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dc.contributor.author신성원-
dc.date.accessioned2021-12-23T02:35:18Z-
dc.date.available2021-12-23T02:35:18Z-
dc.date.issued2021-03-
dc.identifier.citationREMOTE SENSING, v. 13, Issue. 5, Article no. 976, 22ppen_US
dc.identifier.issn2072-4292-
dc.identifier.urihttps://www.mdpi.com/2072-4292/13/5/976-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/166918-
dc.description.abstractCoastal hazards, such as a tsunamis and storm surges, are a critical threat to coastal communities that lead to significant loss of lives and properties. To mitigate their impact, event-driven water level changes should be properly monitored. A tide gauge is one of the conventional water level measurement sensors. Still, alternative measurement systems can be needed to compensate for the role of tide gauge for contingency (e.g., broken and absence, etc.). Global Navigation Satellite System (GNSS) is an emerging water level measurement sensor that processes multipath signals reflected by the water surface that is referred to as GNSS-Reflectometry (GNSS-R). In this study, we adopted the GNSS-R technique to monitor tsunamis and storm surges by analyzing event-driven water level changes. To detect the extreme change of water level, enhanced GNSS-R data processing methods were applied which included the utilization of multi-band GNSS signals, determination of optimal processing window, and Kalman filtering for height rate determination. The impact of coastal hazards on water level retrievals was assessed by computing the confidence level of retrieval (CLR) that was computed based on probability of dominant peak representing the roughness of the water surface. The proposed approach was validated by two tsunami events, induced by 2012 Haida Gwaii earthquake and 2015 Chile earthquake, and two storm surge events, induced by 2017 Hurricane Harvey and occurred in Alaska in 2019. The proposed method successfully retrieved the water levels during the storm surge in both cases with the high correlation coefficients with the nearby tide gauge, 0.944, 0.933, 0.987, and 0.957, respectively. In addition, CLRs of four events are distinctive to the type of coastal events. It is confirmed that the tsunami causes the CLR deduction, while for the storm surges, GNSS-R keep high CLR during the event. These results are possibly used as an indicator of each event in terms of storm surge level and tsunami arrival time. This study shows that the proposed approach of GNSS-R based water level retrieval is feasible to monitor coastal hazards that are tsunamis and storm surges, and it can be a promising tool for investigating the coastal hazards to mitigate their impact and for a better decision making.en_US
dc.language.isoen_USen_US
dc.publisherMDPIen_US
dc.subjecttsunamien_US
dc.subjectstorm surgeen_US
dc.subjectobservationen_US
dc.subjectmulti-GNSSen_US
dc.subjectGNSS-reflectometryen_US
dc.subjectnatural hazardsen_US
dc.titleFeasibility Analysis of GNSS-Reflectometry for Monitoring Coastal Hazardsen_US
dc.typeArticleen_US
dc.relation.no5-
dc.relation.volume13-
dc.identifier.doi10.3390/rs13050976-
dc.relation.page1-23-
dc.relation.journalREMOTE SENSING-
dc.contributor.googleauthorKim, Su-Kyung-
dc.contributor.googleauthorLee, Eunju-
dc.contributor.googleauthorPark, Jihye-
dc.contributor.googleauthorShin, Sungwon-
dc.relation.code2021007541-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY[E]-
dc.sector.departmentDEPARTMENT OF MARINE SCIENCE AND CONVERGENCE ENGINEERING-
dc.identifier.pidsungwshin-


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