Research Papers

Influence of topographic normalization on the vegetation index–surface temperature relationship

[+] Author Affiliations
Jasper Van doninck

Ghent University, Laboratory of Hydrology and Water Management, Coupure links 653, Ghent, Belgium

Jan Peters, Bernard De Baets

Ghent University, Department of Mathematical Modelling, Statistics and Bioinformatics, Coupure links 653, Ghent, Belgium

Eva M. De Clercq, Els Ducheyne

Avia-GIS, Risschotlei 33, Zoersel, Belgium

Niko E. C. Verhoest

Ghent University, Laboratory of Hydrology and Water Management, Coupure links 653, Ghent, Belgium

J. Appl. Remote Sens. 6(1), 063518 (Mar 20, 2012). doi:10.1117/1.JRS.6.063518
History: Received June 30, 2011; Revised December 12, 2011; Accepted January 17, 2012
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Abstract.  The estimation of surface soil moisture status and evapotranspiration from optical remote sensing using the vegetation index–surface temperature (VI-TS) relationship is severely hampered in regions with strong topography, due to the influence of altitude and terrain orientation on surface temperature. In our study, a new empirical approach to normalize surface temperature for terrain elevation—a stratified linear regression model—is presented and is applied on moderate-resolution imaging spectroradiometer (MODIS) data over Calabria, Italy. The method incorporates remotely sensed land surface temperature, a vegetation index, and a digital elevation model. The influence of the newly developed normalization on the VI-TS relationship and on a soil dryness index is compared to the influence of two existing normalization methods: one using a standard lapse rate of 0.65 K per 100 m and one using a lapse rate derived through simple linear regression between elevation and surface temperature. Stratified linear regression adequately corrects surface temperature while the two other normalization techniques seem to overestimate the actual temperature lapse rate during certain periods of the year. Comparison of a soil dryness index derived using the three different normalization methods with limited in situ soil moisture data results in a slightly stronger correlation for the stratified linear regression model than for the two other normalization methods. VI-TS–based soil wetness estimation in mountainous terrains remains, however, limited by other spatially varying factors, including terrain orientation and atmospheric conditions.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Jasper Van doninck ; Jan Peters ; Bernard De Baets ; Eva M. De Clercq ; Els Ducheyne, et al.
"Influence of topographic normalization on the vegetation index–surface temperature relationship", J. Appl. Remote Sens. 6(1), 063518 (Mar 20, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063518


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