Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service
This raster dataset, in Cloud Optimized GeoTIFF format (COG), provides information on land surface changes at the pan-arctic scale. Multispectral Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI imagery (cloud-cover less than 80%, months July and August) was used for detecting disturbance trends (ass...
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Format: | Dataset |
Language: | English |
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PANGAEA
2024
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Online Access: | https://doi.pangaea.de/10.1594/PANGAEA.964814 https://doi.org/10.1594/PANGAEA.964814 |
id |
ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.964814 |
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record_format |
openpolar |
institution |
Open Polar |
collection |
PANGAEA - Data Publisher for Earth & Environmental Science |
op_collection_id |
ftpangaea |
language |
English |
topic |
Arctic_PASSION Arctic_PASSION_Permafrost_Service Arctic PASSION Binary Object Binary Object (File Size) Binary Object (Media Type) CCI Permafrost Circum-arctic permafrost region Coastline change Earth observation ESA_CCI_Permafrost_CCN2 ESA GlobPermafrost File content GlobPermafrost Horizontal datum Lake change Lake drainage Land cover change Latitude northbound southbound Longitude eastbound westbound Multispectral index NSF Permafrost Discovery Gateway Pan-Arctic observing System of Systems: Implementing Observations for societal Needs Permafrost_Discovery_Gateway PETA-CARB Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool Raster cell size River bank erosion SAT satellite data Satellite remote sensing Shore erosion Thaw slumping thermokarst |
spellingShingle |
Arctic_PASSION Arctic_PASSION_Permafrost_Service Arctic PASSION Binary Object Binary Object (File Size) Binary Object (Media Type) CCI Permafrost Circum-arctic permafrost region Coastline change Earth observation ESA_CCI_Permafrost_CCN2 ESA GlobPermafrost File content GlobPermafrost Horizontal datum Lake change Lake drainage Land cover change Latitude northbound southbound Longitude eastbound westbound Multispectral index NSF Permafrost Discovery Gateway Pan-Arctic observing System of Systems: Implementing Observations for societal Needs Permafrost_Discovery_Gateway PETA-CARB Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool Raster cell size River bank erosion SAT satellite data Satellite remote sensing Shore erosion Thaw slumping thermokarst Nitze, Ingmar Lübker, Tillmann Grosse, Guido Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service |
topic_facet |
Arctic_PASSION Arctic_PASSION_Permafrost_Service Arctic PASSION Binary Object Binary Object (File Size) Binary Object (Media Type) CCI Permafrost Circum-arctic permafrost region Coastline change Earth observation ESA_CCI_Permafrost_CCN2 ESA GlobPermafrost File content GlobPermafrost Horizontal datum Lake change Lake drainage Land cover change Latitude northbound southbound Longitude eastbound westbound Multispectral index NSF Permafrost Discovery Gateway Pan-Arctic observing System of Systems: Implementing Observations for societal Needs Permafrost_Discovery_Gateway PETA-CARB Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool Raster cell size River bank erosion SAT satellite data Satellite remote sensing Shore erosion Thaw slumping thermokarst |
description |
This raster dataset, in Cloud Optimized GeoTIFF format (COG), provides information on land surface changes at the pan-arctic scale. Multispectral Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI imagery (cloud-cover less than 80%, months July and August) was used for detecting disturbance trends (associated with abrupt permafrost degradation) between 2003 and 2022. For each satellite image we calculated the Tasseled Cap multi-spectral index to translate the spectral reflectance signal to the semantic information Brightness, Greenness, and Wetness. In order to characterize change information, we calculated the linear trend of the Brightness, Greenness and Wetness over two decades on the individual pixel level. The final map product therefore contains information on the direction and magnitude of change for all three Tasseled Cap parameters in 30m spatial resolution across the pan-arctic permafrost domain. Features detected include coastal erosion, lake drainage, infrastructure expansion, and fires. The general processing methodology was developed by Fraser et al. 2014 and adapted and expanded by Nitze et al. 2016 and Nitze et al. 2018. Here we upscaled the processing to the circum-arctic permafrost region and the recent 20-year period from 2003 through 2022. The service covers the permafrost region up to 81° North: Alaska (USA), Canada, Greenland, Iceland, Norway, Sweden, Finland, Russia, Mongolia, and China. For Russia and China, regions not containing permafrost were excluded. The data has been processed in Google EarthEngine within the research projects ERC PETA-CARB, ESA CCI+ Permafrost, NSF Permafrost Discovery Gateway, and EU Arctic PASSION. The dataset is a contribution to the 'Panarctic requirements-driven Permafrost Service' of the Arctic PASSION project (see references). Changes in the Tasseled Cap indices Brightness, Greenness, and Wetness are displayed in the image bands red, green, and blue, respectively. Here, coastal erosion (a trend of a land surface transitioning to a water surface) is depicted in ... |
format |
Dataset |
author |
Nitze, Ingmar Lübker, Tillmann Grosse, Guido |
author_facet |
Nitze, Ingmar Lübker, Tillmann Grosse, Guido |
author_sort |
Nitze, Ingmar |
title |
Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service |
title_short |
Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service |
title_full |
Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service |
title_fullStr |
Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service |
title_full_unstemmed |
Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service |
title_sort |
pan-arctic visualization of landscape change (2003-2022), arctic passion permafrost service |
publisher |
PANGAEA |
publishDate |
2024 |
url |
https://doi.pangaea.de/10.1594/PANGAEA.964814 https://doi.org/10.1594/PANGAEA.964814 |
op_coverage |
MEDIAN LATITUDE: 53.999933 * MEDIAN LONGITUDE: 179.999122 * SOUTH-BOUND LATITUDE: 26.999825 * WEST-BOUND LONGITUDE: 179.998231 * NORTH-BOUND LATITUDE: 81.000042 * EAST-BOUND LONGITUDE: -179.999986 * DATE/TIME START: 2003-01-01T00:00:00 * DATE/TIME END: 2022-12-31T00:00:00 |
long_lat |
ENVELOPE(179.998231,-179.999986,81.000042,26.999825) |
genre |
Arctic Arctic Greenland Iceland permafrost Thermokarst Alaska |
genre_facet |
Arctic Arctic Greenland Iceland permafrost Thermokarst Alaska |
op_relation |
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung; Arctic PASSION Project: Arctic Landscape Explorer (ALEX). https://alex.awi.de/ Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung; Arctic PASSION Project: Public Web Map Service (WMS, Capabilities). https://maps.awi.de/services/common/permafrost/wms?request=GetCapabilities&service=WMS Arctic PASSION Project: Pan-Arctic observing System of Systems: Implementing Observations for societal Needs (Arctic PASSION) %7C Project website. https://arcticpassion.eu/ Fraser, Robert; Olthof, Ian; Kokelj, Steven V; Lantz, Trevor C; Lacelle, Denis; Brooker, Alexander; Wolfe, Stephen A; Schwarz, Steve (2014): Detecting Landscape Changes in High Latitude Environments Using Landsat Trend Analysis: 1. Visualization. Remote Sensing, 6(11), 11533-11557, https://doi.org/10.3390/rs61111533 Nitze, Ingmar; Grosse, Guido (2016): Detection of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks. Remote Sensing of Environment, 181, 27-41, https://doi.org/10.1016/j.rse.2016.03.038 Nitze, Ingmar; Grosse, Guido; Jones, Benjamin M; Romanovsky, Vladimir E; Boike, Julia (2018): Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic. Nature Communications, 9(1), https://doi.org/10.1038/s41467-018-07663-3 https://doi.pangaea.de/10.1594/PANGAEA.964814 https://doi.org/10.1594/PANGAEA.964814 |
op_rights |
CC-BY-4.0: Creative Commons Attribution 4.0 International Access constraints: unrestricted info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1594/PANGAEA.96481410.3390/rs6111153310.1016/j.rse.2016.03.03810.1038/s41467-018-07663-3 |
_version_ |
1799471116428771328 |
spelling |
ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.964814 2024-05-19T07:32:56+00:00 Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service Nitze, Ingmar Lübker, Tillmann Grosse, Guido MEDIAN LATITUDE: 53.999933 * MEDIAN LONGITUDE: 179.999122 * SOUTH-BOUND LATITUDE: 26.999825 * WEST-BOUND LONGITUDE: 179.998231 * NORTH-BOUND LATITUDE: 81.000042 * EAST-BOUND LONGITUDE: -179.999986 * DATE/TIME START: 2003-01-01T00:00:00 * DATE/TIME END: 2022-12-31T00:00:00 2024 text/tab-separated-values, 16 data points https://doi.pangaea.de/10.1594/PANGAEA.964814 https://doi.org/10.1594/PANGAEA.964814 en eng PANGAEA Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung; Arctic PASSION Project: Arctic Landscape Explorer (ALEX). https://alex.awi.de/ Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung; Arctic PASSION Project: Public Web Map Service (WMS, Capabilities). https://maps.awi.de/services/common/permafrost/wms?request=GetCapabilities&service=WMS Arctic PASSION Project: Pan-Arctic observing System of Systems: Implementing Observations for societal Needs (Arctic PASSION) %7C Project website. https://arcticpassion.eu/ Fraser, Robert; Olthof, Ian; Kokelj, Steven V; Lantz, Trevor C; Lacelle, Denis; Brooker, Alexander; Wolfe, Stephen A; Schwarz, Steve (2014): Detecting Landscape Changes in High Latitude Environments Using Landsat Trend Analysis: 1. Visualization. Remote Sensing, 6(11), 11533-11557, https://doi.org/10.3390/rs61111533 Nitze, Ingmar; Grosse, Guido (2016): Detection of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks. Remote Sensing of Environment, 181, 27-41, https://doi.org/10.1016/j.rse.2016.03.038 Nitze, Ingmar; Grosse, Guido; Jones, Benjamin M; Romanovsky, Vladimir E; Boike, Julia (2018): Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic. Nature Communications, 9(1), https://doi.org/10.1038/s41467-018-07663-3 https://doi.pangaea.de/10.1594/PANGAEA.964814 https://doi.org/10.1594/PANGAEA.964814 CC-BY-4.0: Creative Commons Attribution 4.0 International Access constraints: unrestricted info:eu-repo/semantics/openAccess Arctic_PASSION Arctic_PASSION_Permafrost_Service Arctic PASSION Binary Object Binary Object (File Size) Binary Object (Media Type) CCI Permafrost Circum-arctic permafrost region Coastline change Earth observation ESA_CCI_Permafrost_CCN2 ESA GlobPermafrost File content GlobPermafrost Horizontal datum Lake change Lake drainage Land cover change Latitude northbound southbound Longitude eastbound westbound Multispectral index NSF Permafrost Discovery Gateway Pan-Arctic observing System of Systems: Implementing Observations for societal Needs Permafrost_Discovery_Gateway PETA-CARB Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool Raster cell size River bank erosion SAT satellite data Satellite remote sensing Shore erosion Thaw slumping thermokarst Dataset 2024 ftpangaea https://doi.org/10.1594/PANGAEA.96481410.3390/rs6111153310.1016/j.rse.2016.03.03810.1038/s41467-018-07663-3 2024-04-30T23:34:34Z This raster dataset, in Cloud Optimized GeoTIFF format (COG), provides information on land surface changes at the pan-arctic scale. Multispectral Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI imagery (cloud-cover less than 80%, months July and August) was used for detecting disturbance trends (associated with abrupt permafrost degradation) between 2003 and 2022. For each satellite image we calculated the Tasseled Cap multi-spectral index to translate the spectral reflectance signal to the semantic information Brightness, Greenness, and Wetness. In order to characterize change information, we calculated the linear trend of the Brightness, Greenness and Wetness over two decades on the individual pixel level. The final map product therefore contains information on the direction and magnitude of change for all three Tasseled Cap parameters in 30m spatial resolution across the pan-arctic permafrost domain. Features detected include coastal erosion, lake drainage, infrastructure expansion, and fires. The general processing methodology was developed by Fraser et al. 2014 and adapted and expanded by Nitze et al. 2016 and Nitze et al. 2018. Here we upscaled the processing to the circum-arctic permafrost region and the recent 20-year period from 2003 through 2022. The service covers the permafrost region up to 81° North: Alaska (USA), Canada, Greenland, Iceland, Norway, Sweden, Finland, Russia, Mongolia, and China. For Russia and China, regions not containing permafrost were excluded. The data has been processed in Google EarthEngine within the research projects ERC PETA-CARB, ESA CCI+ Permafrost, NSF Permafrost Discovery Gateway, and EU Arctic PASSION. The dataset is a contribution to the 'Panarctic requirements-driven Permafrost Service' of the Arctic PASSION project (see references). Changes in the Tasseled Cap indices Brightness, Greenness, and Wetness are displayed in the image bands red, green, and blue, respectively. Here, coastal erosion (a trend of a land surface transitioning to a water surface) is depicted in ... Dataset Arctic Arctic Greenland Iceland permafrost Thermokarst Alaska PANGAEA - Data Publisher for Earth & Environmental Science ENVELOPE(179.998231,-179.999986,81.000042,26.999825) |