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Nitze, Ingmar; Lübker, Tillmann; Grosse, Guido (2024): Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.964814

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Abstract:
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 dark blue colors, while coastal accretion (a trend of a water surface transitioning to a land surface) is depicted in bright orange colors. Drained lakes appear in bright yellow or orange colors, depending on the soil conditions and vegetation regrowth. Fire scars are a further common feature, which can appear in different colors, depending on the time of the fire and pre-fire land cover. The data can be explored via the Arctic Landscape EXplorer (ALEX, see references) and is available as a public web map service (WMS, see references), both hosted by Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research.
Keyword(s):
Arctic PASSION; Coastline change; Earth observation; Lake change; Lake drainage; Land cover change; Multispectral index; River bank erosion; satellite data; Shore erosion; Thaw slumping; thermokarst
References:
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) | 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
Funding:
Horizon 2020 (H2020), grant/award no. 101003472: Pan-Arctic observing System of Systems: Implementing Observations for societal Needs (Arctic PASSION)
Seventh Framework Programme (FP7), grant/award no. 338335: Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool
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
Event(s):
Arctic_PASSION_Permafrost_Service * Latitude Start: 26.999825 * Longitude Start: 179.998231 * Latitude End: 81.000042 * Longitude End: -179.999986 * Date/Time Start: 2003-01-01T00:00:00 * Date/Time End: 2022-12-31T00:00:00 * Location: Circum-arctic permafrost region * Method/Device: Satellite remote sensing (SAT)
Comment:
Two Cloud Optimized GeoTIFF files are available: 'TCVIS-2003-2022_mosaic-west_cog.tif' (file size: 130 GB) contains data for USA, Canada, Greenland, and Iceland (coverage: 180°W - 0°W, 41°N - 81°N), 'TCVIS-2003-2022_mosaic-east_cog.tif' (file size: 183 GB) contains data for Norway, Sweden, Finland, Russia, Mongolia, and China (coverage: 3°E - 180°E, 27°N - 81°N).
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1Binary ObjectBinaryNitze, IngmarSatellite remote sensing (SAT)
2Binary Object (Media Type)Binary (Type)Nitze, IngmarSatellite remote sensing (SAT)
3Binary Object (File Size)Binary (Size)BytesNitze, IngmarSatellite remote sensing (SAT)
4Raster cell sizeRaster cell sizeNitze, IngmarSatellite remote sensing (SAT)
5File contentContentNitze, IngmarSatellite remote sensing (SAT)
6Horizontal datumHorizontal datumNitze, IngmarSatellite remote sensing (SAT)
7Longitude, westboundLongitude westNitze, IngmarSatellite remote sensing (SAT)
8Longitude, eastboundLongitude eastNitze, IngmarSatellite remote sensing (SAT)
9Latitude, southboundLatitude southNitze, IngmarSatellite remote sensing (SAT)
10Latitude, northboundLatitude northNitze, IngmarSatellite remote sensing (SAT)
Status:
Curation Level: Basic curation (CurationLevelB) * Processing Level: PANGAEA data processing level 1 (ProcLevel1)
Size:
16 data points

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