Normalized C-HH backscatter from Sentinel-1 (December, 2014-2017) for selected tundra regions

Synthetic aperture radar (SAR) applications often require normalization to a common incidence angle. Angular signatures of radar backscatter depend on surface roughness and vegetation cover, and thus differ, from location to location. Comprehensive reference datasets are therefore required in hetero...

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Bibliographic Details
Main Authors: Widhalm, Barbara, Bartsch, Annett, Goler, Robert
Format: Dataset
Language:English
Published: PANGAEA 2019
Subjects:
Alaska
USA
AWI_PerDyn
C01_Barrow
C02_Toolik
C03_Teshekpuk
C04_Mackenzie_Delta
C07_Lena_Delta
C14_UsaBasin
Cryosphere
ESA Data User Element - GlobPermafrost
ESA-DUE-GlobPermafrost
Event label
File content
File format
File name
File size
MON
Monitoring
Permafrost Research (Periglacial Dynamics) @ AWI
Siberia
Russia
T01_Westsiberia
Uniform resource locator/link to file
Usa River basin
Northeast European Russia
Canada
Mackenzie Delta
Yamal Peninsula
lena delta
permafrost
Tundra
Online Access:https://doi.pangaea.de/10.1594/PANGAEA.897046
https://doi.org/10.1594/PANGAEA.897046
Description
Summary:Synthetic aperture radar (SAR) applications often require normalization to a common incidence angle. Angular signatures of radar backscatter depend on surface roughness and vegetation cover, and thus differ, from location to location. Comprehensive reference datasets are therefore required in heterogeneous landscapes. Multiple acquisitions from overlapping orbits with sufficient incidence angle range are processed in order to obtain parameters of the location specific normalization function. We propose a simpler method for C-band data, using single scenes only. It requires stable dielectric properties (no variations of liquid water content). This method is therefore applicable for frozen conditions. Winter C-band data have been shown of high value for a number of applications in high latitudes before. In this paper we explore the relationship of incidence angle and Sentinel-1 backscatter across the tundra to boreal transition zone. A linear relationship (coefficient of determination R2 = 0.64) can be found between backscatter and incidence angle dependence (slope of normalization function) as determined by multiple acquisitions on a pixel by pixel basis for typical land cover classes in these regions. This allows a simplified normalization and thus reduced processing effort for applications over larger areas. The following regions are covered in the dataset: Yamal peninsula (Russia), Usa Basin (Russia), Lena Delta (Russia), Mackenzie Delta (Canada), Barrow, Toolik and Teshekpuk Lake region (Alaska).

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