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Upward-looking L-band FMCW radar for snow cover monitoring.

Okorn R, Brunnhofer G, Platzer T, Heilig A, Schmid L, Mitterer C, Schweizer J, Eisen O - Cold Reg Sci Technol (2014)

Bottom Line: The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection.Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR).The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor.

View Article: PubMed Central - PubMed

Affiliation: FH JOANNEUM, Department of Electronic Engineering, Kapfenberg, Austria.

ABSTRACT
Forecasting snow avalanche danger in mountainous regions is of major importance for the protection of infrastructure in avalanche run-out zones. Inexpensive measurement devices capable of measuring snow height and layer properties in avalanche starting zones may help to improve the quality of risk assessment. We present a low-cost L-band frequency modulated continuous wave radar system (FMCW) in upward-looking configuration. To monitor the snowpack evolution, the radar system was deployed in fall and subsequently was covered by snowfalls. During two winter seasons we recorded reflections from the overlying snowpack. The influence of reflection magnitude and phase to the measured frequency spectra, as well as the influence of signal processing were investigated. We present a method to extract the phase of the reflection coefficients from the phase response of the frequency spectra and their integration into the presentation of the measurement data. The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection. We developed an automated and a semi-automated snow surface tracking algorithm. Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR). The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor. The percolation of water was observable in the radargrams. Results suggest that the upward-looking FMCW system may be a valuable alternative to conventional snow-depth sensors for locations, where fixed installations above ground are not feasible.

No MeSH data available.


(a) Snow height measured in the winter season 2011–2012 with a laser snow-depth sensor (red), determined with the upward-looking FMCW radar system (lower antenna position) using the fully automated snow surface tracking algorithm fullyAuto (black dots), the semi-automated algorithm semiAuto (green) and determined with an upGPR system using the semi-automated algorithm proposed by (Schmid et al., 2014) (blue). Red circles indicate snow heights measured manually directly above the radar. (b) Differences between the radar determined snow heights and measurements made with the laser snow-depth sensor. The blue background shows when the snowpack was fully wet (according to lysimeter measurements nearby).
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f0045: (a) Snow height measured in the winter season 2011–2012 with a laser snow-depth sensor (red), determined with the upward-looking FMCW radar system (lower antenna position) using the fully automated snow surface tracking algorithm fullyAuto (black dots), the semi-automated algorithm semiAuto (green) and determined with an upGPR system using the semi-automated algorithm proposed by (Schmid et al., 2014) (blue). Red circles indicate snow heights measured manually directly above the radar. (b) Differences between the radar determined snow heights and measurements made with the laser snow-depth sensor. The blue background shows when the snowpack was fully wet (according to lysimeter measurements nearby).

Mentions: Fig. 9: (a) Snow height measured in the winter season 2011–2012 with a laser snow-depth sensor (red), determined with the upward-looking FMCW radar system (lower antenna position) using the fully automated snow surface tracking algorithm fullyAuto (black dots), the semi-automated algorithm semiAuto (green) and determined with an upGPR system using the semi-automated algorithm proposed by Schmid et al. (submitted) (blue). Red circles indicate snow heights measured manually directly above the radar. (b) Differences between the radar determined snow heights and measurements made with the laser snowdepth sensor. The blue background shows when the snowpack was fully wet (according to lysimeter measurements nearby).


Upward-looking L-band FMCW radar for snow cover monitoring.

Okorn R, Brunnhofer G, Platzer T, Heilig A, Schmid L, Mitterer C, Schweizer J, Eisen O - Cold Reg Sci Technol (2014)

(a) Snow height measured in the winter season 2011–2012 with a laser snow-depth sensor (red), determined with the upward-looking FMCW radar system (lower antenna position) using the fully automated snow surface tracking algorithm fullyAuto (black dots), the semi-automated algorithm semiAuto (green) and determined with an upGPR system using the semi-automated algorithm proposed by (Schmid et al., 2014) (blue). Red circles indicate snow heights measured manually directly above the radar. (b) Differences between the radar determined snow heights and measurements made with the laser snow-depth sensor. The blue background shows when the snowpack was fully wet (according to lysimeter measurements nearby).
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4045589&req=5

f0045: (a) Snow height measured in the winter season 2011–2012 with a laser snow-depth sensor (red), determined with the upward-looking FMCW radar system (lower antenna position) using the fully automated snow surface tracking algorithm fullyAuto (black dots), the semi-automated algorithm semiAuto (green) and determined with an upGPR system using the semi-automated algorithm proposed by (Schmid et al., 2014) (blue). Red circles indicate snow heights measured manually directly above the radar. (b) Differences between the radar determined snow heights and measurements made with the laser snow-depth sensor. The blue background shows when the snowpack was fully wet (according to lysimeter measurements nearby).
Mentions: Fig. 9: (a) Snow height measured in the winter season 2011–2012 with a laser snow-depth sensor (red), determined with the upward-looking FMCW radar system (lower antenna position) using the fully automated snow surface tracking algorithm fullyAuto (black dots), the semi-automated algorithm semiAuto (green) and determined with an upGPR system using the semi-automated algorithm proposed by Schmid et al. (submitted) (blue). Red circles indicate snow heights measured manually directly above the radar. (b) Differences between the radar determined snow heights and measurements made with the laser snowdepth sensor. The blue background shows when the snowpack was fully wet (according to lysimeter measurements nearby).

Bottom Line: The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection.Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR).The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor.

View Article: PubMed Central - PubMed

Affiliation: FH JOANNEUM, Department of Electronic Engineering, Kapfenberg, Austria.

ABSTRACT
Forecasting snow avalanche danger in mountainous regions is of major importance for the protection of infrastructure in avalanche run-out zones. Inexpensive measurement devices capable of measuring snow height and layer properties in avalanche starting zones may help to improve the quality of risk assessment. We present a low-cost L-band frequency modulated continuous wave radar system (FMCW) in upward-looking configuration. To monitor the snowpack evolution, the radar system was deployed in fall and subsequently was covered by snowfalls. During two winter seasons we recorded reflections from the overlying snowpack. The influence of reflection magnitude and phase to the measured frequency spectra, as well as the influence of signal processing were investigated. We present a method to extract the phase of the reflection coefficients from the phase response of the frequency spectra and their integration into the presentation of the measurement data. The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection. We developed an automated and a semi-automated snow surface tracking algorithm. Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR). The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor. The percolation of water was observable in the radargrams. Results suggest that the upward-looking FMCW system may be a valuable alternative to conventional snow-depth sensors for locations, where fixed installations above ground are not feasible.

No MeSH data available.