Improvements in the split-window technique for land surface temperature determination

Land surface temperature (LST) retrievals obtained from NOAA Advanced Very High Resolution Radiometer (AVHRR) are of considerable importance for climatic research. However, the accurate evaluation of LST from space has been severely limited because of the difficulty in separating atmospheric from su...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 1994-03, Vol.32 (2), p.243-253
Main Authors: Sobrino, J.A., Zhao-Liang Li, Stoll, M.P., Becker, F.
Format: Article
Language:English
Subjects:
Atmospheric measurements
Atmospheric modeling
Brightness temperature
Earth, ocean, space
Exact sciences and technology
External geophysics
Geophysics. Techniques, methods, instrumentation and models
Land surface
Land surface temperature
Ocean temperature
Satellite broadcasting
Sea surface
Temperature measurement
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Land surface temperature (LST) retrievals obtained from NOAA Advanced Very High Resolution Radiometer (AVHRR) are of considerable importance for climatic research. However, the accurate evaluation of LST from space has been severely limited because of the difficulty in separating atmospheric from surface effects as the surface cannot be modeled as a black-body radiator. With this goal in mind, a novel extension of the split-window technique is presented in which the atmospheric contribution to the radiance measured by the satellite is investigated by the ratioing of covariance and variance of the brightness temperatures measured in channels 4 and 5 of AVHRR/2. Furthermore, the contribution of emissivity is evaluated from coefficients that depend on the spectral emissivities in both thermal channels. Using a wide range of simulations from an atmospheric radiative transfer model it is shown that the proposed algorithm provides an estimate of LST, to within 0.4 K if the spectral surface emissivity is known, which is better than that given by the currently used split-window algorithms for LST determination. Also the limitations on algorithm accuracy are discussed considering different values of noise equivalent temperature. Finally the authors present the preliminary results obtained using the proposed method from AVHRR data over a semi-arid region-of Northwestern Victoria in Australia provided by CSIRO, and a mountainous region of Northeast of France acquired in the frame of Regio Klimat Projekt.< >
ISSN:0196-2892
1558-0644
DOI:10.1109/36.295038