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 Correspondence to: D. G. Hadjimitsis (d.hadjimitsis@cut.ac.cy) 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.
Abstract. The monitoring of aerosol concentrations comprises a high environmental priority, particularly in urban areas. Remote sensing of atmospheric aerosol optical thickness (AOT) could be used to assess particulate matter levels at the ground. However, such measurements often need further validation. In this study, aerosol data retrieved from satellite and sun-photometer, on the one hand, and visibility data at various locations in Cyprus, on the other hand, for the period from January to June 2009 are contrasted. The results obtained by the direct comparison between MODIS and handheld sun-photometer AOT data exhibited a significant correlation (r=0.83); these results are in agreement with those reported by the National Aeronautics and Space Administration (NASA). The correlation between sun-photometer AOT and that estimated from visibility measurements was also significant (r=0.76). A direct and significant relationship between MODIS AOT and AOT estimated from visibility values was also found for all the locations used (the correlation coefficient was found to vary from 0.80 to 0.84). It is concluded that MODIS AOT data provide accurate information on the aerosol content in Cyprus, while in the absence of such data, visibility measurements could be used as a secondary source of aerosol load information, in terms of aerosol optical thickness, and provide useful information on a near-real time basis, whenever data are available.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.