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Proceedings Paper

Application of Landsat images for quantifying the energy balance under conditions of land use changes in the semi-arid region of Brazil
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Paper Abstract

In the Nilo Coelho irrigation scheme, Brazil, the natural vegetation has been replaced by irrigated agriculture, bringing importance for the quantification of the effects on the energy exchanges between the mixed vegetated surfaces and the low atmosphere. Landsat satellite images and agro-meteorological stations from 1992 to 2011 were used together, for modelling these exchanges. Surface albedo (α0), NDVI and surface temperature (T0) were the basic remote sensing parameters necessary to calculate the latent heat flux (λE) and the surface resistance to evapotranspiration (rs) at the large scale. The daily net radiation (Rn) was retrieved from α0, air temperature (Ta) and transmissivity (τsw) throughout the slob equation, allowing the quantification of the daily sensible heat flux (H) by residual in the energy balance equation. With a threshold value for rs, it was possible to separate the energy fluxes from crops and natural vegetation. The averaged fractions of Rn partitioned as H and λE, were in average 39 and 67%, respectively. It was observed an increase of the energy used in the evapotranspiration process inside irrigated areas from 51% in 1992 to 80% in 2011, with the ratio λE/Rn presenting an increase of 3 % per year. The tools and models applied in the current research, can subsidize the monitoring of the coupled climate and land use changes effects in irrigation perimeters, being valuable when aiming the sustainability of the irrigated agriculture in the future, avoiding conflicts among different water users.

Paper Details

Date Published: 23 October 2012
PDF: 9 pages
Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 85310P (23 October 2012); doi: 10.1117/12.965882
Show Author Affiliations
Antônio H. de de C. Teixeira, Embrapa Semiárido (Brazil)
Fernando B. T. Hernandez, Univ. Estadual São Paulo (Brazil)
Hélio L. Lopes, Univ. Federal de Pernambuco (Brazil)

Published in SPIE Proceedings Vol. 8531:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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