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

Bernier, Monique; Fortin, Jean‐Pierre; Gauthier, Yves; Gauthier, R.; Roy, René; Vincent, Pierre

doi:10.1002/(sici)1099-1085(19991230)13:18<3041::aid-hyp14>3.0.co;2-e

Cited by 56 publications

(35 citation statements)

References 14 publications

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“…Methods using SAR (high resolution radar) have also been proposed (Bernier et al, 1999) to get much finer resolution (∼100 m versus 25 km with passive microwave) at the expense of temporal resolution (monthly versus daily). Retrieval of SWE using both the ERS altimeter and passive measurements were also investigated (Papa et al, 2002).…”

Section: Application 1: Continental Snow Cover Extentmentioning

confidence: 99%

Snow physics as relevant to snow photochemistry

et al. 2008

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Abstract. Snow on the ground is a complex multiphase photochemical reactor that dramatically modifies the chemical composition of the overlying atmosphere. A quantitative description of the emissions of reactive gases by snow requires knowledge of snow physical properties. This overview details our current understanding of how those physical properties relevant to snow photochemistry vary during snow metamorphism. Properties discussed are density, specific surface area, thermal conductivity, permeability, gas diffusivity and optical properties. Inasmuch as possible, equations to parameterize these properties as functions of climatic variables are proposed, based on field measurements, laboratory experiments and theory. The potential of remote sensing methods to obtain information on some snow physical variables such as grain size, liquid water content and snow depth are discussed. The possibilities for and difficulties of building a snow photochemistry model by adapting current snow physics models are explored. Elaborate snow physics models already exist, and including variables of particular interest to snow photochemistry such as light fluxes and specific surface area appears possible. On the other hand, understanding the nature and location of reactive molecules in snow seems to be the greatest difficulty modelers will have to face for lack of experimental data, and progress on this aspect will require the detailed study of natural snow samples.

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Section: Application 1: Continental Snow Cover Extentmentioning

confidence: 99%

Snow physics as relevant to snow photochemistry

et al. 2008

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“…In this temporal study, we assumed that soil surface roughness was constant over time for each land use type (untilled versus tilled fields) during the same winter season, because the soil surface would not be ploughed nor naturally modified before spring snowmelt [60]. Under this assumption, it is possible to consider that for each field, the backscattering coefficient (σ • ) was related to soil surface moisture status [31].…”

Section: Frozen Soil Mapping Algorithm the Linear Regression In Thismentioning

confidence: 94%

Mapping Agricultural Frozen Soil on the Watershed Scale Using Remote Sensing Data

Khaldoune

Bochove

Bernier

et al. 2011

Applied and Environmental Soil Science

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This paper presents an empirical model for classifying frozen/unfrozen soils in the entire Bras d'Henri River watershed (167 km 2 ) near Quebec City (Quebec, Canada). It was developed to produce frozen soil maps under snow cover using RADARSAT-1 fine mode images and in situ data during three winters. Twelve RADARSAT-1 images were analyzed from fall 2003 to spring 2006 to discern the intra-and interannual variability of frozen soil characteristics. Regression models were developed for each soil group (parent material-drainage-soil type) and land cover to establish a threshold for frozen soil from the backscattering coefficients (HH polarization). Tilled fields showed higher backscattering signal (+3 dB) than the untilled fields. The overall classification accuracy was 87% for frozen soils and 94% for unfrozen soils. With respect to land use, that is, tilled versus untilled fields, an overall accuracy of 89% was obtained for the tilled fields and 92% for the untilled fields. Results show that this new mapping approach using RADARSAT-1 images can provide estimates of surface soil status (frozen/unfrozen) at the watershed scale in agricultural areas.

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“…This is due to thermal insulation of the developing dry snowpack [49,50], which keeps the ground homogeneously frozen even for short diurnal periods with T air > 0 • C (as is the case during the "cold winter period" after 19 January according to Figure 2d). …”

Section: Multi-angle Retrievalsmentioning

confidence: 99%

Snow Density and Ground Permittivity Retrieved from L-Band Radiometry: Melting Effects

Schwank

Naderpour

2018

Remote Sensing

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Ground permittivity and snow density retrievals for the "snow-free period", "cold winter period", and "early spring period" are performed using the experimental L-band radiometry data from the winter 2016/2017 campaign at the Davos-Laret Remote Sensing Field Laboratory. The performance of the single-angle and multi-angle two-parameter retrieval algorithms employed during each of the aforementioned three periods is assessed using in-situ measured ground permittivity and snow density. Additionally, a synthetic sensitivity analysis is conducted that studies melting effects on the retrievals in the form of two types of "geophysical noise" (snow liquid water and footprint-dependent ground permittivity). Experimental and synthetic analyses show that both types of investigated "geophysical noise" noticeably disturb the retrievals and result in an increased correlation between them. The strength of this correlation is successfully used as a quality-indicator flag for the purpose of filtering out highly correlated ground permittivity and snow density retrievals. It is demonstrated that this filtering significantly improves the accuracy of both ground permittivity and snow density retrievals compared to corresponding reference in-situ data. Experimental and synthetic retrievals are performed in retrieval modes RM = "H", "V", and "HV", where brightness temperatures from polarizations p = H, p = V, or both p = H and V are used, respectively, in the retrieval procedure. Our analysis shows that retrievals for RM = "V" are predominantly least prone to the investigated "geophysical noise". The presented experimental results indicate that retrievals match in-situ observations best for the "snow-free period" and the "cold winter period" when "geophysical noise" is at minimum.

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

Cited by 56 publications

References 14 publications

Snow physics as relevant to snow photochemistry

Snow physics as relevant to snow photochemistry

Mapping Agricultural Frozen Soil on the Watershed Scale Using Remote Sensing Data

Snow Density and Ground Permittivity Retrieved from L-Band Radiometry: Melting Effects

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