University of Oulu

H. Bergstedt et al., "Deriving a Frozen Area Fraction From Metop ASCAT Backscatter Based on Sentinel-1," in IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 9, pp. 6008-6019, Sept. 2020, doi: 10.1109/TGRS.2020.2967364

Deriving a frozen area fraction from Metop ASCAT backscatter based on Sentinel-1

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Author: Bergstedt, Helena1,2,3; Bartsch, Annett4,2; Neureiter, Anton5;
Organizations: 1Department of Geoinformatics-Z_GIS, University of Salzburg, 5020 Salzburg, Austria
2Austrian Polar Research Institute, 1300 Vienna, Austria
3Water and Environmental Research Center, Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, AK 99775 USA
4b.geos, 2100 Korneuburg, Austria
5Department for Climate Research, Zentralanstalt für Meteorologie und Geodynamik (ZAMG), 1190 Vienna, Austria
6Staff Unit Earth Observation, Zentralanstalt für Meteorologie und Geodynamik (ZAMG), 1190 Vienna, Austria
7Department of Geography, University of Portsmouth, Portsmouth PO1 3HE, U.K
8Geography Research Unit, University of Oulu, 90014 Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 14 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-10-16


Surface state data derived from spaceborne microwave sensors with suitable temporal sampling are to date only available in low spatial resolution (25—50 km). Current approaches do not adequately resolve spatial heterogeneity in landscape-scale freeze–thaw processes. We propose to derive a frozen fraction instead of binary freeze–thaw information. This introduces the possibility to monitor the gradual freezing and thawing of complex landscapes. Frozen fractions were retrieved from Advanced Scatterometer (ASCAT, C-band) backscatter on a 12.5-km grid for three sites in noncontinuous permafrost areas in northern Finland and the Austrian Alps. To calibrate the retrieval approach, frozen fractions based on Sentinel-1 synthetic aperture radar (SAR, C-band) were derived for all sites and compared to ASCAT backscatter. We found strong relationships for ASCAT backscatter with Sentinel-1 derived frozen fractions (Pearson correlations of −0.85 to −0.96) for the sites in northern Finland and less strong relationships for the Alpine site (Pearson correlations −0.579 and −0.611, including and excluding forested areas). Applying the derived linear relationships, predicted frozen fractions using ASCAT backscatter values showed root mean square error (RMSE) values between 7.26% and 16.87% when compared with Sentinel-1 frozen fractions. The validation of the Sentinel-1 derived freeze–thaw classifications showed high accuracy when compared to in situ near-surface soil temperature (84.7%–94%). Results are discussed with regard to landscape type, differences between spring and autumn, and gridding. This article serves as a proof of concept, showcasing the possibility to derive frozen fraction from coarse spatial resolution scatterometer time series to improve the representation of spatial heterogeneity in landscape-scale surface state.

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Series: IEEE transactions on geoscience and remote sensing
ISSN: 0196-2892
ISSN-E: 1558-0644
ISSN-L: 0196-2892
Volume: 58
Issue: 9
Pages: 6008 - 6019
DOI: 10.1109/TGRS.2020.2967364
Type of Publication: A1 Journal article – refereed
Field of Science: 1171 Geosciences
Funding: This work was supported by the Austrian Science Fund [Fonds zur Förderung der Wissenschaftlichen Forschung (FWF)] through the Doctoral College GIScience under Grant DK W1237-N23. The work of Annett Bartsch was supported in part by the ESA’s DUE GlobPermafrost Project under Contract 4000116196/15/I-NB, in part by the Zentralanstalt für Meteorologie und Geodynamik (ZAMG) Entwicklungsprojekt under Grant Sen4Austria, and in part by the ESA CCI+ Permafrost. The work of Anton Neureiter, Angelika Höfler, and Barbara Widhalm was supported in part by the ESA’s DUE GlobPermafrost Project under Contract 4000116196/15/I-NB and in part by the ZAMG Entwicklungsprojekt under Grant Sen4Austria. The work of Jan Hjort was supported by the Academy of Finland Project under Grant 315519.
Academy of Finland Grant Number: 315519
Detailed Information: 315519 (Academy of Finland Funding decision)
Copyright information: © The Authors 2020. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see