Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices
Journal
Natural Hazards and Earth System Sciences
Date Issued
January 14, 2010
DOI
10.5194/nhess-10-89-2010
Abstract
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 hydrometeorological
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.
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 hydrometeorological
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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