• Journal of the Korean Geographical Society
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• v.28 no.2
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• pp.112-122
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• 1993

Since more than 50${\%}$ of annual precipitation in Korea falls during Changma, the rainy season of early summer, and Late Changma, the rainy season of late summer, forcasting the onset days Changmas, and the amount related rainfalls would be necessary not only for agriculture but also for flood-control. In this study the authors attempted to build a prediction model for the forecast of the onset date of Changmas. The onset data of each Changma was derived out of daily rainfall data of 47 stations for 30 years(1961~1990) and weather maps over East Asia. Each station represent any of the 47 districts of local forecast under the Korea Meteorological Administration. The average onset dates of Changma during the period was from 21 through 26 June. The dates show a tendency to be delayed in El Ni${\~{n}}o years while they come earlier than the average in La Nina years. In 1982, the year of El Ni${\~{n}}o, the date was 9 Julu, two weeks late compared with the average. The relation of sea surface temperature(SST) over Pacific and Northern hemispheric 500mb height to the Changma onset dates was analyzed for the prediction model by polynomial regression. The onset date of Changma over Korea was correlated with SST in May(SST${_(5)}{^\circ}$C) of the district (8${^\circ}$~12${^\circ}S, 136${^\circ}~148${^\circ}W)of equatirial middle Pacific and the 500mb height in March (MB${_(3)}$"\;"m)over the district of the notrhern Hudson Bay. The relation between this two elements can be expressed by the regression: Onset=5.888SST${_5}"\;"+"\;"0.047MB${_(3)}$"\;"-251.241. This equation explains 77${\%}$ of variances at the 0.01${\%}$ singificance level. The onset dates of Late Changma come in accordance with the degeneration of the Subtro-pical High over northern Pacific. They were 18 August in average for the period showing positive correlation(r=0.71) with SST in May(SST)${_(i5)}{^\circ}$C) over district of IndiaN Ocean near west coast of Australia (24${^\circ}$~32${^\circ}$S, 104${^\circ}$~112${^\circ}$E), but negativ e with SST in May(SST${_(p5)}{^\circ}$ over district (12${^\circ}$~20${^\circ}$S,"\;"136${^\circ}$~148${^\circ}$W)of equatorial mid Pacific (r=-0.70) and with the 500mb height over district of northwestern Siberia (r=-0.62). The prediction model for Late Changma can be expressed by the regression: Onset=706.314-0.080 MB-3.972SST${_(p5)}+3.896 SST${_(i5)}, which explains 64${\%}$ of variances at the 0.01${\%}$ singificance level.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.495-505
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• 2006

In order to classify aerosol type, Aerosol Optical Thickness (AOT) and Fine mode Fraction (FF), which is the optical thickness ratio of small particles$(<1{\mu}m)$ to total particles, data from MODIS (MODerate Imaging Spectraradiometer) aerosol products were analyzed over North-East Asia during one year period of 2005. A study area was in the ocean region of $20^{\circ}N\sim50^{\circ}N$ and $110^{\circ}E\simt50^{\circ}E$. Three main atmospheric aerosols such as dust, sea-salt, and pollution can be classified by using the relationship between AOT and FF. Dust aerosol has frequently observed over the study area with relatively high aerosol loading (AOT>0.3) of large particles (FF<0.65) and its contribution to total AOT in spring was up to 24.0%. Pollution aerosol, which is originated from anthropogenic sources as well as a natural process like biomass burning, has observed in the regime of high FF (>0.65) with wide AOT variation. Average pollution AOT was $0.31{\pm}0.05$ and its contribution to total AOT was 79.8% in summer. Characteristic of sea-salt aerosol was identified with low AOT (<0.3), almost below 0.1, and slightly higher FF than dust and lower FF than pollution. Seasonal analysis results show that maximum AOT $(0.33{\pm}0.11)$ with FF $(0.66{\pm}0.21)$ in spring and minimum AOT $(0.19{\pm}0.05)$, FF $(0.60{\pm}0.14)$ in fall were observed in the study area. Spatial characteristic was that AOT increasing trend is observed as closing to the eastern part of China due to transport of aerosols from China by the prevailing westerlies.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.337-357
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• 2021

Because the growth of paddy rice is affected by meteorological factors, the selection of appropriate meteorological variables is essential to build a rice yield prediction model. This paper examines the suitability of multiple meteorological datasets for the rice yield modeling in South Korea, 1996-2019, and a hindcast experiment for rice yield using a machine learning method by considering the nonlinear relationships between meteorological variables and the rice yield. In addition to the ASOS in-situ observations, we used CRU-JRA ver. 2.1 and ERA5 reanalysis. From the multiple meteorological datasets, we extracted the four common variables (air temperature, relative humidity, solar radiation, and precipitation) and analyzed the characteristics of each data and the associations with rice yields. CRU-JRA ver. 2.1 showed an overall agreement with the other datasets. While relative humidity had a rare relationship with rice yields, solar radiation showed a somewhat high correlation with rice yields. Using the air temperature, solar radiation, and precipitation of July, August, and September, we built a random forest model for the hindcast experiments of rice yields. The model with CRU-JRA ver. 2.1 showed the best performance with a correlation coefficient of 0.772. The solar radiation in the prediction model had the most significant importance among the variables, which is in accordance with the generic agricultural knowledge. This paper has an implication for selecting from multiple meteorological datasets for rice yield modeling.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.853-865
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• 2022

In this study, from August to October 2019, we conducted a survey of the spatial distribution and dominant species of macrobenthos on the rocky intertidal zones of 38 specified islands distributed along the southern coast of Korea. On the basis of observation made using 50 × 50 cm quadrats, we identified a total of 80 species, among which, Mollusca were the most abundant fauna, with 54 species that accounted for 67.4% of the total, followed by Crustacea with 15 species (18.7%). The recorded numbers of Cnidaria, Porifera, and Echinodermata species ranged from 1 to 6. In terms of the regional patterns of species richness, specified islands in Yeosu were found to be the most species rich, supporting 61 species, whereas islands in Hadong, Namhae, and Chujado were found to have a similar level of species richness, ranging from 42 to 46 species. Islands in Boseong and Goheung were home to the fewest species, with only 29 species being recorded. At the sampling station scale, we noted a considerable difference in faunal richness, ranging from 6 (St. 6) to 33 (St. 20) species. Among the recorded species, Echinolittorina radiata was identified as the dominant species on 15 specified islands, with the next most abundant species being Tetraclita japonica, considered an indicator species of climate change, which was recorded on 11 islands. In terms of frequency, E. radiata, found on 36 islands, was identified as the most frequently occurring species, followed by Reishia clavigera (30 islands), Mytilisepta virgata (29), Nerita japonica (28), Ligia. exotica (27), and Littorina brevicula (26). Of the 80 species identified, 9, 4, and 2 species of Mollusca, Crustacea, and Cnidaria, respectively, are classified as Marine fauna of accepted foreign export, whereas 50 are Red List species, 44 are species of Least Concern, 3 are Data Deficient species, and 1 species was not evaluated. However, during the survey, we found no Near Threatened or Not Applicable species. On the basis of the findings of this survey, it would appear that the abundance and richness of macrobenthic fauna inhabiting the rocky intertidal zones of specified islands along the southern coast of Korea differ according to different habitat conditions, particularly with respect to the duration of exposure and the extent and properties of the substrata. The findings of this study will provide baseline data for future monitoring and management of specified islands in Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.882-889
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• 2022

In this study, to understand the factors influencing the flow change the Tsushima Warm Current (TWC), the correlation between the volume transport the TWC, El Niño Southern Oscillation (ENSO), and Pacific Decadal Oscillation (PDO) was analyzed. A calculation of the monthly volume transport of TWC for 25 years (1993-2018) revealed that the seasonal fluctuation cycle was the largest in summer and smallest in winter. Power spectrum analysis to determine the periodicity of the TWC volume transport, Oceanic Niño Undex (ONI), and PDO indicated that the TWC volume transport peaked at a one year cycle, but ONI and PDO showed no clear cycle. Further, to understand the correlation between the TWC transport volume and ONI and PDO, the coherence estimation method was used for analysis. The coherence of ONI and PDO had a high mutual contribution in long-period fluctuations of three years or more but had low mutual contribution in short-period fluctuations within one year. However, the coherence value between the two factors of the TWC volume transport and PDO was 0.7 in the 0.8-1.2 year cycle, which had a high mutual contribution. Meanwhile, the TWC volume transport and PDO have an inverse correlation between period I (1993-2002) and period III (2010-2018). When the TWC maximum transport volume (2.2 Sv or more) was high, the PDO index showed a negative value below -1.0, and the PDO index showed a positive value when the TWC maximum transport volume was (below 2.2 Sv). Therefore, using long-term PDO index data, changes in the TWC transport volume and water temperature in the East Sea coastal area could be predicted.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.1-9
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• 2022

An estuary is an area where a freshwater river or stream meets the ocean. Even before the importance of the value of estuaries was recognized, the estuary was lost because of large-scale conversion by draining, filling, damming, and dredging. In South Korea, 643 estuaries are located, and the total area is 3,248,300 ha, accounting for 32.5% of the total area of South Korea. Over 35% of Korean estuaries are closed estuaries which are only temporally connected with the sea, either permanently or periodically. Since 2008, in order to preserve the estuary ecosystem and solve major issues in the estuary by accumulating knowledge about the estuarine ecosystem, the Ministry of Environment of Republic of Korea has been conducting the "Estuarine Ecosystem Monitoring and Assessment Project". At 668 sites of 325 estuaries, epilithic diatom, benthic macroinvertebrate, fish, and vegetation are investigated, and the habitat condition of each site is evaluated using the newly developed biotic index. More than 100 researchers annually record 2,097 species of estuaries according to the standardized survey guidelines over the past 14 years and provide strictly managed data necessary for establishing estuaries conservation policies. As a result of bibliometric analysis of 1,195 research articles related to the monitoring and assessment of the estuarine ecosystem, research on pollutants such as heavy metals and sediment control have recently been conducted. "Estuarine Ecosystem Monitoring and Assessment Project" is an ecological monitoring type of long-term mandated monitoring that is usually focused on identifying trends. Although it is difficult to identify the mechanism influencing a change in an ecosystem through long-term mandated monitoring, providing empirical data for supporting evidence-based policy, decision-making, and the management of ecosystems. In order to increase the efficiency of the project, research to investigate the relationship between sediments and pollutants and organisms can be conducted at specific estuaries or sites to compensate for the shortcomings of mandatory monitoring.

• Journal of the Korean earth science society
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• v.44 no.6
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• pp.643-654
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• 2023

The West Philippine Basin, an oceanic basin half the size of the Philippine Sea Plate, lies in the western part of the plate and south of the Korean Peninsula on the Eurasian Plate. It subducts beneath the Eurasian Plate and the Philippine Islands bordering the Ryukyu Trench and the Philippine Trench with 25-50% of this basin already consumed. However, the history of the opening of the basin's southern region has been a topic of debate. The non-transform discontinuity formed during the seafloor spreading is similar to the transform fault boundaries normally perpendicular to mid-ocean ridge axes; however, it was created irregularly due to ridge propagations caused by variations of mantle convection attributable to magma supply changes. By analyzing high-resolution multi-beam echo-sounding data, we confirmed that the non-transform discontinuity due to the propagating rift evolved in the entire basin and that the abyssal hill strike direction changed from E-W to NNW-SSE from the fossil spreading center. In the early stage of basin extension, the Amami-Sankaku Basin was rotated 90 degrees clockwise from its current orientation, and it bordered the Palau Basin along the Mindanao Fracture Zone. The Amami-Sankaku Basin separated from the Palau Basin while the spreading of the West Philippine Basin began with a counter-clockwise rotation. This indicates that the non-transform discontinuities formed by a sudden change in magma supply due to the drift of the Philippine Sea Plate and simultaneously with the rapid changes in the spreading direction from ENE-WSW to N-S. The Palau Basin was considered to be the sub-south of the West Philippine Basin, but recent studies have shown that it extends into an independent system. Evidence from sediment layers and crustal thickness hints at the possibility of its existence before the West Philippine Basin opened, although its evolution continues to be debated. We performed a combined analysis using high-resolution multi-beam bathymetry and satellite gravity data to uncover new insights into the evolution of the West Philippine Basin. This information illuminates the complex plate interactions and provides a crucial contribution toward understanding the opening history of the basin and the Philippine Sea Plate.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1173-1183
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• 2023

Over the past 20 years, Korea's overall import and export cargo volume has increased at an average annual rate of approximately 5.3%. About 99% of the cargo is still being transported by sea. Due to recent increases in maritime cargo volume, congestion in maritime logistics has become challenging due to factors such as the COVID-19 pandemic and conflicts. Continuous monitoring of ports has become crucial. Various ground observation systems and Automatic Identification System (AIS) data have been utilized for monitoring ports and conducting numerous preliminary studies for the efficient operation of container terminals and cargo volume prediction. However, small and developing countries' ports face difficulties in monitoring due to environmental issues and aging infrastructure compared to large ports. Recently, with the increasing utility of artificial satellites, preliminary studies have been conducted using satellite imagery for continuous maritime cargo data collection and establishing ocean monitoring systems in vast and hard-to-reach areas. This study aims to visually detect ships docked at berths in the Busan New Port using high-resolution satellite imagery and quantitatively evaluate berth utilization rates. By utilizing high-resolution satellite imagery from Compact Advanced Satellite 500-1 (CAS500-1), Korea Multi-Purpose satellite-3 (KOMPSAT-3), PlanetScope, and Sentinel-2A, ships docked within the port berths were visually detected. The berth utilization rate was calculated using the total number of ships that could be docked at the berths. The results showed variations in berth utilization rates on June 2, 2022, with values of 0.67, 0.7, and 0.59, indicating fluctuations based on the time of satellite image capture. On June 3, 2022, the value remained at 0.7, signifying a consistent berth utilization rate despite changes in ship types. A higher berth utilization rate indicates active operations at the berth. This information can assist in basic planning for new ship operation schedules, as congested berths can lead to longer waiting times for ships in anchorages, potentially resulting in increased freight rates. The duration of operations at berths can vary from several hours to several days. The results of calculating changes in ships at berths based on differences in satellite image capture times, even with a time difference of 4 minutes and 49 seconds, demonstrated variations in ship presence. With short observation intervals and the utilization of high-resolution satellite imagery, continuous monitoring within ports can be achieved. Additionally, utilizing satellite imagery to monitor changes in ships at berths in minute increments could prove useful for small and developing country ports where harbor management is not well-established, offering valuable insights and solutions.