The fragmentation of high-density polyethylene (HDPE) films from single-use supermarket plastic bags to microplastics under laboratory-simulated onshore and nearshore conditions was investigated for a period of 6 months. The weathering process of the plastic strips either on beach sand or in seawater under direct natural sunlight was monitored by tensile strength, molecular weight measurements, FTIR, weight loss, and image processing of photographs of the plastic strips before and after mild mechanical stress was applied. The latter represents a novel method proposed for determining the onset of fragmentation through the application of mild mechanical stress on the weathered plastic samples emulating the action of sand and wind on a beach. It was found that 12 h of application of mild mechanical stress in rotating glass bottles filled partially with sand was sufficient time to reach the maximum degree of fragmentation that could occur for the weathered plastics samples being tested. For example, applied mechanical stress yielded an area loss of almost 14% for samples weathered for a period of 5 months and about 16.7% after 5.5 months. While tensile strength tests and molecular weight measurements were rather inconclusive till the very last month when the onset of fragmentation was identified; FTIR measurements revealed that samples under ultraviolet irradiation were gradually modified chemically until fragmentation commenced. After 6 months of weathering, molecular weight measurements showed a 60% reduction for sample SMB-1 whereas for sample SMB-2 the measurement was not possible due to extensive fragmentation. The onset of fragmentation for SMB-1 and SMB-2 samples occurred at a cumulative luminance of 5.3 × 10 6 lux•d and in the presence of atmospheric oxygen whereby the polymer films broke down partially to microplastics. When the UV exposure reached 7.2 × 10 6 lux•d the weathered plastic strips broke down fully to microplastics with the application of a mild mechanical stress. Samples placed in seawater proved to be resistant to fragmentation compared to those on sand over the 6-month period of the weathering experiment. The direct implication of this work is that beached macroplastic debris should be regularly collected from the seashore before they are weathered by sunlight and returned to the sea as microplastics by the action of high waves or strong winds.

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Being able to quantify land cover changes due to mining and reclamation at a watershed scale is of critical importance in managing and assessing their potential impacts to the Earth system. In this study, a remote sensing-based methodology is proposed for quantifying the impact of surface mining activity and reclamation from a watershed to local scale. The method is based on a Support Vector Machines (SVMs) classifier combined with multi-temporal change detection of Landsat TM imagery. The performance of the technique was evaluated at selected open mining sites located in the island of Milos in Greece. Assessment of the mining impact in the studied areas was based on the confusion matrix statistics, supported by co-orbital QuickBird-2 very high spatial resolution imagery. Overall classification accuracy of the thematic land cover maps produced was reported over 90%. Our analysis showed expansion of mining activity throughout the whole 23-year study period, while the transition of mining areas to soil and vegetation was evident in varying rates. Our results evidenced the ability of the method under investigation in deriving highly and accurate land cover change maps, able to identify the mining areas as well as those in which excavation was replaced by natural vegetation. All in all, the proposed technique showed considerable promise towards the support of a sustainable environmental development and prudent resource management.Peer reviewe

Nowadays, various unmanned aerial vehicle (UAV) applications become increasingly demanding since they require real-time, autonomous and intelligent functions. Towards this end, in the present study, a fully autonomous UAV scenario is implemented, including the tasks of area scanning, target recognition, geo-location, monitoring, following and finally landing on a high speed moving platform. The underlying methodology includes AprilTag target identification through Graphics Processing Unit (GPU) parallelized processing, image processing and several optimized locations and approach algorithms employing gimbal movement, Global Navigation Satellite System (GNSS) readings and UAV navigation. For the experimentation, a commercial and a custom made quad-copter prototype were used, portraying a high and a low-computational embedded platform alternative. Among the successful targeting and follow procedures, it is shown that the landing approach can be successfully performed even under high platform speeds.

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