Estimation of surface snow properties using combined near-infrared reflectance and millimeter-wave backscatter

Ram M. Narayanan; Sandy R. Jackson; Karen M. St. Germain

Estimation of surface snow properties using combined near-infrared reflectance and millimeter-wave backscatter

Ram M. Narayanan
, Sandy R. Jackson
, Karen M. St. Germain

Electrical Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

Remote sensing techniques using combined concurrent measurements of near-infrared passive reflectance and millimeter-wave radar backscatter were used to estimate surface snow properties. The effectiveness of the procedure was tested using 400 combinations of surface parameters. Results indicate that a neural network approach using near-infrared and millimeter-wave measurements show promise in estimating surface snow parameters. Since the spatial resolutions attainable at near-infrared and millimeter-wave spectral regimes are different, a combination of these inversion algorithms has the potential to characterize the spatial distribution of free-water content of snow, while also providing accurate estimates of grain size and surface roughness.

Original language	English (US)
Pages	189-191
Number of pages	3
State	Published - 1995
Event	Proceedings of the 2nd Topical Symposium on Combined Optical-Microwave Earth and Atmosphere Sensing - Atlanta, GA, USA Duration: Apr 3 1995 → Apr 6 1995

Other

Other	Proceedings of the 2nd Topical Symposium on Combined Optical-Microwave Earth and Atmosphere Sensing
City	Atlanta, GA, USA
Period	4/3/95 → 4/6/95

All Science Journal Classification (ASJC) codes

General Earth and Planetary Sciences

Cite this

@conference{7a1b8f68081d4ec0b75918c15c5f18d0,

title = "Estimation of surface snow properties using combined near-infrared reflectance and millimeter-wave backscatter",

abstract = "Remote sensing techniques using combined concurrent measurements of near-infrared passive reflectance and millimeter-wave radar backscatter were used to estimate surface snow properties. The effectiveness of the procedure was tested using 400 combinations of surface parameters. Results indicate that a neural network approach using near-infrared and millimeter-wave measurements show promise in estimating surface snow parameters. Since the spatial resolutions attainable at near-infrared and millimeter-wave spectral regimes are different, a combination of these inversion algorithms has the potential to characterize the spatial distribution of free-water content of snow, while also providing accurate estimates of grain size and surface roughness.",

author = "Narayanan, \{Ram M.\} and Jackson, \{Sandy R.\} and \{St. Germain\}, \{Karen M.\}",

year = "1995",

language = "English (US)",

pages = "189--191",

note = "Proceedings of the 2nd Topical Symposium on Combined Optical-Microwave Earth and Atmosphere Sensing ; Conference date: 03-04-1995 Through 06-04-1995",

}

Estimation of surface snow properties using combined near-infrared reflectance and millimeter-wave backscatter. / Narayanan, Ram M.; Jackson, Sandy R.; St. Germain, Karen M.
1995. 189-191 Paper presented at Proceedings of the 2nd Topical Symposium on Combined Optical-Microwave Earth and Atmosphere Sensing, Atlanta, GA, USA.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - Estimation of surface snow properties using combined near-infrared reflectance and millimeter-wave backscatter

AU - Narayanan, Ram M.

AU - Jackson, Sandy R.

AU - St. Germain, Karen M.

PY - 1995

Y1 - 1995

N2 - Remote sensing techniques using combined concurrent measurements of near-infrared passive reflectance and millimeter-wave radar backscatter were used to estimate surface snow properties. The effectiveness of the procedure was tested using 400 combinations of surface parameters. Results indicate that a neural network approach using near-infrared and millimeter-wave measurements show promise in estimating surface snow parameters. Since the spatial resolutions attainable at near-infrared and millimeter-wave spectral regimes are different, a combination of these inversion algorithms has the potential to characterize the spatial distribution of free-water content of snow, while also providing accurate estimates of grain size and surface roughness.

AB - Remote sensing techniques using combined concurrent measurements of near-infrared passive reflectance and millimeter-wave radar backscatter were used to estimate surface snow properties. The effectiveness of the procedure was tested using 400 combinations of surface parameters. Results indicate that a neural network approach using near-infrared and millimeter-wave measurements show promise in estimating surface snow parameters. Since the spatial resolutions attainable at near-infrared and millimeter-wave spectral regimes are different, a combination of these inversion algorithms has the potential to characterize the spatial distribution of free-water content of snow, while also providing accurate estimates of grain size and surface roughness.

UR - https://www.scopus.com/pages/publications/0029212706

UR - https://www.scopus.com/pages/publications/0029212706#tab=citedBy

M3 - Paper

AN - SCOPUS:0029212706

SP - 189

EP - 191

T2 - Proceedings of the 2nd Topical Symposium on Combined Optical-Microwave Earth and Atmosphere Sensing

Y2 - 3 April 1997 through 6 April 1995

ER -

Estimation of surface snow properties using combined near-infrared reflectance and millimeter-wave backscatter

Abstract

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All Science Journal Classification (ASJC) codes

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