The potential of times series of C-Band SAR data to monitor dry and shallow snow cover

Bernier, Monique; Fortin, Jean‐Pierre

doi:10.1109/36.655332

Cited by 93 publications

(57 citation statements)

References 14 publications

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“…These records confirm that the decrease in radar backscatter in the fall coincided with the gradual penetration of the cold wave through the soil. Before the soil freezes, the accumulation of snow on the ground surface does not significantly affect the backscatter values [39]. The ground temperature patterns in Churchill indicate that the soil must be frozen to depths greater than 20 cm before a snow effect can be observed on the C-band SAR signal.…”

Section: The Effect Of Soil Freezing On Backscatter In Autumn and Earmentioning

confidence: 94%

“…This transect shows an increase of the backscattering coefficient from the open areas to the forested areas; this increase is mostly due to the vegetation gradient. The presence of short vegetation (h < 30 cm) is usually insufficient to affect the backscattering from snow-covered surfaces, such that the soil liquid water content and the surface roughness contribute most of the signal, to a degree that varies as a function of the angle of incidence [39]. The forest is a strong scatterer of radar energy to varying degrees, depending on the density, structure and composition of the forest [40].…”

Section: Spatial Variations In the Radarsat-1 Backscatter At The Timementioning

confidence: 99%

“…The correlation was slightly higher for the VV-polarized data (r = 0.79) compared with the HH-polarized data (r = 0.69), and the effect of dry snow on backscatter was more visible when the snow water equivalent values were greater than 50 mm, likely because of the decreased contribution from the ground. Specifically, the authors of [39] were unable to detect volume scattering within a shallow dry snow cover at the C-band because the radar return was dominated by the soil surface scattering. A semi-empirical model that accounts for this ground effect and that connects the thermal resistance of the snow with the backscatter signal was developed and tested in various environments to retrieve the snow water equivalent from the C-band SAR data [39,54,55].…”

Section: The Effect Of the Dry Snow On Backscatter In The Mid-winter mentioning

confidence: 99%

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C-Band SAR Imagery for Snow-Cover Monitoring at Treeline, Churchill, Manitoba, Canada

Pivot

2012

Remote Sensing

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RADARSAT and ERS-2 data collected at multiple incidence angles are used to characterize the seasonal variations in the backscatter of snow-covered landscapes in the northern Hudson Bay Lowlands during the winters of 1997/98 and 1998/99. The study evaluates the usefulness of C-band SAR systems for retrieving the snow water equivalent under dry snow conditions in the forest-tundra ecotone. The backscatter values are compared against ground measurements at six sampling sites, which are taken to be representative of the land-cover types found in the region. The contribution of dry snow to the radar return is evident when frost penetrates the first 20 cm of soil. Only then does the backscatter respond positively to changes in snow water equivalent, at least in the open and forested areas near the coast, where 1-dB increases in backscatter for each approximate 5-10 mm of accumulated water equivalent are observed at 20-31 incidence angles. Further inland, the backscatter shows either no change or a negative change with snow accumulation, which suggests that the radar signal there is dominated by ground surface scattering (e.g., fen) when not attenuated by vegetation (e.g., forested and transition). With high-frequency ground-penetrating radar, we demonstrate the presence of a 10-20-cm layer of black ice underneath the snow cover, which causes the reduced radar returns (−15 dB and less) observed in the inland fen. A correlation between the backscattering and the snow water equivalent cannot be determined due to insufficient observations at similar incidence angles. To establish a relationship between the snow water equivalent and the backscatter, only images acquired with similar incidence angles should be used, and they must be corrected for both vegetation and ground effects.

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Section: The Effect Of Soil Freezing On Backscatter In Autumn and Earmentioning

confidence: 94%

Section: Spatial Variations In the Radarsat-1 Backscatter At The Timementioning

confidence: 99%

Section: The Effect Of the Dry Snow On Backscatter In The Mid-winter mentioning

confidence: 99%

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C-Band SAR Imagery for Snow-Cover Monitoring at Treeline, Churchill, Manitoba, Canada

Pivot

2012

Remote Sensing

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“…Following the same approach used by Bernier and Fortin, we compute total a0 as a combination of surface scattering from the soil-snow interface and volume scattering in the snow. We use dense medium theory to compute the volume scattering instead of independent scattering theory as used by Bernier The data presented by Bernier and Fortin [1998] includes information about the mean snow density and depth, which we incorporate into the physical model described in section 2. We have assumed a fixed soil water content ar.d texture even though these parameters are probably varying somewhat between data points, so there is some model uncertainty in the fitted soil temperatures.…”

Section: Comparison With Datamentioning

confidence: 99%

“…As pointed out by Bernier and Fortin [1998], the thermal insulation provided by snow cover can have a powerful effect on the soil-snow interface by altering the soil temperature and therefore changing the dielectric contrast. The size of this effect depends on many factors including the temperature difference between the air and the soil at depth, the density of the snow, and the thermal propert!es of the soil.…”

mentioning

confidence: 99%

Potential applications of 1–5 GHz radar backscatter measurements of seasonal land snow cover

West¹

2000

Radio Science

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Abstract.Lower frequency microwave radar observations can help to measure the properties of snow cover on land by providing information about the soil-snow boundary condition. In this theoretical study, we examine the sensitivities of microwave radar measurements to soil and snow characteristics, and we compare a simple model with previously published data. Depending on the surface roughness, copolarized ratios or single polarization time ratios of radar backscattering may be affected only by the incidence angle and the dielectric contrast at the soil-snow boundaryø These measurements can reduce the number of unknowns in any corresponding higher-frequency observations that are also affected by the lower boundary condition. The copolarized ratio is sensitive, first of all, to the snow density, which offers the possibility of measuring this parameter directly if a separate measurement of the soil temperature from a passive microwave system is also available. The thermal insulation provided by snow cover can have a powerful effect on the soil-snow boundary by altering the soil temperature and therefore changing the dielectric contrast. Because the microwave response of snow cover is so sensitive to the conditions of the underlying frozen soil, it is important for future ground truth campaigns that measure snow conditions to also collect data on the temperature, water content, and texture of the soil.

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Determination of snow water equivalent using RADARSAT SAR data in eastern Canada

et al. 1999

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Abstract:In the 1998-1999 winter, the operational feasibility of using RADARSAT SAR data to estimate the spatial distribution of snow water equivalent (SWE) in a large hydroelectric complex managed by Hydro-QueÂ bec (La Grande River watershed) has been successfully demonstrated. This watershed is located in the subarctic climatic region in the north-west of the QueÂ bec province. The vegetation consists of moderately dense to open Black Spruce forests, open lands, burned lands and peat bogs. In the last few years, an original approach well adapted for this region has been developed to estimate the SWE from SAR data (ERS-1, RADARSAT). This approach is based on the fact that the snow cover characteristics in¯uence the underlying soil temperature which in¯uences the dielectric properties of the soil and then the recorded backscattering signal. Then, a linear relationship between the backscattering ratios of a winter image and a snow-free ( fall) image, and the snowpack thermal resistance (thermal insulation properties) has been established. Consequently, the algorithm infers the SWE from the estimated thermal resistance and the measured mean density of the snowpack. This algorithm has been implemented within a MapInfo 2 application that has been named EQeau. It allows mapping of the spatial distribution of the estimated SWE at the desired level ( pixel, square grid, sub-watershed). During the 1998-1999 winter, EQeau has been used successfully in a pre-operational mode using calibrated Wide beam images (W1) from RADARSAT. The algorithm has given mean estimated SWE values similar to the SWE values derived from Hydro-Quebec snow transects (relative dierence between 1% and 13%). Also, the SWE increase measured from January to March 1999 is clearly detected on the maps covering almost 77 000 km 2 . The next steps will be the evaluation of the ScanSAR images and the demonstration of the economical advantages of using RADARSAT data in a hydrological forecasting system.

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The potential of times series of C-Band SAR data to monitor dry and shallow snow cover

Cited by 93 publications

References 14 publications

C-Band SAR Imagery for Snow-Cover Monitoring at Treeline, Churchill, Manitoba, Canada

C-Band SAR Imagery for Snow-Cover Monitoring at Treeline, Churchill, Manitoba, Canada

Potential applications of 1–5 GHz radar backscatter measurements of seasonal land snow cover

Determination of snow water equivalent using RADARSAT SAR data in eastern Canada

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