Preprints
https://doi.org/10.5194/hessd-10-3897-2013
https://doi.org/10.5194/hessd-10-3897-2013
25 Mar 2013
 | 25 Mar 2013
Status: this preprint was under review for the journal HESS but the revision was not accepted.

Remote sensing techniques for predicting evapotranspiration from mixed vegetated surfaces

H. Nouri, S. Beecham, F. Kazemi, A. M. Hassanli, and S. Anderson

Abstract. Evapotranspiration (ET) as the key component of hydrological balance is the most difficult factor to quantity. In the last decades, ET estimation has been benefitted from advances in remote sensing particularly in agricultural fields. However, quantifying evapotranspiration from mixed landscape vegetation environs is still complicated and challenging due to the heterogeneity of plant species, canopy covers, microclimate, and because of costly methodological requirements. Extensive numbers of studies have been conducted in agriculture and forestry that alternatively ought to be borrowed for mixed landscape vegetation studies with some modifications. This review describes general remote sensing-based approaches to estimate ET and their pros and cons. Considering the fact that most of them need extensive time investment, medium to high level of skills and are quite expensive, the simplest approach; interface, is recommended to apply for mixed vegetation. Then, VI-based approach was discussed for two categories of agricultural and non-agricultural environs. Some promising studies were mentioned to support the suitability of the method for mixed landscape environs.

H. Nouri, S. Beecham, F. Kazemi, A. M. Hassanli, and S. Anderson
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
H. Nouri, S. Beecham, F. Kazemi, A. M. Hassanli, and S. Anderson
H. Nouri, S. Beecham, F. Kazemi, A. M. Hassanli, and S. Anderson

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