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<article language="en">
	<journal>
		<journal_title>Hydrology and Earth System Sciences</journal_title>
		<journal_url>www.hydrol-earth-syst-sci.net</journal_url>
		<issn>1027-5606</issn>
		<eissn>1607-7938</eissn>
		<volume_number>13</volume_number>
		<issue_number>6</issue_number>
		<publication_year>2009</publication_year>
	</journal>
	<doi>10.5194/hess-13-749-2009</doi>
	<article_url>http://www.hydrol-earth-syst-sci.net/13/749/2009/</article_url>
	<abstract_html>http://www.hydrol-earth-syst-sci.net/13/749/2009/hess-13-749-2009.html</abstract_html>
	<fulltext_pdf>http://www.hydrol-earth-syst-sci.net/13/749/2009/hess-13-749-2009.pdf</fulltext_pdf>
	<start_page>749</start_page>
	<end_page>758</end_page>
	<publication_date>2009-06-12</publication_date>
	<article_title content_type="html">A Bayesian approach to estimate sensible and latent heat over vegetated land surface</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>C. van der Tol</name>
			<email>tol@itc.nl</email>
		</author>
		<author numeration="2" affiliations="2">
			<name>S. van der Tol</name>
		</author>
		<author numeration="3" affiliations="3">
			<name>A. Verhoef</name>
		</author>
		<author numeration="4" affiliations="1">
			<name>B. Su</name>
		</author>
		<author numeration="5" affiliations="1">
			<name>J. Timmermans</name>
		</author>
		<author numeration="6" affiliations="3">
			<name>C. Houldcroft</name>
		</author>
		<author numeration="7" affiliations="1">
			<name>A. Gieske</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">ITC International Institute for Geo-Information Science and Earth Observation Hengelosestraat 99, P. O. Box 6, 7500 AA Enschede, The Netherlands</affiliation>
		<affiliation numeration="2" content_type="html">Delft University of Technology, Faculty of Electrical Engineering, Mekelweg 4, 2628 CD Delft, The Netherlands</affiliation>
		<affiliation numeration="3" content_type="html">The University of Reading, Department of Soil Science, School of Human and Environmental Sciences, Reading RG6 6DW, UK</affiliation>
	</affiliations>
	<abstract content_type="html">Sensible and latent heat fluxes are often calculated from bulk transfer
equations combined with the energy balance. For spatial estimates of these
fluxes, a combination of remotely sensed and standard meteorological data
from weather stations is used. The success of this approach depends on the
accuracy of the input data and on the accuracy of two variables in
particular: aerodynamic and surface conductance. This paper presents a
Bayesian approach to improve estimates of sensible and latent heat fluxes by
using a priori estimates of aerodynamic and surface conductance alongside
remote measurements of surface temperature. The method is validated for time
series of half-hourly measurements in a fully grown maize field, a vineyard
and a forest. It is shown that the Bayesian approach yields more accurate
estimates of sensible and latent heat flux than traditional methods.</abstract>
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</article>

