Vector dataset of manually mapped retrogressive thaw slumps from very high-resolution multispectral imagery in the Russian High Arctic between 2011 and 2020

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Barth, Sophia;Nitze, Ingmar;Juhls, Bennet;Runge, Alexandra;Grosse, Guido

Description

We present a comprehensive inventory of retrogressive thaw slumps (RTS) for six study sites in the Russian High Arctic covering an area of more than 600 km². The sites are located on the Novaya Zemlya Archipelago, Kolguev Island, Bol'shoy Lyakhovsky Island, and Taymyr Peninsula in ice-rich permafrost characterized by either buried glacial ice or syngenetically formed Yedoma permafrost deposits. This data publication contains geospatial polygon vector files of the individual mapped slumps across multiple time slices. The mapping was performed on multispectral imagery of very high-resolution satellite sensors, including PlanetScope (3m ground resolution), RapidEye (5m), Pléiades (0.5m), and SPOT (1.5m). Cloud free images were acquired between 2011 and 2020 and exist for annual or close-to-annual time steps depending on their availability. Additional data sets such as the ArcticDEM, the Esri Satellite base map, and Tasseled Cap Landsat Trends were used to support the mapping process. The identification and digitization of thaw slumps as polygons (in UTM coordinate reference system) was performed in QGIS 10.3. A total number of 3466 individual RTS were mapped between 2011 or 2013 and 2020. In addition, for the coastal slumps, change distances from headwalls and bluff bases were calculated in ArcMap 10.5 using the Digital Shoreline Analysis System (DSAS) tool version 5 over the study period (2011/2013-2020).Very high-resolution imagery for this study was kindly provided by ESA through Third Party Mission proposal TPM4-ID-54054. We recieved access to the RapidEye imagery via the RapidEye Science Archive (RESA) initiative in the scope of our project 'Thaw Dynamics of Retrogressive Thaw Slumps from High Resolution Images in Siberia (RTStrendr )'. The PlanetScope imagery was recieved in the scope of our project ' Artificial Intelligence for Cold Regions (AI-CORE)'.

Citations (1)

Mentions (0)

Metrics

Dataset Index

1.5

FAIR Score

96%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

PANGAEA

Assigned Domain

Subfield

Atmospheric Science

Field

Earth and Planetary Sciences

Domain

Physical Sciences

Confidence Score

51%

Source

Scholar Data Model

Keywords

climate changeHigh Arcticice-rich PermafrostlandslidemappingPermafrostPermafrost coastspermafrost thawRetrogressive Thaw SlumpsRussiaRussian ArcticSiberiathermokarstEvent labelLATITUDELONGITUDELocationDATE/TIMEGeospatial vector, shapefilesGeospatial vector, shapefiles (File Size)Satellite imageryPermafrost Research (AWI_Perma)

Normalization Factors

FT

30.77

CTw

1.00

MTw

1.00