• Water for future
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• v.56 no.1
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• pp.50-58
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• 2023

• Journal of Wetlands Research
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• v.14 no.2
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• pp.303-315
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• 2012

This study developed a wetland inventory describing the characteristics and change of Nakdong estuary wetland ecosystem. The data which are used to develop the inventory are Landsat TM(April 1, 1986; June 23, 1987; June 18, 1997), Kompsat(Jan. 12, 2008) and LiDAR(March 1, 2009) images and published monitoring data of Busan metropolitan city. The developed inventory was utilized for the classification of wetland cover, the spatiotemporal analysis of wetland and landscape pattern, the distribution of benthos species etc. Furthermore, the developed 3 dimensional wetland map showed a better way to delineate wetland boundary and understand wetland dynamics. Considering these results, it's concluded that it is possible to use the similar techniques for the development of wetland inventory in Korea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.95-104
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• 2018

This study has the purpose of suggesting the method to analyze the spatiotemporal change of satisfaction concerning the officially assessed land price using geostatistical analysis. Analyzing the spatial distribution characteristic of officially assessed land price using present GIS (Geographic Information System) or is staying at qualitatively suggesting the improvement method of the officially assessed land price system. Grouping the appeal strength based on the official price and opinion price of officially assessed land price, GIS DB (Database) was constructed and the time seriate satisfaction were analyzed and compared through spatial density analysis and spatial autocorrelation analysis. As a result, it was found that the difference between the official price and the applicant's price differed depending on individual land, but most of the respondents requested the increase or the reduction of the average land price, which resulted in a large number of request. Analyzing the satisfaction of the officially assessed land price by using GIS, it was known that satisfaction of officially assessed land price could be analyzed by using the difference of the opinion price and not only the officially assessed land price. Spatiotemporal change of officially assessed land price satisfaction was known to be possible through spatiotemporal pattern analysis method such as spatiotemporal auto-corelation analysis and hotspot analysis etc using GIS. In short, regionally positive or negative significant relationship was investigated through spatiotemporal analysis using annual data.

• Fisheries and Aquatic Sciences
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• v.10 no.2
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• pp.74-85
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• 2007

Pacific anchovy (Engraulis japonicus) eggs were collected during the spawning season (2000-2003) using a revised ring net in the coastal waters adjacent to the Geum River Estuary in the West Sea of Korea (Yellow Sea). Anchovy eggs were present from May to September, showing a peak in spawning from June to July when the water temperature and salinity were $17-27^{\circ}C$ and above 30.00 psu, respectively. During the main spawning season, no clear diel cycle (regarding the 24-h sampling period of dusk, night, dawn, and daytime) was detected in the vertical distribution of anchovy eggs near Eocheong Island (50-60m depth). Judging from the developmental stages of the collected eggs, it appeared that anchovies spawned mostly at night and that the eggs hatched at dusk and during the night. The density of anchovy eggs was high in the southwest-northeast direction in June, and spawners appeared to move offshore in July. Mean egg density was higher in June 2002 than in June 2003 when water temperatures and salinities were lower. This study on the spatiotemporal distribution of eggs will contribute to developing management plans for the Pacific anchovy in Korea.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.119-121
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• 2008

Pattern matching is increasingly being employed in various researches as health care service, RFID-based system, facility management, and surveillance. Geosensor filter correlates a data stream to match specific patterns in distribution environments. In this paper, we present a geosensor query language to represent efficiently declarative geosensor query. Geosensor operators are proposed to use for fast query processing in terms of spatial and temporal area in distribution environments. We also propose a geosensor filter to match new query predicates into incoming stream predicates. Our filter can reduce the volume of transmission data and save power consumption of sensors. It can be utilized the stream data mining system to process in real-time various data as location, time, and geosensor information in distribution environments.

• Journal of Ginseng Research
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• v.45 no.6
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• pp.726-733
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• 2021

Background: Panax notoginseng is a highly valued medicinal herb used widely in China and many Asian countries. Its root and rhizome have long been used for the treatment of cardiovascular and hematological diseases. Imaging the spatial distributions and dynamics of metabolites in heterogeneous plant tissues is significant for characterizing the metabolic networks of Panax notoginseng, and this will also provide a highly informative approach to understand the complex molecular changes in the processing of Panax notoginseng. Methods: Here, a high-sensitive MALDI-MS imaging method was developed and adopted to visualize the spatial distributions and spatiotemporal changes of metabolites in different botanical parts of Panax notoginseng. Results: A wide spectrum of metabolites including notoginsenosides, ginsenosides, amino acids, dencichine, gluconic acid, and low-molecular-weight organic acids were imaged in Panax notoginseng rhizome and root tissues for the first time. Moreover, the spatiotemporal alterations of metabolites during the steaming of Panax notoginseng root were also characterized in this study. And, a series of metabolites such as dencichine, arginine and glutamine that changed with the steaming of Panax notoginseng were successfully screened out and imaged. Conclusion: These spatially-resolved metabolite data not only enhance our understanding of the Panax notoginseng metabolic networks, but also provide direct evidence that a serious of metabolic alterations occurred during the steaming of Panax notoginseng.

• Journal of the Korean Professional Engineers Association
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• v.44 no.2
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• pp.23-28
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• 2011

The assumption that the spatiotemporal distribution of rainfall has stationarity for a long period is not realistic due to frequent unusual weather phenomena. Based on the understanding of the situation, this paper investigates the effects of it to hydraulic structures especially dams and deals measures for it.

• Journal of Power Electronics
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• v.16 no.2
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• pp.610-620
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• 2016

The compound active clamp zero voltage soft switching (CACZVS) three-phase power factor correction (PFC) converter has many advantages, such as high efficiency, high power factor, bi-directional energy flow, and soft switching of all the switches. Triple closed-loop PI controllers are used for the three-phase power factor correction converter. The control objectives of the converter include a fast transient response, high accuracy, and unity power factor. There are six parameters of the controllers that need to be tuned in order to obtain multi-objective optimization. However, six of the parameters are mutually dependent for the objectives. This is beyond the scope of the traditional experience based PI parameters tuning method. In this paper, an improved chaotic particle swarm optimization (CPSO) method has been proposed to optimize the controller parameters. In the proposed method, multi-dimensional chaotic sequences generated by spatiotemporal chaos map are used as initial particles to get a better initial distribution and to avoid local minimums. Pareto optimal solutions are also used to avoid the weight selection difficulty of the multi-objectives. Simulation and experiment results show the effectiveness and superiority of the proposed method.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Ocean and Polar Research
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• v.33 no.4
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• pp.421-434
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• 2011

Although thermal effluent from coastal power plants affects marine ecosystems, few studies have examined the spatiotemporal distribution of macrobenthic communities in a coastal area of Korea with thermal discharge. This study analyzed the species composition and abundance of a macrobenthic community in relation to environmental variables for a period of 1 year. In total 334 macrobenthic faunal species were collected; the mean density was 3,221 ind/$m^2$. The number of species and the density of macrobenthic fauna increased with distance from the thermal discharge site. Cluster analysis indicated that the macrobenthic community could be divided into two groups: group I in shallow (< 30 m deep) and group II in the outer areas (> 30 m deep). Group I showed the lowest species density and diversity. Four polychaetes, including Magelona japonica, Spiophanes bombyx, Scolotoma longifolia and Chaetozone setosa, all of which have been dominant species since 1987, exhibited higher mean densities in the area distant from the thermal discharge (the outer and north areas). Conversely, the warm-adapted and opportunistic species, such as the amphipods Urothoe convexa and Mandibulophoxus mai, the bivalve Felaniella sowerbyi, and the polychaete Rhynchospio sp., were more abundant in the thermal discharge region. The results of this study indicate that thermal effluent influences macrobenthic communities in the shallow area, while other environmental variables, such as depth, sediment grain size, and TOC, are more important determinants of the macrobenthic communities in deeper regions (> 30 m deep).