_full |
Drone-based mapping of calving rates of Borebreen in Svalbard ... |
title_fullStr |
Drone-based mapping of calving rates of Borebreen in Svalbard ... |
title_full_unstemmed |
Drone-based mapping of calving rates of Borebreen in Svalbard ... |
title_sort |
drone-based mapping of calving rates of borebreen in svalbard ... |
publisher |
DataverseNO |
publishDate |
2024 |
url |
https://dx.doi.org/10.18710/b553mb https://dataverse.no/citation?persistentId=doi:10.18710/B553MB |
long_lat |
ENVELOPE(14.014,14.014,78.414,78.414) |
geographic |
Borebreen Norway Svalbard |
geographic_facet |
Borebreen Norway Svalbard |
genre |
glacier glacier Svalbard |
genre_facet |
glacier glacier Svalbard |
op_relation |
https://dx.doi.org/10.18710/b553mb/q1w9t0 https://dx.doi.org/10.18710/b553mb/rvo5if https://dx.doi.org/10.18710/b553mb/og4oh7 https://dx.doi.org/10.18710/b553mb/8azv81 https://dx.doi.org/10.18710/b553mb/snypu0 https://dx.doi.org/10.18710/b553mb/0spl08 https://dx.doi.org/10.18710/b553mb/r2fhyc https://dx.doi.org/10.18710/b553mb/vgv45b https://dx.doi.org/10.18710/b553mb/wez1wv https://dx.doi.org/10.18710/b553mb/bbirof https://dx.doi.org/10.18710/b553mb/abwhwf https://dx.doi.org/10.18710/b553mb/u4n9sh https://dx.doi.org/10.18710/b553mb/xy5r9g https://dx.doi.org/10.18710/b553mb/yytqm5 https://dx.doi.org/10.18710/b553mb/vyqjbh https://dx.doi.org/10.18710/b553mb/fwvrpl https://dx.doi.org/10.18710/b553mb/isg8tk https://dx.doi.org/10.18710/b553mb/zj20xv https://dx.doi.org/10.18710/b553mb/qepf7l https://dx.doi.org/10.18710/b553mb/egqt2y |
op_doi |
https://doi.org/10.18710/b553mb10.18710/b553mb/q1w9t010.18710/b553mb/rvo5if10.18710/b553mb/og4oh710.18710/b553mb/8azv8110.18710/b553mb/snypu010.18710/b553mb/0spl0810.18710/b553mb/r2fhyc10.18710/b553mb/vgv45b10.18710/b553mb/wez1wv10.18710/b553mb/bbirof10.1 |
_version_ |
1795032304435855360 |