L‐Band InSAR Snow Water Equivalent Retrieval Uncertainty Increases With Forest Cover Fraction

Abstract There is a pressing need for global monitoring of snow water equivalent (SWE) at high spatiotemporal resolution, and L‐band (1–2 GHz) interferometric synthetic aperture radar (InSAR) holds promise. However, the technique has not seen extensive evaluation in forests. We evaluated this technique across varying forest canopy conditions using eight InSAR pairs collected at the Fraser Experimental Forest, Colorado, USA by NASA UAVSAR during the 10‐week NASA SnowEx 2021 Campaign. Compared with in situ measurements, we found root mean squared errors (RMSEs) of 14–17 mm for SWE changes in forest cover fractions (FCF) < 0.40, but RMSEs increased to 33–40 mm at FCF > 0.50. Statistical distributions between normalized lidar snow depths and normalized UAVSAR SWE were similar at FCF < 0.5, but diverged at FCF > 0.50. Thus, the upcoming NISAR L‐band satellite has strong potential for global snowpack monitoring, including below sparse to moderate forest cover.

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Publication Details

Journal
Geophysical Research Letters
Published
2024-12-22
DOI
https://doi.org/10.1029/2024gl111708
Citations
3
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
1.13

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article

L‐Band InSAR Snow Water Equivalent Retrieval Uncertainty Increases With Forest Cover Fraction

Hans‐Peter Marshall, Randall Bonnell, K. Elder, Naheem Adebisi et al.
3 citations
Geophysical Research Letters
Cryospheric studies and observations
1.13
article

L‐Band InSAR Snow Water Equivalent Retrieval Uncertainty Increases With Forest Cover Fraction

Hans‐Peter Marshall, Randall Bonnell, K. Elder, Naheem Adebisi, Daniel McGrath, Barry M. Starr, Ross T. Palomaki, Zachary Hoppinen
article en
3 citations

Abstract

Abstract There is a pressing need for global monitoring of snow water equivalent (SWE) at high spatiotemporal resolution, and L‐band (1–2 GHz) interferometric synthetic aperture radar (InSAR) holds promise. However, the technique has not seen extensive evaluation in forests. We evaluated this technique across varying forest canopy conditions using eight InSAR pairs collected at the Fraser Experimental Forest, Colorado, USA by NASA UAVSAR during the 10‐week NASA SnowEx 2021 Campaign. Compared with in situ measurements, we found root mean squared errors (RMSEs) of 14–17 mm for SWE changes in forest cover fractions (FCF) < 0.40, but RMSEs increased to 33–40 mm at FCF > 0.50. Statistical distributions between normalized lidar snow depths and normalized UAVSAR SWE were similar at FCF < 0.5, but diverged at FCF > 0.50. Thus, the upcoming NISAR L‐band satellite has strong potential for global snowpack monitoring, including below sparse to moderate forest cover.

Geophysical Research LettersVol. 51(24)
Boise State University (US), Institute of Arctic and Alpine Research (US), University of Colorado Boulder (US), Cold Regions Research and Engineering Laboratory (US), United States Army (US), Rocky Mountain Research Station (US), Colorado State University (US)
National Aeronautics and Space Administration, Cold Regions Research and Engineering Laboratory
Clean water and sanitation
Openalex Percentile: Top 23%
Cryospheric studies and observations
1.13
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