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.

Plastic litter floating in the ocean is a significant problem on a global scale. This study examines whether Sentinel-2 satellite images can be used to identify plastic litter on the sea surface for monitoring, collection and disposal. A pilot study was conducted to determine if plastic targets on the sea surface can be detected using remote sensing techniques with Sentinel-2 data. A target made up of plastic water bottles with a surface measuring 3 m × 10 m was created, which was subsequently placed in the sea near the Old Port in Limassol, Cyprus. An unmanned aerial vehicle (UAV) was used to acquire multispectral aerial images of the area of interest during the same time as the Sentinel-2 satellite overpass. Spectral signatures of the water and the plastic litter after it was placed in the water were taken with an SVC HR1024 spectroradiometer. The study found that the plastic litter target was easiest to detect in the NIR wavelengths. Seven established indices for satellite image processing were examined to determine whether they can identify plastic litter in the water. Further, the authors examined two new indices, the Plastics Index (PI) and the Reversed Normalized Difference Vegetation Index (RNDVI) to be used in the processing of the satellite image. The newly developed Plastic Index (PI) was able to identify plastic objects floating on the water surface and was the most effective index in identifying the plastic litter target in the sea.

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.

Determination of turbidity is a common component of water-quality assessments. In regions where there are a lot of inland waters such as dams, sampling even a small proportion of those dams for monitoring and assessing water quality is cost prohibitive. Satellite remote sensing has the potential to be a powerful tool for assessing water quality over large spatial scales. The overall objective of this study was to examine whether Landsat-5 TM (Thematic Mapper) and Landsat-7 ETM+ (Enhanced Thematic Mapper) could be used to measure turbidity across the Kourris Dam, which is the biggest dam in Cyprus. This paper presents the results obtained by applying the linear regression analysis in order to examine the relationship between the turbidity measurements measured in-situ during the satellite overpass against at-satellite atmospheric corrected reflectance values. It has been found that the reflectance, after atmospheric correction, at Landsat TM Bands 1 and 3 is strongly related with turbidity levels after linear regression analysis. The most significant correlation was occurred when reflectance in TM band 3 and logarithmic reflectance in TM band 3 were correlated with turbidity measurements. Indeed, the correlation coefficient (R) when atmospheric corrected reflectance (ρ) in the Landsat TM band 3 were correlated against turbidity, before atmospheric correction was R = 0.38 and after atmospheric correction was R = 1; and when atmospheric corrected logarithmic reflectance (Log ρ) in the Landsat TM band 3 were correlated against turbidity, before atmospheric correction was R = 0.46 and after atmospheric correction was R = 1.

Disaster risk management (DRM) for cultural heritage is a complex task that requires multidisciplinary cooperation. This short communication underlines the critical role of satellite remote sensing (also known as earth observation) in DRM in dealing with various hazards for cultural heritage sites and monuments. Here, satellite observation potential is linked with the different methodological steps of the DRM cycle. This is achieved through a short presentation of recent paradigms retrieved from research studies and the Scopus scientific repository. The communication focuses on the Eastern Mediterranean region, an area with an indisputable wealth of archaeological sites. Regarding the cultural heritage type, this article considers relevant satellite observation studies implemented in open-air archaeological monuments and sites. The necessity of this communication article emerged while trying to bring together earth observation means, cultural heritage needs, and DRM procedures.

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Cyprus plans to drastically increase the share of renewable energy sources from 13.9% in 2020 to 22.9% in 2030. Solar energy can play a key role in the effort to fulfil this goal. The potential for production of solar energy over the island is much higher than most of European territory because of the low latitude of the island and the nearly cloudless summers. In this study, high quality and fine resolution satellite retrievals of aerosols and dust, from the newly developed MIDAS climatology, and information for clouds from CM SAF are used in order to quantify the effects of aerosols, dust, and clouds on the levels of surface solar radiation for 2004–2017 and the corresponding financial loss for different types of installations for the production of solar energy. Surface solar radiation climatology has also been developed based on the above information. Ground-based measurements were also incorporated to study the contribution of different species to the aerosol mixture and the effects of day-to-day variability of aerosols on SSR. Aerosols attenuate 5–10% of the annual global horizontal irradiation and 15–35% of the annual direct normal irradiation, while clouds attenuate 25–30% and 35–50% respectively. Dust is responsible for 30–50% of the overall attenuation by aerosols and is the main regulator of the variability of total aerosol. All-sky annual global horizontal irradiation increased significantly in the period of study by 2%, which was mainly attributed to changes in cloudiness.

Infrastructure is operational under normal circumstances and is designed to cope with common natural disruptions such as rainfall and snow. Natural hazards can lead to severe problems at the areas where such phenomena occur, but also at neighboring regions as they can make parts of a road network virtually impassable. Landslides are one of the most devastating natural hazards worldwide, triggered by various factors that can be monitored via ground-based and/or satellite-based techniques. Cyprus is in an area of high susceptibility to such phenomena. Currently, extensive field campaigns including geotechnical drilling investigations and geophysical excavations are conducted to monitor land movements, and, at the same time, determine the geological suitability of areas. Active satellite remote sensors, namely Synthetic Aperture Radar (SAR), have been widely used for detecting and monitoring landslides and other ground deformation phenomena using Earth Observation based techniques. This paper aims to demonstrate how the use of Copernicus open-access and freely distributed datasets along with the exploitation of the open-source processing software SNAP (Sentinel’s Application Platform), provided by the European Space Agency, can be used for landslide detection, as in the case study near Pissouri, where a landslide was triggered by heavy rainfall on 15 February 2019, which caused a major disturbance to everyday commuters since the motorway connecting the cities of Limassol and Paphos remained closed for more than a month. The Coherent Change Detection (CCD) methodology was applied successfully by detecting the phenomenon under study accurately, using two indicators (the coherence difference and the normalized coherence difference). Receiver Operating Characteristic (ROC) analysis was carried out to measure their performance with the coherence difference having an overall accuracy of 93% and the normalized coherence difference having an overall accuracy of 94.8% for detecting the landslide and non-landslide areas. The probability of landslide detection was 63.2% in the case of the coherence difference and increased to 73.7% for the normalized coherence difference, whereas the probability of false alarm for both indicators was approximately 1%.