Measuring the expressed abundance of the three phases of water with an imaging spectrometer over melting snow

被引:73
作者
Green, Robert O.
Painter, Thomas H.
Roberts, Dar A.
Dozier, Jeff
机构
[1] CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA
[2] Univ Colorado, Natl Snow & Ice Data Ctr, Boulder, CO 80309 USA
[3] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA
[4] Univ Calif Santa Barbara, Donald Bren Sch Environm Sci & Management, Santa Barbara, CA 93106 USA
关键词
D O I
10.1029/2005WR004509
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
[ 1] From imaging spectrometer data, we simultaneously estimate the abundance of the three phases of water in an environment that includes melting snow, basing the analysis on the spectral shift in the absorption coefficient between water vapor, liquid water, and ice at 940, 980, and 1030 nm respectively. We apply a spectral fitting algorithm that measures the expressed abundance of the three phases of water to a data set acquired by the Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) over Mount Rainier, Washington, on 14 June 1996. Precipitable water vapor varies from 1 mm over the summit of Mount Rainier to 10 mm over the lower valleys to the northwest. Equivalent path absorption of liquid water varies from 0 to 13 mm, with the zero values over rocky areas and high-elevation snow and the high values associated with liquid water held in vegetation canopies and in melting snow. Ice abundance varies from 0 to 30 mm equivalent path absorption in the snow- and glacier-covered portions of Mount Rainier. The water and ice abundances are related to the amount of liquid water and the sizes of the ice grains in the near-surface layer. Precision of the estimates, calculated over locally homogeneous areas, indicates an uncertainty of better than 1.5% for all three phases, except for liquid water in vegetation, where an optimally homogeneous site was not found. The analysis supports new strategies for hydrological research and applications as imaging spectrometers become more available.
引用
收藏
页数:12
相关论文
共 51 条
[21]   MODIS snow-cover products [J].
Hall, DK ;
Riggs, GA ;
Salomonson, VV ;
DiGirolamo, NE ;
Bayr, KJ .
REMOTE SENSING OF ENVIRONMENT, 2002, 83 (1-2) :181-194
[22]   Validation of mineralogical variations evident in simulated ARIES-1 hyperspectral data [J].
Huntington, JF ;
Yang, K ;
Boardman, JW .
HYPERSPECTRAL REMOTE SENSING AND APPLICATIONS, 1998, 3502 :76-86
[23]   INVERSION OF THE PROSPECT + SAIL CANOPY REFLECTANCE MODEL FROM AVIRIS EQUIVALENT SPECTRA - THEORETICAL-STUDY [J].
JACQUEMOUD, S .
REMOTE SENSING OF ENVIRONMENT, 1993, 44 (2-3) :281-292
[24]   REMOTE-SENSING OF WATER-VAPOR IN THE NEAR IR FROM EOS/MODIS [J].
KAUFMAN, YJ ;
GAO, BC .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1992, 30 (05) :871-884
[25]   Measuring snow and glacier ice properties from satellite [J].
König, M ;
Winther, JG ;
Isaksson, E .
REVIEWS OF GEOPHYSICS, 2001, 39 (01) :1-27
[26]  
KURUCZ RL, 1995, P 17 ANN REV C ATM T
[27]  
Liou K. N., 1980, An Introduction to Atmospheric Radiation
[28]  
MCCOY RP, 2002, IGARSS 02 2 INT GEOS, DOI DOI 10.1109/IGARSS.2002.1025624
[29]   A hyperspectral method for remotely sensing the grain size of snow [J].
Nolin, AW ;
Dozier, J .
REMOTE SENSING OF ENVIRONMENT, 2000, 74 (02) :207-216
[30]   Retrieval of subpixel snow-covered area and grain size from imaging spectrometer data [J].
Painter, TH ;
Dozier, J ;
Roberts, DA ;
Davis, RE ;
Green, RO .
REMOTE SENSING OF ENVIRONMENT, 2003, 85 (01) :64-77