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Seasonal spatial-temporal variability in radar penetration depth.

Authors :
Samsonov, Sergey
Source :
Procedia Computer Science; 2024, Vol. 239, p1387-1392, 6p
Publication Year :
2024

Abstract

A fully automated processing system for measuring long-term ground deformation time series and deformation rates frame-by-frame using the Differential Interferometric Synthetic Aperture Radar (DInSAR) processing technique was developed and tested. Among the several factors that affect DInSAR's precision, such as temporal decorrelation and atmospheric noise, it was observed that seasonal spatial-temporal variability in radar penetration depth is the greatest contributor to the loss of precision of the long-term deformation rate measurement. This spatial-temporal signal is described for a specific region in the northern US; however, it is widely observed in multiple regions. In these regions, a gradual penetration depth increase is observed in fall and winter, and an abrupt penetration depth decrease is observed in spring. The latter effect is likely caused by rapid melting of ice and snow that, at the same time, significantly reduces interferometric coherence. Within a specific geographic region, radar penetration depth spatially varies proportionally to the elevation due to an elevation-dependent temperature gradient, producing artifacts that correlate well with the topography. This signal does not extend to high-elevation regions (above ~2500 m) that do not experience seasonal thawing, which allows for distinguishing it from the topography-dependent atmospheric signals. Without accounting for the spatial-temporal variability in radar penetration depth, deformation time series in these areas can contain either an annual periodic signal with an amplitude of over 0.1 m or, if the abrupt penetration depth decrease produced by melting is not resolved due to lower coherence, an erroneous interannual trend. Spatial-temporal variability in radar penetration depth needs to be better understood and corrected to improve the precision of long-term deformation rate products, particularly in regions susceptible to seasonal freezing and thawing. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
239
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
178644842
Full Text :
https://doi.org/10.1016/j.procs.2024.06.310