4S (Ship to Ship, Ship to Shore) communication is the key to strategic development of e-navigation, a core element of IT vessel convergence. 4S communication is intended to integrate and standardize various communication infrastructures on land and communication equipment complying with communication equipment equipped in ships. This paper aims to apply the Korean technology IEEE 802.16e adopted as an international standard, to replace and compensate for existing vessel communication media such as low speed HF/MF/VHF to the ocean environment. To this end, various experimental conditions between the coast station where a relay station was installed and related equipment equipped on a ship are set. Communication signals were monitored and the RSSI and CINR were measured. Based on experimental analysis and results, various challenges and solutions which may occur in ocean environment were sought, and communication availability was analyzed through transmission data throughput, at the maximum effective distance range of the signal. It was proven that high speed multimedia data could be exchanged for up to 20 km even among 80km kph ships moving around near the sea, ensuring that this technology could be applied to the ocean environment.
Journal of the Korean Society for Marine Environment & Energy
/
v.13
no.3
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pp.198-205
/
2010
The purpose of this study is to investigate the characteristics of the grain size distribution and organic matters to understand the current status of the tidal flat sediment for efficient management of Suncheon Bay. We investigated the characteristics of the surface sediments in the mouth area of the Suncheon Bay at fifteen stations in April and July, 2009. Specific conclusions were as follows. The sediments in the most part of tidal flat was shown as muddy facies(clay and silt contents was more than 90%), whereas in the tidal river affected by water flow from the Dongstream was shown as sandy facies. The analyzed values of the tidal flat sediment were in the range of $1.9{\sim}3.8{\phi}$(mean $2.5{\phi}$) for sorting, and -1.5~3.2(mean -0.3) for skewness, and 1.5~14.1(mean 3.9) for kurtosis. So we knew that the tidal flat sediments in the Suncheon Bay was mainly composed by fine-grained sediment. Erosion was happened in the tidal river, whereas sedimentation was occurred in the tidal flat. The most of organic matters was derived from the Dongstream. Total organic matters shown as ignition loss was 5.75%, COD and $H_2S$ values were lower than the eutrophication level(COD; 20.0 mg/g dry, $H_2S$; 0.2 mg S/g dry). From our research the tidal flat of the Suncheon Bay is relatively fine, but a part of the flat was exceed the environmental standard. So we have to establish effective countermeasures to reduce the organic matters and nutrients derived from stream for environmental preservation of the Suncheon bay and conduct scientifically sustainable monitering for streams flowing into Suncheon Bay and tidal flat.
Seoje, Jeong;Wookeen, Chung;Sungryul, Shin;Sumin, Kim
Geophysics and Geophysical Exploration
/
v.25
no.4
/
pp.214-216
/
2022
Distributed acoustic sensing (DAS), an increasingly growing acquisition technique in the oil and gas exploration and seismology fields, has been used to record seismic signals using optical cables as receivers. With the development of imaging methods for DAS data, full waveform inversion (FWI) is been applied to DAS data to obtain high-resolution property models such as P- and S-velocity. However, because the DAS systems measure strain from the phase distortion between two points along optical cables, DAS data must be transformed from strain to particle velocity for FWI algorithms. In this study, a plane-wave FWI algorithm based on the relationship between strain and horizontal particle velocity in the plane-wave assumption is proposed to apply FWI to DAS data. Under the plane-wave assumption, strain equals the horizontal particle velocity, which is scaled by the velocity at the receiver position. This relationship was confirmed using a numerical experiment. Furthermore, 4-layer and modified Marmousi-2 velocity models were used to verify the applicability of the proposed FWI algorithm in various survey environments. The proposed FWI was implemented in land and marine survey environments and provided high-resolution P- and S-velocity models.
Noh, Hyoseob;Kim, Byunguk;Lee, Minjae;Park, Yong Sung;Bang, Ki Young;Yoo, Hojun
Journal of Korea Water Resources Association
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v.56
no.spc1
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pp.1027-1036
/
2023
Coastal topographic information is crucial in coastal management, but point measurment based approeaches, which are labor intensive, are generally applied to land and underwater, separately. This study introduces an efficient method enabling land and undetwater surveys using an unmanned aerial vehicle (UAV). This method involves applying two different algorithms to measure the topography on land and water depth, respectively, using UAV imagery and merge them to reconstruct whole coastal digital elevation model. Acquisition of the landside terrain is achieved using the Structure-from-Motion Multi-View Stereo technique with spatial scan imagery. Independently, underwater bathymetry is retrieved by employing a depth inversion technique with a drone-acquired wave field video. After merging the two digital elevation models into a local coordinate, interpolation is performed for areas where terrain measurement is not feasible, ultimately obtaining a continuous nearshore terrain. We applied the proposed survey technique to Jangsa Beach, South Korea, and verified that detailed terrain characteristics, such as berm, can be measured. The proposed UAV-based survey method has significant efficiency in terms of time, cost, and safety compared to existing methods.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.15
no.4
/
pp.192-202
/
2010
Submarine groundwater discharge (SGD) has been recognized as a provider for freshwater, nutrients, and dissolved constituents from continents to the oceans and paid more attention with regard to the mass balance of water or dissolved constituents on local and global scales. The submarine discharge of fresh groundwater (fresh SGD) through seepage or springs in coastal ocean may be especially important in aspects of water resource and marine environment managements in the future. Based on the worldwide compilations of observed fresh SGD, our review reveals that fresh SGD occurs in various marine environments along most shoreline of the world and the global estimates of fresh SGD were approximately 0.01-17% of surface runoff. In addition, the input of fresh SGD calculated and investigated in this study were about 50%, 57%, 89%, and 420% of total river discharge in Jeju Island, Yeongil Bay, Masan Bay, and Yeoja Bay, respectively. These inputs from fresh SGD along the shoreline of Korea Peninsula are much higher than those of the whole world, greatly vary with the region. However, since these estimates are based on the water balance method mainly used in coastal ocean, we have to perform continuous monitoring of various parameters, such as precipitation, tide, evapotanspiration and water residence time, which have an impact on the water balance in a lot of areas for evaluating the precise input of fresh SGD. In addition, since the method estimating the input of fresh SGD has brought up many problems, it is required to make an intercomparison between various methods such as hydrogeological assumption, numerical modeling, and seepage meter.
In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.
NASA MODIS GPP provides a useful tool to monitor global terrestrial vegetation productivity. Two major problems of NASA GPP in regional applications are coarse spatial resolution ($1.25^{\circ}{\times}1^{\circ}$) of DAO meteorological data and cloud contamination of MODIS FPAR product. In this study, we improved the NASA GPP by using enhanced input data of high spatial resolution (3 km${\times}$3 km) WRF meteorological data and cloud-corrected FPAR over the North Korea. The improved GPP was utilized to investigate characteristics of GPP interannual variation and spatial patterns from 2000 to 2008. The GPP varied from 645 to 863 $gC\;m^{-2}\;y^{-1}$ in 2000 and 2008, respectively. Mixed forest showed the highest GPP (1,076 $gC\;m^{-2}\;y^{-1}$). Compared to NASA GPP (790 $gC\;m^{-2}\;y^{-1}$);FPAR enhancement increased GPP (861) but utilization of WRF data decreased GPP (710). Enhancements of both FPAR and meteorological input resulted in GPP increase (809) and the improvement was the greatest for mixed forest regions (+10.2%). The improved GPP showed better spatial heterogeneity reflecting local topography due to high resolution WRF data. It is remarkable that the improved and NASA GPPs showed distinctly different interannual variations with each other. Our study indicates improvement of NASA GPP by enhancing input variables is necessary to monitor region-scale terrestrial vegetation productivity.
Journal of the Korean Society of Marine Environment & Safety
/
v.14
no.2
/
pp.163-168
/
2008
Ship detection from satellite remote sensing is a crucial application for global monitoring for the purpose of protecting the marine environment and ensuring marine security. It permits to monitor sea traffic including fisheries, and to associate ships with oil discharge. An automatic ship detection approach for RADARSAT Fine Synthetic Aperture Radar (SAR) image is described and assessed using in situ ship validation information collected during field experiments conducted on August 6, 2004. Ship detection algorithms developed here consist of five stages: calibration, land masking, prescreening, point positioning, and discrimination. The fine image was acquired of Ulsan Port, located in southeast Korea, and during the acquisition, wind speeds between 0 m/s and 0.4 m/s were reported. The detection approach is applied to anchoring ships in the anchorage area of the port and its results are compared with validation data based on Vessel Traffic Service (VTS) radar. Our analysis for anchoring ships, above 68 m in length (LOA), indicates a 100% ship detection rate for the RADARSAT single beam mode. It is shown that the ship detection performance of SAR for smaller ships like barge could be higher than the land-based radar. The proposed method is also applied to estimate the ship's dimensions of length and breadth from SAR radar cross section(RCS), but those values were comparatively higher than the actual sizes because of layover and shadow effects of SAR.
This study was carried out to examine the changes in vascular flora in the first and second surveys targeting 32 outstanding forest wetlands in Jeonnam area including Gwangju metropolitan city, and based on this, establish a future monitoring system and effectively manage the excellent forest wetlands. The survey investigated the area seasonally every 4-5 years from 2015 to 2021. The change of flora of 32 excellent forest wetlands in Jeollanam-do increased from 103 families, 311 genera, 496 species, 16 subspecies, 38 varieties, 6 varieties, 556 taxa, to 111 families, 362 genera, 599 species, 16 subspecies, 51 varieties, 8 varieties, 674 taxa. Remarkable plants such as Red list and plants endemic to the Korean Peninsula increased also. However, Nepeta cataria and the like are exterminated locally, so an in situ and ex situ conservation strategy must be established. In the case of plants categorized according to wetland preference, the distribution ratio of such wetland plants slightly decreased and the distribution ratio of such terrestrial plants lightly increased for absolute wetland plants. It is necessary to prepare countermeasures for the terrestrialization of forest wetlands and to develop research techniques that can distinguish boundaries. In addition, the forest wetland should be systematically managed and supervised by designating it as a Forest Genetic Resources Reserve that can effectively conserve it.
Suho Bak;Seon Woong Jang;Heung-Min Kim;Tak-Young Kim;Geon Hui Ye
Korean Journal of Remote Sensing
/
v.39
no.2
/
pp.193-205
/
2023
A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.
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