Experimental study of microwave transmission in snowpack

Abe, Takeo; Yamaguchi, Yoshio; Sengoku, Masakazu

doi:10.1109/36.58981

Cited by 21 publications

(17 citation statements)

References 3 publications

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“…The dielectric properties of snow at 9.65 GHz vary significantly with liquid water volume fraction [19] such that three main scattering regimes can be identified. 1) Wet snow ( > ) can be considered as a surface, because all reflection occurs at the snow surface due to a very low penetration.…”

Section: A Dielectric Properties Of Snowmentioning

confidence: 99%

“…Frequencies at X-band or below penetrate through dry snow such that the main backscatter contributions arise from the frozen soil below. For a transitional range between dry and wet snow ( < < ), the dominant backscattering can occur in the volume; however, for wet snow ( > ), scattering occurs only in the top few centimeters of the surface [18], [19]. Water with its high dielectric constant changes the dielectric properties of snow by orders of magnitude, resulting in a very small penetration depth caused by absorption and reflection [19]- [22].…”

Section: Introductionmentioning

confidence: 99%

“…For a transitional range between dry and wet snow ( < < ), the dominant backscattering can occur in the volume; however, for wet snow ( > ), scattering occurs only in the top few centimeters of the surface [18], [19]. Water with its high dielectric constant changes the dielectric properties of snow by orders of magnitude, resulting in a very small penetration depth caused by absorption and reflection [19]- [22]. The effect that backscattering from a smooth wet surface is much lower than from rough ground was used to detect wet snow and to predict melt water runoff [23]- [26].…”

Section: Introductionmentioning

confidence: 99%

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Snow Height Determination by Polarimetric Phase Differences in X-Band SAR Data

Leinß

Parrella

Hajnsek

2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The copolar phase difference (CPD) between VV and HH polarization of X-band SAR acquisitions shows a significant dependence on the depth of fresh snow. Phase differences of 5-15 deg/10 cm fresh snow were determined at a frequency of 9.65 GHz by comparing spatial and temporal variations of snow depth (SD) with the CPD. Spatial correlations were derived from snow transect measurements during January 2012 and TanDEM-X acquisitions. Temporal correlations were derived from weather station data and TerraSAR-X acquisitions between December 2012 and April 2013. All measurements were done at a test field near the city Sodankylae, Finland. To explain the observed CPD, a model derives birefringent properties from the microstructure of snow, which is described as aligned elliptical particles. The microscopic description is based on computer tomography observations. Different incidence angles were analyzed in consistency with the model. The temporal evolution of the CPD was linked to the temperature-gradient-driven recrystallization process. Sudden increases in the CPD indicate fresh snow. Slow decreases indicate the subsequent recrystallization process. The background signal of wet soil was considered and causes a small negative offset to the CPD. A quantitative determination of the depth of fresh snow is possible, because the specific CPD per meter of snow can be estimated. Spatial resolutions below are achievable with sensors such as TerraSAR-X or TanDEM-X. This paper presents a theoretical relationship between the microstructure of snow and the CPD and relates the CPD theoretically and empirically to the depth of fresh snow.

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Section: A Dielectric Properties Of Snowmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Snow Height Determination by Polarimetric Phase Differences in X-Band SAR Data

Leinß

Parrella

Hajnsek

2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…The co-polarization backscatter (HorizontalHorizontal (HH) and Vertical-Vertical (VV)) responses are nearly 10 times larger than the cross-polarization backscatter (Horizontal-Vertical (HV) or Vertical-Horizontal (VH)) responses . Since the HV components contribute to volume scattering and multiple scattering, the main polarimetric response from snowpack becomes surface scattering in the L-band (Singh et al 2011a, Abe et al 1990). …”

Section: Study Area and Data Usedmentioning

confidence: 99%

Evaluation of modified four-component scattering power decomposition method over highly rugged glaciated terrain

Singh¹,

Yamaguchi²,

Park³

et al. 2012

Geocarto International

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In recent years, there has been increased utilization of fully polarimetric synthetic aperture radar (POLSAR) data to study glaciated terrain features for glaciological and climate change modelling. This article is concerned with more accurate results and appropriate analysis of POLSAR data over a highly rugged glaciated area in Himalayan region. For this purpose, the modified Yamaguchi four-component scattering power decomposition (4-CSPD) method with a rotation concept of 3 6 3 coherency matrix [T] about line of sight is evaluated. It has been found that the modified Yamaguchi 4-CSPD method significantly improved the decomposition results as compared with the original 4-CSPD by minimizing the cross-polarized Horizontal-Vertical (HV) components. This modified 4-CSPD leads to enhancement in the double bounce scattering and surface scattering components and also avoids the overestimation problem in the volume scattering component as compared with the original 4-CSPD from the sloped terrain. The significant reductions of the negative power occurrence in the surface scattering (3.9%) and the double bounce scattering (19.7%) components have also been noticed as compared with the original 4-CSPD method over the glaciated area in this part of the Indian Himalaya.

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“…(From Mintzer et al, 1983) [1] susceptible to landslides;[2] susceptible to landslides under certain conditions;[3] not susceptible to landslides except in dangerous locations.…”

mentioning

confidence: 99%