• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.632-645
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• 2021

Satellite sea surface temperature (SST) composites provide important data for numerical forecasting models and for research on global warming and climate change. In this study, six types of representative SST composite database were collected from 2007 to 2018 and the characteristics of spatial structures of SSTs were analyzed in seas around the Korean Peninsula. The SST composite data were compared with time series of in-situ measurements from ocean meteorological buoys of the Korea Meteorological Administration by analyzing the maximum value of the errors and its occurrence time at each buoy station. High differences between the SST data and in-situ measurements were detected in the western coastal stations, in particular Deokjeokdo and Chilbaldo, with a dominant annual or semi-annual cycle. In Pohang buoy, a high SST difference was observed in the summer of 2013, when cold water appeared in the surface layer due to strong upwelling. As a result of spectrum analysis of the time series SST data, daily satellite SSTs showed similar spectral energy from in-situ measurements at periods longer than one month approximately. On the other hand, the difference of spectral energy between the satellite SSTs and in-situ temperature tended to magnify as the temporal frequency increased. This suggests a possibility that satellite SST composite data may not adequately express the temporal variability of SST in the near-coastal area. The fronts from satellite SST images revealed the differences among the SST databases in terms of spatial structure and magnitude of the oceanic fronts. The spatial scale expressed by the SST composite field was investigated through spatial spectral analysis. As a result, the high-resolution SST composite images expressed the spatial structures of mesoscale ocean phenomena better than other low-resolution SST images. Therefore, in order to express the actual mesoscale ocean phenomenon in more detail, it is necessary to develop more advanced techniques for producing the SST composites.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1043-1060
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• 2023

An acceleration of climate change in recent years has led to increased attention towards 'blue carbon' which refers to the carbon captured by the ocean. However, our comprehension of marine ecosystems is still incomplete. This study classified and analyzed global marine eco-provinces using k-means clustering considering carbon cycling. We utilized five input variables during the past 20 years (2001-2020): Carbon-based Productivity Model (CbPM) Net Primary Production (NPP), particulate inorganic and organic carbon (PIC and POC), sea surface salinity (SSS), and sea surface temperature (SST). A total of nine eco-provinces were classified through an optimization process, and the spatial distribution and environmental characteristics of each province were analyzed. Among them, five provinces showed characteristics of open oceans, while four provinces reflected characteristics of coastal and high-latitude regions. Furthermore, a qualitative comparison was conducted with previous studies regarding marine ecological zones to provide a detailed analysis of the features of nine eco-provinces considering carbon cycling. Finally, we examined the changes in nine eco-provinces for four periods in the past (2001-2005, 2006-2010, 2011-2015, and 2016-2020). Rapid changes in coastal ecosystems were observed, and especially, significant decreases in the eco-provinces having higher productivity by large freshwater inflow were identified. Our findings can serve as valuable reference material for marine ecosystem classification and coastal management, with consideration of carbon cycling and ongoing climate changes. The findings can also be employed in the development of guidelines for the systematic management of vulnerable coastal regions to climate change.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.1
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• pp.63-69
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• 2008

It has an important meaning that the maintenance and management of facility for a onshore construction shall be damaged by oceanic environment. A movement and displacement of these shall be investigated by up-to-date machinery tools like GPS and Lidar and MBES & Gyro. In current a lot of tools and methods for investigation shall be used as a displacement and movement on land mainly. For underwater facility it is very difficult to check because of special conditions below the water surface. In this study, a surveying methods for a movement and displacement of underwater facility as caisson shall be used, i.e. multibeam-echo-sounding system. A possibility as basic data for displacement and environmental monitoring shall be studied by MBES to acquire a caisson's inclination.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.232-235
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• 2006

해저 해빈모래가 다량 유실되어 이 지역의 장기관리를 위해 침식구간에 대한 지속적인 모니터링 작업이 필요하다. 그러나 각 구청은 지형변화 분석 작업 없이, 양빈작업에 급급하고 있어 장기효과가 나타나지 않고 있다. 그러므로 본 연구는 수심측량 및 GPS 측량을 통해 해저 해빈지대의 정확한 공간자료를 구축, RS GIS 기법을 도입하여 지형변화를 정량 정성적으로 탐지 분석하였다. 연구 결과, 해운대 해저지형은 과도한 도시개발과 하천복개공사로 지난 25년간, 평균수심 0.40m, 수표면적 $11,028m^2$, 수중체적 $2,207,884m^3$ 가량 침식되었다. 해빈지형은 지난 5년간, 평균고도 0.27m, 총면적 $6,501m^2$, 총체적 $25,667m^3$ 가량 퇴적되었다. 이의 원인은 지오그리드의 설치로 해빈모래가 서측까지 도달하지 못하고, 계절영향으로 사료된다. 본 연구는 해저 해빈지형의 정확한 측량작업으로 해안 및 지형변화에 관한 모니터링 작업을 실시하여 연안침식 현황을 분석하고, 양빈작업 및 안전한 해양레저 활동, 해수욕장 관리에 필요한 정보를 제공할 수 있을 것으로 판단된다.

• Spatial Information Research
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• v.19 no.2
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• pp.19-28
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• 2011

Three dimensional modeling for seafloor topography is essential to monitoring displacements in underwater structures as well as all sorts of disasters along the shore. MBES is a system that is capable of high-density water depth measurement for seafloor topography and is in broad uses for gathering 3D data and detecting displacements. MBES data, however, contain random errors that take place in the equipment offset and surveying process and require systematic researches on the correction of wrong depth measurements. Thus this study set out to propose a post-processing technique to eliminate an array of random errors taking place after equipment offset correction and basic noise correction in the MBES system and analyze its applicability to seafloor topography modeling by applying it to the subject area.

• Spatial Information Research
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• v.17 no.3
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• pp.341-350
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• 2009

As the power and scale of typhoons are growing due to global warming and socioeconomic damages induced by super-typhoons are increasing, it is important to estimate inundation damages and to prepare proper adaptation plans against an attack of the super-typhoon. In this paper, we estimated the inundation damages of urban area around Haeundae beach induced by super-typhoons which follow the route of Typhoon Maemi with the conditions of Typhoon Vera (Ise Bay in Japan, 1959), Typhoon Durian (Philippine, 2006) and Hurricane Katrina (New Oleans in U.S.A, 2005). The coastal area around the Haeundae beach (Busan and Gyeongnam province) is expectedly damaged by severe storm surges. In this study we calculated the rise of sea level height after harmonizing the different datum levels of land and ocean and estimated the inundation depth, inundation area and the amount of building damages by using airborne LiDAR data and GIS spatial analysis techniques more accurately and quantitatively. As many researchers are predicting that super-typhoon of overwhelming power will occur around the Korean peninsula in the near future, the results of this study are expected to contribute to producing coastal inundation map and evacuation planning.

• Korean Journal of Optics and Photonics
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• v.26 no.3
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• pp.155-161
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• 2015

We report the design and performance analysis of an off-axis three-mirror telescope as the fore optics for a new hyperspectral sensor aboard a small unmanned aerial vehicle (UAV), for low-altitude coastal remote sensing. The sensor needs to have at least 4 cm of spatial resolution at an operating altitude of 500 m, $4^{\circ}$ field of view (FOV), and a signal to noise ratio (SNR) of 100 at 660 nm. For these performance requirements, the sensor's optical design has an entrance pupil diameter of 70 mm and an F-ratio of 5.0. The fore optics is a three-mirror system, including aspheric primary and secondary mirrors. The optical performance is expected to reach $1/15{\lambda}$ in RMS wavefront error and 0.75 in MTF value at 660 nm. Considering the manufacturing and assembling phase, we determined the alignment compensation due to the tertiary mirror from the sensitivity, and derived the tilt-tolerance range to be 0.17 mrad. The off-axis three-mirror telescope, which has better performance than the fore optics of other hyperspectral sensors and is fitted for a small UAV, will contribute to ocean remote-sensing research.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.555-567
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• 2018

In order to identify the characteristics of sea surface temperature (SST) differences between microwave SST from GCOM-W1/AMSR2 and in-situ measurements in the western coast of Korea, a total of 6,457 collocated matchup data were produced using the in-situ temperature measurements from marine buoy stations (Deokjeokdo, Chilbaldo, and Oeyeondo) from July 2012 to December 2017. The accuracy of satellite microwave SSTs was presented by comparing the ocean buoy data of Deokjeokdo, Chilbaldo, and Oeyeondo stations with the AMSR2 SST data more than five years. The SST differences between the microwave SST and the in-situ temperature measurements showed some dependence on environmental factors, such as wind speed and water temperature. The AMSR2 SSTs were tended to be higher than the in-situ temperature measurements during the daytime when the wind speed was low ($<6ms^{-1}$). On the other hand, they showed positive deviation increasingly as the wind speed increased for nighttime. In addition, increasing tendency of SST differences was related to decreasing sensitivity of microwave sensors at low temperatures and data contamination by land. A monthly analysis of the SST difference showed that unlike the previous trend, which was known to be the largest in winter when strong winds were blowing, the SST difference was largest in summer in Deokjeokdo and Chilbaldo buoy stations. This seemed to be induced by differential tidal mixing at the collocated matchup points. This study presented problems and limitations of the use of microwave SSTs with high contribution to the SST composites in the western coastal region off the Korean peninsula.