• Proceedings of the Korean Society of Life Science Conference
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• 2008.10a
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• pp.45.2-45.2
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• 2008

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.665-673
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• 2010

The role of remote sensing in phenological studies is increasingly regarded as a key in understanding large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for vegetation classification using seasonal variation patterns. The vegetation seasonal variation phase of Seoul and provinces in Korea was inferred using 8 day composite MODIS NDVI (Normalized Difference Vegetation Index) dataset of 2006. The seasonal vegetation classification approach is performed with reclassification of 4 categories as urban, crop land, broad-leaf and needle-leaf forest area. The BISE (Best Index Slope Extraction) filtering algorithm was applied for a smoothing processing of MODIS NDVI time series data and fuzzy classification method was used for vegetation classification. The overall accuracy of classification was 77.5% and the kappa coefficient was 0.61%, thus suggesting overall high classification accuracy.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.46 no.2
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• pp.216-222
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• 2013

The seasonal distribution and abundance of larval fishes in the central and southern surface waters of the East Sea were investigated seasonally during 2011 and 2012. During the study period, the larvae of 39 species belonging to 26 families were collected. The most abundant species were Engraulisjaponicus, which accounted for 97.5% of the total number of individuals collected. Scomber japonicus, Clupea pallasii, Chromis notatus, Cottidae sp., and Coryphaena hippurus accounted for 1.7% of the total. The number of species, number of individuals, and species diversity indices fluctuated with the season. The peak number of species and individuals occurred in September and May, respectively. The larvae of the main species displayed a distinct spatial distribution and seasonal occurrence patterns. E. japonicus and C. notatus widely distributed throughout the study area. During summer and autumn, S. japonicus and C. hippurus were abundant in southern and offshore regions. C. pallasii occurred only in the southern region during winter. The seasonal occurrence and patterns of distribution of the larvae of main species seems were correlated with surface water temperature.

• Journal of Electrical Engineering and Technology
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• v.2 no.1
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• pp.1-9
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• 2007

This paper presents the effects of an increase or a decrease of a power reserve by load flow calculations under the seasonal load patterns of each country for the future power shortages faced by the metropolitan areas or by the southeastern area of South Korea in North-East Asia. In this paper, the various cases of the power system interconnections in Far-East Asia are presented, and the resulting interconnected power systems are simulated by means of a power flow analysis performed with the PSS/E 28 version tool. Data for simulation were obtained from the 2-th long term plan of electricity supply and demand in KEPCO. The power flow map is drawn from simulated data and the comparative study is done. In the future, a power flow analysis will be considered to reflect the effects of seasonal power exchanges. And the plan of assumed scenarios will be considered with maximum or minimum power exchanges during summer or winter in North-East Asian countries.

• Korean Journal of Agricultural Science
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• v.12 no.2
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• pp.341-348
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• 1985

This study aims at analysis hog cycles and seasonal price patterns, and at develop the procedure for price forecasting based on the relative price ratios by farmers. Seasonal price patterns have been a persistent feature of hog markets. Some month have historically high price and other months historically low price. Hog price tend to be high in Feb, May, June, Sept, winter (Nov. to Jan.) and tend to be low in the other months. There have been four price cycles for 12 years, 1972-1984, the length of the hog price cycle has varied from 24 month to 42 months, with the irregular frequency. The increasing period of the price cycle lasted 23 months and the decreasing period of the price cycle lasted 13 months. Tables 2, 3, 4 in this study show average hog price ratios and the number of times price fall, rose for one, two, and three months ahead of each calendar month.

• ALGAE
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• v.27 no.4
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• pp.269-281
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• 2012

Marado is a small rocky island located off the south coast of Jeju Island and acts as the first gateway of the Kuroshio Current to Korean coastal ecosystems. This island is one of the most unpolluted and well preserved sea areas around the Jeju coast. We extensively observed macroalgal assemblages of species and functional forms in the intertidal and subtidal zones through four seasons on Marado, Jeju Island, Korea to demonstrate the seasonality of vertical distribution patterns and biomass. A total of 144 species (14 Chlorophyta, 40 Phaeophyta, and 90 Rhodophyta) were identified in quadrats and were analyzed seasonally and vertically to define the variation patterns. The annual mean biomass of macroalgae was $2,932.3g\;wet\;wt\;m^{-2}$ and the highest value was recorded in spring and the lowest was in winter. The annual dominant species by biomass was Ecklonia cava followed by Sargassum fusiforme, S. macrocarpum, Amphiroa galapagensis, Chondria crassicaulis, and S. thunbergii. Obvious biomass zonation patterns of macroalgal species were detected in relation to tidal height and depth. Macroalgal biomass, diversity index (H'), and community dynamics were the highest in the shallow subtidal zone. Species number was higher in the subtidal than in the intertidal zone and similar throughout the entire subtidal zone. Our results provide revealing insights into the distribution patterns of macroalgal assemblages in an unpolluted sea area around Jeju Island.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.2
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• pp.259-268
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• 2005

In this study, we investigated the seasonal variations in the composition and emission patterns of VOC ventilated as landfill gas (LFG) from an urban municipal landfill site during the winter (2002) and summer (2003) period. The results of our study, when examined using the major aromatic VOC components as BTEX, indicated the existence of diverse characteristics in the LFG emissions of VOC. It was found that the relative extent of benzene emission showed most significant increase in the summer season, while most species underwent notable reductions. Despite the presence of certain patterns in the seasonal emissions of BTEX, the gross picture of their emission between summer and winter was not different distinctively so that the wintertime emissions exceed their summer counterparts by about three times. The observations of moderate enhancement in wintertime LFG emissions of BTEX appeared to reflect such environmental changes in the winter season as favorable conditions for LFG ventilation with reduced surface emissions due to frozen soil layers.

• Journal of Korean Society of Transportation
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• v.25 no.1 s.94
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• pp.121-132
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• 2007

Up to now Permanent traffic volumes have been counted by Automatic Vehicle Classification (AVC) on National Highways. When counted data have missing items or errors, the data must be revised to stay statistically reliable This study was carried out to estimate correct data based on outoregression and seasonal AutoRegressive Integrated Moving Average (ARIMA). As a result of verification through seasonal ARIMA, the longer the missed period is, the greater the error. Autoregression results in better verification results than seasonal ARIMA. Traffic data is affected by the present state mote than past patterns. However. autoregression can be applied only to the cases where data include similar neighborhood patterns and even in this case. the data cannot be corrected when data are missing due to low qualify or errors Therefore, these data shoo)d be corrected using past patterns and seasonal ARIMA when the missing data occurs in short periods.

• Journal of Ecology and Environment
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• v.45 no.2
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• pp.88-96
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• 2021

Background: Sika deer, Cervus nippon, were originally introduced to South Korea from Japan and Taiwan for commercial farming purposes. Unfortunately, they were released into the wild during religious events and have since begun to impact the native ecosystem and species endemic to South Korea. The study of activity patterns can improve our understanding of the environmental impact of non-native species and their association with sympatric species. Using camera traps, we studied the diel and seasonal activity patterns of non-native sika deer and quantified the temporal overlap with sympatric mammalian species in the Muljangori-oreum wetlands of Hallasan National Park, South Korea. Results: A total of 970 trap events were recorded for five mammalian species from nine locations during the camera-trap survey. Siberian roe deer (Capreolus pygargus tianschanicus) had the highest number of recorded events (72.0%), followed by sika deer (Cervus nippon) (16.2%), wild boar (Sus scrofa) (5.0%), Asian badger (Meles leucurus) (4.5%), and the Jeju weasel (Mustela sibirica quelpartis) (2.0%). Sika deer had bimodal activity patterns throughout the year, with peaks throughout the spring-autumn twilight, and day and night time throughout the winter. Relating the daily activity of sika deer with other mammalian species, roe deer expressed the highest degree of overlap (Δ₄ = 0.80) while the Asian badger demonstrated the lowest overlap (Δ₄ = 0.37). Conclusions: Our data show that sika deer are a crepuscular species with seasonal variations in daily activity patterns. Additionally, we identified the temporal differences in activity peaks between different mammals in the Muljangori-oreum wetlands and found higher degree of overlap between sika deer and roe deer during twilight hours.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.249-261
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• 2010

Long-term forecasting of seasonal time series is critical in many applications such as planning business strategies and resolving possible problems of a business company. Unlike the traditional approach that depends solely on dynamic models, Li and Hinich (2002) introduced a combination of stochastic dynamic modeling with filter bank approach for forecasting seasonal patterns using highly coherent(High-C) waveforms. We modify the filter selection and forecasting procedure on wavelet domain to be more feasible and compare the resulting predictor with one that obtained from the wavelet variance estimation method. An improvement over other seasonal pattern extraction and forecasting methods based on such as wavelet scalogram, Holt-Winters, and seasonal autoregressive integrated moving average(SARIMA) is shown in terms of the prediction error. The performance of the proposed method is illustrated by a simulation study and an application to the real stock price data.