Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Datasets ...
Here we quantify the abundance and distribution of three primary permafrost region disturbances (PRD; lakes and their dynamics, wildfires, retrogressive thaw slumps) using trend analysis of 30-m resolution Landsat imagery from 1999-2014 and auxiliary datasets. The dataset spans four continental-scal...
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ftdatacite:10.1594/pangaea.894755 2024-09-15T18:29:26+00:00 Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Datasets ... Nitze, Ingmar Grosse, Guido Jones, Benjamin M Romanovsky, Vladimir E Boike, Julia 2018 application/zip https://dx.doi.org/10.1594/pangaea.894755 https://doi.pangaea.de/10.1594/PANGAEA.894755 en eng PANGAEA https://hs.pangaea.de/sat/NitzeI-etal_2018/Nitze_etal_2018-DataDocumentation-v1_0.pdf https://dx.doi.org/10.1038/s41467-018-07663-3 https://hs.pangaea.de/sat/NitzeI-etal_2018/Nitze_etal_2018-DataDocumentation-v1_0.pdf Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 Cryosphere ESA Data User Element - GlobPermafrost ESA-DUE-GlobPermafrost Permafrost Research Periglacial Dynamics @ AWI AWI_PerDyn Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool PETA-CARB article Collection Supplementary Publication Series of Datasets 2018 ftdatacite https://doi.org/10.1594/pangaea.89475510.1038/s41467-018-07663-3 2024-08-01T10:53:02Z Here we quantify the abundance and distribution of three primary permafrost region disturbances (PRD; lakes and their dynamics, wildfires, retrogressive thaw slumps) using trend analysis of 30-m resolution Landsat imagery from 1999-2014 and auxiliary datasets. The dataset spans four continental-scale transects in North America (Alaska, Eastern Canada) and Eurasia (Western Siberia, Eastern Siberia), covering 2.3M km² or ~10% of the permafrost region. This data publication contains geospatial vector files (polygons) of the perimeters of PRD.The data are subdivided by PRD type (lakes, wildfire, retrogressive thaw slumps) and further subdivided by study region (T1_WS, T2_ES, T3_AK, T4_EC).T1_WS: Western SIberiaT2_ES: Eastern SiberiaT3_AK: AlaskaT4_EC: Eastern CanadaThe datasets are documented in detail in the linked document (Nitze_etal_2018: Data Documentation v1.0). ... : Vector format: ESRI ShapefileProjection: Geographic WGS84 (EPSG:4326)Vector type: Polygon ... Article in Journal/Newspaper permafrost Subarctic Alaska Siberia DataCite |
institution |
Open Polar |
collection |
DataCite |
op_collection_id |
ftdatacite |
language |
English |
topic |
Cryosphere ESA Data User Element - GlobPermafrost ESA-DUE-GlobPermafrost Permafrost Research Periglacial Dynamics @ AWI AWI_PerDyn Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool PETA-CARB |
spellingShingle |
Cryosphere ESA Data User Element - GlobPermafrost ESA-DUE-GlobPermafrost Permafrost Research Periglacial Dynamics @ AWI AWI_PerDyn Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool PETA-CARB Nitze, Ingmar Grosse, Guido Jones, Benjamin M Romanovsky, Vladimir E Boike, Julia Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Datasets ... |
topic_facet |
Cryosphere ESA Data User Element - GlobPermafrost ESA-DUE-GlobPermafrost Permafrost Research Periglacial Dynamics @ AWI AWI_PerDyn Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool PETA-CARB |
description |
Here we quantify the abundance and distribution of three primary permafrost region disturbances (PRD; lakes and their dynamics, wildfires, retrogressive thaw slumps) using trend analysis of 30-m resolution Landsat imagery from 1999-2014 and auxiliary datasets. The dataset spans four continental-scale transects in North America (Alaska, Eastern Canada) and Eurasia (Western Siberia, Eastern Siberia), covering 2.3M km² or ~10% of the permafrost region. This data publication contains geospatial vector files (polygons) of the perimeters of PRD.The data are subdivided by PRD type (lakes, wildfire, retrogressive thaw slumps) and further subdivided by study region (T1_WS, T2_ES, T3_AK, T4_EC).T1_WS: Western SIberiaT2_ES: Eastern SiberiaT3_AK: AlaskaT4_EC: Eastern CanadaThe datasets are documented in detail in the linked document (Nitze_etal_2018: Data Documentation v1.0). ... : Vector format: ESRI ShapefileProjection: Geographic WGS84 (EPSG:4326)Vector type: Polygon ... |
format |
Article in Journal/Newspaper |
author |
Nitze, Ingmar Grosse, Guido Jones, Benjamin M Romanovsky, Vladimir E Boike, Julia |
author_facet |
Nitze, Ingmar Grosse, Guido Jones, Benjamin M Romanovsky, Vladimir E Boike, Julia |
author_sort |
Nitze, Ingmar |
title |
Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Datasets ... |
title_short |
Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Datasets ... |
title_full |
Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Datasets ... |
title_fullStr |
Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Datasets ... |
title_full_unstemmed |
Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Datasets ... |
title_sort |
remote sensing quantifies widespread abundance of permafrost region disturbances across the arctic and subarctic, datasets ... |
publisher |
PANGAEA |
publishDate |
2018 |
url |
https://dx.doi.org/10.1594/pangaea.894755 https://doi.pangaea.de/10.1594/PANGAEA.894755 |
genre |
permafrost Subarctic Alaska Siberia |
genre_facet |
permafrost Subarctic Alaska Siberia |
op_relation |
https://hs.pangaea.de/sat/NitzeI-etal_2018/Nitze_etal_2018-DataDocumentation-v1_0.pdf https://dx.doi.org/10.1038/s41467-018-07663-3 https://hs.pangaea.de/sat/NitzeI-etal_2018/Nitze_etal_2018-DataDocumentation-v1_0.pdf |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.1594/pangaea.89475510.1038/s41467-018-07663-3 |
_version_ |
1810470837210316800 |