H. Nouri , S. Beecham , F. Kazemi , A. M. Hassanli , and S. Anderson
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.
Received: 12 Feb 2013 – Discussion started: 25 Mar 2013
Publisher's note : Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
H. Nouri , S. Beecham , F. Kazemi , A. M. Hassanli , and S. Anderson
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Status: closed
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AC : Author comment | RC : Referee comment | SC : Short comment | EC : Editor comment
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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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Jan 2019
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139
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1,569
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142
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1,594
3,884
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1,601
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1,623
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Latest update: 23 Nov 2025