IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2022)

L-Band Radiometry of Alpine Seasonal Snow Cover: 4 Years at the Davos-Laret Remote Sensing Field Laboratory

  • Reza Naderpour,
  • Mike Schwank,
  • Derek Houtz,
  • Christian Matzler

DOI
https://doi.org/10.1109/JSTARS.2022.3195614
Journal volume & issue
Vol. 15
pp. 8199 – 8220

Abstract

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This study reports on four consecutive winter campaigns (2016–2020) at the “Davos-Laret Remote Sensing Field Laboratory” in the Swiss Alps to gain insight into the L-band microwave emission of ground covered with seasonal snow. Close-range L-band Brightness temperatures $T_\mathrm{{B}}^{p,\phi }(\theta)$ were measured over the site scanning different observation nadir angles $\theta$ and azimuth angles $\phi$ at horizontal and vertical polarization p = {H,V}. State parameters (SPs) of the snowpack (e.g., height, density, and snow water equivalent) and the subnivean soil (permittivity, temperature) were measured quasi-simultaneously using in-situ sensors and sampling, as well as meteorological data. In each campaign, $T_\mathrm{{B}}^{p,\phi }(\theta)$ were measured over a “natural area” and a “reflector area” with a metal mesh reflector laid on the ground before snow accumulation. The radiometer measurements over “reflector area” allowed to retrieve the time-series of Snow liquid Water-content $W_\mathrm{{S}}$ and Snow liquid Water-Column ${WC}_\mathrm{{S}}$, which are employed as “derived measurements” to support interpretation of $T_\mathrm{{B}}^{p,\phi }(\theta)$ measured over “natural areas” during different winter phases. The detailed approach for the estimation of $W_\mathrm{{S}}$ and ${WC}_\mathrm{{S}}$ using L-band radiometer data is presented. The data and analyses in this article address the following major points: 1) determination of the characteristic features of measured $T_\mathrm{{B}}^{p,\phi }(\theta)$ during different periods in each of the four winter campaigns; 2) effects of dry and wet snow precipitation on L-band radiometer data compared to corresponding simulations; 3) effect of removal and compression of the snowpack on $T_\mathrm{{B}}^{p,\phi }(\theta)$; 4) effects of spatial heterogeneity on brightness temperatures. Finally, the study is concluded with recommendations relevant for future close-range remote sensing campaigns.

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