• Economic and Environmental Geology
• /
• v.49 no.4
• /
• pp.281-290
• /
• 2016

Coastal areas, used as human utilization areas like leisure space, medical care, ports and power plants, etc., are regions that are continuously changing and interconnected with oceans and land. Regular monitoring of coastal changes is essential at key locations with such volatility. But the survey method of terrestial LiDAR(Light Detection and Ranging) system has much time consuming and many restrictions. For effective monitoring coastal changes, KIOST(Korea Institute of Ocean Science & Technology) has constructed a shipborne mobile LiDAR system. The shipborne mobile LiDAR system, installed in a research vessel, comprised a land based LiDAR(RIEGL LMS-420i), an IMU(MAGUS Inertial+), a RTKGNSS(LEICA GS15 GS25), and a fixed platform. The shipborne mobile LiDAR system is much more effective than a land based LiDAR system in the measuring of fore shore areas without shadow zone. Because the vessel with the shipborne mobile LiDAR system is continuously moved along the shoreline, it is possible to efficiently survey a large area in a relatively short time. We conducted test measurements in the Anmok-Songjung beach around the Gangneung port. Effective monitoring of the changes using the constructed shipborne mobile LiDAR system for seriously eroded coastal areas will be able to contribute to coastal erosion management and response.

• Journal of Internet Computing and Services
• /
• v.22 no.6
• /
• pp.25-32
• /
• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_1
• /
• pp.869-877
• /
• 2018

The area of desert in East Asia is increasing every year, and it cause a great cost of social damage. Because desert is widely distributed and it is difficult to approach people, remote sensing using satellites is commonly used. But the study of desert area comparison is insufficient which is calculated by satellite sensor. It is important to recognize the characteristics of the desert area data that are calculated for each sensor because the desert area calculated according to the selection of the sensor may be different and may affect the climate prediction and desertification prevention measures. In this study, the desert area of Northeast Asia in 2001-2013 was calculated and compared using Moderate Resolution Imaging Spectroradiometer (MODIS) and Vegetation. As a result of the comparison, the desert area of Vegetation increased by $3,020km^2/year$, while in the case of MODIS, it decreased by $20,911km^2/year$. We performed indirect validation because It is difficult to obtain actual data. We analyzed the correlation with the occurrence frequency of Asian dust affected by desert area change. As a result, MODIS showed a relatively low correlation with R = 0.2071 and Vegetation had a relatively high correlation with R = 0.4837. It is considered that Vegetation performed more accurate desert area calculation in Northeast Asian desert area.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.21 no.1
• /
• pp.1-10
• /
• 2016

Currently available surface seawater partial pressure carbon dioxide ($pCO_2$) data sets in the East Sea are not enough to quantify statistically the carbon dioxide flux through the air-sea interface. To complement the scarcity of the $pCO_2$ measurements, we construct a neural network (NN) model based on satellite data to map $pCO_2$ for the areas, which were not observed. The NN model is constructed for the Ulleung Basin, where $pCO_2$ data are best available, to map and estimate the variability of $pCO_2$ based on in situ $pCO_2$ for the years from 2003 to 2012, and the sea surface temperature (SST) and chlorophyll data from the MODIS (Moderate-resolution Imaging Spectroradiometer) sensor of the Aqua satellite along with geographic information. The NN model was trained to achieve higher than 95% of a correlation between in situ and predicted $pCO_2$ values. The RMSE (root mean square error) of the NN model output was $19.2{\mu}atm$ and much less than the variability of in situ $pCO_2$. The variability of $pCO_2$ with respect to SST and chlorophyll shows a strong negative correlation with SST than chlorophyll. As SST decreases the variability of $pCO_2$ increases. When SST is lower than $15^{\circ}C$, $pCO_2$ variability is clearly affected by both SST and chlorophyll. In contrast when SST is higher than $15^{\circ}C$, the variability of $pCO_2$ is less sensitive to changes in SST and chlorophyll. The mean rate of the annual $pCO_2$ increase estimated by the NN model output in the Ulleung Basin is $0.8{\mu}atm\;yr^{-1}$ from 2003 to 2014. As NN model can successfully map $pCO_2$ data for the whole study area with a higher resolution and less RMSE compared to the previous studies, the NN model can be a potentially useful tool for the understanding of the carbon cycle in the East Sea, where accessibility is limited by the international affairs.

• Journal of the Korean earth science society
• /
• v.40 no.5
• /
• pp.447-463
• /
• 2019

Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.

• Korean Journal of Ecology and Environment
• /
• v.54 no.4
• /
• pp.272-279
• /
• 2021

A pump-type eDNA filtering system that can control voltage and hydraulic pressure respectively has been developed, and applied a filter case that can filter out without damaging the filter. The filtering performance of the developed system was evaluated by comparing the eDNA concentration with the conventional vacuum-pressured filtering method at the catchment conduit intake reservoir. The developed system was divided into a voltage control (manual pump system) method and a pressure control (automatic pump system) method, and the pressure was measured during filtering and the pressure change of each system was compared. The voltage control method started with 65 [KPa] at the beginning of the filtering, and as the filtering time elapsed, the amount of filtrate accumulated in the filter increased, so the pressure gradually increased. As a result of controlling the pressure control method to maintain a constant pressure according to the designed algorithm, there was a difference in the width of the hydraulic pressure fluctuation during the filtering process according to the feedback time of the hydraulic pressure sensor, and it was confirmed that the pressure was converged to the target pressure. The filtering performance of the developed system was confirmed by measuring the eDNA concentration and comparing the voltage control method and the hydraulic control method with the control group. The voltage control method obtained similar results to the control group, but the hydraulic control method showed lower results than the control group. It is considered that the low eDNA concentration in the hydraulic control method is due to the large pressure deviation during filtering and maintaining a constant pressure during the filtering process. Therefore, rather than maintaining a constant pressure during filtering, it was confirmed that a voltage control method in which the pressure is gradually increased as the filtrate increases with the lapse of filtering time is suitable for collecting eDNA. As a result of comparing the average concentration of eDNA in lentic zone and lotic zone as a control group, it was found to be 96.2 [ng µL^-1] and 88.4 [ng µL^-1l], respectively. The result of comparing the average concentration of eDNA by the pump method was also high in the lentic zone sample as 90.7 [ng µL^-1] and 74.8 [ng µL^-1] in the lentic zone and the lotic zone, respectively. The high eDNA concentration in the lentic zone is thought to be due to the influence of microorganisms including the remaining eDNA.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.1
• /
• pp.39-46
• /
• 2010

Sounding data is the essential source for the safety of ships navigation system, and fundamental to the reasonable usage and maintenance of the ocean as well. As IT tech, positioning equipment such as GPS and INS, echo sounder are developed, recently, the precise submarine topography database bas been built by Multi-Beam Echo Sounder. However, MBES data includes some inevitable error caused by several factor, and some data have errors where the terrain is wobble. The error, which causes the $moir\acute{e}$ pattern error is the main factor hindering the accuracy of MBES data results, and therefore it is necessary to figure out the main cause of the error for the improvement of the accuracy by removing error data. On this research, the main cause of the error data is studied by analyzing motion sensor value of data including the $moir\acute{e}$ pattern error. Thus, as the result of examination, it turns out that the $moir\acute{e}$ pattern error is related to the standard deviation of Roll, and error data values are results of the non-correspondence between Swath data and Roll values caused by the drastic change of Roll values. Accordingly, the error data is removed by comparing between the gradient of Swath data and Roll values. Finally, as the result of removing error data, it is expected to be able to estimate the quality of MBES using the standard deviation of Motion sensor's Roll value, and calculate the additive error factor, which minimize non-corresponding data, and also this research must be contributed to improve the accuracy of sounding for small vessels with lots of motion in the bad circumstance for navigation.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.39 no.9
• /
• pp.871-877
• /
• 2015

Deep-sea equipment such as underwater robots and unmanned submersible vehicles, include various machine components and sensors, and it is important that their reliabilities be tested before use in the fields. This is necessary because they are affected by complex extreme-environment conditions, such as high pressures, extreme temperatures, and tidal forces that are present in the deep sea. We require test equipment that can conduct empirical tests in conditions that mimic these complex oceanic environments. In this study, we propose specifications that should be met, and a design plan for the primary components, which should limit their use to a maximum water pressure of 2.0 MPa, water temperature of $5{\sim}60^{\circ}C$, and a maximum flow velocity of 2 m/s. in work-in type underwater combined environment test equipment and. We present test system development procedures to verify the reliability of products and systems used in deep-sea environments.

• Korean Journal of Remote Sensing
• /
• v.28 no.4
• /
• pp.421-434
• /
• 2012

Colored Dissolved Organic Matter (CDOM) is one of the important components of optical properties of seawater to determine ecosystem dynamics in a given marine area. The optical characteristics of CDOM may depend on the various ecosystem and environmental variables in the sea and those variables may vary region to region. Therefore, the retrieval algorithm for determining light absorption coefficient of CDOM ($a_{CDOM}$) using satellite remote sensing reflectance ($R_{rs}$) developed from other region may not be directly applicable to the other region, and it must be validated using an in-situ ground-truth observation. We have tested 6 known CDOM algorithms (three Semi-analytical and three Empirical CDOM algorithms) developed from other regions of the world ocean with laboratory determined in-situ values for the East Sea using field data collected during seven oceanographic cruises in the period of 2009~2011. Our field measurements extended from the coastal waters to the open oceanic type CASE-1 Waters. Our study showed that Quasi-Analytical Algorithm (QAA_v5) derived $a_{CDOM}$(412) appears to match in-situ $a_{CDOM}$(412) values statistically. Semi-analytical algorithms appeared to underestimate and empirical ones overestimated $a_{CDOM}$ in the East Sea. $a_{CDOM}$(412) value was found to be relatively high in the relatively high satellite derived-chlorophyll-a area. $a_{CDOM}$(412) value appears to be influenced by the amount of chlorophyll-a in seawater. The outcome of this work may be referenced to develop $a_{CDOM}$ algorithm for the new Korean Geostationary Ocean Color Imager (GOCI).

• Journal of the Korean earth science society
• /
• v.35 no.1
• /
• pp.19-28
• /
• 2014

The radiative transfer for TIROS operational vertical sounder (RTTOV) and the community radiative transfer model (CRTM) are two fast radiative transfer models (RTM) that are used as observation operators in numerical weather prediction (NWP) systems. This study compares the basic structure and input data of the two models. With data from Advanced Microwave Sounding Unit-A (AMSU-A), which has channels of various frequencies, observed brightness temperature ($T_B$) and simulated $T_B$s from the two models are compared over the ocean surface in two cases-one where cloud information is included and the other without it. Regarding AMSU-A sounding channels (5-14), the two models produce no large significant differences in their calculated $T_B$, but RTTOV produces smaller first guess (FG) departures (i.e., better results) in window and near-surface sounding channels than does CRTM. When adding cloud water and ice particles from Unified Model (UM), the $T_B$ bias between observations and simulations are reduced in both models and the bias at 31.4 and 89 GHz is substantially decreased in CRTM compared to those of RTTOV.