• Korean Journal of Ecology and Environment
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• v.37 no.3 s.108
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• pp.344-354
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• 2004

A pilot study was performed from September 2000 to April 2004 to examine the feasibility of the wetland-pond system for the agricultural reuse of reclaimed water. The wetland system was a subsurface flow type, with a hydraulic residence time of 3.5 days, and the subsequent pond was 8 $m^3$ in volume (2 m ${\times}$ 2 m ${\times}$ 2 m) and operated with intermittent-discharge and continuous flow types. The wetland system was effective in treating the sewage; median removal efficiencies of $BOD_5$ and TSS were above 70.0%, with mean effluent concentrations of 27.1 and 16.8 mg $L^{-1}$, respectively, for these constituents. However, they did often exceed the effluent water quality standards of 20 mg $L^{-1}$. Removal of T-N and T-P was relatively less effective and mean effluent concentrations were approximately 103.2 and 7.2 mg $L^{-1}$, respectively. The wetland system demonstrated high removal rate (92 ${\sim}$ 90%) of microorganisms, but effluent concentrations were in the range of 300 ${\sim}$ 16,000 MPN 100 $mL^{-1}$ which is still high for agricultural reuse. The subsequent pond system provided further treatment of the wetland effluent, and especially additional microorganisms removal in addition to wetland-pond system could reduce the mean concentration to 1,000 MPN 100 $mL^{-1}$ from about $10^5$ MPN 100 $mL^{-1}$ of wetland influent. Other parameters in the pond system showed seasonal variation, and the upper layer of the pond water column became remarkably clear immediately after ice melt. Overall, the wetland system was found to be adequate for treating sewage with stable removal efficiency, and the subsequent pond was effective for further polishing. This study concerned agricultural reuse of reclaimed water using natural systems. Considering stable performance and effective removal of bacterial indicators as well as other water quality parameters, low maintenance, and cost-effectiveness, wetland- pond system was thought to be an effective and feasible alternative for agricultural reuse of reclaimed water in rural area.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.543-557
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• 2021

Because aerosols have different spectral characteristics according to the size and composition of the particle and to the satellite sensors, a comparative analysis of aerosol products from various satellite sensors is required. In South Korea, however, a comprehensive study for the comparison of various official satellite AOD (Aerosol Optical Depth) products for a long period is not easily found. In this paper, we aimed to assess the performance of the AOD products from MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite), Himawari-8, and Sentinel-3 by referring to the AERONET (Aerosol Robotic Network) sun photometer observations for the period between January 2015 and December 2019. Seasonal and geographical characteristics of the accuracy of satellite AOD were also analyzed. The MODIS products, which were accumulated for a long time and optimized by the new MAIAC (Multiangle Implementation of Atmospheric Correction) algorithm, showed the best accuracy (CC=0.836) and were followed by the products from VIIRS and Himawari-8. On the other hand, Sentinel-3 AOD did not appear to have a good quality because it was recently launched and not sufficiently optimized yet, according to ESA (European Space Agency). The AOD of MODIS, VIIRS, and Himawari-8 did not show a significant difference in accuracy according to season and to urban vs. non-urban regions, but the mixed pixel problem was partly found in a few coastal regions. Because AOD is an essential component for atmospheric correction, the result of this study can be a reference to the future work for the atmospheric correction for the Korean CAS (Compact Advanced Satellite) series.

• (The)Study of the Eastern Classic
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• no.72
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• pp.299-327
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• 2018

The objective of this study is to examine the regional distribution of Ssireum(Traditional Wrestling) of South and North Korea in the Japanese colonial era. The conclusions of this study are as follows. First, the "Joseon ui hyangto orak(Folk play in Joseon)" showed the record of performing 272 times of Ssireum in 226 regions of the whole nation. Second, the Ssireum of South Korea could be divided into five regions. Seoul/Gyeonggi-do performed Ssireum the most in Dano, Baekjung, and Chuseok while Chungcheong-do performed Ssireum in Baekjung and Chuseok. Jeolla-do and Gyeongsang-do performed Ssireum in Chuseok while Gangwon-do performed Ssireum in Dano and Chuseok. Third, the Ssireum of North Korea could be divided into three regions. All the Hwanghae-do, Pyeongan-do, and Hamgyeong-do performed Ssireum the most in Dano. Fourth, as the period when Ssireum was held the most in the whole nation, Dano, Baekjung, and Chuseok could be pointed out. Ssireum has the characteristics of large-scale play between village communities or regions, instead of individual game. Thus, the Ssireum that was played as a sport event under certain rules for a long time was settled down as a folk play of regional festivals such as Dano, Baekjung, and Chuseok. Fifth, as a folk play and a representative play of seasonal customs, Ssireum was distributed in the whole nation and handed down till today under the regional deviation of South and North Korea. Sixth, the unidentified regions of South Korea that did not perform Ssireum were six places including five dos such as Gapyeong Gyeonggi-do, Boseong Jeollanam-do, Jeju-do, Gunwi and Cheongsong Gyeongsanbuk-do, and Inje Gangwon-do. The regions of North Korea were six places including three dos such as Pyeongyang, Yangdeok, Gangdong, and Gaecheon of Pyeongannam-do, Bakcheon Pyeonganbuk-do, and Dancheon Hamgyeongnam-do. Total 12 places in eight regions were included. Seventh, the number of total items of play names presented in the "Joseon ui hyangto orak(Folk play in Joseon)" was about 6,400 types. Out of them, about 1,300 types were the items including how to play while about 5,100 types were the items presenting the play names only without explanations. Especially, in case of Ssireum, the periods of the lunar calendar were only specified in each region. Unfortunately, it was not possible to check the contents about the actual performance methods and types of Ssireum as they were omitted.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Journal of the Korean Society of International Agriculture
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• v.23 no.5
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• pp.520-530
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• 2011

This study was carried out to evaluate the possibility of rice double cropping in Korea by assessing the growth and yield performance of rice cultivars transplanted at the extremely-early date. When the transplanted rice seedling was exposed to low temperature below 0℃, the survival rate decreased drastically. However, short exposure to below 0℃ one or two times did not damage transplanted rice seedling so severely. Thus, the earliest transplanting in spring would be possible when minimum temperature rises above 0℃. Compared with the conventional seedling nursery tray (CSNT), seedling rearing with the potted nursery tray was more effective for increasing leaf age and seedling dry weight during nursery period. In the first rice cropping, rice cultivation with seedlings reared in PSNT showed shorter growth duration and cumulative temperature from transplanting to heading than that with seedlings reared in CSNT. The earliest heading date on July 4 in Jinbuolbyeo was earlier by two to three days than that of Dunaebyeo. If rice has not exposed to cold damage, the earliest heading date of Jinbujolbyeo can advance to June 30 or July 1. In this case, rice harvest would be possible on August 5, enabling the rice transplanting of the second rice cropping before August 10. At transplanting time with low temperature damage rice yield were less than 400 kg/10a while rice yield exceeded 400 kg/10a at transplanting time without low temperature damage.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.