Passive L-Band Remote Sensing Applications Over Cryospheric Regions
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Date
2019
Publication Type
Doctoral Thesis
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Abstract
The Earth’s climate and its evolution are heavily influenced by the state of
cryosphere snow cover and its subnivean ground through their determinative
role in the exchange of water, heat, and greenhouse gases between land
and the atmosphere. Previous research has shown that L-band radiometry
can be used for the estimation of snow mass density rho_S and ground permittivity
epsilon_G. In this thesis an unprecedented approach for the estimation
of snow liquid water content (wetness) and the beginning of snow melt,
using L-band radiometry and the L-band Specific Microwave Emission
Model of Layered Snowpack (LS–MEMLS), is proposed. Two snow wetness
retrieval data products are computed using tower-based radiometry
over snow-covered natural ground and areas with a metal grid placed on
the ground beneath the accumulating snow. It is experimentally demonstrated
that the metal grid isolates snowpack’s own emission from the
emission of the underlying ground. This allows considering the snow wetness
retrievals derived from brightness temperatures measured over this
artificially prepared area as references for comparison with snow wetness
retrievals from brightness temperatures over natural ground.
Furthermore, the disruptive effects of “geophysical noise” on (rho_S, epsilon_G)
retrievals are investigated for dry snow conditions. Results indicate robust
performance of the two-parameter retrieval approach against spatial
variabilities of snow cover and subnivean soil. This is a promising base
for the application of this two-parameter retrieval approach with coarse resolution
satellite data. Further synthetic and experimental sensitivity
analyses of the melting effects, in form of snow wetness and ground permittivity
heterogeneities, are conducted which quantify their disruptive
effects on the (rho_S, epsilon_G) retrievals. Results indicate reliable retrievals during
snow free and cold winter periods. With the beginning of the early spring period, retrievals’ accuracy decrease and increased time-correlation is recognized
between retrievals rho_S and epsilon_G. Retrieval quality flags are raised
based on this type of retrievals’ correlation which is very useful for the
application with space-borne radiometry data.
Other achievements of this thesis work include the establishment of
the Davos-Laret Remote Sensing Field Laboratory and significant improvement
of radiometry data–measured with ELBARA-II radiometer–calibration
and quality assessment. The latter includes a new more-accurate Radio
Frequency Interference (RFI) filtering approach based on Gaussian curve
fitting and time-dependent correction of transmission losses taking into
account the transmission line ageing effects, for instance.
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published
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Contributors
Examiner : Steffen, Konrad
Examiner : Kerr, Yann
Examiner : Schwank, Mike
Examiner : Kim, Edward
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Journal / series
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Pages / Article No.
Publisher
ETH Zurich
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Geographic location
Date collected
Date created
Subject
Microwave remote sensing; Snowpack monitoring; Freeze–thaw; Permafrost; snow liquid water content; L-band radiometry; Climate Change; LS-MEMLS; geophysical noise
Organisational unit
03977 - Steffen, Konrad (ehemalig) / Steffen, Konrad (former)