DocumentCode :
1274925
Title :
Retrieval of surface temperature in boreal forest zone from SSM/I data
Author :
Pulliainen, Jouni T. ; Grandell, Jochen ; Hallikainen, Martti T.
Author_Institution :
Lab. of Space Technol., Helsinki Univ. of Technol., Espoo, Finland
Volume :
35
Issue :
5
fYear :
1997
fDate :
9/1/1997 12:00:00 AM
Firstpage :
1188
Lastpage :
1200
Abstract :
Novel inversion methods for the retrieval of surface temperature (air temperature at ground level) in forested areas using space-borne multi-channel microwave radiometer data are presented and analyzed. The first technique is an inversion method based on the use of a constrained least squares algorithm for the inversion of a semi-empirical emission model. The other methods discussed are empirical approaches: multiple linear regression and polarization difference formulas. The validity of the inversion method, as well as the feasibility of the empirical approaches, are evaluated in the case of Finnish boreal forests employing SSM/I data. The results show that for conifer dominated boreal forests the surface temperature can be estimated reliably from SSM/I measurements during snow-free conditions. The highest test site-wise determined correlation coefficients (r) between the ground-based reference values (near-surface air temperature) and the SSM/I-based estimates are above 0.97 and the corresponding unbiased rms errors are smaller than 1.3°C. These values were obtained using morning time overpasses of the SSM/I without any data rejection
Keywords :
atmospheric boundary layer; atmospheric techniques; atmospheric temperature; inverse problems; microwave measurement; radiometry; remote sensing; submillimetre wave measurement; temperature measurement; EHF; SHF; SSM/I; atmosphere; boreal forest zone; boundary layer; constrained least squares algorithm; forest; forested area; inverse problem; inversion method; measurement technique; meteorology; microwave radiometry; mm wave; multi-channel microwave radiometry; multiple linear regression; polarization; satellite remote sensing; surface temperature retrieval; vegetation; Frequency; Information retrieval; Land surface temperature; Linear regression; Microwave radiometry; Polarization; Snow; Spatial resolution; Testing; Vegetation;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/36.628786
Filename :
628786
Link To Document :
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