Recent advances in remote sensing of seasonal snow

Nolin, A. W.

doi:10.3189/002214311796406077

Cited by 204 publications

(151 citation statements)

References 66 publications

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“…Passive microwave measurements use a 25 km wide swath measurement [66,67], which immediately provides a significant limitation for the scenarios of interest, as information can only be interpreted at regional to hemispheric scales [66]. This resolution is again, further degraded when translated to the slope-parallel distances of a mountainous environment.…”

Section: Passive Microwave Sensingmentioning

confidence: 99%

“…The latest developments in active SAR, entails the use of Ku-band and X-band radiation, combined. This provides a combination of surface scattering and volume scattering effects [66], which could possibly improve the errors caused by reflections within an inhomogeneous snowpack.…”

Section: Active Microwave Sensingmentioning

confidence: 99%

“…Active microwave measurements use the phase of the reflected and subsequently refracted wave emerging from the snowpack, hence corrections must be made such that it appears that the signal is orthogonally incident on the snowpack [74]; although active microwave satellite resolution is extremely good [66], the resolution of the measurement is also degraded in mountainous terrain due to the additional length component added when a horizontal measurement is converted to a slope parallel measurement.…”

Section: Active Microwave Sensingmentioning

confidence: 99%

“…Comprehensive reviews of satellite-based snow sensing methods and products are provided in [65][66][67]. There are four types of products, using: visible, infrared, active microwave, and passive microwave sensing techniques.…”

Section: Satellite Productsmentioning

confidence: 99%

“…Passive microwave SWE measurement products have been produced since 1978 [66]. In passive microwave measurements, the naturally emitted microwave radiation from the soil is measured and SWE is inferred from the attenuation of the values measured with no snow present.…”

Section: Passive Microwave Sensingmentioning

confidence: 99%

See 4 more Smart Citations

Soil Moisture & Snow Properties Determination with GNSS in Alpine Environments: Challenges, Status, and Perspectives

et al. 2013

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Moisture content in the soil and snow in the alpine environment is an important factor, not only for environmentally oriented research, but also for decision making in agriculture and hazard management. Current observation techniques quantifying soil moisture or characterizing a snow pack often require dedicated instrumentation that measures either at point scale or at very large (satellite pixel) scale. Given the heterogeneity of both snow cover and soil moisture in alpine terrain, observations of the spatial distribution of moisture and snow-cover are lacking at spatial scales relevant for alpine hydrometeorology. This paper provides an overview of the challenges and status of the determination of soil moisture and snow properties in alpine environments. Current measurement techniques and newly proposed ones, based on the reception of reflected Global Navigation Satellite Signals (i.e., GNSS Reflectometry or GNSS-R), or the use of laser scanning are reviewed, and the perspectives offered by these new techniques to fill the current gap in the instrumentation level are discussed. Some key enabling technologies OPEN ACCESSRemote Sens. 2013, 5 3517 including the availability of modernized GNSS signals and GNSS array beamforming techniques are also considered and discussed.

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Section: Passive Microwave Sensingmentioning

confidence: 99%

Section: Active Microwave Sensingmentioning

confidence: 99%

Section: Active Microwave Sensingmentioning

confidence: 99%

Section: Satellite Productsmentioning

confidence: 99%

Section: Passive Microwave Sensingmentioning

confidence: 99%

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Soil Moisture & Snow Properties Determination with GNSS in Alpine Environments: Challenges, Status, and Perspectives

et al. 2013

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The temporal and spatial variability in submeter scale surface roughness of seasonal snow in Sodankylä Finnish Lapland in 2009–2010

Anttila

Manninen

Karjalainen³

et al. 2014

JGR Atmospheres

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Seasonal snow surface roughness is an important parameter for remote sensing data analysis since it affects the scattering properties of the snow surface. To understand the phenomenon, snow surface roughness was measured near the town of Sodankylä, in Finnish Lapland, during winters 2009 and 2010 using a photogrammetry-based plate method. The images were automatically processed so that an approximately 1 m long horizontal profile was extracted from each image. The data set consists of 669 plate profiles from different times and canopy types. This large data set was used to study the temporal and spatial variability of seasonal snow surface roughness. The profiles were analyzed using parameters derived from the root mean square height (σ) and correlation length (L) as functions of measured length. Also, the autocorrelation functions were calculated and analyzed. The (σ) and (L) were found to be so strongly correlated (R 2~0 .97) that a more detailed analysis was made using only the scaling parameters derived from σ. These parameters are related to the distance dependence of the rms height. The results show that they react to different characteristics of the profiles and are therefore well able to distinguish between different types of snow. They also show a clear difference between midwinter snow and melting snow, and the effects of snowfall events and slower melting in forested areas are evident in the data.

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White water: Fifty years of snow research in WRR and the outlook for the future

Sturm

2015

Water Resources Research

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Over the past 50 years, 239 papers related to snow have been published in Water ResourcesResearch (WRR). Seminal papers on virtually every facet of snow physics and snow water resources have appeared in the journal. These include papers on drifting snow, the snow surface energy balance, the effect of grain size on albedo, chemical elution, water movement through snow, and canopy interception. In particular, papers in WRR have explored the distribution of snow across different landscapes, providing data, process knowledge, and the basis for virtually all of the distributed snow models in use today. In this paper, I review these key contributions and provide some personal thoughts on what is likely to be the focus and nature of papers published in the next few decades, a period that is likely to see an increasing ability to map snow cover in detail, which should serve as a basis for the further development and improvement of snow models. It will also be an uncertain future, with profound changes in snow climatology predicted. I expect WRR will continue to play a key role in documenting and understanding these important cryospheric changes.

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Recent advances in remote sensing of seasonal snow

Cited by 204 publications

References 66 publications

Soil Moisture & Snow Properties Determination with GNSS in Alpine Environments: Challenges, Status, and Perspectives

Soil Moisture & Snow Properties Determination with GNSS in Alpine Environments: Challenges, Status, and Perspectives

The temporal and spatial variability in submeter scale surface roughness of seasonal snow in Sodankylä Finnish Lapland in 2009–2010

White water: Fifty years of snow research in WRR and the outlook for the future

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