• The Korean Journal of Air & Space Law and Policy
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• v.30 no.2
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• pp.311-336
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• 2015

This article surveys the current international law with respect to RPAS from both the public air law and private air law perspectives. It then reviews current and proposed Australian domestic RPAS regulation while emphasizing the peculiar risks in operation of RPAS; and how they affect concepts of liability, safety and privacy. While RPAS operations still constitute only a small portion of total operations within commercial aviation, international pilotless flight for commercial air transport remains a future reality. As the industry is developing so quickly the earlier the pursuit of the right policy solutions begins, the better the law will be able to cope with the technological realities when the inevitable risks manifest in accidents. The paper acknowledges that a domestic or regional approach to RPAS, typified by the legislative success of the Australian experience, is and continues to be the principal measure to deal with RPAS issues globally. Furthermore, safety remains the foremost factor in present and revised Australian RPAS regulation. This has an analogue to the international situation. Creating safety-related rules is imperative and must precede the creation or adoption of liability rules because the former mitigates the risk of accidents which trigger the application of the latter. The flipside of a lack of binding airworthiness standards for RPAS operators is potentially a strong argument that the liability regime (and particularly strict liability of operators) is unfair and unsuited to pilotless flight. The potential solutions the authors raise include the need for revised ICAO guidance and, in particular, SARPs with respect to RPAS air safety, airworthiness, and potentially liability issues for participants/passengers, and those on the ground. Such guidance could then be adapted swiftly for appropriate incorporation into domestic laws bypassing the need for or administrative burden and time it would take to activate the treaty process to deal with an arm of aviation that states know all too well is in need of safety regulation and monitoring.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.594-604
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• 2021

To evaluate the causes of beach erosion in Sinji-Myeongsasimni Beach, external forces, such as tides, tidal currents, and waves, were observed seasonally from March 2019 to March 2020, and the surface sediments were analyzed for this period. In addition, the shoreline positions and beach elevations were regularly surveyed with a VRS GPS and fixed-wing drone. From these field data, the speed of the tidal currents was noted to be insufficient, but the waves were observed to af ect the deformation of the beach. As the beach is open to the southern direction, waves of heights over 1 m were received in the S-SE direction during the spring, summer, and fall seasons. Large waves with heights over 2 m were observed during typhoons in summer and fall. Because of the absence of typhoons for the previous two years from July 2018, the beach area over datum level (DL) as of July 2018 was greater by 30,138m² compared with that of March 2019, and the beach area as of March 2020 decreased by 61,210m² compared with that of March 2019 because of four typhoon attacks after July 2018. The beach volume as of March 2019 decreased by 5.4% compared with that of July 2018 owing to two typhoons, and the beach volume as of September 2019 decreased by 7.3% because of two typhoons during the observation year. However, the volume recovered slightly by about 3% during fall and winter, when there were no high waves. According to the sediment transport vectors by GSTA, the sediments were weakly influxed from small streams located at the center of the beach; the movement vectors were not noticeable at the west beach site, but the westward sediment transport under the water and seaward vectors from the foreshore beach were prominently observed at the east beach site. These patterns of westward sediment vectors could be explained by the angle between the annual mean incident wave direction and beach opening direction. This angle was inclined 24° counterclockwise with the west-east direction. Therefore, the westward wave-induced currents developed strongly during the large-wave seasons. Hence, the sand content is high in the west-side beach but the east-side beach has been eroded seriously, where the pebbles are exposed and sand dune has decreased because of the lack of sand sources except for the soiled dunes. Therefore, it is proposed that efforts for creating new sediment sources, such as beach nourishment and reducing wave heights via submerged breakwaters, be undertaken for the eastside of the beach.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.