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.

The reuse of treated wastewater (TWW) for irrigation and the use of biosolids and manures as soil amendment constitute significant pathways for the introduction of the contaminants of emerging concern (CECs) to the agricultural environment. Consequently, CECs are routinely detected in TWW-irrigated agricultural soils and runoff from such sites, in biosolids-and manure-amended soils, and in surface and groundwater systems and sediments receiving TWW. Crop plants grown in such contaminated agricultural environments have been found to uptake and accumulate CECs in their tissues, constituting possible vectors of introducing CECs into the food chain; an issue that is presently considered of high priority, thus needing intensive investigation. This review paper aims at highlighting the responsible mechanisms for the uptake of CECs by plants and the ability of each crop plant species to uptake and accumulate CECs in its edible tissues, thus providing tools for mitigating the introduction of these contaminants into the food chain. Both biotic (e.g. plants' genotype and physiological state, soil fauna) and abiotic factors (e.g. soil pore water chemistry, physico-chemical properties of CECs, environmental perturbations) have been proven to influence the ability of crop plants to uptake and accumulate CECs. According to authors' estimates, based on the thorough elaboration of knowledge produced by existing relevant studies, the ability of crop plants to uptake and accumulate CECs decrease in the order of leafy vegetables > root vegetables > cereals and fodder crops > fruit vegetables; though, the uptake of CECs by important crop plants, such as fruit trees, is not yet evaluated. Overall, further studies must be performed to estimate the potential of crop plants to uptake and accumulate CECs in their edible tissues, and to characterize the risk for human health represented by their presence in human and livestock food products.

This paper presents the findings of the impact of atmospheric effects when applied on satellite images intended for supporting archaeological research. The study used eleven multispectral Landsat TM/ETM+ images from 2009 until 2010, acquired over archaeological and agricultural areas. The modified Darkest Pixel (DP) atmospheric correction algorithm was applied, as it is considered one of the most simple and effective atmospheric corrections algorithm. The NDVI equation was applied and its values were evaluated before and after the application of atmospheric correction to satellite images, to estimate its possible effects. The results highlighted that atmospheric correction has a significant impact on the NDVI values. This was especially true in seasons where the vegetation has grown. Although the absolute impact on NDVI, after applying the DP, was small (0.06), it was considered important if multi-temporal time series images need to be evaluated and cross-compared. The NDVI differences, before and after atmospheric correction, were assessed using student's t-test and the statistical differences were found to be significant. It was shown that relative NDVI difference can be as much as 50%, if OPEN ACCESSRemote Sens. 2011, 3 2606 atmosphere effects are ignored. Finally, the results had proven that atmospheric corrections can enhance the interpretation of satellite images (especially in cases where optical thickness of water vapour is minimized ≈ 0). This fact can assist in the detection and identification of archaeological crop marks. Therefore, removal of atmospheric effects, for archaeological purposes, was found to be of great importance in improving the image enhancement and NDVI values.