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Titel |
Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices |
VerfasserIn |
D. G. Hadjimitsis, G. Papadavid, A. Agapiou, K. Themistocleous, M. G. Hadjimitsis, A. Retalis, S. Michaelides, N. Chrysoulakis, L. Toulios, C. R. I. Clayton |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1561-8633
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Digitales Dokument |
URL |
Erschienen |
In: Natural Hazards and Earth System Science ; 10, no. 1 ; Nr. 10, no. 1 (2010-01-14), S.89-95 |
Datensatznummer |
250007878
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Publikation (Nr.) |
copernicus.org/nhess-10-89-2010.pdf |
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Zusammenfassung |
Solar radiation reflected by the Earth's surface to satellite sensors is
modified by its interaction with the atmosphere. The objective of applying an
atmospheric correction is to determine true surface reflectance values and to
retrieve physical parameters of the Earth's surface, including surface
reflectance, by removing atmospheric effects from satellite images.
Atmospheric correction is arguably the most important part of the
pre-processing of satellite remotely sensed data. Such a correction is
especially important in cases where multi-temporal images are to be compared
and analyzed. For agricultural applications, in which several vegetation
indices are applied for monitoring purposes, multi-temporal images are used.
The integration of vegetation indices from remotely sensed images with other
hydro-meteorological data is widely used for monitoring natural hazards such
as droughts. Indeed, the most important task is to retrieve the true values
of the vegetation status from the satellite-remotely sensed data. Any
omission of considering the effects of the atmosphere when vegetation indices
from satellite images are used, may lead to major discrepancies in the final
outcomes. This paper highlights the importance of considering atmospheric
effects when vegetation indices, such as DVI, NDVI, SAVI, MSAVI and SARVI,
are used (or considered) and presents the results obtained by applying the
darkest-pixel atmospheric correction method on ten Landsat TM/ETM+ images of
Cyprus acquired from July to December 2008. Finally, in this analysis, an
attempt is made to determine evapotranspiration and to examine its dependence
on the consideration of atmospheric effects when multi-temporal image data
are used. It was found that, without applying any atmospheric correction, the
real daily evapotranspiration was less than the one found after applying the
darkest pixel atmospheric correction method. |
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