Snow Water Equivalence Retrieval Using X and Ku band Dual-Polarization Radar

doi:10.1109/IGARSS.2006.564

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Snow Water Equivalence Retrieval Using X and Ku band Dual-Polarization Radar

Proceedings Article•DOI•

Snow Water Equivalence Retrieval Using X and Ku band Dual-Polarization Radar

Jiancheng Shi¹•Institutions (1)

University of California, Santa Barbara¹

01 Jul 2006-pp 2183-2185

TL;DR: The feasibility of using the dual frequency (X-band 9.6 GHz and Ku-band 17 GHz) and dual polarization radar to estimate snow water equivalence through numerical simulations is evaluated.

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Abstract: In this study, we evaluated the feasibility of using the dual frequency (X-band 9.6 GHz and Ku-band 17 GHz) and dual polarization (W and VH) radar to estimate snow water equivalence through numerical simulations.

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Journal Article•DOI•

Cold Regions Hydrology High-Resolution Observatory for Snow and Cold Land Processes

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Helmut Rott¹, Simon Yueh², Donald W. Cline³, Claude R. Duguay⁴, Richard Essery⁵, Christian Haas, F. Heliere⁶, Michael Kern⁶, Giovanni Macelloni⁷, Eirik Malnes, Thomas Nagler, Jouni Pulliainen, H. Rebhan⁶, A. Thompson⁶ - Show less +10 more•Institutions (7)

University of Innsbruck¹, California Institute of Technology², National Oceanic and Atmospheric Administration³, University of Waterloo⁴, University of Edinburgh⁵, European Space Research and Technology Centre⁶, International Federation of Accountants⁷

25 Feb 2010

TL;DR: The scientific drivers and technical approach of the proposed Cold Regions Hydrology High-Resolution Observatory (CoReH2O) satellite mission for snow and cold land processes are described and the dual-frequency and dual-polarization design enables the decomposition of the scattering signal for retrieving snow mass and other physical properties of snow and ice.

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Abstract: Snow is a critical component of the global water cycle and climate system, and a major source of water supply in many parts of the world. There is a lack of spatially distributed information on the accumulation of snow on land surfaces, glaciers, lake ice, and sea ice. Satellite missions for systematic and global snow observations will be essential to improve the representation of the cryosphere in climate models and to advance the knowledge and prediction of the water cycle variability and changes that depend on snow and ice resources. This paper describes the scientific drivers and technical approach of the proposed Cold Regions Hydrology High-Resolution Observatory (CoReH2O) satellite mission for snow and cold land processes. The sensor is a synthetic aperture radar operating at 17.2 and 9.6 GHz, VV and VH polarizations. The dual-frequency and dual-polarization design enables the decomposition of the scattering signal for retrieving snow mass and other physical properties of snow and ice.

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175 citations

Cites methods from "Snow Water Equivalence Retrieval Us..."

...Various options for retrieving physical snow and ice properties from the backscatter measurements were studied, including 1) statistical retrievals based on empirical relations between in-situ snow measurements and backscatter coefficients, 2) inversion of semiempirical backscatter models, 3) optimized statistical inversion, and 4) deterministic inversion of a physically based forward model [37], [45]....
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Journal Article•DOI•

Airborne Ku-Band Polarimetric Radar Remote Sensing of Terrestrial Snow Cover

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Simon Yueh¹, Steven J. Dinardo¹, Ahmed Akgiray¹, Richard West¹, D.W. Cline², K. Elder³ - Show less +2 more•Institutions (3)

California Institute of Technology¹, Remote Sensing Center², United States Forest Service³

18 Aug 2009-IEEE Transactions on Geoscience and Remote Sensing

TL;DR: The cross-polarized backscatter [vertical-horizontal (VH)] showed not only the influence of vegetation but also the strong response to snow accumulation, which suggests the importance of multiple scattering or nonspherical scattering geometry of snow grain in the dense-media radiative transfer scattering model.

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Abstract: Characteristics of the Ku-band polarimetric scatterometer (POLSCAT) data acquired from five sets of aircraft flights in the winter months of 2006-2008 for the second Cold Land Processes Experiment (CLPX-II) in Colorado are described in this paper. The data showed the response of the Ku-band radar echoes to snowpack changes for various types of background vegetation in the study site in north central Colorado. We observed about 0.15-0.5-dB increases in backscatter for every 1 cm of snow-water-equivalent (SWE) accumulation for areas with short vegetation (sagebrush and pasture). The region with the smaller amount of biomass, signified by the backscatter in November, seemed to have the stronger backscatter response to SWE in decibels. The data also showed the impact of surface hoar growth and freeze/thaw cycles, which created large snow-grain sizes, ice crust layers, and ice lenses and consequently increased the radar signals by a few decibels. The copolarized HH/VV backscatter ratio seems to indicate double-bounce scattering between the ground surface and snow or vegetation. The cross-polarized backscatter [vertical-horizontal (VH)] showed not only the influence of vegetation but also the strong response to snow accumulation. The observed HV/VV ratio suggests the importance of multiple scattering or nonspherical scattering geometry of snow grain in the dense-media radiative transfer scattering model. Comparison of the POLSCAT and QuikSCAT data was made and confirmed the effects of mixed terrain covers in the coarse-resolution QuikSCAT data.

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67 citations

Cites background from "Snow Water Equivalence Retrieval Us..."

...More recent modeling research [12], [13] indicated that dual frequencies at combination of X- and Ku-bands are more optimal for remote sensing of SWE....
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Journal Article•DOI•

Review of snow water equivalent microwave remote sensing

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Jiancheng Shi¹, Chuan Xiong¹, Lingmei Jiang²•Institutions (2)

Chinese Academy of Sciences¹, Beijing Normal University²

06 Jan 2016-Science China-earth Sciences

TL;DR: In this article, the authors summarized the re-search and progress in the aspects of electromagnetic scattering/emission modeling over snow covered terrain and snow water equivalent inversion algorithm will be summarized.

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Abstract: Accurate quantitative global scale snow water equivalent information is crucial for meteorology, hydrology, water cycle and global change studies, and is of great importance for snow melt-runoff forecast, water resources management and flood control. With land surface process model and snow process model, the snow water equivalent can be simulated with cer- tain accuracy, with the forcing data as input. However, the snow water equivalent simulated using the snow process models has large uncertainties spatially and temporally, and it may be far from the needs of practical applications. Thus, the large scale snow water equivalent information is mainly from remote sensing. Beginning with the launch of Nimbus-7 satellite, the re- search on microwave snow water equivalent remote sensing has developed for more than 30 years, researchers have made pro- gress in many aspects, including the electromagnetic scattering and emission modeling, ground and airborne experiments, and inversion algorithms for future global high resolution snow water equivalent remote sensing program. In this paper, the re- search and progress in the aspects of electromagnetic scattering/emission modeling over snow covered terrain and snow water equivalent inversion algorithm will be summarized.

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50 citations

Journal Article•DOI•

Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss

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Yurong Cui¹, Chuan Xiong¹, Juha Lemmetyinen¹, Jiancheng Shi¹, Lingmei Jiang¹, Bin Peng¹, Huixuan Li², Tianjie Zhao³, Dabin Ji, Tongxi Hu¹ - Show less +6 more•Institutions (3)

Chinese Academy of Sciences¹, Finnish Meteorological Institute², Beijing Normal University³

16 Jun 2016-Remote Sensing

TL;DR: The bi-continuous vector radiative transfer (bi-Continuous-VRT) model, which firstly constructs snow microstructure more similar to real snow and then simulates the snow backscattering signal, is used as the forward model for SWE estimation and a parameterization scheme of snow volumeBackscattering is proposed.

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Abstract: Snow water equivalent (SWE) is a key parameter in the Earth’s energy budget and water cycle. It has been demonstrated that SWE can be retrieved using active microwave remote sensing from space. This necessitates the development of forward models that are capable of simulating the interactions of microwaves and the snow medium. Several proposed models have described snow as a collection of sphere- or ellipsoid-shaped ice particles embedded in air, while the microstructure of snow is, in reality, more complex. Natural snow usually forms a sintered structure following mechanical and thermal metamorphism processes. In this research, the bi-continuous vector radiative transfer (bi-continuous-VRT) model, which firstly constructs snow microstructure more similar to real snow and then simulates the snow backscattering signal, is used as the forward model for SWE estimation. Based on this forward model, a parameterization scheme of snow volume backscattering is proposed. A relationship between snow optical thickness and single scattering albedo at X and Ku bands is established by analyzing the database generated from the bi-continuous-VRT model. A cost function with constraints is used to solve effective albedo and optical thickness, while the absorption part of optical thickness is obtained from these two parameters. SWE is estimated after a correction for physical temperature. The estimated SWE is correlated with the measured SWE with an acceptable accuracy. Validation against two-year measurements, using the SnowScat instrument from the Nordic Snow Radar Experiment (NoSREx), shows that the estimated SWE using the presented algorithm has a root mean square error (RMSE) of 16.59 mm for the winter of 2009–2010 and 19.70 mm for the winter of 2010–2011.

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36 citations

Cites background from "Snow Water Equivalence Retrieval Us..."

...Shi [16] explored the ideas of snow water equivalent retrieval with the combination of the X (9....
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...The absorption part of snow optical thickness τa is a product of the snow absorption coefficient and snow depth, which is linearly related to SWE [16]....
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...The absorption part of snow optical thickness a τ is a product of the snow absorption coefficient and snow depth, which is linearly related to SWE [16]....
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Journal Article•DOI•

Forward and Inverse Radar Modeling of Terrestrial Snow Using SnowSAR Data

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Jiyue Zhu¹, Shurun Tan¹, Joshua King, Chris Derksen, Juha Lemmetyinen, Leung Tsang¹ - Show less +2 more•Institutions (1)

University of Michigan¹

17 Jul 2018-IEEE Transactions on Geoscience and Remote Sensing

TL;DR: A radar snow water equivalent (SWE) retrieval algorithm based on a parameterized forward model of bicontinuous dense media radiative transfer (Bic-DMRT) which is based on retrieving the absorption loss of the snowpack which is directly proportional to the SWE.

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Abstract: In this paper, we develop a radar snow water equivalent (SWE) retrieval algorithm based on a parameterized forward model of bicontinuous dense media radiative transfer (Bic-DMRT). The algorithm is based on retrieving the absorption loss of the snowpack which is directly proportional to the SWE. In the algorithm, Bic-DMRT is first applied to generate a lookup table (LUT) of snowpack backscattering at X- and Ku-band. Regression training is applied to the LUT to transform the dual-frequency backscatter into functions of two parameters: the scattering albedo at X-band and SWE. The background scattering is subtracted from the SnowSAR data to give the volume scattering of snow. Classification of SnowSAR data is applied to provide a priori information. Based on the obtained volume scattering and the priori information, a cost function is established to find SWE. Performance of the retrieval algorithm was tested using three sets of airborne SnowSAR data acquired over mixed areas in Finland and open tundra landscape in Canada. It is shown that the retrieval algorithm has a root-mean-square error below 30 mm of SWE and a correlation coefficient above 0.64.

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33 citations

Cites background or methods from "Snow Water Equivalence Retrieval Us..."

...From ωX and τX, the absorption loss τX a at X-band is derived by its definition [1], [12]...
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...Since the absorption loss τX a is proportional to SWE [1], [12], [13], we use LUT to perform linear Fig....
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References

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Journal Article•DOI•

An empirical model and an inversion technique for radar scattering from bare soil surfaces

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Yisok Oh¹, Kamal Sarabandi¹, Fawwaz T. Ulaby¹•Institutions (1)

University of Michigan¹

01 Mar 1992-IEEE Transactions on Geoscience and Remote Sensing

TL;DR: An inversion technique was developed for predicting the rms height of the surface and its moisture content from multipolarized radar observations, which was found to yield very good agreement with the backscattering measurements of the present study.

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Abstract: Polarimetric radar measurements were conducted for bare soil surfaces under a variety of roughness and moisture conditions at L-, C-, and X-band frequencies at incidence angles ranging from 10 degrees to 70 degrees . Using a laser profiler and dielectric probes, a complete and accurate set of ground truth data was collected for each surface condition, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. Based on knowledge of the scattering behavior in limiting cases and the experimental observations, an empirical model was developed for sigma degrees /sub hh/, sigma degrees /sub vv/, and sigma degrees /sub hv/ in terms of ks (where k=2 pi / lambda is the wave number and s is the rms height) and the relative dielectric constant of the soil surface. The model, which was found to yield very good agreement with the backscattering measurements of the present study as well as with measurements reported in other investigations, was used to develop an inversion technique for predicting the rms height of the surface and its moisture content from multipolarized radar observations. >

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1,255 citations

"Snow Water Equivalence Retrieval Us..." refers methods in this paper

...Our microwave radiative transfer model is a secondorder radiative transfer model where 1) the surface scattering components are simulated by AIEM model for the co-polarized signals and the semi-empirical model of VH/VV [3] for the cross-polarization signals, 2) the volume scattering component are calculated by the dense medium model with ellipsoid grain shape in order to simulate the cross-polarization signals, and 3) the bi-static AIEM model is used for the boundary condition so that the interaction components between snow volume scattering and the surface scatterings can be correctly simulated....
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...NUMERICAL SIMULATIONS Our microwave radiative transfer model is a secondorder radiative transfer model where 1) the surface scattering components are simulated by AIEM model for the co-polarized signals and the semi-empirical model of VH/VV [3] for the cross-polarization signals, 2) the volume scattering component are calculated by the dense medium model with ellipsoid grain shape in order to simulate the cross-polarization signals, and 3) the bi-static AIEM model is used for the boundary condition so that the interaction components between snow volume scattering and the surface scatterings can be correctly simulated....
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Journal Article•DOI•

Estimation of snow water equivalence using SIR-C/X-SAR. II. Inferring snow depth and particle size

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Jonathan Shi¹, Jeff Dozier¹•Institutions (1)

University of California, Santa Barbara¹

01 Nov 2000-IEEE Transactions on Geoscience and Remote Sensing

TL;DR: The authors develop semi-empirical models for characterizing the snow-ground interaction terms, the relationships between the ground surface backscattering components, and the snowpack extinction properties at C-band and X-band, and with these relationships, snow depth and optical equivalent grain size can be estimated from SIR-C/X-SAR measurements.

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Abstract: For pt.I see ibid., vol.38, no.6, p.2465-74 (2000). The relationship between snow water equivalence (SWE) and SAR backscattering coefficients at C- and X-band (5.5 and 9.6 GHz) can be either positive or negative. Therefore, discovery of the relationship with an empirical approach is unrealistic. Instead, the authors estimate snow depth and particle size using SIR-C/X-SAR imagery from a physically-based first order backscattering model through analyses of the importance of each scattering term and its sensitivity to snow properties. Using numerically simulated backscattering values, the authors develop semi-empirical models for characterizing the snow-ground interaction terms, the relationships between the ground surface backscattering components, and the snowpack extinction properties at C-band and X-band. With these relationships, snow depth and optical equivalent grain size can be estimated from SIR-C/X-SAR measurements. Validation using three SIR-C/X-SAR images shows that the algorithm performs usefully for incidence angles greater than 300, with root mean square errors (RMSEs) of 34 cm and 0.27 mm for estimating snow depth and ice optical equivalent particle radius, respectively.

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141 citations

Proceedings Article•DOI•

Estimation of snow water equivalence using SIR-C/X-SAR

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Jiancheng Shi¹•Institutions (1)

University of California, Santa Barbara¹

19 Aug 1998

TL;DR: In this paper, the authors used the numerically simulated backscattering coefficients to estimate dry snow density, depth, grain size, under-ground dielectric constant and surface RMS height using multi-frequency and -polarization SAR measurements.

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Abstract: Snow water equivalence, which is the product of snow density and depth, is the most important parameter in snow hydrology. This paper demonstrates the algorithms for estimating dry snow density, depth, grain size, under-ground dielectric constant and surface RMS height using multi- frequency and -polarization SAR measurements. The algorithms were developed based on the numerically simulated backscattering coefficients. We use L-band VV and HH to estimate snow density and the underground surface parameters: dielectric constant and roughness RMS height. The underground surface can be either soil or rock. Then, C- band VV, HH and X-band VV are used to estimate snow depth and grain size. The validation from the field snow density measurements averaged from the top and bottom snow layers indicate that an absolute and relative accuracy of 0.042 gcm-3 and 13.15 percent can be expected. The comparison with the ground scatterometer measurements showed RMSE of 4.1 percent by volume for solid moisture estimation and 0.42 cm for the surface RMS height with this newly developed algorithms. The validation by using three SIR-C/X- SAR image data indicated that this algorithm performed well for incidence angle greater than 30 degrees with RMES 34 cm and 0.27 mm for estimation of snow depth and ice optical equivalent particle radius, respectively.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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71 citations

"Snow Water Equivalence Retrieval Us..." refers background in this paper

...As shown in study [5], all snow extinction properties including albedo, extinction, scattering, absorption coefficients are all highly correlated between that at different frequencies....
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Proceedings Article•DOI•

Estimation of snow water equivalence with two Ku-band dual polarization radar

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Jiancheng Shi¹•Institutions (1)

University of California, Santa Barbara¹

27 Dec 2004

TL;DR: This study demonstrates a concept of estimating snow water equivalence under the consideration of a dual frequency Ku band (13.4 GHz and 17 GHz) and a dual polarization system.

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Abstract: Snow water equivalence is an important parameter for studies of the natural sciences, particularly in hydrology and climatology. This study demonstrates a concept of estimating snow water equivalence under the consideration of a dual frequency Ku band (13.4 GHz and 17 GHz) and a dual polarization system

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15 citations

"Snow Water Equivalence Retrieval Us..." refers background or methods in this paper

...As shown in [1-2], the depolarization factor – σvh / σvv is proportional to the direct volume scattering contribution σvv / σvv , and inversely relates the ground surface scattering contribution σvv / σvv at Kuband....
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...Following the studies of the techniques development of retrieval SWE by using the dual frequency and polarization of L-band and Ku-band [1] and two Ku-band radar [2], we evaluated, in this study, the feasibility of using the dual frequency (Xband 9....
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Proceedings Article•DOI•

On estimation of snow water equivalence using L-band and Ku-band radar

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Jiancheng Shi¹, S. Yueh, D. Cline•Institutions (1)

University of California, Santa Barbara¹

21 Jul 2003

TL;DR: This study shows a concept of estimating snow water equivalence under the consideration of a dual frequency L- and Ku-band polarization system.

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Abstract: The study of snow has become an important area of research in the natural sciences, particularly in hydrology and climatology. This study shows a concept of estimating snow water equivalence under the consideration of a dual frequency L- and Ku-band polarization system.

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11 citations

"Snow Water Equivalence Retrieval Us..." refers background or methods in this paper

...Following the studies of the techniques development of retrieval SWE by using the dual frequency and polarization of L-band and Ku-band [1] and two Ku-band radar [2], we evaluated, in this study, the feasibility of using the dual frequency (Xband 9.6 GHz and Ku-band 17GHz) and dual polarization (VV and VH) radar to estimate snow water equivalence....
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...As shown in [1-2], the depolarization factor – σvh / σvv is proportional to the direct volume scattering contribution σvv / σvv , and inversely relates the ground surface scattering contribution σvv / σvv at Kuband....
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...REFFERENCE [1] J. Shi, S. Yueh, and D. Cline, “On Estimation of Snow Water Equivalence Using L-band and Ku-band Radar”, Proceedings of IGRASS’03, IEEE No. 03CH37477C, 2003....
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...Using field snow and underlying-ground property measurements, Du [4] showed good agreement between this model and microwave backscattering measurements at both X-band and Ku-band....
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...After obtaining the direct volume scattering signals from the total backscattering signals, the ratio of the direct volume scattering signals of X-band and Ku-bands can be used to estimate the snow optical thickness difference τ(Ku) - τ(X)....
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