• Journal of Wetlands Research
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• v.23 no.4
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• pp.296-306
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• 2021

Elasticity is a statistical technique that interprets the changing pattern of another variable according to a change in one variable as a quantitative numerical value and provides more information than correlation analysis and is widely used in climate change research. In this study the elasticity was calculated and sensitivity analysis was performed using air temperature and water quality data of the major tributaries of the Nakdong River. In addition the confidence interval for the elasticity was calculated using the T-Test and the validity of the elasticity was examined. The strength of elasticity shows high strength in the order of summer>fall>spring>winter and the direction shows regional characteristics with both negative and positive elasticity. After performing hierarchical cluster analysis on monthly observation data they were classified into 5 clusters and the characteristics of each cluster were visually analyzed using a parallel coordinate graph. The direction and intensity of the air temperature elasticity show regional characteristics due to the relatively high population density and complex influencing factors such as sewage treatment plants, small-scale livestock houses and agricultural activities. In the case of TP it shows great regional variability according to the circulation of nutrients in the ecosystem caused by algae growth and death according to temperature changes. Since the air temperature elasticity of the major tributaries of the Nakdong River is over weak and is valid at the significance level of 5%, it was analyzed that there is a change in water quality according to the air temperature change.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1329-1338
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• 2021

Rain radar provides high spatio-temporal radar rainfall that can be used as input data to short-term precipitation forecasting models. Korea Institute of Civil Engineering and Building Technology (KICT) has developed a flash flood forecasting system that is providing flash flood forecasting based on short-term rainfall forecasts estimated by the radar rainfall. Accuracy of the radar rainfall as well as the short-term rainfall forecasts, however, can deteriorate when radar polarimetric variables have error. In this study, we develope real-time program that can correct the error inherent in the radar polarimetric variables. First, effect according to the correction of the error was verified using 363 rainfall events on non real-time. The accuracy (1-NE) of the radar rainfall was approximately 70% and correlation coefficient was higher than 0.8 after correcting the error on non real-time. The accuracy (1-NE) using the real-time program was also approximately 70% after correcting the error.

• The Journal of Korean society of community based occupational therapy
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• v.9 no.1
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• pp.25-34
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• 2019

Objective : The purpose of this study was to investigate the effect of cognitive level of mild cognitive impaired elderly living in the community on participation in activities and social networks as well as leisure and daily life activities. Methods : The elderly people aged 65 years or older living in the community were selected for the mild cognitive impairment with a score of MMSE-K of 15 or more and 23 or less. MoCA-K was applied in order to examine the cognitive abilities of the subjects and K-ACS and LSNS-18 were applied to confirm the activity participation level and social network index. Results : As a result of examining the relationship between cognition and activity participation, various sub-abilities(spatio-temporal abilities, vocabulary abilities, attention, abstract thinking) of cognition had a significant influence on instrumental activities of daily living, leisure activities and social activities. In addition, all of the sub - abilities of cognition showed a significant correlation with sub-elements of social network. Conclusion : Through this study, it was found that the general elements of cognition influenced activity participation and social network of various areas of mild cognitive impaired elderly people. We suggest that measures for enhancing participation and social participation of the elderly with mild cognitive impairment are provided through follow up studies.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1179-1192
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• 2018

In order to detect the Antarctic Polar Front (PF) among the main fronts in the Southern Ocean, this study is based on the combinations of satellite-based sea surface temperature (SST) and height (SSH) observations. For accurate PF detection, we classified the signals as front or non-front grids based on the Bayesian decision theory from daily SST and SSH datasets, and then spatio-temporal synthesis has been performed to remove primary noises and to supplement geographical connectivity of the front grids. In addition, sea ice and coastal masking were employed in order to remove the noise that still remains even after performing the processes and morphology operations. Finally, we selected only the southernmost grids, which can be considered as fronts and determined as the monthly PF by a linear smoothing spline optimization method. The mean positions of PF in this study are very similar to those of the PFs reported by the previous studies, and it is likely to be well represents PF formation along the bottom topography known as one of the major influences of the PF maintenance. The seasonal variation in the positions of PF is high in the Ross Sea sector (${\sim}180^{\circ}W$), and Australia sector ($120^{\circ}E-140^{\circ}E$), and these variations are quite similar to the previous studies. Therefore, it is expected that the detection approach for the PF position applied in this study and the final composite have a value that can be used in related research to be carried out on the long term time-scale.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.857-868
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• 2018

The microphysics and spatio-temporal distribution of atmospheric aerosols are responsible for estimating the optical properties at a given location. Its accurate estimation is essential to plan efficient simulation for radiative transfer. For this sake, synergetic use of reanalysis data with optics database was used as a potential tool to precisely derive the aerosol model on the basis of the major representative particulates exist within a model grid. In detail, mixing of aerosol types weighted by aerosol optical depth (AOD) components has been developed. This synergetic aerosol model (SAM) is spectrally extended up to $40{\mu}m$. For the major aerosol event cases, SAM showed that the mixed aerosol particles were totally different from the typical standard aerosol models provided by the radiative transfer model. The correlation among the derived aerosol optical properties along with ground-based observation data has also been compared. The current results will help to improve the radiative transfer model simulation under the real atmospheric environment.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.507-516
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• 2018

The closed chamber method, which is one of the most commonly used method for measuring greenhouse gases produced in rice paddy fields, has limitations in measuring dynamic $CH_4$ flux with spatio-temporal constrains. In order to deal with the limitation of the closed chamber method, some studies based on open-path of eddy covariance method have been actively conducted recently. The aim of this study was to compare the $CH_4$ fluxes measured by open-path and closed chamber method in the paddy rice fields. The open-path, one of the gas ($CO_2$, $CH_4$ etc.) analysis methods, is technology where a laser beam is emitted from the source passes through the open cell, reflecting multiple times from the two mirrors, and then detecting. The $CH_4$ emission patterns by these two methods during rice cultivation season were similar, but the total $CH_4$ emission measured by open-path method were 31% less than of the amount measured by closed chamber. The reason for the difference in $CH_4$ emission was due to overestimation by closed chamber and underestimation by open-path. The closed chamber method can overestimate $CH_4$ emissions due to environmental changes caused by high temperature and light interruption by acrylic partition in chamber. On the other hand, the open-path method for eddy covariance can underestimate its emission because it assumes density fluctuations and horizontal homogeneous terrain negligible However, comparing $CH_4$ fluxes at the same sampling time (AM 10:30-11:00, 30-min fluxes) showed good agreements ($r^2=0.9064$). The open-path measurement technique is expected to be a good way to compensate for the disadvantage of the closed chamber method because it can monitor dynamic $CH_4$ fluctuation even if data loss is taken into account.

• Journal of Wetlands Research
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• v.23 no.2
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• pp.122-132
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• 2021

We reviewed the methods employed in Korean tidal flat surveys to measure the local abundance of the endangered wildlife and marine protected species, the fiddler crab, Austruca lactea. A complete census for infinite population is impossible even in a limited habitat within a tidal flat, and density estimates from samples strongly vary due to diverse biological and ecological factors. The habitat boundaries and areas shift with periodicities or rhythmic activities of organisms as well as measurement errors. Hence the local abundance calculated from density and habitat areas should be regarded as transient. This conjecture was valid based on the spatio-temporal variations of the density averages, standard error ranges, and spatial distribution of the crab, A. lactea observed for 3 years (2015-2017) in Songdo tidal flat in Incheon. We proposed the potential habitat areas using the occurrence probability of 50% from logistic regression model, reflecting the importance of habitat conservation value as an alternative to local abundance. The spatial shape of potential habitat predicted from a generalized model would remain constant over time unless the species' critical environmental conditions change rapidly. The species-specific model is expected to be used for the introduction of desired species in future habitat restoration/creation projects.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.655-662
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• 2021

This study aimed to estimate exploitable groundwater for the sustainable supply of groundwater in the Jinju region of South Gyeongsang Province. As an integrated hydrologic analysis model, SWAT-MODFLOW was used to estimate the distributed groundwater recharge in consideration of land use and soil distribution. As a result of calibration of the model, the coefficient of determination between the observed flow and the simulated flow was 0.75-0.80, which was good. The simulated groundwater recharge rate showed a spatio-temporal distribution due to heterogeneous watershed characteristics. The amount of groundwater recharge shows lower values over winter and spring, but it increases according to the pattern of precipitation in summer and autumn. The calculated average annual groundwater recharge was compared with the result using the baseflow separation method of natural flow, and the deviation of both results was small, within 3 %, confirming the validity of the estimated groundwater recharge. Exploitable groundwater is defined as the amount of recharge corresponding to low flow with 10 years of return period. Therefore, in this study, 14.2 % of the annual precipitation was found to be exploitable as a result of calculating the amount of recharge at a 10-year frequency using a statistical frequency analysis technique.

• Korean Journal of Plant Resources
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• v.35 no.1
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• pp.10-22
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• 2022

This study investigated field data to understand the spatio-temporal distribution of pollinating insects and buckwheat flowers. We set the in-situ observation sites in different locations to get altitude and cropping system distribution data for five years (2016 to 2020) in Korea. Twenty-five different insect species, belonging to 8 orders, were recorded. Over the past five years, species from the orders Diptera and Hymenoptera were the principal visitors. Hymenoptera was mainly represented by honey bees (Apis cerana), while Diptera was represented by bean seed fly (Delia platura) and several other species. Some bees and other Hymenoptera species could, however, act as co-pollinators because of their high relative frequency and activity. Compared with open-field cultivation (conventional), the pollination mediating effect of flies and bees was superior in net house, so the yield was high, and it was also found to be slightly higher in the mixed treatment of flies and bees than in the single treatment. Based on the above results, flies and bees were found to be the most active pollinating insects in buckwheat and it is necessary to actively utilize the selected insects to improve buckwheat productivity. This relationship will be utilized in establishing the system of seed production on pollinating regulation of a primary plant.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1047-1056
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• 2022

Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.